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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095697 ijerph-19-05697 Review Environmental Enrichment Enhances Cerebellar Compensation and Develops Cerebellar Reserve https://orcid.org/0000-0002-3935-2164 Gelfo Francesca 12* https://orcid.org/0000-0001-7464-5168 Petrosini Laura 2 Tchounwou Paul B. Academic Editor 1 Department of Human Sciences, Guglielmo Marconi University, Via Plinio 44, 00193 Rome, Italy 2 IRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179 Rome, Italy; laura.petrosini@uniroma1.it * Correspondence: f.gelfo@hsantalucia.it 07 5 2022 5 2022 19 9 569730 3 2022 05 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The brain is able to change its structure and function in response to environmental stimulations. Several human and animal studies have documented that enhanced stimulations provide individuals with strengthened brain structure and function that allow them to better cope with damage. In this framework, studies based on the exposure of animals to environmental enrichment (EE) have provided indications of the mechanisms involved in such a beneficial action. The cerebellum is a very plastic brain region that responds to every experience with deep structural and functional rearrangement. The present review specifically aims to collect and synthesize the evidence provided by animal models on EE exposure effects on cerebellar structure and function by considering the studies on healthy subjects and on animals exposed to EE both before and after damage involving cerebellar functionality. On the whole, the evidence supports the role of EE in enhancing cerebellar compensation and developing cerebellar reserve. However, since studies addressing this issue are still scarce, large areas of inconsistency and lack of clarity remain. Further studies are required to provide suggestions on possible mechanisms of enhancement of compensatory responses in human patients following cerebellar damage. environmental enrichment cerebellum cerebellar reserve cognition neuroplasticity neuroprotection compensation recovery of functions animal models rodents This research received no external funding. ==== Body pmc1. Introduction The brain is characterized by the now-recognized capacity of changing its own structure and function in response to stimulations that can come from both internal and external environments, which is known as neuroplasticity [1,2]. Structural and functional plastic rearrangements are triggered by the transmission of information through neuronal circuitries, which react to each experience by circulating electrochemical signals. Such a plastic reorganization occurs during neural system development, when the brain is engaged in learning and memory, and also when the nervous system undergoes damage [3]. In fact, the brain always tends to respond with the maximum possible compensation for damage by reorganizing itself in order to recover as much function as possible and to reach a new homeostatic equilibrium [4,5]. In the context of the studies focused on neuroplasticity, the reserve hypothesis has been formulated. This theory affirms that the experiences that individuals encounter throughout their life affect and fine-tune brain structure and function, providing the individuals with a resilient apparatus [6]. As first observation, it was described that patients affected by Alzheimer’s disease with different life experiences exhibited symptoms in association with different levels of neural injury or degeneration, thus showing different susceptibility to brain damage [7]. This concept has then been enlarged to a wide range of pathological conditions [8]. The concept of reserve evolved over the years; originally articulated in two components—the brain reserve and the cognitive reserve—it is now described as a multifactorial frame. The brain reserve conceptualizes the evidence that an individual that is provided with a more and better structured brain is able to more resiliently face damage. This principle applies to all the components of cerebral structure at molecular and supramolecular levels, such as brain weight and volume, neuron number, neuronal morphology, density and morphology of neuroglia and synapses, structure of circulatory system, neurotransmitters, and neurotrophic factors [9,10,11]. On the other hand, the cognitive reserve is tightly linked to cognitive processes. It can be described as a high-level capacity to efficiently engage the residual functions in order to fulfill tasks and address daily activities [9,10,11]. The neural reserve is intended as a kind of summa of the two previous concepts and regards the ability to efficiently engage neuronal networks and alternative strategies in cognitive performance [9,10,11]. Recently, the concept of brain maintenance has been included in this framework. This idea is somehow similar to the one of brain reserve, and accounts for the capacity of genetics and lifestyle to protect the brain from the development and accumulation of pathological changes [9,10,11]. Finally, it is noteworthy that all these concepts are also linked to the capacity of the brain of compensation, which is the ability of the brain to cope with damage by reacquiring as much function as possible [12]. A fundamental issue on which the studies in this field have focused regards the investigation of the experiential factors that are able to act as “reserve-builders”. Fundamentally, three dimensions are understood to be mainly involved: the cognitive factor, the social factor, and the physical factor [9,10,13]. The cognitive factor regards all the activities that involve the individual by requiring a high-level mental investment. Basically, educational level and job complexity are considered, but a large range of leisure activities may be included in this aspect [14,15,16,17]. The social factor regards the social networks in which the individual is involved. All social relationships fall in this category, in a large range that includes familiar status, parentage, friendship, etc. [18,19]. The physical factor regards the habits that constitute the lifestyle of the individual, such as physical activity, diet, smoking, sleep, alcohol intake, and consumption of beneficial dietary elements [20,21,22]. In animal models, the effects of the enhancement of these three factors on brain structure and function has been studied by using the environmental enrichment (EE) experimental paradigm. The EE paradigm was introduced in the sixties and then widely used with rodents by comparing animals reared in an enriched environment with animals reared in standard laboratory housing conditions [23,24]. By means of this paradigm, it is possible to manipulate the variables concerning rearing conditions with a high-level control. In this way, it is possible to construct a specific design in which to test the effects of a single factor or a combination of factors; to determine the starting, the duration, and the end of the exposure period; to choose the way in which one manipulates each factor (e.g., by stimulating only a sensory channel or more than one in association); and to exactly establish the characteristics of the animals exposed to EE (e.g., species, age, gender, healthy or pathological conditions, etc.) [9,25,26]. Basically, in animals the cognitive factor is mimicked by making the rearing environment more complex, providing the cage with a number of objects of various natures, shapes, sizes, and colors, which are frequently rearranged and replaced, in order to enhance the exposure to novelty; the social factor is mimicked by modulating the number of individuals that are reared in the same cage, typically augmenting the quantity in comparison to the minimum for laboratory standard; the physical factor is mimicked by using cages bigger than the standard ones and equipped with shelves, ladders, and running wheels (frequently indicated as a key-element), to stimulate motor activity and explorative behavior. In addition, specific supplementary diets may be administered [13,26,27,28]. Several studies have used the EE paradigm to model the lifespan experiences of individuals. Consequently, structural and functional cerebral effects of EE have been studied in healthy animals and also in pathological models. In this way, the neuroprotective effects of highly stimulating life experiences have been studied by exposing animals early to a more or less lengthy period of EE before the occurrence of brain damage. Furthermore, the EE paradigm has been used as a versatile paradigm of therapeutic non-pharmacological treatments (useful to enhance spontaneous brain compensation abilities) by exposing animals to a more or less lengthy period of EE after the occurrence of brain damage. On the whole, substantial evidence has been provided by the studies based on the EE paradigm about the experience-empowering impact of EE on the entire brain structure, at both molecular and supramolecular levels [27,29,30,31,32,33,34]. Moreover, motor, behavioral, and cognitive functions have been reported to be improved by the exposure to an enriched environment [26,35,36,37,38]. However, several issues remain open regarding the systematic effects of EE on specific processes and brain regions in relation to the healthy or pathological condition of animals [10,27,29]. A brain region known to greatly respond to somatosensory integration and control with plastic rearrangement, including in adult age, is the cerebellum. This cerebral area is classically known to support high-level cognitive and emotional abilities (such as learning and memory processes, spatial cognition, language, reasoning, emotions, and mood) by recursively rearranging its complex connections with the cortical and sub-cortical regions [39,40,41,42,43,44,45,46,47,48,49,50,51]. Moreover, several studies have documented the cerebellar capacity to compensate deficits derived from damages of multifarious nature [52,53,54,55,56]. Numerous mechanisms at both cellular and sub-cellular levels are involved in such a plastic re-adaptation [4,52,55,57,58,59]. Consequently, it is of great interest to analyze how the environment interacts with the predisposition of the cerebellum to recover functions in the presence of damage. The EE paradigm appears to be an ideal tool for such investigations. Interestingly, Cutuli et al. [60] evaluated the effects of two different EE protocols by exposing animals to an enriched environment only before or only after the ablation of a half of the cerebellum (hemicerebellectomy). By investigating postural and locomotor behaviors, in association with striatal synaptic activity and morphology of interneurons, the authors documented that the exposure to EE exerted beneficial effects on the compensation of the cerebellar deficits when the exposure to an enriched environment occurred both before and after the damage. In this framework, the present review specifically aims to collect and synthesize the evidence provided by animal models on the EE effects on cerebellar structure and function by taking into account the studies on healthy subjects and on animals exposed to EE both before and after damage involving cerebellar functionality. 2. Methodology of Literature Search A methodical literature search was conducted in PubMed and Embase databases by screening all titles and abstracts obtained by searching for the combination of the “environmental enrichment” OR “enriched environment” AND “cerebell*” key-words. Moreover, full texts and reference lists were screened to identify further potentially relevant articles. Articles fulfilling the following criteria were included in the present overview:i. as population of interest, we selected rodents, both healthy subjects and pathological models; ii. as intervention of interest, we selected the exposure to multidimensional EE in a period between birth and death (in healthy conditions, before damage, or after damage). As for pathological models based on genetic manipulations, the exposure to EE was considered as preceding the damage when it occurred in early life, before the onset of disease symptoms; it was considered as following the damage when it occurred later in life, after the onset of disease symptoms; iii. as control group of interest, we selected animals reared in standard laboratory conditions; iv. as outcomes of interest, we selected structural and functional cerebellar effects of rearing conditions. It is worth emphasizing that only studies analyzing at least one (structural, physiological, or biological) cerebellar effect of rearing conditions were included. Cognitive and behavioral effects were considered of interest only when associated with a cerebellar correlate. No language limitation was selected. No publication period limitation was selected. Records indexed up to February, 2022 were screened. We identified 114 records from databases. After duplicate record removing, we screened titles and abstracts of 65 papers. After title and abstract screening, we assessed 32 studies for eligibility. Among these, 11 were excluded, since they did not meet our inclusion criteria. Moreover, 3 eligible studies were obtained from citation searching. Consequently, 24 relevant papers (12 on healthy subjects; 5 on subjects exposed to EE before the damage; 7 on subjects exposed to EE after the damage) that met the inclusion criteria were considered for the present review. Figure 1 shows a detailed flow-diagram of the literature search conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations [61]. We collected the following data: authors; year of publication; animal species; pathological model, when present; animals’ age or weight at the start of the exposure to EE; EE type (by specifically noting if the paradigm encompasses running wheels and novelty manipulation); EE duration; EE effects on cerebellar structure and function; animal age at the effects evaluation. As for cerebellar correlates, when not specified, the evaluation regarded the entire region. All data collected are illustrated in Tables. 3. Environmental Enrichment Effects in the Cerebellum of Healthy Animals Most studies dedicated to cerebellar effects of EE in healthy animals were focused on early exposure, that is, when the rearing of the subjects in an enriched environment started from weaning or even earlier. Several (n = 10) studies specifically evaluated the effects of an early exposure to EE on synaptic plasticity. De Bartolo et al. [62] reported that a 100-day-long exposure to multidimensional EE—starting from weaning—induced a significant increase in dendritic spine density and size of Purkinje cells both in the vermis and in the hemispheres of adult rats. Such indices of synaptogenesis indicate a substantial strengthening of cerebellar circuitries. Moreover, Kim and colleagues [63] revealed that a 28-day-long exposure to multidimensional EE—starting at 3 weeks of age—induced a selective increase in parallel fiber-to-Purkinje cell synapses of same dendritic origin in mice cerebellum, indicating local synaptic strengthening aimed at the refinement of preexisting cerebellar networks. Conversely, previous studies did not report cerebellar synaptogenesis after early exposure to multidimensional EE. In mice, after a 30-day-long exposure to multidimensional EE from 28 days onwards, Nithianantharajah et al. [64] found unchanged cerebellar levels of synaptophysin, an integral membrane protein in synaptic vesicles. In agreement with this Pascual and Bustamante [65] failed to find changes in rat vermal Purkinje cell dendritic outgrowth after a 10-day-long exposure to multidimensional EE (starting from weaning). The finding of unchanged anxiety-like behavior was associated with such a neural correlate. The early exposure to EE has also been demonstrated to induce plastic rearrangement in cerebellar molecular factors, such as the neurotrophins brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF), factors known to be strongly involved in neuronal survival and activity-dependent plasticity. In particular, Angelucci et al. [57] found increased BDNF and NGF expression in the cerebellum of rats exposed to multidimensional EE from weaning for about 120 days. In a more complex investigation, Vazquez-Sanroman et al. [66] analyzed cerebellar BDNF expression in mice exposed to multidimensional EE (but without running wheels, a key element for physical activity enhancement) starting from weaning and lasting for varying periods (1, 4, and 8 weeks). The analysis was performed through immunostaining and immunoblotting, which analyzed the expression of both immature and mature BDNF proteins. After 1 week of exposure, BDNF immunoreactivity was found to be increased only at the granular layer. After 4 and 8 weeks, BDNF immunoreactivity increased at both granular and Purkinje layers. As for the two BDNF protein isoforms, they were both unchanged after 1 week of EE exposure, whereas they were both increased after 8 weeks of EE exposure. As for neurotransmitter expression, an investigation was conducted by Naka et al. [67] in mice exposed to multidimensional EE for 40 days starting from 28 days of age. They found increased noradrenaline but unchanged serotonin expressions in the cerebellum. In addition, cerebellar chromatin levels, involved in RNA synthesis, also appear to be influenced by an early exposure to multidimensional EE. Uphouse [68] reported that in rats exposed to multidimensional EE (without running wheels) for 32 days from 28 days of age, cerebellar chromatin levels were increased. However, Uphouse and Tedeschi [69] reported that such change was not present after 60 days of the same treatment. Finally, Eshra et al. [70] investigated the effects of the exposure of mice to multidimensional EE from birth to 70th–80th postnatal days on cerebellar electrophysiology. Authors showed a higher granule cell firing frequency induced by EE. This electrophysiological alteration was accompanied by enhanced motor performance. A few (n = 2) studies investigated the effects on cerebellar structure and function of the exposure of animals to EE occurring later in life. Scholz et al. [71] analyzed the effects of exposing adult mice (7 weeks old) to 24 h or 21 days of multidimensional EE mainly based on a three-level maze, frequently rearranged. The authors reported a decrease in cerebellar volume, as revealed by in vivo and ex vivo MRI. The volume loss was interpreted to be associated with the synaptic pruning aimed at refining cerebellar circuitry functioning. After the 21-day-long exposure, such a volume change was associated with improved spatial learning. Furthermore, Horvat et al. [72] investigated the effects of a 21-day-long exposure to multidimensional EE (without running wheels) of 6-month-old rats. The authors reported increased expression of pituitary adenylate cyclase activating polypeptide, which regulates multifarious physiological and pathophysiological processes and exerts neuroprotective action. Details on the studies cited in this section are provided in Table 1. 4. Neuroprotective Effects of Environmental Enrichment on the Cerebellum A few (n = 5) studies investigated in animal models the neuroprotective effects of the exposure to multidimensional EE before damage occurs with the specific aim of analyzing what happens in the cerebellum. Ultimately, evidence is available on EE neuroprotective effects in models of Rett syndrome and in a model of cerebellar trauma. Rett syndrome is a disease predominant in females mainly provoked by mutations in the X-linked gene for methyl CpG-binding protein 2 (Mecp2). This syndrome is characterized by an postnatal development typical in the early phases followed by the progressive loss of the acquired motor and cognitive skills, a deficit usually appearing between 6 and 18 months of age [73]. The Mecp2 mutant mice show many of the deficits observed in patients affected by Rett syndrome, such as motor impairments and alterations in social, cognitive, and emotional behavior [74]. Kondo et al. [75] investigated the effects of early exposure to multidimensional EE (without manipulation of the social factor) on hemizygous male and heterozygous female Mecp2tm1Tam mice. Males (in which the symptoms show more rapid onset and progression) were exposed to EE starting from 28 days of age and lasting for 6 weeks. Females were exposed to EE from 28 days of age for 26 weeks. In hemizygous males, after the exposure to EE, unchanged BDNF expression was found in the cerebellum, in association with unchanged locomotor activity and motor coordination. In heterozygous females, although middle-term evaluations revealed that EE prevented early onset of motor coordination deficits, when the evaluation was carried out at the end of the exposure (after 26 weeks) EE failed in reversing motor coordination deficits, and cerebellar BDNF expression was found not significantly different in respect to controls reared in standard conditions. Locomotor activity was already unaffected by EE after 11 weeks of exposure. In male Mecp21lox mice, Nag et al. [76] showed that early exposure to multidimensional EE (from 21st postnatal day for 23 days—without manipulation of the social factor) did not affect cerebellar volume, motor coordination, and contextual or cued fear conditioning. However, locomotor deficits were prevented. Finally, Lonetti et al. [77] investigated the effects of a 50-day-long exposure to multidimensional EE on male Mecp2tm1Jae mice, starting from 10 days of age. In this case, the authors reported that density of inhibitory synapses was higher in mutant mice than in wild-type controls and was further increased in mutant animals exposed to EE. This finding was accompanied by the prevention of deficits in motor coordination and motor learning. A couple of studies investigated the effects of the exposure to multidimensional EE before the occurrence of a hemicerebellectomy, a model in which the animals are surgically deprived of a half of the vermis and one entire hemisphere. Lesioned animals show characteristic postural and locomotor asymmetries of cerebellar origin. Complex motor behavior, spatial learning, and memory performance are impaired. Typically, postural and locomotor symptoms are almost completely compensated after about 3 weeks. However, complex motor behavior and spatial performance remain defective [78]. The almost complete compensation of postural and locomotor deficits shown by lesioned animals is accompanied by plastic rearrangements in the spared hemivermis and hemisphere. Namely, Purkinje cell spine size augments in both regions. Moreover, spine density appears rearranged (decreased in the hemivermis and increased in the hemisphere) in order to maintain an homeostatic equilibrium in synaptic transmission by responding to the functional rewiring of the connectivity of the two cerebellar regions [4]. As for neurotrophin expression, both NGF and BDNF levels appear increased in the spared hemicerebellum of lesioned animals [79]. Gelfo et al. [4] showed that when animals were previously exposed to multidimensional EE (from 21st postnatal day for about 4 months), the compensation of locomotor and postural deficits was anticipated by at least one week. In addition, motor behavior, spatial learning, and memory performance were completely restored. As for cerebellar circuitry, previously enriched animals maintained the increase in Purkinje cell dendritic spine size and density induced by the EE, without showing the further increase elicited by the lesion. At the molecular level, Gelfo et al. [79] demonstrated that in the same model, NGF levels were further increased in the spared hemicerebellum of previously enriched animals. In contrast, BDNF levels were not further increased compared to the ones showed by non-enriched lesioned animals. Details on the studies cited in this section are provided in Table 2. 5. Therapeutic Effects of Environmental Enrichment on the Cerebellum A slightly larger number of studies (n = 7) investigated EE therapeutic effects in animal models after damage with the specific aim of analyzing what happens in the cerebellum. Therapeutic effects of the exposure to multidimensional EE have been investigated in several models of prenatal exposure to detrimental factors, such as alcohol, stress, and betamethasone. Prenatal exposure to alcohol (carried out by exposing the mother to it during gestation) induces significant alterations in brain areas, particularly in the cerebellum, accompanied by abnormalities in behavior and cognition [80]. Parks et al. [81] prenatally exposed male and female rats to alcohol and then to multidimensional EE (without running wheels) starting from weaning for a period of 42 days. The authors reported that NGF and neurotrophin-3 (NT-3) vermal expression were altered by prenatal exposure to alcohol. The exposure to EE did not affect NGF levels but increased NT-3 expression at cerebellar level. Stressful prenatal experiences (caused by exposing the mother to them during gestation) are reported to induce neuropsychiatric disorders and cerebellar alterations, particularly affecting the morphology of Purkinje cells [82,83]. Pascual et al. [84] prenatally exposed male mice to restraint stress and then to multidimensional EE starting from weaning for 30 days. EE restored vermal Purkinje cell dendritic arborizations, which did not show stress-induced deterioration. In association, authors reported that enriched animals exhibited reduced anxiety-like behavior in comparison to standard reared controls. Finally, prenatal exposure to betamethasone, a corticosteroid commonly used in obstetrics (carried out by exposing the mother to it during gestation), constitutes a risk factor for the development of behavioral, cognitive, and neurological alterations [85]. Valencia et al. [86] reported that prenatal treatment with betamethasone induced alterations of vermal synaptophysin levels in young adult rats. The exposure to multidimensional EE starting from weaning for 18 days was able to restore standard vermal synaptophysin levels and recover motor coordination. Two studies performed in the last century analyzed the effects of exposure to an enriched environment in animals previously undernourished in the first postnatal period. Malnutrition in early life is reported to provoke neural changes in both humans and animals by impairing brain morphology and functionality. A selective decrement of cerebellar structure is described [87] in association with alterations in cognition and behavior [88]. McConnel et al. [87] exposed male and female rats to undernutrition from birth to 30th postnatal day and then to a 140-day-long period of multidimensional EE (without running wheels). After EE, the authors described a restoration of cerebellar weight in females but not in males. In contrast, Lima et al. [88] undernourished male rats from birth to 50th postnatal day and exposed these animals to handling from birth for 21 days and then to multidimensional EE (without running wheels) for 27 days. After the exposure to EE, the enriched animals showed increased cerebellar weight in comparison to the non-enriched controls, with increased total deoxyribonucleic acid (DNA) amount and unchanged total ribonucleic acid (RNA) amount. Notably, enriched animals showed a reduction in aversiveness in the inhibitory avoidance test. Aging is known to provoke cognitive decline and alterations in brain structure and function, including changes in cerebellar levels of nitric oxide, which is produced by neurons and acts as a neurotransmitter to regulate functions ranging from digestion and blood flow to memory and vision [89]. Tomiga et al. [90] investigated in a model of aging (male mice of 19.5 months of age) the effects of the exposure to 6 weeks of multidimensional EE. The authors reported that nitric oxide synthase expression increased in the cerebellum of aged mice but was reduced by the exposure to EE. In parallel, reduced anxiety-like behaviors were reported in enriched aged mice. Finally, the therapeutic effects of EE have also been investigated in a mouse model of hereditary cerebellar degeneration, the Lurcher mutant mice. In this model, Purkinje cells almost completely degenerate within 3 months of age. In addition, massive alterations of the other cerebellar cell populations occur. At a functional level, Lurcher mutant mice show cerebellar ataxia with cognitive and behavioral deficits [91]. In a recent study, Salomova et al. [92] exposed 8-week-old male and female Lurcher mutant mice to 9 weeks of multidimensional EE. At the end of the treatment, although some reduction of behavioral disinhibition was found in enriched animals, motor performance remained impaired and cerebellar BDNF remained unchanged. Details on the studies cited in this section are provided in Table 3. 6. Conclusions The aim of this review was the collection and the synthesis of the evidence provided by animal models on the effects of EE exposure on cerebellar structure and function, taking into account the studies on healthy subjects and on animals exposed to EE before and after damage involving cerebellar functionality. Figure 2 shows a panel summarizing the evidence synthesized in this review. To the best of our knowledge, this is the first review of the literature on the effects of exposure to EE specifically devoted to such a topic. On the whole, the evidence collected suggests that EE is able to enhance cerebellar compensation and develop cerebellar reserve. However, the limited indications available do not still offer a clear and coherent framework. As for the healthy animals, most findings concern the effects of early exposures to EE, starting from the birth or the weaning of the animals. Several studies report that EE induces plastic rearrangements in the cerebellar regions, describing changes in synaptogenesis [62,63], neurotrophin levels [57,66], neurotransmitter expression [67], and chromatin levels [68], as well as electrophysiological modifications [70]. However, opposing evidence reports the absence of EE effects on synaptogenesis [64,65], neurotrophin [66] and neurotransmitter expression [67], and chromatin levels [69]. As regards the exposure of animals to EE later in life, within the limited indications available, the changes in cerebellar volume and polypeptides associated with improved spatial learning described in mice and rats exposed to EE in adulthood should be mentioned [71,72]. On the whole, it is possible to include cerebellar rearrangement among the beneficial effects of EE, even if more systematic research and more consistent results are needed to understand the mechanisms involved. Stamenkovic et al. [93] advanced that the extracellular matrix glycoprotein tenascin-C contributes to the regulation of cerebellar structural plasticity, also in response to EE, and that the interaction between such a glycoprotein and the degrading enzyme matrix metalloproteinase-9 may be critical for the occurrence of EE-driven rearrangement. Interestingly, some evidence has also been provided on transgenerational effects of the exposure to EE on cerebellar plasticity. Pre-reproductive maternal exposure to EE is reported to result in enhanced cerebellar BDNF and NGF expression in pups both at birth and at weaning, associated with earlier acquisition of complex motor abilities [94]. As for the evidence available on the beneficial neuroprotective action of EE in developing a cerebellar reserve that strengthens the capacity of the individual to cope with brain damage, studies have been conducted with reference to two pathological conditions involving cerebellar functionality, namely Rett syndrome (modeled in transgenic mice) and cerebellar trauma (modeled by unilateral cerebellar ablation). In mice transgenic models of Rett syndrome, it has been demonstrated that the early exposure to EE was able to at least partially prevent motor deficits [75,76,77] and to modulate cerebellar inhibitory synaptic density [77]. However, unchanged cerebellar volume [76] and BDNF expression [75] were also reported. On the other hand, in rats exposed to EE from weaning before hemicerebellectomy, it has been demonstrated that in association with an accelerated motor recovery, Purkinje cells maintained the strengthened rearrangement induced by the EE, without showing most changes present in standard reared lesioned animals [4]. Similarly, the augmented BDNF expression induced by the EE was not further rearranged as a consequence of the lesion [79]. This pattern seems to indicate that further morphological rearrangements aiming to support cerebellar compensation may not be needed in a brain previously empowered by the exposure to EE. It has been advanced that this pattern was accompanied by an EE-driven massive rearrangement of the rest of the brain, involving neocortical and striatal neural morphology [31,60] and neocortical neurotrophin expression [79]. Finally, evidence has also been provided about the therapeutic action of EE in enhancing spontaneous cerebellar compensation following damage, as well as when the exposure occurs and the damage is already present. EE therapeutic effects have been investigated in the presence of a number of different pathological patterns. The exposure to EE in periods following weaning affects cerebellar structure and function after prenatal exposure to detrimental factors, such as alcohol [81], stress [84], and betamethasone [86], by inducing changes at molecular and supramolecular levels in association with reduction of behavioral symptoms. Beneficial EE effects are also documented after undernourishment in early life, in which is reported the reduction of aversiveness in the inhibitory avoidance and change in cerebellar weight and DNA total amount [87,88]. Beneficial effects are also found in a mouse aging model, in which EE reduces anxiety-like behaviors and nitric oxide synthase expression [90]. Finally, in a mouse ataxia model, EE was found to reduce behavioral disinhibition but failed to change motor performance and cerebellar BDNF expression [92]. Additionally, in the case of exposure to EE after the damage, it has been advanced that the enhancement of cerebellar compensation that follows EE may be due to the synergistic action of other brain areas, such as the striatum [95]. In conclusion, evidence provided by animal studies supports the beneficial action of enhanced stimulations in developing a cerebellar reserve that is able to potentiate spontaneous cerebellar capacities to compensate for deficits induced by brain injury or neurodegeneration. Such a beneficial action is also present when the complex stimulations are applied after the occurrence of the damage. However, studies addressing this issue with a specific interest in the cerebellum are still scarce, and the poor evidence provided means that large areas of inconsistency and lack of clarity remain. Moreover, the studies were performed at various points across a long period of time, and thus a significant number did not use modern innovative techniques and methodological standards. Thus, it would be advisable that increased attention is devoted to this issue, since it could be very relevant for management of cerebellar patients. Indeed, in terms of clinical implications, deepening the biological bases of experiential stimulation effects on the development of a cerebellar reserve, to be spent in case of damage, and on the enhancement of cerebellar spontaneous compensation after damage may be crucial for two key reasons. Firstly, such a line of research could shed some light on mechanisms involved in cerebellar reserve and compensation of human pathologies that involve cerebellar functionality [96]. Secondly, understanding the direction and extent of the cerebellar rearrangements, as well as the timing of effective interventions, may provide a good basis for tuned and effective clinical interventions in humans. Human studies described the high cerebellar capacity to compensate for damage due to acute focal lesions or diffuse neurodegeneration. Such a compensation occurs in the so-called “restorable stage”, in which intact cerebellar and extra-cerebellar areas are still able to cope with damage [55]. This could be an ideal period in which plastic factors may act to improve cerebellar compensation capacity. However, human studies devoted to analyzing the effects of experiences occurring before or after an injury on cerebellar capacity to compensate for a damage are still scarce. Some indications are provided by studies on the beneficial effects of physical activity on motor and cognitive performances of older adults (65–86 years) by documenting that such effects are accompanied by a more targeted and less widespread cerebellar activation [97]. Moreover, some evidence has been provided in patients with cerebellar degeneration, in whom physical training improves motor deficits. Such an effect would be mediated by increased cerebellar volumes accompanied by increased gray matter volumes of non-affected neocortical regions [98]. Further, if applied when residual cerebellar reserve is present, even non-invasive cerebellar stimulation techniques are able to potentiate compensation in many human cerebellar pathologies [99]. However, on the whole, as also reported by human secondary studies, the neuronal mechanisms underlying experiential and non-invasive stimulations of the development of cerebellar reserve and of the enhancement of compensation are still largely unknown [100]. Further animal and human primary and systematic secondary studies may provide valid suggestions on mechanisms involved in such phenomena. Author Contributions Conceptualization and study design, F.G. and L.P.; literature search and analysis, F.G.; writing and editing of the manuscript, F.G. and L.P. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The concept reported in this manuscript is not associated with raw data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PRISMA flow-diagram [61] illustrating the literature search process. Figure 2 The panel synthesizes the evidence provided by animal models on the effects of environmental enrichment exposure on the cerebellum, taking into account the studies on healthy subjects (box in the middle) and on animals exposed to EE before (box at the bottom on the left side) and after (box at the bottom on the right side) a damage involving cerebellar functionality. BDNF: brain-derived neurotrophic factor; DNA: deoxyribonucleic acid. ijerph-19-05697-t001_Table 1 Table 1 Studies on environmental enrichment’s effects in healthy animals. Reference Species (Age or Weight at the Start of Environmental Enrichment) Environmental Enrichment Type (Duration) Environmental Enrichment Effects on Cerebellar Structure and Function (Age at the Effect Evaluations) Uphouse, 1978 [68] Male Fischer rats (28 days) Environmental enrichment —without running wheels; with novelty manipulation (32 days) Increased chromatin level (2 months) Uphouse and Tedeschi, 1979 [69] Male Fischer rats (28 days) Environmental enrichment —without running wheels; with novelty manipulation (60 days) Unchanged chromatin level (about 3 months) Naka et al., 2002 [67] Male ICR mice (28 days) Environmental enrichment —with running wheels and novelty manipulation (40 days) Increased noradrenaline expression; unchanged serotonin and metabolites expression (about 2 months) Nithianantharajah et al., 2004 [64] Female C57BL/6 mice (28 days) Environmental enrichment —with running wheels and novelty manipulation (30 days) Unchanged synaptophysin level (about 2 months) Angelucci et al., 2009 [57] Male Wistar rats (21 days) Environmental enrichment —with running wheels and novelty manipulation (about 120 days) Increased nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) levels (140 days) Pascual and Bustamante, 2013 [65] Male Sprague–Dawley rats (22 days) Environmental enrichment —with running wheels and novelty manipulation (10 days) Unchanged anxiety-like behavior (33–34 days); unchanged vermal Purkinje cell dendritic outgrowth (36 days) Vazquez-Sanroman et al., 2013 [66] Male Balb/c AnNHsd mice (21 days) Environmental enrichment —without running wheels; with novelty manipulation (1/4/8 weeks) After 1 week: unchanged pro-BDNF and mature BDNF proteins; increased BDNF immunoreactivity at granular layer; unchanged BDNF immunoreactivity at Purkinje layer (4 weeks) After 4 weeks: increased BDNF immunoreactivity at granular and Purkinje layers (7 weeks) After 8 weeks: increased pro-BDNF and mature BDNF proteins; increased BDNF immunoreactivity at granular and Purkinje layers (11 weeks) De Bartolo et al., 2015 [62] Male Wistar rats (21 days) Environmental enrichment —with running wheels and novelty manipulation (about 100 days) Increased cerebellar Purkinje cell dendritic spine density and size (about 120 days) Horvat et al., 2015 [72] Male Wistar rats (6 months) Environmental enrichment —without running wheels; with novelty manipulation (21 days) Increased pituitary adenylate cyclase activating polypeptide (PACAP) 27 expression; unchanged PACAP 38 expression (27 weeks) Scholz et al., 2015 [71] Male C57BL/B6 mice (7 weeks) Environmental enrichment —with running wheels and novelty manipulation—based on a three-level maze, without objects (24 h; 21 days) Improved spatial learning (10 weeks); decreased volume (about 7 weeks; 10 weeks) Eshra et al., 2019 [70] C57BL/6 mice (at birth) Environmental enrichment —with running wheels and novelty manipulation (70–80 days) Improved motor performance; higher granule cell firing frequency (70–80 days) Kim et al., 2019 [63] C57BL/6 mice (3 weeks) Environmental enrichment —with running wheels and novelty manipulation (28 days) Selective increase in parallel fiber-to-Purkinje cell synapses of same dendritic origin, with local synaptic strengthening (7 weeks) Note: unless otherwise specified, the described effects involve the entire cerebellar structure. ijerph-19-05697-t002_Table 2 Table 2 Studies on neuroprotective environmental enrichment effects in pathological animal models. Reference Species and Pathological Model (Age or Weight at the Start of Environmental Enrichment) Environmental Enrichment Type (Duration) Environmental Enrichment Effects on Cerebellar Structure and Function (Age at the Effect Evaluation) Kondo et al., 2008 [75] Hemizygous male and heterozygous female Mecp2tm1Tam mice; model of Rett syndrome (more rapid onset and progression of symptoms in males) (28 days) Environmental enrichment —with running wheels and novelty manipulation; without social manipulation (Males: 6 weeks; Females: 26 weeks) In males: unchanged locomotor activity (6; 9 weeks) and motor coordination (7; 8; 9 weeks); unchanged BDNF expression (10 weeks) In females: prevention of early motor coordination deficits (20; 23; 26 weeks); unchanged locomotor activity (15 weeks) and late motor coordination (29 weeks); unchanged BDNF expression (30 weeks) Nag et al., 2009 [76] Male Mecp21lox mice; model of Rett syndrome (21 days) Environmental enrichment —with running wheels and novelty manipulation; without social manipulation (23 days) Prevention of locomotor deficits; unchanged motor coordination and contextual or cued fear conditioning (29–43 days); unchanged volume (44 days) Lonetti et al., 2010 [77] Male Mecp2tm1Jae mice; model of Rett syndrome (10 days) Environmental enrichment —with running wheels and novelty manipulation (50 days) In males: prevention of motor coordination and motor learning deficits (30–60 days); increased inhibitory synaptic density (52 days) Gelfo et al., 2011 [79] Male Wistar rats; model of cerebellar trauma (hemicerebellectomy at 75th postnatal day) (21 days) Environmental enrichment —with running wheels and novelty manipulation (about 4 months) Accelerated motor recovery (1–42 post-operative days); increased NGF expression; unchanged BDNF expression (5 months) Gelfo et al., 2016 [4] Male Wistar rats; model of cerebellar trauma (hemicerebellectomy at 75th postnatal day) (21 days) Environmental enrichment —with running wheels and novelty manipulation (about 4 months) Accelerated motor recovery and restoration of complex motor behaviors (1–56 post-operative days); increased spatial learning and memory performance (about 4 months); maintaining of Purkinje cell dendritic spine density and size (about 4.5 months) Note: unless otherwise specified, the described effects involve the entire cerebellar structure. ijerph-19-05697-t003_Table 3 Table 3 Studies on the therapeutic environmental enrichment effects in pathological animal models. Reference Species and Pathological Model (Age or Weight at the Start of Environmental Enrichment) Environmental Enrichment Type (Duration) Environmental Enrichment Effects on Cerebellar Structure and Function (Age at the Effect Evaluation) McConnell et al., 1981 [87] Male and female rats; undernourished from birth to 30th postnatal day (30 days) Environmental enrichment —without running wheels; with novelty manipulation (140 days) In males: no restoration of cerebellar weight (170 days) In females: restoration of cerebellar weight (170 days) Lima et al., 1998 [88] Male Wistar rats; undernourished from birth to 50th postnatal day (handling from birth to 21 days; then environmental enrichment) Environmental enrichment —without running wheels and novelty manipulation (27 days) Reduction of aversiveness in the inhibitory avoidance test (47 days); Increased weight; increased total deoxyribonucleic acid (DNA) amount; unchanged total ribonucleic (RNA) amount (50 days) Parks et al., 2008 [81] Male/female Sprague–Dawley rats; prenatal alcohol exposure from gestational day 8 to gestational day 20 (21 days) Environmental enrichment —without running wheels; with novelty manipulation (42 days) Unchanged vermal NGF expression; increased vermal (neurotrophin-3) NT-3 expression (66 days) Pascual et al., 2015 [84] Male CF-1 mice; exposed to prenatal restraint stress from gestational day 14 to gestational day 21 (22 days) Environmental enrichment —with running wheels and novelty manipulation (30 days) Reduced anxiety-like behavior; rescuing of the vermal Purkinje cell dendritic deterioration (82 days) Tomiga et al., 2016 [90] Male C57BL/6J mice; model of aging (19.5 months) Environmental enrichment —with running wheels and novelty manipulation (6 weeks) Reduced anxiety-like behavior; reduced nitric oxide synthase expression (21 months) Valencia et al., 2019 [86] Male Sprague–Dawley rats; exposed to prenatal treatment with betamethasone on gestational day 20 (21 days) Environmental enrichment —with running wheels and novelty manipulation (18 days) Restored motor coordination; restored vermal synaptophysin level (52 days) Salomova et al., 2021 [92] Male and female Lurcher mutant mice (8 weeks) Environmental enrichment —with running wheels and novelty manipulation (9 weeks) Unchanged motor performance; reduction in behavioral disinhibition (15–16 weeks); unchanged BDNF expression (17 weeks) Note: unless otherwise specified, the described effects involve the entire cerebellar structure. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Innocenti G.M. Postnatal development of corticocortical connections Ital. J. Neurol. Sci. 1986 5 25 28 3093402 2. Innocenti G.M. Chapter 1—Defining Neuroplasticity Handbook of Clinical Neurology Quartarone A. Ghilardi M.F. Boller F. Neuroplasticity Elsevier Amsterdam, The Netherlands 2022 Volume 184 3 18 3. Merzenich M.M. Van Vleet T.M. Nahum M. Brain plasticity-based therapeutics Front. Hum. Neurosci. 2014 8 385 10.3389/fnhum.2014.00385 25018719 4. Gelfo F. Florenzano F. Foti F. Burello L. Petrosini L. De Bartolo P. Lesion-induced and activity-dependent structural plasticity of Purkinje cell dendritic spines in cerebellar vermis and hemisphere Brain Struct. Funct. 2016 221 3405 3426 10.1007/s00429-015-1109-5 26420278 5. Nahmani M. Turrigiano G.G. Adult cortical plasticity following injury: Recapitulation of critical period mechanisms? Neuroscience 2014 283 4 16 10.1016/j.neuroscience.2014.04.029 24791715 6. Stern Y. Zarahn E. Hilton H.J. Flynn J. DeLaPaz R. Rakitin B. Exploring the neural basis of cognitive reserve J. Clin. Exp. Neuropsychol. 2003 25 691 701 10.1076/jcen.25.5.691.14573 12815506 7. Stern Y. Tang M.X. Denaro J. Mayeux R. Increased risk of mortality in alzheimer’s disease patients with more advanced educational and occupational attainment Ann. Neurol. 1995 37 590 595 10.1002/ana.410370508 7755353 8. Perneczky R. Kempermann G. Korczyn A.D. Matthews F.E. Ikram M.A. Scarmeas N. Chetelat G. Stern Y. Ewers M. Translational research on reserve against neurodegenerative disease: Consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer’s Association Reserve, Resilience and Protective Factors Professional Interest Area working groups BMC Med. 2019 17 47 10.1186/s12916-019-1283-z 30808345 9. Serra L. Gelfo F. Petrosini L. Di Domenico C. Bozzali M. Caltagirone C. Rethinking the Reserve with a Translational Approach: Novel Ideas on the Construct and the Interventions J. Alzheimers Dis. 2018 65 1065 1078 10.3233/JAD-180609 30149458 10. Serra L. Gelfo F. What good is the reserve? A translational perspective for the managing of cognitive decline Neural Regen. Res. 2019 14 1219 1220 10.4103/1673-5374.251328 30804252 11. Stern Y. Arenaza-Urquijo E.M. Bartrés-Faz D. Belleville S. Cantilon M. Chetelat G. Ewers M. Franzmeier N. Kempermann G. Kremen W.S. Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance Alzheimers Dement. 2020 16 1305 1311 10.1016/j.jalz.2018.07.219 30222945 12. Stern Y. Barnes C.A. Grady C. Jones R.N. Raz N. Brain reserve, cognitive reserve, compensation, and maintenance: Operationalization, validity, and mechanisms of cognitive resilience Neurobiol. Aging 2019 83 124 129 10.1016/j.neurobiolaging.2019.03.022 31732015 13. Mandolesi L. Gelfo F. Serra L. Montuori S. Polverino A. Curcio G. Sorrentino G. Environmental Factors Promoting Neural Plasticity: Insights from Animal and Human Studies Neural Plast. 2017 2017 e7219461 10.1155/2017/7219461 28740740 14. Lövdén M. Fratiglioni L. Glymour M.M. Lindenberger U. Tucker-Drob E.M. Education and Cognitive Functioning Across the Life Span Psychol. Sci. Public Interest 2020 21 6 41 10.1177/1529100620920576 32772803 15. Pudas S. Rönnlund M. School Performance and Educational Attainment as Early-Life Predictors of Age-Related Memory Decline: Protective Influences in Later-Born Cohorts J. Gerontol. Ser. B 2019 74 1356 1365 10.1093/geronb/gby137 30445430 16. Vance D.E. Cody S.L. Yoo-Jeong M. Jones G. Lynn D. Nicholson W.C. The Role of Employment on Neurocognitive Reserve in Adults With HIV: A Review of the Literature J. Assoc. Nurses AIDS Care 2015 26 316 329 10.1016/j.jana.2015.04.003 26066688 17. Yates L.A. Ziser S. Spector A. Orrell M. Cognitive leisure activities and future risk of cognitive impairment and dementia: Systematic review and meta-analysis Int. Psychogeriatr. 2016 28 1791 1806 10.1017/S1041610216001137 27502691 18. Sachdev P.S. Social health, social reserve and dementia Curr. Opin. Psychiatry 2022 35 111 117 10.1097/YCO.0000000000000779 35084381 19. Zahodne L.B. Psychosocial Protective Factors in Cognitive Aging: A Targeted Review Arch. Clin. Neuropsychol. Off. J. Natl. Acad. Neuropsychol. 2021 36 1266 1273 10.1093/arclin/acab051 20. Chapko D. McCormack R. Black C. Staff R. Murray A. Life-course determinants of cognitive reserve (CR) in cognitive aging and dementia—A systematic literature review Aging Ment. Health 2018 22 921 932 10.1080/13607863.2017.1348471 21. Phillips C. Lifestyle Modulators of Neuroplasticity: How Physical Activity, Mental Engagement, and Diet Promote Cognitive Health during Aging Neural Plast. 2017 2017 e3589271 10.1155/2017/3589271 22. Song S. Stern Y. Gu Y. Modifiable lifestyle factors and cognitive reserve: A systematic review of current evidence Ageing Res. Rev. 2022 74 101551 10.1016/j.arr.2021.101551 34952208 23. Diamond M.C. Law F. Rhodes H. Lindner B. Rosenzweig M.R. Krech D. Bennett E.L. Increases in cortical depth and glia numbers in rats subjected to enriched environment J. Comp. Neurol. 1966 128 117 125 10.1002/cne.901280110 4165855 24. Rosenzweig M.R. Bennett E.L. Psychobiology of plasticity: Effects of training and experience on brain and behavior Behav. Brain Res. 1996 78 57 65 10.1016/0166-4328(95)00216-2 8793038 25. Mo C. Renoir T. Hannan A.J. What’s wrong with my mouse cage? Methodological considerations for modeling lifestyle factors and gene–environment interactions in mice J. Neurosci. Methods 2016 265 99 108 10.1016/j.jneumeth.2015.08.008 26279343 26. Petrosini L. De Bartolo P. Foti F. Gelfo F. Cutuli D. Leggio M.G. Mandolesi L. On whether the environmental enrichment may provide cognitive and brain reserves Brain Res. Rev. 2009 61 221 239 10.1016/j.brainresrev.2009.07.002 19631687 27. Gelfo F. Mandolesi L. Serra L. Sorrentino G. Caltagirone C. The Neuroprotective Effects of Experience on Cognitive Functions: Evidence from Animal Studies on the Neurobiological Bases of Brain Reserve Neuroscience 2018 370 218 235 10.1016/j.neuroscience.2017.07.065 28827089 28. Sampedro-Piquero P. Begega A. Environmental Enrichment as a Positive Behavioral Intervention Across the Lifespan Curr. Neuropharmacol. 2017 15 459 470 10.2174/1570159X14666160325115909 27012955 29. Cutuli D. Landolfo E. Petrosini L. Gelfo F. Environmental Enrichment Effects on the Brain-Derived Neurotrophic Factor Expression in Healthy Condition, Alzheimer’s Disease, and Other Neurodegenerative Disorders J. Alzheimers Dis. 2022 85 975 992 10.3233/JAD-215193 34897089 30. Durán-Carabali L.E. Odorcyk F.K. Sanches E.F. de Mattos M.M. Anschau F. Netto C.A. Effect of environmental enrichment on behavioral and morphological outcomes following neonatal hypoxia-ischemia in rodent models: A systematic review and meta-analysis Mol. Neurobiol. 2022 59 1970 1991 10.1007/s12035-022-02730-9 35040041 31. Gelfo F. De Bartolo P. Giovine A. Petrosini L. Leggio M.G. Layer and regional effects of environmental enrichment on the pyramidal neuron morphology of the rat Neurobiol. Learn. Mem. 2009 91 353 365 10.1016/j.nlm.2009.01.010 19340947 32. Kuznetsova M. Wilson C. Hannan A.J. Renoir T. How the enriched get richer? Experience-dependent modulation of microRNAs and the therapeutic effects of environmental enrichment Pharmacol. Biochem. Behav. 2020 195 172940 10.1016/j.pbb.2020.172940 32413435 33. Mandolesi L. De Bartolo P. Foti F. Gelfo F. Federico F. Leggio M.G. Petrosini L. Environmental enrichment provides a cognitive reserve to be spent in the case of brain lesion J. Alzheimers Dis. 2008 15 11 28 10.3233/JAD-2008-15102 18780964 34. Smail M.A. Smith B.L. Nawreen N. Herman J.P. Differential impact of stress and environmental enrichment on corticolimbic circuits Pharmacol. Biochem. Behav. 2020 197 172993 10.1016/j.pbb.2020.172993 32659243 35. Gelfo F. Does Experience Enhance Cognitive Flexibility? An Overview of the Evidence Provided by the Environmental Enrichment Studies Front. Behav. Neurosci. 2019 13 150 10.3389/fnbeh.2019.00150 31338030 36. Gubert C. Hannan A.J. Environmental enrichment as an experience-dependent modulator of social plasticity and cognition Brain Res. 2019 1717 1 14 10.1016/j.brainres.2019.03.033 30930150 37. Leggio M.G. Mandolesi L. Federico F. Spirito F. Ricci B. Gelfo F. Petrosini L. Environmental enrichment promotes improved spatial abilities and enhanced dendritic growth in the rat Behav. Brain Res. 2005 163 78 90 10.1016/j.bbr.2005.04.009 15913801 38. Singhal G. Morgan J. Jawahar M.C. Corrigan F. Jaehne E.J. Toben C. Breen J. Pederson S.M. Hannan A.J. Baune B.T. The effects of short-term and long-term environmental enrichment on locomotion, mood-like behavior, cognition and hippocampal gene expression Behav. Brain Res. 2019 368 111917 10.1016/j.bbr.2019.111917 31004685 39. Bosman L.W.J. Konnerth A. Activity-dependent plasticity of developing climbing fiber–Purkinje cell synapses Neuroscience 2009 162 612 623 10.1016/j.neuroscience.2009.01.032 19302832 40. Cesa R. Strata P. Axonal and synaptic remodeling in the mature cerebellar cortex Progress in Brain Research Creating coordination in the cerebellum Elsevier Amsterdam, The Netherlands 2005 Volume 148 45 56 41. De Bartolo P. Mandolesi L. Federico F. Foti F. Cutuli D. Gelfo F. Petrosini L. Cerebellar involvement in cognitive flexibility Neurobiol. Learn. Mem. 2009 92 310 317 10.1016/j.nlm.2009.03.008 19362159 42. Argyropoulos G.P. Cerebellar Theta-Burst Stimulation Selectively Enhances Lexical Associative Priming Cerebellum 2011 10 540 550 10.1007/s12311-011-0269-y 21451999 43. Argyropoulos G.P. Muggleton N.G. Effects of Cerebellar Stimulation on Processing Semantic Associations Cerebellum 2013 12 83 96 10.1007/s12311-012-0398-y 22752996 44. D’Mello A.M. Turkeltaub P.E. Stoodley C.J. Cerebellar tDCS Modulates Neural Circuits during Semantic Prediction: A Combined tDCS-fMRI Study J. Neurosci. 2017 37 1604 1613 10.1523/JNEUROSCI.2818-16.2017 28069925 45. Gatti D. Van Vugt F. Vecchi T. A causal role for the cerebellum in semantic integration: A transcranial magnetic stimulation study Sci. Rep. 2020 10 18139 10.1038/s41598-020-75287-z 33097802 46. Gatti D. Vecchi T. Mazzoni G. Cerebellum and semantic memory: A TMS study using the DRM paradigm Cortex 2021 135 78 91 10.1016/j.cortex.2020.11.017 33360762 47. Hoffland B.S. Bologna M. Kassavetis P. Teo J.T.H. Rothwell J.C. Yeo C.H. van de Warrenburg B.P. Edwards M.J. Cerebellar theta burst stimulation impairs eyeblink classical conditioning J. Physiol. 2012 590 887 897 10.1113/jphysiol.2011.218537 22199171 48. Lesage E. Morgan B.E. Olson A.C. Meyer A.S. Miall R.C. Cerebellar rTMS disrupts predictive language processing Curr. Biol. 2012 22 R794 R795 10.1016/j.cub.2012.07.006 23017990 49. Miall R.C. Antony J. Goldsmith-Sumner A. Harding S.R. McGovern C. Winter J.L. Modulation of linguistic prediction by TDCS of the right lateral cerebellum Neuropsychologia 2016 86 103 109 10.1016/j.neuropsychologia.2016.04.022 27126840 50. Moberget T. Gullesen E.H. Andersson S. Ivry R.B. Endestad T. Generalized role for the cerebellum in encoding internal models: Evidence from semantic processing J. Neurosci. Off. J. Soc. Neurosci. 2014 34 2871 2878 10.1523/JNEUROSCI.2264-13.2014 51. Monaco J. Casellato C. Koch G. D’Angelo E. Cerebellar theta burst stimulation dissociates memory components in eyeblink classical conditioning Eur. J. Neurosci. 2014 40 3363 3370 10.1111/ejn.12700 25185744 52. Burello L. De Bartolo P. Gelfo F. Foti F. Angelucci F. Petrosini L. Functional recovery after cerebellar damage is related to GAP-43-mediated reactive responses of pre-cerebellar and deep cerebellar nuclei Exp. Neurol. 2012 233 273 282 10.1016/j.expneurol.2011.10.016 22063813 53. Carulli D. Buffo A. Strata P. Reparative mechanisms in the cerebellar cortex Prog. Neurobiol. 2004 72 373 398 10.1016/j.pneurobio.2004.03.007 15177783 54. Luciani L. Il Cervelletto. Nuovi Studi di Fisiologia Normale E Patologica Philos. Rev. 1893 2 475 477 10.2307/2175726 55. Mitoma H. Buffo A. Gelfo F. Guell X. Fucà E. Kakei S. Lee J. Manto M. Petrosini L. Shaikh A.G. Consensus Paper. Cerebellar Reserve: From Cerebellar Physiology to Cerebellar Disorders Cerebellum 2020 19 131 153 10.1007/s12311-019-01091-9 31879843 56. Mitoma H. Kakei S. Yamaguchi K. Manto M. Physiology of Cerebellar Reserve: Redundancy and Plasticity of a Modular Machine Int. J. Mol. Sci. 2021 22 4777 10.3390/ijms22094777 33946358 57. Angelucci F. De Bartolo P. Gelfo F. Foti F. Cutuli D. Bossù P. Caltagirone C. Petrosini L. Increased Concentrations of Nerve Growth Factor and Brain-Derived Neurotrophic Factor in the Rat Cerebellum After Exposure to Environmental Enrichment Cerebellum 2009 8 499 506 10.1007/s12311-009-0129-1 19688409 58. Fucà E. Guglielmotto M. Boda E. Rossi F. Leto K. Buffo A. Preventive motor training but not progenitor grafting ameliorates cerebellar ataxia and deregulated autophagy in tambaleante mice Neurobiol. Dis. 2017 102 49 59 10.1016/j.nbd.2017.02.005 28237314 59. Gelfo F. Petrosini L. Is it possible to develop a cerebellar reserve? Neural Regen. Res. 2022 17 994 996 10.4103/1673-5374.324836 34558516 60. Cutuli D. Rossi S. Burello L. Laricchiuta D. De Chiara V. Foti F. De Bartolo P. Musella A. Gelfo F. Centonze D. Before or after does it matter? Different protocols of environmental enrichment differently influence motor, synaptic and structural deficits of cerebellar origin Neurobiol. Dis. 2011 42 9 20 10.1016/j.nbd.2010.12.007 21182946 61. Page M.J. McKenzie J.E. Bossuyt P.M. Boutron I. Hoffmann T.C. Mulrow C.D. Shamseer L. Tetzlaff J.M. Akl E.A. Brennan S.E. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews BMJ 2021 372 n71 10.1136/bmj.n71 33782057 62. De Bartolo P. Florenzano F. Burello L. Gelfo F. Petrosini L. Activity-dependent structural plasticity of Purkinje cell spines in cerebellar vermis and hemisphere Brain Struct. Funct. 2015 220 2895 2904 10.1007/s00429-014-0833-6 25023735 63. Kim H.-W. Oh S. Lee S.H. Lee S. Na J.-E. Lee K.J. Rhyu I.J. Different types of multiple-synapse boutons in the cerebellar cortex between physically enriched and ataxic mutant mice Microsc. Res. Tech. 2019 82 25 32 10.1002/jemt.23054 29774619 64. Nithianantharajah J. Levis H. Murphy M. Environmental enrichment results in cortical and subcortical changes in levels of synaptophysin and PSD-95 proteins Neurobiol. Learn. Mem. 2004 81 200 210 10.1016/j.nlm.2004.02.002 15082021 65. Pascual R. Bustamante C. Early postweaning social isolation but not environmental enrichment modifies vermal Purkinje cell dendritic outgrowth in rats Acta Neurobiol. Exp. 2013 73 387 393 66. Vazquez-Sanroman D. Sanchis-Segura C. Toledo R. Hernandez M.E. Manzo J. Miquel M. The effects of enriched environment on BDNF expression in the mouse cerebellum depending on the length of exposure Behav. Brain Res. 2013 243 118 128 10.1016/j.bbr.2012.12.047 23295397 67. Naka F. Shiga T. Yaguchi M. Okado N. An enriched environment increases noradrenaline concentration in the mouse brain Brain Res. 2002 924 124 126 10.1016/S0006-8993(01)03257-7 11744005 68. Uphouse L. In vitro RNA synthesis by chromatin from three brain regions of differentially reared rats Behav. Biol. 1978 22 39 49 10.1016/S0091-6773(78)91989-2 623608 69. Uphouse L. Tedeschi B. Environmental enrichment and brain chromatin Behav. Neural Biol. 1979 25 268 270 10.1016/S0163-1047(79)90636-8 464978 70. Eshra A. Hirrlinger P. Hallermann S. Enriched Environment Shortens the Duration of Action Potentials in Cerebellar Granule Cells Front. Cell. Neurosci. 2019 13 289 10.3389/fncel.2019.00289 31379501 71. Scholz J. Allemang-Grand R. Dazai J. Lerch J.P. Environmental enrichment is associated with rapid volumetric brain changes in adult mice NeuroImage 2015 109 190 198 10.1016/j.neuroimage.2015.01.027 25595504 72. Horvath G. Kiss P. Nemeth J. Lelesz B. Tamas A. Reglodi D. Environmental enrichment increases PACAP levels in the CNS of adult rats Neuro Endocrinol. Lett. 2015 36 143 147 26071583 73. Ivy A.S. Standridge S. Rett Syndrome: A Timely Review From Recognition to Current Clinical Approaches and Clinical Study Updates Semin. Pediatr. Neurol. 2021 37 100881 10.1016/j.spen.2021.100881 33892852 74. Harris J.C. Animal models of neurodevelopmental disorders with behavioral phenotypes Curr. Opin. Psychiatry 2021 34 87 93 10.1097/YCO.0000000000000675 33395099 75. Kondo M. Gray L.J. Pelka G.J. Christodoulou J. Tam P.P.L. Hannan A.J. Environmental enrichment ameliorates a motor coordination deficit in a mouse model of Rett syndrome –Mecp2 gene dosage effects and BDNF expression Eur. J. Neurosci. 2008 27 3342 3350 10.1111/j.1460-9568.2008.06305.x 18557922 76. Nag N. Moriuchi J.M. Peitzman C.G.K. Ward B.C. Kolodny N.H. Berger-Sweeney J.E. Environmental enrichment alters locomotor behaviour and ventricular volume in Mecp21lox mice Behav. Brain Res. 2009 196 44 48 10.1016/j.bbr.2008.07.008 18687363 77. Lonetti G. Angelucci A. Morando L. Boggio E.M. Giustetto M. Pizzorusso T. Early Environmental Enrichment Moderates the Behavioral and Synaptic Phenotype of MeCP2 Null Mice Biol. Psychiatry 2010 67 657 665 10.1016/j.biopsych.2009.12.022 20172507 78. Foti F. Laricchiuta D. Cutuli D. De Bartolo P. Gelfo F. Angelucci F. Petrosini L. Exposure to an enriched environment accelerates recovery from cerebellar lesion Cerebellum Lond. Engl. 2011 10 104 119 10.1007/s12311-010-0236-z 79. Gelfo F. Cutuli D. Foti F. Laricchiuta D. De Bartolo P. Caltagirone C. Petrosini L. Angelucci F. Enriched Environment Improves Motor Function and Increases Neurotrophins in Hemicerebellar Lesioned Rats Neurorehabil. Neural Repair 2011 25 243 252 10.1177/1545968310380926 20966156 80. Almeida L. Andreu-Fernández V. Navarro-Tapia E. Aras-López R. Serra-Delgado M. Martínez L. García-Algar O. Gómez-Roig M.D. Murine Models for the Study of Fetal Alcohol Spectrum Disorders: An Overview Front. Pediatr. 2020 8 359 10.3389/fped.2020.00359 32760684 81. Parks E.A. McMechan A.P. Hannigan J.H. Berman R.F. Environmental Enrichment Alters Neurotrophin Levels After Fetal Alcohol Exposure in Rats Alcohol. Clin. Exp. Res. 2008 32 1741 1751 10.1111/j.1530-0277.2008.00759.x 18652597 82. Rasser P.E. Schall U. Peck G. Cohen M. Johnston P. Khoo K. Carr V.J. Ward P.B. Thompson P.M. Cerebellar grey matter deficits in first-episode schizophrenia mapped using cortical pattern matching NeuroImage 2010 53 1175 1180 10.1016/j.neuroimage.2010.07.018 20633666 83. Talge N.M. Neal C. Glover V. The Early Stress, Translational Research and Prevention Science Network: Fetal and Neonatal Experience on Child and Adolescent Mental Health Antenatal maternal stress and long-term effects on child neurodevelopment: How and why? J. Child Psychol. Psychiatry 2007 48 245 261 10.1111/j.1469-7610.2006.01714.x 17355398 84. Pascual R. Valencia M. Bustamante C. Purkinje Cell Dendritic Atrophy Induced by Prenatal Stress Is Mitigated by Early Environmental Enrichment Neuropediatrics 2015 46 37 43 10.1055/s-0034-1395344 25535699 85. Stålnacke J. Heijtz R.D. Norberg H. Norman M. Smedler A.-C. Forssberg H. Cognitive Outcome in Adolescents and Young Adults after Repeat Courses of Antenatal Corticosteroids J. Pediatr. 2013 163 441 446.e1 10.1016/j.jpeds.2013.01.030 23485033 86. Valencia M. Illanes J. Santander O. Saavedra D. Adaros M. Ibarra A. Saavedra G. Pascual R. Environmental enrichment restores the reduced expression of cerebellar synaptophysin and the motor coordination impairment in rats prenatally treated with betamethasone Physiol. Behav. 2019 209 112590 10.1016/j.physbeh.2019.112590 31252027 87. McConnell P. Uylings H.B.M. Swanson H.H. Verwer R.W.H. Sex differences in effects of environmental stimulation on brain weight of previously undernourished rats Behav. Brain Res. 1981 3 411 415 10.1016/0166-4328(81)90010-3 7306389 88. Lima J.G. de Oliveira L.M. Almeida S.S. Effects of Early Concurrent Protein Malnutrition and Environmental Stimulation on the Central Nervous System and Behavior Nutr. Neurosci. 1998 1 439 448 10.1080/1028415X.1998.11747254 27406551 89. Law A. O’Donnell J. Gauthier S. Quirion R. Neuronal and inducible nitric oxide synthase expressions and activities in the hippocampi and cortices of young adult, aged cognitively unimpaired, and impaired Long–Evans rats Neuroscience 2002 112 267 275 10.1016/S0306-4522(02)00082-9 12044445 90. Tomiga Y. Ito A. Sudo M. Ando S. Maruyama A. Nakashima S. Kawanaka K. Uehara Y. Kiyonaga A. Tanaka H. Effects of environmental enrichment in aged mice on anxiety-like behaviors and neuronal nitric oxide synthase expression in the brain Biochem. Biophys. Res. Commun. 2016 476 635 640 10.1016/j.bbrc.2016.06.010 27282485 91. Cendelin J. From mice to men: Lessons from mutant ataxic mice Cerebellum Ataxias 2014 1 4 10.1186/2053-8871-1-4 26331028 92. Salomova M. Tichanek F. Jelinkova D. Cendelin J. Forced activity and environmental enrichment mildly improve manifestation of rapid cerebellar degeneration in mice Behav. Brain Res. 2021 401 113060 10.1016/j.bbr.2020.113060 33316321 93. Stamenkovic V. Stamenkovic S. Jaworski T. Gawlak M. Jovanovic M. Jakovcevski I. Wilczynski G.M. Kaczmarek L. Schachner M. Radenovic L. The extracellular matrix glycoprotein tenascin-C and matrix metalloproteinases modify cerebellar structural plasticity by exposure to an enriched environment Brain Struct. Funct. 2017 222 393 415 10.1007/s00429-016-1224-y 27089885 94. Caporali P. Cutuli D. Gelfo F. Laricchiuta D. Foti F. De Bartolo P. Mancini L. Angelucci F. Petrosini L. Pre-reproductive maternal enrichment influences offspring developmental trajectories: Motor behavior and neurotrophin expression Front. Behav. Neurosci. 2014 8 195 10.3389/fnbeh.2014.00195 24910599 95. De Bartolo P. Gelfo F. Burello L. De Giorgio A. Petrosini L. Granato A. Plastic Changes in Striatal Fast-Spiking Interneurons Following Hemicerebellectomy and Environmental Enrichment The Cerebellum 2011 10 624 632 10.1007/s12311-011-0275-0 21509479 96. Al-Shaikh R.H. Wernick A.I. Strongosky A.J. Soto-Beasley A.I. van Gerpen J.A. Cheshire W.P. Uitti R.J. Ross O.A. Wszolek Z.K. Spinocerebellar ataxia type 6 family with phenotypic overlap with Multiple System Atrophy Neurol. Neurochir. Pol. 2020 54 350 355 10.5603/PJNNS.a2020.0053 32687595 97. Nissim M. Livny A. Barmatz C. Tsarfaty G. Berner Y. Sacher Y. Bodini R. Ratzon N.Z. Effects of Ai-Chi Practice on Balance and Left Cerebellar Activation during High Working Memory Load Task in Older People: A Controlled Pilot Trial Int. J. Environ. Res. Public. Health 2021 18 12756 10.3390/ijerph182312756 34886482 98. Burciu R.G. Fritsche N. Granert O. Schmitz L. Spönemann N. Konczak J. Theysohn N. Gerwig M. van Eimeren T. Timmann D. Brain Changes Associated with Postural Training in Patients with Cerebellar Degeneration: A Voxel-Based Morphometry Study J. Neurosci. 2013 33 4594 4604 10.1523/JNEUROSCI.3381-12.2013 23467375 99. Billeri L. Naro A. A narrative review on non-invasive stimulation of the cerebellum in neurological diseases Neurol. Sci. 2021 42 2191 2209 10.1007/s10072-021-05187-1 33759055 100. Lanza G. Casabona J.A. Bellomo M. Cantone M. Fisicaro F. Bella R. Pennisi G. Bramanti P. Pennisi M. Bramanti A. Update on intensive motor training in spinocerebellar ataxia: Time to move a step forward? J. Int. Med. Res. 2020 48 300060519854626 10.1177/0300060519854626 31537137

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19094990 ijerph-19-04990 Article Use of Health Services and Rehabilitation before and after the Beginning of Long-Term Sickness Absence—Comparing the Use by Employment and Disability Pension Transition after the Sickness Absence in Finland https://orcid.org/0000-0002-3199-3952 Perhoniemi Riku * https://orcid.org/0000-0001-5466-0205 Blomgren Jenni Iavicoli Ivo Academic Editor The Social Insurance Institution of Finland, 00250 Helsinki, Finland; jenni.blomgren@kela.fi * Correspondence: riku.perhoniemi@kela.fi 20 4 2022 5 2022 19 9 499010 3 2022 11 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The objective of the study was to follow the health care and rehabilitation use before, during and after long-term sickness absence (LTSA), and to compare the use by post-LTSA labour market situation in terms of disability pension and employment. Individuals aged 18–58 with a ≥30-day LTSA spell in 2015 (N = 2427) were included from the total population of the city of Oulu, Finland. Register data included LTSA spells, outpatient health care visits, inpatient care spells and rehabilitation spells, disability pensions (DP), employment dates, and demographic, socioeconomic and disability-related covariates. The study population was followed for one year before, and three years after the start of LTSA. Negative binomial regression models were utilized to examine covariate-adjusted use of the three service types and group differences. The use of outpatient health care peaked at the start of the LTSA spell, and adjusted for covariates, the height of the peak was similar regardless of post-LTSA labour market situation. Adjusted for covariates, those who transferred to permanent DP after an LTSA used more outpatient (predicted mean 4.87 for attendance days quarterly, 95% CI 4.36–5.38) and inpatient (predicted mean 84 days quarterly, 95% CI 0.62–1.06) health care than others during three years after the start of LTSA. Individuals not employed after an LTSA showed the highest and increasing level of rehabilitation use. The results indicate that Individuals returning to employment after an LTSA are provided with relatively high amount of early outpatient care, possibly aiding the return. For individuals not employed after an LTSA, rehabilitation is used quite frequently but rather late in the disability process. The frequent use of health care among future disability pensioners is consistent with their increasing health problems leading to retirement. long-term sickness absence health care rehabilitation employment disability pension labour market status socioeconomic determinants trajectories longitudinal ==== Body pmc1. Introduction In OECD countries, disability benefits, health care and rehabilitation services cause great public expenses [1,2]. Long sickness absence spells and a high frequency of health care use are also indicators of a risk for permanent disability [3,4,5,6,7] and societal expenses. Thus, in the literature, research shows that sickness absences and a higher frequency of health care use have often been studied as risk outcomes themselves [8,9,10,11,12,13,14,15,16,17]. The association between long-term sickness absence (LTSA) and health care use has been examined as well, both internationally and in a Finnish context. More frequent health care use is associated with more frequent and longer sickness absence spells later [7,12,18,19,20]. Vice versa, longer sick leaves and disability pensions (DP) are associated with increased health care use [14,17,21,22]. However, studies are scarce concerning the temporal associations between LTSA and health care use. Similarly, studies on the temporal associations between LTSA and rehabilitation actions are lacking, although early vocational or medical rehabilitation are highlighted in Finnish policies. In the Nordic countries, multidisciplinary and vocational rehabilitation have shown modest effectiveness on return to work, inter alia [23,24], and that rehabilitation in the early stages of sickness absence may be important for recovery [25]. In Finland, studies on the timing of rehabilitation in Finland have shown that the amount of early vocational rehabilitation can be insufficient both for future disability pensioners [26,27] and rejected DP applicants [28,29]. More longitudinal studies are needed in order to know how disability benefits, health care and rehabilitation services together succeed in supporting work ability and resumption of employment after disability. It is not understood how health care use develops before and during an LTSA spell or how rehabilitation is timed in relation to LTSA, nor is it well known how the use of health care or rehabilitation varies according to the labour market outcome of the LTSA spell. Do those who return to employment, those who do not and those who end up on disability pension have distinctive health care or rehabilitation use trajectories? Is the labour market outcome of the LTSA spell associated with health care use or rehabilitation use levels when the roles of LTSA duration, LTSA diagnosis, or demographic, socioeconomic and disease-related covariates [8,9,10,11,12,13,14,15,16,17,30,31,32] are examined as well? Following health care and rehabilitation use before occupational disability can reveal distinctive profiles for groups with differing labour market outcomes of sickness absence. It may also identify groups in risk of permanent disability or marginalization (i.e., those with lowered work ability outside employment). Only a few studies have examined changes in health care use in relation to disability benefits. Perhoniemi and Blomgren [30] showed a high level of outpatient health care use both before and during LTSA for individuals with a statutory maximum length of LTSA. The use of health care has been also shown to decrease but remain high after a disability pension transition [33,34,35]. Still, register-based follow-up studies examining how the use of health services and rehabilitation develop before LTSA and as LTSA progresses in particular are still lacking. When examining the level of health care and rehabilitation use in relation to LTSA, it is necessary to account not only for the chronic diseases of the individual and the duration of the LTSA spells, but also for the LTSA diagnosis, as it can affect service use frequency [19,22]. The objective of this study is to follow three central service schemes for supporting occupational ability—outpatient health care, inpatient care and rehabilitation—before and during an LTSA spell at least 30 days long. In addition, this study compares the use of the three service types between groups defined by employment and disability pension (DP) transition after an LTSA, taking demographic, socioeconomic and chronic disability-related covariates into account. 2. Materials and Methods 2.1. Study Population Register-based data were collected from several registers for the years 2014–2018 for the total population of the city of Oulu, situated in Northern Finland [36]. With a population of 209,197 inhabitants in 2021, Oulu is the fifth largest city of Finland. Oulu does not differ in any systematic way from Finland as a whole on various demographic, socioeconomic or health care-related indicators [36]. Data on residency, demographics, socioeconomic status and LTSA spells were retrieved from registers of the Social Insurance Institution of Finland (Kela, Helsinki, Finland). Residents of Oulu who were 18–58 years old, not on a pension or a student at the start of 2015, were first included in the data (N = 73,766). The age limits were set so that all the subjects would be of adult age and would not reach the lowest limit of old-age pension in Finland (63 years) during the follow-up. Those receiving a pension were excluded, as pensioners are not entitled to sickness allowance. Students were excluded as our data on outpatient health care lacked information on student health care. Then, persons who started an LTSA spell lasting at least 30 days during 2015 but had no previous LTSAs during 12 months prior to the spell were finally included in the study (N = 2427). A flowchart of the whole inclusion/exclusion process of study subjects is presented in Supplementary Materials (Figure S1). 2.2. Long-Term Sickness Absence (LTSA) and Disability Pension Long-term sickness absence (LTSA) was measured through compensated sickness allowance days. Kela can pay sickness allowance to non-retired persons aged 16–67 as compensation for loss of income due to sickness or impairment. The allowance can be paid, when the sickness absence exceeds 10 working days, covered by the employer. A physician’s sickness certificate is needed for the allowance. Based on a certain diagnosis, the allowance can generally be paid for one year during two years’ time. Register data on sickness allowance spells were derived from Kela, including the start and end dates and diagnoses of LTSA spells. LTSA spells ≥ 30 days were studied, as longer sickness absences both signal a need for care or rehabilitation and are more significant risks for permanent disability [5,37]. A disability pension may be considered after the statutory maximum period of LTSA. Data on permanent disability pensions 2015–2018 was derived from registers of Kela and the Finnish Center for Pensions, including the start dates of DP. 2.3. The Follow-Up Setting The start of the first LTSA spell in 2015 was set as baseline. The study population was followed for four years in total: 4 three-month periods (one year in all) before and 12 three-month periods (3 years in all) after the start of the LTSA spell. The three-year follow-up from baseline was chosen, since the third year after the start of LTSA is often a period for gaining disability pension, or returning to work, if the LTSA spell reaches its maximum length (see above). The visit to obtain a sickness certificate from a physician (first day of illness), needed for the sickness allowance, was included in the first follow-up period. 2.4. Grouping Based on Employment and Disability Pension Transition after an LTSA The study population was divided into four groups based on employment and disability pension grants during the last 12 months of the follow-up. This third follow-up year is timed after an LTSA for all subjects, as two years has passed since the start of the LTSA, and sickness allowance can be received maximally over two years’ time (see above). Employment spells for 2015–2018 were retrieved from registers of the Finnish Centre for Pensions. Group 1 (N = 189) transferred to disability pension (DP) after the ≥30-day LTSA and by the end of the follow-up. Group 2 (N = 1639) were mostly employed after an LTSA—at least half of the last 12 follow-up months. Group 3 (N = 169) had some employment, at least 30 calendar days, but less than half of the last 12 months. Group 4 (N = 430) were not employed after an LTSA. This group had fewer than 30 employment days during the last 12 follow-up months. These LTSA groups are also presented in Supplementary Materials (Table S1). 2.5. Data on Outpatient and Inpatient Health Care and Rehabilitation Data on the use of outpatient health care was collected for the years 2014–2018 covering all schemes of the Finnish service system (public, occupational, private). Data on public health care use was provided by the municipality of Oulu and the Care Register for Health Care [38]. The data on public care included visits to municipal health centres and outpatient visits to hospital-based specialized care. Data on occupational health service (OHS) visits were gathered from the four largest OHS providers in Oulu (Terveystalo, Mehiläinen, Attendo and Työterveys Virta), estimated to cover around 92% of employee clients entitled to OHS in Oulu [39]. Finally, data on private outpatient care visits were retrieved from the reimbursement registers of Kela. In Finland, public outpatient primary health care is offered for all residents of municipalities in health centres. For the working population, however, OHSs are the main provider of primary care; all employees are entitled to preventive care, provided by the employer, and employers frequently also provide primary care through OHS [40]. Private health care is state-supported via partial reimbursement. The reimbursement varies, but is around one seventh for a general practitioner consultation. The role of the private scheme is growing but still rather small, due to the strong and affordable public and OHS schemes. Both public and private schemes, and to a small extent OHS, provide outpatient specialized care. Face-to-face visits, phone calls and virtual consultations were included as they are active visits to health care professionals. Dental care and laboratory visits were excluded to harmonize the data between the service schemes. The number of outpatient visits was approximated by counting separate attendance days with each provider, as separate visits with the same date were inconsistent in the different register holders’ data. Then, the total number of attendance days was calculated for each subject, and for each three-month period. Data on inpatient care were obtained from the Care Register for Health Care. The inpatient care periods included both hospitalization and inpatient care in public health centres. The total number of days in inpatient care for each three-month period was calculated for each subject. Rehabilitation periods were studied using data of rehabilitation benefit spells from the registers of Kela and the Finnish Centre for Pensions. The benefit’s intended use is to secure income during vocational or medical rehabilitation. The total number of days in rehabilitation for each three-month period was calculated for each subject. 2.6. Covariates Sex, age, marital status, socioeconomic status and entitlement to reimbursements for medicine expenses in 2014 were retrieved from registers of Kela. Unemployment benefit spells were retrieved for 2014 and 2015 from registers of Finnish Centre for Pensions. The study population was classified into four age groups (see Table 1). Marital status was categorized as married, unmarried, and divorced, separated or widowed. Socioeconomic status was measured in terms of occupational class. Occupational class distinguished between upper and lower non-manual employees, manual workers, entrepreneurs, and others following the classification of Statistics Finland [41]. The occupational class “others” included the long-term unemployed and persons without a statistical classification. Labour market status at the start of the LTSA was defined as employed, unemployed (on unemployment benefit) or other. Entitlement to reimbursements for medicine expenses was used as a proxy measure for chronic or severe disease [42]. These entitlements are ensured through National Health Insurance and guarantee the recipients’ access to medicines needed for the treatment of certain long-term diseases at a reasonable cost. A division between no diseases, one disease, and multiple chronic diseases (entitlements) was used. The total length of LTSA during the follow-up was counted and classified into ‘under two months’, ‘two months to eleven months’, and ‘maximum length. The study population was classified according to the diagnosis group of their first LTSA spell. This was carried out according to the International Statistical Classification of Diseases and Related Health Problems [43]. Diagnosis groups were mental disorders (‘mental LTSA’), musculoskeletal diseases (‘musculoskeletal LTSA’), and other diagnoses for LTSA. 2.7. Statistical Methods The average, unadjusted number of outpatient health care visits, number of days in inpatient care, and the number of days in rehabilitation for each of the 4 three-month periods before and for each of the 12 three-month periods after the start of LTSA were first calculated. Covariate-adjusted estimates for the use of these three services for each period were then calculated using negative binomial regression models. This method is suitable for count data with a right-skewed distribution [44]. Finally, the association of the LTSA groups and covariates with the level of use for each service type during the three years after the start of the LTSA spell were analysed with negative binomial regression models. For these models, incidence rate ratios (IRRs) and predicted means with their 95 % confidence intervals are presented. The analyses were conducted using Stata statistical software package version 14.1 [45]. 3. Results 3.1. Characteristics of the LTSA Groups There were clear differences in the distributions of the covariates between the four LTSA groups (Table 1). Compared to others, persons in group 1 (transfer to DP after an LTSA) were on average older, had more chronic or severe diseases, and more often reached the statutory maximum period of LTSA during the follow-up. Persons in group 2 (mostly employed after an LTSA) were more often 31–50 years old, married, non-manual employees, and employed at the start of LTSA, than other groups. Persons in group 3 (some employment after an LTSA) were more often 18–30 years old than other groups, often unmarried, and had quite a similar socioeconomic profile to group 1. Persons in groups 2 and 3 were more often females and had a shorter total amount of LTSA than persons in other groups. Finally, those in group 4 (not employed after an LTSA) were often unmarried, unemployed at the start of LTSA, and had an LTSA based on a mental disorder more often than other groups. 3.2. Unadjusted Averages for Outpatient Health Care, Inpatient Care and Rehabilitation Use Figure 1 presents the unadjusted averages for the number of outpatient health care visits, days in inpatient care and days in rehabilitation during each three-month period of the follow-up. Outpatient health care visits (Figure 1a) started to increase 4 to 6 months before the start of the LTSA spell that was set as baseline. The number of visits peaked when the LTSA spell started. That peak was slightly higher for group 1 (mean 9.4 visits in three months) than others. After that the level of outpatient health care use decreased gradually for groups 1 and 4, and rapidly for groups 2 and 3. Group differences in the level of use remained stable over the three years after the start of the LTSA spell. Group 1 had the most outpatient care visits on average, whereas groups 2 and 3 had the least. For average inpatient care days (Figure 1b), there was a similar peak in the three-month period beginning from the start of the LTSA spell, and the number of days in that period was highest in group 1 (mean 6.6 days). For all LTSA groups, the days in inpatient care then decreased rapidly, but for group 1 the level remained higher compared to others until around 1.5 years (months 16 to 18) after the start of LTSA. For rehabilitation days (Figure 1c), the group trajectories were less consistent over time, with variation between the time periods. Before LTSA and well into the LTSA spell there were no clear LTSA group differences. A year after the start of the LTSA spell (months 13 to 15) the average rehabilitation days started increasing for group 4, and continued to increase almost to the end of the follow-up. For group 1, average rehabilitation days decreased 12 months after the start of LTSA on, and were on average near to zero around months 22–24. For group 2, the amount of rehabilitation days was relatively low and stable. Group 3 showed a somewhat similar but lower peak after an LTSA than group 4. Adjusting for covariates between LTSA groups in each time period narrowed the LTSA group differences for all three service types (predicted means in Figure 2), and the differences proved mostly statistically non-significant (see confidence intervals). The early peak in the outpatient care use proved the same in size between the LTSA groups. The average level of outpatient health care use (Figure 2a) was higher for group 1 than group 2 in months 7 to 33. After adjusting for covariates, the visibly higher level of rehabilitation use for group 4 proved statistically non-significant (Figure 2c), with broad confidence intervals indicating large variation within group 4. Finally, the number of rehabilitation days was higher for group 2 than group 1 from month 22 onwards, reflecting the near-zero average among those transferring to DP. 3.3. The Association of LTSA Groups with Service Use after the Start of the LTSA Spell The association of LTSA groups and covariates with the average number of outpatient health care visits, days in inpatient care and days in rehabilitation were examined for the whole three-year period after the start of LTSA. This was carried out since Figure 1 and Figure 2 showed LTSA group differences only for the time following the start of LTSA. Predictor variables were entered to the negative binomial regression models in three blocks. Model 1 included LTSA groups with the sex and age group as covariates. Model 2 added marital status, occupational class, and labour market status at the start of LTSA as covariates. Fully adjusted model 3 further added the number of chronic or severe diseases, LTSA length and LTSA diagnosis group as covariates. Predicted means with their 95% confidence intervals for the LTSA groups are presented in Table 2. Comprehensive results for the estimates of both LTSA groups and covariates (including incident rate ratios (IRRs)) are presented in Supplementary Materials (Tables S2–S4). In all nine models, the negative binomial models fitted the outcome distribution better compared to Poisson regression models (dispersion parameter alpha not equal to zero). For outpatient health care visits, model 1, adjusted for sex and age, showed on average more visits for group 1, compared to other LTSA groups (predicted mean 7.6 visits). Group 4 also had more visits on average than groups 2 and 3. Adding marital status and the two socioeconomic covariates (model 2) did not change these statistically significant LTSA group differences. However, adding the disease-related covariates in model 3 changed the LTSA group differences: the level of health care use was higher for group 1 than groups 2 and 3, but no longer higher than group 4. In model 1 for inpatient care in days, group 1 had, on average, more inpatient care days (predicted mean 2.0 days) than other LTSA groups, while group 2 had fewer days (predicted mean 0.3 days) than other groups. In model 2, the difference between groups 2 and 3 proved statistically non-significant. The fully adjusted model 3 further narrowed the LTSA group differences considerably. In model 3, only group 1 with more inpatient care days differed from other groups in a statistically significant way—other groups did not differ from each other. Finally, in model 1 for the rehabilitation days, group 4 had, on average, more rehabilitation days (predicted mean 4.4 days) than group 2. In model 2, group 4 differed from both groups 1 and 2 with a higher amount of rehabilitation days. These LTSA group differences remained in the fully adjusted model 3. The effects of covariates on the use of the three services varied (see Supplementary Materials). The number of chronic or severe diseases and LTSA length were strongly associated with the use of all three services, and especially with the number of rehabilitation days. Mental LTSA was associated with most outpatient care visits. In fully adjusted models, the youngest age group had the most inpatient care and rehabilitation days (see IRRs). Furthermore, in fully adjusted models, entrepreneurs had fewer outpatient care visits than others. Upper non-manual employees had fewer outpatient health care visits than lower non-manual employees, and fewer rehabilitation days than manual employees. 4. Discussion The aim of this study was to understand how the use of outpatient and inpatient health care and rehabilitation develop one year before and three years after the start of long-term sickness absence (LTSA), and how the use of the three service types depends on the labour market situation after the LTSA in terms of disability pension and employment. We utilized extensive register data for non-pensioned, working age residents of Oulu, a city in Finland, with a ≥30-day LTSA spell in 2015 (N = 2427). 4.1. Outpatient and Inpatient Health Care Outpatient health care visits and inpatient care days showed a relatively similar temporal pattern. Regardless of the labour market outcome of the LTSA, the level of service use peaked when the LTSA started. After that, the use gradually decreased until the end of the follow-up. Persons who were mostly, or to some extent, employed during the year after an LTSA had approximately the same number of outpatient care visits as future disability pensioners and persons not returning to employment at the start of the LTSA, but had a low outpatient use level from that point onward. This early peak in health care use may be due to their access to occupational health services (OHS), since over 90% of this group was employed already at the start of the LTSA. It is widely recognized that those with access to OHS in Finland receive better and faster care [46]. In addition, a better socioeconomic position removes financial barriers, and enables access to quality care (e.g., private care) [47,48,49]. Interestingly, adjusting for covariates, this early peak remained the same relative to other LTSA groups, indicating that the peak may reflect sufficient early care aiding the return to work. The rapidly decreasing and low average outpatient care use after that peak reflects fast recovery and short LTSA spells in these groups, most likely related to milder health conditions and working conditions that enable early return to work. In addition, a covariate-adjusted analysis showed that persons employed after an LTSA used outpatient health care on average less frequently during the three-year period after the start of LTSA compared to persons transferring to DP. Unadjusted results showed that persons who transferred to DP after an LTSA had the highest peak level at the start of LTSA in both outpatient and inpatient health care use. Additionally, when examining the whole three-year period from the start of LTSA and adjusting for covariates, persons who transferred to DP showed higher average levels of outpatient and inpatient health care use than the non-retiring LTSA groups. If outpatient and inpatient health care signal ill health, these results indicate that persons with disabling health problems are successfully identified by health care and pension systems. Studies on health symptom trajectories [50] and the psychotropic drug consumption [51,52] of retirees have shown a steep rise in the disability indicators before the pension grant, and a steady long decline after the pension grant. In this study, however, the decline started soon after the start of LTSA. For outpatient health care, this is partly due to the fact that certification from a physician is needed for the sickness allowance, and this is demonstrated by a peak in the number of visits. More generally, a higher level of health care use for future DP retirees may reflect a good standard of care. Those who are to transfer to DP possibly benefit from a more thorough attempt to improve their functional capacity during LTSA. A greater number of outpatient health care visits may also mean more accurate documentation of occupational disability, increasing chances for a disability pension award. These interpretations are not mutually exclusive and can thus all play a role in the results. Adjusting for covariates mostly removed the LTSA group differences for the three-month interval measures and narrowed LTSA group differences when examining average service use during the three years after the start of LTSA. This shows that much of the differences in LTSA group levels were due to differences in demographic, socioeconomic, or disability-related background. For instance, those transferring to DP were older than other LTSA groups, and older age was associated with more frequent health care use in general [7,19]. Similarly, the differences between persons employed and persons not employed after an LTSA were narrower in the adjusted results, since a lower socioeconomic status is associated with very frequent health care use in general [15,16,17]. 4.2. Rehabilitation For rehabilitation use, the trajectories were different from those concerning health care. The trajectories were also quite different between the LTSA groups as there were no clear simultaneous peaks in the service use. Instead, for individuals not employed after an LTSA, the average rehabilitation days started increasing approximately one year after the start of LTSA. The increase continued almost to the end of the follow-up, i.e., after the LTSA. Half of this group was unemployed already at the start of their LTSA. The unemployed do not have access to occupational health services who specialize in occupational ability. It is known that slower care, ref. [46] less frequent care and poorer documentation of the condition due to lack of access to OHS may lead to both over-representation of unemployed persons among the DP applicants but under-representation among those who are granted the pension [53]. Further, there is a greater risk of marginalization among those unemployed if work ability is not regained after an LTSA [54]. However, our results indicate that the lack of access to quality care does not mean lesser access to rehabilitation. The unemployed do receive rehabilitation relatively often, but rather late in the process. A risk for prolonged and late rehabilitation among persons with a lower socioeconomic position has also been shown by Madsen [32]. The higher frequency of rehabilitation naturally signals not only access to, but the need for, rehabilitation. Individuals with a lower educational level or socioeconomic status tend to have poorer health [55,56] and are over-presented in rehabilitation activities in general [31,32]. Here, persons not employed after an LTSA had more than the average number of rehabilitation days after the start of LTSA even when all covariates, including chronic morbidity, were adjusted for. Persons with some employment after an LTSA showed a somewhat similar but a weaker peak in rehabilitation use after an LTSA, presumably for the same reasons as persons not employed. Among individuals who later transferred to DP—even if this group had the most health care, and supposedly had the most limiting medical conditions—there were, interestingly, only relatively few rehabilitation days during the year prior to an LTSA or the 12 months after the start of LTSA. Possibly a part of the conditions causing DP are very difficult to rehabilitate, and this is understood by pension insurers and other rehabilitation actors already when the rehabilitation chances are evaluated during an LTSA. Those with fewer work-years ahead of them and a medical condition requiring more effort may have less motivation for rehabilitation as well, reducing rehabilitative actions [57]. On the other hand, directing clients to at least occupational rehabilitation may be insufficient, as register- and document-based studies on disability pensioners in Finland have shown [26,27]. In Finland, those in rehabilitation have often experienced that the rehabilitation is provided too late, and this experience has been shown to be associated with a lower probability of returning to employment [58]. In our study, rehabilitation days decreased further during the follow-up, as this group started to transfer to DP. Individuals mostly employed after an LTSA had a steady low level of rehabilitation, a result echoing those concerning health care use. For those returning to work, the disabling medical conditions are deemed to be less severe and chronic, requiring care or rehabilitation less frequently compared to other individuals on LTSA. 4.3. Strengths and Limitations Our study population was based on register data of the total working-age population of the city of Oulu, Finland. We were able to utilize register data on date-level health care and rehabilitation use, LTSA spells, disability pensioning, and covariates. Especially, the rarely used register data on health care, based on comprehensive registers and covering all schemes relevant to the Finnish working-age population, strengthens the validity of our study. Registers are deemed to be highly reliable and objective, with no self-report bias and no loss to follow-up. However, a limitation is the restriction of our study population to residents of one city, and to individuals with no LTSA or pensions in the previous year. This of course warrants caution in generalizing the results to the whole working-age population that experience LTSA in Finland or to other countries. Internationally, the results are probably best generalizable to countries with roughly similar benefit and health care systems, for example, the Nordic countries. Similar international studies are needed to show whether the findings are generalizable to other systems and contexts. A second limitation is the setting, not enabling us to gain insight into the actual consequences of the three service types, let alone the causality between the services and the outcome of the LTSA spell. A further limitation is the criteria behind our LTSA grouping. We opted for dividing non-retiring subjects based on the primary employment status during the last follow-up year, rather than actual labour market transitions. This was due to the modest size of the study population. Finally, considering the group not employed after an LTSA, the follow-up years were clearly insufficient to show the role of rehabilitation as the rehabilitation frequency peaked in the last 1.5 years for this group. Therefore, we could not detect the possible labour market consequences of the rehabilitation for this group. As positive labour market transitions after sickness absence may often require time, longer follow-up settings in general would benefit future studies. Similarly, longer timelines concerning pre-LTSA health care or rehabilitation use could be beneficial in identifying early risk factors for disability. 4.4. Practical Implications Our results indicate that those not employed after an LTSA receive rehabilitation relatively often, but rather late in the disability process. Providing those outside employment preventive outpatient care—that is, equally quickly and with a clinician who has equal expertise on occupational ability issues as in OHS—may decrease the need for rehabilitation for some clients and advance direction to early rehabilitation for others. Legislative and administrative reforms could aid the group-specific challenges implied by our study. In addition to providing equal care for the unemployed, such improvements could be bringing down the waiting times in non-urgent public care, and directing those with lowered occupational ability to rehabilitation measures earlier in the process. In Finland, the government has made a proposal for care guarantee legislation for bringing down the maximum waiting times in non-urgent public care [59], possibly increasing preventive care for socioeconomic groups mainly using public health services. Those transferring to disability pension after an LTSA had relatively low frequency of rehabilitation even if health care use was frequent. It is possible that part of the pensions could be avoided by better direction to rehabilitation, as indicated by earlier studies [26,27,58]. 5. Conclusions Studying outpatient and inpatient health care and rehabilitation use one year before and three years after the start of long-term sickness absence, there were group difference based on the post-LTSA labour market situation: those who returned to employment after an LTSA seemed to have been provided with instant outpatient care for disability, aiding their return. For those not returning to employment after an LTSA, rehabilitation was used rather late in the disability process. For future disability pensioners, on the other hand, the high use of outpatient and inpatient health care was consistent with their increasing health problems leading to retirement. However, those who ended up on a disability pension were relatively rarely in rehabilitation before the pension. Legislative and administrative reforms could aid the group-specific challenges implied by our study. Such improvements could provide equal care for the unemployed, reducing waiting times in non-urgent public care and directing those with lowered occupational ability to rehabilitation measures earlier in the process. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19094990/s1, Figure S1: Flowchart of subjects who met inclusion criteria; Table S1: The LTSA groups; Table S2: The LTSA groups and covariates associated with the expected number of outpatient health care visits after the start of LTSA in negative binomial regression analysis models (Incident rate ratios [IRR], predicted means and 95% confidence intervals [CI]). Group 1 as the reference group; Table S3: The LTSA groups and covariates associated with the expected number of days in inpatient care after the start of LTSA in negative binomial regression analysis models (Incident rate ratios [IRR], predicted means and 95% confidence intervals [CI]). Group 1 as the reference group; Table S4: The LTSA groups and covariates associated with the expected number of days in rehabilitation after the start of LTSA in negative binomial regression analysis models (Incident rate ratios [IRR], predicted means and 95% confidence intervals [CI]). Group 1 as the reference group. Click here for additional data file. Author Contributions R.P. and J.B. contributed to the planning and conducting the study. R.P. wrote first and successive drafts of the manuscript and conducted the statistical analyses. J.B. contributed to writing and revising the manuscript, and advised on statistical modelling. All authors have read and agreed to the published version of the manuscript. Funding This study was funded by the Social Insurance Institution of Finland (Kela). Institutional Review Board Statement Ethical review and approval were waived for this study, as the study used only secondary administrative data retrieved from registers and no human subjects were contacted to collect the data. Thus, no ethics approval was required according to Finnish law and practices [60]. Informed Consent Statement Patient consent was waived because the study utilized administrative register data that can be used without informed consent in scientific research. Data Availability Statement Data cannot be shared publicly because strict restrictions apply to the availability of confidential individual-level register data. These analyses were conducted with permissions from third-party data holders for the current study. Permissions to obtain register data from the City of Oulu, from the Social Insurance Institution of Finland (Kela), from Finnish Centre for Pensions and from the occupational health care providers may be applied for scientific research purposes from the Finnish Health and Social Data Permit Authority Findata (https://www.findata.fi/en/, accessed on 1 March 2022). A license to obtain register data from Statistics Finland may be applied for separately (https://www.tilastokeskus.fi/meta/tietosuoja/kayttolupa_en.html, accessed on 1 March 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 The use of three service types in the four LTSA groups. (a) Number of outpatient health care visits; (b) number of days in inpatient care; (c) number of days in rehabilitation. Figure 2 Covariate-adjusted * use of three service types in the four LTSA groups (predicted means and 95% confidence intervals). (a) Number of outpatient health care visits; (b) number of days in inpatient care; (c) number of days in rehabilitation. Note: * Sex, age group, marital status, occupational class, labour market status at the start of LTSA, chronic or severe diseases, LTSA length, and LTSA diagnosis group. ijerph-19-04990-t001_Table 1 Table 1 The covariates in the study population and by LTSA group. All Group 1—Transfer to DP after LTSA Group 2—Mostly Employed after LTSA Group 3—Some Employment after LTSA Group 4—Not Employed after LTSA N = 2427 N = 189 N = 1639 N = 169 N = 430 % % % % % Sex Male 42.3 50.8 40.4 43.8 45.1 Female 57.7 49.2 59.6 56.2 54.9 Age group 18–30 20.2 2.1 16.8 39.6 33.3 31–40 24.2 4.2 27.0 21.9 23.3 41–50 27.0 17.5 30.1 17.8 23.3 51–58 28.6 76.2 26.1 20.7 20.2 Marital status Married 46.2 44.4 51.9 37.9 28.8 Unmarried 36.6 28.6 32.5 49.7 50.9 Divorced/separated/ widowed 17.1 27.0 15.7 12.4 20.2 Occupational class Upper non-manual employee 15.6 7.9 19.8 10.7 5.1 Lower non-manual employee 34.2 23.3 41.5 28.4 13.7 Manual worker 22.9 24.3 24.8 24.3 14.7 Entrepreneur 5.3 5.8 5.1 4.7 6.1 Other 21.9 38.6 8.9 32.0 60.5 Labour market status at the start of LTSA Employed 77.3 61.4 91.7 66.3 33.3 Unemployed 17.2 33.9 6.4 21.3 49.3 Other 5.6 4.8 17.9 12.4 17.4 Chronic or severe diseases No diseases 72.4 44.4 75.4 75.7 72.1 One disease 19.3 33.9 17.9 18.9 18.4 Multiple diseases 8.3 21.7 6.8 5.3 9.5 LTSA length Under 2 months 31.1 2.1 38.6 31.4 15.1 Two months to 11 months 48.5 28.6 53.8 53.3 34.9 Maximum length (one year) 20.4 69.3 7.6 15.4 50.0 LTSA diagnosis group Mental LTSA 20.8 14.3 15.8 26.6 40.2 Musculoskeletal LTSA 26.6 32.3 27.7 23.1 21.2 Other diagnosis LTSA 52.7 54.4 56.5 50.3 38.6 All 100.0 100.0 100.0 100.0 100.0 ijerph-19-04990-t002_Table 2 Table 2 Negative binomial regression analysis models. The LTSA groups’ expected number of outpatient health care visits, days in inpatient care and days in rehabilitation after the start of LTSA in (predicted means and 95% confidence intervals). M1 M2 M3 Predicted Means 95% CI Predicted Means 95% CI Predicted Means 95% CI The Expected Number of Outpatient Health Care Visits G1—Transfer to DP after an LTSA 7.56 6.75–8.36 7.43 6.62–8.23 4.87 4.36–5.38 G2—Mostly employed after an LTSA 3.65 3.51–3.79 3.66 3.51–3.81 3.79 3.65–3.94 G3—Some employment after an LTSA 3.96 3.49–4.43 3.94 3.47–4.40 3.69 3.28–4.10 G4—Not employed after an LTSA 5.57 5.18–5.97 5.51 5.06–5.96 4.22 3.89–4.55 The Expected Number of Days in Inpatient Care G1—Transfer to DP after an LTSA 1.95 1.47–2.43 1.79 1.34–2.23 0.84 0.62–1.06 G2—Mostly employed after an LTSA 0.31 0.28–0.35 0.32 0.28–0.36 0.29 0.26–0.33 G3—Some employment after an LTSA 0.52 0.36–0.68 0.49 0.34–0.63 0.40 0.28–0.52 G4—Not employed after an LTSA 0.77 0.63–0.90 0.62 0.50–0.75 0.42 0.33–0.51 The Expected Number of Days in Rehabilitation G1—Transfer to DP after an LTSA 1.59 0.46–2.73 1.08 0.30–1.87 0.40 0.12–0.68 G2—Mostly employed after an LTSA 1.11 0.86–1.36 1.06 0.82–1.30 0.76 0.60–0.93 G3—Some employment after an LTSA 2.72 0.82–4.63 2.41 0.65–4.17 1.29 0.37–2.21 G4—Not employed after an LTSA 4.42 2.42–6.40 4.08 2.21–5.59 2.22 1.28–3.16 M1: Adjusted for sex, age group. M2: Adjusted for sex, age group, marital status, occupational class, labour market status at the start of LTSA. M3: Adjusted for sex, age group, marital status, occupational class, labour market status at the start of LTSA, chronic diseases, LTSA length, LTSA diagnosis group (fully adjusted model). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. OECD Sickness, Disability and Work: Breaking the Barriers—A Synthesis of Findings across OECD Countries OECD Paris, France 2010 2. OECD Public Spending on Incapacity 2020 Available online: https://data.oecd.org/socialexp/public-spending-on-incapacity.htm#indicator-chart (accessed on 1 July 2021) 3. Kivimäki M. Ferrie J. Hagberg J. Head J. Westerlund H. Vahtera J. Alexanderson. Diagnosis-specific sick leave as a risk marker for disability pension in a Swedish population J. Epidemiol. Community Health 2007 61 915 920 10.1136/jech.2006.055426 17873230 4. Alexanderson K. Kivimäki M. Ferrie J.E. Westerlund H. Vahtera J. Singh-Manoux A. Melchior M. Zins M. Goldberg M. Head J. Diagnosis-specific sick leave as a long-term predictor of disability pension: A 13-year follow-up of the GAZEL cohort study J. Epidemiol. Community Health 2012 66 155 159 10.1136/jech.2010.126789 22003081 5. Salonen L. Blomgren J. Laaksonen M. Niemelä M. Sickness absence as a predictor of disability retirement in different occupational classes: A register-based study of a working-age cohort in Finland in 2007–2014 BMJ Open 2018 8 e020491 10.1136/bmjopen-2017-020491 29743328 6. Mittendorfer-Rutz E. Härkänen T. Tiihonen J. Haukka J. Association of Socio-Demographic Factors, Sick-Leave and Health Care Patterns with the Risk of Being Granted a Disability Pension among Psychiatric Outpatients with Depression PLoS ONE 2014 9 e99869 10.1371/journal.pone.0099869 24963812 7. Perhoniemi R. Blomgren J. Frequent attenders of three outpatient health care schemes in Finland: Characteristics and association with long-term sickness absences, 2016–2018 BMC Public Health 2021 21 870 10.1186/s12889-021-10866-x 33957897 8. Laaksonen M. Mastekaasa A. Martikainen P. Rahkonen O. Piha K. Lahelma E. Gender differences in sickness absence—The contribution of occupation and workplace Scand. J. Work Environ. Health 2010 36 394 403 10.5271/sjweh.2909 20213051 9. Löve J. Hensing G. Holmgren K. Torén K. Explaining the social gradient in sickness absence: A study of a general working population in Sweden BMC Public Health 2013 13 545 10.1186/1471-2458-13-545 23738703 10. Beemsterboer W. Stewart R. Groothoff J. Nijhuis F. A literature review on sick leave determinants (1984–2004) Int. J. Occup. Med. Environ. Health 2009 22 169 179 10.2478/v10001-009-0013-8 19617195 11. Blomgren J. Jäppinen S. Incidence and Length of Sickness Absence among Hierarchical Occupational Classes and Non-Wage-Earners: A Register Study of 1.6 Million Finns Int. J. Environ. Res. Public. Health 2021 18 501 10.3390/ijerph18020501 12. Bergh H. Baigia A. Månsson J. Mattsson B. Marklund B. Predictive factors for long-term sick leave and disability pension among frequent and normal attenders in primary health care over 5 years Public Health 2007 121 25 33 10.1016/j.puhe.2006.08.018 17166531 13. Foster A. Jordan K. Croft P. Is frequent attendance in primary care disease-specific? Fam. Pract. 2006 23 444 452 10.1093/fampra/cml019 16675502 14. Karlsson H. Lehtinen V. Joukamaa M. Frequent attenders of Finnish public primary health care: Sociodemographic characteristics and physical morbidity Fam. Pract. 1994 11 424 430 10.1093/fampra/11.4.424 7895972 15. Pymont C. Butterworth P. Longitudinal cohort study describing persistent frequent attenders in Australian primary healthcare BMJ Open 2015 5 e008975 10.1136/bmjopen-2015-008975 16. Sumanen H. Harkko J. Piha K. Pietiläinen O. Rahkonen O. Kouvonen A. Association between socioeconomic position and occupational health service use trajectories among young municipal employees in Finland BMJ Open 2019 9 e028742 10.1136/bmjopen-2018-028742 31780585 17. Vedsted P. Olesen F. Social environment and frequent attendance in Danish general practice Br. J. Gen. Pract. 2005 55 510 515 16004735 18. Ropponen A. Gémes K. Frumento P. Almondo G. Bottai M. Friberg E. Alexanderson K. Predicting the duration of sickness absence spells due to back pain: A population-based study from Sweden Occup. Environ. Med. 2020 77 115 121 10.1136/oemed-2019-106129 31822514 19. Reho T. Atkins S. Talola N. Sumanen M. Viljamaa M. Uitti J. Occasional and persistent frequent attenders and sickness absences in occupational health primary care: A longitudinal study in Finland BMJ Open 2019 9 e024980 10.1136/bmjopen-2018-024980 20. Harkko J. Sumanen H. Pietiläinen O. Piha K. Mänty M. Lallukka T. Rahkonen O. Kouvonen A. Socioeconomic Differences in Occupational Health Service Use and Sickness Absence Due to Mental Disorders: A Register-Based Retrospective Cohort Study Int. J. Environ. Res. Public Health 2020 17 e2064 10.3390/ijerph17062064 32244960 21. Al-Windi A. Elmfeldt D. Svärdsudd K. The influence of sociodemographic characteristics on health care use in a Swedish municipality Upps. J. Med. Sci. 2004 109 33 42 10.3109/2000-1967-108 15124951 22. Jyväsjärvi S. Keinänen-Kiukaanniemi S. Väisänen E. Larivaara P. Kivelä S. Frequent attenders in a Finnish health centre: Morbidity and reasons for encounter Scand. J. Prim. Health Care 1998 16 141 148 9800226 23. Norlund A. Ropponen A. Alexanderson K. Multidisciplinary interventions: Review of studies of return to work after rehabilitation for low back pain J. Rehabil. Med. 2009 41 115 121 10.2340/16501977-0297 19229442 24. Leinonen T. Viikari-Juntura E. Husgafvel-Pursiainen K. Juvonen-Posti P. Laaksonen M. Solovieva S. The effectiveness of vocational rehabilitation on work participation: A propensity score matched analysis using nationwide register data Scand. J. Work Environ. Health. 2019 45 651 660 10.5271/sjweh.3823 30977515 25. Waddell G. Burton K. Kendall N. Vocational Rehabilitation: What Works, for Whom, and When? TSO London, UK Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/209474/hwwb-vocational-rehabilitation.pdf (accessed on 14 January 2020) 26. Gould R. Laaksonen M. Kivekäs J. Ropponen T. Kettunen S. Hannu T. Käppi I. Ripatti P. Rokkanen T. Turtiainen S. Työkyvyttömyyseläkettä Edeltävät Vaiheet: Asiakirja-Aineistoon Perustuva Tutkimus [Phases Preceding Disability Pension—A Study of Documentation] Raportteja 6/2014 Eläketurvakeskus Helsinki, Finland 2014 (In Finnish, with English Abstract) 27. Laaksonen M. Blomgren J. Gould R. Työkyvyttömyyseläkkeelle siirtyneiden sairauspäiväraha-, kuntoutus- ja työttömyyshistoria. Rekisteripohjainen Tarkastelu [Sickness Absence, Rehabilitation and Unemployment History of Disability Retirees—A Register Study] Eläketurvakeskuksen raportteja 5/2014 Eläketurvakeskus Helsinki, Finland 2014 (In Finnish, with English Abstract) 28. Gould R. Nyman H. Työkyvyttömyyseläkepäätökset 2000–2011 [Disability Pension Decisions 2000–2011] Eläketurvakeskuksen Keskustelualoitteita 3/2012 Eläketurvakeskus Helsinki, Finland 2012 (In Finnish, with English Abstract) 29. Juopperi J. Lampi J. Työllisyys Ja Kuntoutus Ennen Työkyvyttömyyseläkepäätöstä [Employent and Rehabilitation before Disability Pension Decision] Eläketurvakeskuksen Keskustelualoitteita 01/2012 Eläketurvakeskus Helsinki, Finland 2012 (In Finnish, with English Abstract) 30. Perhoniemi R. Blomgren J. Outpatient health care use before and during a long-term sickness absence spell—A register-based follow-up study comparing health care use by the length of sickness absence and transition to disability pension in Finland BMJ Open 2022 12 e053948 10.1136/bmjopen-2021-053948 35217537 31. Laaksonen M. Rantala J. Liukko J. Polvinen A. Varis J. Kesälä M. Kuivalainen S. Individual-and company level determinants of vocational rehabilitation: A multilevel study Eur. J. Public Health 2019 29 (Suppl. S4) 498 499 10.1093/eurpub/ckz186.311 32. Madsen A. Return to work after first incidence of long-term sickness absence: A 10-year prospective follow-up study identifying labour-market trajectories using sequence analysis Scand. J. Public Health 2020 48 134 143 10.1177/1403494818821003 30973057 33. Højsted J. Albanb A. Hagildc K. Eriksens J. Use of health care system by chronic pain patients who applied for disability pensions Pain 1999 82 275 282 10.1016/S0304-3959(99)00055-X 10488678 34. Eden L. Ejlertsson G. Leden I. Health and health care use among early retirement pensioners with musculoskeletal disorders Scand. J. Prim. Health Care 1995 13 211 216 10.3109/02813439508996763 7481174 35. Wallman T. Burell G. Kullman S. Svärdsudd K. Health care use before and after retirement due to illness. A 13-year population-based follow-up study of prematurely retired men and referents from the general population Scand. J. Prim. Health Care 2004 22 95 100 10.1080/02813430410005126 15255489 36. Blomgren J. Jäppinen S. Sosiaali- Ja Terveyspalveluiden Ja Etuuksien Käyttö Oulussa 2013–2018. Tutkimushankkeen Aineiston Yleiskuvaus [Social and Health Care Services and Social Security Benefits in Oulu in 2013–2018; Basic Description of Data] Kela Working Papers 154/2020 Kela Helsinki, Finland 2020 (In Finnish, with English Abstract) 37. Gjesdal S. Bratberg E. Diagnosis and duration of sickness absence as predictors for disability ension: Results from a three-year, multi-register based and prospective study Scand. J. Public Health 2003 31 246 254 10.1080/14034940210165154 15099029 38. Gissler M. Haukka J. Finnish health and social welfare registers in epidemiological research Nor. Epidemiologi. 2004 14 113 120 39. Hujanen T. Mikkola H. Työterveyshuollon kustannuskehitys [Cost development of occupational health services] Suom. Laakaril. 2016 71 1537 1540 (In Finnish, with English Abstract) 40. Räsänen K. Heikkinen J. Myllykangas M. Työterveyshuollon sairaanhoitopalvelujen käyttö vaihtelee tarjonnan mukaan [Supply and use of consultation services in occupational health units in the nine biggest cities in Finland] Suom. Laakaril. 2014 69 1325 1330 (In Finnish, with English Summary) 41. Statistics Finland Sosioekonominen Asema 1989 [Classification of Socioeconomic Groups 1989] Available online: https://www.stat.fi/meta/luokitukset/sosioekon_asema/001-1989/index.html (accessed on 1 March 2020) 42. Saastamoinen L. Aaltonen K. Maljanen T. Tuominen U. Martikainen J. Health registers as a source of data for research and policy making Dosis 2012 28 199 205 43. World Health Organization (WHO) International Statistical Classification of Diseases and Related Health Problems, 10th Revision World Health Organization Geneva, Switzerland 2016 44. Cameron A. Trivedi P. Microeconometrics Using Stata, Revised Edition Stata Press College Station, TX, USA 2010 45. StataCorp Stata Statistical Software: Release 14 StataCorp LP College Station, TX, USA 2015 46. Keskimäki I. Tynkkynen L. Reissell E. Koivusalo M. Syrjä V. Vuorenkoski L. Rechel B. Karanikolos M. Finland: Health system review Health Syst. Transition 2019 21 1 166 47. Blomgren J. Virta L. Socioeconomic differences in use of public, occupational and private health care: A register-linkage study of a working-age population in Finland PLoS ONE 2020 15 e0231792 10.1371/journal.pone.0231792 32298356 48. Regidor E. Martınez D. Calle M. Astasio P. Ortega P. Domınguez V. Socioeconomic patterns in the use of public and private health services and equity in health care BMC Health Serv. Res. 2008 8 183 10.1186/1472-6963-8-183 18789164 49. Van Doorslaer E. Masseria C. Koolman X. Inequalities in access to medical care by income in developed countries CMAJ 2006 174 177 183 10.1503/cmaj.050584 16415462 50. Øverland S. Glozier N. Henderson M. Mæland J. Hotopf J. Mykletun A. Health status before, during and after disability pension award: The Hordaland Health Study (HUSK) Occup. Environ. Med. 2008 65 769 773 10.1136/oem.2007.037861 18940958 51. Perhoniemi R. Tuulio-Henriksson A. Blomgren J. Laaksonen M. Consumption of psychotropic drugs among disability pension applicants with mental disorders: Comparing awarded and rejected applicants in Finland Soc. Psychiatry Psychiatr. Epidemiol. 2021 56 437 448 10.1007/s00127-020-01850-8 32172305 52. Laaksonen M. Metsä-Simola N. Martikainen P. Pietiläinen O. Rahkonen O. Gould R. Partonen T. Lahelma E. Trajectories of mental health before and after old-age and disability retirement: A register-based study on purchases of psychotropic drugs Scand. J. Work Environ. Health 2012 38 409 417 10.5271/sjweh.3290 22411588 53. Perhoniemi R. Blomgren J. Laaksonen M. Determinants of disability pension applications and awarded disability pensions in Finland, 2009 and 2014 Scand. J. Public Health 2020 48 172 180 10.1177/1403494819843778 31044651 54. Perhoniemi R. Blomgren J. Laaksonen M. Sources of income following a rejected disability pension application: A sequence analysis study Disabil. Rehabil. 2020 42 2161 2169 10.1080/09638288.2018.1555619 31081397 55. Cockerham W. Social Causes of Health and Disease 2nd ed. Polity Press Cambridge, UK 2007 56. Marmot M. Allen J. Bell R. Bloomer E. Goldblatt P. WHO European review of social determinants of health and the health divide Lancet 2012 380 1011 1029 10.1016/S0140-6736(12)61228-8 22964159 57. Härkäpää K. Järvikoski A. Gould R. Motivational orientation of people participating in vocational rehabilitation J. Occup. Rehabil. 2014 24 658 669 10.1007/s10926-013-9496-z 24452474 58. Gould R. Härkäpää K. Järvikoski A. Too Late? The Timing of Vocational Rehabilitation Int. J. Rehabil. Res. 2009 32 S64 59. Ministry of Social Affairs and Health Press Release 253/2021 Available online: https://valtioneuvosto.fi/en/-//1271139/progress-made-in-seven-day-cap-on-waiting-times-for-access-to-care (accessed on 2 January 2022) 60. Finnish National Board on Research Integrity TENK The Ethical Principles of Research with Human Participants and Ethical Review in the Human Sciences in Finland Tutkimuseettisen Neuvottelukunnan Julkaisuja 3/2019 Finnish National Board on Research Integrity Helsinki, Finland 2019

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095592 ijerph-19-05592 Editorial Biological Factors in the Workplace—Current Threats to Employees, the Effects of Infections, Prevention Options https://orcid.org/0000-0002-1677-8146 Garus-Pakowska Anna Department of Nutrition and Epidemiology, Medical University of Lodz, 90-419 Lodz, Poland; anna.garus-pakowska@umed.lodz.pl 05 5 2022 5 2022 19 9 559227 4 2022 29 4 2022 © 2022 by the author. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This research received no external funding. ==== Body pmcInfectious diseases or communicable diseases are spread from person to person by various routs. So we have airborne diseases, bloodborne diseases, and contact diseases. In the work environment, pathogens can spread from employee to employee, often leading to the development of an occupational disease [1]. According to the definition, an occupational disease is both acute and chronic disease, resulting from the performance of an occupation, resulting from the nature of the work or the conditions in which it takes place [2]. Biological agents in the workplace are classified according to their infectious effect. The criteria for this breakdown include:- The possibility of causing disease in humans; - The degree of risk to workers; - Probability of spreading in the population; - Possibility of prophylaxis and/or effective treatment [3]. Directive 2000/54/EC describes the principles of risk assessment, prevention, and control of biological agents at work. Biological agents are classified into four risk groups according to their level of risk of infection: Group 1—Biological agents for which there is a low probability of causing disease in humans, and, therefore, they practically do not pose a threat to workers (e.g., weakened strains of bacteria used in the production of vaccines or yeasts intended for production purposes); Group 2—Biological agents with documented harmful effects on the human body. They can pose a risk to workers but are unlikely to spread to the human population. In addition, there are methods of effective prevention or treatment. Examples include Staphylococcus aureus causing skin infections, Borrelia burgdorferii causing Lyme Disease and Hepatitis A virus (HAV); Group 3—Biological agents that are dangerous to humans and can cause serious diseases. They pose a serious threat to workers and are very likely to spread through the population. The current state of knowledge enables the implementation of effective prevention and/or treatment of these factors. This group includes: Mycobacterium tuberculosis, Hepatitis B virus (HBV), Hepatitis C virus (HCV), and Human immunodeficiency virus (HIV). SARS-CoV-2 was also included in group 3; Group 4—Biological factors that cause severe disease in humans and most often lead to death. They pose a serious threat and their spread in the population of workers is very likely. At the same time, it is impossible to apply effective prophylaxis and treatment. This group includes only viruses: Ebola hemorrhagic fever virus, Lassa hemorrhagic fever virus and Variola virus [3]. Infectious diseases are an important part of the diseases to which workers are exposed. In Poland, infectious diseases dominate among occupational diseases in recent years. Tuberculosis, HCV, and HBV are the most frequently diagnosed among healthcare workers. After all, not only medical personnel get sick. There are also teachers, officials, drivers, and all other employees who have contact with another person at the workplace (or optionally contact with an animal, e.g., foresters and farmers) [4]. The number of workers who become ill because they have had contact with the pathogen in the workplace is much greater. It is difficult to estimate how many because most of these events are unregistered. The ongoing COVID-19 pandemic has made this problem even worse. In Poland, 2800 outbreaks of nosocomial infections were reported in 2020 (including 2265 outbreaks caused by SARS-CoV-2). Of the SARS-CoV-2 outbreaks, every fourth (25.5%, n = 577) outbreak related to staff reporting of infections. The number of healthcare workers infected with SARS-CoV-2 in connection with work in 2020 amounted to 20,697 people [5]. SARS-CoV-2 infections among healthcare workers have been and are reported worldwide [6,7,8,9]. Due to the way the virus is transmitted and its high contagiousness, there is no profession that is free from the risk of infection. However, private (non-professional) contacts cannot be ruled out in this case [10,11]. Another interesting example of an infectious occupational disease is Lyme disease. A tick bite can occur both in a farmer, a forester, and a paramedic who provided assistance to the injured in the accident. Lyme disease has been registered in many occupational groups, especially those working outdoors, including forestry workers, farmers, veterinarians, military recruits, and orienteers [12]. Currently, Lyme disease is the most frequently diagnosed occupational disease in the general population in Poland [4]. The specificity of infections varies depending on the profession. Among some employees, injuries with sharp tools are a significant problem, which may result in the transmission of blood-borne infection [13,14,15]. Postexposure prophylaxis (PEP) is recommended for workers who have an occupational exposure to blood, tissue, or other body fluids that may contain HCV, HBV, HIV, but also for workers exposed to tetanus or rabies [16,17,18]. Unfortunately, the knowledge of employees about the risk of infection, as well as methods and possibilities of infection prevention, is insufficient, which is emphasized by the authors in their publications [19,20]. Prophylaxis in the workplace may include non-specific methods, such as the use of personal protective equipment (gloves, masks), or washing and disinfecting hands, which is often emphasized as the most important method of interrupting the transmission of infectious agents [21]. There are also specific methods of preventing infections, and here we should mention vaccination of workers and methods of post-exposure prophylaxis. Manuscripts on this topic will also be very valuable for our Special Issue. The new epidemic challenges are related to the psychological burden on employees. It is true that the stress of the global epidemic threat affects society as a whole. However, medical staff experienced higher levels of anxiety, depression, and insomnia [22]. These health problems affect hospital staff as well as primary care workers, where direct patient access has been limited in many countries due to the pandemic [23]. We invite authors who, in their manuscripts, will focus on the mental health of employees exposed to the risk of infection in the workplace. Fighting infections in the workplace requires legal bases that control behavior, describe the obligations of employers, regulate the rules of prevention, and, finally, regulate conflicts between the employee and the employer (e.g., Directive 2000/54/EC [3] or Directive 2010/32/EU-prevention from sharp injuries in the hospital and healthcare sector [24]). Authors are also invited to submit manuscripts related to the legislation on infections. To sum up, this Special Issue focuses on the prevalence of communicable diseases in the workplace. It can be divided into several thematic sections: (1) Occupational infections in the workplace (different occupational groups, different routes of spreading, various pathogens); (2) Prevention of infections in the workplace; (3) Psychological problems of employees related to the risk of infection in the workplace; (4) Legal aspects of infections in the workplace. I have great pleasure to invite all authors to submit manuscripts for a Special Issue ”Infectious Diseases in the Workplace”. It will be a great compendium of the latest knowledge and developments in the field of workplace infection. Conflicts of Interest The author declares no conflict of interest. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Zurich Service Corporation Infectious Disease Control in the Workplace Available online: https://www.rpta.org/safety/4infectious_disease_control.pdf (accessed on 14 April 2022) 2. Canadian Centre for Occupational Health and Safety Occupational Hygiene—Occupational Disease Available online: https://www.ccohs.ca/oshanswers/hsprograms/occ_hygiene/occ_disease.html (accessed on 14 April 2022) 3. Directive 2000/54/EC of the European Parliament and of the Council of 18 September 2000 on the Protection of Workers from Risks Related to Exposure to Biological Agents at Work Official Journal of the European Communities 2000 Available online: http://www.biosafety.be/PDF/2000_54.pdf (accessed on 22 April 2022) 4. Świątkowska B. Hanke W. Szeszenia-Dąbrowska N. Occupational Diseases in Poland in 2019 Nofer Institute of Occupational Medicine Lodz, Poland 2020 978-83-63253-25-7 5. Chief Sanitary Inspectorate in Poland The Sanitary Condition of the Country in 2020 Available online: https://www.gov.pl/web/gis/stan-sanitarny-kraju-w-2020-roku (accessed on 24 April 2022) 6. Lenggenhager L. Martischang R. Sauser J. Perez M. Vieux L. Graf C. Cordey S. Laubscher F. Nunes T.R. Zingg W. Occupational and community risk of SARS-CoV-2 infection among employees of a long-term care facility: An observational study Antimicrob. Resist. Infect. Control 2022 11 51 10.1186/s13756-022-01092-0 35303939 7. El-Raey F. Alboraie M. Youssef N. Yousef A. Abdelmoaty A.A. Hassan E. Hassany S.M. Abd-Elsalam S. Elsharkawy R. Farrag K. Predictors for Severity of SARS-CoV-2 Infection Among Healthcare Workers J. Multidiscip. Healthc. 2021 14 2973 2981 10.2147/JMDH.S335226 34729011 8. Kantele A. Lääveri T. Kareinen L. Pakkanen S.H. Blomgren K. Mero S. Patjas A. Virtanen J. Uusitalo R. Lappalainen M. SARS-CoV-2 infections among healthcare workers at Helsinki University Hospital, Finland, spring 2020: Serosurvey, symptoms and risk factors Travel Med. Infect. Dis. 2021 39 101949 10.1016/j.tmaid.2020.101949 33321195 9. Rafferty A.C. Hewitt M.C. Wright R. Hogarth F. Coatsworth N. Ampt F. Dougall S. Alpren C. Causer L. Coffey C. COVID-19 in health care workers, Australia 2020 Commun. Dis. Intell. 2021 45 1 11 10.33321/cdi.2021.45.57 10. Sami S. Vuong N. Miller H. Priestley R. Payne M. Licata-Portentoso G. Drobeniuc J. Petersen L.R. SARS-CoV-2 Infection and Mitigation Efforts among Office Workers, Washington, DC, USA Emerg. Infect. Dis. 2021 27 669 672 10.3201/eid2702.204529 33496649 11. Kindzierski S. van Loon W. Theuring S. Hommes F. Thombansen E. Böttcher M. Matthes H. Rössig H. Weiger D. Wiesmann C. SARS-CoV-2 infection among educational staff in Berlin, Germany, June to December 2020 Eurosurveillance 2022 27 2100524 10.2807/1560-7917.ES.2022.27.11.2100524 35301979 12. Piacentino J.D. Schwartz B.S. Occupational risk of Lyme disease: An epidemiological review Occup. Environ. Med. 2002 59 75 84 10.1136/oem.59.2.75 11850549 13. Mengistu D.A. Tolera S.T. Demmu Y.M. Worldwide Prevalence of Occupational Exposure to Needle Stick Injury among Healthcare Workers: A Systematic Review and Meta-Analysis Can. J. Infect. Dis. Med. Microbiol. 2021 2021 9019534 10.1155/2021/9019534 33564345 14. Getie A. Wondmieneh A. Tesfaw G. The Prevalence of Needlesticks and Sharp Injuries, and the Associated Factors Among Midwives and Nurses in North Wollo Zone Public Hospitals, North East Ethiopia: An Institution-based Cross-sectional Study Drug Healthc. Patient Saf. 2020 12 187 193 10.2147/DHPS.S273669 33116914 15. Garus-Pakowska A. Górajski M. Epidemiology of needlestick and sharp injuries among health care workers based on records from 252 hospitals for the period 2010–2014, Poland BMC Public Health 2019 19 634 10.1186/s12889-019-6996-6 31126266 16. Centers for Diseases Control and Precention Post-Exposure Prophylaxis (PEP) Available online: https://www.cdc.gov/hiv/risk/pep/index.html (accessed on 22 April 2022) 17. Callison C. Nguyen H. Tetanus Prophylaxis StatPearls Updated 7 June 2021 StatPearls Publishing Treasure Island, FL, USA 2022 Available online: https://www.ncbi.nlm.nih.gov/books/NBK559008/ (accessed on 25 April 2022) 18. Centers for Diseases Control and Precention ACIP Recommendations Use of a Reduced (4-Dose) Vaccine Schedule for Postexposure Prophylaxis to Prevent Human Rabies Available online: https://www.cdc.gov/rabies/resources/acip_recommendations.html (accessed on 25 April 2022) 19. Aluko O.O. Adebayo A.E. Adebisi T.F. Ewegbemi M.K. Abidoye A.T. Popoola B.F. Knowledge, attitudes and perceptions of occupational hazards and safety practices in Nigerian healthcare workers BMC Res. Notes 2016 9 71 10.1186/s13104-016-1880-2 26852406 20. Wu Q. Xue X.F. Shah D. Zhao J. Hwang L.Y. Zhuang G. Knowledge, Attitude, and Practices Regarding Occupational HIV Exposure and Protection among Health Care Workers in China: Census Survey in a Rural Area J. Int. Assoc. Provid. AIDS Care (JIAPAC) 2016 15 363 369 10.1177/2325957414558300 25425637 21. World Health Organization 19, Organizing an Educational Programme to Promote Hand Hygiene WHO Guidelines on Hand Hygiene in Health Care: First Global Patient Safety Challenge Clean Care Is Safer Care World Health Organization Geneva, Switzerland 2009 Available online: https://www.ncbi.nlm.nih.gov/books/NBK144010/ (accessed on 25 April 2022) 22. Zhang X. Zhao K. Zhang G. Feng R. Chen J. Xu D. Liu X. Ngoubene-Atioky A.J. Huang H. Liu Y. Occupational Stress and Mental Health: A Comparison Between Frontline Medical Staff and Non-frontline Medical Staff During the 2019 Novel Coronavirus Disease Outbreak Front. Psychiatry 2020 11 555703 10.3389/fpsyt.2020.555703 33424651 23. Shi L. Xu R.H. Xia Y. Chen D. Wang D. The Impact of COVID-19-Related Work Stress on the Mental Health of Primary Healthcare Workers: The Mediating Effects of Social Support and Resilience Front. Psychol. 2022 12 800183 10.3389/fpsyg.2021.800183 35126252 24. Council Directive 2010/32/EU of 10 May 2010 Implementing the Framework Agreement on Prevention from Sharp Injuries in the Hospital and Healthcare Sector Concluded by HOSPEEM and EPSU (Text with EEA Relevance) Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010L0032 (accessed on 26 April 2022)

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093357 materials-15-03357 Article Exploration of Carbon Dioxide Curing of Low Reactive Alkali-Activated Fly Ash Harirchi Peyman https://orcid.org/0000-0002-5781-8765 Yang Mijia * Hu Jie Academic Editor Department of Civil, Construction and Environmental Engineering, North Dakota State University, Fargo, ND 58104, USA; peyman.harirchi@ndsu.edu * Correspondence: mijia.yang@ndsu.edu 07 5 2022 5 2022 15 9 335703 4 2022 04 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In this paper, the effect of carbon curing procedure on low reactive fly ash alkali-activated pastes was investigated. Specimens were cured with pure carbon dioxide (CO2) gas for different curing times under 4 bar pressure. Chemical and physical characteristics of the geopolymer pastes were obtained from mass monitoring, titration test, XRD, FTIR and TGA-DTG analyses. Regarding the test results, after three days of CO2 curing, the highest CO2 uptake was obtained at 4.8 wt% of fly ash precursor, with carbon sequestration efficiency at 22.6%. The ratio of carbon dioxide absorbed as efflorescence to the total absorbed CO2 was measured. The results show that at early age, almost 50% of carbonated products appeared as efflorescence; however, by increasing the curing time, and after 3 days of curing, about 80% of carbon dioxide was stored in the matrix. It was found that, in all cases, carbonation curing was detrimental to the geopolymerization process due to a high amount of efflorescence and led to a reduction in the compressive strength. At 24 h and 3 days, the specimens showed a lower reduction in compressive strength in comparison to CO2 samples cured at 3 h, 6 h and 12 h. Regarding the XRD results, calcite was detected in the 24 h and 3 days specimens, which contributes to lower pore sizes due to a higher molar volume and production of silica gel that might participate in the polymerization processes and results in densified microstructures. carbon dioxide curing alkali-activated material fly ash FTIR efflorescence XRD ND NSF EPSCoRThe research is funded by ND NSF EPSCoR. ==== Body pmc1. Introduction Due to calcination reaction of the carbonate minerals in cement manufacturing, the production of one tonne of cement approximately releases one tonne of carbon dioxide (CO2) [1]. Consequently, the cement industry has been responsible for almost 8% of CO2 emissions in 2020; therefore, the reduction and control of CO2 emission is becoming a major trend in the cement and concrete industry [2]. In recent years, CO2 curing of fresh concrete as a carbon capture and storage (CCS) method has been adopted due to the urgency of CO2 mitigation [3,4,5]. Using this technology, gaseous CO2 is permanently fixed into thermodynamically stable minerals, such as calcium or magnesium carbonates [6,7], which leads to improvement of physical properties and durability of concrete [3,8]. The effect of carbon curing generally depends on the rate of CO2 diffusion, carbonation rate, concentration of carbon dioxide, relative humidity and chemical composition of the mix [9,10,11,12]. The enhancement of the properties of final products is rooted in the quality and quantity of calcium carbonate generated in the pore structure in the early ages of hydration. Pro-environment alternatives to the ordinary Portland cement (OPC) have been developed since 1940 called alkali-activated materials (AAMs) and geopolymer concrete (GC) [13]. AAMs are aluminosilicate industry byproducts, such as granulated blast furnace slag (GBFS) or fly ash (FA), which show cementitious properties by adding alkali solutions, such as sodium hydroxide (NaOH) and water glass [8]. The reaction forms a three-dimensional Si-O-(Si or Al) framework, and the final product contains sodium-aluminosilicate-hydrate (N-A-S-H) and calcium-aluminosilicate-hydrate (C-A-S-H) gels. The resulting solid has a rapid strength gain, low permeability, high chemical, high heat resistance and low thermal conductivity, which make these materials qualified candidates for replacing OPC with a significant reduction in CO2 [8,14,15,16,17]. The conventional curing methods of FA-based concrete are water curing and steam curing in which curing time and temperature are the most important factors for controlling the compressive strength [18]. Recent studies have investigated the effect of carbon dioxide curing on both OPC and AAMs for further reduction in CO2 footprint. Zhang et al. investigated the effect of CO2 curing on the pozzolanic reaction in fly ash concrete [7]. They found that if carbonation is limited to 12 h, it activates the fly ash OPC specimen at an early time of hydration, and the pH value of the pore solution is comparable to the control sample without the fly ash. Kassim et al. measured the effect of carbonation curing on the mechanical properties of alkali-activated electric arc furnace slag and reported a significant improvement of physical properties in CO2 curded samples [19]. Park et al. examined the effect of CO2 rich environment on FA-based alkali-activated materials with oven heating treatment [20]. They observed that the carbonated minerals densify the microstructure and improve the compressive strength of CO2 cured samples. It was found that in CO2 cured samples, the aluminosilicate gel contained a higher amount of silicates. Mei et al. investigated the mechanical and microstructure properties of alkaline-activated blast furnace slag (BFS) under accelerated carbonation [2]. They concluded that the carbonation of AAMs under a high CO2 concentration deteriorates the matrix structure due to the consumption of Ca ions in C-S-H gel. Consequently, the resulting pores in carbonated specimens accelerate CO2 diffusion and contribute to the weakening of the structure. Ohenoja et al. used peat-wood fly ashes from different sources for mineral carbonation [6]. The results showed an inconsistent effect of carbonation curing on the mechanical properties and a reduction in compressive strength in one fly ash sample, while in other samples, an increase in compressive strength was observed. Yamazaki et al. reported that in fly ash AAM, the N-A-S-H structure does not change with respect to accelerated carbonation [8]. Ul Haq et al. enhanced the fly-ash-based GC by in situ carbonation and reported that higher geopolymerization was achieved in the carbonated specimens [15]. Similarly, the polymerization effect of carbonation was reported by Nedeljkovic et al. [12]. The effect of CO2 on the geopolymerization process and the effectiveness of carbon mineralization require further investigation due to the inconsistency of reported results in the literature. Annually, large-volume fly ash fails to meet the requirements of national standards, such as ASTM C618, due to low reactivity [21]. In this paper, the effect of carbonation curing on alkali-activated pastes composed of low reactive fly ash without heat treatment is examined. The CO2 mineralization capacity is measured through titration tests for specimens cured in a carbonation chamber under 4 bar pressure of pure CO2. The mechanical properties of these samples are then tested, and the effect of carbon curing is investigated by XRD, FTIR and TGA analyses. 2. Materials The chemical composition of the fly ash used in this study is measured by a Rigaku Supermini 200 X-ray fluorescence spectrometer (Applied Rigaku Technologies, Inc., Austin, TX, USA) and shown in Table 1. The composition indicates that the fly ash contains high amounts of SiO2, Al2O3 and CaO, and is categorized under type F regarding the ASTMC618-19 standard [22]. The basicity coefficient (Kb=CaO+MgOSiO2+Al2O3) and the hydration coefficient (HM=CaO+MgO+Al2O3SiO2) are calculated as 0.27 and 0.78, respectively. The majority minerals found by the X-ray diffraction test are quartz, mullite and hematite, as shown in Figure 1. The surface area calculated through the Brunauer–Emmett–Teller (BET) method is 0.5034 m2/g. The alkali activator used in this study is a mixture of sodium hydroxide (NaOH) with a purity of 98(%) and sodium silicate (Na2SiO3) solution with 9% Na2O and 28% SiO2. An amount of 5 M/L solution of NaOH is mixed with Na2SiO3 solution in a way that the molar ratio of silicon oxide to sodium oxide equals 1 (SiO2/Na2O = 1). The alkali activator is prepared 24 h before being added to the fly ash precursor and kept at laboratory temperature. 2.1. Preparation of Samples and Experimental Set-Up The water to binder ratio (w/b) is set to 0.3 for all samples. Besides the added water in the activator, water of the sodium silicate solution is considered in the calculation of water content. For each curing time, three samples are prepared. The compressive strength test is conducted with respect to ASTM C305-20 using 2-inch cubes [23]. After demolding, the samples are cured in the carbonation chamber under 4 bar pressure of 100% CO2 in a set-up shown in Figure 2. Non-carbonation samples (NC) are cured in an ambient environment with 66% relative humidity (RH) at 22 °C temperature. The samples are cured for 3, 6, 12, 24 h and 3 days, and are named 3 h, 6 h, 12 h, 24 h and 3 days, respectively. 2.2. Characterization Methods 2.2.1. Mass Monitoring For measuring CO2 absorption, the mass monitoring method as a nondestructive method was adopted by previous researchers [24,25,26,27]. The key in measuring the CO2 uptake in carbonated samples is the estimation of water evaporation; therefore, a comparison between NC samples and carbonated samples is made for measuring the evaporable water. First, the water loss rate for NC samples (WRNC) is measured using Equation (1), and then, the change of mass with respect to CO2 curing is calculated by assuming the same evaporable water content for the carbonated samples. Based on ASTM C566-19, the samples are heated in an oven at a temperature 110 ± 5 °C to measure the mass of evaporable water [28]. (1) WRNC=M1−M2M1×100 In Equation (1), M1 and M2 are mass of a sample before and after oven heating, respectively. The mass of evaporable water (Mw) in all samples is calculated using WRNC and the initial mass of a sample (M1) by applying Equation (2). (2) Mw=M1×WRNC100 The CO2 uptake for carbonated samples is calculated using Equation (3) in which Mb is the mass of fly ash used in each sample. (3) CO2 uptake(%)=(M2+MW)−M1Mb×100% 2.2.2. Measurement of Absorbed CO2 One important issue in the implementation of geopolymer concrete is efflorescence on the surface of specimens. Unreacted alkali ions diffuse on the surface, react with CO2 in the air and form white carbonates known as efflorescence [26]. The reduction in efflorescence can be investigated by the surface modification method [29], through the control of concrete microstructure and decrease in the fluidity of alkali [30]. Efflorescence can be evaluated in different ways, such as immersing the specimens in water and measuring the weight of dissolved salts after drying the solution [31]. In another method, the efflorescence image is captured using a camera and compared with Na+ concentration at a different pH value of leachate [30]. However, the image-based method is not accurate because the efflorescence products include calcium and potassium cations in addition to sodium cations [26,32]. Additionally, the measurement of OH− and HCO3− must be considered in the evaluation of efflorescence. Due to lack of efflorescence measurement standards in AAMs, the water immersion method is adopted in this study, since carbonation products, including sodium carbonates and bicarbonates, are soluble in water. After CO2 curing, the samples are immersed in water for 2 days. In this process, water dissolves sodium carbonates and bicarbonates on the surface, but the calcium carbonate fixed in the matrix remains insoluble. The concentration of carbonate minerals in the solution is obtained by applying the titration test following the requirements of ASTM D3875-15 [33]. The ratio of CO2 in the soluble products to the total CO2 absorption shows the efficiency of carbonation curing. 2.2.3. Compressive Strength The samples, with respect to different carbon curing durations, are tested by the universal compression testing machine. The low reactivity of fly ash indicates that only late-age compressive strength is detectable; therefore, a 28-day compressive strength is reported for all samples regarding ASTM C109/C109M [34]. For each CO2 curing configuration, three samples are prepared, and the average compressive strength is plotted as a bar chart with the error bar representing the range of the strength variation. 2.2.4. X-ray Diffraction (XRD) XRD diffractograms are conducted using Rigaku SmartLab (Applied Rigaku Technologies, Inc., Austin, TX, USA) for identification of minerals and phase changes of crystals in all samples [8]. XRD test shows the crystalline phases for samples with respect to different carbonation times. Different polymorphs of calcium carbonates could be detected at high pressure of CO2. The peaks of calcium carbonates, including calcite (higher stability and crystallinity) and vaterite (lower stability and crystallinity), are expected in this experiment. 2.2.5. Fourier Transform Infrared Spectroscopy (FTIR) FTIR measures the absorption of infrared radiation by different functional groups; it identifies the molecular components and structures in the material [35]. FTIR is applied to specimens through the Thermo Scientific Nicolet 8700 FT-IR spectrometer (BRUKER, Allentown, PA) to monitor the change of the gel structure for different carbon-cured samples. FTIR is also conducted for measuring the reactivity of fly ash by the method proposed by Zhang et al. [36]. By deconvolution of the absorbance spectrum between 400 cm−1 and 1400 cm−1 band, the Gaussian curves corresponding to the active and inactive bonds are obtained. In the active bonds, Si and Al atoms are easily dissolved in the geopolymerization process. The active bonds are represented in Table 2. The relative area of convoluted bonds is assumed as an index of concentration of each bond. Since the solubility of active bonds is not equal, reactivity coefficients are applied to modify the contribution of each active bond. Regarding Ref [36], weaker bonds appear in the lower regions of the FTIR spectrum; consequently, reactivity coefficients for high to low regions are chosen as 0.25, 0.5, 0.75 and 2. 2.2.6. Thermogravimetric Analysis (TGA) TGA is performed on all samples using TA Instrument Q500 to analyze their chemical compositions. The samples are heated with pure nitrogen gas from 25 °C to 1000 °C at the rate of 20 °C/min to quantify both carbonated and amorphous minerals. 3. Results and Discussions The test results of the CO2 cured samples are presented in this section. First, the reactivity of the fly ash samples is measured using FTIR, and then, the mechanical properties, including mass change, compressive strength and amount of CO2 absorption, are presented. Next, spectroscopic results of the CO2 cured samples and NC samples are demonstrated by XRD, FTIR and TGA. 3.1. Quantitative Measurement of Reactivity of Fly Ash Figure 3 shows the FTIR absorbance and Gaussian convoluted curves of the active bonds. It is assumed that the relative area of a resolved bond represents its concentration in the sample. The reactive surface area is calculated by multiplication of the active concentration by surface area obtained from the BET gas adsorption test. The relative area, reactive coefficient, active concentration and reactive surface area of the FA sample are shown in Table 3. The active bond represents the Si-O-Al bond, which is easily broken in the presence of an alkali activator and dissolves at a faster rate in comparison to the inactive bonds. These bonds are mostly related to non-bridging oxygen with the Q3, Q2, Q1 and Q0 molecular structure [36]. The reactive surface value (0.144 m2/g), in comparison to the values reported in Ref [36], indicates low reactivity of the FA sample in this study. 3.2. Mass Change of Carbon-Cured Geopolymer Paste and the CO2 Absorption Capacity The mass change after oven heating shows the amount of evaporable water for NC samples. The evaporable water is measured as 18.1% of the initial mass of the specimen. The mass change for CO2 cured sample is lower compared to NC samples because of CO2 absorption (Figure 4). The reduction in mass change by increasing the curing time indicates more absorption of CO2. CO2uptake per mass of binder is calculated using Equation (3) and the average evaporable water in NC samples. The CO2 uptake at the early age occurs rapidly, and the rate of CO2 uptake for the first 3 h is about 0.46%/h. However, the CO2 uptake rate decreases between 3 and 24 h (Figure 4). This might be because of the presence of carbonated products that precipitate on the surface and in the pore structure, which hinders the diffusion of gaseous CO2 into the samples. By further CO2 curing, the gas molecules diffuse deeply into the matrix, and the precipitation rate of carbonated products increases. The maximum capacity of CO2 absorption can be determined by the chemical composition of cementitious materials through Equation (4) [37,38]:(4) CO2=0.785(CaO−0.7SO3)+1.091MgO+1.42Na2O+0.935K2O It should be noted that the above formula was suggested for OPC. Consequently, caution should be taken when using Equation (4) for alkali-activated materials [37]. Based on Equation (4), the maximum CO2 absorption capacity of the specimens is 21.23%. The maximum CO2 uptake after 3-day CO2 curing is approximately 5% from the test data, which indicates a major portion of the samples is not carbonated. Depending on the source of the fly ash, different values of CO2 uptake efficiency have been reported. Hernandez et al. proposed the aqueous mineralization of carbon dioxide in fly ash powder without addition of an activator and calculated a 2.6% CO2 uptake per tonne of fly ash [39]. Calcium hydroxide carbonation was considered the main reaction controlling the mineral sequestration of CO2. The same reaction mechanism was considered by Mazzella et al. who obtained CO2 uptake at about 18 wt% fly ash by gas–solid carbonation treatment [40]. 3.3. Efflorescence Measurement CO2 cured samples show a high amount of efflorescence. This phenomenon deteriorates both the appearance aesthetics and mechanical properties of AAMs. High amount of efflorescence is observed on the surfaces, especially on the top of the samples. Regarding the titration test, only carbonate and hydroxide ions are observed, while bicarbonate ions are not detected. By measuring the concentration of carbonate ions, the weight of hydrated carbon dioxide in the solution is calculated. Figure 5 represents the CO2 uptake and its rate per mass of the paste versus curing time obtained from the titration test. The absorption rate of carbon dioxide indicates that in the early stages of curing, the paste has a high absorption capacity, while this potential decreases significantly over time. The efficiency of CO2 mineralization mentioned in the literature for aqueous carbonation and gas–solid carbonation is 82% and 74%, respectively [39,40]. These efficiencies are obtained for powder samples, while the CO2 mineralization examined here is for the paste specimens. The efficiency ratios for 3 h, 6 h, 12 h, 24 h and 3 days specimens are obtained by dividing the CO2 uptakes from Figure 5 by the total capacity of carbonation calculated from Equation (4), which are 6.6, 9.4, 11.3, 12.7 and 22.6%, respectively. The ratio of CO2 absorbed as efflorescence to the total absorbed CO2 shows the effectiveness of carbon curing (Figure 6). In the early age of carbonation, almost half of the carbonated products appear as efflorescence due to the existence of a high amount of free alkaline ions on the sample surface, while at longer curing times, more CO2 is fixed in the matrix. The dissolution of CO2 forms carbonic acid in the pore solution and may cause a reduction in the pH of the pore solution, which occurs in natural carbonation and hinders further progress of the reaction. In OPC, calcium hydroxide acts as a buffer and saturates the pore solution with Ca2+ and OH−; consequently, the pH level of the pore solution stays above 12, which protects the steel reinforcement against corrosion. CO2 buffer capacity significantly affects the carbonation resistance and can be represented as the ratio of water to reactive calcium oxide [10]. In severe cases, after the consumption of portlandite, the pH of the pore solution starts to decrease. By lowering the pH under 12.6, C-S-H, ettringite (AFt) and monosulfate (AFm) become unstable. Additionally, the protection layer of steel reinforcement disappears when the pH is less than 9.5, and eventually, calcium carbonates precipitate in the pore structure. In AAMs, carbonation occurs in a two-step process:(1) Precipitation of sodium carbonates and reduction in pH of the pore solution. (2) Consumption of calcium-rich products. The carbonation of AAMs, unlike OPC, depends on both the reactive CaO and Na2O content of the precursor [12]. In comparison to OPC, AAMs do not include portlandite and contain low amount of reactive calcium. The lack of portlandite results in the decalcification of C-A-S-H gel and the production of silica gel that might be engaged in the geopolymerization process and densify the AAMs’ microstructure. 3.4. Compression Strength Results The change of the 28 days’ strength is monitored for NC and CO2 cured samples in Figure 7. The CO2 curing is found to be detrimental in all cases in comparison to NC samples. However, in 24 h and 3 days specimens, higher compressive strength was obtained compared to 3 h, 6 h and 12 h samples. This is probably due to the existence of calcium carbonates in the pores and the participation of the produced silicates in the polymerization process. After a 12 h curing, CO2 is absorbed as a stable carbonate product, such as calcium carbonate, with different morphologies, including calcite, aragonite and vaterite. Calcium silicates are mostly converted to calcium carbonates based on the following reaction in carbon-cured samples [15]:(5)  CaSiO3+CO2⟶CaCO3+SiO2  The produced silicate reacts with the silicate network in the geopolymer and improves the structure of the matrix. The polymerization of the aluminosilicate gel and increasing molar volume of products, which reduces the porosity, have been reported in previous literature [41,42]. Unlike OPC, where the production of calcium carbonate (CaCO3) is detrimental during carbonation, in GC, this phenomenon could have the opposite effect because the main structure in AAMs is constructed based on silicates and aluminates [15], and the additional SiO2 produced through the reaction explained by Equation (5) might supply more reactive silica and enhance the geopolymerization process. This might be the reason for the increased strength in 24 h and 3 days samples. The presence of calcite in 24 h and 3 days specimens detected by XRD is further evidence that could explain this discrepancy in compressive strength results. 3.5. XRD Test Results XRD analysis is conducted to analyze the products of CO2 curing geopolymer with respect to the different curing durations (Figure 8). According to the XRD patterns, 24 h and 3 days samples are similar with respect to the identified minerals. The calcite peaks (2θ = 29.6°, 39.5°, 43.6°, 47.2°) [8] are detected in both samples. The presence of calcite, which precipitates in the pores, might be the reason for the increased strength after 24 h CO2 curing. The formation of calcite and vaterite after one day in alkaline-activated blast furnace slag (BFSS) has also been reported in the literature [2]. Vaterite is unstable under accelerated carbonation and converts to calcite; however, the growth of calcite depends on the adequate supply of CO2 and dissolution rate of Vaterite [2]. Gaylussite (Na2Ca(CO3)2·5H2O.) is detected in both 24 h and 3 days samples. Natron is a carbonation product of low CO2 concentration, and nahcolite is a carbonation product of high concentration of carbon dioxide [41]. In the obtained XRD patterns, nahcolite (2θ = 30.58°, 34.58°, 40.84°) peaks might be overlapped with gaylussite peaks. In the initial steps of carbonation, vaterite is expected to form as a metastable polymorph of calcium carbonate [43,44]. Quartz, mullite and hematite are identified in the samples as well [45]. In the presence of high humidity, vaterite crystallizes into calcite [46]. Besides the moisture content, the pH value of pore solution also contributes to the crystallization of vaterite. The pH value of pore solutions in AAMs after carbonation is usually above 9 in natural carbonation [47]. C(N)-A-S-H gel is thermodynamically less stable than C-S-H gel and is mainly amorphous, which causes different phase dissolution resulting from carbonation compared to OPC [48,49]. Pirssonite (Na2Ca(CO3)2 · 2H2O) and calcium disilicate (CaSi2O5) are detected in 3 h, 6 h and 12 h NC samples. 3.6. FTIR Test Results The infrared spectra for NC and CO2 cured samples are shown in Figure 9. The absorption bands are divided into three regions, including water-related bonds, Si-O-Si bond and carbonate-related bonds [12]. In geopolymers, the amount of the non-bridging oxygen (NBO) depends on the SiO2/Na2O ratio of the activator solution [50]. When SiO2/Na2O ratio decreases, NBO decreases and contributes to lower silicon coordination with oxygen, such as the SiQ2 and SiQ1 units. Q stands for the oxygen bond formed with Si, and numbers 1 and 2 stand for the number of bonds formed. The geopolymerization process is recognized by Si-O-T (T: Si or Al) bonds with a wave number at 950 cm−1 to 1200 cm−1 and at 650 cm−1 to 750 cm−1. Bands at 450 cm−1 to 1300 cm−1 are related to the Si-O-Si bond, and bands between 1600 cm−1 and 4000 cm−1 represent chemically bonded water. The stretching vibrational bonds of Si-O-Si are infrared active. The silicon coordination number, including SiQ4, SiQ3, SiQ2, SiQ1 and SiQ0, is identified by wavenumbers at 1200, 1100, 950, 900 and 850 cm−1, respectively [35,43,50,51]. In all samples, it is seen that the absorption bands related to Q3 and Q2 are dominant. The 713 cm−1 absorption peak that appears in the 12 h, 24 h and 3 days samples shows the bending vibration of CO32− in calcite and aragonite [2,43]. The increase in band intensity at this wavenumber can be considered as the condensation of aluminosilicate gel with a high amount of aluminum. The absorbance that appears between 1400 cm−1 and 1500 cm−1 is related to the stretching of CO32− and represents the existence of calcite and vaterite [35,52,53]. It is seen that by increasing the CO2 curing time, the intensity of the band increases. At the early-age CO2 curing, the existence of aragonite and vaterite for NC, 3 h, 6 h samples is observed at 1489 cm−1 and 1490 cm−1. The existence of this band for non-carbonated samples shows the effect of carbonation weathering. The presence of nahcolite (NaHCO3) is seen at band 1450 cm−1, and calcite is detected at band 1419 cm−1 [12] for 12 h, 24 h and 3 days samples, which is consistent with the XRD results. As CO2 curing progresses, more crystalized CaCO3 forms. The out-of-plane bending mode of the carbonates is located at 875 cm−1 [35], which is only detected for 12 h, 24 h and 3 days samples. In 12 h, 24 h and 3 days samples, a peak close to 2950 cm−1 is seen, which could possibly indicates the existence of vibrational bonds between carbon and hydrogen that has been detected in stearic acid [54]. The bending vibration of H-OH bonds appears in 1640 cm−1, which shows the existence of chemically bonded water [12,35]. It is seen that the peak is almost unchanged among all samples. The absorption at 3445 cm−1 shows the stretching vibration of the O-H bond in bonded water [2]. The absorption of bonded water in calcium hydroxide appears at 3644 cm−1 [2,55,56], which has low intensity. 3.7. TGA Test Results The results of thermogravimetric analysis (TGA) and its derivative to temperature (DTG) are represented in Figure 10. In the NC sample, the predominant mass loss occurs below 400 °C. The change of mass between 25 °C and 105 °C shows the loss of evaporable water. The mass change from 105 °C to 215 °C shows the loss of bonded water in matrix and decomposition of C(N)-A-S-H gel [8]. The amount of C(N)-A-S-H gel decreases from NC samples to 3 days samples. The surface area under the DTG curves shows that CO2 cured samples have a lower amount of bonded water in their structure [35,57]. The peak at 170 °C is related to thermal decomposition of hydrotalcite [58]. The dehydration of pirssonite and gaylussite occurs at temperatures under 250 °C [59]. Natron is dehydrated at 160 °C [60] in CO2 cured samples, and the intensity of the peak reduces as curing progresses. The decomposition of total carbonated phases occurs in the range of 400 °C to 800 °C [35,42,61]. Amorphous calcium carbonate (CaCO3) decomposes at 400–600 °C [8]. Higher amount of crystalline CaCO3 is detected (600–750 °C [8]) in the case of increased CO2 curing time [62]. However, the morphology of calcium carbonates in FA-based AAMs is more amorphous [12]. Regarding the literature, the crystallinity of polymorphs of calcium carbonates depends on many factors, including temperature, relative humidity, chemical composition of the binder and concentration of carbon dioxide [12,63]. 4. Conclusions In this study, the effect of CO2 curing on low reactive fly ash alkali-activated pastes in the early ages was investigated. Five CO2 curing times were applied on alkaline-activated FA samples in the presence of pure CO2 under four-bar pressure. The following conclusions are drawn according to the experimental results:Curing time had a significant effect on the carbonation products and the amount of absorbed CO2. The maximum CO2 uptake was obtained for the 3 days sample at 4.8 wt% fly ash, and the maximum efficiency was obtained at 22.6%. In short-term curing times, almost 50% of the absorbed carbon dioxide was efflorescence; however, by increasing the curing time, the absorbed CO2 in the matrix increased in the form of insoluble and stable products. It was observed that carbon curing had a detrimental effect on the compressive strength in all specimens in comparison to the control sample. The presence of carbonic acid consumed the alkali and hydroxide ions in the pore solution, which lowered the pH of the pore solution and, consequently, hindered the progress of the geopolymerization reaction. At later ages of curing (after 24 h), the compressive strength started to rise slightly, which could be due to the presence of calcite and silica gel in the pore structure that was detected by XRD in 24 h and 3 days specimens. Author Contributions Conceptualization, M.Y. and P.H.; Funding acquisition, M.Y.; Investigation, P.H.; Methodology, M.Y.; Project administration, M.Y. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data sharing not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 XRD results of the used fly ash sample. Figure 2 Carbon curing set-up. Figure 3 FTIR absorbance and Gaussian curves of active bonds in the FA sample. Figure 4 Mass change of samples after oven heating (%). Figure 5 CO2uptake per mass of FA and its average rate with respect to curing time for specimens. Figure 6 Percentage of CO2 absorbed as efflorescence with respect to curing time. Figure 7 28 days’ compressive strength. Figure 8 XRD diffractograms of non-carbonated and carbonated samples. Figure 9 FTIR spectroscopy of NC and CO2 cured samples. Figure 10 Thermogravimetric analysis results. materials-15-03357-t001_Table 1 Table 1 Chemical composition of the used fly ash. CaO SiO2 Al2O3 MgO Fe2O3 TiO2 K2O Na2O Other Fly ash 13.7 51.1 16.2 4.2 6.1 0.7 2.64 2.85 2.51 materials-15-03357-t002_Table 2 Table 2 FTIR range of active bonds in geopolymerization (adopted from Ref [36]). Range Bond Description 1085–1092 Asymmetric stretching of (Si, Al)-O-Si in glass phase, Q3 997–1011 Asymmetric stretching of (Si, Al)-O-Si in amorphous glass phase 900–915 Asymmetric stretching of Si-OM where M is an alkali metal 692–730 Symmetric stretching of Al-O in (Si, Al)-O-Al materials-15-03357-t003_Table 3 Table 3 Reactive bond parameters and reactivity calculation of the FA sample. Active Peak Center Identified Bond Relative Area (%) Reactivity Coefficient Active Concentration (%) 710.1 Al-O 1.37 2 2.74 912.5 Si-O-M 11.34 0.75 8.5 1007 (Si, Al)-O-Si 29.3 0.5 14.7 1087 (Si, Al)-O-Si 10.3 0.25 2.6 Total active concentration 28.54 Reactive surface area (m2/g) 0.144 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Thomas R.J. Peethamparan S. Alkali-activated concrete: Engineering properties and stress–strain behavior Constr. Build. Mater. 2015 93 49 56 10.1016/j.conbuildmat.2015.04.039 2. Mei K. Gu T. Zheng Y. Zhang L. Zhao F. Gong P. Huang S. Zhang C. Cheng X. Effectiveness and microstructure change of alkali-activated materials during accelerated carbonation curing Constr. Build. Mater. 2021 274 122063 10.1016/j.conbuildmat.2020.122063 3. Zhang D. Ghouleh Z. Shao Y. Review on carbonation curing of cement-based materials J. CO2 Util. 2017 21 119 131 10.1016/j.jcou.2017.07.003 4. Haselbach L.M. Thomle J.N. An alternative mechanism for accelerated carbon sequestration in concrete Sustain. Cities Soc. 2014 12 25 30 10.1016/j.scs.2014.01.001 5. Lippiatt N. Ling T.-C. Rapid hydration mechanism of carbonic acid and cement J. Build. Eng. 2020 31 101357 10.1016/j.jobe.2020.101357 6. Ohenoja K. Rissanen J. Kinnunen P. Illikainen M. Direct carbonation of peat-wood fly ash for carbon capture and utilization in construction application J. CO2 Util. 2020 40 101203 10.1016/j.jcou.2020.101203 7. Zhang D. Cai X. Shao Y. Carbonation Curing of Precast Fly Ash Concrete J. Mater. Civ. Eng. 2016 28 04016127 10.1061/(ASCE)MT.1943-5533.0001649 8. Yamazaki Y. Kim J. Kadoya K. Hama Y. Physical and Chemical Relationships in Accelerated Carbonation Conditions of Alkali-Activated Cement Based on Type of Binder and Alkali Activator Polymers 2021 13 671 10.3390/polym13040671 33672428 9. Cui H. Tang W. Liu W. Dong Z. Xing F. Experimental study on effects of CO2 concentrations on concrete carbonation and diffusion mechanisms Constr. Build. Mater. 2015 93 522 527 10.1016/j.conbuildmat.2015.06.007 10. Leemann A. Nygaard P. Kaufmann J. Loser R. Relation between carbonation resistance, mix design and exposure of mortar and concrete Cem. Concr. Compos. 2015 62 33 43 10.1016/j.cemconcomp.2015.04.020 11. Nedeljković M. Ghiassi B. van der Laan S. Li Z. Ye G. Effect of curing conditions on the pore solution and carbonation resistance of alkali-activated fly ash and slag pastes Cem. Concr. Res. 2019 116 146 158 10.1016/j.cemconres.2018.11.011 12. Nedeljković M. Ghiassi B. Melzer S. Kooij C. van der Laan S. Ye G. CO2 binding capacity of alkali-activated fly ash and slag pastes Ceram. Int. 2018 44 19646 19660 10.1016/j.ceramint.2018.07.216 13. Li Z. Li S. Effects of wetting and drying on alkalinity and strength of fly ash/slag-activated materials Constr. Build. Mater. 2020 254 119069 10.1016/j.conbuildmat.2020.119069 14. Zhang X. Long K. Liu W. Li L. Long W.-J. Carbonation and Chloride Ions’ Penetration of Alkali-Activated Materials: A Review Molecules 2020 25 5074 10.3390/molecules25215074 15. Ul Haq E. Padmanabhan S.K. Licciulli A. In-situ carbonation of alkali activated fly ash geopolymer Constr. Build. Mater. 2014 66 781 786 10.1016/j.conbuildmat.2014.06.012 16. He J. Gao Q. Wu Y. He J. Pu X. Study on improvement of carbonation resistance of alkali-activated slag concrete Constr. Build. Mater. 2018 176 60 67 10.1016/j.conbuildmat.2018.04.117 17. Arbi K. Nedeljković M. Zuo Y. Ye G. A Review on the Durability of Alkali-Activated Fly Ash/Slag Systems: Advances, Issues, and Perspectives Ind. Eng. Chem. Res. 2016 55 5439 5453 10.1021/acs.iecr.6b00559 18. Amran M. Fediuk R. Murali G. Avudaiappan S. Ozbakkaloglu T. Vatin N. Karelina M. Klyuev S. Gholampour A. Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties Materials 2021 14 4264 10.3390/ma14154264 34361457 19. Kassim D. Lamaa G. Silva R.V. de Brito J. Performance Enhancement of Alkali-Activated Electric Arc Furnace Slag Mortars through an Accelerated CO2 Curing Process Appl. Sci. 2022 12 1662 10.3390/app12031662 20. Park S.-M. Jang J.-G. Kim G.-M. Lee H.-K. Park S.-M. Jang J.-G. Kim G.-M. Lee H.-K. Strength Development of Alkali-Activated Fly Ash Exposed to a Carbon Dioxide-Rich Environment at an Early Age J. Korean Ceram. Soc. 2016 53 18 23 10.4191/kcers.2016.53.1.18 21. Li Z. Xu G. Shi X. Reactivity of coal fly ash used in cementitious binder systems: A state-of-the-art overview Fuel 2021 301 121031 10.1016/j.fuel.2021.121031 22. ASTM C618-19 Specification for Coal Fly Ash and Raw or Calcined Natural Pozzolan for Use in Concrete ASTM International West Conshohocken, PA, USA 2019 10.1520/C0618-19 23. ASTM C305-20 Practice for Mechanical Mixing of Hydraulic Cement Pastes and Mortars of Plastic Consistency ASTM International West Conshohocken, PA, USA 2020 10.1520/C0305-20 24. Huntzinger D.N. Gierke J.S. Kawatra S.K. Eisele T.C. Sutter L.L. Carbon Dioxide Sequestration in Cement Kiln Dust through Mineral Carbonation Environ. Sci. Technol. 2009 43 1986 1992 10.1021/es802910z 19368202 25. Pacheco-Torgal F. Shi C. Palomo A. Carbon Dioxide Sequestration in Cementitious Construction Materials Woodhead Publishing Sawston, UK 2018 978-0-08-102447-8 26. Wang Y. Liu X. Zhang W. Li Z. Zhang Y. Li Y. Ren Y. Effects of Si/Al ratio on the efflorescence and properties of fly ash based geopolymer J. Clean. Prod. 2020 244 118852 10.1016/j.jclepro.2019.118852 27. Zhang D. Shao Y. Early age carbonation curing for precast reinforced concretes Constr. Build. Mater. 2016 113 134 143 10.1016/j.conbuildmat.2016.03.048 28. ASTM C566-19 Test Method for Total Evaporable Moisture Content of Aggregate by Drying ASTM International West Conshohocken, PA, USA 2019 10.1520/C0566-19 29. Xue X. Liu Y.-L. Dai J.-G. Poon C.-S. Zhang W.-D. Zhang P. Inhibiting efflorescence formation on fly ash–based geopolymer via silane surface modification Cem. Concr. Compos. 2018 94 43 52 10.1016/j.cemconcomp.2018.08.013 30. Zhang Z. Provis J.L. Ma X. Reid A. Wang H. Efflorescence and subflorescence induced microstructural and mechanical evolution in fly ash-based geopolymers Cem. Concr. Compos. 2018 92 165 177 10.1016/j.cemconcomp.2018.06.010 31. Najafi Kani E. Allahverdi A. Provis J.L. Efflorescence control in geopolymer binders based on natural pozzolan Cem. Concr. Compos. 2012 34 25 33 10.1016/j.cemconcomp.2011.07.007 32. Yao X. Yang T. Zhang Z. Compressive strength development and shrinkage of alkali-activated fly ash–slag blends associated with efflorescence Mater. Struct. 2016 49 2907 2918 10.1617/s11527-015-0694-3 33. ASTM D3875-15 Test Method for Alkalinity in Brackish Water, Seawater, and Brines ASTM International West Conshohocken, PA, USA 2017 10.1520/D3875-15 34. C01 Committee Test Method for Compressive Strength of Hydraulic Cement Mortars (Using 2-in. or [50-mm] Cube Specimens) ASTM International West Conshohocken, PA, USA 2020 10.1520/C0109_C0109M-20B 35. Zhang J. Shi C. Zhang Z. Effect of Na2O concentration and water/binder ratio on carbonation of alkali-activated slag/fly ash cements Constr. Build. Mater. 2021 269 121258 10.1016/j.conbuildmat.2020.121258 36. Zhang Z. Wang H. Provis J.L. Quantitative study of the reactivity of fly ash in geopolymerization by FTIR J. Sustain. Cem. Based Mater. 2012 1 154 166 10.1080/21650373.2012.752620 37. Ashraf W. Carbonation of cement-based materials: Challenges and opportunities Constr. Build. Mater. 2016 120 558 570 10.1016/j.conbuildmat.2016.05.080 38. Fernández Bertos M. Simons S.J.R. Hills C.D. Carey P.J. A review of accelerated carbonation technology in the treatment of cement-based materials and sequestration of CO2 J. Hazard. Mater. 2004 112 193 205 10.1016/j.jhazmat.2004.04.019 15302440 39. Montes-Hernandez G. Pérez-López R. Renard F. Nieto J.M. Charlet L. Mineral sequestration of CO2 by aqueous carbonation of coal combustion fly-ash J. Hazard. Mater. 2009 161 1347 1354 10.1016/j.jhazmat.2008.04.104 18539389 40. Mazzella A. Errico M. Spiga D. CO2uptake capacity of coal fly ash: Influence of pressure and temperature on direct gas-solid carbonation J. Environ. Chem. Eng. 2016 4 4120 4128 10.1016/j.jece.2016.09.020 41. Bernal S.A. Provis J.L. Walkley B. San Nicolas R. Gehman J.D. Brice D.G. Kilcullen A.R. Duxson P. van Deventer J.S.J. Gel nanostructure in alkali-activated binders based on slag and fly ash, and effects of accelerated carbonation Cem. Concr. Res. 2013 53 127 144 10.1016/j.cemconres.2013.06.007 42. Shi Z. Shi C. Wan S. Li N. Zhang Z. Effect of alkali dosage and silicate modulus on carbonation of alkali-activated slag mortars Cem. Concr. Res. 2018 113 55 64 10.1016/j.cemconres.2018.07.005 43. Zhang J. Shi C. Zhang Z. Carbonation induced phase evolution in alkali-activated slag/fly ash cements: The effect of silicate modulus of activators Constr. Build. Mater. 2019 223 566 582 10.1016/j.conbuildmat.2019.07.024 44. Sarkar A. Mahapatra S. Synthesis of All Crystalline Phases of Anhydrous Calcium Carbonate Cryst. Growth Des. 2010 10 2129 2135 10.1021/cg9012813 45. Nedeljković M. Šavija B. Zuo Y. Luković M. Ye G. Effect of natural carbonation on the pore structure and elastic modulus of the alkali-activated fly ash and slag pastes Constr. Build. Mater. 2018 161 687 704 10.1016/j.conbuildmat.2017.12.005 46. Sˇauman Z. Lach V. Long-term carbonization of the phases 3CaO·Al2O3·6H2O and 3CaO·Al2O3·SiO2·4H2 Cem. Concr. Res. 1972 2 435 446 10.1016/0008-8846(72)90058-0 47. Bernal S.A. Provis J.L. Brice D.G. Kilcullen A. Duxson P. van Deventer J.S.J. Accelerated carbonation testing of alkali-activated binders significantly underestimates service life: The role of pore solution chemistry Cem. Concr. Res. 2012 42 1317 1326 10.1016/j.cemconres.2012.07.002 48. Hidalgo A. Domingo C. Garcia C. Petit S. Andrade C. Alonso C. Microstructural changes induced in Portland cement-based materials due to natural and supercritical carbonation J. Mater. Sci. 2008 43 3101 3111 10.1007/s10853-008-2521-5 49. White C.E. Daemen L.L. Hartl M. Page K. Intrinsic differences in atomic ordering of calcium (alumino) silicate hydrates in conventional and alkali-activated cements Cem. Concr. Res. 2015 67 66 73 10.1016/j.cemconres.2014.08.006 50. Dimas D. Giannopoulou I. Panias D. Polymerization in sodium silicate solutions: A fundamental process in geopolymerization technology J. Mater. Sci. 2009 44 3719 3730 10.1007/s10853-009-3497-5 51. Ye H. Cai R. Tian Z. Natural carbonation-induced phase and molecular evolution of alkali-activated slag: Effect of activator composition and curing temperature Constr. Build. Mater. 2020 248 118726 10.1016/j.conbuildmat.2020.118726 52. Zhang Z. Wang H. Provis J.L. Bullen F. Reid A. Zhu Y. Quantitative kinetic and structural analysis of geopolymers. Part 1. The activation of metakaolin with sodium hydroxide Thermochim. Acta 2012 539 23 33 10.1016/j.tca.2012.03.021 53. Andersen F. Brečević L. Infrared Spectra of Amorphous and Crystalline Calcium Carbonate ChemInform 1992 23 10.1002/chin.199209005 54. Qu Z.Y. Gauvin F. Wang F.Z. Liu G. Brouwers H.J.H. Effect of hydrophobicity on autogenous shrinkage and carbonation of alkali activated slag Constr. Build. Mater. 2020 264 120665 10.1016/j.conbuildmat.2020.120665 55. Lee W.K.W. van Deventer J.S.J. Use of Infrared Spectroscopy to Study Geopolymerization of Heterogeneous Amorphous Aluminosilicates Langmuir 2003 19 8726 8734 10.1021/la026127e 56. Van Jaarsveld J.G.S. Van Deventer J.S.J. Schwartzman A. The potential use of geopolymeric materials to immobilise toxic metals: Part II. Material and leaching characteristics Miner. Eng. 1999 12 75 91 10.1016/S0892-6875(98)00121-6 57. Zuo Y. Nedeljković M. Ye G. Coupled thermodynamic modelling and experimental study of sodium hydroxide activated slag Constr. Build. Mater. 2018 188 262 279 10.1016/j.conbuildmat.2018.08.087 58. Rey F. Fornés V. Rojo J.M. Thermal decomposition of hydrotalcites. An infrared and nuclear magnetic resonance spectroscopic study J. Chem. Soc. Faraday Trans. 1992 88 2233 2238 10.1039/FT9928802233 59. Johnson D.R. Robb W.A. Gaylussite: Thermal properties by simultaneous thermal analysis Am. Mineral. 1973 58 778 784 60. Sharma S.K. Jotshi C.K. Kumar S. Thermal stability of sodium salt hydrates for solar energy storage applications Sol. Energy 1990 45 177 181 10.1016/0038-092X(90)90051-D 61. Kim G.M. Jang J.G. Naeem F. Lee H.K. Heavy Metal Leaching, CO2 Uptake and Mechanical Characteristics of Carbonated Porous Concrete with Alkali-Activated Slag and Bottom Ash Int. J. Concr. Struct. Mater. 2015 9 283 294 10.1007/s40069-015-0111-x 62. Šauman Z. Carbonization of porous concrete and its main binding components Cem. Concr. Res. 1971 1 645 662 10.1016/0008-8846(71)90019-6 63. Johannesson B. Utgenannt P. Microstructural changes caused by carbonation of cement mortar Cem. Concr. Res. 2001 31 925 931 10.1016/S0008-8846(01)00498-7

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094937 ijms-23-04937 Review Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? https://orcid.org/0000-0002-4818-9047 Halder Amit Kumar 12 Moura Ana S. 1 https://orcid.org/0000-0003-3375-8670 Cordeiro Maria Natália D. S. 1* Rahimi-Gorji Mohammad Academic Editor 1 LAQV@REQUIMTE, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal; amit.halder@fc.up.pt (A.K.H.); ana.cristina.moura@fc.up.pt (A.S.M.) 2 Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713212, West Bengal, India * Correspondence: ncordeir@fc.up.pt; Tel.: +35-12-2040-2502 29 4 2022 5 2022 23 9 493728 3 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Conventional in silico modeling is often viewed as ‘one-target’ or ‘single-task’ computer-aided modeling since it mainly relies on forecasting an endpoint of interest from similar input data. Multitasking or multitarget in silico modeling, in contrast, embraces a set of computational techniques that efficiently integrate multiple types of input data for setting up unique in silico models able to predict the outcome(s) relating to various experimental and/or theoretical conditions. The latter, specifically, based upon the Box–Jenkins moving average approach, has been applied in the last decade to several research fields including drug and materials design, environmental sciences, and nanotechnology. The present review discusses the current status of multitasking computer-aided modeling efforts, meanwhile describing both the existing challenges and future opportunities of its underlying techniques. Some important applications are also discussed to exemplify the ability of multitasking modeling in deriving holistic and reliable in silico classification-based models as well as in designing new chemical entities, either through fragment-based design or virtual screening. Focus will also be given to some software recently developed to automate and accelerate such types of modeling. Overall, this review may serve as a guideline for researchers to grasp the scope of multitasking computer-aided modeling as a promising in silico tool. multitasking in silico modeling moving average approach virtual screening software FCT/MCTESUIDB/50006/2020 UIDB/50006/2020 This work was supported by UIDB/50006/2020 with funding from FCT/MCTES through national funds. Ana S. Moura also acknowledges IF CEECIND/03631/2017. ==== Body pmc1. Introduction The current year marks 60 years of the onset of two-dimensional quantitative structure–activity relationship (2D-QSAR) modeling, following the pioneering work of Hansch in 1962 [1]. In fact, Hansch’s work has paved the way for computer-aided drug design endeavors that, since then, have been enriched by several other ligand-based (e.g., 3D-6D QSAR, pharmacophore mapping, etc.) and structure-based (e.g., molecular docking, molecular simulations, homology modeling, etc.) methodologies [2,3,4]. However, the advent of these relatively new in silico approaches does not definitely extinguish the relevance of 2D-QSAR modeling in computational chemistry [5]. Rather, owing to its simple and versatile nature, the practice of 2D-QSAR modeling has been expanding and is applied now to numerous different areas of science such as nanotechnology, materials, environment, and so forth [2]. Even for the drug discovery and development process, where the researchers have many other in silico alternatives, 2D-QSAR still offers fast and effective solutions [6,7]. While the primary objective remained unchanged, i.e., the consistent prediction of response variable(s), it is undeniable that the past few decades have witnessed a variety of progress in concepts and applications of 2D-QSAR modeling [3]. Modern 2D-QSAR practices now embody a set of in silico modeling tools in which statistical and/or machine learning techniques are applied to derive relationships between the targeted response variable(s) and the descriptors encoding molecular structural attributes and properties. Naturally, the reliability of these in silico modeling tools largely depend on the size and diversity of the datasets employed [2]. Indeed, due to the steady growth of available data, ‘big-data’ became a new trend for in silico modeling tools that in turn have been fueled by numerous advances in computational efficiency as well as in model development strategies. However, resorting to big data does not always ensure an improvement of the applicability of the derived models since variations in the experimental (or theoretical) conditions used to determine the response variable(s) are often ignored [8]. That is why strategic data integration-based in silico modeling approaches appear promising [8,9,10], mainly because they do not only help to increase the size and diversity of the targeted data but at the same time, account for the variations that are frequently encountered while merging data collected from several sources [11,12]. Multitarget or multitasking (mtk) in silico modeling is a comparatively novel advanced strategy that allows the merging of datasets pertaining to multiple conditions to simultaneously predict the response variable(s) under such diverse conditions [2,13,14,15]. The present review covers the main aspects of multitasking classification modeling based on the Box–Jenkins moving average approach, since the latter has emerged as one of the simplest approaches for building up unique 2D-QSAR models from large heterogeneous datasets with multiple features [15,16]. Apart from discussing the objectives, methodologies and applications, the review also sheds light on the software recently developed for supporting and facilitating mtk-QSAR analyses. The future scope of such multitasking modeling is also discussed in detail. It is important to mention here that the application of perturbation theory along with machine learning techniques (PTML), as well as those combined with the information fusion technique (PTMLIF), also falls within the scope of the Box–Jenkins-based multitasking modeling, but such methodologies have been thoroughly reviewed very recently [10] and have thus been excluded to maintain brevity of this review. 2. Multitasking QSAR Modeling: Rationale and Existing Challenges In silico QSAR modeling stands for the common practice of looking for relationships between the endpoint (EP) response(s) of interest and descriptors encoding the molecular structures (S) and properties (P) of a set of chemicals, through multivariate statistical methods and/or machine learning techniques [2,17]. These relationships aiming at either classification-based or quantitative predictions of the response(s) values pertain then to mathematical models as follows:EP = f (S,P) (1) in which EP is considered to be only a function of S and P. However, it is well known that the response(s) values clearly depend on the type of experimental procedures or theoretical calculations employed or even if following the same type of protocol but in different conditions (C). Therefore, with a larger perspective, the mathematical models are to be described as follows:EP = f (S,P,C)(2) The workflow usually tracked for setting up QSAR models begins by assembling the chemicals with known EP response(s) to form a dataset and in so doing, one frequently encounters very dissimilar conditions. Conventional QSAR modeling, often referred to as ‘one target’ or ‘single-task’ in silico modeling, relies primarily on assuming similarity in the experimental and/or theoretical conditions that often ends up limiting the inclusion of small datasets. Even if datasets with multiple experimental/theoretical conditions are being included, the influence of their variation is frequently ignored. As explained hereafter, the moving average-based multitasking (MA-mtk) in silico modeling tends to overcome such limitations [12,13]. Firstly, small datasets with large variations in the experimental and/or theoretical protocols followed can be conveniently accommodated in the modeling datasets, thereby enhancing their diversity as well as the applicability of the following in silico models. Therefore, a shortage of data for a specific experimental/theoretical condition does not pose any challenge for the modeler. This may be exemplified from a recently reported study [18], in which the primary objective was to characterize the cytotoxicity of acrylic acid-based dental monomers through QSAR modeling. The maximum number of data points found for compounds assayed against one single type of cell line was 39, using the same biological measurement, but when the cytotoxicity against other cell lines ought to be included, a dataset of 138 data points could be built. Since this larger dataset included information pertaining to as many as 18 different cell lines probed by five types of measurements, it seemed worthwhile resorting to a moving average-based multitasking approach to retrieve a more reliable QSAR model as compared to a single-task model, aside from covering a larger response and experimental space [19]. Secondly, one unique mtk-QSAR model is capable of predicting multiple outcomes simultaneously and the models’ descriptors may serve as ‘global descriptors’ to derive general and holistic mechanistic interpretations for the endpoint response(s), which may be disconnected on the grounds of conditions but are likely to be linked with each other regarding mechanism(s) of action [8,20]. Finally, multitasking QSAR modeling improves the scope of virtual screening since the virtual hits that are obtained display predictivity against several different conditions. Therefore, the modelers are left with the options to select those hits that are predicted to have positive responses either against all/maximum conditions (for the design of pan-inhibitors, for example) or against some specific conditions (e.g., for choosing isoform specific inhibitors) depending on the aim of the investigation [21,22]. Nevertheless, one may face several challenges while developing moving average-based multitasking in silico models as not only additional steps are involved but additional statistical and validation criteria are also to be satisfied, when compared to conventional ‘single-task’ in silico modeling [19]. It must be emphasized that similar to conventional QSAR approaches, MA-mtk modeling follows the best practices outlined by the Organization for Economic Co-Operation and Development (OECD), which state that each model should have a defined end point, an unambiguous algorithm with a defined domain of applicability, goodness of fit, robustness and predictive ability, as well as a mechanistic interpretation, if possible [23]. The main challenge lies in the fact that the decision regarding some choices may vary from one investigation to another and a general consensus is difficult to achieve. For example, in the initial stages, the modeler needs to decide how many experimental and/or theoretical conditions are to be taken into account for the modeling. Variations in the biological targets, types of biological measurements, and experimental protocols are often easily identified as possible experimental conditions but such selection may vary depending on the investigation purpose. Furthermore, such selection of experimental (theoretical) conditions often depends on the availability of information in the literature or databases. On the other hand, since the moving average-based mtk-QSAR approach discussed in this review aims at developing classification-based models, the selection of acceptable cut-off values for the response variable(s) becomes crucial. Naturally, such selection is expected to vary in different studies and research. Recently, Kleandrova et al. recommended that for drug-design purposes, the selected cut-off values should be set at least at the sub-micromolar level and at the same time, the chosen cut-offs should prevent any excessive imbalance between the number of chemicals assigned as active/positive and those assigned as inactive/negative [24]. Another key challenge is to ensure that the predictivity of the so derived models may be overestimated on the basis of some experimental and/or theoretical conditions. The chance is higher because this type of in silico modeling constitutes a single computational framework that yields a unique model and thus, it is likely that low predictive accuracy against some conditions is overshadowed by the high accuracy over other conditions. Ideally, the model should uniformly predict all experimental and/or theoretical conditions. To tackle this challenge, the ‘condition-wise prediction’ strategy has recently been introduced since it readily provides predictions of the model versus each considered condition [12,25]. After carefully checking the results, the conditions with poor prediction statistics may be identified as outliers and at least a warning may be provided to avoid making predictions with such conditions [18,21,25]. 3. Multitasking In Silico Modeling Methodologies 3.1. Moving Average Approach The moving average (MA) approach is fundamental for developing multitasking models through data-integration, including PTML-based modeling efforts [10,13]. In such an approach, the descriptors are transformed in a way so that these encode information about both the compounds’ structures and the experimental/theoretical conditions under which their response variable(s) have been attained. Therefore, even if the same chemical compound displays two different endpoint responses pertaining to two different conditions, the MA approach must generate two different descriptors for it. Originally, the Box–Jenkin’s moving average (BJMA) approach has been delineated for time-series analysis, that is, based on computing successive average values of a defined system property to forecast its value at a different time [13,26]. In MA-mtk modeling, the Box–Jenkin’s operation is not related to the time domain but instead rather to the various targeted experimental and/or theoretical conditions. Even though a range of BJMA schemes have so far been employed, all of these originated from the following formula:∆(Di)cj = Di − avg(Di)cj(3) Therefore, the new descriptors ∆(Di)cj, also referred to as ‘deviation descriptors’, are calculated by subtracting from the input descriptors (Di) the avg(Di)cj values, in which the latter stands for the arithmetic mean of active/positive data points of a specific element of the experimental and/or theoretical conditions (ontology). Along with ∆(Di)cj, the avg(Di)cj values have also been used as descriptors in previous works [27,28]. Other operators that have recently been employed are basically modified forms of this formula, corresponding to normalizations of the original operator with respect to the variation in sample size against each condition and/or Di values (see Table 1). Still, there is not enough evidence to prove that these modified operators may actually give rise or not to better statistical models than the original operator. In a recent study, a comparative analysis was carried out using some of these modified BJMA operators but a large variation in the predictive accuracy of the derived models was not observed [12]. Yet, the importance of such modifications in developing more predictive models may not be ruled out entirely. 3.2. Descriptor Calculation The role of the original descriptors (Di) should not be overlooked in multitasking QSAR modeling even though these are transformed by BJMA. Note that due to the nature of the moving average approach already discussed, descriptors with high variances should be preferred for modeling since near-constant descriptors may fail to provide information about the experimental systems. This is why a number of mtk-QSAR models were developed using 2D-atom and bond-based topological, as well as 2.5D chiral algebraic molecular descriptors. Open-access Java-based tools such as QuBiLS-MAS and MODESLAB have been extensively employed to develop mtk-QSAR models since these software tools allow the computing of a large number of unique graph-based topological descriptors [36,37,38]. Software such as Dragon [39] has also a long history in setting up QSAR models with a large number of descriptors that belong to various categories (e.g., constitutional, atom-based fragments, geometrical, topological, etc.). Moving average-based multitasking QSAR modeling is no exception and several models have been reported lately, using such DRAGON descriptors. As such, it can be judged that there are no restrictions on the type of descriptors to be employed in MA-mtk in silico modeling but no matter what type of descriptor is used, pre-treatment is required to remove the near-constant descriptors. Here, it is important to mention that even though moving average approaches help in merging the information pertaining to experimental conditions with that of the original descriptors Di for jointly handling structural and physicochemical properties, the mechanistic interpretation of the new descriptors ∆(Di)cj becomes much more complicated. Simply put, these new descriptors explain the contribution of the original descriptors Di with respect to the experimental elements cj. In fact, ∆(Di)cj descriptors built with the same Di values but with different experimental elements (cj) were found in some models. From one side, these models are clearly justified by the ability of such variables towards usefully predicting the desired endpoints, though with costs regarding their mechanistic interpretation. For example, in one work [21] two different descriptors ∆(C-012)me and ∆(C-012)bt appeared in the same model with opposite correlation with the response variable. Therefore, it was inferred that the molecular fragment descriptor C-012 improves the biological activity when it is associated with the experimental condition—a kind of measurement of effects (me), whereas it deteriorates it when the same descriptor is related to another experimental condition as the assay types (at). Similar to conventional QSAR modeling, models containing a smaller number of simpler descriptors are preferred. For example, in a very recently published study [40], the authors developed two non-linear models with almost similar statistical results. One of these was preferred over the other since it consisted of a smaller number of descriptors and, at the same time, it provided a simpler and more detailed mechanistic interpretation for the dataset. 3.3. Data Pooling, Databases, and Inclusion/Exclusion Criteria Dataset collection and curation are undeniably crucial in MA-mtk in silico modeling. Whenever endpoint responses are aimed to be modeled, one may rely upon databases of compounds, such as the databases ChEMBL (https://www.ebi.ac.uk/chembl/), BindingDatabase (https://www.bindingdb.org/bind/index.jsp), or AFLOW (http://aflowlib.org/), for a quick retrieval of data points. However, often datasets are required to be manually collected from the literature. Unlike conventional in silico modeling, MA-mtk modeling incurs risks when merging data points coming from diverse experimental and/or theoretical conditions and therefore, the curation of the datasets needs to be carefully performed. That is, one specific compound may be placed in the dataset for MA-mtk modeling multiple times only if it leads to data points pertaining to different conditions. If one compound is found to have the same categorical end-point with respect to the same experimental and/or theoretical conditions, only one data point is retained, for obvious reasons. However, given the same experimental/theoretical conditions, if two different categorical end-points (for example, one active and another inactive) are found, both such data points should be excluded to avoid inconsistent outcomes. In the latter case, it is always better to fully inspect the reported investigations where such large variations in results have been obtained and try to address what could have caused the variations before including their data in the modeling dataset. 3.4. Dataset Division Another important consideration is, of course, in regard to dataset division. In one approach, the entire modeling set is used for deriving the models and then the dataset is divided into a training and a prediction set [41,42,43]. Alternatively, a second approach may be adopted where the dataset is first divided into a modeling set and an external validation set. The modeling set is only used for computing the avg(Di)cj descriptors and subsequently the values of those are used in the calculation of ∆(Di)cj descriptors for both the modeling and the external validation set [11,12,18]. In this second approach, the external validation set has no role either in the model development or descriptor generation, and thus it can be regarded as a true validation set. Noticeably, in such an approach, avg(Di)cj is fixed and any new compound can then be directly fitted with the developed model for its prediction. One should note, however, that the modeling dataset may be further divided into a training and a test set, where the latter may serve multiple purposes. Firstly, it can act as an additional validation set and if similarity is reached regarding the predictive accuracy between this test and the external validation set, that thereby further justifies the consistent prediction of the models, irrespective of which dataset division approach is adopted. Actually in a previous work, we found that, for most cases, the predictive accuracy of test and external validation sets are remarkably close to each other. On the other hand, such a test set may also serve as a calibration set for selecting the best model out of many possible. Some methods, such as the PS3M later described or hyperparameter optimization for machine learning techniques, often require calibration and the test set may thus be utilized to ensure better performance of these techniques [11,12,18,25]. 3.5. Set-Up of the MA-Mtk Model Undoubtedly, robust model development strategies are required for setting up moving average-based mtk-QSAR models, since the number of input descriptors are actually multiplied based on the number of experimental conditions. Due to the same reason, effective variable selection procedures should be employed for building linear or non-linear interpretable models with a limited number of features. Forward selection strategies such as the fast stepwise selection algorithm have been successfully employed initially to develop linear discriminant analysis (LDA) models using commercial software packages [27,37]. However, a more advanced stochastic approach, such as the genetic algorithm, later proved to be an extremely useful alternative and was applied on the open source software QSAR-Co for setting up LDA-based mtk-QSAR models [44]. Recently, two non-stochastic approaches, namely the fast stepwise (FS) and sequential forward selection (SFS) algorithms, were available for establishing LDA models in another open source software QSAR-Co-X [12]. Both stochastic and non-stochastic strategies have their advantages and disadvantages. For example, the stochastic GA variable selection approach lacks reproducibility and it is not known a priori how many runs are needed to reach the best LDA model, meaning that it might be needed to be repeated several times [12]. Nevertheless, due to its unique feature selection methodology, the chance of obtaining a highly predictive LDA model with GA is remarkably high, especially when other strategies fail to develop predictive models from a large number of independent parameters. In contrast, with the same parameter settings, the FS or SFS variable selection algorithms are always reproducible and the corresponding LDA models are also easily obtained. Yet, no feature selection algorithm is flawless and comparative analysis may be the only way to retrieve the most predictive linear model [30]. Very recently, a post-selection similarity search-based modification strategy (so-called PS3M) has been proposed with the hypothesis that, no matter what variable selection algorithm is employed, the model produced should be treated as a reference model that itself is not the best model but it should be similar to the best model [18]. As such, descriptors which are similar or highly correlated to each descriptor of the model are firstly searched using a Euclidian distance scheme. Subsequently, each original model descriptor is replaced with its similar descriptors found and the resulting modified models checked to see if they have better statistical quality or not. If a better model is obtained, it is automatically treated as a reference model and the same steps repeated until no better model is obtained. As of now, PS3M appears as a promising strategy, especially when a large pool of descriptors is employed and therefore its potential in mtk-QSAR modeling may not be ignored [18,21]. Apart from the selection schemes referred, the Shannon entropy has also been used in research for the most discriminating features to set-up non-linear models [33,45]. Even though non-linear models developed with a maximum pool of descriptors, the latter abolishes the mechanistic interpretability and, therefore, feature-selection strategies are often employed to establish models with a limited number of variables that afford highlighting of the most significant descriptors. Similarly, several advanced machine learning (ML) tools have been applied to search the most predictive non-linear models (see Table 2), which at the cost of mechanistic interpretability produce highly predictive mtk-QSAR models [12,25]. So far, ML techniques such as artificial neural networks and tree-based techniques such as random forests (RF) and gradient boosting have proven to be the most successful ones [18,21,24,33,41,42,43,46]. In a recent work, even though deep neural networks gave rise to a highly predictive model its predictivity was similar to the RF model, which was ultimately reported [21]. Thus, deep learning may play an important role in future developments of MA-mtk models [2]. Due to the complex nature of the data-matrices involved in this type of in silico modeling, it is always advisable that along with deploying multiple ML strategies, hyperparameter tuning should also be taken into consideration for optimizing the parameters to obtain the validated models [12]. For example, in one recent investigation [18], six different ML methods (i.e., RF, GB, SVM, kNN, NB and ANN) were employed with hyperparameter optimization to develop non-linear models and it was the ANN model that afforded the most predictive model. In another study [25], seven different ML methods were employed with hyperparameter optimization, and the internal predictivity (confirmed by 10-fold cross-validated accuracy) was as follows: GB (91.54%) > RF (91.02%) > DT (84.33%) > ANN (82.97%) > kNN (79.20%) > NB (69.40%) > SVM (62.30%). It is noticeable that even with hyperparameter optimization, large variations in predictivity may be observed when one switches from one ML tool to another. Therefore, the application of multiple robust ML methods definitely improves the scope of reaching better predictive models. 3.6. Statistical Analysis and Validation The statistical quality of both linear and non-linear mtk-QSAR classification models can be judged in terms of the criteria goodness-of-fit and goodness-of-prediction. Goodness-of-fit is frequently checked by standard statistics such as the Wilks’ lambda (λ), chi-square (χ2), the Fisher ratio (F), and the corresponding p-level (p). Similarly, the predictive accuracy of the models is commonly estimated by means of the confusion matrix that comprises the number of true positives (TP), true negatives (TN), false positives (FP), false negatives (FN), and allows then to compute other statistics such as the accuracy (Acc), the Matthews correlation coefficient (MCC), and so forth [25,44]. The moving average methodology generally gives rise to highly correlated modified variables and data pretreatment is thus required to remove such redundant features. In particular, the proposed linear model should also be assessed for chance correlation by the Y-randomization test [44], recently modified for mtk-QSAR modeling to also consider the role of experimental conditions (cj). In this modified test, so called Y randomization with conditions (Yc) [12], the response variable(s) along with the experimental elements are scrambled to generate multiple randomized data-matrices. New models, based on the fits to these scrambled data-matrices, are then calculated using the same original model descriptors. A high difference between the statistical parameters (i.e., λ and Acc) of the new models and the original model then conveys its robustness [12]. The range of validity of a QSAR model must be well assayed, in terms of the range of biological response data within, it will predict reliably and also in terms of the type of chemical structure on which it is based. No in silico QSAR model is meant to predict the whole range of possible chemicals and targeted response(s). That is, any QSAR model must have a defined applicability domain (AD). From the viewpoint of mt-QSAR modeling, the AD is the endpoint response(s) and experimental (theoretical) space within which the model can make trustworthiness predictions. A number of strategies have so far been applied to define the AD of QSAR models and none of these has proven to be superior to others [47]. Two different ways may be used to determine the applicability domain of the MA-mtk models. The first one is essentially defined by the experimental elements since it is always advisable to consider only external validation compounds that follow the same experimental and/or theoretical conditions under which the modelling dataset samples have been obtained. Structural outliers are generally identified through the same procedures by which conventional classification-based QSAR models are (e.g., the leverage approach). However, AD determination methods may vary depending on the type of model, i.e., linear or non-linear models. For linear models, the AD set by the standardization method proposed by Roy et al. [48] has lately been applied in several studies [11,12,18]. In contrast, the AD of non-linear models is difficult to define but techniques such as the confidence estimation approach [49] can be used to identify structural outliers [12,44]. Recently, another method for establishing the AD of any type of model has been suggested, in which local binary scores are calculated for its descriptors based on their minimum and maximum values. Subsequently, these scores are summed up to obtain a total score from which the outliers are detected as the latter should have a total score less than this [38]. 4. Applications of Mtk-QSAR Modeling A considerable number of mtk-QSAR models based on the moving average approach have been developed and proposed in the last 10 years for tackling a wide range of applications, such as drug design and development, toxicology, and environmental sciences, including nanotechnology. For the sake of discussion, in this section, such mtk-QSAR models will be divided into two main categories considering the main objective of the study, namely as targeting the activity against cells, organisms, and species (a), or that against bio-macromolecular targets (b). There are however some investigations that fall into both categories [28,43,50,51,52,53]. Most of these models have been developed by collecting data from the CHEMBL database, which is regarded as one of the largest and most reliable databases to date. 4.1. MA-Mtk Modeling of the Activity against Cells/Organisms/Species Due to a complex bio-functional mechanism, the activity of a compound may vary from one cell to another as often observed in research focused on the anticancer or antimicrobial properties of chemicals [27,33]. Therefore, a major focus has been invested in applying multitasking modeling for predicting the antiproliferative or antimicrobial activity of compounds against various cells (i.e., mammalian or microbial). Let us start with a fragment-based mtk-QSAR modeling study reported in 2011, based on a dataset containing 449 compounds with measured cytotoxicity against twelve different mammalian sarcoma cells (making a total of 3017 data points) [27]. In this study, just one particular category of descriptors was employed, namely substructural descriptors comprising functional group counts, atom centered fragments and spectral moments of the bond adjacency matrix. Among these, only the spectral moment descriptors were subjected to the moving average approach to derive avg(Di)cj as well as ∆(Di)cj descriptors. Combining these different classes of descriptors and by adopting a linear discriminant analysis (LDA), an interpretable model with a pool of thirteen descriptors was finally built that demonstrated consistent accuracy of ca. 91 and 90% over the training (Ntraining = 1887) and test (Ntest =1130) data-point sets, respectively. A similar methodology was followed in the next few years to develop predictive mtk-QSAR models based on datasets of chemicals with tested antiproliferative potential against prostate carcinoma cells [54], breast carcinoma cells [55], gliomas [56], colorectal carcinoma cells [57] and bladder cancer cells [58]. A couple of remarks from these studies are picked out here. First, these mtk-QSAR models have always been derived by resorting to deviation descriptors. Second, in some of the later studies, an artificial neural network (ANN) methodology has also been employed to set-up non-linear models with selected features. In fact, the non-linear models obtained through including a larger number of ∆(Di)cj features displayed a higher predictive accuracy as compared to their LDA counterparts. These remarks clearly indicate the significance of ∆(Di)cj descriptors. Furthermore, despite the fact that such models were based on a considerably large number of data points, all depicted an overall predictive accuracy higher than 85% and the majority of them attained an accuracy above 90%. Worth mentioning as well here, is that the antiproliferative potential of chemicals is a difficult biological property to target from a computer-aided modeling point of view, due to the fact that numerous biochemical mechanisms may be involved. Therefore, from this aspect, the performance of all these models should be considered as highly satisfactory. What is more, one should highlight the advantage of resorting to fragment-based descriptors in mtk-QSAR modeling, that is, the possibility of estimating the contributions of different fragments to the biological activity studied that can be employed as 2D pharmacophores for designing new possible leads. As an example, Figure 1 shows new anti-breast cancer leads suggested following that strategy, based on their fragment contributions [55]. More recently, Kleandrova et al. reported a multitasking modeling study with the aim of simultaneously predicting the inhibitory activity of chemicals against various liver cancer cell lines [32]. The dataset used in this study was collected from the Genomics of Drug Sensitivity in Cancer (GDSC) and contained 192 (FDA approved or experimental) drugs that have been assayed against 17 different liver cancer cell lines, resulting in a total of 3079 data points. Furthermore, only ∆(Di)cj descriptors derived from total and local (atom-based) non-stochastic quadratic indices were chosen to build non-linear classification models using ANN. The best mtk-QSAR model found contained nine descriptors and gave rise to a moderate predictivity (ca. 85% overall accuracy) but enabled the virtual design of six new promising anticancer agents against the liver cancer cell lines considered. A significant number of multitasking modeling studies based on the moving average approach have been performed to probe antimicrobial and antiviral activities in the last 10 years [31,50,51,52,53,59,60,61,62,63,64,65,66]. Table 3 displays the details of the methodology employed, the studied endpoint responses, and bio-targets considered, per year. While the evidence of a preference for ANN-based models is observed in certain instances, FS-LDA is the most usual choice for the methodological approach to be followed. The type of endpoints investigated also covered a wide range apart from the antimicrobial or antiviral activities, ranging from solely toxicity properties to absorption, distribution, metabolism, elimination, and toxicity (ADMET) since the latter play a key role on guiding hit-to-lead and lead-optimization efforts, and on average the predictive accuracy for these models was in the proximity of 90% or greater. However, some of the works had particular aspects that needed more detailed address. Regarding antimicrobial peptides (AMP) [50,64], since they have a unique structural nature, as an approach to effectively compute the challenging AMP molecular descriptors, the peptide sequences were first converted to FASTA sequences, which were subsequently converted to 3D formats for the calculation of topological indices (e.g., Kier–Hall indices and Broto–Moreau autocorrelations) that were then subjected to the BJMA technique. Both works adopted the strategy of collecting AMPs from the Database of Antimicrobial Activity and Structure of Peptides (DBAASP), and the models exhibited a predictive accuracy higher than 90% in both the training and prediction sets. Another team established as its main goal to generate complex networks of AIDS incidence among USA counties, relative to the preclinical activity of drugs against the human immunodeficiency virus (HIV) [62]. Several ANNs have been trained for such a purpose, using as input information the indices of social networks (taken from public epidemiological databases) and molecular graphs (i.e., Balaban information indices to describe the chemical structures of anti-HIV drugs). The best mtk-QSAR found was a linear ANN and exhibited an overall accuracy of ca. 80%. Moreover, the drug–county network built from such a model supplied useful information about the most effective drugs to treat HIV in different populations (from the US counties) with a given epidemiological prevalence. Another work that was published more recently, in 2017, is also worth mentioning here [31]. Given the fact that Hepatitis C is one of the deadliest, unresolved health problems globally, the modeling addressed both the anti-Hepatitis C potency and ADMET profiles of several chemicals collected from ChEMBL by considering also their testing conditions, namely: the types of biological measurements, different bio-targets, information regarding the assays (labeling whether the assay focused on the study of binding phenomena, functional/physiological responses, or ADMET profiles), as well as the involved target mappings. Furthermore, this work, apart from considering the latter experimental conditions, modified the moving average formulae by multiplying the deviation descriptors with a probabilistic factor (pc) denoting the degree of reliability of the experimental assay (i.e., autocuration, intermediate, and expert, respectively). As such, the best FS-LDA-based linear model found (40,158 data points), developed with topological descriptors known as bond-based quadratic indices [36], afforded an overall accuracy higher than 95%. Notwithstanding, all of the above-mentioned investigations developed the MA-mtk models with relatively large datasets, something that was not the case for two recent reports, one that involved the environmental toxicity of deep eutectic solvents [66] and another about the cytotoxicity of acrylic acid-based dental monomers, this latter with only 138 data points [18]. As the last dataset was highly inhomogeneous in nature, given the fact that 58 different chemicals were tested against 18 different cell lines with five different types of measurements, apart from model generation, the challenges which also remained were the validation of the model and to establish that each experimental condition of the dataset was predicted with consistent accuracy. The development strategy involved the selection of the best mtk-QSAR model from twelve different linear models generated by varying data-distribution and feature-selection techniques. The most predictive linear model was generated with moderate to good predictivity against the training (91%), test (91%) and external validation (85%) sets. Note that, in this work, the PS3M strategy was employed for the first time, and it led to a ‘similar’ model with higher statistical accuracy against the training (94%) and the external validation (89%) sets without any change in the predictive accuracy of the test set. Finally, a technique named ‘condition-wise prediction’ was employed to split the prediction results into different experimental conditions in order to identify poorly predicted experimental conditions. However, it was observed that the model provided satisfactory predictivity against most of these conditions. Such investigations show that the MA-mtk modeling approach may also be applied to relatively small datasets but many more of these studies should be reported in the future along with experimental validation to confirm this idea. To conclude this analysis of MA-mtk modeling of the activity against cells/organisms/species, going beyond the scope of drug design and discovery, some MA-mtk studies have also focused on the environmental toxicity of diverse categories of chemicals [28,33,67]. Particularly noteworthy is a recent multitasking modeling study of the ecotoxicity of various classes of pesticides [33]. Departing from 260 structurally diverse peptides, a dataset containing 3610 data points was formed by considering four primary different experimental conditions, namely: me (toxicity measurements), bs (bioindicator species), ag (assay guidelines) and ep (exposure periods). Alongside these, three secondary additional experimental conditions, i.e., concentration lethality (lc), target mapping (tm) and time classification (tc), were also considered for computing the moving average-based descriptors. The ANN model with the highest discriminant power found thereafter included nine deviation descriptors, computed from the original graph-based topological features, and depicted an overall accuracy of 83 and 76% in the training and prediction sets, respectively. The same dataset and starting descriptors were later used in another investigation [12] for building multitasking models using a different machine learning tool—i.e., random forests (RF), but in particular with the aim of comparing different moving average-based algorithms to understand their effects in the models’ predictive accuracy. Five different moving average algorithms, which had been employed previously in different investigations, were used to derive five different models. Interestingly, the comparative analyses showed that the predictive accuracy of these models did not vary to a large extent. 4.2. MA-Mtk Modeling of the Activity against Bio-Macromolecular Targets As different pathways and bio-macromolecular targets have increasingly been identified in the last few decades, MA-mtk modeling is becoming an interesting tool in the design of both selective and pan-inhibitors, depending on the roles of these closely related bio-macromolecular targets against any specific disease. Quite expectedly, significant efforts have since been invested to set up mtk-QSAR models with multiple macromolecular cellular targets [38,68,69,70]. For example, in 2013, with a strategy encompassing LDA and ANN tools to set up linear and non-linear models for probing several proteins involved in the progression of leukemia, the substructural and global descriptors that were used had no modification but spectral moments derived from the bond adjacency matrix (µk) were subjected to the moving average approach to compute the deviation descriptors [69]. Both ANN and LDA models had an overall accuracy above 90%, with the ANN model comprising a total of eleven descriptors out of which four belonged to ∆(Di)cj. Another study by Casañola-Martin et al. [70] is worth mentioning here. Starting from 2954 unique drugs retrieved from the CHeMBL database making 5062 data points, the authors developed an LDA-based mtk-QSAR model with seven descriptors that predicted the outcomes of more than 450 different type of assays against at least 1 out of 20 experimental parameters related to the ubiquitin–proteasome pathway. Though affording an overall accuracy of 70%, when considering the complexity of the modeling-data matrix as well as the fact that numerous biochemical mechanisms are likely to be involved in the ubiquitin–proteasome pathway, this study clearly demonstrated that the moving average-based mtk-QSAR modeling may be expanded towards overly complex biochemical pathways. More recently, several works have focused on targeting the inhibition of various bio-macromolecular targets of cancer such as PI3K [11], AKT [25], ERK [46], MNK [21], HSP90 [41], and BET bromodomain [38]. Their main aim was to set-up models capable of simultaneously predicting the inhibitory potential of the chemicals against various isoforms of such biological targets. Notwithstanding, these models may definitely be used for obtaining isoform-specific inhibitors. Integrating other in silico strategies, especially structure-based techniques, when bio-macromolecular targets are involved can provide that aspect. In fact, recently linear and non-linear MA-mtk models were developed for coping with the inhibitors of three different isoforms of the BET (bromodomain and extra-terminal) family of bromodomain-containing proteins (i.e., BRD2, BRD3, BRD4) that serve as epigenetic regulators in the progression of cancer [38]. High accuracy values (>85%) were obtained for both models though the ANN-based model was definitely more predictive. In addition, not only the desirable fragments were identified for the design of potential virtual leads against these targets, but also the designed leads were separately docked into the active sites of X-ray crystal structures of BRD2, BRD3, BRD4 to find the most promising candidate among these leads (Figure 2). The approach of mixing or coupling in silico strategies is a key aspect in these MA-mtk-QSARs. Support from other ligand- and structure-based in silico methodologies may assist in further filtering and ranking the positive hits obtained from the QSAR model (Figure 3), as the latter action cannot be provided by simple virtual screening. Furthermore, assessment of the druggability and synthetic accessibility may also help in curtaining the number of hits [8,21,24]. Table 4 lists some of these tools and webservers that have already been used along with MA-mtk models to select the hits. Though the choice of an in silico strategy to be adopted depends largely on the researchers, more often it is the nature of the biological targets involved in the work that becomes the most crucial factor for choosing which method is to be adopted. Discussing two recently published investigations, one involving the design of pan-AKT inhibitors [25] and the other one focused on the design of pan-MNK inhibitors [21], may enlighten how rigorous application of in silico methods helps in the selection of the promising hits (see Figure 3). Being kinase enzymes, both AKT and MNK possess highly flexible catalytic sites and therefore semi-rigid docking may be unreliable. Therefore, in both these investigations, MD simulations of ligand-receptor complexes was chosen as the last resort to finalize the hits. For AKT inhibitors, virtual hits obtained from the predictive linear (GA-LDA model yielding an overall accuracy > 88%) and non-linear (developed with XGBoost yielding an overall accuracy > 91%) MA-mtk models were further filtered through reverse pharmacophore mapping strategy, i.e., the pharmacophores generated on each query compound were matched with a large database containing structure-based pharmacophores generated with the X-ray crystal structures of ligand-receptor complexes to rank these complexes as per the fit values. As such, a reverse pharmacophore mapping strategy may be exploited to validate the results of virtual screening and for filtering the hits. Here, seven virtual hits were obtained from MA-mtk modeling but five hits were retained after pharmacophore mapping for further processing. Finally, MD simulations were carried out with each of these five hits to ensure the theoretical binding potentials of these hits against all AKT isoforms and on the basis of these analyses, one candidate was selected as the most promising virtual hit for pan-AKT inhibition. Regarding the MNK-1 and MNK-2 inhibitors [21], the final MA-mtk model was used for the screening of the commercial library to obtain 20 potential virtual hits. Unlike resorting to reverse pharmacophore mapping to improve confidence over these hits and to select the most promising hits, a much faster strategy based on similarity searching was taken into consideration. In this method, the fingerprints of the virtual hits were cross-matched with a database containing MNK-1 and MNK-2 inhibitors to identify those hits with a maximum number of matches vs. the experimentally tested potent MNK-1/2 inhibitors. These filtered hits were further processed by MD simulation analyses and theoretical binding energy calculations that led to only the four most promising candidates. In future it is expected that experimental validation coupled with these in silico strategies may lead towards finding target-based therapeutic agents for various other diseases. In addition to the cancer progression targets discussed above, biological targets related to other diseases such as antimicrobial [24,80,81,82], antihypertensive [83], neuroprotective and neurotoxic [13,84], and anti-inflammatory agents [35], and have been the object of research within the MA-mtk-QSAR context. In a recent work aimed at designing anti-inflammatory agents through the dual inhibition of caspase-1 and TNF-α, the dataset contained 1476 data points built from 1444 molecules with activity tested against caspase-1 or TNF-α [35]. Evidently, the data was structurally and biologically diverse in nature and so the authors considered only two experimental conditions, namely the biological targets and their experimental assay types, to derive the deviation descriptors starting from topological indices. Two similar but different cut-off values of 1000 nM and 1635 nM were assigned for these two biological targets to distinguish the active samples from inactive ones. The resulting MLP-ANN non-linear model afforded an overall predictive accuracy higher than 88%, and a virtual screening was performed with agency-regulatory chemicals to select and rank the most promising virtual hits for dual inhibition of these two proteins. 5. Software Developed for Multitasking Modeling This section briefly describes three software packages that have been developed recently for accelerating MA-mtk modeling as outlined in the current review. These are QSAR-Co, QSAR-Co-X and FRAMA. Both QSAR-Co and QSAR-Co-X are available in the public domain with detailed instruction manuals. 5.1. QSAR-Co QSAR-Co [44], which was introduced in 2019, is a Java based open-access tool for developing moving average-based mtk-QSAR models by means of GA-LDA and RF techniques (available at https://sites.google.com/view/qsar-co, see Figure 4). This software, which utilizes the WEKA library for RF-based model development, was designed to automatically calculate moving average-based deviation descriptors starting from the original descriptors, which are fed into the software as a .csv file, alongside the name of compounds, the experimental/theoretical conditions, and the endpoint response(s) to be targeted. The software automatically yields output .csv files containing statistical parameters such as the sensitivity, specificity, accuracy, the Matthews correlation coefficient (MCC), etc., and receiver operating characteristics (ROC) plots of the models, along with the selected features values, observed and predicted response(s), as well as the applicability domain estimated by either the standardization approach or the confidence estimation approach. Furthermore, QSAR-Co allows the remotion of less important descriptors to be performed, the division of the dataset with multiple methods, and is also capable of diagnosing query chemicals, which is extremely useful in virtual screening efforts. 5.2. QSAR-Co-X With the aim of expanding the scope of software QSAR-Co, another software named QSAR-Co-X [12] was introduced in 2021. This open source standalone toolkit built by using Python 3 (available at https://github.com/ncordeirfcup/QSAR-Co-X) comprises four different modules. Module 1 is designed for the calculation of deviation descriptors using diverse Box–Jenkins’s operators, starting from the categorical endpoint response(s), the related experimental/theoretical conditions, and the original descriptors. The same module performs data division for generating the training, test and external validation sets, followed by the descriptor generation and development of the linear mtk-QSAR models by application of the LDA technique along with FS or SFS feature-selection algorithms. Subsequently, either prediction when the endpoint response is known or screening when it is unknown can be performed using the external validation set to estimate the ‘true’ predictivity of the model. Furthermore, this module performs Yc-randomization and produces output files containing the resulting statistical parameters, and the information regarding the model descriptors and its applicability domain determined by either the standardization or the confidence estimation approach (see Figure 5). Modules 2 and 3, on the other hand, are intended for the development of non-linear models using multiple machine learning methods including (a) k-nearest neighborhood (kNN), (b) Bernoulli naïve Bayes (NB) classifier, (c) support vector classifier (SVC), (d) random forests (RF), (e) gradient boosting (GB), and (f) multilayer perceptron (MLP) neural networks. For all these non-linear modeling techniques, the Scikit-learn machine learning package is used. Module 2 provides the facility of hyperparameter optimization for each of these ML tools based on the information provided by the user in .csv format. On the other hand, non-linear models are developed using the fixed user-specific parameters. Module 4 is used for ‘condition-wise prediction’ to assess the accuracy of the generated models against each experimental condition. 5.3. FRAMA FRAMA, is a Windows desktop application developed in 2017 [10,85], which supports various file formats and allows the user to perform several data preprocessing and classification tasks of the input and output variables (see Figure 6). After pretreating the data, the selected variables can then be subjected to batch operations by the user, in which classical BJMA operators can be computed for conducting multilinear regression or classification multitasking assessments, as well as PTML analyses. The processing information alongside several parametric statistics computed for each type of modeling is stored in .csv spreadsheets for further analysis. 6. Future Scope MA-mtk modeling techniques have been applied, with excellent results, in a number of different research areas. Irrespective of the nature of the chemicals, disease, targets, experimental conditions, or even dataset size, highly predictive models have been obtained. However, as the majority of investigations have been focused on anticancer and antimicrobial research, the likelihood, in coming years, of MA-mtk modeling expanding to cover diseases such as diabetes, cardiovascular disorders, inflammatory disorders, or CNS disorders, where only a few investigations have been performed till date, is to be expected. In addition, the scope of deep learning has already been discussed in model development, and similarly, model development and validation should be improved with the inclusion of more refined feature selection and ML tools (e.g., logistic regression), which are still witnessing extensive advancement and transformation [86,87]. Further work may also be required on the modification of Box–Jenkin’s moving average algorithms, and comparative analyses should be performed to understand if any of such modification leads to a model with improved predictive accuracy or not. Another aspect to consider is that investigations have so far focused on fragment-based design [8,27,28], whereas other relied on virtual screening of commercial databases [21,46]. Recently, the application of Bemis–Murcko scaffolds was suggested to extract the fragments from large databases to estimate their contributions [11,46]. However, lead generation and optimization from favorable fragments should be made more systematic in the future by using methods such as scaffold hopping, fragment linking, fragment growing, R-group analyses, or PROTAC design, for example [88]. New techniques, if implemented, made available to the users in the form of tools in software packages such as QSAR-Co, QSAR-Co-X, etc., will allow the advance of the research globally. Finally, experimental validation of the proposed hits must be encouraged to realize the true potential of MA-mtk modeling. 7. Conclusions With increasing chemical and biological knowledge, which produces a huge amount of available data, continuously accumulated in scientific literature and databases, the in silico methods adopted for the design of new molecular entities must be able to tackle in a fast and simple manner this scientific data, if molecular design is to evolve towards a multitasking optimization process. The current review focuses on the current status and future scope of moving average-based multitasking in silico modeling that tend to serve the above-mentioned purpose. Alongside discussing the basic methodologies of MA-mtk modeling, some works were specifically addressed at understanding how their integration of datasets with variable experimental assay conditions improves the diversity and reliability of in silico models. This discussion may provide a more wholistic idea about mechanistic interpretations. Furthermore, the discussion of these recent advances included the newly-developed tools for facilitating such modeling. As such, not only does this review provide important updates and guidelines for multitasking in silico classification modeling but it also explores how it is expected that such modeling will expand the research areas that are yet to be covered. Author Contributions A.K.H. and M.N.D.S.C. contributed equally to conceive, analyze, write and prepare the draft and critically evaluate the manuscript. A.S.M. and M.N.D.S.C. have contributed equally to review and editing the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Examples of new anti-breast cancer leads suggested in the mtk-QSAR modeling study by Speck-Planche et al. [55]. Figure 2 Promising BET bromodomain inhibitory leads proposed in the mtk-QSAR modeling study by Scotti and co-worker [38]. Figure 3 The virtual screening strategy adopted for the design of pan-AKT inhibition (left) and pan-MNK inhibition (right) [25]. Figure 4 Screenshot of the latest version of QSAR-Co (version 1.1.0) [44]. Figure 5 Screenshots of the Modules 1–3 graphic interface from the toolkit QSAR-Co-X [12]. Figure 6 Screenshot of the latest version of the Windows software FRAMA [10,85]. ijms-23-04937-t001_Table 1 Table 1 Box–Jenkins operators used in the different studies [24,29,30,31,32,33,34,35]. Operators Remarks ∆(Di)cj = Di − avg(Di)cj avg(Di)cj=1n(cj)∑i=1n(cj)Di ∆(Di)cj = pc·[Di − avg(Di)cj] pc: A probabilistic term ∆(Di)cj = [Di − avg(Di)cj]/(Dimax − Dimin) Dimax: Maximum value of Di Dimin:Minimum value of Di ∆(Di)cj = [Di − avg(Di)cj]/[(Dimax − Dimin) p(cj)c] p(cj)c = n(cj)/N (N: Total number of data points in the modeling set) ∆(Di)cj = [Di − avg(Di)cj]/[(Dimax − Dimin) √p(cj)c] p(cj)c = n(cj)/N ∆(Di)cj = [(Di − avg(Di)cj]/[SD(Di) √p(cj)c] SD(Di): Standard deviation of Di ijms-23-04937-t002_Table 2 Table 2 Feature selection and machine learning tools used for moving average based multitasking modeling [12,21,44]. Feature Selection Tools—Linear Models (LDA) Machine Learning Tools—Non-Linear Models Fast stepwise (FS) selection Decision trees (DT) Sequential forward selection (SFS) Random forests (RF) Genetic algorithm (GA) selection Gradient boosting (GB) Post-selection similarity search modification (PS3M) Support vector machines (SVM) k-nearest neighborhood (kNN) Bernoulli naïve Bayes (NB) Artificial neural networks (ANN) Deep neural networks (DNN) ijms-23-04937-t003_Table 3 Table 3 Selected multitasking classification modeling studies in antimicrobial and antiviral research. Year Methodology a No. of Chemicals (Ndp) b Endpoint Responses c Bio-Targets d Acc (%) e Ref. 2013 RBF-ANN 8560 (10,918) Anti-Enterococci activities and toxicological profiles Enterococci strains; Mus musculus; Rattus norvegicus; human lymphocytes 92.30 [59] 2013 RBF-ANN 6974 (11,576) Anti-Streptococci activities and toxicological profiles Streptococci strains; Mus musculus; Rattus norvegicus 98.08 [60] 2013 FS-LDA 20,863 (34,629) Anti-Mycobacterial activity and ADMET properties Mycobacterium spp. strains; proteins; Mus musculus; Rattus norvegicus; Homo sapiens 94.80 [51] 2014 FS-LDA 23,705 (37,834) Anti-Escherichia coli activities and ADMET properties Escherichia coli strains; proteins; laboratory animals (mice and rats); Homo sapiens 95.85 [52] 2014 FS-LDA 26,945 (48,874) Anti-cocci activities and ADMET properties Gram-positive cocci strains; proteins; cell lines; laboratory animals; humans 92.89 [61] 2014 LNN-LDA 21,582 (43,249) Anti-HIV-1 activity and epidemiological profile Viral or human proteins/enzymes (e.g., CC-CKR-5, HIV-1 RT, and HIV-1 PR); laboratory animals; humans 76.76 [62] 2015 FS-LDA 30,738 (54,682) Anti-Pseudomonas activities and ADMET properties Pseudomonas spp. strains; proteins/enzymes; Mus musculus; Rattus norvegicus; Homo sapiens 90.62 [63] 2015 FS-LDA 22,009 (30,181) Anti-NOMA activity and ADMET profiles Bacteria linked to NOMA infections (e.g., Fusobacterium spp., Prevotella spp., Bacillus, etc.); cell lines; laboratory animals; humans 92.12 [53] 2016 FS-LDA 2123 (3592) Anti-microbial peptides (AMP) activity and cytotoxicity Gram-negative bacterial strains; mammalian cell types 97.40 [50] 2016 FS-LDA 1581 (2488) AMP activity Gram-positive bacterial strains 94.57 [64] 2017 FS-LDA 20,562 (29,682) Anti-HIV activity and ADMET properties HIV; proteins/enzymes; cell lines; laboratory animals; humans 96.26 [43] 2017 FS-LDA 29,863 (40,158) Anti-Hepatitis C activity and ADMET properties Hepatitis C; proteins/enzymes; mammalian cells 95.35 [31] 2020 MLP-ANN 18,798 (21,369) Anti-malarial activity, cytotoxicity, and pharmacokinetic properties Plasmodium falciparum strains; proteins; mammalian cells; plasma and liver microsomes 90.49 [65] a RBF: radial basis function; ANN: artificial neural networks; FS-LDA: forward stepwise–linear discriminant analysis; LNN: linear neural networks; MLP: multilayer perceptron. b No. of chemicals: Number of chemicals with unique structures; Ndp: Number of data points considered in the modeling taking into account the experimental conditions. c ADMET: absorption, distribution, metabolism, elimination, and toxicity; AMP: antimicrobial peptides. d CC-CKR-5: C−C chemokine receptor type 5; HIV-1 RT: HIV-1 reverse transcriptase; HIV-1 PR: HIV-1 protease; NOMA: cancrum oris; Mtb: Mycobacterium tuberculosis. e Average accuracy obtained from the training and prediction sets. ijms-23-04937-t004_Table 4 Table 4 Some in silico tools and webservers employed for multitasking modeling. Method Software/Webserver Pharmacophore mapping PharmMapper [25,71] Molecular docking AutoDock [21,25,72], AutoDock Vina [25,73], Molegro Virtual Docker [24,74] Similarity search SIMSEARCH [21] Molecular dynamics simulations Amber [21,75], Gromacs [46,76] Homology modeling SwissModel [25,77] Drug-likeness SwissADME [21,78] Synthetic accessibility SwissADME [21,78] Graph-based signature MycoCSM [22,79] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hansch C. Maloney P.P. Fujita T. Muir R.M. Correlation of Biological Activity of Phenoxyacetic Acids with Hammett Substituent Constants and Partition Coefficients Nature 1962 194 178 180 10.1038/194178b0 2. Muratov E.N. Bajorath J. Sheridan R.P. Tetko I.V. Filimonov D. Poroikov V. Oprea T.I. Baskin I.I. Varnek A. Roitberg A. QSAR Without Borders Chem. Soc. Rev. 2020 49 3525 3564 10.1039/D0CS00098A 32356548 3. Neves B.J. Braga R.C. Melo-Filho C.C. Moreira-Filho J.T. Muratov E.N. Andrade C.H. QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery Front. Pharmacol. 2018 9 1275 10.3389/fphar.2018.01275 30524275 4. Yu W. MacKerell A.D. Computer-Aided Drug Design Methods Antibiotics. Methods in Molecular Biology Sass P. Humana Press New York, NY, USA 2017 Volume 1520 85 106 978-1-4939-6634-9 5. Abdolmaleki A. Ghasemi J. Ghasemi F. Computer Aided Drug Design for Multi-Target Drug Design: SAR/QSAR, Molecular Docking and Pharmacophore Methods Curr. Drug Targets 2017 18 556 575 10.2174/1389450117666160101120822 26721410 6. Sabe V.T. Ntombela T. Jhamba L.A. Maguire G.E.M. Govender T. Naicker T. Kruger H.G. Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review Eur. J. Med. Chem. 2021 224 113705 10.1016/j.ejmech.2021.113705 34303871 7. Halder A.K. Moura A.S. Cordeiro M.N.D.S. QSAR modelling: A therapeutic patent review 2010-present Expert Opin. Ther. Pat. 2018 28 467 476 10.1080/13543776.2018.1475560 29745270 8. Speck-Planche A. Recent advances in fragment-based computational drug design: Tackling simultaneous targets/biological effects Future Med. Chem. 2018 10 2021 2024 10.4155/fmc-2018-0213 30058835 9. Searls D.B. Data integration: Challenges for drug discovery Nat. Rev. Drug Discov. 2005 4 45 58 10.1038/nrd1608 15688072 10. Ortega-Tenezaca B. Quevedo-Tumailli V. Bediaga H. Collados J. Arrasate S. Madariaga G. Munteanu C.R. Cordeiro M.N.D.S. Gonzalez-Díaz H. PTML Multi-Label Algorithms: Models, Software, and Applications Curr. Top. Med. Chem. 2020 20 2326 2337 10.2174/1568026620666200916122616 32938352 11. Halder A.K. Cordeiro M.N.D.S. Development of Multi-Target Chemometric Models for the Inhibition of Class I PI3K Enzyme Isoforms: A Case Study Using QSAR-Co Tool Int. J. Mol. Sci. 2019 20 4191 10.3390/ijms20174191 12. Halder A.K. Cordeiro M.N.D.S. QSAR-Co-X: An open source toolkit for multitarget QSAR modelling J. Cheminform. 2021 13 29 10.1186/s13321-021-00508-0 33858509 13. Speck-Planche A. Cordeiro M.N.D.S. Multitasking models for quantitative structure–biological effect relationships: Current status and future perspectives to speed up drug discovery Expert Opin. Drug Discov. 2015 10 245 256 10.1517/17460441.2015.1006195 25613725 14. Lambrinidis G. Tsantili-Kakoulidou A. Multi-objective optimization methods in novel drug design Expert Opin. Drug Discov. 2020 16 647 658 10.1080/17460441.2021.1867095 33353441 15. Speck-Planche A. Multi-Scale Modeling in Drug Discovery against Infectious Diseases Mini Rev. Med. Chem. 2019 19 1560 1563 10.2174/138955751919191024110000 31833463 16. Toropov A.A. Toropova A.P. QSPR/QSAR: State-of-Art, Weirdness, the Future Molecules 2020 25 1292 10.3390/molecules25061292 17. Roy K. Kar S. Das R.N. Chemical Information and Descriptors Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment Academic Press Amsterdam, The Netherlands 2015 47 80 9780128016336 18. Halder A.K. Delgado A.H.S. Cordeiro M.N.D.S. First multi-target QSAR model for predicting the cytotoxicity of acrylic acid-based dental monomers Dental Mater. 2022 38 333 346 10.1016/j.dental.2021.12.014 19. Prado-Prado F.J. Gonzalez-Díaz H. de la Vega O.M. Ubeira F.M. Chou K.-C. Unified QSAR approach to antimicrobials. Part 3: First multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds Bioorg. Med. Chem. 2008 16 5871 5880 10.1016/j.bmc.2008.04.068 18485714 20. Kleandrova V.V. Speck-Planche A. The urgent need for pan-antiviral agents: From multitarget discovery to multiscale design Future Med. Chem. 2021 13 5 8 10.4155/fmc-2020-0134 33225723 21. Halder A.K. Cordeiro M.N.D.S. Multi-Target in Silico Prediction of Inhibitors for Mitogen-Activated Protein Kinase-Interacting Kinases Biomolecules 2021 11 1670 10.3390/biom11111670 34827668 22. Kleandrova V.V. Scotti M.T. Speck-Planche A. Computational Drug Repurposing for Antituberculosis Therapy: Discovery of Multi-Strain Inhibitors Antibiotics 2021 10 1005 10.3390/antibiotics10081005 34439055 23. Cumming J.G. Davis A.M. Muresan S. Haeberlein M. Chen H. Chemical predictive modelling to improve compound quality Nat. Rev. Drug Discov. 2013 12 948 962 10.1038/nrd4128 24287782 24. Kleandrova V.V. Scotti L. Junior F.J.B.M. Muratov E. Scotti M.T. Speck-Planche A. QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites Front. Chem. 2021 9 634663 10.3389/fchem.2021.634663 33777898 25. Halder A.K. Cordeiro M.N.D.S. AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery Int. J. Mol. Sci. 2021 22 3944 10.3390/ijms22083944 33920446 26. Box G.E.P. Jenkins G.M. Reinsel G.C. Ljung G.M. Time Series Analysis: Forecasting and Control Holden-Day San Francisco, CA, USA 1970 27. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Fragment-based QSAR model toward the selection of versatile anti-sarcoma leads Eur. J. Med. Chem. 2011 46 5910 5916 10.1016/j.ejmech.2011.09.055 22030313 28. Speck-Planche A. Kleandrova V.V. Scotti M.T. Fragment-based approach for the in silico discovery of multi-target insecticides Chemom. Intell. Lab. Syst. 2012 111 39 45 10.1016/j.chemolab.2011.11.010 29. Halder A.K. Haghbakhsh R. Voroshylova I.V. Duarte A.R.C. Cordeiro M.N.D.S. Density of Deep Eutectic Solvents: The Path Forward Cheminformatics-Driven Reliable Predictions for Mixtures Molecules 2021 26 5779 10.3390/molecules26195779 34641322 30. Speck-Planche A. Cordeiro M.N.D.S. De novo computational design of compounds virtually displaying potent antibacterial activity and desirable in vitro ADMET profiles Med. Chem. Res. 2017 26 2345 2356 10.1007/s00044-017-1936-4 31. Speck-Planche A. Cordeiro M.N.D.S. Speeding up Early Drug Discovery in Antiviral Research: A Fragment-Based in Silico Approach for the Design of Virtual Anti-Hepatitis C Leads ACS Comb. Sci. 2017 19 501 512 10.1021/acscombsci.7b00039 28437091 32. Kleandrova V.V. Scotti M.T. Scotti L. Nayarisseri A. Speck-Planche A. Cell-based multi-target QSAR model for design of virtual versatile inhibitors of liver cancer cell lines SAR QSAR Environ. Res. 2020 31 815 836 10.1080/1062936X.2020.1818617 32967475 33. Speck-Planche A. Multi-Scale QSAR Approach for Simultaneous Modeling of Ecotoxic Effects of Pesticides Ecotoxicological QSARs. Methods in Pharmacology and Toxicology Roy K. Springer New York, NY, USA 2020 639 660 978-1-0716-0150-1 34. Kleandrova V.V. Scotti M.T. Scotti L. Speck-Planche A. Multi-target Drug Discovery via PTML Modeling: Applications to the Design of Virtual Dual Inhibitors of CDK4 and HER2 Curr. Top. Med. Chem. 2021 21 661 675 10.2174/1568026621666210119112845 33463472 35. Speck-Planche A. Kleandrova V.V. Scotti M.T. In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha Biomolecules 2021 11 1832 10.3390/biom11121832 34944476 36. Valdés-Martiní J.R. Marrero-Ponce Y. García-Jacas C.R. Martinez-Mayorga K. Barigye S.J. Vaz d‘Almeida Y.S. Pham-The H. Pérez-Giménez F. Morell C.A. QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations J. Cheminform. 2017 9 35 10.1186/s13321-017-0211-5 29086120 37. García I. Fall Y. Gómez G. Gonzalez-Díaz H. First computational chemistry multi-target model for anti-Alzheimer, anti-parasitic, anti-fungi, and anti-bacterial activity of GSK-3 inhibitors in vitro, in vivo, and in different cellular lines Mol. Divers. 2010 15 561 567 10.1007/s11030-010-9280-3 20931280 38. Speck-Planche A. Scotti M.T. BET bromodomain inhibitors: Fragment-based in silico design using multi-target QSAR models Mol. Divers. 2018 23 555 572 10.1007/s11030-018-9890-8 30421269 39. Mauri A. Consonni V. Pavan M. Todeschini R. DRAGON software: An easy approach to molecular descriptor calculations MATCH Commun. Math. Comput. Chem. 2006 56 237 248 40. Kleandrova V.V. Speck-Planche A. PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors Biomedicines 2022 10 491 10.3390/biomedicines10020491 35203699 41. Speck-Planche A. Combining Ensemble Learning with a Fragment-Based Topological Approach to Generate New Molecular Diversity in Drug Discovery: In Silico Design of Hsp90 Inhibitors ACS Omega 2018 3 14704 14716 10.1021/acsomega.8b02419 30555986 42. Speck-Planche A. Multicellular Target QSAR Model for Simultaneous Prediction and Design of Anti-Pancreatic Cancer Agents ACS Omega 2019 4 3122 3132 10.1021/acsomega.8b03693 43. Kleandrova V.V. Speck-Planche A. Multitasking Model for Computer-Aided Design and Virtual Screening of Compounds with High Anti-HIV Activity and Desirable ADMET Properties Multi-Scale Approaches in Drug Discovery Speck-Planche A. Elsevier Amsterdam, The Netherlands 2017 55 81 97800-81011294 44. Ambure P. Halder A.K. Gonzalez Diaz H. Cordeiro M.N.D.S. QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models J. Chem. Inf. Model. 2019 59 2538 2544 10.1021/acs.jcim.9b00295 31083984 45. Urias R.W.P. Barigye S.J. Marrero-Ponce Y. García-Jacas C.R. Valdes-Martiní J.R. Perez-Gimenez F. IMMAN: Free software for information theory-based chemometric analysis Mol. Divers. 2015 19 305 319 10.1007/s11030-014-9565-z 25620721 46. Halder A.K. Giri A.K. Cordeiro M.N.D.S. Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents Molecules 2019 24 3909 10.3390/molecules24213909 31671605 47. Roy K. Kar S. Das R.N. Validation of QSAR Models Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment Academic Press Amsterdam, The Netherlands 2015 231 289 97801-28016336 48. Roy K. Kar S. Ambure P. On a simple approach for determining applicability domain of QSAR models Chemom. Intell. Lab. Syst. 2015 145 22 29 10.1016/j.chemolab.2015.04.013 49. Ambure P. Bhat J. Puzyn T. Roy K. Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: An in silico approach J. Biomol. Struct. Dyn. 2018 37 1282 1306 10.1080/07391102.2018.1456975 29578387 50. Kleandrova V.V. Ruso J.M. Speck-Planche A. Cordeiro M.N.D.S. Enabling the Discovery and Virtual Screening of Potent and Safe Antimicrobial Peptides. Simultaneous Prediction of Antibacterial Activity and Cytotoxicity ACS Comb. Sci. 2016 18 490 498 10.1021/acscombsci.6b00063 27280735 51. Speck-Planche A. Cordeiro M.N.D.S. Simultaneous Modeling of Antimycobacterial Activities and ADMET Profiles: A Chemoinformatic Approach to Medicinal Chemistry Curr. Top. Med. Chem. 2013 13 1656 1665 10.2174/15680266113139990116 23889052 52. Speck-Planche A. Cordeiro M.N.D.S. Simultaneous Virtual Prediction of Anti-Escherichia coli Activities and ADMET Profiles: A Chemoinformatic Complementary Approach for High-Throughput Screening ACS Comb. Sci. 2014 16 78 84 10.1021/co400115s 24383958 53. Speck-Planche A. Cordeiro M.N.D.S. Enabling Virtual Screening of Potent and Safer Antimicrobial Agents against Noma: Mtk-QSBER Model for Simultaneous Prediction of Antibacterial Activities and ADMET Properties Mini Rev. Med. Chem. 2015 15 194 202 10.2174/138955751503150312120519 25769968 54. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Multi-target drug discovery in anti-cancer therapy: Fragment-based approach toward the design of potent and versatile anti-prostate cancer agents Bioorg. Med. Chem. 2011 19 6239 6244 10.1016/j.bmc.2011.09.015 21967806 55. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Chemoinformatics in anti-cancer chemotherapy: Multi-target QSAR model for the in silico discovery of anti-breast cancer agents Eur. J. Pharm. Sci. 2012 47 273 279 10.1016/j.ejps.2012.04.012 22538055 56. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Chemoinformatics in Multi-target Drug Discovery for Anti-cancer Therapy: In Silico Design of Potent and Versatile Anti-brain Tumor Agents Anti-Cancer Agents Med. Chem. 2012 12 678 685 10.2174/187152012800617722 57. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Rational drug design for anti-cancer chemotherapy: Multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents Bioorg. Med. Chem. 2012 20 4848 4855 10.1016/j.bmc.2012.05.071 22750007 58. Speck-Planche A. Kleandrova V.V. Luan F. Cordeiro M.N.D.S. Unified Multi-target Approach for the Rational in silico Design of Anti-bladder Cancer Agents Anti Cancer Agents Med. Chem. 2013 13 791 800 10.2174/1871520611313050013 23272967 59. Speck-Planche A. Cordeiro M.N.D.S. Chemoinformatics in Drug Design. Artificial Neural Networks for Simultaneous Prediction of Anti-Enterococci Activities and Toxicological Profiles Proceedings of the 5th International Joint Conference on Computational Intelligence Algarve, Portugal 20–22 September 2013 458 465 60. Speck-Planche A. Kleandrova V.V. Cordeiro M.N.D.S. Chemoinformatics for rational discovery of safe antibacterial drugs: Simultaneous predictions of biological activity against streptococci and toxicological profiles in laboratory animals Bioorg. Med. Chem. 2013 21 2727 2732 10.1016/j.bmc.2013.03.015 23582445 61. Speck-Planche A. Cordeiro M.N.D.S. Chemoinformatics for medicinal chemistry: In silico model to enable the discovery of potent and safer anti-cocci agents Future Med. Chem. 2014 6 2013 2028 10.4155/fmc.14.136 25531966 62. Gonzalez-Díaz H. Herrera-Ibatá D.M. Duardo-Sánchez A. Munteanu C.R. Orbegozo-Medina R.A. Pazos A. ANN Multiscale Model of Anti-HIV Drugs Activity vs. AIDS Prevalence in the US at County Level Based on Information Indices of Molecular Graphs and Social Networks J. Chem. Inf. Mod. 2014 54 744 755 10.1021/ci400716y 63. Speck-Planche A. Cordeiro M.N.D.S. Computer-Aided Discovery in Antimicrobial Research: In Silico Model for Virtual Screening of Potent and Safe Anti-Pseudomonas Agents Comb. Chem. High Throughput Screen 2015 18 305 314 10.2174/1386207318666150305144249 25747443 64. Speck-Planche A. Kleandrova V.V. Ruso J.M. Cordeiro M.N.D.S. First Multitarget Chemo-Bioinformatic Model to Enable the Discovery of Antibacterial Peptides against Multiple Gram-Positive Pathogens J. Chem. Inf. Model. 2016 56 588 598 10.1021/acs.jcim.5b00630 26960000 65. Speck-Planche A. Kleandrova V.V. Demystifying Artificial Neural Networks as Generators of New Chemical Knowledge: Antimalarial Drug Discovery as a Case Study Machine Learning in Chemistry Cartwright H.M. Royal Society of Chemistry Cambridge, UK 2020 398 423 978-1-78801-789-3 66. Kleandrova V.V. Luan F. Gonzalez-Díaz H. Ruso J.M. Melo A. Speck-Planche A. Cordeiro M.N.D.S. Computational ecotoxicology: Simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions Environ. Int. 2014 73 288 294 10.1016/j.envint.2014.08.009 25173945 67. Halder A.K. Cordeiro M.N.D.S. Probing the Environmental Toxicity of Deep Eutectic Solvents and Their Components: An In Silico Modeling Approach ACS Sustain. Chem. Eng. 2019 7 10649 10660 10.1021/acssuschemeng.9b01306 68. Marzaro G. Chilin A. Guiotto A. Uriarte E. Brun P. Castagliuolo I. Tonus F. Gonzalez-Díaz H. Using the TOPS-MODE approach to fit multi-target QSAR models for tyrosine kinases inhibitors Eur. J. Med. Chem. 2011 46 2185 2192 10.1016/j.ejmech.2011.02.072 21447431 69. Speck-Planche A. Luan F. Cordeiro M.N.D.S. Abelson Tyrosine-Protein Kinase 1 as Principal Target for Drug Discovery Against Leukemias. Role of the Current Computer-Aided Drug Design Methodologies Curr. Top. Med. Chem. 2013 12 2745 2762 10.2174/1568026611212240005 23368101 70. Casañola-Martin G.M. Le-Thi-Thu H. Pérez-Giménez F. Marrero-Ponce Y. Merino-Sanjuán M. Abad C. Gonzalez-Díaz H. Multi-output model with Box–Jenkins’s operators of linear indices to predict multi-target inhibitors of ubiquitin–proteasome pathway Mol. Divers. 2015 19 347 356 10.1007/s11030-015-9571-9 25754075 71. Liu X.F. Ouyang S.S. Yu B.A. Liu Y.B. Huang K. Gong J.Y. Zheng S.Y. Li Z.H. Li H.L. Jiang H.L. PharmMapper server: A web server for potential drug target identification using pharmacophore mapping approach Nucleic Acids Res. 2010 38 W609 W614 10.1093/nar/gkq300 20430828 72. Morris G.M. Huey R. Lindstrom W. Sanner M.F. Belew R.K. Goodsell D.S. Olson A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility J. Comput. Chem. 2009 30 2785 2791 10.1002/jcc.21256 19399780 73. Trott O. Olson A.J. Software news and update AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading J. Comput. Chem. 2010 31 455 461 19499576 74. Thomsen R. Christensen M.H. MolDock: A new technique for high-accuracy molecular docking J. Med. Chem. 2006 49 3315 3321 10.1021/jm051197e 16722650 75. Case D.A. Cheatham T.E. Darden T. Gohlke H. Luo R. Merz K.M. Onufriev A. Simmerling C. Wang B. Woods R.J. The Amber biomolecular simulation programs J. Comput. Chem. 2005 26 1668 1688 10.1002/jcc.20290 16200636 76. Hess B. Kutzner C. van der Spoel D. Lindahl E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation J. Chem. Theory Comput. 2008 4 435 447 10.1021/ct700301q 26620784 77. Guex N. Peitsch M.C. SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling Electrophoresis 1997 18 2714 2723 10.1002/elps.1150181505 9504803 78. Daina A. Michielin O. Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules Sci. Rep. 2017 7 42717 10.1038/srep42717 28256516 79. Pires D.E.V. Ascher D.B. mycoCSM: Using Graph-Based Signatures to Identify Safe Potent Hits against Mycobacteria J. Chem. Inf. Model. 2020 60 3450 3456 10.1021/acs.jcim.0c00362 32615035 80. Speck-Planche A. Cordeiro M.N.D.S. Multi-Target QSAR Approaches for Modeling Protein Inhibitors. Simultaneous Prediction of Activities against Biomacromolecules Present in Gram-Negative Bacteria Curr. Top. Med. Chem. 2015 15 1801 1813 10.2174/1568026615666150506144814 25961517 81. Kleandrova V.V. Luan F. Speck-Planche A. Cordeiro M.N.D.S. Review of Structures Containing Fullerene-C60 for Delivery of Antibacterial Agents. Multitasking model for Computational Assessment of Safety Profiles Curr. Bioinform. 2015 10 565 578 10.2174/1574893610666151008011628 82. Speck-Planche A. Kleandrova V.V. In silico design of multi-target inhibitors for C–C chemokine receptors using substructural descriptors Mol. Divers. 2011 16 183 191 10.1007/s11030-011-9337-y 22020812 83. Kleandrova V.V. Rojas-Vargas J.A. Scotti M.T. Speck-Planche A. PTML modeling for peptide discovery: In silico design of non-hemolytic peptides with antihypertensive activity Mol. Divers. 2021 1 12 84. Speck-Planche A. Luan F. Cordeiro M.N.D.S. Role of Ligand-Based Drug Design Methodologies toward the Discovery of New Anti-Alzheimer Agents: Futures Perspectives in Fragment-Based Ligand Design Curr. Med. Chem. 2012 19 1635 1645 10.2174/092986712799945058 22376033 85. Gonzalez-Diaz H. Ortega-Tenezaca B. Quevedo-Tumailli V. FRAMA 1.0: Framework for Moving Average Operators Calculation in Data Analysis Proceedings of the MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd Ed Basel, Switzerland 15 January–15 December 2017 86. Le N.Q.K. Kha Q.H. Nguyen V.H. Chen Y.-C. Cheng S.-J. Chen C.-Y. Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer Int. J. Mol. Sci. 2021 22 9254 10.3390/ijms22179254 34502160 87. Hung T.N.K. Le N.Q.K. Le N.H. Tuan L.V. Nguyen T.P. Thi C. Kang J.H. An AI-based Prediction Model for Drug-drug Interactions in Osteoporosis and Paget’s Diseases from SMILES Mol. Inform. 2022 e2100264 10.1002/minf.202100264 34989149 88. Imrie F. Hadfield T.E. Bradley A.R. Deane C.M. Deep generative design with 3D pharmacophoric constraints Chem. Sci. 2021 12 14577 14589 10.1039/D1SC02436A 34881010

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093246 sensors-22-03246 Article Tomek Link and SMOTE Approaches for Machine Fault Classification with an Imbalanced Dataset Swana Elsie Fezeka 1 https://orcid.org/0000-0001-9043-9882 Doorsamy Wesley 2* https://orcid.org/0000-0002-9178-2700 Bokoro Pitshou 1 Fort Ada Academic Editor Addabbo Tommaso Academic Editor 1 Department of Electrical and Electronics Engineering Technology, Doornfontein Campus, University of Johannesburg, Johannesburg 2028, South Africa; eswana@uj.ac.za (E.F.S.); pitshoub@uj.ac.za (P.B.) 2 Institute for Intelligent Systems, Auckland Park Campus, University of Johannesburg, Johannesburg 2006, South Africa * Correspondence: wdoorsamy@uj.ac.za 23 4 2022 5 2022 22 9 324601 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Data-driven methods have prominently featured in the progressive research and development of modern condition monitoring systems for electrical machines. These methods have the advantage of simplicity when it comes to the implementation of effective fault detection and diagnostic systems. Despite their many advantages, the practical implementation of data-driven approaches still faces challenges such as data imbalance. The lack of sufficient and reliable labeled fault data from machines in the field often poses a challenge in developing accurate supervised learning-based condition monitoring systems. This research investigates the use of a Naïve Bayes classifier, support vector machine, and k-nearest neighbors together with synthetic minority oversampling technique, Tomek link, and the combination of these two resampling techniques for fault classification with simulation and experimental imbalanced data. A comparative analysis of these techniques is conducted for different imbalanced data cases to determine the suitability thereof for condition monitoring on a wound-rotor induction generator. The precision, recall, and f1-score matrices are applied for performance evaluation. The results indicate that the technique combining the synthetic minority oversampling technique with the Tomek link provides the best performance across all tested classifiers. The k-nearest neighbors, together with this combination resampling technique yielded the most accurate classification results. This research is of interest to researchers and practitioners working in the area of condition monitoring in electrical machines, and the findings and presented approach of the comparative analysis will assist with the selection of the most suitable technique for handling imbalanced fault data. This is especially important in the practice of condition monitoring on electrical rotating machines, where fault data are very limited. imbalanced data Bayesian classification support vector machine k-nearest neighbor Tomek link synthetic minority over-sampling sampling wound-rotor induction generator ==== Body pmc1. Introduction Rotating electrical machines are essential equipment in industries such as wind turbines, compressors, gearboxes, cranes, motors, generators, power plants, etc., across several different applications [1]. Regardless of design improvements, operation, and maintenance of rotating electrical machines over the years, in practice, these machines are still vulnerable to a variety of faults which may lead to production and revenue losses due to unscheduled maintenance and repairs [2]. Condition monitoring, in the form of predictive maintenance, is a desirable capability that enables online and incipient fault detection [3]. The most common problems occurring in induction machines are inter-turn faults on stator and rotor windings, broken rotor bars and end rings, static and dynamic air-gap irregularities, bowed shaft, bearings misalignment, and mechanical imbalances [4]. Modern condition monitoring methods may be broadly categorized into model-based and data-driven approaches. Although model-based methods have been successfully applied in practice over the years, new techniques continue to be proposed to further improve and progress the field. Model-based methods are based on physics and mathematical modeling to outline the machine’s fault type and prior assumptions of various physics parameters are required. These techniques are typically based on parameter estimations, parity equations, and state observers [5]. The model-based techniques generally operate by using a threshold on generated residual signals to detect faults. Once the threshold is exceeded, the fault can be isolated. This approach has the advantage that it can provide high accuracy, easy interpretation, and clear analysis, and does not require large amounts of historical data. However, they have limitations, namely—assumptions about the system need to be made, prior knowledge of the exact physical processes and failure mechanism is required to build an expert system, and accuracy and robustness inherently depend on the model development conditions [6]. On the other hand, data-driven methods based on machine learning and the feature extraction process could be either statistical or non-statistical, and they require data generated under various conditions. Despite their numerous advantages, data-driven methods, particularly supervised-learning fault classifiers, are not used widely in practice due to the problem of a lack of adequate fault-condition data as compared to healthy condition data. This paper aims at overcoming the challenges that data imbalances poss to supervised-learning-based condition monitoring on a WRIG. This research specifically deals with classification stator and rotor winding inter-turn short-circuits and brush faults on a WRIG. The supervised-learning classifiers, namely, Naïve Bayes Classifier (NBC), Support Vector Machines (SVM), and k-nearest neighbors (k-NN), together with synthetic minority over-sampling technique (SMOTE) and Tomek link (T-link) methods, are applied on combined features extracted from multiple electrical signals—i.e., stator voltage and current and rotor current signals. A comparative analysis of the aforementioned approaches is presented when dealing with various levels of imbalanced data. The performances are then comprehensively evaluated through several key measures, namely, precision, recall, and F-measure. The presented research is intended to address progress in the development of data-driven approaches for the condition monitoring of generators. In this investigation, SMOTE and T-link will be implemented on multiple simulated and experimental data of the WRIG. To the best of the authors’ knowledge, an investigation into addressing fault data imbalances for data-driven condition monitoring on a WRIG has not yet been presented and will certainly contribute to condition monitoring practice and the growing knowledge in this area. The rest of the paper is organized as follows. A brief motivation for the presented study is presented. Thereafter, a review of the investigated resampling approaches—that is, the Tomek link (T-link) and Synthetic minority over-sampling technique (SMOTE) are briefly presented. The methodology including the machine modeling, feature extraction, and application of the techniques are then presented before a detailed comparison, integrated techniques, and interpretation of the results is given. Finally, a summary of the key findings of the research is presented in Section 5. 2. Background 2.1. Overview Data-driven methods are primarily based on machine learning, which necessitates data generated under various conditions to be diagnosed. The generated data enable an automatic fault detection and diagnosis to be constructed [7]. For instance, the literature shows that the application of deep learning neural networks reduces manual labor and expect knowledge [8,9]. The data-driven approaches are based on historical data and can be classified into supervised, unsupervised, self-supervised, semi-supervised, and reinforcement learning condition monitoring. While supervised-learning condition monitoring methods are based on training and classifying with labeled data to predict unlabeled data [10], unsupervised learning methods can extract information and apply hidden patterns based on input data to produce a model from unlabelled data. Self-supervised learning is a relatively new approach that learns representative examples, which automates the supervisory signals from unlabelled input datasets and predicts the remaining input dataset. The self-supervised capability to learn unlabelled data allows it to perform big data analysis, which makes it attractive for condition monitoring [11] but requires further research development for practicable application. When it comes to rotating electrical machines, specifically generators—large amounts of condition data are generated, which can be employed by data-driven approaches for predictive maintenance purposes. Data-driven methods are becoming more attractive due to their flexibility, ease of development, and relatively lower costs. Additionally, these approaches are also well suited under real-time constraints [8]. The commonly used supervised-learning methods include artificial neural networks (ANN), support vector machine (SVM), Naïve Bayes classifier (NBC), and decision tree [11]. The application of these supervised-learning methods have been applied successfully and presented to be effective for condition monitoring in electrical machines. However, the effectiveness of the above-mentioned methods has been based on the assumption that each class has been presented with the same number of instances. An experimental setup may be built to generate balanced data for various machine conditions. However, in practice, the machine mostly operates under healthy conditions and that results in abundantly healthy data being collected. The faulty data will only be generated when the machine experiences some faults, and there are significantly lower numbers of faulty data instances compared to healthy data. This results in the different numbers of instances or observations for the various classes, and this is referred to as an imbalanced dataset. This imbalanced dataset may lead to misclassification. Various methods have been proposed to reduce the data imbalance challenges, namely, the resampling (under-sampling of majority instances/over-sampling of minority instances) algorithm technique and ensemble methods, together with algorithm approaches for the enhancement of classifiers [12]. Chawla proposed a synthetic minority over-sampling technique (SMOTE) which is based on the k-nearest neighbor to generate new instances [13]. Sun [14] proposed an integrated method that includes SMOTE with AdaBoost support vector machine with time weighting for financial distress data. In [15], the data sampling method together with logistic regression, SVM, and k-NN were applied to an imbalanced cardiac surgery dataset. The results presented were based on the original data, undersampling, and oversampling, with very poor sensitivity of the logistic regression, SVM, and kNN based on the original data. With the application of the sampling methods, the results improved. The cluster MWMOTE was proposed to overcome the limitations of oversampling techniques (SMOTE, ADASYN) based on k-NN, which are overgeneralization, noise, sensitivity, and missing some boundary instances [16]. However, MWMOTE does not improve the boundary instances [17]. In addition, the minority class separation is ignored. In [18], the sample-characteristic oversampling technique (SCOTE) based on LS-SVM was proposed for bearing faults diagnosis with an imbalanced dataset. The SCOTE filters out the noisy points by applying k-NN-based noise processing and then trained with LS-SVM. In [19], the comparison of naïve Bayes classifier (NBC), decision tree, and Adaboost algorithm together with SMOTE techniques was implemented for rotor fault on an induction motor. The AdaBoost method was presented to be performing better compared to the other two methods, and NBC has been presented to have the worst performance. However, as the severity of the fault increased, AdaBoost showed poor performance results as presented by performance metrics. In addition, after the SMOTE application, the performance of each classifier improved. The ROC curve performance evaluation presented that AdaBoost outperforms the NBC and decision tree. However, the application of these aforementioned methods to handle the imbalanced dataset is very limited when it comes to condition monitoring in electrical machines, specifically the wound-rotor induction generators (WRIG). 2.2. Imbalanced Dataset When the imbalanced datasets are presented, one class has majority instances and the other classes have minority instances. This results in an uneven distribution of classes and misclassification of minority instances as the classifier system tends to be biased and in favor of the majority instances [20]. The classifier system also tends to ignore the minority classes and detect them as noise [21]. When it comes to electrical machines, the majority of instances are associated with the healthy class and the minority instances are associated with various faults. The data imbalance strategies such as resampling, cost-sensitive learning, and ensemble were developed to work together with various data-driven techniques to handle the imbalanced data. The recall, precision, F-measure, G-mean, and receiver operating characteristics (ROC) curves are the commonly used assessment performance metrics for data imbalance [12]. 2.3. Intelligent Approaches Supervised learning depends on trained and labeled data to predict unlabelled data. The supervised-learning technique is the most commonly used machine learning in electrical machines for the improvement of data imbalance challenges. Bayesian classification is a supervised learning technique that applies logical calculus for making decisions under uncertainty. The key benefit of Bayesian classification is its strong theoretical foundation and mathematical computation to make predictions. Bayesian classification employs Bayes’ theorem, which is an algebraic model based on the fundamentals of probability theory [22]. The additional benefit of NBC includes its time efficiency, CPU usage, and memory. NBC also applies strong independence assumptions and works using an independent feature model [23]. A support vector machine (SVM) is a classifier that aims at determining the hyperplane in linear classification. SVM works well in handling a small amount of data and can improve accuracy. In this method, every single data point is presented as a vector and with each of these data points belonging to two different classes the maximum distance between these points contributes to accuracy and in determining the best hyperplane. For nonlinear classification, SVM employs a kernel machine that replaces the data points. The kernel machine does not require prior information and its computation is simple. However, kernel machine takes longer to process large datasets [11]. 2.4. Resampling Techniques Resampling aims at equalizing the number of instances per class either reducing the majority class instances, known as under-sampling, or increasing the minority class instances, known as over-sampling. Under-sampling techniques reduce the majority instances by randomly eliminating majority class instances [24]. With the advantage that it can improve run time and storage problems. However, it can eliminate important data. The remaining data may be a biased sample and unable to provide accuracy for classes distribution [20,24]. Various under-sampling methods have been proposed, and the most commonly used are random under-sampling and Tomek link (T-link). Tomek developed the Tomek link, which was originally designed for two different classes (one majority and one minority), where, if the majority and minority classes are xa and xb, then the distance between them will be d(xa,xb) and is known as the Tomek link, provided that no other class xz such that d(xa, xz)<d(xa,xb) or d(xb, xz)<d(xa,xb) [25]. T-link works by eliminating the majority class instances that are closer to the minority class by applying the nearest neighbor rule to select instances [26]. T-link is also classified as an improved condensed nearest neighbor [27]. This method can also be applied for post-processing cleaning data when instances from the majority and minority classes are removed, which is due to the lack of well-defined borderline regions. This method can be an under-sampling only when the majority class instances are removed [25]. T-link was applied together with a random forest classifier for the prediction of depression symptoms based on their severity. The results presented to be very poor for some classes based on the evaluation matrices with original imbalanced data. After the T-link application, the results improved drastically. The T-link method was performed as post-process cleaning data. The hybrid of T-link and random oversampling presented improved accuracy compared to individual performances. Over-sampling increases the minority instances by randomly replicating the minority class instances to a required level to represent a balanced class distribution [20,24]. This method has the advantage that no data are eliminated and it performs better compared to under-sampling. However, this method may lead to overfitting due to replicated instances. The synthetic minority over-sampling technique (SMOTE) is an improved oversampling technique that was developed by Chawla [13]. SMOTE is based on a k-nearest neighbor to generate new synthetic sampling in feature space based on a certain percentage for the minority classes. SMOTE can generate new synthetic data based on the existing minority class data without replicating it to overcome the overfitting challenge. This synthetically generated data can be formulated as given in Equation (1):(1) Ssyn=r(SkNN−Sf)+Sf. where Ssyn—generated synthetic samples; Sf—feature samples; SkNN—considered feature sample k-nearest neighbor; and r—a random number between 0 and 1. The classifier develops specific regions based on the synthetic samples. When it comes to rotating machines, the SMOTE has been limited to induction motor faulty rotor bars where NBC, decision tree, and Adaboost algorithm together with SMOTE techniques were compared. After the SMOTE application, the performance of each classifier improved [19]. In this paper, SMOTE and T-link are both used with multiple data generated from both the simulation and experimental work of WRIG. The generator is operated at a resistive load of 300 Ω per phase conditions. 2.5. Assessment Metrics The assessment metrics are based on the confusion matrix, which presents the true positive and true negative classes as shown in Table 1. The metrics are well-defined by Equations (2)–(5) [12]: sensors-22-03246-t001_Table 1 Table 1 Confusion Matrix. Positive Negative Positive True positive (TP) False negative(FN) Negative False positive (FP) True negative (TN) (2) Recall=TPTP+FN (3) Precision=TPTP+FP (4) F−measure=(1+β2)×Recall×Precisionβ2×Recall+Precision (5) G−mean=TPTP+FN×TNTN+FP where recall represents the correctly classified positive attributes and is not sensitive to data changes. In addition, the recall does not provide information with regards to the incorrectly positive labeled attributes [12]. Precision measures the actual correctly labeled attributes and is sensitive to data changes. Similar to recall, precision also does not provide information about incorrectly labeled instances. However, recall and precision have been presented to be effective with data imbalance. The F−measure is the combination of recall and precision as a measure of effectiveness in terms of the ratio of either recall or precision which is weighted by the coefficient β where β is the coefficient to vary the relative importance of precision against the recall. Although the F-measure is sensitive to data changes, it is capable to provide more information compared to accuracy and error rate metrics. The geometry mean (G-mean) metric evaluates the inductive bias degree in terms of correctly classified positive and negative attributes. G−mean performs better compared to the traditional metrics [20]. The receiver operating characteristics (ROC) curves employ single column-based evaluation metrics, which present the true positive rate and false-positive rate. The ROC can provide the threshold of true positives and false positives. The ROC also provides the function sensitivity values and all the points are joined together to form a graph [28]. The ROC’s performance is based on the inclined leaning towards the y-axis and the area under the curve analysis. 3. Methodology 3.1. Overview Typically, the supervised learning classification in condition monitoring depends on the clear distribution of classes. In the case where the distribution of classes is imbalanced—the lack of availability of fault data, as compared to healthy operation data, conveys a challenge to detect which brings uncertainties to applying these methods. The presented methodology investigates the NBC, SVM, and k-NN performances based on simulated and experimental imbalanced data for condition monitoring of a WRIG using combined multiple signals. Then, the resampling methods, namely, SMOTE, T-link, and a combination of SMOTE and T-link are applied to the combined data. Whereas SMOTE is an oversampling method that replicates the minority classes, T-link is an under-sampling method, which, in this investigation, was performed as post-processing cleaning data. The classification techniques verified that with the application of resampling methods, the imbalanced data challenges based on condition monitoring can be reduced for a WRIG. 3.2. Process Description The 3-phase, 1 kW, 380 V, 4 pole wound-rotor induction machine model was created using ANSYS Maxwell. The geometry of the healthy model, indicating flux lines distribution amongst 4 poles, is presented in Figure 1a. Figure 1b presents the geometry with the stator inter-turn short circuit fault implemented in the simulations and the flux lines depict asymmetry distribution. The corresponding external circuit used for excitation of the WRIG is shown in Figure 1c. The faults considered are inter-turn short circuits on the stator windings and the rotor windings, and brush faults. These faults are considered separately, and therefore, multiple models were created—i.e., healthy, stator fault, rotor fault, and brush fault. The WRIG machine has three-phase windings on both the rotor and stator. Faults are modeled through short-circuiting the turns of one of the phase coils. Three and six turns are short-circuited in each case to incorporate the different levels of the same fault type. The brush fault is simulated by connecting a 0.5 Ω resistor in series with the brush rotor in the external circuit. Different instances are obtained by randomly varying the external circuit excitation capacitor by ±2% [29]. The WRIG experimental layout, the stator inter-turn short circuit, and rotor inter-turn faults modifications on the machine are presented in Figure 2a–c. The setup entails a three-phase, 1 kW, 380 V, 4 pole wound-rotor induction machine, capacitor bank, circuit breakers, prime mover, variable speed drive, variable resistors, voltage/current transducer, shaft encoder, and data acquisition card. The WRIG model constructed is modified to account for the three considered fault conditions, which are the inter-turn short circuit in the stator windings, the inter-turn short circuit in the rotor windings, and the brush fault. The modification for inter-turn winding faults is implemented on the overhangs of the stator and the rotor. The 3.7 Ω variable resistor is connected in series with the brush for fault implementation. 3.3. Feature Extraction The data attained through the simulation measurements are processed with the Fast-Fourier transform (FFT) applied to all the signals. In practice, these signals are simply recorded using voltage and current sensing. A sample of the stator voltage under healthy steady-state conditions for a portion of the acquisition time for the WRIG with load is presented in Figure 3a. Figure 3b presents the spectra with a two-second acquisition time for the measured stator voltage signals under healthy conditions, where the WRIG is operated at resistive load conditions of 300 Ω per phase at 1347 rpm speed. These signals consist of 11 orders per phase including the DC component for both stator current and voltage, and 10 per phase for the rotor current. The 11 orders for each case start from and DC harmonic component and odd and even harmonics up to 500 Hz. Therefore, 33 various features were obtained for each data instance of stator phase voltage and current and 30 features for each instance of the rotor phase currents. The harmonics obtained from the FFT are then normalized with respect to the maximum and minimum harmonic for feature scaling, better harmonic resolution, and relative significance of the fundamental harmonic. Therefore, when normalized, the magnitude of all harmonics orders are calculated with respect to the fundamental. The fundamental harmonic component is equal to unity after normalization. Each harmonic for multiple signals is then extracted and used as features for various classification and resampling methods, namely, Bayesian classification, Support Vector Machines (SVM), and k-nearest neighbors (k-NN), together with Tomek link (T-link), synthetic minority over-sampling sampling (SMOTE), and combined SMOTE and T-link methods. 3.4. Classification Process The classification of the generator imbalanced data was performed with python anaconda for each scenario, that is, the stator voltage and current, and rotor current as presented in Table 2. These cases are for training purposes, and the faults may not occur at the same time. The investigated method is shown in Figure 4. The NBC, SVM, and k-NN classification methods were first applied to the original imbalanced simulated and experimental data cases. The data had a test split of 20% in each case. The resampling methods were applied individually which are SMOTE and T-link based on each data case. the integrated SMOTE and T-link method was also applied based on each case. The classification methods were reapplied to the resampled simulated and experimental data with the accuracy score, weighted averages of precision, recall, and F1-score results recorded. 4. Results and Analysis 4.1. Simulation Analysis The NBC, SVM, and k-NN applications, together with SMOTE, T-link, and the combination of SMOTE/T-link for each case, are presented. The performance measures such as precision, recall, and F1-score are also presented. The weighted average of these performance measures ranges from 45% to 50% with the application of NBC on the original data for 20% of the test data. For various test data and cases, the improvement can be identified as presented in the figures below. Figure 5, Figure 6 and Figure 7 present the NBC with SMOTE, NBC with T-link, and NBC with a combination of SMOTE/T-link. The NBC with SMOTE presents the highest accuracy and recall—0.722; precision—0.839; andF1-score—0.777 with data level case 4. With data level case 6 being the worst scenario with the accuracy and recall—0.5, precision—0.504; and F1-score—0.49. The NBC with SMOTE has a minimum of 50% and a maximum of 70%. The NBC with T-link on data level case 2 has the worst performance with an accuracy and recall of 42.9%, a precision of 35.7, and an F1-score of 38.4%. The data level case 4 has the best performance with 0.7—accuracy and recall; 0.65—precision; and 0.643—F1-score. Although the precision of case 6 is 0.929, its F1-score is 0.554, which presents a low performance. The NBC with T-link has a minimum accuracy of 40% and a maximum of 60%. The NBC with combined SMOTE/T-link presents improvements on all the data level cases of individual SMOTE. When combined compared to the individual performance of the T-link, most cases have drastically improved except case 3 with 0.636—accuracy and recall; 0.62—precision; and 0.6—F1-score performance below the individual T-link. The NBC with combined SMOTE/T-link has a minimum accuracy of 63% and a maximum of 78%. Figure 8, Figure 9 and Figure 10 present the SVM with SMOTE, SVM with T-link, and SVM with a combination of SMOTE/T-link. The SVM with SMOTE presents the best data level cases performance with slight improvements. Data level cases 3 and 6 show performances below the SVM without SMOTE with 17.7% and 21%—accuracy and recall; 14.3% and 21.1%—precision; and 10.79% and 12.8%—F1-score, respectively. The SVM with SMOTE has a minimum accuracy of 36% and a maximum of 58%. The SVM with T-link shows improvements in each case, with case 5 being the lowest, which performs with 0.6—accuracy and recall; 0.55—precision; and 0.543—F1-score. Case 6 shows the best performance with 0.786—accuracy and recall; 0.764—precision; and 0.728—F1-score. The SVM with T-link has a minimum accuracy of 60% and a maximum of 78%. In the SVM with combined SMOTE/T-link, most cases show slight improvements, with cases 3 and 6 present the poorest performances of 15.7% and 8.7%—accuracy and recall; 0.3% precision; and 12.4% and 3.8%—F1-score, respectively, which is below the classifier’s performance without the resampling technique. The SVM with combined SMOTE/T-link has a minimum accuracy of 48% and a maximum of 63%. Figure 11, Figure 12 and Figure 13 present the k-NN with SMOTE, k-NN with T-link, and k-NN with a combination of SMOTE/T-link. The k-NN with SMOTE presents improvements for all the cases, with case 4 showing better results of 0.806—accuracy and recall; 0.821—precision; and 0.806—F1-score. The k-NN with SMOTE has a minimum of 61% and a maximum of 80% accuracy. The k-NN with T-link presents improvements for most cases, excluding case 4, which presents a performance that is below the k-NN without T-link with 7.3%—accuracy and recall; 10.1%—precision; and 10.6%—F1-score. The k-NN with T-link has a minimum of 57% and a maximum of 70% accuracy. The k-NN with combined SMOTE/T-link shows improvements in all the cases, with case 3 showing the highest performance with 0.848—accuracy and recall; 0.878—precision; and 0.843—F1-score. Case 5 presents the lowest performance with 0.758—accuracy and recall; 0.811—precision; and 0.734—F1-score. Although case 5 has the lowest performance, the improvement is over 30% compared to k-NN without the SMOTE/T-link method. The k-NN with combined SMOTE/T-link has a minimum accuracy of 75% and a maximum of 84%. 4.2. Experimental Analysis Based on the various cases with the split of 20% test experimental data. Figure 14, Figure 15 and Figure 16 present the weighted average performances of NBC with SMOTE, NBC with T-link, and NBC with SMOTE/T-link. The NBC with SMOTE presents case 5 with the best performance of 0.75—accuracy and recall; 0.86—precision; and 0.751—F1-score. The lowest performance is presented in case 6. The NBC with SMOTE has a minimum accuracy of 50% and a maximum of 75%. The NBC with T-link presents case 3 with the highest performance of 0.643—accuracy and recall; 0.81—precision; and 0.68—F1-score. Case 4 presents the poor performance of 0.25—accuracy and recall; 0.5—precision; and 0.333—F1-score, which is below the NBC without T-link. The NBC with T-link has a minimum accuracy of 25% and a maximum of 64%. The NBC with combined SMOTE/T-link presents case 5 with the highest performance of 0.697—accuracy and recall; 0.739—precision; and 0.686—F1-score. The NBC with combined SMOTE/T-link has a minimum accuracy of 51% and a maximum of 70%. Figure 17, Figure 18 and Figure 19 present the weighted average performances of SVM with SMOTE, SVM with T-link, and SVM with SMOTE/T-link. The SVM with SMOTE presents case 2 having the highest performance of 0.5—accuracy and recall; 0.707—precision; and 0.506—F1-score. All other cases present slight improvements. The SVM with SMOTE has a minimum of 45% and a maximum of 56% accuracy. The SVM with T-link shows most of the cases with slight improvements, except case 6, which presents a performance with 16% lower accuracy and recall and a 13.4% lower F1-score than the performance of SVM without T-link. The SVM with T-link has a minimum accuracy of 40% and a maximum of 57%. The SVM with combined SMOTE/T-link presents each case with slight improvements. Case 4 has the highest performance with a 0.656 accuracy and recall, a 0.571 precision, and a 0.605 F1-score. Although case 6 precision is 0.732, which is higher, but the accuracy and F1-score are lower compared to case 4. The SVM with combined SMOTE/T-link has a minimum accuracy of 39% and a maximum of 65%. Figure 20, Figure 21 and Figure 22 present the weighted average performances of k-NN with SMOTE, k-NN with T-link, and k-NN with SMOTE/T-link. The k-NN with SMOTE presents the highest performance of 0.972—accuracy and recall; 0.975—precision; and 0.971—F1-score. Although case 5 is shown to be the lowest performer with 0.722—accuracy and recall; 0.734—precision; and 0.713—F1-score, the performance has tremendously improved. The k-NN with SMOTE has a minimum accuracy of 72% and a maximum of 97%. The k-NN with T-link presents case 6 with the highest performance of 0.9—accuracy and recall; 0.976—precision; and 0.9—F1-score. Cases 4 and 5 present very slight improvements, with case 5 being the lowest performer. The k-NN with T-link has a minimum of 45% and a maximum of 90% accuracy. The k-NN with combined SMOTE/T-link presents extreme improvements for all the cases. Cases 2 and 6 presented the highest performance of 0.972—accuracy and recall; 0.976—precision; and 0.972—F1-score. The k-NN with combined SMOTE/T-link has a minimum accuracy of 71% and a maximum of 97%. 4.3. Discussions In this study, T-link was performed in a data-handling pipeline to address imbalanced data in both simulation and experiments. For the simulation testing, the NBC performance after applying T-link presents improved results compared to original imbalanced data and NBC with SMOTE. The combination of SMOTE and T-link provided improved results in some cases, and in other cases, the performances present improvement compared to SMOTE results and underperformance compared to T-link. For experimental testing, the NBC with SMOTE presented improved and higher performance results compared to T-link and also outperforms the combination of SMOTE/T-link. The NBC with resampling methods for simulated and experimental data has a minimum of 40% and 50% and a maximum of 78% and 75%, respectively. In the SVM with SMOTE application for simulation, the performance measurements present average improvement for other cases, and for some cases, they perform similar to the original imbalanced data. Even with the combination of SMOTE and T-link sampling methods, in this study, there are cases where the performance is similar to the original. On experimental data, the SVM with SMOTE showed improvements in each case, which outperforms the SVM with T-link which presented case 6 to be performing below the SVM without T-link. The SVM with the combination of SMOTE/T-link outperforms individual methods. The SVM with resampling methods for simulated and experimental data has a minimum of 36% and 39% and a maximum of 78% and 65%, respectively. In the k-NN with original imbalanced data, the performance measures range from 33.3% to 50%. After the application of SMOTE and T-link, the performance increased for various cases and test data. With the combined SMOTE and T-link, the performances present improvement for each case. On experimental, the k-NN with SMOTE presented the best performance results compared to the k-NN with T-link. The k-NN with the combined methods outperforms individual methods. The k-NN with resampling methods for simulated and experimental data has a minimum of 57% and 71% and a maximum of 84% and 97%, respectively. The application of NBC, SVM, and k-NN classification algorithms to an imbalanced distribution affects the performance of the classification. The introduction of SMOTE and T-link resampling methods improved the performance of these classifiers. The T-link method in this investigation presented superior performance compared to SMOTE for simulated data. With experimental data, the SMOTE was superior compared to T-link. The SVM classification presented a poor performance compared to NBC and k-NN for both the simulated and experimental data. The integration of SMOTE and T-link outperforms the individual sampling methods. The T-link method performs as post-processing cleaning data by eliminating the majority and minority classes to provide well-defined borderlines. Then, SMOTE is performed with clear regions which provide improved performance for each classification method. 5. Conclusions Data-driven approaches have become attractive in condition monitoring on electrical machines, as they offer the potential benefits of flexibility, scalability, and relatively quicker and cheaper development. Within the data-driven approaches, the supervised learning methods are accuracy-driven and adjust the overall accuracy with minimum errors and ignoring the distribution of each class. The classifier’s accuracy effectiveness depends on even distribution for each class. The misclassification of abnormalities can be costly. The challenge of data imbalance remains an issue for supervised learning approaches—the classifier becomes biased and favors the majority class. There is typically a lack of fault data for different fault classes in practice, which hinders the proliferation of supervised learning-based condition monitoring systems for electrical rotating machines, such as the WRIG. This paper address this challenge and presents a comparative analysis of fault data imbalance approaches, based on different classifiers. Several key metrics are used to evaluate the approaches when applied on different levels and types of WRIG-fault-data imbalance. The NBC, SVM, and k-NN classifiers are compared when used in conjunction with the SMOTE, T-link, and a combination of SMOTE and T-link methods on combined features for fault classification. The evaluation metrics were presented, and the analysis of the above-mentioned classifiers indicates improved performances after the application of SMOTE, T-link, and a combination of the resampling methods. Based on the WRIG’s simulated and experimental imbalanced data under investigation, the accuracies of each of the tested classifiers with the resampling methods are as follows:The NBC with resampling methods for simulated and experimental data has a minimum accuracy of 40% and 50% and a maximum of 78% and 75%, respectively. The SVM with resampling methods for simulated and experimental data has a minimum accuracy of 36% and 39% and a maximum of 78% and 65%, respectively. The k-NN with resampling methods for simulated and experimental data has a minimum accuracy of 57% and 71% and a maximum of 84% and 97%, respectively. Although the k-NN classifier, when tested with the presented resampling methods, shows the best overall performance for both simulated and experimental data cases, it is found that the combination of the SMOTE and T-link resampling methods does yield improved performance across all classifiers. Author Contributions E.F.S.: conceptualisation, formal analysis, methodology, experiments, writing, editing and results validation. W.D.: Formal analysis, writing, editing, results validation, project administration, supervision, conceptualisation and critical revision. P.B.: project administration, supervision, and critical revision. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the University of Johannesburg, and by Eskom under the Tertiary Education Support Program (TESP) grant (“Analytics for predictive maintenance on electrical machines”) awarded to W.D. Institutional Review Board Statement Not Applicable. Informed Consent Statement Not Applicable. Data Availability Statement Not Applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (a) Geometry of wound-rotor induction generator model with flux lines distribution; (b) Flux lines distribution with stator winding inter-turn fault indicated (by arrow); (c) External circuit of the investigated wound-rotor induction generator. Figure 2 (a) Experimental layout; (b) Stator winding inter-turn fault; (c) Rotor winding inter-turn fault. Figure 3 (a) Three-phase steady−state stator phase voltage shown for a portion of acquisition time used; (b) stator voltage phase U under healthy conditions. Figure 4 The method for WRIG imbalanced data. Figure 5 Simulation performance of NBC classification with SMOTE. Figure 6 Simulation performance of NBC classification with T-link. Figure 7 Simulation performance of NBC classification with SMOTE/T-link. Figure 8 Simulation performance of SVM classification with SMOTE. Figure 9 Simulation performance of SVM classification with T-link. Figure 10 Simulation performance of SVM classification with SOMTE/T-link. Figure 11 Simulation performance of k-NN classification with SMOTE. Figure 12 Simulation performance of k-NN classification with T-link. Figure 13 Simulation performance of k-NN classification with SMOTE/T-link. Figure 14 Experimental performance of NBC classification with SMOTE. Figure 15 Experimental performance of NBC classification with T-link. Figure 16 Experimental performance of NBC classification with SMOTE/T-link. Figure 17 Experimental performance of SVM classification with SMOTE. Figure 18 Experimental performance of SVM classification with T-link. Figure 19 Experimental performance of SVM classification with SMOTE/T-link. Figure 20 Experimental performance of k-NN classification with SMOTE. Figure 21 Experimental performance of k-NN classification with T-link. Figure 22 Experimental performance of k-NN classification with SMOTE/T-link. sensors-22-03246-t002_Table 2 Table 2 Summary of tested cases indicated number of examples per class (or condition on WRIG). Description Class Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Healthy 0 30 30 30 30 30 30 Brush 1 30 18 12 9 6 24 Inter-turn short stator—3 2 30 15 9 7 6 18 Inter-turn short stator—6 3 30 9 6 6 6 9 Inter-turn short rotor—3 4 30 9 8 7 6 18 Inter-turn short rotor—6 5 30 7 6 6 6 6 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Khan M.U. Imtiaz M.A. Aziz S. Kareem Z. Waseem A. Akram M.A. System design for early fault diagnosis of machines using vibration features Proceedings of the IEEE 5th International Conference on Power Generation Systems and Renewable Energy Technologies Istanbul, Turkey 26–27 August 2019 2. Spyropoulos D.V. Mitronikas E.D. A review on the faults of electric machines used in electric ships Adv. Power Electron. 2013 2013 216870 10.1155/2013/216870 3. Salomon C.P. Ferreira C. Sant’Ana W. Lambert-Torres G. Borges da Silva L.E. Bonaldi E.L. Oliveira L. Torres B. A study of fault diagnosis based on electrical signature analysis for synchronous generators predictive maintenance in bulk electric systems Energies 2019 12 1506 10.3390/en12081506 4. Rehman A.U. Chen Y. Wang L. Zhao Y. Yonghong Y. Yonghong C. Tanaka T. Experimental research and analysis on rotor winding inter-turn circuit fault in DFIG Proceedings of the IEEE International Conference on Condition Monitoring and Diagnosis Xi’an, China 25–28 September 2016 5. Sun W. Zhao R. Yan R. Shao S. Chen X. Convolutional discriminative feature learning for induction motor fault diagnosis IEEE Trans. Ind. Inform. 2017 13 1350 1359 10.1109/TII.2017.2672988 6. Jung D. Sundström C. A combined data-driven and model-based residual selection algorithm for fault detection and isolation IEEE Trans. Control. Syst. Technol. 2017 27 616 630 10.1109/TCST.2017.2773514 7. Dai X. Gao Z. From model, signal to knowledge: A data-driven perspective of fault detection and diagnosis IEEE Trans. Ind. Inform. 2013 9 2226 2238 10.1109/TII.2013.2243743 8. Wang L. Zhang Z. Long H. Xu J. Liu R. Wind turbine gearbox failure identification with deep neural networks IEEE Trans. Ind. Inform. 2017 13 1360 1368 10.1109/TII.2016.2607179 9. Zhao X. Jia M. Liu Z. Semi-supervised graph convolution deep belief network for fault diagnosis of electromechanical system with limited labeled data IEEE Trans. Ind. Inform. 2020 17 5450 5460 10.1109/TII.2020.3034189 10. Wang Z. Chen C. Li H.X. Dong D. Tarn T.J. Incremental reinforcement learning with prioritized sweeping for dynamic environments IEEE/ASME Trans. Mechatron. 2019 24 621 632 10.1109/TMECH.2019.2899365 11. Zhang T. Chen J. Li F. Zhang K. Lv H. He S. Xu E. Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions ISA Trans. 2021 119 152 171 33736889 12. Mathew R.M. Gunasundari R. A review on handling multiclass imbalanced data classification in education domain Proceedings of the International Conference on Advance Computing and Innovative Technologies in Engineering Greater Noida, India 4–5 March 2021 13. Chawla N.V. Bowyer K.W. Hall L.O. Kegelmeyer W.P. SMOTE: Synthetic Minority Over-sampling Technique J. Artif. Intell. Res. 2002 16 321 357 10.1613/jair.953 14. Sun J. Li H. Fujita H. Fu B. Ai W. Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting Inf. Fusion 2020 54 128 144 10.1016/j.inffus.2019.07.006 15. Wah Y.B. Rahman H.A.A. He H. Bulgiba A. Handling imbalanced dataset using SVM and AIP Conf. Proc. 2016 1750 020023 16. Babar V.S. Ade R. A review on imbalanced learning methods Int. J. Comput. Appl. 2015 975 23 27 17. Jianan W. Haisong H. Liguo Y. Yao H. Qingsong F. Dong H. New imbalanced fault diagnosis framework based on Cluster-MWMOTE and MFO-optimized LS-SVM using limited and complex bearing data Eng. Appl. Artif. Intell. 2020 96 103966 18. Wei J. Huang H. Yao L. Hua Y. Fan Q. Huang D. New imbalanced bearing fault diagnosis method based on Appl. Soft Comput. J. 2021 101 107043 10.1016/j.asoc.2020.107043 19. Martin-Diaz I. Morinigo-Sotelo D. Duque-Perez O. Romero-Troncoso R.J. Early fault detection in induction motors using AdaBoost with imbalanced small data and optimized sampling IEEE Trans. Ind. Appl. 2017 53 3066 3075 10.1109/TIA.2016.2618756 20. Fergus P. Huang D. Hamdan H. Prediction of intrapartum hypoxia from cardiotocography data using machine learning Applied Computing in Medicine and Health—Emerging Topics in Computer Science and Applied Computing Al-Jumeily D. Hussain A. Mallucci C. Oliver C. Elsevier Amsterdam, The Netherlands 2016 Volume 1 125 146 21. Napierala K. Stefanowski J. Types of minority class examples and their influence on learning classifiers from imbalanced data J. Intell. Inf. Syst. 2016 46 563 597 10.1007/s10844-015-0368-1 22. Doorsamy W. Cronje W.A. Optimisation of shaft voltages based condition monitoring in generators using a Bayesian approach Proceedings of the 7th IET International Conference on Power Electronics (PEMD), Machines and Drives Manchester, UK 8–10 April 2014 23. Taroni F. Biedermann A. Bozza S. Garbolino P. Aitken C. Bayesian Networks for Inference and Decision Analysis in Forensic Science 2nd ed. John Wiley & Sons Hoboken, NJ, USA 2014 1 43 24. Hasib A.K. Iqbal M. Shah F. Mahmud J. Popel M. Showrov M.I.H. Ahmed S. Rahman O. A Survey of methods for managing the classification and solution of data imbalance Problem J. Comput. Sci. 2020 16 1546 1557 10.3844/jcssp.2020.1546.1557 25. Pereira R.M. Costa Y.M.G. Silla C.N. Jr. MLTL: A multi-label approach for the Tomek Link undersampling algorithm Neurocomputing 2020 383 95 105 10.1016/j.neucom.2019.11.076 26. Sawangarreerak S. Thanathamathee P. Random Forest with sampling techniques for handling imbalanced prediction of university student depression Informations 2020 11 519 10.3390/info11110519 27. Tusneem E. Aljourf M. Al-Mohanna F. Mohamed S. Classification of imbalance data using Tomek link (T-link) combined with random under-sampling (RUS) as a data reduction method Glob. J. Technol. Optim. 2021 1 1 12 28. Bekkar M. Djemaa H.K. Alitouche T.A. Evaluation measures for models assessment over imbalanced data sets J. Inf. Eng. Appl. 2013 3 27 38 29. Swana E.F. Doorsamy W. Investigation of combined electrical modalities for fault diagnosis on a wound-rotor induction generator IEEE Access 2019 7 32333 32342 10.1109/ACCESS.2019.2904238

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093220 sensors-22-03220 Article High Sensitivity Surface Plasmon Resonance Sensor Based on a Ge-Doped Defect and D-Shaped Microstructured Optical Fiber Cunha Nilson H. O. * https://orcid.org/0000-0003-1843-7879 da Silva José P. Missinne Jeroen Academic Editor Van Steenberge Geert Academic Editor Geernaert Thomas Academic Editor Post-Graduated Program in Electrical and Computer Engineering, Technology Center, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; jose.patrocinio@ufrn.br * Correspondence: nilson.ee@gmail.com 22 4 2022 5 2022 22 9 322001 4 2022 19 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In this work a plasmonic sensor with a D-Shaped microstructured optical fiber (MOF) is proposed to detect a wide range of analyte refractive index (RI ;na) by doping the pure silica (SiO2) core with distinct concentrations of Germanium Dioxide (GeO2), causing the presentation of high spectral sensitivity. In this case, the fiber is shaped by polishing a coating of SiO2, on the region that will be doped with GeO2, in the polished area, a thin gold (Au) layer, which constitutes the plasmonic material, is introduced, followed by the analyte, in a way which the gold layer is deposited between the SiO2. and the analyte. The numerical results obtained in the study shows that the sensor can determine efficiently a range of 0.13 refractive index units (RIU), with a limit operation where na varies from 1.32 to 1.45. Within this application, the sensor has reached an average wavelength sensitivity (WS) of up to 11,650.63 nm/RIU. With this level of sensitivity, the D-Shaped format and wide range of na detection, the proposed fiber has great potential for sensing applications in several areas. optical sensors microstructured optical fiber surface plasmon resonance refractive index detection Ge-doped defect ==== Body pmc1. Introduction Optical sensors, in general, have the function of determining characteristics of unknown materials, be it temperature, pressure, color, distance or any other parameter. These devices can be constructed from conventional fibers, D-shaped, H-shaped, or any other shape fibers, assuming that it complies with the principle of operation, which is the emission and reception of light and the interpretation of the data received. However, these types of sensors can be optimized with compatible techniques, as is the case of the optical sensors that use the phenomenon of surface plasmon resonance (SPR). In addition, the SPR-based sensors have been widely studied in recent years, mainly due to their real-time response, greater accuracy, sensitivity, adaptability and ease in construction [1,2,3,4], which make these types of sensors very attractive in various applications. The Effect of SPR occurs when light excites an interface between two materials, specifically a metal–dielectric interface, which will cause oscillations of charge density along the interface, these oscillations are called surface plasmon oscillations (SPO) and the quantum of these oscillations is called surface plasmon mode (SPM) [3,4]. The surface plasmons are evanescent waves, that is, they are accompanied by a longitudinal electric field that decays exponentially along the propagation, therefore, the visualization and use of the SPR effect is performed locally, hence the term localized surface plasmon resonance (LSPR) [2,3,4,5,6,7,8]. In this work, the SPR effect is stimulated in the region between the gold layer and the analyte, when the structure is excited at optical frequencies. SPR-based sensors can be easily obtained. In most cases its construction is based only by introducing a metal layer in contact with an excited dielectric material at optical frequencies. However, some models of plasmonic sensors are obtained from special optical fibers, such as those designed from Photonic Crystal Fibers (PCF). In this case, the distribution of the air holes that characterize the PCF can increase the precision of the device, however, they can be more difficult to build. PCF present periodic distribution of air holes along the direction of signal propagation. On the other hand, Microstructured Optical Fibers (MOF) can present a very unique distribution of air holes, including quasi–periodic formats, or even asymmetrical formats [9], which can increase the rate of precision and speed in the SPR response. In this case, the MOF-based SPR presented in this paper, can be easily constructed, as it presents a smaller number of distributed holes, better organized in the transversal section. Thus, it is quite clear that an SPR can be compatible with several models of existing optical structures, as is the case of MOF. Microstructured optical fibers are structures that have holes, usually of air, along their entire direction of propagation. The function of these holes, for the most part, is to create photonic bandgaps, causing the signal to be confined in a certain region of the fiber. As such, these holes can have different shapes, such as rectangular and elliptical [7,8], for example, in addition to being able to cause multicores in the fiber [10,11]. The applications, in which the MOF appear are the most varied, such as for chromatic dispersion adjustment [12], interferometers operating point adjustment [13], imaging [14] and even gas sensing, using the holes of the structure as microchannels [15]. When studying SPR-based MOF sensors, the effect that the holes cause on the sensor is highly relevant to obtain the desired results. The air holes can be utilized as guides for the internal fields of fiber, producing LSPR in the desired regions, which is where the analysis materials are. Therefore, parameters such as sensitivity, range of operation, confinement losses, among others, are directly determined by the distribution, shape and parameterization of the MOF holes. It is important to note that the study of MOF holes are of great importance when it is desired to build SPR-based sensors, as they provide a wide variety of devices [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32], each unique and with distinct properties, which can be used in specific applications. In this work, the analysis of an SPR-based optical sensor on a substrate formed by a MOF with a D-shape is proposed. In the following sections are presented the simulation theories, the proposed sensor design, the results of the sensor characteristics that were obtained in the development of this work, as well as a comparison of the proposed sensor with other studies found in the literature, and finally, the conclusions and possible applications of this device. 2. Plasmonic Sensor Design and Simulation In this work, a D-shaped fiber was developed as a sensor. Normally, these fiber models are not easy to theoretically model, mainly due to the disturbance in its axial symmetry, when one of its edges is subjected to a polishing process. For the MOF project in question, polishing occurs in its longitudinal plane, by removing a part of the fiber SiO2 core. The removal of a part of the core allows the evanescent field, which propagates in this region of the optical fiber, to be coupled to the external environment. To take advantage of this phenomenon, a thin film of gold is fixed to the SiO2 core, where part of the material was removed, where on the other side of this blade is placed the material that constitutes the analyte, as seen in Figure 1, which shows the design of the structure used as an optical sensor. Thus, a change in the coupling condition is caused when the structure is excited at optical frequencies. In Figure 1, rc=17 μm, represents the radius of the SiO2 core; d1=1.6 μm, represents the diameter of the defect, included in the center of the structure; d2=2.8 μm represents the diameter of the air holes, quasi-periodically distributed; Λ=7.93 μm, is the distance between the centers of the air holes (pitch). In addition, in this work the thickness of the gold layer used was tAu=50 nm, while the distance from the center of the structure to the gold film used was d=2.55 μm. For surface wave absorption, a circular type PML (Perfectly Matched Layer), of thickness tPML=1 μm, was used. For the theoretical analysis of the structure, a formulation [33] based on the finite element method (FEM) is used. For the purpose of applying the FEM, the structure was discretized in 12,171 triangular elements, concentrating smaller elements, with minimum size of 10.8 nm, on the Au film. In the other regions of the structure, the maximum size of the elements was 4.68 μm. The x and y coordinates represent the transverse directions and z represents the direction of propagation, as shown in Figure 1. In this case, the formulation is directly obtained from the Maxwell equations, reaching a global matrix equation given by: [A]{φ}=neff2[B]{φ}. Here [A] and [B] are complex and sparse matrices. In addition, this equation can be solved using an iterative subspace method, where refractive index (RI) doping variations are included directly in the calculations. Since, neff represents the effective refractive index, it can be directly obtained through the matrix expression mentioned above. Other important aspects for the good performance of the sensor are the materials that form the signal guiding structure, as well as the plasmonic response of the gold film when subjected to optical frequencies. As the structure is composed of materials with different permittivity and when these materials are excited at optical frequencies, an effective permittivity is obtained, from which the effective refractive index of the structure can be calculated. In this design, the guiding structure is composed of a MOF with a SiO2 core, in which a defect is introduced, as shown in Figure 1. The permittivity of the material that forms the defect is initially constituted by SiO2, and then tests are carried out using doping with Germanium Dioxide (GeO2). The concentrations of GeO2 used were 4.1%, 6.3%, 13.5% and 19.3%, respectively. These doping values were chosen due to implications for the construction process. It is important to note that a small percentage of atoms of the dopant material in the silica crystal lattice may produce drastic changes in its dielectric proprieties, in this case, the doping percentages were selected so as not to cause structural damage in the fiber manufacturing process. In conventional fibers, the maximum percentage of core varies is around 4% so that no damage occurs when pulling the fiber. On the other hand, in microstructured optical fibers (MOF) the pure silica matrix supports higher percentages of GeO2, and in this case, these values were chosen to meet the manufacturing needs. The air holes of MOF are distributed in a quasi-periodic way in the cross section of D-shaped fiber and extend along the direction of propagation (z). The geometric distribution of the holes, as well as their respective dimensions, were obtained based on [12] using genetic algorithms with fitness function guided by a local search space, where the optimized parameters were the radius of the air holes, the radius of the defect and the distance between the centers of the air holes. The plasmonic element used is the gold and sensing analysis is verified by the RI of the analyte (na). Generally, to measure the capacity of a plasmonic sensor, several parameters can be used, however, the most common are the confinement losses (CL) and wavelength sensitivity (WS). However, parameters such as amplitude sensitivity (AS), transmission coefficient (T) and plasmonic field amplitude can be used. The effect of noise and distortions in the fiber were not considered in the simulations. Confinement loss is a common effect, which usually is associated with air holes when the fiber is microstructured. That is, it can be directly related to the size, distribution, number of air holes of the MOF and the wavelength of operation [34]. The CL can be obtained according to Equation (1):(1) CL(dB/cm)=8.686×2×π×104×Im(neff)λ  where neff is the complex effective refractive index, obtained from the modal analysis of the structure and λ is the wavelength of operation in micrometers. The wavelength sensitivity, or spectral sensitivity, represents the rate of variation in the excitation wavelength in relation to na, that is, the variation in the analyte will be detected by the change of peak resonance [27,28,35], and its result defines WS in terms of the refractive index unit (RIU). The WS can be obtained by Equation (2):(2) WS=∆λΔn (nm/RIU) , where ∆λ is the variation in the wavelength of the peak resonance and Δn indicates the variation in the refractive index. In all simulations, to obtain the permittivity of the materials, the Sellmeier equation [35] was used, according to Equation (3):(3) ε(λ)=1+∑k=13Bkλ2λ2−Ck2, where λ represents the excitation wavelength in μm, B and C are the coefficients of the Sellmeier equation that vary according to the material used. Table 1 shows the values of Sellmeier coefficients used in this work. In addition, Table 2 shows the refractive index values obtained for the different silica doping with GeO2, with the direct application of the Sellmeier equation, presented in Equation (3). As the Sellmeier equation returns a result as a function of the wavelength, then for the case of this article, a step of 0.5 μm in the wavelength was considered and in this way the RI values for the entire analysis spectrum were obtained. It is important to highlight that the percentages of doping could not be optimized as they were obtained from experimental studies [35] on Sellmeier equations, so the coefficients are predetermined. Due to the formulation used in this work to perform the simulations, all materials must be treated as dielectric. Therefore, to obtain the complex permittivity of the plasmonic element used in this work, the Drude–Lorentz model [36] was applied. This model represents a widespread way of determining the complex permittivity of metallic materials as a function of wavelength. Thus, the refractive index of the plasmonic element can be obtained directly by application of the Drude–Lorentz model. Figure 2 shows the variation in the real part (red line) and the imaginary part (blue line) of the Au refractive index. 3. Results and Discussions To perform the simulations, a proper formulation was used [33]. The formulation uses the Helmholtz wave equation, obtained from the Maxwell Equations, considering the complex permittivity of dielectric material with transverse anisotropy. In this algorithm, the wave equation is numerically solved using the FEM in conjunction with the Galerkin Method. The cross section of the structure is discretized with triangular elements and the characteristics of the materials used are directly introduced into the permittivity (including the gold layer). To limit the computational domain, Perfectly Matched Layers (PML) of the circular type are applied directly in the formulation. The computational code is implemented in the FORTRAN language and the results are exported to be plotted in other numeric computing platforms. In addition, to generate the mesh of the structure a mesh generation software is used, and the data is generated on these platforms and exported directly to the computation algorithm. First, the modal analysis of the structure was performed to obtain the fundamental mode, or first order mode, as well as the verification of the emergence of LSPR, through the contour lines of the magnetic field (H), polarized in the y direction, presented in Figure 3. Figure 3a shows that the energy concentration of the fundamental mode in the core is contained by the air holes of the MOF, however, it is perceived as the appearance of LSPR, as can be analyzed in more detail in Figure 4. In Figure 3b, due to the percentage of doping added in the defect, there is a greater passage of energy from the fundamental mode to the plasmonic mode. This is explained by the increase in energy within the defect, being closer to the metal-dielectric interface, and when the structure reaches the plasmonic frequency, the intensity of the plasmonic mode becomes consequently higher. Analyzing Figure 4, the localized appearance of surface plasmons is confirmed. It is also confirmed that the field inside the region of the gold layer is practically null, which in fact proves the effect of SPR. For the defects doped with GeO2 (4.1%), GeO2 (6.3%) and GeO2(19.3%) the same effect is observed, however, what occurs are variations in the intensities of the fundamental and plasmonic modes, which will directly interfere in the parameters of the confinement losses and wavelength sensitivity. In this work, four variations in doping in the defect immersed in the MOF core will be analyzed and compared, in addition to the analysis considering doping of 0%, which corresponds to pure silica. The visualization of the plasmonic and fundamental mode, can be observed more easily from the analysis of the one-dimensional electric field (E) component, calculated from a cross-sectional line positioned in y = 0. Thus, one can see in a more simplified way the effects that occur in plasmonic and fundamental modes, in relation to the variations in na. Figure 5 presents a horizontal cut performed in the center of the fiber, to show a generic example of the one-dimensional E-field, in which the plasmonic modes and the fundamental modes are formed. All simulations used to analyze the electric field were performed for the excitation wavelength of 1.55 μm. This wavelength was chosen due to the greater number of applications with optical fibers being around this wavelength range, however, it should be noted that the sensor was designed to operate in a wider spectrum. Figure 6 shows one-dimensional E curves, considering the sensor with SiO2 core without the defect in the center of the structure, for a wavelength of 1.55 μm. In Figure 6a, it can be observed that for analytes within the RI range of 1.35 to 1.43, the effect of LSPR occurs, and a portion of the energy contained in the fundamental mode is coupled to the plasmonic mode, that is, as na increases, the energy of the fundamental mode decreases, while that of the plasmonic mode increases. For na=1.35, the fundamental mode reaches a maximum of 97.83 V/m, while the maximum plasmonic mode is 14.46 V/m. At the other extreme, for na=1.43, the peak of the fundamental mode is 53.36 V/m and that of the plasmonic mode is 41.62 V/m, about 45% of the fundamental mode. In addition, the detection range of this sensor configuration operates for analytes with RI between 1.35 and 1.42. Figure 6a also shows a bandgap where the air hole of the MOF is located, which is already an expected effect of these type of fibers, there is also a discontinuity of the E-field in the gold laminate, which was also predictable, since due to the skin effect, the field inside a conductive material tends to be null. Figure 6b presents a local analysis of the E-field, around the region of the gold layer, which is the region where the surface plasmons will appear. Figure 6b confirms that as the energy concentrated in the fiber defect decreases, the energy located in the plasmonic mode increases. Figure 7 shows the variation in E-field, considering the introduction, in the core of the MOF, of a defect filled with silica material doped with germanium. In this case, a similar behavior is observed, as can be seen in the following curves. For simulation purposes, graphs in Figure 6 and Figure 7 were generated with the same number of points. In Figure 7, it is observed that with the introduction of the GeO2 in the defect, there is an increase in the detection range of the proposed sensor. Figure 7a, shows results considering the material of the defect doping with GeO2 (4.1%). Here, the operating range of analyte for RI occurs for values from 1.35 to 1.44. With na=1.34 the maximum value of the fundamental mode is 77.46 V/m, while that of the plasmonic mode is 8.67 V/m, for na=1.44, the highest value of the fundamental mode is 16.5 V/m while that of plasmonic mode is 47.76 V/m. Figure 7b, shows results for a defect doping with GeO2 (6.3%), this configuration allows the sensor to operate for analytes with RI ranging from 1.33 to 1.43, so for na=1.33 the maximum value of the fundamental mode is 89.66 V/m while the plasmonic mode is 6.03 V/m, for na=1.43, the maximum value of the fundamental mode is as 41.07 V/m while that of the plasmonic mode is 48.82 V/m. In Figure 7c, the doping in defect with GeO2 was 13.5% for a detection range of 0.12 RIU, with na varying from 1.32 to 1.44. Para na=1.32 the maximum value of the fundamental mode is as 76.98 V/m while that of the plasmonic mode is 7.13 V/m, for na=1.44 the peak value of the fundamental mode is as 16.11 V/m while the plasmonic mode is 47.69 V/m. Finally, in Figure 7d, the percentage of doping with GeO2 was 19.3%. In this case, the highest detection range was observed among the cases studied (0.13 RIU), which allowed a sensor operating range with na varying from 1.32 to 1.45. For na=1.32, the maximum value of the fundamental mode is 78.5 V/m while that of the plasmonic mode is 7.49 V/m, for the na=1.44, the maximum value of the fundamental mode is as 19.37 V/m and that of the plasmonic mode is 36.44 V/m. According to the results presented in Figure 7, it is noticed that the introduction of the defect in the core of the MOF, with material consisting of SiO2 doped with GeO2, causes an increase in the operating range of sensors based on SPR. This is a positive aspect, as plasmonic sensors, despite having a high sensitivity, are also known to have a narrow range of operation, which can greatly limit their applications. The result of the CL and WS analysis of the sensor is presented below to verify the effect of the defect introduction in these parameters, considering the values of the na ranges obtained in the projects. Figure 8 investigates the behavior of confinement loss curves of the proposed configurations for the entire spectrum of analysis. According to the results presented in Figure 8, it can be observed that the CL curves follow a similar pattern. It can be seen that, within an analysis range of 0.8 to 1.2 μm, the lower the na, the lower are the losses, and as the RI of the analyte increases, the losses also increase. Figure 8b,d show that for analytes with na=1.44, there were higher values of CL occurred, as expected, however, it is noticed that at the wavelength of 1.15 μm there is a rapid decrease in the values of those losses. On the other hand, in Figure 8e, the upper limit of the sensor detection range is increased to 1.45, due to the high concentration of GeO2, which made the curves more stable, for this operating limit. It can be seen that in all situations around the wavelength of 1.55 μm, the confinement losses are strongly reduced, stabilizing at values between 15 and 60 dB/cm. Figure 9 shows the effective RI variation as a function of wavelength for different RI values of the analyte. These results are necessary to obtain the wavelength sensitivity as a function of the effective RI value of the analyte. From the variation in the wavelength, in relation to the effective refractive index, it is possible to obtain the spectral sensitivity of the proposed sensor. The sensitivity can be obtained in full range, taking into account the entire spectrum, however, it can also be obtained locally, taking into account only specific intervals of wavelengths, as shown in Figure 10. In addition, Table 3 presents the values of general and local sensitivity of the sensors, based on the results obtained in Figure 9. The maximum WS was obtained on the sensor without any doping, for na=1.42, reaching the value of 12,133.47 nm/RIU, while the maximum local sensitivities were obtained in the region of 1.6 to 2.0 μm, where for the sensor without doping with na=1.38 the sensitivity obtained was 111,111.11 nm/RIU. For doping with GeO2 (4.1%) and na=1.43 the sensitivity was 100,000.00 nm/RIU. In doping with GeO2 (6.3%), and na=1.43 the obtained value was 95,238.09 nm/RIU. The device with the defect doped with GeO2 (13.5%) obtained a maximum sensitivity with na=1.44, reaching the value of 235,294.12 nm/RIU. Finally, the defect doped with GeO2 (19.3%) showed the maximum sensitivity for na=1.45 in the value of 190,476.19 nm/RIU, moreover, with this doping, for na in the range of 1.37 to 1.45, the WS was stable at the value of 133,333.33 nm/RIU. Among all the possibilities, the total minimum sensitivity occurred in doping with GeO2 (19.3%) and for na=1.42, with the value of 8658.00 nm/RIU, the minimum local sensitivity also occurred for this same concentration and RI of the analyte, in the range of 0.8 to 1.2 μm, with sensitivity of 4739.33 nm/RIU. It is noticed that the total sensitivity of the plasmonic sensor is higher when the core of the MOF is constituted only by SiO2. Figure 11 shows a graph of the total sensitivity versus RI of the analytes for the various proposed dopings. To complement Figure 11, the Table 4 presents the polynomials obtained in the curve fits performed. Figure 11a shows the highest sensitivity, which is achieved when the effective refractive index of the structure varies from 1.41 to 1.42. For the cases, in which the defect was doped with GeO2, it is possible to see that when closer to the effective refractive index of 1.42, the sensitivity values are lower. It is also possible to see the case of doping with GeO2 (6.3%), shown in Figure 11c, which showed a certain stability, where the sensitivity varied little in relation to the range of 1.35 to 1.42, referring to the effective refractive index. Finally, Table 5 presents a comparison of the results obtained in this work with other sensors found in the literature. 4. Discussion In this work, a new plasmonic sensor model was proposed using a microstructured optical fiber to detect the refractive index of reference. In addition, a study of this structure was carried out considering several GeO2 dopings, introduced in a circular defect of diameter d1, immersed in the center of the MOF. The sensor studied used a D-shaped optical fiber as base, in order to allow the analyte to be deposited in a polished region, located on one side of the fiber. The modes of propagation, including fundamental modes and plasmonic modes, were analyzed, as well as a detailed study into the confinement losses and wavelength sensitivity. According to the results obtained, it was noticed that as the concentration of the dopant material located in the defect increases, the detection range of the sensor also increases, allowing the sensor to operate to detect a greater diversity of analytes. On the other hand, the highest sensitivity detected was in the structure without any doping, with a spectral sensitivity of 12,133.47 nm/RIU, and it was noticed that as the concentration of GeO2 increases and the sensitivity of the sensor decreases very slightly. Nevertheless, the lowest average sensitivity found was for structure with a SiO2+GeO2 (19.3%) defect, with 9229.90 nm/RIU, which is still high sensitivity and does not prevent the application of the defect. In addition, this setting has increased the sensor detection range to operate with values between 1.32–1.45 RIU. Finally, a comparative table was presented with other structures found in the literature. We can conclude that the proposed sensor can overcome some limitations presented in other sensors based on MOF-SPR. This is due to the fact that the vast majority of plasmonic sensors presented in the literature lose their efficiency in the detection of analytes, for a wide range of operations, and for this aspect, the device exhibits great potential for sensing applications in the biological and chemical areas. Acknowledgments The authors wish to acknowledge the Federal University of Rio Grande do Norte, the Post-Graduated Program in Electrical and Computer Engineering—UFRN/PPGEEC and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES). Author Contributions Investigation, N.H.O.C. and J.P.d.S. All authors have read and agreed to the published version of the manuscript. Funding This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Cross section sensor design. Figure 2 Real and imaginary part of the gold RI, for the wavelength range between 0.24797 μm and 6.1992 μm. Figure 3 Magnetic field in fiber for: (a) Fiber with SiO2 defect, na=1.43 and λ=1.55 μm; (b) Defect with doping SiO2+GeO2(13.5%), na=1.43 and λ=1.55 μm. Figure 4 Detail of the LSPR in fiber with SiO2 defect. Figure 5 1D analysis scheme of plasmonic and fundamental modes. Figure 6 One-dimensional E-field for sensor with SiO2 defect for: (a) Entire diameter; (b) Close to SPR. Figure 7 One-dimensional E-field for sensor with defect doped with GeO2: (a) 4.1%; (b) 6.3; (c) 13.5%; (d) 19.3%. Figure 8 Confinement loss versus wavelength, considering the defect: (a) without doping; (b) doped with GeO2 (4.1%); (c) doped with GeO2 (6.3% ); (d) doped with GeO2 (13.5%); (e) doped with GeO2 (19.3%). Figure 9 Relationship between effective RI and wavelength for the various detection ranges: (a) Defect without doping; (b) Doping with GeO2 (4.1%); (c) Doping with GeO2 (6.3%); (d) Doping with GeO2 (13.5%); (e) Doping with GeO2 (19.3%). Figure 10 Sensor sensitivity regions scheme for doping with GeO2 (19.3%) and na=1.41. Figure 11 Adjustment of curves for the sensitivity values obtained: (a) Defect without doping; (b) Doping with GeO2 (4.1%); (c) Doping with GeO2 (6.3%); (d) Doping with GeO2 (13.5%); (e) Doping with GeO2 (19.3%). sensors-22-03220-t001_Table 1 Table 1 Sellmeier coefficients. Sensors B1 B2 B3 C1 C2 C3 No doping 0.6961663 0.4079426 0.8974794 0.0684043 0.1162414 9.896161 SiO2+GeO2 (4.1%) 0.6867178 0.4348151 0.8956551 0.0726752 0.1151435 10.002398 SiO2+GeO2 (6.3%) 0.7083925 0.4203993 0.8663412 0.0853842 0.1024839 9.896175 SiO2+GeO2 (13.5%) 0.73454395 0.4271083 0.8210340 0.00869769 0.1119519 10.48654 SiO2+GeO2 (19.3%) 0.7347008 0.4461191 0.8081698 0.0764679 0.1246081 9.896203 sensors-22-03220-t002_Table 2 Table 2 RI values obtained for different GeO2 concentrations. Wavelength (μm) No Doping SiO2+GeO2 (4.1%) SiO2+GeO2 (6.3%) SiO2+GeO2 (13.5%) SiO2+GeO2 (19.3%) 0.80 1.4533172548 1.4596845495 1.4622823847 1.4715515550 1.4810033015 0.85 1.4524982860 1.4588361870 1.4614292333 1.4709993384 1.4800696281 0.90 1.4517539550 1.4580689419 1.4606585052 1.4704900422 1.4792367010 0.95 1.4510651315 1.4573624396 1.4599496556 1.4700118200 1.4784802919 1.00 1.4504174094 1.4567013392 1.4592871988 1.4695557639 1.4777821857 1.05 1.4497997593 1.4560738981 1.4586592708 1.4691150616 1.4771284601 1.10 1.4492036097 1.4554709933 1.4580566479 1.4686844229 1.4765083153 1.15 1.4486222069 1.4548854402 1.4574720609 1.4682596813 1.4759132590 1.20 1.4480501614 1.4543115084 1.4568997094 1.4678375126 1.4753365304 1.25 1.4474831206 1.4537445737 1.4563349105 1.4674152314 1.4747726841 1.30 1.4469175294 1.4531808627 1.4557738414 1.4669906435 1.4742172864 1.35 1.4463504523 1.4526172632 1.4552133484 1.4665619352 1.4736666904 1.40 1.4457794402 1.4520511825 1.4546508033 1.4661275918 1.4731178664 1.45 1.4452024286 1.4514804385 1.4540839942 1.4656863342 1.4725682741 1.50 1.4446176596 1.4509031772 1.4535110411 1.465237071 1.4720157629 1.55 1.4440236217 1.4503178079 1.4529303310 1.4647788624 1.4714584966 1.60 1.4434190019 1.4497229527 1.4523404668 1.4643108884 1.4708948926 1.65 1.4428026489 1.4491174068 1.4517402268 1.4638324286 1.4703235752 1.70 1.4421735426 1.4485001066 1.4511285325 1.4633428423 1.4697433377 1.75 1.4415307705 1.4478701039 1.4505044226 1.4628415542 1.4691531123 1.80 1.4408735085 1.4472265460 1.4498670326 1.4623280424 1.4685519459 1.85 1.4402010046 1.4465686581 1.4492155773 1.4618018289 1.4679389798 1.90 1.4395125664 1.4458957302 1.4485493372 1.4612624715 1.4673134341 1.95 1.4388075504 1.4452071054 1.4478676464 1.4607095576 1.4666745939 2.00 1.4380853528 1.4445021703 1.4471698840 1.4601426981 1.4660217981 sensors-22-03220-t003_Table 3 Table 3 Details of the sensitivity of the proposed sensor, for the various dopings and analytes. Doping na(RIU) WS_Total (nm/RIU) WS (0.8–1.2 μm) (nm/RIU) WS (1.2–1.6 μm) (nm/RIU) WS (1.6–2.0 μm) (nm/RIU) No doping (0%) 1.35 11,374.41 4744.96 24,691.36 80,000.00 1.36 11,352.89 4756.24 24,242.42 78,431.37 1.37 11,538.46 4872.11 23,952.09 76,923.07 1.38 11,695.90 4884.00 23,391.81 111,111.11 1.39 11,869.43 5012.53 22,727.27 108,108.11 1.40 12,060.30 4987.53 25,974.02 102,564.10 1.41 11,764.70 4987.53 25,000.00 68,965.52 1.42 12,133.47 5154.63 23,952.09 86,956.52 1.43 11,111.11 5376.34 22,857.14 24,844.72 SiO2+GeO2 (4.1%) 1.35 9554.14 4901.96 11,627.90 41,666.66 1.36 9508.72 4884.00 11,527.37 41,666.66 1.37 9538.95 4932.18 11,396.01 41,666.66 1.38 9463.72 4907.97 11,204.48 41,666.66 1.39 9493.67 4968.94 11,019.28 41,666.66 1.40 9516.26 5044.13 10,752.68 41,666.66 1.41 9382.33 5174.64 9779.95 41,237.11 1.42 9167.30 5095.54 10,050.25 31,746.03 1.43 9811.94 5235.60 9546.54 100,000.00 1.44 9900.99 5641.74 18,099.54 14,184.39 SiO2+GeO2 (6.3%) 1.33 9463.72 4938.27 11,695.90 34,482.75 1.34 9360.37 4866.18 11,627.90 34,482.75 1.35 9382.32 4901.96 11,527.37 34,482.75 1.36 9331.25 4878.04 11,428.57 34,482.75 1.37 9367.68 4932.18 11,299.43 34,482.75 1.38 9295.12 4907.97 11,111.11 34,482.75 1.39 9324.00 4968.94 10,928.96 34,482.75 1.40 9338.52 5208.33 9975.06 34,482.75 1.41 9216.58 5174.64 9708.73 34,188.03 1.42 9167.30 5095.54 9950.24 32,786.88 1.43 9787.92 5228.75 9546.53 95,238.09 SiO2+GeO2 (13.5%) 1.32 9577.01 5188.06 10,025.06 48,192.77 1.33 9478.67 5115.08 9975.06 48,192.77 1.34 9375.00 5044.13 9900.99 48,192.77 1.35 9389.67 5069.70 9876.54 47,619.04 1.36 9331.25 5044.13 9779.95 47,619.04 1.37 9353.07 5089.05 9685.23 47,619.04 1.38 9273.57 5050.50 9569.37 47,619.04 1.39 9287.92 5108.55 9411.76 47,619.04 1.40 9295.12 5167.95 9237.87 47,619.04 1.41 9042.95 4889.97 9803.92 39,603.96 1.42 9153.32 5141.39 8869.18 48,780.48 1.43 9324.01 5263.16 8928.57 50,632.91 1.44 10,058.67 5376.34 8583.69 235,294.12 SiO2+GeO2 (19.3%) 1.32 9748.17 5181.34 9324.00 133,333.33 1.33 9654.06 5115.08 9280.74 133,333.33 1.34 9546.53 5044.13 9216.58 133,333.33 1.35 9486.16 5012.53 9153.31 133,333.33 1.36 9389.67 4950.49 9090.90 133,333.33 1.37 9345.79 4938.27 9009.00 133,333.33 1.38 9230.76 4872.10 8908.68 133,333.33 1.39 9181.33 4866.18 8791.20 133,333.33 1.40 9118.54 4866.18 8620.68 133,333.33 1.41 8961.91 4796.16 8421.05 133,333.33 1.42 8658.00 4739.33 8368.20 62,500.00 1.43 8778.34 4790.41 8733.62 54,054.05 1.44 8670.52 4981.32 9280.74 26,666.66 1.45 9448.81 5319.14 8048.28 190,476.19 sensors-22-03220-t004_Table 4 Table 4 Comparison of performance with plasmonic sensors reported in the literature. Figure Polynomials Figure 11a Y(X)=−6.7734×1012+2.9314×1013X−5.2856×1013X2+5.0825×1013X3−2.7489×1013X4+7.9285×1012X5−9.5276×1011X6 Figure 11b Y(X)=−3.0959×1012+1.3339×1013X−2.3944×1013X2+2.2921×1013X3−1.2341×1013X4+3.5432×1012X5−4.2382×1011X6 Figure 11c Y(X)=8.1793×1011−3.5704×1012X+6.4931×1012X2−6.2972×1012X3+3.4349×1012X4−9.9917×1011X5+1.2109×1011X6 Figure 11d Y(X)=6.3266×1010−2.7952×1011X+5.1453×1011X2−5.0509×1011X3+2.7886×1011X4−8.2105×1010X5+1.0071×1010X6 Figure 11e Y(X)=9.6532×1010−4.2282×1011X+7.7154×1011X2−7.5074×1011X3+4.1084×1011X4−1.1989×1011X5+1.4575×1010X6 sensors-22-03220-t005_Table 5 Table 5 Comparison of performance with plasmonic sensors reported in the literature. References Type of Sensing RI Range Min CL(dB/cm) Average WS (nm/RIU) Max WS (nm/RIU) [8] External 1.33–1.35 − 3558.33 4200.00 [18] Internal 1.33–1.42 − 11,000.00 − [27] External 1.45–1.60 3000.00 4800.00 11,800.00 [28] External 1.33–1.42 80.00 28,000.00 − [29] External 1.43–1.48 35.00 7200.00 10,000.00 [30] External 1.33–1.39 296.00 22,000.00 − [31] Internal 1.33–1.38 2000.00 4600.00 7040.00 This Work No doping External 1.35–1.43 2100.00 11,650.63 12,133.47 SiO2+GeO2 (4.1%) External 1.35–1.44 530.00 9533.80 9900.99 SiO2+GeO2 (6.3%) External 1.33–1.43 1980.00 9366.80 9787.92 SiO2+GeO2 (13.5%) External 1.32–1.44 600.00 9380.02 10,058.67 SiO2+GeO2 (19.3%) External 1.32–1.45 2000.00 9229.90 9748.17 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Li B. Zhang F. Yan X. Zhang X. Wang F. Li S. Cheng T. Numerical Analysis of Dual-Parameter Optical Fiber Sensor with Large Measurement Range Based on Surface Plasmon Resonance IEEE Sens. J. 2021 21 10719 10725 10.1109/JSEN.2021.3062839 2. Wang B. Wang Q. Sensitivity-Enhanced Optical Fiber Biosensor Based on Coupling Effect Between SPR and LSPR IEEE Sens. J. 2018 18 8303 8310 10.1109/JSEN.2018.2866169 3. Sharma A.K. Jha R. Gupta B.D. Fiber-Optic Sensors Based on Surface Plasmon Resonance: A Comprehensive Review IEEE Sens. J. 2007 7 1118 1129 10.1109/JSEN.2007.897946 4. Guo X. Surface Plasmon Resonance Based Biosensor Technique: A Review J. Biophotonics 2012 5 483 501 10.1002/jbio.201200015 22467335 5. Chen Y. Ming H. Review of Surface Plasmon Resonance and Localized Surface Plasmon Resonance Sensor Photonics Sens. 2012 2 37 49 10.1007/s13320-011-0051-2 6. Paul D. Biswas R. Influence of Probe Geometry of Optical Fibers in Sensing Volatile Liquids Through Localized Surface Plasmon Resonance IEEE Trans. Nanotechnol. 2021 20 69 74 10.1109/TNANO.2020.3041255 7. Seifouri M. Rouini M.A. Olyaee S. Design of a Surface Plasmon Resonance Biosensor Based on Photonic Crystal Fiber with Elliptical Holes Opt. Rev. 2018 25 555 562 10.1007/s10043-018-0447-y 8. Yasli A. Ademgil H. Geometrical Comparison of Photonic Crystal Fiber-Based Surface Plasmon Resonance Sensors Opt. Eng. 2018 57 030801 10.1117/1.OE.57.3.030801 9. Lou J. Cheng T. Li S. Zhang X. Surface Plasmon Resonance Photonic Crystal Fiber Biosensor Based on Gold-Graphene Layers Opt. Fiber Technol. 2019 50 206 211 10.1016/j.yofte.2019.03.028 10. Rifat A.A. Mahdiraji G.A. Shee Y.G. Shawon M.J. Adikan F.R.M. A Novel Photonic Crystal Fiber Biosensor Using Surface Plasmon Resonance Procedia Eng. 2016 140 1 7 10.1016/j.proeng.2015.08.1107 11. Rifat A.A. Mahdiraji Y.M. Sua Y.M. Shee Y.G. Ahmed R. Chow D.M. Adikan F.R.M. Surface Plasmon Resonance Photonic Crystal Fiber Biosensor: A Practical Sensing Approach IEEE Photonics Technol. Lett. 2015 27 1628 1631 10.1109/LPT.2015.2432812 12. Silva J.P. Bezerra D.S. Rodriguez-Esquerre V.F. Fonseca I.E. Hernández-Figueroa H.E. Ge-Doped Defect-Core Microstructured Fiber Design by Genetic Algorithm for Residual Dispersion Compensation IEEE Photonics Technol. Lett. 2010 22 1337 1339 10.1109/LPT.2010.2055235 13. Tian J. Zhang Q. Fink T. Li H. Peng W. Han M. Tuning Operating Point of Extrinsic Fabry-Perot Interferometric Fiber-Optic Sensors Using Microstructured Fiber and Gas Pressure Opt. Lett. 2012 37 4672 4674 10.1364/OL.37.004672 23164875 14. Kong D. Wang L. Ultrahigh-Resolution Fiber-Optic Image Guides Derived from Microstructured Polymer Optical Fiber Preforms Opt. Lett. 2009 34 2435 2437 10.1364/OL.34.002435 19684807 15. Yan G. Zhang A.P. Ma G. Wang B. Kim B. Im J. He S. Chung Y. Fiber-Optic Acetylene Gas Sensor Based on Microstructured Optical Fiber Bragg Gratings IEEE Photonics Technol. Lett. 2011 23 1588 1590 10.1109/LPT.2011.2164575 16. Wang S. Sun X. Luo Y. Peng G. Surface Plasmon Resonance Sensor Based on D-Shaped Hi-Bi Photonic Crystal Fiber Opt. Commun. 2020 467 125675 10.1016/j.optcom.2020.125675 17. Azkune M. Ayesta I. Ruiz-Rubio L. Arrospide E. Vilas-Vilela J.L. Zubia J. Hydrogel-Core Microstructured Polymer Optical Fibers for Selective Fiber Enhanced Raman Spectroscopy Sensors 2021 21 1845 10.3390/s21051845 33800805 18. Lopez-Torres D. Elosua C. Arregui F.J. Optical Fiber Sensors Based on Microstructured Optical Fibers to Detect Gases and Volatile Organic Compounds—A Review Sensors 2020 20 2555 10.3390/s20092555 19. Haque E. Hossain M.A. Ahmed F. Namihira Y. Surface Plasmon Resonance Sensor Based on Modified D-Shaped Photonic Crystal Fiber for Wides Range of Refractive Index Detection IEEE Sens. J. 2018 18 8287 8293 10.1109/JSEN.2018.2865514 20. Qi M. Zhang N.M.Y. Li K. Tjin S.C. Wei L. Hybrid Plasmonic Fiber-Optic Sensors Sensors 2020 20 3266 10.3390/s20113266 21. Mo X. Lv J. Liu Q. Jiang X. Si G. A Magnetic Field SPR Sensor Based on Temperature Self-Reference Sensors 2021 21 6130 10.3390/s21186130 34577337 22. Melwin G. Senthilnathan K. High Sensitive D-Shaped Photonic Crystal Fiber Sensor with V-Groove Analyte Channel Int. J. Light Electron. Opt. 2020 213 164779 10.1016/j.ijleo.2020.164779 23. Portosi V. Laneve D. Falconi M.C. Prudenzano F. Advances on Photonic Crystal Fiber Sensors and Applications Sensors 2019 19 1892 10.3390/s19081892 24. Han H. Hou D. Luan N. Bai Z. Song L. Liu J. Hu Y. Surface Plasmon Resonance Sensor Based on Dual-Side Polished Microstructured Optical Fiber with Dual-Core Sensors 2020 20 3911 10.3390/s20143911 25. Shrivastav A.M. Gunawardena D.S. Liu Z. Tam H. Microstructured Optical Fiber Based Fabry-Pérot Interferometer as a Humidity Sensor Utilizing Chitosan Polymeric Matrix for Breath Monitoring Sci. Rep. 2020 10 6002 10.1038/s41598-020-62887-y 32265462 26. Antonio-Lopez J.E. Eznaveh Z.S. LiKamWa P. Schülzgen A. Amezcua-Correa R. Multicore Fiber Sensor for High-Temperature Applications up to 1000 °C Opt. Lett. 2014 39 4309 4312 10.1364/OL.39.004309 25078164 27. Monfared Y.E. Hajati M. Liang C. Qasymeh M. Quasi-D-Shaped Fiber Optic Plasmonic Biosensor for High-Index Analyte Detection IEEE Sens. J. 2021 21 17 23 10.1109/JSEN.2019.2945003 28. Mahfuz M.A. Hossain M.A. Haque E. Hai N.H. Namihira Y. Ahmed F. Dual-Core Photonic Crystal Fiber-Based Plasmonic RI Sensor in the Visible to Near-IR Operating Band IEEE Sens. J. 2020 20 7692 7700 10.1109/JSEN.2020.2980327 29. Luan N. Zhao L. Lian Y. Lou S. A High Refractive Index Plasmonic Sensor Based on D-Shaped Photonic Crystal Fiber with Laterally Accessible Hollow-Core IEEE Photonics J. 2018 10 6803707 10.1109/JPHOT.2018.2873826 30. Haider F. Aoni R.A. Ahmed R. Islam M.S. Miroshnichenko E. Propagation Controlled Photonic Crystal Fiber Based Plasmonic Sensor via Scaled-Down Approach IEEE Sens. J. 2019 19 962 969 10.1109/JSEN.2018.2880161 31. Fan Z. Li S. Liu Q. An G. Chen H. Li J. Chao D. Li H. Zi J. Tian W. High-Sensitivity of Refractive Index Sensor Based on Analyte-Filled Photonic Crystal Fiber with Surface Plasmon Resonance IEEE Photonics J. 2015 7 2432079 10.1109/JPHOT.2015.2432079 32. White T.P. McPhedran R.C. Sterke C.M. Botten L.C. Steel M.J. Confinement Losses in Microstructured Optical Fibers Opt. Lett. 2001 26 1660 1662 10.1364/OL.26.001660 18049691 33. da Silva J.P. Simulação por Elementos Finitos de Propagação de Feixes Ópticos em Estruturas Fotônicas Ph.D. Thesis Campinas State University—UNICAMP Campinas, Brazil 11 April 2013 34. Gauvreau B. Hassani A. Fehri M.F. Kabashin A. Skorobogatiy M. Photonic Bandgap Fiber-Based Surface Plasmon Resonance Sensors Opt. Express 2007 15 11413 11426 10.1364/OE.15.011413 19547499 35. Brückner V. To the Use of Sellmeier Formula Elements of Optical Networking: Basics and Practice of Optical Data Communication 1st ed. Brückner V. Springer Berlin/Heidelberg, Germany 2011 Volume 1 194 36. Rakić A.D. Djurišić A.B. Elazar J.M. Majewski M.L. Optical Proprieties of Metallic Films for Vertical-Cavity Optoelectronic Devices Appl. Opt. 1998 37 5271 5283 10.1364/AO.37.005271 18286006

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093525 sensors-22-03525 Article A Visual Servoing Scheme for Autonomous Aquaculture Net Pens Inspection Using ROV https://orcid.org/0000-0002-7401-5120 Akram Waseem 1* Casavola Alessandro 1 https://orcid.org/0000-0002-1167-2000 Kapetanović Nadir 2* Miškovic Nikola 2 Martins Felipe Academic Editor 1 Department of Informatics, Modeling, Electronics, and Systems (DIMES), University of Calabria, 87036 Rende, Italy; a.casavola@dimes.unical.it 2 Laboratory for Underwater Systems and Technologies (LABUST), Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia; nikola.miskovic@fer.hr * Correspondence: waseem.akram@dimes.unical.it (W.A.); nadir.kapetanovic@fer.hr (N.K.) 05 5 2022 5 2022 22 9 352507 4 2022 29 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Aquaculture net pens inspection and monitoring are important to ensure net stability and fish health in the fish farms. Remotely operated vehicles (ROVs) offer a low-cost and sophisticated solution for the regular inspection of the underwater fish net pens due to their ability of visual sensing and autonomy in a challenging and dynamic aquaculture environment. In this paper, we report the integration of an ROV with a visual servoing scheme for regular inspection and tracking of the net pens. We propose a vision-based positioning scheme that consists of an object detector, a pose generator, and a closed-loop controller. The system employs a modular approach that first utilizes two easily identifiable parallel ropes attached to the net for image processing through traditional computer vision methods. Second, the reference positions of the ROV relative to the net plane are extracted on the basis of a vision triangulation method. Third, a closed-loop control law is employed to instruct the vehicle to traverse from top to bottom along the net plane to inspect its status. The proposed vision-based scheme has been implemented and tested both through simulations and field experiments. The extensive experimental results have allowed the assessment of the performance of the scheme that resulted satisfactorily and can supplement the traditional aquaculture net pens inspection and tracking systems. autonomous vehicles inspection aquaculture applications computer vision European Regional Development Fund-The Competitiveness and Cohesion Operational Programme Competitiveness and Cohesion 2014–2020KK.01.1.1.04.0036 Interreg Italy-Croatia InnovaMare project10248782 This research was funded by the European Regional Development Fund, Operational Programme Competitiveness and Cohesion 2014–2020, through project Heterogeneous Autonomous Robotic System in Viticulture and Mariculture (HEKTOR)—grant number KK.01.1.1.04.0036; and the European Regional Development Fund through the Interreg Italy–Croatia InnovaMare project (Partnership ID 10248782). ==== Body pmc1. Introduction Today, fish farming plays a key role in food production, and the number of fish farms is increasing rapidly [1]. Typically, fish farming is carried out in open sea net cages that are natural marine environments. These fish cages are prone to various environmental changes that include biofouling, the growth of organisms such as algae, mussels, hydroids and many more. Furthermore, the water movement also causes net deformation and increased stress on the mooring. These environmental changes may cause harm to the net status and fish health. For example, if netting damage happens, and if it not is discovered in time, the fish escape from the net, decreasing growth performance and food efficiency. Thus, to obtain sustainable fish farming, inspection and maintenance must be performed on a regular and efficient basis [2]. Traditionally, fish net pens inspection and maintenance are carried out by expert divers. However, this method poses high risks to human life and health because of strong oceans waves and currents in the marine environment. A recent trend in the literature is the use of remotely operator vehicles (ROVs) or autonomous underwater vehicles (AUVs) for underwater fish net pens inspection tasks. These vehicles offer low-size and low-cost effective solutions for the aforementioned tasks and can automate the operations using advanced information and communication technology, intelligence control and navigation systems. The use of sonar, compass and depth sensors allows real-time localization without the need for a geographic positioning system (GPS). Furthermore, the use of camera sensors and current computer vision methodologies provides real-time streaming of the environment and interpretation of the captured scenes [3]. In recent years, many researchers have shown increased interest in the development of methods and techniques for autonomous fish net pens inspection using ROVs/AUVs controlled by computer vision approaches. Some of these works are discussed in a later section of this article (see related work Section 2). From our review of the current state of the art, we have seen many research studies that have made use of computer vision technology for addressing the net inspection problem. Currently, these studies cover net damage detection methods including hole detection, biofouling detection, deformation detection, etc. These detection tasks have been performed through traditional computer vision techniques, and also some work has proposed the use of deep-learning methods. However, this area of research is still under development, and there have been considerable research efforts specifically devoted to the integration of control and detection techniques. The current solutions only focus on the detection part, while there are less or very few attempts toward the automatic control and navigation of the vehicle in the net inspection task. Main Contribution This paper demonstrates how a low-cost and camera-equipped ROV, integrated with a topside server on the surface, can be used for auto-inspection and relative positioning in the aquaculture environment. The main objective of this work is to develop a vision-based positioning and control scheme to cut the use of Ultra-Short Baseline (USBL) and to increase vehicle navigation autonomously. In this regard, we first reviewed in-depth the related work dealing with the autonomous vision-based net inspection problem. From our review, we noticed that most of the work only focused on damage detection and its relative position extraction. None of the related work deals with auto-positioning as well as navigation in a uniform and integrated structure. In this paper, we present an underwater robotic application for automating the net inspection task in underwater fish farms. The strategy consists of an integrated and hybrid modular-based scheme, developed by using existing and well-known frameworks and tools, i.e., ROS, OpenCV, and Python, which is assessed in both virtual and real environments. To enable cost-effective fish net pens inspection, we propose the use of two-parallel ropes attached to the net plane. More specifically, we use traditional computer vision techniques, i.e., SURF (Speeded Up Robust Features) image features and Canny edge detector, for the detection of reference points in the camera images captured in run-time and point triangulation and PnP techniques for vehicle positions relative to the net. Both monocular and stereo imaging techniques were utilized to assess the robustness and correctness of the scheme. In addition, the ROV is directed by using a closed-loop control law to traverse the net from top to bottom along the net plane. As a consequence, we test our methods in simulation as well as in a real environment that illustrates the natural condition of the net installed on a farm. The corresponding results are presented and discussed. 2. Related Works In this section, we review the currently available solutions for the fish net pens tracking and inspection problem. We start by looking in-depth at the available literature, their contributions and what they missed. In [4], an autonomous net damage detection based on a curve features method was proposed. In this scheme, a bilateral filter, an interclass variance method and a gradient histogram were used in the prepossessing part. Next, the peak cure of the mesh was calculated and the position of the curve was determined for the tracking objective. The detection was performed by determining the characteristic of the net mesh in the image. The results were assessed both with simulations and real field experiments. However, the work only describes the image processing steps for the whole detection of the net, while the vehicle control and guidance aspects have not been addressed. In [5], the authors proposed a real-time net structure monitoring system. The idea of integrating positioning sensors with a numerical analysis model is examined. The acoustic sensors were installed on the net. Then, because of different ocean currents and waves, the net position differences were calculated at different time steps. The scheme was used to determine the current velocity profiles in the aquaculture environment that cause the net deformation. However, the scheme needs to integrate communication sensors to provide the positions data to the end users. In [6], the authors proposed a method for the pose, orientation and depth estimation of the vehicle relative to the net. The fast Fourier transform method was used to estimate the depth values from the camera images with known camera parameters. The scheme was tested both in virtual and real environments. However, also in this work, the vehicle control problem is not addressed. Fish cage dysfunctionalities trigger system loss both from an economic and operational perspective. The bad infrastructure of the net allows fish to escape. To reduce the death rate of the fish, a periodic inspection is required. In this regard, authors of [7] discussed the design of a small-sized autonomous vehicle-based inspection system for underwater fish cages. The scheme offers net hole detection features while the vehicle navigates autonomously during the inspection. The depth estimation is carried out using the OpenCV triangulation method based on the target detection in the camera image. Based on the depth information, the vehicle is instructed to move forward/backward. The scheme was tested successfully in a real environment. However, to achieve more autonomy in the system, top-down movement control is required. ROV/AUV-based aquaculture inspection poses localization issues as the GPS system does not work underwater. Alternatively, the surface vehicle area is easy to deploy and maintain with fewer limitations on communication and localization. In [8], authors discussed the design and implementation of an omnidirectional surface vehicle (OSV) for fish cage inspection tasks. A depth-adjustable camera was installed with the vehicle that captures the net structure at different depths. Furthermore, the net damage detection problem was solved by using a pretrained deep-learning-based method. However, the factors that interfere with the position estimation were not incorporated. In [9], authors presented an extension of a former work by incorporating the artificial-intelligence-based mission planning technique. A hierarchical task network was exploited to determine the rules for vehicle movement. However, the scheme is not validated in a realistic environment. The traditional methods for biofouling removal are costly and have a great impact on fish net stability and fish health. The waste products are left in the water creating a bad environment for the fish. In this regard, ROV/AUV-based biofouling detection and removal provide a more sophisticated solution. In addition, static sensors are also used to regularly monitor environmental conditions. Authors of [10] reported a detailed theoretical analysis of robotic solutions for biofouling prevention and inspection in fish farms. Various technical and operational requirements are proposed and discussed. The study proposed an automatic robotic system for biofouling detection and cleaning that consists of environmental condition monitoring, net and biofouling inspection, growth prevention and fish monitoring inside the cages. As a result, that work proposed specifications and requirements for the development of such a system that offers detailed guidelines for the deployment of the robotic system for the aquaculture inspection task. In [11], the authors proposed a novel method for net inspection problems. This work suggested the use of a Doppler velocity log (DVL) to approximate the vehicle’s relative position in front of the local region of the net. The position coordinates are then used in line-of-sight guidance control laws for the heading movement at a constant depth and angle with respect to the net plan. However, the scheme required noise handling in DVL to achieve better tracking results. Furthermore, due to an unfriendly environment, a more robust control law is required to deal with the model uncertainty. In fish farming, water quality matters for the health of cultured fish. Thus, water quality assessment is also an issue of great interest in the fish farming environment. In [12], the authors presented a fish cage inspection system that integrates monitoring water quality along with the net status. Different sensors were installed on the net to monitor potential hydrogen (pH), oxidation reduction potential (ORP), dissolved oxygen (DO) and temperature. For net damage detection, a Hough Transform method was used to construct the net mesh, and based on the incomplete net pattern, the damaged part was detected in the camera image. Although the work was tested in an experimental environment, the vehicle was controlled manually. Similarly, the authors in [13] deployed hardware and software solutions including SeaModem for communication, HydroLab for water quality monitoring, and energy harvesting system through propellers in underwater fish farms via acoustic IoT networks. Another regular inspection of the fish cage net is carried out in [14]. In this work, the distance control scheme is presented for net status inspection through video streaming in a real-time environment. This scheme requires a physical object attached to the net considered as the target location. Then, computer vision methods, e.g., canny edge detector, are used to detect the target in the image under fixed distance and angle. The target information is then used to instruct the vehicle to move forward/backward toward the net plan. Although the presented scheme is simple and easy to deploy, it requires that predetermined target objects be attached to the net surface. Additionally, the controller is not robust to environmental disturbances and noise. Traditional positioning methods involving the use of a long-baseline and ultra-short baseline methods, require predeployed and localized infrastructure, increasing the cost and operational complexity. On the other hand, the laser and optical systems are easy to deploy and are efficient solutions in a dynamic environment. In this regard, the authors of [15] proposed a laser–camera triangulation-based autonomous inspection of the fish cage net. In this scheme, the idea is to project two parallel laser lines on the net plan. By using image processing techniques, the lines were extracted from the images and their positions were estimated by the triangulation method. This approach showed better results when compared to the DVL method. However, this work only suggested the position estimation for the net tracking problem and does not consider the underlying control problem. The laser triangulation method needs to be used in a closed-loop under a tracking controller suitably designed for tracking purposes. A trend in recent years is to introduce artificial intelligence and Internet of Things technology in aquaculture systems to obtain real-time information and optimal aquaculture performance. In [16], an attempt has been made toward the application of an IoT-based smart fish net cage system. In this work, the authors developed a smart cage system that integrates artificial intelligence, IoT, a cloud system, big data analysis, sensors and communication technology. The system communicates field information to the cloud where the big data analysis is performed. The system generates real-time information related to fish health, survival rate and food residuals. However, this work only considered data collection and processing. Vehicle autonomous control and guidance problems are not considered. Fish cages are floating structures, and it is difficult to get a planned image of the net through camera imaging. More robust image processing is required to deal with the different net structures, shapes and sizes. The different blurred scenes should also be considered. In this regard, the authors in [17] studied net hole detection of different shapes and sizes under different underwater conditions. In this work, a combination of Hough Transform and statistical analysis methods were used to perform a local and global search for detection problems. The work was only tested on the offline images sequence. However, the work needs to be tested on a real vehicle in real-time systems to verify its relevance. Recent studies in [18,19,20] discussed the development and results of the HECTOR- heterogeneous autonomous robotic system in viticulture and mariculture project. The purpose of the project is to use an unmanned aerial vehicle (UAV), unmanned surface vehicle (USV) and ROV in an integrated and coordinated manner to carry out different missions such as vineyard surveillance, spraying and bud-rubbing in the viticulture domain and fish net monitoring in the mariculture domain. The research carried out as a part of the HECTOR project in [21] developed an autonomous control scheme that allows vehicles to navigate autonomously while performing the detection of net status. In this work, an ROV was allowed to move autonomously and stream video to the topside computer, perform image processing to detect two parallel ropes in an image considered as target positions and then generate the velocity commands to the vehicle for implementing a distance and top/down control. Additionally, a pretrained deep neural network was used to perform real-time biofouling detection on the net. However, the proposed scheme is not robust in the sunlight and produces blurred images in a real-time environment. In the literature, pose estimation is mainly performed with feature-matching techniques. However, such approaches are prone to generate inconsistent results in the estimation because of the similarity in different regions of the net plan. To overcome this problem, the authors in [22] proposed a novel pose estimation method by considering junction detection. In this work, the knots of the net and their topology in the camera image were used in the pose estimation relative to the camera position. This approach cuts the computation burden of feature extraction from the image on the system performance. However, vehicle control and localization are not discussed. Moreover, the pose estimation is not robust in distorted images. As we have seen, ROVs are mostly used for the autonomous fish cage inspection problem. However, ROVs feature low maneuverability and low efficiency in limited working space and a long and dynamic environment. To improve the performance of ROVs in inspection tasks, the authors of [23] developed a novel inspection scheme called Sea Farm inspector. The system integrates a ROV with a surface vehicle for the fish net inspection and tracking problem. The surface vehicle is responsible for controlling and communicating with the ROV during the operations. Furthermore, the design and control scheme is described in the work. However, this work is at the initial phase and the real implementation is ongoing. Further extensions have been undertaken in the work (17). In the latter study, the authors provide system coherence by properly integrating a surface vehicle, winch and ROV. However, the camera integration for net inspection is still being developed. Next, a summary of the reviewed related work is shown in Table 1. 3. Design, Algorithm and Implementation In this section, we present the design and implementation details of the proposed vision-based control scheme for the net inspection problem. 3.1. Overview The proposed scheme follows a modular approach consisting of two modules. The first module is responsible for distance estimation using traditional computer vision techniques. The second module is responsible to guide and control the vehicle movement along the net plane to inspect its status. In this work, two different designs are investigated, namely Method 1 and Method 2, based on the camera use. There are a certain number of other applications that can profit from the proposed visual control strategies, see, e.g., [24,25,26]. In the following, a detailed description of the system is provided. 3.2. Distance Estimation In this section, we describe distance detection by considering a reference point in the image frame of the net. We employed two different methods that are described hereafter: 3.2.1. Method 1: Stereo Image Design In this section, we discuss the design of the proposed Method 1. The proposed idea is taken from [27] and further elaborated in this work. In the latter, a vision-based positioning system is presented for docking operation of the USVs in the harbor environment. We extend the solution of that previous work by allowing the online detection of the target positions in images, and the generated path is used to solve a fish net tracking problem for an ROV model. In Figure 1, a schematic of Method 1 is shown. The forward-looking (left and right) cameras installed on the vehicle are used to collect the image sequences. The “cv-bridge” package is used to convert the obtained images from ROS to OpenCV formats. Next, the obtained images are forwarded to the object detector that extracts the net and draws a bounding box around the region of interest (ROI) using a canny edge detection algorithm. Next, from the right image, the image SURF features are extracted from the bounding box and searched in the corresponding bounding box of the left image along the horizontal lines. The matched points are used to compute the disparity map based on the triangulation method. Finally, the disparity map is used to obtain the relative positions of the vehicle with the objective to traverse the net from top to bottom while keeping a safe distance from it. In this method, a stereo imaging design is employed. First, two raw images from the available cameras are collected as shown in Figure 2. The obtained images may contain some noise and distortion. Then, we recover the rectified images by using the “unDistortRectify” OpenCV method. This requires the availability of the camera matrix and distortion coefficients obtained from the calibrated camera installed along with the simulator. (1) A=fx0cx0fycy001 where fx and fy are the focal lengths, and cx and cy are principal points. Moreover, (2) K=[k1,k2,k3,p1,p2] are the distortion parameters, where k1,k2,k3 denote the radial distortion parameters and p1,p2 the tangential ones [15]. Next, a small region of interest (ROI) is selected in the image. Because the whole net has the same pattern, it is easy to select a small portion of the net to reduce the computational burden during the features extraction. The selected region of interest of size “300 by 200” pixel is shown in Figure 3. Next, we can recover the edges in the ROI image by calling up the “Canny” edge detection algorithm. The Canny algorithm is a popular mathematical operator that finds prominent edges in images using a multi-stage approach consisting of noise reduction, finding intensities, non-maximum suppression and thresholding. This step is required to check if there are enough pixels related to the net area inside the selected ROI. Otherwise, the search and extraction of the features of interest may not be effective. The final result containing strong edges in the image is shown in Figure 4. The next step is to design the stereo vision system. Here, the epipolar geometry concept is employed. The basic idea of the system is to search the SURF features in the bounding box containing the detected edges in the right image. SURF features are a scale and rotation-invariant interest point detector and descriptor [28]. Next, the same feature extraction steps are followed in the bounding box by considering horizontal scale lines corresponding to the left image. The next phase is to perform feature matching and find the best match in the corresponding left and right images. For points matching purposes, the K-Nearest Neighbour routine by OpenCV is used, and a filter is applied to detect only the best matches. Those are the ones that have a constant distance less than 0.6, and they are labeled as a best-matched point. Finally, the best match points are obtained and drawn as shown in Figure 5. Algorithm 1 returns the pixel positions of best-matched points in the left and right images that are further sorted according to the distance value, and the points pair with minimum distance is selected which is used to calculate the pixel difference of these two points to compute the disparity. Then, the distance value is obtained with the help of the following formulas:(3) f=(w/2)/(tan(fov/2))d=|cxl−cxr|distance=(f∗b)/(d)x=((cxl−cx)∗b)/(d)y=((cyl−cy)∗b)/(d) where f denotes the focal length, w denotes the width of the image frame, fov the camera angle, d the disparity, cxl and cxr the pixel coordinates of the points in the left and right images, cx and cy the center midpoints of the image, and b the baseline, that is the distance between the two cameras. Algorithm 1 Stereo vision-based positioning algorithm Initialization:1: set: camera-left, camera-right Online Phase 1: fort>0do 2:     get-images: Read images from both cameras 3:     do-rectify: Remove distortion 4:     get-roi: Select region of interest (ROI) 5:     get-edges: Apply canny edge detector 6:     draw-contours: Calculate a rectangular region containing the detected edges 7:     find-features: Extract features present in contours 8:     match-features: Match features pairs in the second image 9:     filter-matched-features: Apply filter to get the best match feature pairs 10:   return the pixel positions of the matched best feature pair 11: end for 3.2.2. Method 2: Monocular Image Design In this section, we discuss the design of the proposed Method 2 that is achieved by elaborating and extending ideas presented in [21]. Specifically, we have generalized the approach for the Blueye Pro ROV in a field environment and performed the assessment of the performance of the scheme. The basic idea of the scheme here is to identify two parallel ropes attached on the net in the image frame and then determine the position of the rope in the image to perform the distance estimation of the net with respect to the vehicle. In Figure 6, a schematic of Method 2 is depicted. Both methods share the same functionality except for the usage of the cameras. In Method 2, a monocular camera is used. Here, the idea is having two parallel ropes along the net surface. Then, by means of edge detection and Hough transform algorithms, the ropes in the image are extracted, and pixel distance is calculated. Next, by using the computed pixel distance and knowing the real distance between the ropes, the positions are obtained which are the necessary input to the vehicle control and navigation algorithms. The vehicle on-board camera is used to capture the cage net as shown in Figure 7. The input image is of size “1920 × 1080”—a high resolution image. To make the detection process easier and robust, it is necessary to undertake some preprocessing steps. Thus, first we modify the input image by applying the “CLAHE” OpenCV method. The CLAHE (contrast limited adaptive histogram equalization) recalculates the values of each pixel in the image and redistributes the brightness level, thereby increasing contrast in the image. This results in better visibility of the image objects and makes the identification easier. Next, the image is converted to gray and the “Bilateral filter” by OpenCV is used. The filter makes use of one or more Gaussian filters and blurs the neighborhood pixels of similar intensities while preserving the edges. The image dimension is reduced by a 25% of the original one with the intention to eliminate the unnecessary details in the image. The resulting image is then used for the distance estimation process. The next essential step is the identification of the two parallel ropes in the image. The ropes are recovered by applying the Canny edge detection algorithm. The algorithm follows a three step-procedure which include noise reduction, the calculation of the intensity gradient, the suppression of false edges and hysteresis thresholding. The resultinb image is shown in Figure 8. The ropes in the image can essentially be considered as parallel straight lines. As we are only interested in these lines, we can freely discard the minor edges and only extract the large edges in the image. Therefore, the detection of the lines is achieved by applying the Hough transform method. This method requires an input image containing all edge information obtained from the previous steps and uses gradient information for the detection of the lines. The gradient is a measurement of the changing intensities of pixel coordinates inside an image and mathematically can be written as:(4) ∇f(x,y)=GxGy=∂f/x∂f/y where Gx is the gradient of the x-axis, Gy is the gradient of the y-axis, ∂f/x shows change in intensity of the x-axis, and ∂f/y shows change in intensity of the y-axis. Furthermore, the size and direction of the gradient are calculated by:(5) |∇f|=Gx2+Gx2θ=arctanGy/Gx Given the size (|∇f|) and direction (θ) of the gradient, the direction of an edge is determined by a perpendicular line at any given point in the image. Next, to draw the lines in the image, the polar coordinate system is used (6) r=xcos(θ)+ysin(θ) The pair (r,θ) shows the intersection point of a line that passes through two points (x) and (y). Here, r denotes the distance from the origin to the nearest point on the line, and θ denotes the angle between the x-axis and the line which connects the origin with that nearest point. Thus, each line in the image is constructed, and the resulting image is shown in Figure 9. The overall procedure of Method 2 is summarized in the following algorithm. Algorithm 2 returns pixel positions of the detected two parallel lines in the image based on pixel differences and is calculated by:(7) d=|PL−PR|distance=(f∗object/d)∗scale where the term d denotes the difference between average pixel values detected in left and right ropes in the images that are denoted by PL and PR, respectively, and the object denotes the real distance between the two ropes that need to be known in advance, and the term scale takes into account the ROV camera tilt angle. Algorithm 2 Monocular vision-based positioning algorithm Initialization:1: set: camera Online Phase 1: for t>0do 2:     get-images: Read image from camera 3:     pre-process: Improve image quality 4:     get-edges: Apply canny edge detector 5:     draw-lines: Apply Hough-lines transform algorithm 6:     separate-lines: Get the two parallel lines 7:     return the pixel positions of the obtained parallel lines 8: end for 3.3. Control Law The ROV is described in 4 DOFs: surge, sway, heave and yaw. To solve the control design problem, first we assumed that:The roll and pitch motion is passively stabilized by gravity and can therefore be neglected. The vehicle is neutrally buoyant, and the motion in heave can therefore be neglected. In particular, here we focus on the control of surge, sway, heave and yaw speed of the vehicle to perform the net pens inspection task. The control law is designed which directs the ROV heading toward the net pen and makes the ROV traverse the net pen with a desired distance and speed. This way, the camera view is directed toward the net such that the ROI stays in camera view while the ROV is traversing. The control module is used to instruct the vehicle to perform a predetermined course outside the net to generate live streaming to the topside user and to inspect its status [21]. This part complements the methodology of the auto-inspection of nets using ROVs. The control commands use the position and distance information obtained from the object detection module via computer vision methods on the acquired images of the vehicle cameras. To this end, a simple but efficient control law is synthesized that generates the velocity set point for vehicle movement based on the reference position and distance data. The overall navigation problem can be stated as follows: Given the depth information, generate the velocity commands to move the vehicle from top to bottom under a certain predefined distance while keeping the net plane in a parallel position with respect to the vehicle position. In view of the above statement, the algorithm works as follows. First, the distance estimation module is called that preprocesses and detects target points in the images to identify the reference point. It checks if the target is visible or not. If the target is not visible, a rotation command is sent to the vehicle. Once the target is detected, it checks if the distance between the vehicle and the net is in the range of the predefined distances. If too far or too close, the forward/backward commands are sent to the vehicle, respectfully. Once the vehicle is at the desired distance, a top to bottom movement command is sent to the vehicle until the bottom area is detecte, and the navigation is stopped. The overall control procedures are explained with the help of Algorithm 3. The goal of this study is the design of a control method allowing the ROV to traverse the net pens from top to bottom. Once the ROV reaches the bottom of the net pens, the distance estimation module is not receiving the input and sends a stop command to the vehicle. Once the one drive is completed, ROV is manually lifted to the docking/surface position. Incorporating the autonomous docking capability, in addition to the proper control of the heading and velocity, is out of the paper scope and will be addressed in a future study. Algorithm 3 Control and Navigation algorithm Initialization:1: set: target positions 2: choose: ref-distance 3: store: net-distance, wanted-distance, x-force, z-force Online Phase 1: for t>0do 2:     compute: the net-distance by solving (3) or (7) 3:     if net-distance > ref-distance then 4:         move-fwd 5:     else if net-distance < ref-distance then 6:         move-bwd 7:     else if net-distance==ref-distance then 8:         move-dwn 9:     else 10:         wait 11:     end if 12: end for 4. Results The proposed schemes used, both in simulations and experiments, a ROV and net pens with the same characteristics. First, the structure of the net pen was developed in the blender tool that supposedly roughly covered the size of the net pens used in the experiments. In addition, the methods only need to know in advance the distance between the reference points attached to the net pens. The ROV was used for image acquisition and tracking purposes, which is evident both from the undertaken simulations and experiments. Following the design of the proposed vision-based control scheme, we move over to the results. The results are divided into two parts, i.e., Simulation and Experiments, where each focuses on the different design choices proposed in this work. Here, we discuss how the experiments were conducted and what we achieved. Finally, based on the obtained results, we make some conclusions. 4.1. Simulation Results 4.1.1. Description To test the proposed Method 1 and Method 2 schemes in the simulation setting, we adopted the “unmanned underwater vehicle simulator” (UUV) simulator [29]. It is a set of packages that includes plugins and ROS applications that allow carrying out simulations of underwater vehicles in Gazebo and Rviz tools. The simulation environment consisted of an underwater scene and the ROV vehicle that performed the tracking tasks. To simulate the net-tracking scenario, we designed the net structure using the blender tool. The simulation was performed on ROS Melodic distribution installed on Ubuntu 18.04.4 LTS. In the simulator, the vehicle model named “rexrov-default” was used that consists of a mechanical based with two cameras and other sensing devices, e.g., inertial measurement unit (IMU) and LIDAR. Furthermore, the Doppler velocity log (DVL) was also available to measure the vehicle velocity during the simulation. The model also consisted of the implementation of Fossen’s motion equations for the vehicle [30] and the thruster management package. By following the stereo and monocular imaging design, the two forward-looking cameras were used during images acquisition with the objective of testing the vision-based auto-inspection of the net structure. The simulation setup is shown in Figure 10 where the vehicle model is cloned in the underwater scene and facing toward the net plane. 4.1.2. Results In this section, the simulation results are described. The main objective of the simulation was to test the performance of both Method 1 and Method 2 described in the earlier sections for distance estimation and tracking purposes. First, as an example, the working of the scheme is shown in Figure 11 where different ROS nodes are called in the terminal windows and communicate with the vehicle. During the simulation, we observed the estimation of the distance between the vehicle camera and the net plane via Method 1 and Method 2. This is shown in Figure 12. From our results, we found that the monocular image-based method produced smooth results compared with the stereo-image-based method. The signal produced by Method 1 had multiple abrupt changes during the simulation. This was due to the fact that if the obtained images were blurred or not flat, the scheme extract features incorrectly caused the ambiguous estimation. From our experiments, we learned that Method 1 is highly influenced by the choice of hardware, feature extraction and computation cost. In contrast, Method 2 showed reasonable performance for the distance estimation. We can conclude that Method 2, which makes use of the monocular imaging design technique, is feasible for tracking underwater fish net pens at sea. The second test that we performed was finalized to observe the vehicle states during the simulation. This is shown in Figure 13, where the vehicle positions (x, y, z and yaw) achieved by applying Method 1 and Method 2 can be seen. In terms of performance, we noticed that Method 2 showed better performance compared to Method 1. This can be seen more clearly in the state x and angle yaw. With Method 1, the path covered was not linear despite the absence of external noise imposed in the control path. Furthermore, the state z confirmed the top/down traversing during the simulation. From our results, we can conclude that Method 2 is more suitable to be used for tracking. The third test was organized to analyze the velocity profiles during the simulation. This is shown in Figure 14 and Figure 15. Here, the results show the velocity set points for x and z. The x set point was used for the longitudinal movement while the z set poin twas used for the depth movement of the vehicle. The results confirm that whenever the vehicle stays at the desired distance from the net, the controller generates the z velocity set point correctly. From our analysis, we can conclude that the proposed schemes could be used to address the tracking problem. 4.2. Experimental Results 4.2.1. Description To test the proposed Method 2 scheme in a real environment setting, a small set of experiments were conducted during the workshop “BTS (Breaking the Surface) 2022” organized by the Laboratory for Underwater Systems and Technologies (LABUST) at the Faculty of Electrical Engineering and Computing, University of Zagreb in October 2021 at Biograde de Muro, Croatia. The experiments were performed in the pool setup as shown in Figure 16. Blueye Pro ROV as shown in Figure 17 was acquired from the LABUST during the experiments. The Blueye Pro ROV is produced by Blueye Robotics and has dimensions of 48.5 × 25.7 × 35.4 cm length, width and height, respectively. The ROV weighs 9 kg, it can go down to 300 m depth, and it has a 400 m cable for tethering. It is also equipped with a battery allowing 2 h of autonomy. The ROV can be used in saltwater, brackish, or freshwater. The drone moves with help of the available four thrusters of 350 w. The ROV has a full HD forward-looking camera with a [−30 deg, 30 deg] tilt angle and 25–30 fps imaging capability. Additionally, it is equipped with a powerful light that ensures well-lit imagery under low-light scenarios. Other sensory devices including IMU, accelerometer, compass and temperature are also installed on it. The ROV allows control and communication with a topside user on the surface through both WiFi and Ethernet cable in a wireless environment [18]. Furthermore, the ROV is integrated with an open-source BlueyeSDK-ROS2 interface (see [31]). This allowed for achieving a connection between the Python-based ROS nodes running on a topside computer and the ROV. 4.2.2. Results In this section, the experimental results are described. The main objective of the experiments was to test the performance of the proposed vision-based positioning and control scheme for the underwater fish net pens inspection problem using the Blueye Pro ROV. Here, we performed experiments by following the proposed Method 2 that makes use of the monocular imaging-based design technique. Generally, the adopted ROV had several challenges during the experiments. First, there is no interface provided by the manufacturer where one can get access to the vehicle’s internal parameters which are necessary for the feedback control. Second, there is a lack of vehicle position, velocity and depth estimation. The only possible way to interact with the vehicle is to use the Blueye Python SDK that comes with the vehicle. SDK allowed us to subscribe to the “Thruster force” topic and publish a constant velocity set point to the surge, sway, heave and yaw motion of the vehicle as shown in Figure 18. Another main problem faced during the experiments was the uncalibrated vehicle camera that generated noisy images resulting in degradation of the algorithm performance. Despite the above-mentioned challenges, the vehicle was used for the distance estimation of the vehicle relative to the fish net pens in a field trial as shown in Figure 16, and some results were collected. In Figure 19 the running interface is shown. In the figure, one can clearly see that the algorithm is working by identifying the ropes as two parallel lines in the input image. Next, these lines are used to estimate the distance to the fish net pens. The estimated distance is shown in Figure 20. The reference distance used during the experiments was 200 cm, and based on the current distance, the vehicle was instructed to move forward/backward. While the vehicle got in range of the wanted distance, the top to down motion was called. Here, we performed two different experiments and examined the estimated distance. The results show similar performance from both experiments. However, false estimation was also observed during the experiments. By clearly examining the results and after tuning the algorithm parameters, we concluded that the estimation process is influenced by the input data. From the experiments, we learned that the algorithm was showing performance degradation with sunlight and poor weather. Moreover, the distance estimation data showed that the proposed scheme was capableof being used for the distance estimation and tracking of the fish cage net. For thoroughness, the thruster force profiles during Experiments 1 and Experiments 2 are shown in Figure 21 and Figure 22, respectively. Here, the results confirmed that the control part successfully generated the velocity set point x and z whenever necessary on the basis of the reference distance. 4.3. Comment This work aimed at the design and development of an autonomous fish net pens tracking system. The obtained results are promising and indicate the capability of the schemes for efficiently detecting, localizing, and tracking the fish net pens in the real environment. However, the robustness of the proposed methods has to be routinely tested with a sequence of sea trials over time. 5. Conclusions In this paper, a vision-based positioning and control scheme is described that can be used for auto-inspection of the fish net pens in underwater fish farms. We employed both stereo and monocular image design approaches for the input data acquisition and the traditional computer vision methods for the target position detection. The vision algorithm was integrated with a control module that allows the vehicle to perform the traversing along the net plane. The system was tested both in a simulation and in a real environment. In terms of performance, we found that the monocular image-based method is more suitable than the stereo-image-based method. From the obtained results, we learned that the stereo-image-based method is highly influenced by the choice of hardware design, features extraction and computation cost. In contrast, the monocular image-based method is found to be easily adopted in real applications because of fewer requirements and lower computation costs. The scheme also avoids tracking the image features and does not suffer from repeated scenes in the input data. In the future, we are interested to overcome the existing limitations by performing more experiments, providing the state’s data, and evaluating the results with the true positions and state data. We also plan to modify the control part and integrate it with the feedback control law to make the scheme more automatic. Acknowledgments The authors would like to thank Matej Fabijanić from LABUST for providing contributions to algorithm development and sea trials. We would also like to thank Đula Nađ, Fausto Ferreira, Igor Kvasić, Nikica Kokir, Martin Oreč, Vladimir Slošić, and Kristijan Krčmar for providing useful discussions and assistance during sea trials. Our thanks also go to Marco Lupia from DIMES for providing help on ROS. Author Contributions Conceptualization, N.K. and N.M.; Data curation, A.C.; formal analysis, W.A. and N.K.; funding acquisition, N.M.; investigation, N.M.; methodology, W.A. and N.K.; project administration, N.M.; resources, N.K. and N.M.; software, W.A. and N.K.; supervision, A.C. and N.M.; validation, W.A., A.C. and N.K.; visualization, W.A.; writing—original draft, W.A. and A.C.; writing—review and editing, W.A., A.C., N.K. and N.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Method 1. A stereo image design scheme for positioning and auto-inspection of the underwater fish cage net adopted from [27]. Figure 2 Input images from the vehicle cameras: (a) left camera’s image; (b) right camera’s image. Figure 3 This figure illustrates how ROI is extracted. This region is used for edge detection and features extraction. Figure 4 Output images after applying Canny edge detector: (a) detected edges in ROI; (b) resulted image. Figure 5 Matched points in both right and left image. Figure 6 Method 2. Monocular image design scheme for positioning and auto-inspection of the underwater fish cage net adopted from [21]. Figure 7 An example of the input image from the blueye vehicle camera obtained during the experiments. Figure 8 Results after preprocessing the original image and applying the Canny edge detector. Figure 9 Output image with two identified parallel lines after applying OpenCv methods. Figure 10 Simulation setup. Model initialized in Gazebo simulator. Figure 11 Simulation screen captured during run-time. Figure 12 Fish cage net distance estimation during simulation. Figure 13 Vehicle positions during simulation. Figure 14 Velocity profile by Method 1. Figure 15 Velocity profile by Method 2. Figure 16 Field trial view before experiments. Figure 17 The Blueye Pro ROV. Figure 18 Screenshot of rqt-graph of all the ROS nodes during run-time. Figure 19 Experiments screen captured during run-time. Figure 20 Fish cage net distance estimation. Figure 21 Velocity profile during Experiment 1. Figure 22 Velocity profile during Experiment 1. sensors-22-03525-t001_Table 1 Table 1 Review of fish net tracking and inspection techniques. Ref. Technique Task Remarks [4] Bilateral filter Damage detection Does not incorporate the vehicle control [5] Kalman filter Structure detection Positions data is not communicated [6] Fourier Transform Pose estimation Does not incorporate the vehicle control [7] Canny edge detector Hole detection Does not perform top-down tracking [8] Deep learning Damage detection Experience pose estimation error [11] DVL Net inspection Not robust to noise [12] Hough transform Damage detection and water quality monitoring The vehicle is controlled manually [13] IoT network Water quality monitoring Does not consider net tracking [14] Canny edge detector Net status inspection Required predetermined target location on the net plane [15] Canny edge detector Net status inspection Does not consider vehicle control [17] Hough transform Hole detection Worked on offline images without control system [21] Canny edge detector Net status inspection Not robust to sunlight and blurred images Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Jovanović V. Svendsen E. Risojević V. Babić Z. Splash detection in fish Plants surveillance videos using deep learning Proceedings of the 2018 14th Symposium on Neural Networks and Applications (NEUREL) Belgrade, Serbia 20–21 November 2018 1 5 2. Liao W. Zhang S. Wu Y. An D. Wei Y. Research on intelligent damage detection of far-sea cage based on machine vision and deep learning Aquac. Eng. 2022 96 102219 10.1016/j.aquaeng.2021.102219 3. Ubina N.A. Cheng S.C. A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management Drones 2022 6 12 10.3390/drones6010012 4. Zhao Y.P. Niu L.J. Du H. Bi C.W. An adaptive method of damage detection for fishing nets based on image processing technology Aquac. Eng. 2020 90 102071 10.1016/j.aquaeng.2020.102071 5. Su B. Kelasidi E. Frank K. Haugen J. Føre M. Pedersen M.O. An integrated approach for monitoring structural deformation of aquaculture net cages Ocean. Eng. 2021 219 108424 10.1016/j.oceaneng.2020.108424 6. Schellewald C. Stahl A. Kelasidi E. Vision-based pose estimation for autonomous operations in aquacultural fish farms IFAC-PapersOnLine 2021 54 438 443 10.1016/j.ifacol.2021.10.128 7. Chalkiadakis V. Papandroulakis N. Livanos G. Moirogiorgou K. Giakos G. Zervakis M. Designing a small-sized autonomous underwater vehicle architecture for regular periodic fish-cage net inspection Proceedings of the 2017 IEEE International Conference on Imaging Systems and Techniques (IST) Beijing, China 18–20 October 2017 1 6 8. Tao Q. Huang K. Qin C. Guo B. Lam R. Zhang F. Omnidirectional surface vehicle for fish cage inspection Proceedings of the OCEANS 2018 MTS/IEEE Charleston Charleston, SC, USA 22–25 October 2018 1 6 9. Lin T.X. Tao Q. Zhang F. Planning for Fish Net Inspection with an Autonomous OSV Proceedings of the 2020 International Conference on System Science and Engineering (ICSSE) Kagawa, Japan 31 August–3 September 2020 1 5 10. Ohrem S.J. Kelasidi E. Bloecher N. Analysis of a novel autonomous underwater robot for biofouling prevention and inspection in fish farms Proceedings of the 2020 28th Mediterranean Conference on Control and Automation (MED) Saint-Raphaël, France 15–18 September 2020 1002 1008 11. Amundsen H.B. Caharija W. Pettersen K.Y. Autonomous ROV inspections of aquaculture net pens using DVL IEEE J. Ocean. Eng. 2021 47 1 19 10.1109/JOE.2021.3105285 12. Betancourt J. Coral W. Colorado J. An integrated ROV solution for underwater net-cage inspection in fish farms using computer vision SN Appl. Sci. 2020 2 1 15 10.1007/s42452-020-03623-z 13. Cario G. Casavola A. Gjanci P. Lupia M. Petrioli C. Spaccini D. Long lasting underwater wireless sensors network for water quality monitoring in fish farms Proceedings of the OCEANS 2017-Aberdeen Aberdeen, UK 19–22 June 2017 1 6 14. Livanos G. Zervakis M. Chalkiadakis V. Moirogiorgou K. Giakos G. Papandroulakis N. Intelligent navigation and control of a prototype Autonomous underwater vehicle for automated inspection of aquaculture net pen cages Proceedings of the 2018 IEEE International Conference on Imaging Systems and Techniques (IST) Krakow, Poland 16–18 October 2018 1 6 15. Bjerkeng M. Kirkhus T. Caharija W. T Thielemann J. B Amundsen H. Johan Ohrem S. Ingar Grøtli E. ROV Navigation in a Fish Cage with Laser-Camera Triangulation J. Mar. Sci. Eng. 2021 9 79 10.3390/jmse9010079 16. Chang C.C. Wang J.H. Wu J.L. Hsieh Y.Z. Wu T.D. Cheng S.C. Chang C.C. Juang J.G. Liou C.H. Hsu T.H. Applying Artificial Intelligence (AI) Techniques to Implement a Practical Smart Cage Aquaculture Management System J. Med. Biol. Eng. 2021 41 652 658 10.1007/s40846-021-00621-3 17. Paspalakis S. Moirogiorgou K. Papandroulakis N. Giakos G. Zervakis M. Automated fish cage net inspection using image processing techniques IET Image Process. 2020 14 2028 2034 10.1049/iet-ipr.2019.1667 18. Kapetanović N. Nad D. Mišković N. Towards a Heterogeneous Robotic System for Autonomous Inspection in Mariculture Proceedings of the OCEANS 2021 Conference and Exposition, San Diego—Porto (Hybrid) San Diego, CA, USA 20–23 September 2021 1 6 19. Rezo M. Čagalj K.M. Kovačić Z. Collecting information for biomass estimation in mariculture with a heterogeneous robotic system Proceedings of the 44th International ICT Convention MIPRO Opatija, Croatia 27 September–1 October 2021 1295 1300 20. Goričanec J. Kapetanović N. Vatavuk I. Hrabar I. Kurtela A. Anić M. Vasilijević G. Bolotin J. Kožul V. Stuhne D. Heterogeneous autonomous robotic system in viticulture and mariculture-project overview Proceedings of the 16th International Conference on Telecommunications-ConTEL Zagreb, Croatia 30 June–2 July 2021 1 8 21. Borković G. Fabijanić M. Magdalenić M. Malobabić A. Vuković J. Zieliński I. Kapetanović N. Kvasić I. Babić A. Mišković N. Underwater ROV Software for Fish Cage Inspection Proceedings of the 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO) Opatija, Croatia 27 September–1 October 2021 1747 1752 22. Duda A. Schwendner J. Stahl A. Rundtop P. Visual pose estimation for autonomous inspection of fish pens Proceedings of the OCEANS 2015-Genova Genova, Italy 18–21 May 2015 1 6 23. Osen O.L. Leinan P.M. Blom M. Bakken C. Heggen M. Zhang H. A novel sea farm inspection platform for norwegian aquaculture application Proceedings of the OCEANS 2018 MTS/IEEE Charleston Charleston, SC, USA 22–25 October 2018 1 8 24. DeCarlo R.A. Zak S.H. Matthews G.P. Variable structure control of nonlinear multivariable systems: A tutorial Proc. IEEE 1988 76 212 232 10.1109/5.4400 25. Conte G. Scaradozzi D. Mannocchi D. Raspa P. Panebianco L. Screpanti L. Development and experimental tests of a ROS multi-agent structure for autonomous surface vehicles J. Intell. Robot. Syst. 2018 92 705 718 10.1007/s10846-017-0700-9 26. Djapic V. Nad D. Using collaborative autonomous vehicles in mine countermeasures Proceedings of the OCEANS’10 IEEE SYDNEY Sydney, NSW, Australia 24–27 May 2010 1 7 27. Volden Ø. Stahl A. Fossen T.I. Vision-based positioning system for auto-docking of unmanned surface vehicles (USVs) Int. J. Intell. Robot. Appl. 2021 6 86 103 28. Ferreira F. Veruggio G. Caccia M. Bruzzone G. Real-time optical SLAM-based mosaicking for unmanned underwater vehicles Intell. Serv. Robot. 2012 5 55 71 10.1007/s11370-011-0103-x 29. Manhães M.M.M. Scherer S.A. Voss M. Douat L.R. Rauschenbach T. UUV Simulator: A Gazebo-based package for underwater intervention and multi-robot simulation Proceedings of the OCEANS 2016 MTS/IEEE Monterey Monterey, CA, USA 19–23 September 2016 10.1109/oceans.2016.7761080 30. Fossen T.I. Handbook of Marine Craft Hydrodynamics and Motion Control John Wiley & Sons Hoboken, NJ, USA 2011 31. Kapetanović N. Vuković J. Blueye SDK-ROS2 Interface 2021 Available online: https://github.com/labust/blueye-ros2-pkg.git (accessed on 22 July 2021)

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==== Front Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells11091460 cells-11-01460 Article Analysis of the Seasonal Fluctuation of γδ T Cells and Its Potential Relation with Vitamin D3 Bernicke Birthe 1† Engelbogen Nils 2 https://orcid.org/0000-0002-9450-5987 Klein Katharina 1 Franzenburg Jeanette 2 https://orcid.org/0000-0002-5489-0032 Borzikowsky Christoph 3 https://orcid.org/0000-0002-7669-3806 Peters Christian 1 https://orcid.org/0000-0002-9612-8900 Janssen Ottmar 1 Junker Ralf 2 Serrano Ruben 1*‡ https://orcid.org/0000-0002-4160-7103 Kabelitz Dieter 1* Wilson Mark R. Academic Editor 1 Institute of Immunology, University Hospital Schleswig-Holstein (UKSH) Campus Kiel, 24105 Kiel, Germany; birthebernicke@web.de (B.B.); katharina.klein@uksh.de (K.K.); christian.peters@uksh.de (C.P.); ottmar.janssen@uksh.de (O.J.) 2 Institute of Clinical Chemistry, University Hospital Schleswig-Holstein (UKSH) Campus Kiel, 24105 Kiel, Germany; nils.engelbogen@uksh.de (N.E.); jeanette.franzenburg@uksh.de (J.F.); ralf.junker@uksh.de (R.J.) 3 Institute of Bioinformatics and Statistics, University Hospital Schleswig-Holstein (UKSH) Campus Kiel, 24105 Kiel, Germany; c.borzikowsky@gmx.de * Correspondence: SerranoGuerrero.Ruben@mh-hannover.de (R.S.); dietrich.kabelitz@uksh.de (D.K.) † This work forms part of the M.D. thesis of B.B. ‡ Current address: Institute of Immunology, Medical University Hannover, 30625 Hannover, Germany. 26 4 2022 5 2022 11 9 146018 3 2022 23 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In addition to its role in bone metabolism, vitamin D3 exerts immunomodulatory effects and has been proposed to contribute to seasonal variation of immune cells. This might be linked to higher vitamin D3 levels in summer than in winter due to differential sun exposure. γδ T cells comprise a numerically small subset of T cells in the blood, which contribute to anti-infective and antitumor immunity. We studied the seasonal fluctuation of γδ T cells, the possible influence of vitamin D3, and the effect of the active metabolite 1α,25(OH)2D3 on the in vitro activation of human γδ T cells. In a retrospective analysis with 2625 samples of random blood donors, we observed higher proportions of γδ T cells in winter when compared with summer. In a prospective study over one year with a small cohort of healthy adults who did or did not take oral vitamin D3 supplementation, higher proportions of γδ T cells were present in donors without oral vitamin D3 uptake, particularly in spring. However, γδ T cell frequency in blood did not directly correlate with serum levels of 25(OH)D3. The active metabolite 1α,25(OH)2D3 inhibited the in vitro activation of γδ T cells at the level of proliferation, cytotoxicity, and interferon-γ production. Our study reveals novel insights into the seasonal fluctuation of γδ T cells and the immunomodulatory effects of vitamin D3. calcitriol cytokine production cytotoxicity flow cytometry gamma/delta T cells immunophenotyping seasonal fluctuation vitamin D3 ==== Body pmc1. Introduction γδ T cells account for approximately 5% of CD3 T cells in human peripheral blood. In contrast to the major populations of CD4 and CD8 T cells expressing the conventional αβ T cell receptor (TCR), the germ line TCR repertoire of γδ T cells is very small. There are only six expressed Vγ genes and a similarly small number of Vδ genes. Among the γδ T cells in peripheral blood, most express Vγ9 paired with Vδ2, while other subsets (e.g., Vδ1) are usually rare in blood but more abundant in mucosal tissues [1]. However, the proportion of γδ T cells and their subset distribution varies greatly in the peripheral blood of healthy adult donors and is influenced by age and gender [2,3,4]. Vγ9Vδ2 T cells (referred to as Vδ2 in the following) recognize pyrophosphate molecules (“phosphoantigens” (pAg)) independently of HLA class I or class II molecules. However, recognition of such pAg, which are secreted by many microbes but can also be produced by tumor cells, is absolutely dependent on members of the butyrophilin (BTN) family of transmembrane molecules, notably BTN3A1 and BTN2A1 [5,6,7]. The production of endogenous pAg, such as isopentenyl pyrophosphate (IPP), can be massively stimulated by nitrogen-containing aminobisphosphonates (e.g., Zoledronate (ZOL)), which block an enzyme in the mevalonate pathway leading to upstream accumulation of IPP [8,9]. In view of their HLA-independent tumor cell recognition and their potent cytotoxic activity, γδ T cells have recently attracted great interest as potential effector cells in cell-based cancer immunotherapy [10,11,12]. In addition, however, γδ T cells can also exert regulatory functions [13,14], and the potential involvement of γδ T cells in autoimmune diseases has been discussed [15,16]. Vitamin D3 is an essential regulator of calcium and phosphate metabolism and thus of bone homeostasis. In addition, immunoregulatory properties of vitamin D3 have been identified, and various diseases spanning from autoimmunity and chronic inflammation to some infections have been associated with vitamin D3 deficiency [17,18]. Vitamin D3 can affect both innate and adaptive immunity and appears to inhibit Th1 and favor Th2 T cell responses [19,20,21,22,23]. Low vitamin D3 levels favor inflammatory conditions and Th17 T cell differentiation associated with an increased incidence of autoimmune diseases [19,24]. During exposure to sunlight, 7-dehydrocholesterol in the skin absorbs UV-B radiation and is converted to previtamin D3, which then isomerizes to vitamin D3. This is sequentially metabolized in the liver to 25(OH)D3 and in the kidney to the biologically active metabolite 1α,25(OH)2D3 (1,25(OH)2D3 in the following) by 25-hydroxyvitamin D-1-α-hydroxylase (CYP27B1) [25,26]. Insufficient endogenous production of biologically active 1,25(OH)2D3 resulting from poor sunlight exposure (e.g., during the winter season) can be compensated by oral supplementation with vitamin D3 (cholecalciferol). The recommendations for adequate serum levels of 25(OH)D3 vary to some extent, but levels of <20 µg/L are considered inappropriately low and require oral supplementation [18]. Previous studies have shown that seasonal variations in serum levels of vitamin D3 are associated with a fluctuation in the subset distribution of peripheral blood T cells [27]. Moreover, it has previously been reported that the active vitamin D3 metabolite 1,25(OH)2D3 modulates the in vitro activation of human γδ T cells [28]. However, a systematic analysis of the seasonal variation of circulating γδ T cells and the possible correlation with vitamin D3 has not yet been performed. To address this issue, our study was designed to comprise three parts: (i) a retrospective analysis of the seasonal proportion of Vδ2 γδ T cells among CD3 T cells in a large cohort of random blood donors; (ii) a prospective study of γδ T cells and other immune cell subsets over a one-year period in a small group of healthy donors who did or did not take oral vitamin D3; and (iii) an in vitro analysis of the effects of 1,25(OH)2D3 on γδ T cell activation at the level of proliferation, cytotoxic activity, and cytokine production. 2. Materials and Methods Blood samples. Leukocyte concentrates obtained from healthy adult blood donors were provided by the Institute of Transfusion Medicine, University Hospital Schleswig-Holstein (UKSH) Campus Kiel. From the years 2011 to 2020, all samples obtained on a weekly basis were regularly screened for the proportion of total γδ T cells and Vδ2 γδ T cells among CD3+ T lymphocytes. These data were used in the retrospective analysis to calculate the proportion of γδ T cells in a large cohort of random healthy blood donors without consideration of age and sex. Such leukocyte concentrates were also used to isolate peripheral blood mononuclear cells (PBMC) for the analysis of the effects of 1,25(OH)2D3 on the activation and effector function of γδ T cells. In a prospective study, EDTA blood and serum were collected from 31 healthy adult blood donors every four to eight weeks for one year. The study participants were grouped according to their oral vitamin D3 uptake pattern into three groups: (i) no vitamin D3 (14 donors), (ii) interrupted vitamin D3 (no uptake mainly during late spring to early autumn (summer); 8 donors), and (iii) regular vitamin D3 (uptake throughout the year; 9 donors). Oral vitamin D3 (cholecalciferol) dosage ranged from a calculated average of 500 to 20,000 (mean 1877 ± 1968) IU per day. The actual schedule varied among donors. Information on the gender and age distribution of the study group is presented in Supplementary Table S1. The studies were performed in accordance with the declaration of Helsinki. The use of leukocyte concentrates from random donors for in vitro analysis and the study protocol of the prospective study have been approved by the Ethics Committee of the Medical Faculty of Christian-Albrechts University Kiel (code 405/10 and D579/19). Determination of 25(OH)D3 serum levels. Serum levels of 25(OH)D3 (calcifediol) were measured using UHPLC as part of the routine diagnostic at the Institute of Clinical Chemistry, UKSH. Blood samples were centrifuged for 10 min at 3000× g to collect the serum. Prior to UHPLC analysis, the serum samples were prepared using kit reagents and sample preparation procedures from RECIPE (Munich, Germany). During the first step, 200 µL of the serum sample was treated with 200 µL of precipitation reagent to reduce the matrix load of the sample. Afterward, 200 µL of the organic solution containing the internal standard was added to extract vitamin D from the sample. After mixing and centrifugation, 5 µL of the upper phase, which contains the concentrated vitamin D, was injected into the UHPLC system. For the UHPLC analysis, a Chromaster HPLC-system (VWR, Radnor, PA, USA) with an isocratic pump, autosampler, column heater, and a UV detector was used. Then, 25(OH)D3 was chromatographically separated under isocratic conditions with a flow rate of 0.7 mL/min using the column and mobile phase provided with the reagent kit. The column temperature was kept at 35 °C, and the backpressure stayed below 300 bar. The injection interval between samples was 3 min with a retention time of 25(OH)D3 of 1.6 min. Peak detection is performed at a UV wavelength of 264 nm. Quantification of 25(OH)D3 was achieved by comparing its peak area to the peak area of the internal standard (retention time 2.1 min), which was added during sample preparation and behaved similarly to the analyte. The normal range of serum levels of 25(OH)D3 was defined as >20 µg/L [29]. Flow cytometry. Immunophenotyping in the prospective study was performed with EDTA blood as part of the routine diagnostic protocol in the Institute of Clinical Chemistry, UKSH Campus Kiel, and included relative proportions and absolute cell counts of CD3, CD4, CD8, CD19, and CD14 cells. Further subset analysis of γδ T cells was performed on Ficoll-Hypaque density gradient-separated peripheral blood mononuclear cells (PBMC). The following mAb were obtained from BioLegend (San Diego, CA, USA): anti-CD3-BV605 (clone OKT3), anti-CD3-PE (clone SK7), and anti-TCR Vδ2-FITC (clone B6). Anti-CD3-PE/APC (clone SK7), anti-TCR γδ-PECy7 (clone 11F2), anti-IFN-γ-PE (clone 4S.B3), and IgG1-PE were from BD Biosciences (Heidelberg, Germany). Anti-Vδ2-FITC (clone IMMU389) was obtained from Beckman Coulter (Krefeld, Germany). Anti-TCR γδ-FITC (clone 11F2) and anti-TCR Vδ2-VioBlue (clone REA771) were from Miltenyi Biotech (Bergisch Gladbach, Germany), and Anti-TCR Vγ9-FITC (clone 7A5) was generated in our laboratory [30]. For cell surface staining, 4 × 105 cells were washed, stained in V-bottom microtiter plates for 20 min on ice with mAb, washed twice, and resuspended in 1% paraformaldehyde. FcR blocking reagent (Miltenyi Biotech) was added at 1:20 dilution before staining. For intracellular staining, cells were washed with staining buffer and stained with antibodies for cell surface CD3 and Vγ9. Subsequently, cells were permeabilized using Cytofix/Cytoperm kit (BD Biosciences) before staining with fluorochrome-conjugated anti-IFN-γ mAb or isotype control. All analyses were measured on a FACS-Canto or LSR-Fortessa cytometer (BD Biosciences), using DIVA (Data-Interpolating Variational Analysis) for acquisition and FlowJo™ v10.6.1 (Ashland, OR, USA) for data analysis. Cell culture and measurement of γδ T cell proliferation. To generate short-term expanded γδ T cell lines, PBMC were stimulated at 1 × 106 cells/mL in 6-well plates with 2.5 μM zoledronate (ZOL) and 50 IU/mL IL-2 in the absence or presence of 1,25(OH)2D3 (Sigma Aldrich, Taufkirchen, Germany, or Enzo Life Sciences, Lörrach, Germany). Zoledronate and recombinant human IL-2 (Proleukin) were kindly provided by Novartis (Basel, Switzerland. A 50 µM stock solution of 1,25(OH)2D3 was prepared in DMSO and stored at −20 °C. The DMSO solvent control (1:1000) corresponding to the highest concentration of 1,25(OH)2D3 did not have any effect. IL-2 was added every other day, and cell cultures were split when required. The purity of γδ T cell lines after 14 d was routinely 74 to 92%. Cell cultures were subjected to microscopic inspection, and photographs were taken at ×100 magnification with an Axiovert 10 microscope (Leitz, Wetzlar, Germany) equipped with an Axiocam 105 camera device and ZEN 2 core v2.5 software (Zeiss, Oberkochen, Germany). For intracellular analysis of cytokine expression, 4 × 105 freshly isolated PBMC were cultured for 48 h in 96-well round-bottom microtiter plates in the presence or absence of 2.5 µM ZOL and 50 nM 1,25(OH)2D3, and 3 μM monensin (Sigma Aldrich) was added during the last 4 h to prevent cytokine secretion. The culture medium was RPMI 1640 (Thermo Fisher Scientific) supplemented with antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin) and 10% of heat-inactivated fetal bovine serum. All cell cultures were incubated at 37 °C in a humidified atmosphere of 5% CO2. Absolute numbers of viable γδ T cells per microculture well were measured after 8 d by a flow cytometry-based method termed standard cell dilution assay (SCDA), as described previously [31]. Briefly, cultured cells from 96-well round-bottom plates were washed and stained with anti-Vγ9-FITC mAb. After one washing step, cells were resuspended in a sample buffer containing a defined number of fixed standard cells and 0.2 μg/mL propidium iodide (PI). Standard cells were purified CD4 T cells that had been stained with APC-labeled antibodies and thereafter had been fixed in 1% paraformaldehyde. Based on the known number of standard cells (FITC−PI+APC+), the absolute number of viable Vγ9 T cells (FITC+PI−) in a given microculture well was determined as described previously [31,32]. The expansion rate was calculated in relation to the absolute number of Vγ9 T cells measured in ZOL- or HMBPP-stimulated cultures in the absence of 1,25(OH)2D3. Measurement of interferon-γ in cell culture supernatants. Short-term γδ T cell lines expanded for 14 d were washed and plated at 2 × 105 cells/well in 96-well round-bottom plates coated or not with 0.5 µg anti-CD3 mAb OKT3 (BioLegend) per well or stimulated with 10 nM (E)-4-Hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP; Echelon Biosciences, Salt Lake City, UT, USA). Then, 50 nM 1,25(OH)2D3 was added as indicated. After 24 h, cell-free supernatants were collected and stored at −20 °C until use. IFN-γ was quantified by ELISA with the DuoSet ELISA Kit from R&D Systems (Wiesbaden, Germany), following the manufacturer’s instructions. In each experimental setting, two replicates were included. Cytotoxicity measured by Real-Time Cell Analyzer. Cytotoxic effector activity of short-term expanded γδ T cell lines against U251MG glioblastoma and BxPC3 pancreatic ductal adenocarcinoma target cells was determined by xCELLigence Real-Time Cell Analyzer (RTCA; Agilent, Santa Clara, CA, USA) which measures the decrease in the impedance of adherent tumor cells over extended time periods as a correlate of cell lysis. U251MG (ECACC 89081403) was obtained from the European Collection of Authenticated Cell Cultures (ECACC, Salisbury, UK). BxPC3 [33] was provided by Dr. Christian Röder, Institute for Experimental Cancer Research (UKSH Kiel, Germany). Tumor cell lines were maintained in a complete culture medium, and 0.05% trypsin/0.02% EDTA or accutase (Thermo Fisher Scientific) was used to detach adherent cell lines from flasks. RTCA was performed as previously described [34,35]. Briefly, 8000 tumor cells in complete medium were added to each well of the micro-E plates. After overnight incubation, γδ effector T cells were added at an effector/target ratio of 10:1 with or without HMBPP as a positive control to enhance TCR-dependent lysis. The impedance of the cells was recorded via electronic sensors on the bottom of the 96-well micro-E-plate every 3 min for up to 48 h. Results were analyzed with RTCA software (version 2.0.0.1301; Agilent, Santa Clara, CA, USA) and normalized, as described in [34]. Results of several experiments with different γδ T cell lines are summarized as the percentage of cell death induced by γδ T cells at various time points in relation to the corresponding tumor cell index in medium and Triton-X100 (maximal lysis). Time point zero was defined as the first measurement after the addition of γδ T cells. Statistical analysis. All analyses were performed with the Graphpad Prism 8 (GraphPad Software, San Diego, CA, USA) and SPSS 28.0 software (IBM, Armonk, NY, USA). Linear regression was performed for the seasonal analysis of γδ T cells in the retrospective analysis. Statistical comparisons between groups were made using the Wilcoxon matched pairs signed-rank test for dependent samples without a normal distribution (RTCA, ELISA, SCDA). The Mann–Whitney U test was used in the case of the non-normal distribution of independent data in two groups. Non-normal data sets with more than two groups were analyzed with Kruskal–Wallis test and Dunn’s multiple comparison test. Levels of significance were set as * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. 3. Results Our study consisted of three parts: (i) a retrospective analysis over ten years of the proportion of γδ T cells in a large cohort of random healthy blood donors; (ii) a prospective immunophenotypic analysis of γδ T cells and other immune cells in a small cohort of healthy adults who did or did not take oral vitamin D3 supplementation; and (ii) in vitro studies on the modulation of γδ T cell activation by the active vitamin D metabolite 1,25(OH)2D3. 3.1. Retrospective Analysis As a first approach to investigate a possible seasonal fluctuation in the proportion of γδ T cells circulating in peripheral blood, we performed a retrospective analysis of data from the weekly screening of leukocyte concentrates from random healthy adult blood donors. Parameters such as age, gender, or potential vitamin D3 uptake were not taken into consideration. From 2011 to 2020, a total of 2625 blood samples were stained for CD3/pan-γδ and CD3/Vδ2, and the proportion of total γδ T cells and Vδ2 T cells among CD3 T lymphocytes was calculated. The gating strategy used in this analysis is shown in Supplementary Figure S1. The results with the mean values per month of each year are displayed for total γδ T cells in Supplementary Figure S2a and for Vδ2 T cells in Supplementary Figure S2b. Next, we combined results from individual months into four seasons (Spring: March, April, May; Summer: June, July, August; Autumn: September, October, November; Winter: December, January, February). The results of the ten years from all donors according to the season are displayed for total γδ T cells in Figure 1a and for Vδ2 T cells in Figure 1b. In the left panels, all data points and the means are displayed to illustrate the range of γδ T cell proportions, while in the right panels, mean values ± SEM with a higher resolution on the y axis are displayed to better visualize seasonal differences. Significantly higher total γδ and Vδ2 T cell proportions were observed in winter when compared with summer, and in the case of total γδ T cells also when compared with spring. The screening of random blood donors over 10 years was performed because of our continued interest in identifying donors with reasonable proportions of γδ T cells for a variety of functional experiments with isolated γδ T cells. For this reason, we did not include other markers such as CD4 and CD4 in the screening, which would have provided important additional information on the seasonal variation of immune cells. While many parameters might influence the seasonal fluctuation of immune cell frequencies, one such parameter could be vitamin D3 which is subject to seasonal alterations related to the intensity of sunshine exposure. Furthermore, cholesterol, which is the precursor molecule of vitamin D synthesis, is a metabolite of the mevalonate pathway, which generates Vγ9Vδ2 T cell-activating pyrophosphates (IPP, geranyl pyrophosphate) [8]. Therefore, our next step was to perform a prospective immunophenotypic study with up to eight time points over one year in a small cohort of healthy adult donors who did or did not take oral vitamin D3 supplementation. 3.2. Prospective Analysis Characteristics of blood donors are summarized in Supplementary Table S1. There were 14 men and 17 women; the mean age was 27.3 ± 3.3 years. Among them, 14 donors did not take any oral vitamin D3 (group 1), 9 donors took vitamin D3 regularly throughout the year (group 3), while 8 donors took vitamin D3 irregularly (group 2). The gating strategy for measuring total γδ T cells and Vδ2 T cells among CD3+ T cells is shown in Supplementary Figure S3. We first compared Vδ2 T cell proportions according to oral vitamin D3 uptake in all respective donors per group and across all time points (Figure 2). In this analysis, the donors who did not take vitamin D3 (group 1) had higher Vδ2 T cell proportions compared with the donors who regularly took vitamin D3 (group 3) (mean 6.1% vs. 4.5%, p < 0.05). Next, we determined serum levels of 25(OH)D3 and the proportion of Vδ2 T cells in the three groups according to the seasons (defined as in Section 3.1). Donors who did not take oral vitamin D3 (group 1) had low serum levels (<20 µg/mL) of 25(OH)D3 in spring and winter and—as expected—significantly higher levels in summer and autumn due to increased sun exposure (Figure 3a, left panel). Donors who took vitamin D3 with an interruption during the summer months (group 2; Figure 3a, middle panel) or regularly throughout the year (group 3; Figure 3a, right panel) had, on average, normal (>20 µg/mL) serum levels of 25(OH)D3 throughout the year. We then determined the proportion of Vδ2 T cells among CD3 T cells in the three groups and according to the season. Throughout the year, the highest mean values for Vδ2 T cell proportions were always observed in group 1 donors without oral vitamin D3 supplementation (Figure 3b). This tendency was most prominent in spring when the mean Vδ2 T cell proportion was 7.0% in group 1, 4.5% in group 2, and 3.5% in group 3 donors (p = 0.0276). However, there was no direct correlation between the actually measured 25(OH)D3 serum levels with the proportion of Vδ2 T cells across all donors (Supplementary Figure S4). In addition to Vδ2 T cells which dominate in peripheral blood, we also analyzed seasonal changes in the proportion of the minor subset of non-Vδ2 γδ T cells (which mainly comprises Vδ1 γδ T cells), but there was no obvious seasonal fluctuation in non-Vδ2 γδ T cells (Supplementary Figure S5a). The proportion of non-Vδ2 γδ T cells also did neither correlate with low (<20 µg/L) or higher serum levels of 25(OH)D3 (Supplementary Figure S5b) nor with oral vitamin D3 (Supplementation (Supplementary Figure S5c)). In addition to γδ T cells, we also performed immunophenotyping of conventional immune cell subsets (CD3, CD4, CD8, CD19, CD14) in the prospective study. To delineate a possible influence of serum 25(OH)D3 levels, we grouped all study participants into low (<20 µg/L) and normal (>20 µg/L) serum levels and according to the season. These results are presented in Figure 4a–e. While there was a slight tendency for lower CD8 T cell proportions when serum levels of 25(OH)D3 were > 20 µg/L (Figure 4d), no clear-cut correlation between 25(OH)D3 serum levels and immune cell subset distribution emerged. Relative proportions of immune cell subsets are shown in Figure 4, but similar patterns were observed if absolute cell counts were considered (results not shown). Because of the slightly reduced CD8 T cell proportions (Figure 4d), a slightly higher CD4/CD8 ratio was observed in donors with higher 25(OH)D3 serum levels (Figure 4f; mean 1.83 vs. 1.67, statistically not significant). For comparison, we also performed a similar analysis for total γδ T cells and Vδ2 T cells (Supplementary Figure S6a,b). 3.3. Modulation of γδ T Cell Activation In Vitro In the third part of this study, we investigated the modulatory role of vitamin D3 on the in vitro activation of γδ T cells. To this end, we investigated the effects of the active vitamin D3 metabolite 1α,25-Dihydroxyvitamin D3 [1,25(OH)2D3] on the proliferative activity, antitumor cytotoxicity, and cytokine production of γδ T cells. 3.3.1. Inhibition of γδ T Cell Expansion PBMC were activated with predetermined optimal concentrations of ZOL (2.5 µM) or HMBPP (10 nM) in the presence of 50 IU/mL IL-2 and titrated concentrations of 1,25(OH)2D3, or solvent control DMSO corresponding to the highest possible concentration in which 1,25(OH)2D3 was dissolved (1:1000). Dose-dependent inhibition of T cell proliferation was observed macroscopically after 6 d (Supplementary Figure S7a) and could be verified upon microscopic inspection (Supplementary Figure S7b). Next, we quantified the inhibitory effect of 1,25(OH)2D3 on γδ T cell proliferative expansion stimulated by ZOL or HMBPP. To this end, PBMC were cultured in 96-well round-bottom plates and were activated by 2.5 µM ZOL or 10 nM HMBPP in the presence of IL-2 and titrated concentrations of 1,25(OH)2D3. After 8 d, the absolute number of viable Vγ9 T cells per microculture well was determined, and the measured cell number in untreated control cultures was set as 100%. As shown for ZOL in Figure 5a and HMBPP in Figure 5b, 1,25(OH)2D3 dose-dependently inhibited the Vγ9 T cell expansion to both selective γδ T cell stimuli, with >50% inhibition observed at 50 nM 1,25(OH)2D3. The solvent control DMSO at 1:1000 dilution did not affect γδ T cell expansion (not shown). In the SCDA analysis, cell cultures are stained with propidium iodide (PI) to exclude dead cells (see Materials and Methods). While there was more cell death of Vγ9 T cells (i.e., PI+Vγ9+) in ZOL-stimulated cultures in comparison with HMBPP-activated cell cultures, this was not modulated in the presence of 1,25(OH)2D3, suggesting induction of apoptosis was not the main reason for the observed growth inhibition (Supplementary Figure S8). 3.3.2. Modulation of Cytotoxic Effector Activity Short-term γδ T cell lines to be used as effector cells in cytotoxicity assay were generated by activating PBMC with ZOL and IL-2 in the absence or presence of 50 nM 1,25(OH)2D3. Cell cultures were supplemented with IL-2 every two days and were split when appropriate. 1,25(OH)2D3 was added once again after 7 d. Such cell lines contained 74–92% CD3+ Vδ2+ γδ T cells after 14 d, the time point when cells were washed and used as effector cells in RTCA cytotoxicity assays with pancreatic adenocarcinoma BxPC3 or glioblastoma U251MG target cells. In some experiments, γδ T cells were used earlier than d 14. The RTCA plot over a total time period of 48 h of one experiment with BxPC3 target cells is shown in Figure 6a. Tumor cells were seeded at time point 0 h, and effector cells +/− HMBPP, as well as Triton-X 100, were added at time point 26 h. From this time point, the RTCA continued for another 22 h. Cytotoxicity after 6 h of coculture thus corresponds to time point 32 h in Figure 6a, whereas cytotoxicity after 22 h corresponds to time point 48 h in this graph. As expected, the addition of the TCR stimulus HMBPP to the assay greatly increased the cytotoxic activity of expanded Vδ2 T cells. Interestingly, the Vδ2 effector T cells expanded in the presence of 1,25(OH)2D3 were less active in killing BxPC3 target cells, as evidenced by the yellow line (1,25(OH)2D3) in comparison with the blue line (medium) in Figure 6a. The lower activity of 1,25(OH)2D3-expanded Vδ2 effector T cells was also not fully restored in the presence of HMBPP (compare purple and green lines). A summary of experiments with 10 different Vδ2 T cell lines generated from different donors and BxPC3 target cells at an E/T ratio of 10:1 is shown in Figure 6b (time point 6 h) and Figure 6c (time point 22 h). Lysis of BxPC3 cells in the absence of HMBPP was moderate after 6 and 22 h and tended to be lower at 22 h with Vδ2 effector cells generated in the presence of 1,25(OH)2D3, which, however, did not reach statistical significance. As expected, lysis at both 6 and 22 h was strongly increased in the presence of HMBPP. Interestingly, at both time points, killing by 1,25(OH)2D3-expanded Vδ2 effector cells in the presence of HMBPP was slightly but significantly reduced (p < 0.05). U251MG glioblastoma target cells are known to be more sensitive to γδ T cell lysis compared with BxPC3 [35]. In line, the strong killing of U251MG target cells by ZOL-expanded γδ T cells was already observed after 6 h (Figure 6d) and was further increased after 22 h (Figure 6e). When measured after 22 h, Vδ2 T cells expanded in presence of 1,25(OH)2D3 were slightly but significantly less efficient in killing U251MG tumor cells (Figure 6e). The addition of HMBPP further enhanced the killing activity, both at 6 h and 22 h. In the presence of HMBPP, there was almost complete lysis already after 6 h, and this was slightly reduced with Vδ2 effector T cells expanded in the presence of 1,25(OH)2D3. 3.3.3. Modulation of Cytokine Production Finally, we analyzed the effect of 1,25(OH)2D3 on the IFN-γ production by activated γδ T cells in two different setups, namely by flow cytometry in γδ T cells within freshly isolated PBMC and by ELISA in supernatants of expanded γδ T cell lines. To this end, PBMC were activated with ZOL, and short-term expanded γδ T cell lines were restimulated with HMBPP or immobilized anti-CD3 antibody. As shown in Figure 7a (left dot plot), 32.1% of γδ T cells stained positive for intracellular IFN-γ when PBMC were activated for 48 h with ZOL. In the presence of 1,25(OH)2D3, this proportion was reduced to 15.1% (Figure 7a, right dot plot). γδ T cell lines expanded for 14 d secreted IFN-γ when restimulated overnight with HMBPP or with immobilized anti-CD3 antibody (Figure 7b). The presence of 1,25(OH)2D3 significantly reduced the IFN-γ secretion in response to HMBPP (mean 0.95 ng/mL vs. 1.33 ng/mL). Stimulation with immobilized anti-CD3 antibody is a much stronger activation signal and induced a threefold higher concentration of secreted IFN-γ (mean 3.95 ng/mL). Again, this was reduced by 1,25(OH)2D3 (mean 3.67 ng/mL), but the inhibition did not reach statistical significance (Figure 7b). 4. Discussion Under physiologic conditions, the homeostasis of the immune system is well controlled. While the global immune cell composition is influenced by genetic background, sex, age, and environmental factors such as a persistent CMV infection [36,37,38], there are also variations over time at the individual level. These include seasonal variability in gene expression and some immune parameters, but also nonseasonal longitudinal variation in functional immune responses [39,40,41]. Previous studies have investigated the fluctuation of defined immune cell subsets in healthy individuals at several time points during one year, thus providing a snapshot of variation during the seasons. Using multicolor flow cytometry, Khoo et al. [27] observed enhanced CD4, and to a lesser extent CD8, T cell counts in spring and summer compared with winter, as well as seasonal variation in homing marker expression on CD4 T cells. Only moderate variability over time in relation to the season was reported in more recent studies employing multicolor flow cytometry or high throughput mass cytometry for phenotyping [40,41]. Interestingly, CD4+CD25high regulatory T cells (Treg) were found to be most strongly affected by seasonality, with their frequency peaking in autumn [40]. However, the minor population of γδ T cells was not included in previous analyses [27,40,41]. Many factors might impact the variation of immune parameters, including the contrasting weather conditions in summer vs. winter, but also physical activity and diet. Exposure to solar or artificial ultraviolet radiation has an impact on immune cells in human blood [42]. In this context, vitamin D is an important factor that is not only a regulator of calcium and phosphate metabolism but also a potent modulator of immune cell function [18,21]. The essential step is the generation of vitamin D3, which results from the absorption of UV-B radiation (and thus sun exposure) by 7-dehydrocholesterol in the skin. The subsequent metabolism in the liver and kidney produces the biologically active 1,25(OH)2D3, which exerts its functional activity via the nuclear vitamin D receptor (VDR). Vitamin D sensing by the transcription factor VDR initiates epigenetic and transcriptional regulation of a plethora of target genes [43]. Serum levels of 25(OH)D3 (the immediate precursor of 1,25(OH)2D3) vary considerably, with higher levels measured in summer when sun exposure is more intensive compared with winter [44]. In view of its immunoregulatory role, vitamin D3 deficiency has been associated with various diseases, notably with the onset of various autoimmune diseases and the incidence and severity of infections, including upper respiratory tract infections caused by influenza and SARS-CoV-2 [17,18,45]. To maintain sufficient serum levels of vitamin D3 throughout the year, the oral supplementation with vitamin D3 (cholecalciferol) or (less frequently) vitamin D2 (ergocalciferol) is widely recommended, even though there is no uniform opinion about the optimal dosage and serum concentration [18,45,46,47]. The immunomodulatory effects of vitamin D3 might be beneficial on the basis of several mechanisms of action which have been described. It must be emphasized, however, that there is also controversy as to how some of the in vitro observations translate into measurable effects in vivo upon oral vitamin D3 uptake [48]. This notwithstanding, it is obvious that vitamin D3 affects both innate and adaptive immunity. The vitamin D receptor (VDR) has been shown to act as a negative regulator of the NLRP3 oligomerization and activation. In consequence, vitamin D3 inhibits NLRP3 inflammasome activation and IL-1β secretion and thus might be useful in the treatment of inflammatory conditions [49]. At the crossroads between innate and adaptive immunity, vitamin D3 induces a tolerogenic phenotype in dendritic cells (DCs) [50], which has recently been linked to JAK2-mediated STAT3 phosphorylation [51]. The induction of tolerogenic DCs might help control autoreactive T cells in autoimmune diseases. This could also be supported by the promotion of Treg activation and suppressive activity by vitamin D3. In several studies, vitamin D3 was found to increase the expression of the Treg-specific transcription factor FoxP3 in naturally occurring Treg [20,52,53,54], and this may be associated with enhanced suppressive activity, cell cycle progression, and proliferation of Treg [54,55,56,57]. However, additional mechanisms could contribute to the potentially beneficial effect of vitamin D3 on autoreactive T cells, including the upregulation of immunosuppressive CD73, the induction of IL-10, and the inhibition of proinflammatory Th17 cells [20,58,59,60,61]. The focus of our study was twofold, i.e., (i) to investigate the seasonal variation of γδ T cells in healthy adult individuals and (ii) to analyze the possible impact of vitamin D3 on the seasonal frequency and on in vitro activation of γδ T cells. Even though a numerically small subset of peripheral blood T cells, γδ T cells fulfill important functions in the immune response to infection and stressed/transformed cells [10,11,12]. Because of their HLA-nonrestricted mode of action and potent cytotoxic activity, multiple approaches are currently under investigation to apply γδ T cells in immunotherapy of cancer and viral (re)infection [10,11,12,62,63]. The recent demonstration that it is safe to transfer γδ T cells expanded in vitro from healthy donors across HLA barriers into cancer patients has opened the way to apply off-the-shelf γδ T cell therapy to treat cancer patients [64]. Our retrospective analysis of 2625 samples of random blood donors over ten years revealed small but statistically significant differences in the proportion of γδ T cells (both total γδ T cells and the Vδ2 subset) across the seasons, with higher γδ T cell proportions recorded in winter compared with spring and summer. We are fully aware of the limitations of this analysis as we did not consider confounders such as age, sex, potential oral vitamin D3 supplementation, etc. We performed the screening over 10 years to identify random blood donors with sufficient numbers of γδ T cells for various γδ T cell-focused projects. It is certainly an additional limitation of the retrospective analysis that we did not include other markers such as CD4 and CD8. Nevertheless, in view of the very large sample number, we took this as an indication that there might be a seasonal variation of γδ T cells circulating in the blood. Furthermore, we considered that this could be influenced by vitamin D3 levels, which are higher in summer compared with winter. Given the paucity of the information in the literature, this is the first hint for seasonal variation of γδ T cells in a large cohort of random healthy adult blood donors. To investigate the seasonal fluctuation in individual donors, we initiated a small prospective study with 31 healthy adults who did or did not take oral vitamin D3 supplementation. We performed immunophenotyping, including γδ T cells and conventional immune cell subsets at up to eight time points over one year; serum levels of 25(OH)D3 were measured at the same time points. Several observations emerged from this analysis which point to a possible influence of vitamin D3 on circulating γδ T cell frequency. First, the analysis of all data points from all donors indicated a higher proportion of Vδ2 T cells in donors who did not take oral vitamin D3 in comparison with individuals who took vitamin D3 supplementation throughout the year (Figure 2). Secondly, the measured serum levels of 25(OH)D3 correlated as expected with the practice of taking oral vitamin D3 or not. Thus, low levels were measured in spring and winter, and higher levels in summer and autumn in individuals who did not take any oral vitamin D3. By contrast, higher levels with little seasonal variation were measured both in individuals who regularly took vitamin D3 and in those who took vitamin D3 with interruptions during the summer (Figure 3a). In line with the assumption that low levels of vitamin D3 are associated with higher proportions of circulating γδ T cells, we measured, on average, the highest γδ T cell frequencies across the four seasons in donors without oral vitamin D3 supplementation, whereas lower γδ T cell proportions were detected during the year in individuals taking oral vitamin D3. This difference reached statistical significance in spring but not in the other seasons (Figure 3b). These results suggest that vitamin D3 might have a negative impact on the proportion of circulating γδ T cells, an assumption which would be in line with the observed suppressive effects of the active vitamin D3 metabolite 1,25(OH)2D3 in vitro (see below). Obviously, a verification of this hypothesis will require a larger prospective study with more individuals and under strictly controlled vitamin D3 uptake conditions. In a previous study on osteoporosis patients who were on ZOL treatment, De Santis et al. did not observe a correlation between 25(OH)D3 serum levels and γδ T cell numbers [65]. However, this study cannot be directly compared with our results in untreated healthy individuals since the therapeutic application of ZOL induces in vivo activation of γδ T cells but also leads to a depletion of circulating γδ T cells upon prolonged treatment with aminobisphosphonates [66,67]. In parallel to γδ T cells, we also analyzed the frequency of other immune cells in the prospective cohort and categorized the results according to the measured 25(OH)D3 serum levels. The proportion of CD8 T cells tended to be lower in individuals with higher serum levels of 25(OH)D3, resulting in a slightly elevated CD4/CD8 ratio as compared with individuals with <20 μg/L 25(OH)D3. Overall, these results of immunophenotyping are in line with previous studies with more extensive marker panels [40,41]. However, it is well possible that serum 25(OH)D3 levels and vitamin D3 uptake have more pronounced effects on particular subsets of conventional CD4 and CD8 T cells. In this respect, Khoo et al. observed seasonal variation of CD4 T cell subsets defined by memory marker and homing receptor expression [27]. Seasonal variation in the intensity of UV radiation may also affect other factors relevant to the immune system, such as nitric oxide (NO). NO is an important modulator of T cell activation [68,69] and is generated in the skin by UV-A and near-infrared wavelength [70,71]. It is currently unknown how skin-derived NO might affect γδ T cell plasticity in vivo. We also investigated the modulation of in vitro activation and effector functions of γδ T cells by the active metabolite 1,25(OH)2D3. Numerous previous studies have reported the modulation of CD4 T cell differentiation by 1,25(OH)2D3, but only one previous study has focused on γδ T cells [28]. The accumulated evidence supports the notion that vitamin D3 inhibits CD4 T cell proliferation and inhibits their inflammatory gene program by suppressing IL-17 and IL-9 and favoring IL-10 induction [19,72,73,74,75]. A recent molecular analysis demonstrated that Th1 cells could turn off their proinflammatory cytokine program in an autocrine manner and switch to IL-10 production in response to vitamin D3, a process that depends on several transcription factors, including c-JUN, STAT3, and BACH2 [23]. We observed that 1,25(OH)2D3 drastically inhibited the in vitro expansion of γδ T cells when PBMC were stimulated with γδ T cell-specific ligands such as ZOL and HMBPP. The experiments were carried out in the presence of exogenous IL-2, so growth inhibition did not occur at the level of endogenous IL-2 production. Using a different read-out system, Chen and colleagues also reported γδ T cell growth inhibition by 1,25(OH)2D3 [28]. The activation of γδ T cells within PBMC using ZOL as a stimulus completely depends on the presence of monocytes [8]. One possible reason for the inhibition seen in the presence of 1,25(OH)2D3 could be that 1,25(OH)2D3 interferes with the production of the γδ T cell-activating pAg IPP in monocytes which would have to be analyzed in future studies. On the other hand, proliferative expansion was also inhibited in response to the synthetic pAg HMBPP, which is less dependent on monocytes but also requires accessory cells [76]. Our data extracted from the SCDA experiments do not suggest that there was significant additional cell death of γδ T cells in the presence of up to 50 nM 1,25(OH)2D3. This indicates that growth inhibition might result from cell cycle arrest rather than induction of apoptosis. On the other hand, Chen et al. observed increased cell death when γδ T cells were activated with IPP and higher (100 nM) concentrations of 1,25(OH)2D3 than used in our study [28]. Taken together, the analysis of the precise molecular mechanisms of growth inhibition of γδ T cells by 1,25(OH)2D3 will require further investigation. We also observed that 1,25(OH)2D3 inhibits the IFN-γ production in human γδ T cells. Inhibition of IFN-γ induction in γδ T cells within PBMC was previously reported by Chen et al. [28], and we confirmed this observation in a slightly different system. Again, we stimulated PBMC with ZOL in the absence or presence of 1,25(OH)2D3. When analyzed after 48 h, the proportion of γδ T cells expressing IFN-γ was markedly reduced in the presence of 1,25(OH)2D3. Under these conditions, it is likely that monocytes play an essential role. We extended these experiments to demonstrate that 1,25(OH)2D3 also reduced IFN-γ secretion when expanded γδ T cell lines are stimulated with pAg or anti-CD3 antibody. While the effect in the anti-CD3 antibody stimulation was minimal, it was significant when γδ T cell lines were activated with HMBPP. Therefore, 1,25(OH)2D3 can directly act on activated γδ T cells, in line with the demonstration that activated T cells express a functional VDR [28,77]. While our and the previous results [28] clearly demonstrate that 1,25(OH)2D3 suppresses IFN-γ induction in human γδ T cells, it remains to be investigated if 1,25(OH)2D3 might also act to drive γδ T cell differentiation towards IL-10 production. γδ T cell lines expanded in the presence of 1,25(OH)2D3 displayed reduced cytotoxic activity towards two different tumor target cells. The RTCA system applied here has been extensively used to follow the cytotoxic effect of γδ T cells on tumors over extended time periods [34,35]. The two tumor cell lines applied here are differentially susceptible to γδ T cell-mediated lysis. The glioblastoma U251MG is highly susceptible, while the pancreatic adenocarcinoma BxPC3 is much less susceptible [35]. In all settings, 1,25(OH)2D3-expanded γδ T cells were not more active than the control γδ T cell lines. In fact, the enhanced lysis of BxPC3 target cells noticed in the presence of the TCR-activating pAg HMBPP was also reduced at both early (6 h) and later (22 h) time points by 1,25(OH)2D3 treatment. There were fewer differences between control and 1,25(OH)2D3-expanded γδ T cells when U251MG were used as target cells, but again, there was some reduction in the absence of HMBPP after 22 h and a minor reduction in the presence of HMBPP after 6 h. Again, the underlying mechanisms have not been investigated in more detail in this study. γδ T cells can utilize both death receptor/ligand pathways (e.g., Fas/CD95, TRAIL) as well as the secretory pathway (perforin, granzyme B, granulysin) to kill target cells [78,79,80]. Previous investigations have demonstrated that 1,25(OH)2D3 downregulates the cytotoxic effector response in pulmonary tuberculosis by reducing the expression of perforin, granulysin, and granzyme B [81]. It remains to be investigated if a similar mechanism contributes to the regulation of cytotoxic function in human γδ T cells by vitamin D3. While binding of 1,25(OH)2D3 to the nuclear VDR is an established mode of action, it is also known that several other vitamin D3 hydroxyderivatives can act on other nuclear receptors such as the liver X receptors (LXRs) and retinoic acid-related orphan receptors (RORs) [82,83]. How the activation of such receptors by vitamin D3 hydroxyderivatives might impact the in vivo fluctuation of immune cells and the in vitro activation of γδ T cells is presently unknown. Overall, the results of our in vitro studies imply that 1,25(OH)2D3 exerts mainly inhibitory effects on human γδ T cells (at least in the read-out systems analyzed here). If relevant in vivo, such an inhibitory effect could be in line with the higher proportion of γδ T cells in the blood of individuals with low 25(OH)D3 serum levels in spring and winter—a hypothesis that certainly needs further validation. The results of our study are of interest in the context of the potential application of exogenous vitamin D3 in diseases, notably when harnessing γδ T cells for immunotherapy of cancer. Enhancing Treg activity and modulating T cell differentiation by suppressing Th1 and Th17 responses towards IL-10 induction by vitamin D3 supplementation might be advisable for autoimmune and inflammatory diseases [84]. However, the inhibition of effector functions might also have a negative impact on T cell-mediated antitumor immunity, as recently shown in a 3D tumor spheroid model [85]. This notwithstanding, vitamin D3 has been proposed to exert anticancer effects by acting on the tumor microenvironment as well as directly on some tumor cell types [86,87]. Given the current enthusiasm to translate the unique features of γδ T cells into novel cancer immunotherapies, further studies are warranted to investigate in more detail the impact of vitamin D3 and its therapeutic application on the γδ T cell compartment. 5. Conclusions Our study points to a possible role of vitamin D3 in the homeostasis of peripheral blood γδ T cells, which needs to be verified in a larger cohort and under well-controlled conditions of vitamin D3 supplementation. In vitro, the active vitamin D3 metabolite 1,25(OH)2D3 inhibited γδ T cell activation and effector functions. Oral vitamin D3 supplementation is frequently recommended to cancer patients, and γδ T cells are in development as novel cellular cancer immunotherapy. Our study raises a caveat as to whether (high) dose vitamin D3 therapy is advisable during γδ T cell immunotherapy by adoptive γδ T cell transfer of in vivo activation of γδ T cells [12]. Acknowledgments We gratefully acknowledge the technical assistance of Monika Kunz with cell culture and ELISA. We also thank Daniela Wesch for coordinating the weekly supply of leukocyte concentrates from the Department of Transfusion Medicine, UKSH Campus Kiel. We thank Siegfried Goerg and the Department of Transfusion Medicine, UKSH Campus Kiel, for providing leukocyte concentrates. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells11091460/s1, Table S1: characteristics of 31 prospective study group participants, Figure S1: gating strategy for retrospective analysis, Figure S2: mean values of total γδ T cells and Vδ2 T cells in retrospective analysis, Figure S3: gating strategy for prospective analysis, Figure S4: correlation of Vδ2 T cells with serum 25(OH)D3 levels, Figure S5: seasonal analysis of non-Vδ2 γδ T cells and correlation with Vitamin D3 in the prospective analysis, Figure S6: seasonal variation of γδ T cells and correlation with serum 25(OH)D3 levels, Figure S7: growth inhibition of Zoledronate-activated PBMC by 1α,25(OH)2D3. Figure S8: influence of 1α,25(OH)2D3 on cell death of Vγ9 T cells. Click here for additional data file. Author Contributions Conceptualization, R.S. and D.K.; data curation, J.F.; formal analysis, B.B. and C.B.; investigation, B.B., N.E., K.K. and C.P.; project administration, B.B. and R.S.; resources, R.J.; supervision, O.J., R.S. and D.K.; validation, B.B., N.E. and R.J.; writing—original draft, D.K.; writing—review & editing, C.P., O.J., R.J., R.S. and D.K. All authors have read and agreed to the published version of the manuscript. Funding B.B. was the recipient of a research fellowship provided by the Medical Faculty of the Christian-Albrechts University Kiel. R.S. was the recipient of a long-term research fellowship (grant number 91562239) provided by the German Academic Exchange Service (DAAD). D.K. and R.J. are members of the Excellence Cluster Precision Medicine in Chronic Inflammation. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Medical Faculty of Christian-Albrechts University Kiel (code D 579/19, approved 19 December 2019). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data underlying the results presented in this paper are available upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Seasonal variation of γδ T cells in random blood donors over ten years. A total of 2625 blood samples from random healthy adult blood donors collected from 2011 to 2020 were analyzed for the proportion of total γδ T cells (a) and Vδ2 T cells (b) among CD3+ T cells. In the left panels, all individual data points are displayed, while in the right panels, mean values ± SEM are shown. For statistical analysis, a linear regression was performed. The dependent variable was total γδ T cells (R2 = 0.003) in (a) and Vδ2 T cells (R2 = 0.002) in (b). For statistical comparison, the reference season was Winter, * p < 0.05. Figure 2 The proportion of Vδ2 T cells among CD3+ T cells according to oral vitamin D3 supplementation. All analyzed time points of all donors in three groups are displayed: group 1 (blue): no oral vitamin D3, 14 donors; group 2 (green): interrupted oral vitamin D3 supplementation, 8 donors; group 3 (orange): continuous vitamin D3 uptake, 9 donors. Bars represent mean values ± SEM. Statistical comparison was made by Kruskal–Wallis test and Dunn’s multiple comparison test. * p = 0.0113. Figure 3 Seasonal fluctuation of serum 25(OH)D3 levels and proportion of Vδ2 T cells according to oral vitamin D3 supplementation. (a) Serum levels of 25(OH)D3 in donors without vitamin D3 supplementation (left panel, blue symbols), in donors with interrupted vitamin D3 uptake (middle panel, green symbols), and in donors with regular vitamin D3 uptake (right panel, orange symbols). Statistical comparison was made by Wilcoxon matched pairs signed-rank test, by testing each season against winter. (b) The proportion of Vδ2 T cells among CD3 T cells according to the season in the same individuals. Bars represent mean values ± SEM. Statistical comparison was made by Kruskal–Wallis test and Dunn’s multiple comparison test. * p = 0.0276; ** p < 0.01, and **** p < 0.0001. Figure 4 Seasonal variation of immune cell subsets and correlation with serum 25(OH)D3 levels. Proportions of CD3 (a), CD19 (b), CD4 (c), CD8 (d), and CD14 (e) cells were measured in blood samples from all donors in the prospective study. Mean values ± SEM and individual data points are displayed according to the season and according to the serum level of 25(OH)D3: low (left panels: <20 µg/L), normal (right panels: >20 µg/L). (f) CD4/CD8 ratio according to serum 25(OH)D3 levels (all donors, all time points). Statistical comparison in (f) was made by Mann–Whitney U test but did not reach significance. Figure 5 1,25(OH)2D3 inhibits γδT cell expansion. PBMC from healthy donors were activated with 2.5 µM Zoledronate (a) or 10 nM HMBPP (b) in the presence of IL-2 and the indicated concentrations of 1,25(OH)2D3. After 8 d, the absolute number of viable Vγ9 T cells was determined. The number of viable γδ T cells in control cultures without 1,25(OH)2D3 was set as 100%, and the relative growth of γδ T cells in the presence of 1,25(OH)2D3 was calculated. Mean ± SEM of 8–9 (a) and 6–7 (b) independent experiments are shown. Statistical significance was analyzed by the Wilcoxon matched pairs signed-rank test. * p < 0.05, ** p < 0.01. Figure 6 Cytotoxic activity of γδ T cells expanded in the absence or presence of 1,25(OH)2D3. Vδ2 T cell lines expanded for 14 d from ZOL-stimulated PBMC in the absence or presence of 50 nM 1,25(OH)2D3 were used as effector cells (E/T ratio 10:1) in the RTCA with BxPC3 (a–c) or U251MG target cells (d,e). Where indicated, HMBPP was added at a final concentration of 10 nM. The impedance was continuously recorded over 48 h beginning with the addition of tumor cells. Effector cells were added at time point 26 h, and the % specific lysis was calculated in relation to spontaneous tumor cell growth and Triton X-100 induced maximal lysis at 6 h and 22 h after addition of effector cells, based on the normalized cell index, which was set to 1 at the time when effector cells were added. (a) RTCA plot with one Vδ2 effector cell population and BxPC3 tumor target cells. (b,c) Specific lysis of BxPC3 target cells at 6 h (b) and 22 h (c) by control or 1,25(OH)2D3-expanded Vδ2 effector T cells in the absence or presence of HMBPP. (d,e) Specific lysis of U251MG target cells at 6 h (d) and 22 h (e) by control or 1,25(OH)2D3-expanded Vδ2 effector T cells in the absence or presence of HMBPP. Mean ± SEM of experiments with 10 different Vδ2 T cell lines is shown. Statistical significance was analyzed by the Wilcoxon matched pairs signed-rank test. * p < 0.05. Figure 7 1,25(OH)2D3 inhibits IFN-γ induction in γδ T cells. (a) PBMC were activated with 2.5 µM ZOL in the absence (left dot plot) or presence (right dot plot) of 50 nM 1,25(OH)2D3. After 48 h, cells were stained for intracellular detection of IFN-γ in CD3+Vγ9+ T cells. One of two experiments is shown. (b) γδ T cell lines generated from ZOL-activated PBMC and expanded for 14 d were cultured overnight in a medium (n = 6), with HMBPP (n = 6) or immobilized anti-CD3 antibody (n = 4) in the absence or presence of 50 nM 1,25(OH)2D3, as indicated. IFN-γ in culture supernatants was measured by ELISA. Statistical analysis was performed with Wilcoxon matched pairs signed-rank test. * p = 0.0313. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kalyan S. Kabelitz D. Defining the nature of human γδ T cells: A biographical sketch of the highly empathetic Cell Mol. Immunol. 2013 10 21 29 10.1038/cmi.2012.44 23085947 2. Argentati K. Re F. Donnini A. Tucci M.G. Franceschi C. Bartozzi B. Bernardini G. Provinciali M. Numerical and functional alterations of circulating gammadelta T lymphocytes in aged people and centenarians J. Leukoc. Biol. 2002 72 65 71 12101264 3. Caccamo N. Dieli F. Wesch D. Jomaa H. Eberl M. Sex-specific phenotypical and functional differences in peripheral human Vgamma9/Vdelta2 T cells J. Leukoc. Biol. 2006 79 663 666 10.1189/jlb.1105640 16461739 4. Xu W. Lau Z.W.X. Fulop T. Larbi A. The Aging of γδ T Cells Cells 2020 9 1181 10.3390/cells9051181 32397491 5. Harly C. Guillaume Y. Nedellec S. Peigne C.M. Monkkonen H. Monkkonen J. Li J. Kuball J. Adams E.J. Netzer S. Key implication of CD277/butyrophilin-3 (BTN3A) in cellular stress sensing by a major human gammadelta T-cell subset Blood 2012 120 269 279 10.1182/blood-2012-05-430470 22767497 6. Rigau M. Ostrouska S. Fulford T.S. Johnson D.N. Woods K. Ruan Z. McWilliam H.E.G. Hudson C. Tutuka C. Wheatley A.K. Butyrophilin 2A1 is essential for phosphoantigen reactivity by γδ T cells Science 2020 367 eaay5516 10.1126/science.aay5516 31919129 7. Herrmann T. Fichtner A.S. Karunakaran M.M. An Update on the Molecular Basis of Phosphoantigen Recognition by Vγ9Vδ2 T Cells Cells 2020 9 1433 10.3390/cells9061433 8. Roelofs A.J. Jauhiainen M. Monkkonen H. Rogers M.J. Monkkonen J. Thompson K. Peripheral blood monocytes are responsible for gammadelta T cell activation induced by zoledronic acid through accumulation of IPP/DMAPP Br. J. Haematol. 2009 144 245 250 10.1111/j.1365-2141.2008.07435.x 19016713 9. Gober H.J. Kistowska M. Angman L. Jeno P. Mori L. De Libero G. Human T cell receptor gammadelta cells recognize endogenous mevalonate metabolites in tumor cells J. Exp. Med. 2003 197 163 168 10.1084/jem.20021500 12538656 10. Silva-Santos B. Mensurado S. Coffelt S.B. γδ T cells: Pleiotropic immune effectors with therapeutic potential in cancer Nat. Rev. Cancer 2019 19 392 404 10.1038/s41568-019-0153-5 31209264 11. Sebestyen Z. Prinz I. Déchanet-Merville J. Silva-Santos B. Kuball J. Translating gammadelta (γδ) T cells and their receptors into cancer cell therapies Nat. Rev. Drug Discov. 2020 19 169 184 10.1038/s41573-019-0038-z 31492944 12. Kabelitz D. Serrano R. Kouakanou L. Peters C. Kalyan S. Cancer immunotherapy with γδ T cells: Many paths ahead of us Cell Mol. Immunol. 2020 17 925 939 10.1038/s41423-020-0504-x 32699351 13. Fleming C. Morrissey S. Cai Y. Yan J. γδ T Cells: Unexpected Regulators of Cancer Development and Progression Trends Cancer 2017 3 561 570 10.1016/j.trecan.2017.06.003 28780933 14. Peters C. Kabelitz D. Wesch D. Regulatory functions of γδ T cells Cell Mol. Life Sci. 2018 75 2125 2135 10.1007/s00018-018-2788-x 29520421 15. Zarobkiewicz M.K. Kowalska W. Roliński J. Bojarska-Junak A.A. γδ T lymphocytes in the pathogenesis of multiple sclerosis and experimental autoimmune encephalomyelitis J. Neuroimmunol. 2019 330 67 73 10.1016/j.jneuroim.2019.02.009 30831520 16. Bank I. The Role of Gamma Delta T Cells in Autoimmune Rheumatic Diseases Cells 2020 9 462 10.3390/cells9020462 32085540 17. Höck A.D. Review: Vitamin D3 deficiency results in dysfunctions of immunity with severe fatigue and depression in a variety of diseases In Vivo 2014 28 133 145 24425848 18. Charoenngam N. Holick M.F. Immunologic Effects of Vitamin D on Human Health and Disease Nutrients 2020 12 2097 10.3390/nu12072097 32679784 19. Palmer M.T. Lee Y.K. Maynard C.L. Oliver J.R. Bikle D.D. Jetten A.M. Weaver C.T. Lineage-specific effects of 1,25-dihydroxyvitamin D(3) on the development of effector CD4 T cells J. Biol. Chem. 2011 286 997 1004 10.1074/jbc.M110.163790 21047796 20. Urry Z. Chambers E.S. Xystrakis E. Dimeloe S. Richards D.F. Gabryšová L. Christensen J. Gupta A. Saglani S. Bush A. The role of 1α,25-dihydroxyvitamin D3 and cytokines in the promotion of distinct Foxp3+ and IL-10+ CD4+ T cells Eur. J. Immunol. 2012 42 2697 2708 10.1002/eji.201242370 22903229 21. Martens P.J. Gysemans C. Verstuyf A. Mathieu A.C. Vitamin D’s Effect on Immune Function Nutrients 2020 12 1248 10.3390/nu12051248 32353972 22. Maboshe W. Macdonald H.M. Wassall H. Fraser W.D. Tang J.C.Y. Fielding S. Barker R.N. Vickers M.A. Ormerod A. Thies F. Low-Dose Vitamin D3 Supplementation Does Not Affect Natural Regulatory T Cell Population but Attenuates Seasonal Changes in T Cell-Produced IFN-γ: Results From the D-SIRe2 Randomized Controlled Trial Front. Immunol. 2021 12 623087 10.3389/fimmu.2021.623087 34262557 23. Chauss D. Freiwald T. McGregor R. Yan B. Wang L. Nova-Lamperti E. Kumar D. Zhang Z. Teague H. West E.E. Autocrine vitamin D signaling switches off pro-inflammatory programs of TH1 cells Nat. Immunol. 2022 23 62 74 10.1038/s41590-021-01080-3 34764490 24. Murdaca G. Tonacci A. Negrini S. Greco M. Borro M. Puppo F. Gangemi S. Emerging role of vitamin D in autoimmune diseases: An update on evidence and therapeutic implications Autoimmun. Rev. 2019 18 102350 10.1016/j.autrev.2019.102350 31323357 25. Nair R. Maseeh A. Vitamin D: The “sunshine” vitamin J. Pharmacol. Pharmacother. 2012 3 118 126 10.4103/0976-500X.95506 22629085 26. Wacker M. Holick M.F. Sunlight and Vitamin D: A global perspective for health Dermatoendocrinology 2013 5 51 108 10.4161/derm.24494 24494042 27. Khoo A.L. Koenen H.J. Chai L.Y. Sweep F.C. Netea M.G. van der Ven A.J. Joosten I. Seasonal variation in vitamin D₃ levels is paralleled by changes in the peripheral blood human T cell compartment PLoS ONE 2012 7 e29250 10.1371/journal.pone.0029250 22235276 28. Chen L. Cencioni M.T. Angelini D.F. Borsellino G. Battistini L. Brosnan C.F. Transcriptional profiling of gamma delta T cells identifies a role for vitamin D in the immunoregulation of the V gamma 9V delta 2 response to phosphate-containing ligands J. Immunol. 2005 174 6144 6152 10.4049/jimmunol.174.10.6144 15879110 29. Munns C.F. Shaw N. Kiely M. Specker B.L. Thacher T.D. Ozono K. Michigami T. Tiosano D. Mughal M.Z. Mäkitie O. Global Consensus Recommendations on Prevention and Management of Nutritional Rickets J. Clin. Endocrinol. Metab. 2016 101 394 415 10.1210/jc.2015-2175 26745253 30. Janssen O. Wesselborg S. Heckl-Ostreicher B. Pechhold K. Bender A. Schondelmaier S. Moldenhauer G. Kabelitz D. T cell receptor/CD3-signaling induces death by apoptosis in human T cell receptor gamma delta + T cells J. Immunol. 1991 146 35 39 1824593 31. Pechhold K. Pohl T. Kabelitz D. Rapid quantification of lymphocyte subsets in heterogeneous cell populations by flow cytometry Cytometry 1994 16 152 159 10.1002/cyto.990160209 7924684 32. Serrano R. Wesch D. Kabelitz D. Activation of Human γδ T Cells: Modulation by Toll-Like Receptor 8 Ligands and Role of Monocytes Cells 2020 9 713 Erratum in Cells 2020, 9, 1977 10.3390/cells9030713 32183240 33. Sipos B. Möser S. Kalthoff H. Török V. Löhr M. Klöppel G. A comprehensive characterization of pancreatic ductal carcinoma cell lines: Towards the establishment of an in vitro research platform Virchows. Arch. 2003 442 444 452 10.1007/s00428-003-0784-4 12692724 34. Oberg H.H. Peters C. Kabelitz D. Wesch D. Real-time cell analysis (RTCA) to measure killer cell activity against adherent tumor cells in vitro Methods Enzymol. 2020 631 429 441 10.1016/bs.mie.2019.07.020 31948561 35. Serrano R. Lettau M. Zarobkiewicz M. Wesch D. Peters C. Kabelitz D. Stimulatory and inhibitory activity of STING ligands on tumor-reactive human gamma/delta T cells Oncoimmunology 2022 11 2030021 10.1080/2162402X.2022.2030021 35127253 36. Carr E.J. Dooley J. Garcia-Perez J.E. Lagou V. Lee J.C. Wouters C. Meyts I. Goris A. Boeckxstaens G. Linterman M.A. The cellular composition of the human immune system is shaped by age and cohabitation Nat. Immunol. 2016 17 461 468 Erratum in: Nat Immunol. 2021, 22, 254 10.1038/ni.3371 26878114 37. Müller L. Di Benedetto S. Pawelec G. The Immune System and Its Dysregulation with Aging Subcell Biochem. 2019 91 21 43 10.1007/978-981-13-3681-2_2 30888648 38. Picarda G. Benedict C.A. Cytomegalovirus: Shape-Shifting the Immune System J. Immunol. 2018 200 3881 3889 10.4049/jimmunol.1800171 29866770 39. Goldinger A. Shakhbazov K. Henders A.K. McRae A.F. Montgomery G.W. Powell J.E. Seasonal effects on gene expression PLoS ONE 2015 10 e0126995 10.1371/journal.pone.0126995 26023781 40. Lakshmikanth T. Muhammad S.A. Olin A. Chen Y. Mikes J. Fagerberg L. Gummesson A. Bergström G. Uhlen M. Brodin P. Human Immune System Variation during 1 Year Cell Rep. 2020 32 107923 10.1016/j.celrep.2020.107923 32697987 41. Ter Horst R. Jaeger M. van de Wijer L. van der Heijden W.A. Janssen A.M.W. Smeekens S.P. Brouwer M.A.E. van Cranenbroek B. Aguirre-Gamboa R. Netea-Maier R.T. Seasonal and Nonseasonal Longitudinal Variation of Immune Function J. Immunol. 2021 207 696 708 10.4049/jimmunol.2000133 34261668 42. Hart P.H. Norval M. More Than Effects in Skin: Ultraviolet Radiation-Induced Changes in Immune Cells in Human Blood Front. Immunol. 2021 12 694086 10.3389/fimmu.2021.694086 34177957 43. Hanel A. Malmberg H.R. Carlberg C. Genome-wide effects of chromatin on vitamin D signaling J. Mol. Endocrinol. 2020 64 R45 R56 10.1530/JME-19-0246 32229699 44. Klingberg E. Oleröd G. Konar J. Petzold M. Hammarsten O. Seasonal variations in serum 25-hydroxy vitamin D levels in a Swedish cohort Endocrine 2015 49 800 808 10.1007/s12020-015-0548-3 25681052 45. Ao T. Kikuta J. Ishii M. The Effects of Vitamin D on Immune System and Inflammatory Diseases Biomolecules 2021 11 1624 10.3390/biom11111624 34827621 46. Correale J. Ysrraelit M.C. Gaitán M.I. Immunomodulatory effects of Vitamin D in multiple sclerosis Brain 2009 132 Pt 5 1146 1160 10.1093/brain/awp033 19321461 47. Mohan M. Cherian J.J. Sharma A. Exploring links between vitamin D deficiency and COVID-19 PLoS Pathog. 2020 16 e1008874 10.1371/journal.ppat.1008874 32946517 48. Calton E.K. Keane K.N. Newsholme P. Zhao Y. Soares M.J. The impact of cholecalciferol supplementation on the systemic inflammatory profile: A systematic review and meta-analysis of high-quality randomized controlled trials Eur. J. Clin. Nutr. 2017 71 931 943 10.1038/ejcn.2017.67 28488684 49. Rao Z. Chen X. Wu J. Xiao M. Zhang J. Wang B. Fang L. Zhang H. Wang X. Yang S. Vitamin D Receptor Inhibits NLRP3 Activation by Impeding Its BRCC3-Mediated Deubiquitination Front. Immunol. 2019 10 2783 10.3389/fimmu.2019.02783 31866999 50. Navarro-Barriuso J. Mansilla M.J. Quirant-Sánchez B. Teniente-Serra A. Ramo-Tello C. Martínez-Cáceres E.M. Vitamin D3-Induced Tolerogenic Dendritic Cells Modulate the Transcriptomic Profile of T CD4+ Cells Towards a Functional Hyporesponsiveness Front. Immunol. 2021 11 599623 10.3389/fimmu.2020.599623 33552054 51. Català-Moll F. Ferreté-Bonastre A.G. Godoy-Tena G. Morante-Palacios O. Ciudad L. Barberà L. Fondelli F. Martínez-Cáceres E.M. Rodríguez-Ubreva J. Li T. Vitamin D receptor, STAT3, and TET2 cooperate to establish tolerogenesis Cell Rep. 2022 38 110244 10.1016/j.celrep.2021.110244 35045292 52. Kang S.W. Kim S.H. Lee N. Lee W.W. Hwang K.A. Shin M.S. Lee S.H. Kim W.U. Kang I. 1,25-Dihyroxyvitamin D3 promotes FOXP3 expression via binding to vitamin D response elements in its conserved noncoding sequence region J. Immunol. 2012 188 5276 5282 10.4049/jimmunol.1101211 22529297 53. Chambers E.S. Suwannasaen D. Mann E.H. Urry Z. Richards D.F. Lertmemongkolchai G. Hawrylowicz C.M. 1α,25-dihydroxyvitamin D3 in combination with transforming growth factor-β increases the frequency of Foxp3⁺ regulatory T cells through preferential expansion and usage of interleukin-2 Immunology 2014 143 52 60 10.1111/imm.12289 24673126 54. Morales-Tirado V. Wichlan D.G. Leimig T.E. Street S.E. Kasow K.A. Riberdy J.M. 1α,25-dihydroxyvitamin D3 (vitamin D3) catalyzes suppressive activity on human natural regulatory T cells, uniquely modulates cell cycle progression, and augments FOXP3 Clin. Immunol. 2011 138 212 221 10.1016/j.clim.2010.11.003 21167785 55. Khoo A.L. Joosten I. Michels M. Woestenenk R. Preijers F. He X.H. Netea M.G. van der Ven A.J. Koenen H.J. 1,25-Dihydroxyvitamin D3 inhibits proliferation but not the suppressive function of regulatory T cells in the absence of antigen-presenting cells Immunology 2011 134 459 468 10.1111/j.1365-2567.2011.03507.x 22044285 56. Zhou Q. Qin S. Zhang J. Zhon L. Pen Z. Xing T. 1,25(OH)2D3 induces regulatory T cell differentiation by influencing the VDR/PLC-γ1/TGF-β1/pathway Mol. Immunol. 2017 91 156 164 10.1016/j.molimm.2017.09.006 28926770 57. Moore J.R. Hubler S.L. Nelson C.D. Nashold F.E. Spanier J.A. Hayes C.E. 1,25-Dihydroxyvitamin D3 increases the methionine cycle, CD4+ T cell DNA methylation and Helios+Foxp3+ T regulatory cells to reverse autoimmune neurodegenerative disease J. Neuroimmunol. 2018 324 100 114 10.1016/j.jneuroim.2018.09.008 30267995 58. Mann E.H. Chambers E.S. Chen Y.H. Richards D.F. Hawrylowicz C.M. 1α,25-dihydroxyvitamin D3 acts via transforming growth factor-β to up-regulate expression of immunosuppressive CD73 on human CD4+ Foxp3- T cells Immunology 2015 146 423 431 10.1111/imm.12519 26251265 59. Fawaz L. Mrad M.F. Kazan J.M. Sayegh S. Akika R. Khoury S.J. Comparative effect of 25(OH)D3 and 1,25(OH)2D3 on Th17 cell differentiation Clin. Immunol. 2016 166–167 59 71 10.1016/j.clim.2016.02.011 60. Ribeiro V.R. Romao-Veiga M. Nunes P.R. Matias M.L. Peracoli J.C. Peracoli M.T.S. Vitamin D modulates the transcription factors of T cell subsets to anti-inflammatory and regulatory profiles in preeclampsia Int. Immunopharmacol. 2021 101 Pt B 108366 10.1016/j.intimp.2021.108366 34810124 61. Ribeiro V.R. Romao-Veiga M. Nunes P.R. de Oliveira L.R.C. Romagnoli G.G. Peracoli J.C. Peracoli M.T.S. Immunomodulatory effect of vitamin D on the STATs and transcription factors of CD4+ T cell subsets in pregnant women with preeclampsia Clin. Immunol. 2022 234 108917 10.1016/j.clim.2021.108917 34973430 62. Caron J. Ridgley L.A. Bodman-Smith M. How to Train Your Dragon: Harnessing Gamma Delta T Cells Antiviral Functions and Trained Immunity in a Pandemic Era Front. Immunol. 2021 12 666983 10.3389/fimmu.2021.666983 33854516 63. Janssen A. van Diest E. Vyborova A. Schrier L. Bruns A. Sebestyen Z. Straetemans T. de Witte M. Kuball J. The Role of γδ T Cells as a Line of Defense in Viral Infections after Allogeneic Stem Cell Transplantation: Opportunities and Challenges Viruses 2022 14 117 10.3390/v14010117 35062321 64. Xu Y. Xiang Z. Alnaggar M. Kouakanou L. Li J. He J. Yang J. Hu Y. Chen Y. Lin L. Allogeneic Vγ9Vδ2 T-cell immunotherapy exhibits promising clinical safety and prolongs the survival of patients with late-stage lung or liver cancer Cell Mol. Immunol. 2021 18 427 439 10.1038/s41423-020-0515-7 32939032 65. De Santis M. Cavaciocchi F. Ceribelli A. Crotti C. Generali E. Fabbriciani G. Selmi C. Massarotti M. Gamma-delta T lymphocytes and 25-hydroxy vitamin D levels as key factors in autoimmunity and inflammation: The case of zoledronic acid-induced acute phase reaction Lupus 2015 24 442 447 10.1177/0961203314559633 25801887 66. Dieli F. Vermijlen D. Fulfaro F. Caccamo N. Meraviglia S. Cicero G. Roberts A. Buccheri S. D’Asaro M. Gebbia N. Targeting human {gamma}delta} T cells with zoledronate and interleukin-2 for immunotherapy of hormone-refractory prostate cancer Cancer Res. 2007 67 7450 7457 10.1158/0008-5472.CAN-07-0199 17671215 67. Kalyan S. Quabius E.S. Wiltfang J. Mönig H. Kabelitz D. Can peripheral blood γδ T cells predict osteonecrosis of the jaw? An immunological perspective on the adverse drug effects of aminobisphosphonate therapy J. Bone Miner. Res. 2013 28 728 735 10.1002/jbmr.1769 22991330 68. García-Ortiz A. Serrador J.M. Nitric Oxide Signaling in T Cell-Mediated Immunity Trends Mol. Med. 2018 24 412 427 10.1016/j.molmed.2018.02.002 29519621 69. Navasardyan I. Bonavida B. Regulation of T Cells in Cancer by Nitric Oxide Cells 2021 10 2655 10.3390/cells10102655 34685635 70. Holliman G. Lowe D. Cohen H. Felton S. Raj K. Ultraviolet Radiation-Induced Production of Nitric Oxide:A multi-cell and multi-donor analysis Sci. Rep. 2017 7 11105 10.1038/s41598-017-11567-5 28894213 71. Barolet A.C. Litvinov I.V. Barolet D. Light-induced nitric oxide release in the skin beyond UVA and blue light: Red & near-infrared wavelengths Nitric. Oxide. 2021 117 16 25 10.1016/j.niox.2021.09.003 34536586 72. Sheikh V. Kasapoglu P. Zamani A. Basiri Z. Tahamoli-Roudsari A. Alahgholi-Hajibehzad M. Vitamin D3 inhibits the proliferation of T helper cells, downregulate CD4+ T cell cytokines and upregulate inhibitory markers Hum. Immunol. 2018 79 439 445 10.1016/j.humimm.2018.03.001 29522785 73. Bianchi N. Emming S. Zecca C. Monticelli S. Vitamin D and IFN-β Modulate the Inflammatory Gene Expression Program of Primary Human T Lymphocytes Front. Immunol. 2020 11 566781 10.3389/fimmu.2020.566781 33343562 74. Vyas S.P. Hansda A.K. Kaplan M.H. Goswami R. Calcitriol Regulates the Differentiation of IL-9-Secreting Th9 Cells by Modulating the Transcription Factor PU.1 J. Immunol. 2020 204 1201 1213 10.4049/jimmunol.1901205 31932499 75. Zhou L. Wang J. Li J. Li T. Chen Y. June R.R. Zheng S.G. 1,25-Dihydroxyvitamin D3 Ameliorates Collagen-Induced Arthritis via Suppression of Th17 Cells Through miR-124 Mediated Inhibition of IL-6 Signaling Front. Immunol. 2019 10 178 10.3389/fimmu.2019.00178 30792721 76. Nerdal P.T. Peters C. Oberg H.H. Zlatev H. Lettau M. Quabius E.S. Sousa S. Gonnermann D. Auriola S. Olive D. Butyrophilin 3A/CD277-Dependent Activation of Human γδ T Cells: Accessory Cell Capacity of Distinct Leukocyte Populations J. Immunol. 2016 197 3059 3068 10.4049/jimmunol.1600913 27619996 77. Kongsbak M. von Essen M.R. Boding L. Levring T.B. Schjerling P. Lauritsen J.P. Woetmann A. Ødum N. Bonefeld C.M. Geisler C. Vitamin D up-regulates the vitamin D receptor by protecting it from proteasomal degradation in human CD4+ T cells PLoS ONE 2014 9 e96695 10.1371/journal.pone.0096695 24792400 78. Dokouhaki P. Schuh N.W. Joe B. Allen C.A. Der S.D. Tsao M.S. Zhang L. NKG2D regulates production of soluble TRAIL by ex vivo expanded human γδ T cells Eur. J. Immunol. 2013 43 3175 3182 10.1002/eji.201243150 24019170 79. Li X. Lu H. Gu Y. Zhang X. Zhang G. Shi T. Chen W. Tim-3 suppresses the killing effect of Vγ9Vδ2 T cells on colon cancer cells by reducing perforin and granzyme B expression Exp. Cell Res. 2020 386 111719 10.1016/j.yexcr.2019.111719 31726050 80. Lettau M. Dietz M. Dohmen K. Leippe M. Kabelitz D. Janssen O. Granulysin species segregate to different lysosome-related effector vesicles (LREV) and get mobilized by either classical or non-classical degranulation Mol. Immunol. 2019 107 44 53 10.1016/j.molimm.2018.12.031 30658247 81. Afsal K. Selvaraj P. Harishankar M. 1, 25-dihydroxyvitamin D3 downregulates cytotoxic effector response in pulmonary tuberculosis Int. Immunopharmacol. 2018 62 251 260 10.1016/j.intimp.2018.07.018 30032050 82. Slominski A.T. Kim T.K. Hobrath J.V. Oak A.S.W. Tang E.K.Y. Tieu E.W. Li W. Tuckey R.C. Jetten A.M. Endogenously produced nonclassical vitamin D hydroxy-metabolites act as “biased” agonists on VDR and inverse agonists on RORα and RORγ J. Steroid Biochem. Mol. Biol. 2017 173 42 56 10.1016/j.jsbmb.2016.09.024 27693422 83. Slominski A.T. Kim T.K. Qayyum S. Song Y. Janjetovic Z. Oak A.S.W. Slominski R.M. Raman C. Stefan J. Mier-Aguilar C.A. Vitamin D and lumisterol derivatives can act on liver X receptors (LXRs) Sci. Rep. 2021 11 8002 10.1038/s41598-021-87061-w 33850196 84. Prietl B. Treiber G. Mader J.K. Hoeller E. Wolf M. Pilz S. Graninger W.B. Obermayer-Pietsch B.M. Pieber T.R. High-dose cholecalciferol supplementation significantly increases peripheral CD4⁺ Tregs in healthy adults without negatively affecting the frequency of other immune cells Eur. J. Nutr. 2014 53 751 759 10.1007/s00394-013-0579-6 23999998 85. Gorchs L. Ahmed S. Mayer C. Knauf A. Fernández Moro C. Svensson M. Heuchel R. Rangelova E. Bergman P. Kaipe H. The vitamin D analogue calcipotriol promotes an anti-tumorigenic phenotype of human pancreatic CAFs but reduces T cell mediated immunity Sci. Rep. 2020 10 17444 10.1038/s41598-020-74368-3 33060625 86. Muralidhar S. Filia A. Nsengimana J. Poźniak J. O’Shea S.J. Diaz J.M. Harland M. Randerson-Moor J.A. Reichrath J. Laye J.P. Vitamin D-VDR Signaling Inhibits Wnt/β-Catenin-Mediated Melanoma Progression and Promotes Antitumor Immunity Cancer Res. 2019 79 5986 5998 10.1158/0008-5472.CAN-18-3927 31690667 87. Wu X. Hu W. Lu L. Zhao Y. Zhou Y. Xiao Z. Zhang L. Zhang H. Li X. Li W. Repurposing vitamin D for treatment of human malignancies via targeting tumor microenvironment Acta Pharm. Sin. B 2019 9 203 219 10.1016/j.apsb.2018.09.002 30972274

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093533 sensors-22-03533 Article Single Image Video Prediction with Auto-Regressive GANs Huang Jiahui 1 Chia Yew Ken 2 https://orcid.org/0000-0003-4647-8539 Yu Samson 2 Yee Kevin 2 https://orcid.org/0000-0001-8992-5648 Küster Dennis 3 https://orcid.org/0000-0003-1894-2517 Krumhuber Eva G. 4* https://orcid.org/0000-0001-8607-1640 Herremans Dorien 2 https://orcid.org/0000-0002-6439-8076 Roig Gemma 5 Szwoch Mariusz Academic Editor 1 Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; gabrie20@cs.ubc.ca 2 Information Systems Technology and Design (ISTD), Singapore University of Technology and Design, Singapore 487372, Singapore; chiayewken@gmail.com (Y.K.C.); samyubj@gmail.com (S.Y.); kevin-yee@outlook.com (K.Y.); dorien_herremans@sutd.edu.sg (D.H.) 3 Cognitive Systems Lab, Department of Mathematics and Computer Science, University of Bremen, 28359 Bremen, Germany; kuester@uni-bremen.de 4 Department of Experimental Psychology, University College London, 26 Bedford Way, London WC1H 0AP, UK 5 Department of Computer Science, Goethe University Frankfurt, Robert-Meyer-Str. 11-15, 60325 Frankfurt, Germany; roig@cs.uni-frankfurt.de * Correspondence: e.krumhuber@ucl.ac.uk 06 5 2022 5 2022 22 9 353301 3 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In this paper, we introduce an approach for future frames prediction based on a single input image. Our method is able to generate an entire video sequence based on the information contained in the input frame. We adopt an autoregressive approach in our generation process, i.e., the output from each time step is fed as the input to the next step. Unlike other video prediction methods that use “one shot” generation, our method is able to preserve much more details from the input image, while also capturing the critical pixel-level changes between the frames. We overcome the problem of generation quality degradation by introducing a “complementary mask” module in our architecture, and we show that this allows the model to only focus on the generation of the pixels that need to be changed, and to reuse those that should remain static from its previous frame. We empirically validate our methods against various video prediction models on the UT Dallas Dataset, and show that our approach is able to generate high quality realistic video sequences from one static input image. In addition, we also validate the robustness of our method by testing a pre-trained model on the unseen ADFES facial expression dataset. We also provide qualitative results of our model tested on a human action dataset: The Weizmann Action database. video prediction autoregressive GANs emotion generation Singapore Ministry of EducationMOE2018-T2-2-161 This project was partially supported by the Singapore Ministry of Education, Grant no. MOE2018-T2-2-161. ==== Body pmc1. Introduction Recent advancements in generative neural networks have greatly improved the quality of image generation [1,2,3,4]. In the domain of video generation, however, the problem becomes much more intricate because the temporal information is introduced as another dimension. Most results produced by the existing methods are still not satisfactory to human eyes [5,6,7,8]. Our proposed approach focuses on a specific task in the domain of video generation: generating a sequence of frames based on the information provided by a single still image. We name this task “Single image video prediction”. Many of the existing methods for video prediction take multiple frames as the input to their models, and then extrapolate the future frames by observing the trend of pixel movements within those input frames [9,10]. We view single image video prediction as a much harder task because no temporal information is provided by the input, and the model has to take into account that movements of the pixels predicted in the future frames should adhere to a timeline. We show that this ability to predict a “movement-based timeline” can be learned by our model during the training phase under certain conditions when we detail our proposed model in Section 2.1. While single image video prediction is a significantly harder task, we believe it has a wide range of applications. One example is turning static images into vivid GIFs, or making clips of different facial expressions based on the same input image. Moreover, the generated results could be used in perception studies to examine whether the animated GIFs enhance emotion perception of otherwise static images and, e.g., websites. Eventually such a tool might be used to better understand how humans may engage in a similar process of extrapolating single images in interactions. For instance, video sequences might be generated on the fly, and depending on user inputs, but in a more experimentally controlled manner than through other means, such as pre-recorded videos. In this paper, we introduce an autoregressive approach to the single image video prediction problem. As illustrated in Figure 1, the model will constantly produce one frame at a time based on the frame generated by the previous time step, and this process is initiated and conditioned with the input image as the starter frame. This approach has several advantages: Firstly, the information is passed smoothly between the frames. Secondly, the model is able to generate videos with arbitrary lengths. Lastly, because the generation process is sequential, the resulting videos show a smooth trajectory of changes from frame to frame, thus following a continuous and consistent timeline. However, this generation process could have a significant drawback: cumulative quality degradation. As the generation process goes on, noises and undesirable artifacts accumulate, and as a result, the generation quality suffers incrementally over time. To overcome this problem, we introduce a mechanism that we refer to as complementary masking into our model. This mechanism learns to filter out the pixels that should remain static in the generation process, and lets the model focus on the pixels that need to be changed. We show in Section 3.3 that our complementary masking mechanism is very effective when dealing with cumulative quality degradation. We conduct extensive experiments to validate our method against other competing approaches, and show that our method is of superior quality. In addition, we demonstrate the robustness of our model by testing a pre-trained model on an unseen facial expression dataset. We also conduct experiments on an action dataset to show the generalization of our model to another video domain. 2. Materials and Methods 2.1. Proposed Video Autoregressive GAN Here, we introduce the notation that we use in the rest of the paper, as well as the components of our proposed autoregressive generative network for single image video prediction. 2.1.1. Autoregressive Generation Our main goal is to generate a sequence of T video frames, denoted as V′:={ft′}t=1T, given an input image f0∈RH×W×3 as its starter frame. The generation process is autoregressive, meaning for each time step, the input to the generator network is always the output of the previous time step. The algorithm behaves slightly different in the training and testing phases. During the training phase, the ground truth frame ft is taken from the training video V:={ft}t=0T at time step t, the losses for both generator G and discriminator D networks are calculated based on the true ft+1 and generated ft+1′. During the testing phase, the only input to the process is f0, and the rest of the frames {ft′}t=1T are all generated based on previous generations. To reduce the discrepancy between training and testing, we propose to perform scheduled sampling (SS) [11] in the later epochs of the training phase. After some number of initial guiding epochs Eg, the model randomly switches its input between the ground truth current frame ft and the synthesised current frame ft′ produced by the previous time step, with a sampling rate r. In this way, we can increase the model’s exposure to its own generations, and bridge the behavioral gap between training and testing phases. The process is summarized in the following algorithm. 2.1.2. The Generator Network As discussed in the introduction, quality degradation poses a substantial problem in a sequential autoregressive generation process, because noises and undesirable artifacts will accumulate as the generation process goes on. Inspired by [5], we adopt a two-stream architecture to form a complementary masking mechanism to avoid this problem. The formulation of our output is as follows:(1) G(ft)=m(ft)⊙d(ft)+[1−m(ft)]⊙ft, where G represents the generator component of the GAN model, m(·) is a function that outputs a soft mask with values between 0 and 1 (0≤m(ft)≤1), d(·) is a function whose output can be viewed as a difference map between ft and ft+1, and ⊙ is element-wise multiplication. The intuition behind Equation (1) is that when composing the next frame, some pixels should remain static compared to the current frame, which we call static pixels; while the rest of the pixels should be changed to follow the motion of the subject in the video, which we call variable pixels. Our formulation enforces a complementary relation such that the mask for static pixels and the mask for variable pixels sum up to 1. This simulates the formation of a complete frame, by adding both static and variable pixels together. We illustrate the autoregressive generation with the complementary mask in Figure 2a,b, respectively. In our ablation studies, we show that the complementary mask module helps the model to focus on the variable pixels, which in turn helps to reduce quality degradation. In our setup, we use a ResNet [12] based architecture for m(·), and a U-Net [13] based architecture for g(·). 2.1.3. The Discriminator Network We use two discriminators in our autoregressive GAN architecture, the global and the local discriminator. The global discriminator Dg overviews the entire frame and distinguishes between the ground truth next frame and its counterpart’s generation. (2) Dg(ft,ft+1∨ft+1′)=real∨fake. The local discriminator Dl puts more attention to the variable pixels. Here, we reuse the mask generated in the generator to eliminate static pixels: by subtracting ft on both sides of Equation (1), we get:(3) fvar,t+1′=m(ft)⊙(d(ft)−ft). We also subtract ft from the real ft+1 to get the ground truth variable pixels:(4) fvar,t+1=ft+1−ft. Finally, our second discriminator Df can be formulated as:(5) Dl(ft,fvar,t+1∨fvar,t+1′)=real∨fake. We illustrate the discriminator network in Figure 2c. Unlike other methods [14,15] that employ a predefined region (mouth region cropping, eye region cropping, etc.) for the local discriminator, we can benefit from the mask learned by the generator and automatically crop out the regions of interest. Thus, we argue that our design for the local discriminator is more flexible and generalizable to different domains and datasets, as we show in the experimental section. In our setup, we use Patch-GAN [2] for both our global and local discriminators. 2.1.4. Joint Objective Function We propose an objective function that consist of the sum of an adversarial objective function, a reconstruction loss and the mask sparsity loss. Since we have two discriminators in our GAN architecture, the adversarial objective can be written as: (6) LGAN(G,Dg,Dl)=Eft+1[logDg(ft,ft+1)]+Eft+1[logDl(ft,ft+1)]+Eft[log(1−Dg(ft,G(ft))]+Eft[log(1−Dl(ft,G(ft))], where G tries to minimize this objective against its adversaries Dg and Dl that try to maximize it:(7) G*=argminGmaxDg,DlLGAN(G,Dg,Dl). We also add a reconstruction loss because it is proven to be effective for improving the quality of the generated samples with GANs. Here, we combine the traditional L1 distance with our GAN objective. While the discriminators’ task remains unchanged, the generator should produce outputs that are as close to the ground truth as possible in an L1 sense:(8) LL1(G)=Eft∥ft+1−G(ft)∥1. Following [5], we found that adding a sparsity prior on the mask can encourage the generator to reuse as many pixels from its input as possible, thus reducing noise accumulation during the generation process:(9) LMS(G)=λ∥m(ft)∥1, where λ here can be interpreted as the strength of this prior. A larger λ will encourage the network to reuse more pixels from its input. We set λ=0.2 in our experiments. Similar to the reconstruction loss, the mask sparsity loss only affects the generator. To sum up, our final objective to train the network can be written as:(10) G*=argminGmaxDg,Dl[LGAN(G,Dg,Dl)+LL1(G)+LMS(G)]. 2.2. Implementation As discussed above, we have two streams in our generator G: a function m(·) that outputs a mask, and a function d(·) that generates the difference map. For m(·), we use a ResNet [12] based architecture with two downsampling/upsampling layers scattered between 9 residual blocks, and we use the tanh function to rescale the output to [0,1]. For d(·), we employ an 8-layer U-Net [13] with skip connections to enable the flow of both low-level and high-level features. We use the PatchGAN [2] discriminator with 70×70 patch size for both the global and local discriminators. We set the video batch size to 1 and sample 10 frames from each individual clip for training. We use the Adam [16] optimizer and set the learning rate to 0.0002, the learning rate linearly decays to 0 starting from the half of the total epochs. The scheduled sampling process starts at the half of the total epochs in the training. We set our initial sampling rate to 0.1 and increase this by 0.1 for every 20 epochs. All input frames are resized to 256×256 and the values normalized to [−1,1]. We train separate models for each emotion, and we do not have classifiers for emotion classification. The same approach is used for human actions, in which we have one model per action. We will make the code publicly available upon acceptance of the paper. 2.3. Datasets 2.3.1. Facial Expression Generation We require each training sample to contain a single facial expression that begins with a neutral expression, and reaches a single apex of expression intensity. We use the UT Dallas dataset [17] as our base dataset. Considering that this dataset holds a different number of samples for different facial expressions, we selected 4 expression classes with the largest number of videos: Happiness (316 videos), Disgust (254 videos), Surprise (192 videos), and Sadness (60 videos). We trim these videos into clips between 1–2 s to remove any idling frames. Following this, we sample 10 frames for each clip and resize them to 256×256 pixels. For each emotion class, we take 20 different subjects for the testing split, and the remainder for the training split. 2.3.2. Human Actions Generation We use the Weizmann Action database [18], and selected 4 different actions (“one-hand wave”, “two-hands wave”, “skip” and “jump”) to train and test our model. Each action category contains 9 videos of different performers, we trim the videos to make sure there is no repetitions. We randomly select 7 subjects for training and 2 subjects for testing. All frames are resized to 64×64 in size. Due to the small sample size, we did not conduct a quantitative evaluation on this dataset. Instead, we provide visual results in Figure 3, to showcase the generalizability of our method to different video domains. 3. Results In this section, we provide detailed analysis and results of our model on different perspectives, including an ablation study on the effects of different components of our model design, and comparison to other methods in the literature. 3.1. Quantitative Results For quantitative comparisons, we use Frechet Inception Distance (FID, a lower value indicates better quality) [19] and the Inception Score (IS, a higher value indicates better quality) [20] to measure perceptual quality and diversity. On Table 1, we compare our method against two other temporal-based video generation models: ConvLSTM [6] and the flow-grounded spatial-temporal (FGST) method [7], with the ground truth frames results (first row) as reference. We also report results generated by non-temporal-based method AffineGAN [14] for comparison. All models are trained and tested on the “Happiness” class in the UT Dallas dataset. We observe that our method is considerably better than the other two temporal-based models on both evaluation metrics, and its performance is comparable to that of the AffineGAN. Notice that the AffineGAN model is unaware of the temporal information and requires additional guidance (the expression intensity score) in the generation process. The model has to scatter the expression intensity along the timeline, and then generate each frame independently to produce the final clip, thus, it should be categorized as an image-translation task, which is an easier task compared to ours. 3.2. Qualitative Results Figure 4 shows the visual comparisons of our method and three other temporal-based video generation models: ConvLSTM, FGST (temporal-based) and AffineGAN (non-temporal-based), with the ground truth (GT) frames in the first row. All models are trained on the “Happiness” class with the same number of epochs, and we show our results on the test set. As shown in the figure, among the temporal-based methods, our model is able to produce what appears to be the most realistic frames with consistent continuity. We also compare our results with the non-temporal-based method AffineGAN in the last row. As discussed above, the generation process in the AffineGAN setup should be considered as an easier task compared to ours. Nevertheless, we can still observe that the results generated by our model are comparable to the AffineGAN results in both realism and continuity. Figure 5 shows more results generated by our model trained on different emotions. Our model is able to learn some generalised traits for different emotions, for example, pouting and frowning in the “Disgust” category, lifting eyebrows in “Surprise”, and the crying face in “Sadness”. As we did not introduce any prior to the model during the training phase, all of these traits were summarised and learnt by the model itself by observing the training data. In Figure 6, we demonstrate the robustness of our model by testing it on an unseen dataset, the Amsterdam Dynamic Facial Expression Set (ADFES) [21]. The model tested is trained on the “Happiness” class on the UT Dallas dataset. We observe that our model is able to produce frames with consistent quality and smoothness, even though the background, illumination and video setup is different from the training dataset (UT Dallas). Figure 3 shows the results of our model trained and tested on the Weizmann Action database. We show the results generated by our model on four different action classes: “one hand wave”, “tow hands wave”, “skip” and “jump”. Our model is able to predict both the limb and body movements for the performers on the test set. This demonstrates the potential of our model for generating videos that are not limited to the facial expression domain. 3.3. Ablation Studies 3.3.1. Complementary Mask The complementary mask mechanism is the key component of our generator network, since it separates the static pixels and variable pixels such that the model will learn to reuse some of the pixels from the previous time step. In this way, the quality degradation problem in the autoregressive generation process appears to be greatly suppressed. Figure 7a shows the example results generated by our model with/without the complementary mask mechanism, illustrating that without the mask, the model suffers from quality degradation when generating later frames. On Table 2, numbers also suggest that implementing the complementary mask mechanism improves the generation quality of our model. 3.3.2. Two Discriminators In addition to the global discriminator in our framework, we employ another local discriminator that puts more attention to the variable pixels filtered by the mask mechanism in the generator network. It helps refine the details of the generated image, especially for the regions that are activity involved in the expression. As illustrated in Figure 7b, without any prior knowledge, the model learned to mask out the eye and mouth regions on the subject’s face, and the local discriminator pressured the generator to refine. Unlike previous methods [14,15], this entire process is fully automatic. Table 2 shows that having two discriminators in our network improves both the FID and the Inception Score. Scheduled Sampling (SS) The nature of autoregressive generation leads to discrepant behaviours during the training and the testing phases. If we only use ground truth next-frames during the training phase, the model will lack the ability to adjust itself to deal with generated frames. Figure 7c shows the effectiveness of scheduled sampling (SS) during the training process. We observe that applying SS during training results in an improvement of the vividness of the generated sequence at test time(the expression generated is more intense). Table 2 shows that performing SS slightly lowers the Inception Score, but it helps reduce the FID score. This is reasonable because the Inception Score only takes measurements on individual images, while FID measures the perceptual distance between the predicted and the target image. The number suggests that performing SS helps the model generate images that are closer to the ground truth. 3.4. Mask Visualization In Figure 8, we visualize the masks produced by the generator of our architecture. Recall that the mask has 3 channels (RGB) within the range of [0,1], each channel will be multiplied with a foreground difference map, and its complement will be multiplied with the previous frame. All three channels are stacked and rescaled to a range of [0,255] for visualization. As a result, higher values correspond to the foreground change (variable pixels), and lower values correspond to the background (static pixels). We take three different subjects in the “Happiness” category for illustration. The masks shown in the figure are sampled from the first, fourth and seventh timestep in the generation process. Interestingly, our model learnt to crop out facial regions that are “important” in facial expressions generations, such as the mouth, eyes and cheeks. This demonstrates the model’s ability to automatically detect regions of interest that may help with the generation process. 4. Discussion Here, we first include previous work, including methods in the literature that are related to our approach. These are methods that do image-to-image translation and temporal based image prediction, both connected to video prediction from a single image. We have also included methods that tackle the problem of semantic foreground and background distinction, which are related to the usage of the mask in our system to avoid degradation of the predicted face over time. Then, we discuss how our proposed method is framed in relation to those methods from the literature, and our specific contributions with respect to them. 4.1. Previous Work 4.1.1. Image-to-Image Translation Image-to-image translation has been an active area of computer vision in recent years [22,23]. It is the task of generating a new image from another input image. The mapping between the input and output image from different domains is learned, and can then be used for applications style transfer [3,4], photo enhancement [24,25] and future state prediction [26]. Generative adversarial networks (GANs) [1] are the backbone of most recent work in this area due to their powerful capability to generate sharp images. One popular variant is the conditional GAN [27], where the model generates images with characteristics from specific class labels, rather than generic samples from an unknown noise distribution. Our proposed method follows a similar architecture as proposed in the Pix2Pix model [2]. In [2], the conditional GAN has a generic loss function that allows it to learn effective mappings between input and output images from diverse domains. Like [2], our generator has a “U-Net” structure [13] with skip-connections [12], which helps preserve low-level information that is shared between input and output images. Similarly to [2], our discriminator judges whether each N×N patch in an image is more likely to be real or fake, and outputs the average probability. This helps to reduce parameters and training time. 4.1.2. Semantic Foreground-Background Distinction For better video generation, some methods have also distinguished the foreground information from the background information. For instance, [5] explicitly models the background and foreground as two different parts. This is motivated by the observation that the background is relatively static in most videos, and helps the model to learn the motion pattern of objects. This approach of semantic distinction is also useful for video understanding applications, such as in [28], where salient movements are detected by taking into account the temporal relationships between pixels of subsequent frames. In another approach [29], they used the Mask R-CNN [30] instead of object proposals to model scene transition by segmenting the region of interest from the background. 4.1.3. Temporal-based Video Prediction Videos are composed of frames that are temporally related and that follow a sequential order. Hence, most of the previous approaches for video prediction use recurrent neural networks [8,9,31] or 3D convolutional neural networks [5,7,10] to capture the temporal relationships between the frames. For example, in Villegas et al. [9], a convolutional LSTM encoder-decoder architecture was used to predict the next frames conditioned on previous frames up to a fixed number of time steps. In [10], the authors use a spatial-temporal architecture with 3D convolution layers to capture an optical flow map which is used to generate future frames from the first frame. Amazing results have been achieved in the domain of facial expression generation. In one such approach [14,15], an anchor image, as well as a facial expression intensity score as guidance were used to generate corresponding frames for an expression. However, this type of approach requires additional information such as facial landmark cropping [14], or AU annotation [15]. Furthermore, note that these kinds of information are very specific, and limited to the domain of facial images. In addition, these methods can only generate videos with pre-defined lengths, depending on how much they want to scatter their intensity score. 5. Advances of Our Approach in Relation to Previous Work In contrast to the aforementioned previous works for generating a video sequence based on a single input image, our model is able to generate frames of an arbitrary length, which provides flexibility in generating the desired intensity of a given target expression, possibly beyond the intensity of expressions exhibited in the training data. We tackle the problem by proposing an autoregressive approach during the generation process, which uses the output generated in one time step, as input to the next step to ensure smooth trajectories of the generated video. To ensure that the quality of the generated frames is not degraded along the generative process, we introduce a complementary mask to avoid noise and artifacts accumulating over time. We reported the robustness of the model by using images from an unseen facial expression dataset. Furthermore, given that our model does not require any guidance in the generation process, this allows us to go beyond the facial expression domain with respect to testing our method on other types of videos, as demonstrated in the experiments on the Weizmann Action database, which show the robustness of the proposed method. While generating videos from single images is a very hard task and immediate use of the method might not be possible depending on the quality needed for a given application, such as high quality animation for any expression, we believe that our method poses an advancement in the quality of the generated results with respect to previous work, and it poses a new framework in which more improvements can be potentially incorporated. 6. Conclusions In this paper, we propose a solution to the single image animation problem based on an autoregressive approach. By constantly re-feeding the output of the model to itself, the model is able to generate videos with arbitrary lengths. The autoregressive approach has two distinctive advantages: (1) It helps preserve the details and the context from the starter frame. (2) It enforces the generation results to be sequential, thus following a continuous timeline. We use the complementary mask mechanism to suppress the quality degradation effect caused by the autoregressive process. We propose a two-discriminator setup that reuses the mask produced in the generator to refine details in critical regions, since this process is automatic, no extra information such as region of interest cropping is needed. We conduct extensive experiments on a facial expression dataset, and demonstrate our model is able to generate realistic and continuous facial expression videos with only one starter image and no other extra information such as expression intensity guidance. We also show the potential of our model for video generation in other domains by testing it on a human action dataset. For future work, one could explore if expanding the input of the generative model to capture all previously generated frames improves further the quality of the results. Author Contributions Conceptualization, J.H., E.G.K., D.K. and G.R.; methodology, J.H. and G.R.; software, J.H.; validation, Y.K.C., S.Y. and K.Y.; formal analysis, J.H. and G.R.; investigation, J.H., Y.K.C., S.Y., K.Y. and G.R.; resources, D.H. and G.R.; data curation, D.K. and E.G.K.; writing—original draft preparation, J.H.; writing—review and editing, G.R., D.K. and E.G.K.; visualization, J.H.; supervision, G.R.; project administration, G.R.; funding acquisition, G.R. and D.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Autoregressive generation. G denotes the generator network, and D denotes the discriminator network. The model generates one frame at a time, the input to the model is always the output from the previous time step. Figure 2 Architecture Overview. (a) is the generator, it takes a frame ft as input, and produces a difference map Dt and a mask Mt. (b) is the complementary masking module that uses the mask Mt to merge the input frame ft and the difference map Dt into the predicted next frame ft+1′. (c) is the discriminator network. Figure 3 Results on the Human Action dataset. Figure 4 Qualitative comparison with different models for the “Happiness” class on the test set. The first row are the ground truth frames, the following rows are frames generated using different models. We also compare our results with the AffineGAN, which is not a temporal-based model. Our results are clearly better than ConvLSTM and FGST, and are comparable to results produced by AffineGAN. Figure 5 Different Emotions. We train our model on four different emotions on the UT Dallas dataset: Happiness, Disgust, Surprise and Sadness. Here, we show the results from the test set. Figure 6 Results on the unseen ADFES dataset. Figure 7 Ablation Studies. (a) Complementary Masking. (b) Two discriminators vs. one discriminator. (c) Scheduled Sampling (SS). Figure 8 Mask Visualization. Without any manual annotation, our model learns to crop out some facial landmarks that are important for expression generation. sensors-22-03533-t001_Table 1 Table 1 Quantitative comparison with ConvLSTM, FGST (temporal-based) and AffineGAN (non-temporal based). We use Frechet Inception Distance (FID) and Inception Score (IS) as evaluation metrics. We report the results on the test set of the “Happiness” class. Model FID IS Ground Truth 0 2.124 ConvLSTM 95.468 1.635 FGST 116.994 1.829 Ours 33.616 2.012 AffineGAN 15.869 2.111 sensors-22-03533-t002_Table 2 Table 2 Quantitative results for the ablation studies. All the models are trained and tested on the UT Dallas dataset, “Happiness” class. Model FID IS Ours w/o Mask 49.759 1.942 Ours w/o two discriminators 33.678 1.891 Ours w/o SS 33.821 2.024 Ours 33.616 2.012 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Goodfellow I.J. Pouget-Abadie J. Mirza M. Xu B. Warde-Farley D. Ozair S. Courville A. Bengio Y. Generative Adversarial Networks Proceedings of the 28th Annual Conference on Neural Information Processing Systems 2014 Montreal, QC, Canada 8–13 December 2014 2. Isola P. Zhu J.Y. Zhou T. Efros A.A. Image-to-Image Translation with Conditional Adversarial Networks Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Honolulu, HI, USA 21–26 July 2017 3. Karras T. Laine S. Aila T. A Style-Based Generator Architecture for Generative Adversarial Networks Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Long Beach, CA, USA 15–20 June 2019 4. Zhu J.Y. Park T. Isola P. Efros A.A. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks Proceedings of the IEEE International Conference on Computer Vision Venice, Italy 22–29 October 2017 5. Vondrick C. Pirsiavash H. Torralba A. Generating videos with scene dynamics Adv. Neural Inf. Process. Syst. 2016 29 613 621 6. Shi X. Chen Z. Wang H. Yeung D. Wong W. chun Woo W. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Proceedings of the Advances in Neural Information Processing Systems 28 Montreal, QC, Canada 7–12 December 2015 7. Li Y. Fang C. Yang J. Wang Z. Lu X. Yang M.H. Flow-Grounded Spatial-Temporal Video Prediction from Still Images Proceedings of the European Conference on Computer Vision (ECCV) Munich, Germany 8–14 September 2018 8. Cai H. Bai C. Tai Y.-W. Tang C.-K. Deep Video Generation, Prediction and Completion of Human Action Sequences Proceedings of the European Conference on Computer Vision (ECCV) Munich, Germany 8–14 September 2018 374 390 9. Villegas R. Yang J. Hong S. Lin X. Lee H. Decomposing Motion and Content for Natural Video Sequence Prediction arXiv 2017 1706.08033 10. Reda F.A. Liu G. Shih K.J. Kirby R. Barker J. Tarjan D. Tao A. Catanzaro B. SDCNet: Video Prediction Using Spatially-Displaced Convolution Proceedings of the European Conference on Computer Vision (ECCV) Munich, Germany 8–14 September 2018 718 733 11. Bengio S. Vinyals O. Jaitly N. Shazeer N. Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks Proceedings of the Advances in Neural Information Processing Systems 28 Montreal, QC, Canada 7–12 December 2015 12. He K. Zhang X. Ren S. Sun J. Deep Residual Learning for Image Recognition Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Las Vegas, NE, USA 26 June–1 July 2016 770 778 13. Ronneberger O. Fischer P. Brox T. U-Net: Convolutional Networks for Biomedical Image Segmentation Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention Munich, Germany 5–9 October 2015 14. Shen G. Huang W. Gan C. Tan M. Huang J. Zhu W. Gong B. Facial Image-to-Video Translation by a Hidden Affine Transformation Proceedings of the 27th ACM International Conference on Multimedia Nice, France 21–25 October 2019 15. Pumarola A. Agudo A. Martínez A. Sanfeliu A. Moreno-Noguer F. GANimation: Anatomically-aware Facial Animation from a Single Image Proceedings of the European Conference on Computer Vision (ECCV) Munich, Germany 8–14 September 2018 Volume 11214 835 851 16. Kingma D.P. Ba J. Adam: A Method for Stochastic Optimization arXiv 2014 1412.6980 17. O’Toole A. Harms J. Snow S.L. Hurst D. Pappas M.R. Ayyad J.H. Abdi H. A video database of moving faces and people IEEE Trans. Pattern Anal. Mach. Intell. 2005 27 812 816 10.1109/TPAMI.2005.90 15875802 18. Gorelick L. Blank M. Shechtman E. Irani M. Basri R. Actions as Space-Time Shapes IEEE Trans. Pattern Anal. Mach. Intell. 2007 29 2247 2253 10.1109/TPAMI.2007.70711 17934233 19. Heusel M. Ramsauer H. Unterthiner T. Nessler B. Hochreiter S. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium Proceedings of the Advances in Neural Information Processing Systems 30 Montreal, QC, Canada 7–12 December 2015 20. Salimans T. Goodfellow I.J. Zaremba W. Cheung V. Radford A. Chen X. Improved Techniques for Training GANs Proceedings of the Advances in Neural Information Processing Systems 29 Barcelona, Spain 6–10 December 2016 21. van der Schalk J. Hawk S.T. Fischer A.H. Doosje B. Moving faces, looking places: Validation of the Amsterdam Dynamic Facial Expression Set (ADFES) Emotion 2011 11 907 920 10.1037/a0023853 21859206 22. Choi Y. Choi M. Kim M. Ha J.W. Kim S. Choo J. StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Salt Lake City, UT, USA 18–23 June 2018 8789 8797 23. Kim J. Kim M. Kang H. Lee K. U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation arXiv 2019 1907.10830 24. Chen Y.S. Wang Y.C. Kao M.H. Chuang Y.Y. Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Salt Lake City, UT, USA 18–23 June 2018 6306 6314 25. Deng Y. Loy C.C. Tang X. Aesthetic-Driven Image Enhancement by Adversarial Learning Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Salt Lake City, UT, USA 18–23 June 2018 6306 6314 26. Zhou Y. Berg T.L. Learning Temporal Transformations From Time-Lapse Videos Proceedings of the European Conference on Computer Vision Amsterdam, The Netherlands 8–16 October 2016 27. Mirza M. Osindero S. Conditional Generative Adversarial Nets arXiv 2014 1411.1784 28. Zhuo T. Cheng Z. Zhang P. Wong Y. Kankanhalli M. Unsupervised online video object segmentation with motion property understanding IEEE Trans. Image Process. 2019 29 237 249 10.1109/TIP.2019.2930152 31369377 29. Minkesh A. Worranitta K. Taizo M. Human extraction and scene transition utilizing Mask R-CNN arXiv 2019 1907.08884 30. He K. Gkioxari G. Dollár P. Girshick R. Mask r-cnn Proceedings of the IEEE International Conference on Computer Vision Venice, Italy 22–29 October 2017 2961 2969 31. Tulyakov S. Liu M.-Y. Yang X. Kautz J. Mocogan: Decomposing motion and content for video generation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Salt Lake City, UT, USA 18–23 June 2018 1526 1535

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095421 ijerph-19-05421 Article Wealth and Education Inequities in Maternal and Child Health Services Utilization in Rural Ethiopia https://orcid.org/0000-0003-2497-4494 Wuneh Alem Desta 1* Bezabih Afework Mulugeta 1 Okwaraji Yemisrach Behailu 23 https://orcid.org/0000-0003-0710-7954 Persson Lars Åke 23 Medhanyie Araya Abrha 1 Tchounwou Paul B. Academic Editor 1 School of Public Health, College of Health Sciences, Mekelle University, Mekelle P.O. Box 1871, Ethiopia; afework.mulugeta@gmail.com (A.M.B.); araya.medhanyie@gmail.com (A.A.M.) 2 London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK; yemisrach.okwaraji@lshtm.ac.uk (Y.B.O.); lars.persson@lshtm.ac.uk (L.Å.P.) 3 Ethiopian Public Health Institute, Addis Ababa P.O. Box 1242, Ethiopia * Correspondence: alemdw@gmail.com 29 4 2022 5 2022 19 9 542113 3 2022 25 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). As part of the 2030 maternal and child health targets, Ethiopia strives for universal and equitable use of health services. We aimed to examine the association between household wealth, maternal education, and the interplay between these in utilization of maternal and child health services. Data emanating from the evaluation of the Optimizing of Health Extension Program intervention. Women in the reproductive age of 15 to 49 years and children aged 12–23 months were included in the study. We used logistic regression with marginal effects to examine the association between household wealth, women’s educational level, four or more antenatal care visits, skilled assistance at delivery, and full immunization of children. Further, we analyzed the interactions between household wealth and education on these outcomes. Household wealth was positively associated with skilled assistance at delivery and full child immunization. Women’s education had a positive association only with skilled assistance at delivery. Educated women had skilled attendance at delivery, especially in the better-off households. Our results show the importance of poverty alleviation and girls’ education for universal health coverage. inequity antenatal care skilled assistance at delivery full child immunization maternal education household wealth interaction Bill & Melinda Gates FoundationINV-009691 The study was funded by the Bill & Melinda Gates Foundation (INV-009691) to the London School of Hygiene and Tropical Medicine. The funder had no role in the study design, collection, management, analysis, and interpretation of data. ==== Body pmc1. Introduction The 2030 Sustainable Development Goals (SDGs) call for reducing maternal mortality to less than 70 per 100,000 live births, under-five mortality to not more than 25/1000 live births, and neonatal mortality to 12/1000 live births or less. The third development goal is set to ensure equitable health coverage across all low-, middle-, and high-income countries [1]. Despite the decline in maternal and under-five mortality during the Millennium Development Goals era, high mortality rates prevail in sub-Saharan Africa [2], to a large extent avoidable [3], and linked to social determinants [4]. To reach the mortality targets and the goal of universal health coverage [5], these health inequities must be addressed [6]. Many studies have described socioeconomic inequities in maternal and child health services utilization [7,8]. Better-off households and educated parents are more likely to use the health services, while the poor and those without education show low coverage of services [9]. Providing equitable maternal and child health care services, such as antenatal care and skilled birth assistance, improves maternal health and reduces maternal and child mortality [2]. Inequities in the coverage of these services are prominent in sub-Saharan Africa [10]. An analysis from three sub-Saharan African countries, including Ethiopia, described persistent inequities despite an increase in the coverage of essential maternal and newborn care interventions [11]. Common social determinants linked to inequities in the utilization of maternal and child health services are economic conditions, parents’ education level, the mothers’ age, and socio-cultural factors [12]. In Ethiopia, the poorest households show the lowest coverage of maternal, newborn, and child health services [13]. Women’s educational level, household wealth, and maternal age have been reported as determinants of health service utilization [14]. Based on a recent survey of mainly rural populations in four Ethiopian regions, we did not find evidence of wealth-based inequity in full child immunization coverage [15]. In contrast, an analysis based on national-level data found inequities related to household wealth and maternal education [16]. While inequities in maternal, newborn, and child healthcare services utilization frequently have been described, most studies report unidimensional analyses, either related to household wealth [15] or maternal education [17] but without exploring the association with the combination of household wealth and maternal education levels [14,18]. Hence, this study aimed to examine the association between household wealth, maternal education, and the interplay between household wealth and maternal education on the utilization of four or more antenatal visits, skilled assistance at delivery, and full child immunization. 2. Methods 2.1. Study Design and Setting A cross-sectional study was conducted in 46 districts of four Ethiopian regions, i.e., Amhara, Oromia, Southern Nations, Nationalities and Peoples Region, and Tigray, from December 2018 to February 2019. These regions are the most populous in the country, where the Ethiopian Government initiated the Optimizing the Health Extension Program interventions. The survey was conducted jointly by the London School of Hygiene and Tropical Medicine, the Ethiopian Public Health Institute, and four Ethiopian universities; the University of Gondar, Jimma, Mekelle, and Hawassa Universities. The country has a three-tiered health system with primary healthcare units and secondary and tertiary levels of care. The population size of the study districts was on average 130,000 people, with 23% being women of the reproductive age and 20% children below the age of five years. One-third of the districts had a hospital. There were, on average, five health centers per district and five health posts under each health center [19]. 2.2. Data Source This study used data from the evaluation of the Optimizing the Health Extension Program intervention that aimed at improving services utilization. A two-stage stratified cluster sampling technique was used to select study subjects. First, 194 enumeration areas, the primary sampling unit, were obtained based on the 2007 Ethiopian Housing and Population Census using probability proportional to the size of the districts. Second, all households within the clusters were listed. Sixty households per cluster were selected using systematic random sampling. All women of reproductive age (15–49 years old) and children under the age of five years, who lived in the selected households, were included in the study. A standard sample size formula was used to calculate the sample size. The sample size was estimated to be 6000 households per group (12,000 in total). The sample size determination was detailed elsewhere [20]. The questionnaire was developed based on existing large-scale survey tools in English, translated into local language and back translated and pretested. Data collectors were trained for 10 days including field training before the start of data collection. Information about antenatal care attendance and delivery by skilled birth assistance was collected from all reproductive-age women who had a live birth during one year preceding the survey. Immunization information was collected by combining data recorded on children’s vaccination cards and responses from the parents if the vaccination card was missing. The questionnaire also included information on sociodemographic data and household assets. Data were collected on personal digital assistants (Companion Touch 8), and tablets (Toshiba and Hewlett Packard) programmed with CSPro 7.1. through face-to-face interviews. Data collectors sent encrypted data from the field to the password-protected server at the Ethiopian Public Health Institute. Data managers conducted quality checks and provided feedback to field teams. Data were cleaned and checked for consistency and completeness. 2.3. Measurements Outcome Variables The analysis included three maternal and child health indicators: four or more antenatal care visits, skilled birth assistance, and full immunization of children aged 12–23 months. Four or more antenatal care visits were defined as the percentage of women of reproductive age with a live birth within the last 12 months preceding the survey who attended four or more antenatal care visits during pregnancy. Skilled birth assistance was represented in the percentage of women aged 13–49 years with a live birth within the last 12 months preceding the survey who were attended at delivery by skilled health personnel. Full immunization was defined as the percentage of children aged 12–23 months who had received one dose of BCG vaccine, three doses of polio vaccine, three doses of pentavalent vaccine, and one dose of measles vaccine [21]. All these outcomes were coded as 1 when the subjects had received the service or 0 when the subjects had not received the service. Covariates. The covariates included in this study were household wealth, which was created by dividing the household wealth index into three equal tertiles (Tertile 1, Tertile 2, and Tertile 3) to classify households as poor, middle, and better-off. The wealth tertile was created based on ownership of durable assets, access to utilities and infrastructure, and housing characteristics. The construction of the wealth tertile was done using principal component analysis as detailed in a previous publication [19]. Maternal education was categorized into two levels: no education (not attended formal education) and educated (primary or above). Other covariates included were maternal age in years (15–24, 25–34, and 35–49), birth order (1, 2–3, and 4 and above births), region (Amhara, Oromia, SNNPR, and Tigray), religion (Orthodox Christian, Muslim, Protestant, and others), and sex of the child. Wealth-education was also created by combining household wealth and maternal education and was categorized into six levels: tertile 1*no education, tertile 1*educated, tertile 2*no education, tertile 2*educated, tertile 3*no education, and tertile 3*educated. 2.4. Data Analysis Descriptive analyses included frequency distributions of the determinants and covariates and outcomes of the service utilization. The utilization of services was cross-tabulated with socioeconomic and other background factors. Logistic regression was used to examine the associations between household wealth, maternal education, maternal age, birth order, region and religion and outcomes of the service utilization, and interactions between household wealth and maternal education. The results from the logistic regression analyses were presented as average marginal effects with 95% confidence intervals for the main effects and 90% confidence intervals for the interaction terms. The average marginal effects were used to estimate the discrete change for the factor’s levels from the reference. The Chi-square test was used to measure the significance of the change. Potential multicollinearity between the covariates used in the multivariate regression model was assessed using variance inflation factors. The Delta method was used for the standard errors to estimate the variation. The marginal effects were estimated using the margins command in Stata 14.1 for windows (GSW) (StataCorp LLC, College Station, TE, USA), which considered the interaction terms included in the model. Marginsplot command in Stata [22] was used to graphically display the results. During the analysis, all the commands were preceded with svy to account for clustering. Ethical review: Ethical approval was obtained from the Ethiopian Public Health Institute (SERO-012-8-2016; Version 001), London School of Hygiene and Tropical Medicine (LSHTM Ethic Ref: 11235), and the IRB office of College of Health Sciences of Mekelle University in Ethiopia (ERC 1434/2018). Written consent and assent were also obtained from the participants. 3. Results 3.1. Participants’ Characteristics Data were collected from 10785 rural households. A total of 1720 women who had a live birth during the year preceding the survey and 677 children in the age interval 12–23 months were included in the analysis. The women had a mean (SD) age of 28.6 (6.04) years, and about half had no education (Table 1). Moreover, 52% of women who gave birth during the year preceding the survey had received four or more antenatal care visits, and 56% of them had got skilled assistance at delivery. Utilization of four or more antenatal care visits was slightly lower than skilled assistance at delivery. Full immunization in children aged 12–23 months was 38% (Table 1). 3.2. Utilization of Four or More Antenatal Care, Delivery Care and Child Immunization Receiving four or more antenatal care visits was slightly higher among women belonging to better-off households. Skilled attendance at birth was higher among women from the better-off households and the educated ones (Table 2). Similarly, children aged 12–23 months from better-off households had higher coverage of full child immunization. Full immunization did not differ by maternal education. Skilled assistance at delivery and full child immunization increased with increasing household wealth and maternal education (Table 2). Social Determinants of Antenatal Care, Skilled Birth Assistance, and Full Child Immunization Four or more antenatal care visits did not significantly differ by household wealth levels (p = 0.142). Similarly, there was no significant difference in receiving four or more antenatal care visits by levels of maternal education (p = 0.178). However, women from better-off households had skilled assistance at delivery more frequently than those from poor households (p < 0.001). Similarly, educated women had skilled assistance at delivery more often than non-educated (p = 0.011). Children from better-off households had higher coverage of full immunization compared to children from poor households (p = 0.004). There was no association between maternal education and full immunization (p = 0.913) (Table 3). Household wealth and education interaction were observed for skilled assistance at delivery at higher household wealth. In better-off households, the association between women’s education and skilled assistance at delivery was more pronounced (p < 0.001) (Table 3). Also, educated women in the middle household wealth had higher-skilled assistance at delivery (p = 0.027). However, the analyses of the interaction between household wealth and women’s education on four or more antenatal care visits and full child immunization showed overlapping estimates and were therefore inconclusive (Figure 1, Figure 2 and Figure 3 and Table 3). 4. Discussion In this study in rural areas of four Ethiopian regions, we have shown that household wealth was positively associated with skilled assistance at delivery and full child immunization. Women’s education had a positive association only with skilled assistance at delivery. Educated women had higher-skilled assistance at delivery, especially for those living in better-off households. However, there was no interaction between household wealth and education on four or more antenatal visits or full child immunization. Half of the pregnant women had attended antenatal care four or more times, a bit more than half had skilled assistance at delivery, and four out of ten children were fully immunized. We did not find any association between household wealth and four or more antenatal care visits. This indicates that the present level of antenatal care coverage is relatively equitable in the study districts in four rural Ethiopian regions. Our findings corroborate with a community-based study from north-eastern Ethiopia [23] and Myanmar [24]. However, in a study conducted two years earlier in the same geographic area [15] as well as in the Ethiopian Demographic and Health Survey 2019 [25], there were pro-rich inequities in the utilization. Other studies in African countries have also shown social differences in the use of these services [2]. Similarly, maternal education was not associated with antennal care visits. The community-based pro-poor and pro-rural policy initiatives in Ethiopia, such as the health extension workers and women’s development groups mobilize all pregnant women to use the antenatal care services. The women’s development groups are key community actors in supporting the health extension workers by identifying pregnant women and linking them with the health extension workers and health facilities for antenatal follow-up [26]. Such policy initiatives may have contributed to the equitable utilization of antenatal care by pregnant women at different levels of socioeconomic status. Nonetheless, household wealth was positively associated with skilled assistance at delivery. The better-off women were more likely to get skilled assistance at delivery. In Ethiopia, skilled assistance at delivery is provided at fixed health facilities staffed with skilled health workers. This implies that services delivered at higher-level health facilities by skilled providers would likely be inequitably distributed. Such divides are frequently found in studies from low- and middle-income countries [27,28]. The reasons behind this may be associated with the costs linked to the use of these services, such as buying medicines from private pharmacies [29], transport costs [17], and other opportunity costs [30]. These findings are in line with previous studies in Ethiopia [15] and a narrative review carried out in African countries [31], which found pro-rich differentials in facility delivery. Poverty is closely linked to low-skilled assistance at birth. Empowering women and poverty alleviation efforts may enhance equity in the coverage of facility delivery. Hence, the community-based health insurance and poverty alleviation initiatives in Ethiopia should be strengthened to increase equitable utilization of maternal health services. Educated women were more likely to get skilled assistance at delivery. The expansion of schools in rural areas has resulted in more educated women [17]. An educated woman is more able to access and use information about community-based initiatives and the benefit of maternal health services. She is empowered to make her own decisions and to seek care for herself and her children [17,31]. This implies that Ethiopia is a long way towards the universal coverage of skilled assistance as a centrality of the SDGs that still put the poor and uneducated at a disadvantage. Full child immunization was more common in children belonging to better-off households. This association was also found in the 2019 Ethiopian Demographic and Health Survey report [25], other Ethiopian studies [16], and in other African countries [32]. However, a study conducted two years earlier in the same geographic area could not find social inequity in immunization coverage [15]. Immunization is provided freely but costs related to transporting especially for poor mothers, and productivity loss as taking time off work to access immunization may negatively affect equitable coverage [16]. Weaknesses in monitoring and supervision could also have reduced outreach services and access to immunization [16]. Further, the civil unrest in many parts of the country may have increased inequity in immunization coverage. Conflict as a barrier to services utilization is also evidenced in a systematic review from low-income African countries [33]. Any failure in community mobilization may also result in inequities in child immunization coverage [34]. The highest utilization of skilled assistance at delivery was shown among women in the better-off households who were educated. This interaction between household wealth and maternal education on skilled assistance at delivery suggests that poverty alleviation combined with enhanced education efforts, especially for girls, may result in women delivering in health facilities to an extent that is even larger than expected. This is substantiated by prior studies [35] that have found better utilization of maternal health services among educated women in better-off households. This shows that the poor and uneducated women are still behind universal coverage for skilled assistance at delivery in Ethiopia. For example, a study from Afghanistan [36] has reported better utilization of skilled assistance at delivery among women belonging to the better-off and literate households. On the other hand, a study in India showed that poor, non-educated women are less likely to utilize healthcare services [37]. This may lead to adverse birth outcomes among the poor who are uneducated women [2]. The results did not show an association between full child immunization and the interaction of household wealth and maternal education. We did not also find an association between maternal education and full child immunization. In Ethiopia, immunization is delivered at health facilities, primarily at the primary care level, and at community level through outreach and occasionally via national campaigns with blanket coverage, especially in the rural areas. The health extension workers and women development groups deliver community-based immunization services through outreach [16,26]. While the women development groups mobilize and educate mothers to vaccinate their children, the health extension workers administer the vaccination. The support of women development group to health extension programme was evidenced in a study from Ethiopia [38]. The success of community health extension program has led to equitable access to immunization for children in rural areas [26]. This suggests that strengthening community-based outreach services has the potential to ensure social equities in immunization coverage, which is documented in previous systematic reviews from low- and -middle-income countries [27,39]. In the countdown report, it was also documented that community-based interventions tended to be more equitable than facility-based interventions [28]. In general, our findings show that the 2030 SDGs targets related to maternal and child health are left behind in rural Ethiopia. Education, economy, and their interactions are evidenced as major social determinants of inequity in maternal health services and then maternal mortality [4]. These inequities are also evidenced to deter the achievement of universal health coverage related to SDGs [40] that requires actions. The poor who are uneducated are left behind. So, the findings entail a need for intersectoral interventions; enhancing education (i.e., SDG-4), and poverty alleviation (SDG-1) programs to promote equitable universal health coverage towards SDG targets related to maternal and child health (SDG-3.8.1) [41]. The health sector interventions alone cannot reduce inequities [42]. To reinforce the Ethiopian Health Policy statement [43], intersectoral approaches and actions are needed in the policy initiatives to increase the equitable coverage of maternal, newborn, and child health services. Intersectoral approaches have been proven to promote universal health coverage [42]. Our study has strengths and limitations. We have contributed to the knowledge of inequities in the utilization of maternal, and child health services in Ethiopia. The study also identified the most disadvantaged population segments in the maternal and child health services utilization by household wealth and education. The study has some limitations. Our findings are relevant for the study districts in the four most populous regions in Ethiopia but may not represent the entire region or Ethiopia as a whole. The economic status of households was measured using a household wealth index that may not reflect the actual economic strength at the time of the study. The household wealth index is an established method for economic status but does not directly show the ability to cover costs associated with the use of health services. Education was also dichotomized into no education and educated due to the small sample of women with secondary or higher levels of education. In other studies, the empowerment of education is often shown for secondary or higher education levels. The interaction effect was estimated through the combination of household wealth and maternal education. The interactions may also be explained by other factors that potentially explain inequity in the utilization of maternal, and child health services. Finally, the use of cross-sectional data for our analysis limited causal inference. 5. Conclusions The findings suggest that the combination of wealth and education plays a significant role in the utilization of maternal health services. The interaction of wealth and education has a significant effect on the utilization of skilled birth attendance. While educated women belonging to wealthier households have a higher tendency of utilizing SBA. But, the interaction of wealth and education neutralizes the utilization of ANC4+ and full child immunization. This showed that the use of SBA and full immunization of the child were positively associated with the birth outcomes. The findings underscore the importance of empowering girls and women through poverty alleviation and education as goals of health programs. This, therefore, requires, policy strategies that promote intersectoral approaches and actions aimed at ensure universal coverage in maternal and child health outcomes. Future studies involving interaction of social determinants to estimate inequity in the maternal and child health services utilization should consider large sample sizes. Acknowledgments We thank all participants of this study. Author Contributions Conceptualization, A.D.W., L.Å.P. and A.A.M.; Data curation, Y.B.O.; Formal analysis, A.D.W.; Investigation, A.D.W.; Methodology, A.D.W. and L.Å.P.; Project administration, A.A.M.; Supervision, A.M.B., L.Å.P. and A.A.M.; Validation, A.D.W., A.M.B., Y.B.O. and L.Å.P.; Writing—original draft, A.D.W.; Writing—review & editing, A.D.W., A.M.B., Y.B.O., L.Å.P. and A.A.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical approval was obtained from the Ethiopian Public Health Institute (SERO-012-8-2016; Version 001), London School of Hygiene and Tropical Medicine (LSHTM Ethic Ref: 11235), and the IRB office of College of Health Sciences of Mekelle University in Ethiopia (ERC 1434/2018). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Deidentified data may be available from the data repository at EPHI upon request to Mrs. Martha Zeweldemariam, email: martha.zeweldemariam@lshtm.ac.uk. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Probability of four or more antenatal care use by household wealth and maternal education with 95% confidence intervals. Figure 2 Probability of skilled birth assistance use by household wealth and maternal education with 95% confidence intervals. Figure 3 Probability of full immunization use by household wealth and maternal education with 95% confidence intervals. ijerph-19-05421-t001_Table 1 Table 1 Characteristics of study participants in four Ethiopian regions. Characteristics Frequency % 95%CI Maternal characteristics (n = 1720) Four or more antenatal care visits No 823 48 (45–50) Yes 897 52 (50–54) Skilled birth assistance No 753 44 (41–46) Yes 967 56 (54–59) Maternal age 15–24 421 24 (22–26) 25–34 980 57 (55–59) 35–49 319 19 (17–20) Household wealth Tertile 1 (Poor) 585 34 (32–36) Tertile 2 571 33 (31–35) Tertile 3 (Better-off) 564 33 (31–35) Maternal education No education 872 51 (48–53) Educated 848 49 (47–52) Birth order 1 birth 274 16 (14–18) 2–3 births 618 36 (34–38) ≥4 births 823 48 (46–50) Religion Orthodox Christian 942 55 (52–57) Muslim 504 29 (27–32) Protestant and others 274 16 (14–18) Region Amhara 563 33 (30–35) Oromia 661 38 (36–41) SNNPR * 196 11 (10–13) Tigray 300 18 (16–19) Child characteristics (n = 677) Immunization Not fully immunized 422 62 (59–66) Fully immunized 255 38 (34–41) Sex of child Boy 350 52 (48–55) Girl 327 48 (45–52) * Southern Nations, Nationalities and Peoples Region. ijerph-19-05421-t002_Table 2 Table 2 Utilization of maternal, newborn and child health services by household wealth, maternal education and their interactions. Determinants Antenatal Care Four or More Visits (n = 1715) Skilled Birth Assistance (n = 1715) Full Child Immunization (n = 677) % p-Value % p-Value % p-Value Household wealth Tertile 1 (Poor) 54 40 30 Tertile 2 47 0.005 55 0.000 34 0.000 Tertile 3 (Better-off) 56 75 47 Maternal education No education 54 0.237 52 0.000 37 0.942 Educated 51 61 38 Wealth*education Tertile 1*no education 57 39 32 Tertile 1*educated 48 41 27 Tertile 2*no education 50 0.003 57 0.000 34 0.003 Tertile 2*educated 43 52 34 Tertile 3*no education 53 68 50 Tertile 3*educated 58 78 46 ijerph-19-05421-t003_Table 3 Table 3 Probability of utilization of four or more antenatal care visits, skilled attendance at delivery, and full immunization of children aged 12–23 months by household wealth, maternal education, and their interaction. Average marginal effect estimates (main effects and interactions) based on multivariable logistic regression. Covariates Four or More Antenatal Care Visits Skilled Birth Assistance Full Immunization AME (95%CI) AME (95%CI) AME (95%CI) Main effects Household wealth Tertile 1 (Poor) Referent Referent Referent Tertile 2 −0.06 (−0.12–0.003) 0.05 (−0.00–0.11) −0.01 (−0.09–0.08) Tertile 3 (Better-off) 0.05 (−0.02–0.11) 0.21 (0.15–0.26) *** 0.14 (0.04–0.23) ** Maternal education No education Referent Referent Referent Educated −0.04 (−0.09–0.02) 0.06 (0.01–0.11) * 0.01 (−0.07–0.09) Joint effects (wealth*education) Tertile 1*no education Referent Referent Referent Tertile 1*educated −0.08 (−0.17–0.01) 0.04 (−0.04–0.12) −0.02 (−0.16–0.11) Tertile 2*no education −0.06 (−0.13–0.02) 0.06 (−0.01–0.13) −0.01 (−0.11–0.10) Tertile 2*educated −0.13 (−0.21–0.04) 0.09 (−0.01–0.16) ** 0.02 (−0.11–0.15) Tertile 3*no education −0.02 (−0.11–0.07) 0.15 (0.06–0.23) *** 0.11 (−0.02–0.24) Tertile 3*educated 0.02 (−0.06–0.10) 0.28 (0.21–0.35) *** 0.13 (0.01–0.25) * AME = Average Marginal Effect = the discrete change from the base level. Logistic regression, adjusted for maternal age, birth order, region, religion, sex of a child. 95% confidence intervals in brackets, * p < 0.05, ** p < 0.01, *** p < 0.001. Comparison is made against the referent individuals. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Mcarthur J.W. Rasmussen K. Yamey G. How Many Lives are at Stake? Assessing 2030 Sustainable Development Goal Trajectories for Maternal and Child Health BMJ 2018 360 1 9 10.1136/bmj.k373 29449222 2. Yaya S. Ghose B. Global Inequality in Maternal Health Care Service Utilization: Implications for Sustainable Development Goals Health Equity 2019 3 145 154 10.1089/heq.2018.0082 31289773 3. Alvarez J.L. Gil R. Hernández V. Gil A. Factors Associated with Maternal Mortality in Sub-Saharan Africa: An Ecological Study BMC Public Health 2009 9 1 8 10.1186/1471-2458-9-462 19121216 4. Batist J. An Intersectional Analysis of Maternal Mortality in Sub-Saharan Africa: A Human Rights Issue J. Glob. Heal. 2019 9 010320 10.7189/jogh.09.010320 31217956 5. United Nations Resolution Adopted by the General Assembly on 25 September 2015. Transforming our World: The 2030 Agenda for Sustainable Development-A/RES/70/1 United Nations New York, NY, USA 2015 6. Kyei-nimakoh M. Carolan-olah M. Mccann T.V. Access barriers to obstetric care at health facilities in sub-Saharan Africa—A systematic review BMC 2017 6 1 16 10.1186/s13643-017-0503-x 28587676 7. Çalışkan Z. Kılıç D. Öztürk S. Atılgan E. Equity in Maternal Health Care Service Utilization: A Systematic Review for Developing Countries Int. J. Public Health 2015 60 815 825 10.1007/s00038-015-0711-x 26298441 8. Peven K. Mallick L. Taylor C. Bick D. Day L.T. Kadzem L. Purssell E. Equity in newborn care, evidence from national surveys in low- and middle-income countries Int. J. Equity Health 2021 20 1 16 10.1186/s12939-021-01452-z 33386078 9. Say L. Raine R. A systematic review of inequalities in the use of maternal health care in developing countries: Examining the scale of the problem and the importance of context Bull. World Health Organ. 2007 85 812 819 10.2471/BLT.06.035659 18038064 10. Faye C.M. Wehrmeister F.C. Melesse D.Y. Kavao M. Mutua K. Maïga A. Amouzou A. Jiwani S.S. da Silva I.C.M. Sidze E.M. Large and Persistent Subnational Inequalities in Reproductive, Maternal, Newborn and Child Health Intervention Saharan Africa Coverage in Sub-Saharan Africa BMJ Glob. Health 2020 5 1 9 10.1136/bmjgh-2019-002232 11. Marchant T. Beaumont E. Makowiecka K. Della B. Tessema T. Gautham M. Singh K. Umar N. Usman A.U. Tomlin K. Coverage and equity of maternal and newborn health care in rural Nigeria, Ethiopia and India Can. Med. Assoc. J. 2019 191 1179 1188 10.1503/cmaj.190219 12. Adgoy E.T. Key social determinants of maternal health among African countries: A documentary review MOJ Public Health 2018 7 140 144 10.15406/mojph.2018.07.00219 13. Barros A.J.D. Wehrmeister F.C. Ferreira L.Z. Vidaletti L.P. Hosseinpoor A.R. Victora C.G. Are the Poorest Poor being Left Behind? Estimating Global Inequalities in Reproductive, Maternal, Newborn and Child Health BMJ Glob. Health 2020 5 e002229 10.1136/bmjgh-2019-002229 32133180 14. Gebre E. Worku A. Bukola F. Inequities in maternal health services utilization in Ethiopia 200–2016: Magnitude, trends, and determinants Reprod. Health 2018 15 1 9 10.1186/s12978-018-0556-x 29304829 15. Wuneh A.D. Medhanyie A.A. Bezabih A.M. Persson L.Å. Schellenberg J. Okwaraji Y.B. Wealth-based equity in maternal, neonatal, and child health services utilization: A cross-sectional study from Ethiopia Int. J. Equity Health 2019 18 1 9 10.1186/s12939-019-1111-2 30606218 16. Geweniger A. Abbas K.M. Childhood vaccination coverage and equity impact in Ethiopia by socioeconomic, geographic, maternal, and child characteristics Vaccine 2020 38 3627 3638 10.1016/j.vaccine.2020.03.040 32253099 17. Oh J.H. Educational expansion and health disparities in Ethiopia, 2005–2016 Soc. Sci. Med. 2019 235 1 9 10.1016/j.socscimed.2019.05.021 18. Bobo F.T. Yesuf E.A. Woldie M. Inequities in utilization of reproductive and maternal health services in Ethiopia Int. J. Equity Health 2017 16 1 8 10.1186/s12939-017-0602-2 28057005 19. Berhanu D. Okwaraji Y.B. Defar A. Bekele A. Lemango E.T. Medhanyie A.A. Wordofa M.A. Yitayal M. W/Gebriel F. Desta A. Does a complex intervention targeting communities, health facilities and district health managers increase the based child utilisation of community- health services? A before and after study in intervention and comparison areas of Ethiopia BMJ Open 2020 10 e040868 10.1136/bmjopen-2020-040868 20. Berhanu D. Okwaraji Y.B. Belayneh A.B. Lemango E.T. Agonafer N. Birhanu B.G. Abera K. Betemariam W. Medhanyie A.A. Abera M. Protocol for the evaluation of a complex intervention aiming at increased utilisation of primary child health services in Ethiopia: A before and after study in intervention and comparison areas BMC Heal. Serv. Res. 2020 20 1 12 10.1186/s12913-020-05151-3 21. Restrepo-Méndez M.C. Barros A. Wong K. Johnson H.L. Pariyo G. França G.V. Wehrmeister F.C. Victora C. Inequalities in full immunization coverage: Trends in low- and middle-income countries Bull. World Health Organ. 2016 94 794 805A 10.2471/BLT.15.162172 27821882 22. Williams R. Using the Margins Command to Estimate and Interpret Adjusted Predictions and Marginal Effects Stata J. Promot. Commun. Stat. Stata 2012 12 308 331 10.1177/1536867X1201200209 23. Shibre G. Mekonnen W. Socio-economic inequalities in ANC attendance among mothers who gave birth in the past 12 months in Debre Brehan town and surrounding rural areas, North East Ethiopia: A community-based survey Reprod. Health 2019 16 1 14 10.1186/s12978-019-0768-8 30621726 24. Myint A.N.M. Liabsuetrakul T. Htay T.T. Wai M.M. Sundby J. Bjertness E. Inequity in the utilization of antenatal and delivery care in Yangon region, Myanmar: A cross-sectional study Int. J. Equity Health 2018 17 1 9 10.1186/s12939-018-0778-0 29301537 25. Ethiopian Public Health Institute (EPHI) [Ethiopia] and ICF Ethiopia Mini Demographic and Health Survey 2019: Key Indicators EPHI and ICF Rockville, MD, USA 2019 26. Assefa Y. Gelaw Y.A. Hill P.S. Taye B.W. Van Damme W. Community health extension program of Ethiopia, 2003–2018: Successes and challenges toward universal coverage for primary healthcare services Glob. Health 2019 15 1 11 10.1186/s12992-019-0470-1 30914055 27. Schleiff M. Freeman P.A. Gupta S. Bahie M. Comprehensive Review of the Evidence Regarding the Effectiveness of Community-Based Primary Health Care in Improving Maternal, Neonatal and Child Health: 5 Equity Effects for Neonates and Children J. Glob. Health 2017 7 010905 10.7189/jogh.07.010905 28685043 28. Boerma T. Requejo J. Victora C. Amouzou A. George A. Agyepong I.A. Barroso C. Barros A.J.D. A Bhutta Z. E Black R. Countdown to 2030: Tracking progress towards universal coverage for reproductive, maternal, newborn, and child health Lancet 2018 391 1538 1548 10.1016/S0140-6736(18)30104-1 29395268 29. Kiros M. Dessie E. Jbaily A. Tolla M.T. Johansson K.A. Norheim O.F. Memirie S.T. Verguet S. The Burden of Household Out-of-Pocket Health Expenditures in Ethiopia: Estimates from a Nationally Representative Survey (2015–16) Health Policy Plan. 2020 35 1003 1010 10.1093/heapol/czaa044 32772112 30. Browne E. Barriers Affecting Demand for RMNCH Services in Developing Countries Institute of Development Studies Brighton, UK 2020 31. Musizvingoza R. Social Determinants Affecting Utilization of Maternal Health Services in Africa: A Narrative Review of the Evidence Int. J. Health Serv. Res. Policy 2020 5 64 74 10.33457/ijhsrp.688559 32. Arsenault C. Harper S. Nandi A. Mendoza J.M. Hansen P.M. Johri M. Monitoring equity in vaccination coverage: A systematic analysis of demographic and health surveys from 45 Gavi-supported countries Vaccine 2017 35 951 959 10.1016/j.vaccine.2016.12.041 28069359 33. Dahab R. Sakellariou D. Barriers to Accessing Maternal Care in Low Income Countries in Africa: A Systematic Review Int. J. Environ. Res. Public Health 2020 17 4292 10.3390/ijerph17124292 34. Lafond A. Kanagat N. Steinglass R. Fields R. Sequeira J. Drivers of Routine Immunization Coverage Improvement in Africa: Findings from District-Level Case Studies Health Policy Plan. 2015 30 298 308 10.1093/heapol/czu011 24615431 35. Amugsi D. Mumah J. Izugbara C.O. Women’s education and utilization of maternal health services in africa: A multi-country and socioeconomic status analysis J. Biosoc. Sci. 2018 50 725 748 10.1017/S0021932017000505 29103388 36. Kim C. Erim D. Natiq K. Salehi A.S. Zeng W. Combination of Interventions Needed to Improve Maternal Healthcare Utilization: A Multinomial Analysis of the Inequity in Place of Childbirth in Afghanistan Front. Glob. Women’s Health 2020 1 571055 10.3389/fgwh.2020.571055 34816155 37. Dey A. Hay K. Afroz B. Chandurkar D. Singh K. Dehingia N. Raj A. Silverman J.G. Understanding intersections of social determinants of maternal healthcare utilization in Uttar Pradesh, India PLoS ONE 2018 13 e0204810 10.1371/journal.pone.0204810 30286134 38. Kok M.C. Kea A.Z. Datiko D.G. Broerse J.E.W. Dieleman M. Taegtmeyer M. Tulloch O. A qualitative assessment of health extension workers’ relationships with the community and health sector in Ethiopia: Opportunities for enhancing maternal health performance Hum. Resour. Health 2015 13 80 10.1186/s12960-015-0077-4 26423049 39. Yuan B. Målqvist M. Trygg N. Qian X. Ng N. Thomsen S. What Interventions are Effective on Reducing Inequalities in Maternal and Child Health in Low- and Middle-Income Settings? A Systematic Review BMC Public Health 2014 14 1 14 10.1186/1471-2458-14-634 24383435 40. Degefa T. Hoelscher K. Development aid and health equity in Ethiopia Dev. Stud. Res. 2020 7 83 92 10.1080/21665095.2020.1794921 41. Fonseca L.M. Domingues P. Dima A.M. Mapping the Sustainable Development Goals Relationships Sustainability 2020 12 3359 10.3390/su12083359 42. Huda T.M. Tahsina T. Arifeen S.E. Dibley M.J. The importance of intersectoral factors in promoting equity-oriented universal health coverage: A multilevel analysis of social determinants affecting neonatal infant and under-five mortality in Bangladesh Glob. Health Action 2016 9 29741 10.3402/gha.v9.29741 26880153 43. Transitional Government of Ethiopia Health Policy of The Transitional Government of Ethiopia IPHCE Addis Ababa, Ethiopia 1993

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==== Front Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells11091543 cells-11-01543 Review Evaluation of Proteasome Inhibitors in the Treatment of Idiopathic Pulmonary Fibrosis https://orcid.org/0000-0002-9770-8544 Chen I-Chen 123 Liu Yi-Ching 1 Wu Yen-Hsien 1 Lo Shih-Hsing 1 Dai Zen-Kong 123 Hsu Jong-Hau 1 https://orcid.org/0000-0002-2558-2209 Tseng Yu-Hsin 1* Das Anindita Academic Editor Samidurai Arun Academic Editor 1 Department of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80756, Taiwan; yljane.chen@gmail.com (I.-C.C.); furtherchia@gmail.com (Y.-C.L.); eddiewu1986@gmail.com (Y.-H.W.); allenjay66@gmail.com (S.-H.L.); zenkong@gmail.com (Z.-K.D.); jhh936@yahoo.com.tw (J.-H.H.) 2 Department of Pediatrics, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan 3 Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan * Correspondence: grapepuff@gmail.com; Tel.: +886-7-312-1101 (ext. 6356) 04 5 2022 5 2022 11 9 154331 3 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Idiopathic pulmonary fibrosis (IPF) is the most common form of idiopathic interstitial pneumonia, and it has a worse prognosis than non-small cell lung cancer. The pathomechanism of IPF is not fully understood, but it has been suggested that repeated microinjuries of epithelial cells induce a wound healing response, during which fibroblasts differentiate into myofibroblasts. These activated myofibroblasts express α smooth muscle actin and release extracellular matrix to promote matrix deposition and tissue remodeling. Under physiological conditions, the remodeling process stops once wound healing is complete. However, in the lungs of IPF patients, myofibroblasts re-main active and deposit excess extracellular matrix. This leads to the destruction of alveolar tissue, the loss of lung elastic recoil, and a rapid decrease in lung function. Some evidence has indicated that proteasomal inhibition combats fibrosis by inhibiting the expressions of extracellular matrix proteins and metalloproteinases. However, the mechanisms by which proteasome inhibitors may protect against fibrosis are not known. This review summarizes the current research on proteasome inhibitors for pulmonary fibrosis, and provides a reference for whether proteasome inhibitors have the potential to become new drugs for the treatment of pulmonary fibrosis. idiopathic pulmonary fibrosis proteasome inhibitor transforming growth factor-beta the Ministry of Science and TechnologyMOST109-2314-B-037-103-MY3 Kaohsiung Medical University HospitalKMUH110-0R45 This research was funded by the Ministry of Science and Technology, grant number MOST109-2314-B-037-103-MY3, and by Kaohsiung Medical University Hospital, grant number KMUH110-0R45. ==== Body pmc1. Introduction Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually lethal disease characterized by an abnormal fibrotic response involving large areas of the lungs. Risk factors associated with IPF include smoking, environmental factors, comorbidities, and viral infections [1]. Most patients have persistent dyspnea and limited exercise tolerance resulting in a poor quality of life. Many patients develop pulmonary hypertension and are at an increased risk of pulmonary embolism and sudden cardiac death [2]. The molecular mechanisms underlying the pathogenesis and development of IPF are unclear, however molecules including chemokines, cytokines, growth factors, adenosine, glycosaminoglycans, and non-coding RNA, and cellular processes, including apoptosis, senescence, hypoxia, endothelial–mesenchymal transition, oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, and alternative polyadenylation have been linked with the development of IPF [3]. Pirfenidone and nintedanib are the mainstays of current medical treatment of IPF, however they do not completely prevent or improve lung function. It is essential to find additional drugs that can effectively reduce the pro-fibrotic maturation of lung fibroblasts, and ultimately prevent IPF progression. Understanding the molecular mechanisms of IPF will aid in drug discovery. The wound healing response induced by repeated microinjuries of epithelial cells during which fibroblasts differentiate into myofibroblasts is a major contributor to IPF. Activated myofibroblasts express α smooth muscle actin (α-SMA) and release extracellular matrix (ECM) to promote matrix deposition and tissue remodeling [4,5]. In general, the remodeling process stops once wound healing is complete; however, myofibroblasts remain active and deposit excess ECM in the lungs of patients with IPF. This leads to the destruction of alveolar tissue, the loss of lung elastic recoil, and a rapid decrease in lung function. Several studies have suggested that proteasomal inhibition can decrease the expressions of ECM proteins and metalloproteinases. In addition, proteasome inhibitors have been reported to inhibit transforming growth factor (TGF)-β1-induced collagen I and tissue inhibitor of metalloproteinase-1 [6,7]. However, the mechanisms by which proteasomal inhibition may protect against fibrosis are not fully understood. This review summarizes the current research on proteasome inhibitors for pulmonary fibrosis, and provides a reference for whether proteasome inhibitors have the potential to become new drugs for the treatment of pulmonary fibrosis. 2. Risk Factors for Idiopathic Pulmonary Fibrosis 2.1. Intrinsic Risk Factors Intrinsic risk factors including genetic susceptibility, aging, male sex, the lung microbiome, and comorbidities have been associated with the pathogenesis of IPF [8]. The susceptibility genes associated with the pathogenesis of IPF are currently classified into four categories: (1) genes related to alveolar stability (such as SFTPC, SFTPA1, SFTPA2); (2) genes related to accelerated cellular senescence by disrupting telomerase function (such as TERT, TERC, DKC1, PARN, and RTEL1); (3) genes related to host defense (such as MUC5B and TOLLIP); and (4) genes related to impaired integrity of the epithelial barrier (such as DSK) [8,9]. In addition, two genome-wide association studies reported that variants of MUC5B and TOLLIP are common [10,11]. IPF is also considered to be an age- and sex-related disease. IPF occurs mainly in elderly over 60 years of age, and the incidence and prevalence increase with age [12]. Germline mutations in telomerase (TERT) or its RNA component (TERC) are present in up to 10% of patients with IPF. Even in patients with IPF without a mutation in the telomerase gene, telomeres in peripheral blood leukocytes and in lung tissue have been reported to be shorter than those in controls [13,14]. Globally, IPF is more prevalent in men, possibly due to sex hormones. Several animal studies have indicated that male sex hormones are associated with accelerated fibrosis, and that female sex hormones may have a protective effect against pulmonary fibrosis [15,16]. However, the effects of sex hormones are organ- and species-specific, so sex hormone studies in humans are needed to determine their role in IPF. Testosterone is the most important male sex hormone. Plasma testosterone and leucocyte telomere length are significantly reduced, and testosterone is positively correlated with leucocyte telomere length in male patients with IPF [17]. Estrogen is a female sex hormone and may also contribute to the potential role of sex-specific differences in the lung. For example, TGF-β1 (a central factor in the development of pulmonary fibrosis) inhibits the expression of estrogen receptors, especially estrogen receptor alpha (ESR1) in human bronchial epithelial cells. In addition, TGF-β1 and estrogen inversely regulated the expression of several genes participating processes, such as extracellular matrix renewal, airway smooth muscle cell contraction, and calcium flux regulation [18]. The microbiome refers to the symbiotic and pathogenic microorganisms that make up the microbial ecosystem, and it has gained attention for its potential association with the initiation, perpetuation, and exacerbation of the fibrotic process in IPF [19]. Patients with IPF had a greater bacterial burden in bronchoalveolar lavage fluid (BALF) compared to controls and patients with moderate chronic obstructive pulmonary disease (COPD) [8,20]. Compared with healthy individuals, the microbiome of patients with IPF is enriched in Haemophilus, Streptococcus, Neisseiria, and Veillonella genera, which may play a causative role in acute exacerbation of IPF. Bacteria can cause epithelial alveolar injury and activate an immune cascade response due to their presence alone, the following pro-inflammatory and pro-fibrotic cascades leading to changes in lung architecture [21]. Greater bacterial burden in patients with IPF may be a biomarker for rapidly progressive disease and predicts worse survival [22]. In addition, mutations in the gene encoding MUC5B, which is essential for mucociliary clearance and in host-bacterial defense, have been associated with an increased incidence of IPF [23]. Common comorbidities in patients with IPF include gastroesophageal reflux (GER), obstructive sleep apnea, diabetes mellitus (DM), and herpesvirus infection. Repetitive lung injury from GER with subsequent secondary and chronic microaspiration has been considered as a risk factor in the pathogenesis of IPF. The prevalence of hiatal hernia on CT scan indicate that GER-related hiatal hernias occur more frequently in patients with IPF than in those with asthma or COPD [24]. The effect of anti-acid therapy on lung function changes are inconsistent [25,26], but the use of anti-acid therapy has been shown to be associated with longer survival. In addition, laparoscopic anti-reflux surgery may provide benefit on lung function of patients with IPF [27]. Obstructive sleep apnea is characterized by periodic apneas or hypopneas due to repetitive collapse of the upper airway during sleep. Despite the proximal occlusion, the respiratory muscles continue to make efforts to inspiration, so that the pleural pressure fluctuates greatly, resulting in traction microinjuries to the alveoli. These injuries result in aberrant epithelial cell activation, which, in combination with fibroblast recruitment, is involved in the pathogenesis mechanisms of IPF. [28,29]. Although definitive impacts of DM on the lungs is unclear, several studies have focused on the relationship between DM and pulmonary fibrosis. The hyperglycemia-mediated overproduction of advanced glycation end products leading to oxidative injury, and the subsequent overexpression of pro-fibrotic cytokines, fibroblast proliferation, and ECM deposition have been suggested as potential mechanisms by which DM may be a risk factor for IPF [30]. Metformin is the most commonly used oral diabetes medications, and it has been demonstrated to attenuate TGF-β1-mediated epithelial-mesenchymal transition (EMT) in vitro. In addition, metformin was also demonstrated to attenuate and reverse fibrosis in the bleomycin mouse model of pulmonary fibrosis [31,32]. Chronic viral infection, especially with members of the Herpesviridae family, cause repetitive alveolar epithelial injuries leading to the dysregulation of repair-responses, which has been proposed to be a mechanism of pulmonary fibrosis in IPF [33]. There are a greater proportion of Herpesviridae viruses have been identified in lung tissue and serum from subjects with IPF as compared to control subjects [34,35]. 2.2. Extrinsic Risk Factors As with other lung diseases, cigarette smoking is closely related to IPF. However, the mechanisms by which smoking affects the onset and progression of IPF are not fully understood. Cigarette smoking has been demonstrated to stimulate the overexpression of genes associated with EMT and a fibroblast-like phenotype in vitro [36], acceleration of telomere shortening in vivo [37], endoplasmic reticulum stress [38], and repetitive mechanical stretch [3,8]. Nicotine, the main chemical in tobacco, has addictive properties and can itself induce the production of TGF-β, an important mediator of fibrosis in IPF [39]. Consistent evidence has confirmed that cigarette smoking is associated with an increased rate of lung function loss, and that long-term smoking is an independent factor for IPF development. Moreover, IPF patients with a history of smoking have been reported to have shorter survival compared to those who have never smoked [3]. In addition, certain occupational and environmental exposure to pollutants may be associated with IPF. Some of the most common occupations involve exposure to such pollutants, including metallurgy, farming, textile work, welding, and veterinarians. For example, analyses of autopsy results from the United Kingdom [40] and Japan [41] found that metal workers had a relatively high risk of death from IPF. In addition, studies in Sweden and the United States have reported a direct relationship between exposure to wood dust and the risk of IPF. However, a significant number of IPF patients do not have any history of occupational exposure to pollutants. Some environmental factors, including dust, fibers, fumes, and particulate matter, may also contribute to the pathogenesis of IPF [3]. 3. Mechanisms of Pulmonary Fibrosis Pulmonary fibrosis is an end-stage pathological change caused by chronic repetitive alveolar injuries of various causes (such as heredity, infection, and environmental exposure), resulting in excessive ECM deposition and accumulation. In contrast to pulmonary fibrosis induced by drugs, viral infection, or acute lung injury which may be partially stabilized and reversed after treatment, IPF is persistent and irreversible even after aggressive treatment [42,43]. After the hazard has been eliminated, reversible pulmonary fibrosis gradually resolves with treatment. Almost all animal models of pulmonary fibrosis are characterized by spontaneous regression. Bleomycin-induced pulmonary fibrosis animal models have the advantages of simple modeling method, low cost, and obvious fibrotic lesions, and so they are widely used in research [44]. In general, 28 days after bleomycin injury, the fibrotic lesions gradually regress and eventually approach normal [45]. IPF is the most common progressive pulmonary fibrosis disease and is considered to be absolutely irreversible. Due to the unclear pathogenesis and lack of relevant animal models, it is difficult to elucidate the causes and mechanisms by which irreversible pulmonary fibrosis occurs. Recently, researchers showed that repetitive intratracheal instillation of bleomycin in young mice or a single dose of bleomycin in aged mice resulted in persistent pulmonary fibrosis without spontaneous resolution, and these models can provide the basis for pathogenesis studies on persistent pulmonary fibrosis [46,47,48]. The pathogenesis of persistent pulmonary fibrosis involves a complex network. Lung injury induces fibroblast recruitment, leading to collagen deposition and fibrosis. In addition, abnormal alveolar epithelial hyperplasia and the overproduction of mucin due to the incomplete differentiation of alveolar epithelia, which may cause interference with wound healing and promote pulmonary fibrosis. The loss of the endothelial phenotype and high vascular permeability cause pulmonary vascular dysfunction, which may induce abnormal vascular remodeling and further enlarges the fibrotic lesions, and then lead to the persistent and progressive development of pulmonary fibrosis. Although the pathogenesis of irreversible pulmonary fibrosis is unclear, factors associated with the development of fibrosis, including apoptosis resistance of (myo)fibroblasts, dysfunction of pulmonary vessels, cell mitochondria and autophagy, aberrant epithelial hyperplasia, and lipid metabolism disorder have been reported [48]. The wound repair process can be dysregulated in any stage of fibrosis associated with IPF. The most significant wound healing stages leading to the development of pulmonary fibrosis are represented in Figure 1. 3.1. Apoptosis Resistance of (Myo)Fibroblasts In the process of wound healing, fibroblasts are recruited to the injured area by epithelial injury-induced inflammation and differentiate into myofibroblasts induced by TGF-β. Normally, myofibroblasts gradually undergo apoptosis as the wound heals. However, in pathological conditions, persistent activation of (myo)fibroblasts leads to excessive scar hyperplasia and organ fibrosis [49]. Altered levels of apoptosis resistance in IPF (myo)fibroblasts lead to their persistent activation and pulmonary fibrosis [50]. In the fibrotic lung, elevated levels of reactive oxygen species (ROS)-related factor NADPH oxidase 4 (Nox4) induce lung fibroblasts to transform into a senescent and apoptosis-resistant phenotype, promoting pulmonary fibrosis. The expression of Nox4 has been reported to be significantly increased, and the expression of Nrf2, an antioxidant factor that can neutralize Nox4, to be significantly decreased in lung fibroblasts from patients with IPF and bleomycin-induced pulmonary fibrosis mice [51]. In IPF, dysfunction of death factor Fas signaling induces lung fibroblasts which are resistant to apoptosis and retain the pro-fibrotic phenotype and persistently activate COL1A1 and α-SMA promoters [52]. 3.2. Dysfunction of Pulmonary Vessels Pulmonary vessels are responsible for carrying blood for gas exchange and nutrient transport in a mature lung. In addition, pulmonary capillary endothelial cells (PCECs) release various cytokines to support the development, regeneration, and wound healing of the lungs. An imbalance in the abundance of pulmonary vascular endothelial cells and progenitors, as well as an imbalance between profibrotic and antifibrotic cytokines may result in aberrant vascular remodeling and alveolar capillary permeability changes. The degree of increased vascular permeability has been associated with the prognosis of patients with IPF [48,53]. Following lung injury, endothelial cells increase the expression of nitric oxide synthase 3 (NOS3) to synthesize endothelial nitric oxide synthase, which causes nitric oxide activate soluble guanylate cyclase, thereby promoting inactivation of lung fibroblasts and regression of pulmonary fibrosis [54]. Lung injury induce the activation of PCECs and the expression of chemokine receptor CXCR7, which protects alveolar epithelial cells from injury by inhibiting Jag1-Notch pathway-mediated EMT and pulmonary fibrosis. However, the degeneration of pulmonary vessels causes the reduction in vessel density, the loss of the endothelial phenotype and unable to encode NOS3 by endothelial cells, thereby resulting in persistent pulmonary fibrosis. Chronic lung injury caused by repetitive bleomycin instillation has been shown to suppress the expression of CXCR7 and promote the recruitment of macrophages around vessels [48,55], which stimulates PCECs to increase Wnt/β-catenin-dependent Jag 1 (one Notch ligand), thereby promoting persistent pulmonary fibrosis through the sustained activation of Notch signaling in perivascular fibroblasts [48,55]. 3.3. Mitochondrial Dysfunction Mitochondrial dysfunction is considered an important pathological feature of pulmonary fibrosis. Peroxisome proliferator-activated receptor gamma co-activator 1-alpha (PGC1α) is a transcriptional coactivator. In addition to regulating mitochondrial biogenesis, oxidative phosphorylation, and ROS detoxification, PGC1α also mediates the regression of fibrotic lesions [56]. The stable inhibition of PGC1α has been demonstrated to reduce mitochondrial mass and function in IPF lung fibroblasts [57]. Mitochondrial dysfunction induces persistent pulmonary fibrosis through activating a pro-fibrotic fibroblast phenotype and promoting the senescence of adjacent cells via a paracrine mechanism. In addition, PTEN-induced putative kinase 1 (PINK1) is a key regulator of mitochondrial function, and is low expression in aged-related lungs and IPF lungs [48,58]. In addition, a lower expression of PINK1 has been shown to cause mitochondrial dysfunction in type II alveolar epithelial cells (ATIIs), leading to endoplasmic reticulum stress and mitophagy dysfunction. Furthermore, a deficient expression of PINK1 in ATIIs can induce the release of profibrotic factors. 3.4. Autophagy Dysfunction Autophagy is an important cytoprotective mechanism that can maintain cellular homeostasis and regulate redox balance. In fibroblasts and alveolar epithelia, decreased autophagy induces activation of lung fibroblasts and promotes pulmonary fibrosis. Moreover, autophagy dysfunction induces apoptosis-resistant lung fibroblasts and persistent pulmonary fibrosis by activating the mammalian target of rapamycin signaling pathway in IPF lung fibroblasts. In lung endothelial cells, impaired autophagic flux induces the changes of endothelial structure and affects the progression of pulmonary fibrosis, which may be accompanied by a loss of the autophagy gene ATG7 [59,60]. 3.5. Aberrant Epithelia Hyperplasia and Dysfunction The alveolar epithelium is composed of type I alveolar epithelial cells (ATIs) and ATIIs [61]. Histological analysis showed that more ATIIs in the lungs of patients with IPF or bleomycin-induced pulmonary fibrosis mice compared with controls, particularly prominent in areas close to fibrobastic foci consisting of small dome-shaped collections of spindle-forming (myo)fibroblasts within a myxoid-appearing matrix [62]. Specimens from the control group showed normal alveolar characteristics similar to ATIs and ATIIs lined with thin-walled alveolar septa. Specimens from patients with IPF present with the pathological pattern of usual interstitial pneumonia (UIP), including patchy fibrosis and architectural distortion and fibroblast foci [63]. In normal lungs, ATIs cover over 90% of the alveolar surface. During lung injury, ATIs are susceptible to damage and even death. ATIIs are regarded as stem cells of the alveolar epithelium to participate alveolar epithelial repair [61,64]. Lung injury induces the activation and proliferation of surfactant-producing ATIIs to form wound clots, which are constructed by hyperplasia of ATIIs covering exposed alveolar surfaces, the activation of local coagulation pathways, and initiation of provisional matrix formation [65]. Hyperplastic ATIIs regulate apoptosis and have the ability to transdifferentiate into ATIs to re-establish a fully functional alveolar epithelium [66]. During normal wound healing, lung tissue eventually returns to its original structure and function as the provisional matrix gradually dissipates. However, persistent disturbance of the epithelial basement membrane following extensive damage may lead to alveolar collapse and ATIIs fail to re-epithelialize [67]. This results in the initiation of an abnormal wound repair response, whereby epithelial cells, mainly ATIIs, release pro-fibrotic cytokines, growth factors, and other chemokines at the site of injury to promote the activation and proliferation of (myo)fibroblasts and to increase ECM stiffness in IPF [68,69]. 3.6. Lipid Metabolism Disorder The balance of lipid metabolism is critical for maintaining the structure and function of the alveolar epithelium. Excessive accumulation of cholesterol leads to alveolar collapse and injury [70]. Elongation of long-chain fatty acids family member 6 and stearoyl CoA desaturase 1 are lipid metabolism-related molecules, and levels of these molecules have been reported to be reduced in IPF lungs [71,72]. In addition, suppression of these genes in mice has been shown to increase fibrosis susceptibility. Sequencing data have revealed that the genes and signaling pathways related to lipid metabolism are down-regulated in the lungs of IPF patients and in aged mice with bleomycin injury [73,74]. 3.7. Transforming Growth Factor-Beta in Idiopathic Pulmonary Fibrosis Growth factors, such as TGF-β, insulin-like growth factor-1 (IGF-1), binding proteins, tumor necrosis factor-alpha (TNF-α), platelet-derived growth factor (PDGF), interleukins (ILs), endothelin-1, connective tissue growth factor (CTGF), vascular endothelial growth factor (VEGF), and fibroblast growth factor (FGF) have been shown to be involved in the pathology of IPF at a molecular level. Of these factors, TGF-β has been identified as a central factor in the development of pulmonary fibrosis [3]. Alveolar epithelial damage leads to the recruitment of fibroblasts, which are activated by TGF-β, resulting in collagen deposition and organ fibrosis. TGF-β is a superfamily of more than 35 structurally different protein isoforms, of which TGFβ-1, TGFβ-2, and TGFβ-3 are present only in mammals and are known to act as major pro-fibrotic factors in the pathogenesis of fibrosis through multiple pathways, and to exhibit different phenotypes and functions [2,75]. TGF-β was named after the discovery of the protein TGFβ-1, which is highly expressed in IPF [6]. In fibrosis, TGF-β has both stimulatory and inhibitory properties. TGFβ-1 is involved in the promotion and induction of fibrosis in various tissues. In addition, TGF-β1 is the only isoform of TGF-β to affect the function of the endocrine system. In IPF, TGF-β acts as a pro-fibrotic factor in the process of EMT through both Smad-dependent and Smad-independent pathways. If TGF-β is activated through the Smad-dependent pathway, it affects the genetic level of α-SMA, collagen, and PAI-1 [76]. In addition, TGF-β causes the upregulation of IGF in fibrotic tissue and fibroblast cells, resulting in altered lung function. TGF-β is a pleiotropic cytokine which damages lung tissue, and plays a role in lung tissue development and in maintaining homeostasis in other tissues of the lungs [77,78]. 3.8. Inflammation Inflammation and changes in innate and adaptive immune responses have also been implicated in the development of IPF. Inflammatory cells in the lungs of patients with IPF have been shown to produce increased levels of ROS, which can drive the production of pro-inflammatory cytokine, including IL-1β [67]. The secretion of IL-1β has been associated with the progression of fibrosis by enhancing the expressions of the inflammatory mediators IL-6 and TNF-α, disrupting alveolar structure, and increasing lung fibroblasts, as well as collagen deposition [79]. In addition, IL-1β has been shown to increase lung infiltration by neutrophils and macrophages, and to increase the expressions of matrix metalloproteinase and chemokine ligands [80]. IL-1β in BALF has also been shown to stimulate the release of the pro-fibrotic cytokines TGF-1 and PDGF [79]. The pro-inflammatory cytokine IL-17A is expressed by CD4+ T-helper (TH-17) cells, and has been linked with enhanced the recruitment of neutrophil and TGF- and IL-1β-mediated fibrosis [81]. In addition, increased percentage of neutrophil in BALF is considered to be a prognostic predictor of early mortality in patients with IPF [82]. TH-1 effector T cells are thought to induce anti-fibrotic activities through the production of interferon-γ [83], and TH-2 effector T cells are thought to promote fibrosis through the production of some cytokines, such as IL-4, IL-5, and IL-13 [84,85]. 4. The Mainstay of Medication and The Potential of Proteasome Inhibitors for IPF Pirfenidone and nintedanib were approved by the FDA for the treatment of IPF in 2014 based on positive phase 3 trials, and they are currently the mainstay of medical therapy for IPF, with acceptable safety and tolerability. With the approval of pirfenidone and nintedanib for patients with mild-to-moderate IPF, early diagnosis is a prerequisite for earlier treatment. These drugs help to prevent further scarring and slow the progression of the disease, but do not cure IPF. In addition, there are insufficient data on proven effective treatments for severe IPF, although it may also be because patients with severe IPF usually not participate in randomized, prospective, multicenter, international trials [86]. It is necessary to find novel effective treatment strategy for IPF. New drugs and combinations of pirfenidone or nintedanib with other drugs have subsequently been developed. For example, the autotaxin-lysophosphatidic acid (ATX/LPA) pathway, CTGF, pentraxin-2, G protein-coupled receptor agonists/antagonists, αvβ6 integrin, and galectin-3 are novel targets that have been shown to be effective in phase 2 clinical trials [18]. In addition, several studies have indicated that proteasome inhibition can provide anti-fibrotic effects in different tissues and in several experimental mouse models. However, the effect of proteasome inhibitors on pulmonary fibrosis remains controversial. The mechanisms mediating these anti-fibrotic effects have yet to be fully elucidated, however they appear to involve the attenuation of pro-fibrotic TGF-β signaling. In the following sections, we review relevant studies on the effect of proteosome inhibitors on pulmonary fibrosis, and evaluate the potential of using proteasome inhibitors in the treatment of pulmonary fibrosis. A number of different treatments, with advantages and disadvantages, have been used to induce pulmonary fibrosis in animals. Although none of them induce the same pathology as human IPF, each model recapitulates some key features of IPF and provide a convenient platform to study collagen regulation in disease settings. Agents for inducing pulmonary fibrosis in animals include etiologic agents (such as asbestos, silica, and radiation) and chemical agents (such as bleomycin, monocrotaline, fluorescein isothiocyanate, oxidants, and phorbol myristate acetate). The bleomycin-induced lung fibrosis model is the most widely used [87]. Bleomycin is an anticancer drug that induces DNA damage in target cells, and is usually administered as a single dose in saline or PBS by intratracheal, intranasal, intraperitoneal, oropharyngeal, or intravenous routes. A continuous or repetitive delivery method of bleomycin induce more fibrosis in the lung, and fibrotic phenotype more similar to IPF than single bleomycin delivery methods [47]. Selecting an appropriate mouse strain is important because there is strong evidence that genetic background can influence the degree of pulmonary fibrosis following bleomycin treatment. C57BL/6J mice are the most commonly used strain for bleomycin treatment, because of the reproducibly high levels of inducible lung collagen deposition for at least 12 weeks [88]. 4.1. Pirfenidone and Nintedanib Pirfenidone is an anti-fibrotic and anti-inflammatory drug which reduces fibroblast proliferation and the accumulation of collagen [89]. Pirfenidone should be taken three times daily with meals, with a target dose of 801 mg, which is usually achieved within two weeks. The details are a dose of 267 mg administered three times a day (801 mg/day) for 1 week, a dose of 534 mg administered three times a day (1602 mg/day) for 1 week, and then a dose of 801 mg administered three times daily thereafter (2403 mg/day). Baseline liver enzyme levels should be measured prior to taking pirfenidone, and subsequently monitored at monthly for 6 months, and then every 3 months thereafter. Pirfenidone should not be administered to patients with Child-Pugh Class C hepatic impairment or those requiring dialysis [90,91]. Side effects of pirfenidone include rash, photosensitivity, and gastrointestinal discomfort. Therefore, patients taking pirfenidone are advised to avoid exposure to sunlight or use sunscreen and clothing to protect from sun exposure. In addition, if gastrointestinal symptoms persist with pirfenidone with meals, antacids and antiemetics may be prescribed. However, omeprazole may modulate pirfenidone level, so omeprazole treatment should be avoided in patients taking pirfenidone. If side effect symptoms or hepatotoxicity occur, the dose can be reduced, or temporarily discontinued and then reintroduced after a few weeks using a slower dose titration. [92]. Because pirfenidone is mainly metabolized by cytochrome P450 1A2 (CYP1A2) enzymes, patients should avoid the concomitant use of other CYP1A2 inhibitors (e.g., fluvoxamine and ciprofloxacin) or inducers (e.g., tobacco, omeprazole, and rifampicin) [93]. Nintedanib is a small-molecule inhibitor of receptor tyrosine kinases, including FGF receptor, PDGF receptor, and VEGF receptor [94]. Nintedanib should be taken orally 150 mg twice daily, and liver enzymes should be monitored monthly for 3 months and every 3 months thereafter. In addition, nintedanib treatment is not recommended for patients with moderate or severe liver impairment (Child-Pugh Class B or C) [90]. Side effects of nintedanib include diarrhea and nausea, which can often be effectively controlled with antidiarrheal medications or antiemetics [95,96]. As with pirfenidone treatment, when side effect symptoms or hepatotoxicity occur, the dose can be reduced, or temporarily discontinue and reintroduce after a few weeks using a slower dose titration. Since nintedanib is a substrate of P-glycoprotein (P-gp) and CYP3A4, the co-administration with oral doses of P-gp and CYP3A4 inhibitors (e.g., ketoconazole and erythromycin) should be avoided, so as not to increase exposure to nintedanib [97]. Multiple trials have demonstrated that both pirfenidone and nintedanib were associated with a reduction in mortality compared to placebo, and could effectively reduce lung volume loss, regardless of the initial reported forced vital capacity and diffusing capacity of the lung for carbon monoxide [98,99]. Of note, nintedanib may increase the risk of bleeding by inhibiting VEGF receptor signal transduction, so pirfenidone may be a better option than nintedanib when patients receive full-dose anticoagulation or dual antiplatelet therapy [94,100]. However, the higher proportion of bleeding in clinical trials of patients taking nintedanib compared to placebo were minor events, such as bruising or epistaxis. Therefore, nintedanib may be selected over pirfenidone based on a patient’s inability to avoid sun exposure, and in those with pre-existing dermatologic conditions. The co-administration of nintedanib and pirfenidone has been shown to have a manageable safety and tolerability profile in patients with IPF, with no relevant effects on pharmacokinetic drug–drug interactions [90,101,102]. However, clinical trials are still needed to assess whether this combination can improve efficacy. 4.2. Overview of Proteasome Inhibitors and the Effects of Proteasome Inhibitors in Patients with Pulmonary Fibrosis The ubiquitin-proteasome system is responsible for the programmed degradation of most intracellular proteins. Proteins are targeted for proteasomal degradation by linkage to polyubiquitin chains as a degradation signal. Polyubiquitination proceeds along a cascade of enzymatic reactions involving E1, E2, and E3 enzymes which transfer activated ubiquitin to lysine residues of substrate proteins. The polyubiquitinated proteins are then transferred to and hydrolyzed by proteasomes [103,104]. Proteasomes are multimeric protease complexes and the center of cellular protein degradation, thereby activating or shutting down some pathways. The 26S proteasome is a multicatalytic enzyme complex, comprising a 20S core catalytic complex with 19S regulatory subunits at each end. The 20S core catalytic complex contains three active sites residing in the β5, β2, and β1 subunits that cleave polypeptides after different amino acids, which are named chymotrypsin-like (CT-L), trypsin-like (T-L), and caspase-like (C-L) active sites, respectively [105]. Proteasomes are present in all cells, but they are relatively abundant in multiple myeloma cells, making that disease a target for proteasome inhibitors. Many proteasome inhibitors are currently in development. Although several protease inhibitors are developed, the molecular mechanism has not been fully studied. These compounds have commonly been reported to be inhibitors of the NF-κB pathway. However, the regulation of the NF-κB pathway by the same proteasome inhibitor may still vary depending on the cell type. In addition, proteasome inhibitors have been reported to induce apoptosis by regulating pathways other than NF-κB. These compounds incorporate different chemical warheads to inhibit the catalytic activity of the proteasome. Currently, proteasome inhibitors used in research or clinical treatment for multiple myeloma were listed in Table 1. Several studies are also actively investigating the effectiveness of proteasome inhibitors in various diseases including pulmonary fibrosis. 4.2.1. MG-132 The first synthetic proteasome inhibitor contained a peptide backbone with an aldehyde on its C terminus forming a reversible complex with the active site threonine. MG-132, originally named ZLLLal, is a modified version with a different peptide backbone, and it is more potent and cell permeable [106]. Studies indicated that MG-132 suppress NF-κB activity in various cells by inducing nuclear translocation and accumulation of IκBα, which then binds with NF-κB p50/65 and interferes DNA binding activity of NF-κB [107,108]. The combination therapy of MG-132 and GSK-470, a PDK1 inhibitor, induce apoptosis by inhibiting phosphorylation of mTOR and AKT, and inducing nuclear accumulation of PTEN in multiple myeloma cells [109]. Myocardial remodeling is an adaptive response of the myocardium to several forms of stress, ultimately leading to cardiac fibrosis, left ventricular dilation, and loss of contractility. MG-132 has been shown to suppress the activity of matrix metalloproteinases (MMPs) and the RNA expressions of MMPs and collagens in rat cardiac fibroblasts. In addition, MG-132 treatment over 12 weeks was shown to effectively suppress the expressions of MMPs and collagens in spontaneously hypertensive rats, resulting in a marked reduction in cardiac fibrosis compared with control animals [6,110]. In NRK-49F cells (rat renal interstitial fibroblasts), MG-132 was shown to downregulate the expressions of CTGF, α-SMA, fibronectin and collagen III simulated by TGF-β1 [111]. Tank binding protein kinase-1 (TBK1) is a kinase that was recently identified as a candidate regulator of fibroblast activation. Reducing the activity or expression of TBK1 has been shown to result in a 40–60% reduction in smooth muscle actin stress fiber levels and a 50% reduction in the deposition of the ECM components collagen I and fibronectin in TGF-stimulated normal and IPF fibroblasts. In addition, yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are related mechanosensory proteins known to regulate fibroblast activation [112]. TBK1 stabilizes YAP/TAZ levels by reducing YAP/TAZ proteasome degradation, and TBK1 knockdown or inhibition has been shown to reduce the total and nuclear protein levels of YAP/TAZ. The treatment of fibroblasts with MG-132 has been shown to result in increased YAP/TAZ levels in both TBK1 siRNA and non-targeting siRNA control-treated cells [113]. These results suggest that proteasome inhibitors may promote fibroblast activation by reducing YAP/TAZ proteasome degradation. 4.2.2. Bortezomib Bortezomib, a dipeptide boronic acid derivative, is the first proteasome inhibitor to receive FDA approval for the treatment of multiple myeloma and other plasma cell malignancies, and it has been associated with significant improvements in response rates and overall survival in front-line and relapsed/refractory settings [104,114]. Numerous clinical trials of bortezomib focusing on its efficacy in other tumors, in combination with other drugs, and for non-cancer applications have also been conducted [106]. Bortezomib is formulated as a mannitol ester and administered via intravenous or subcutaneous routes. Bortezomib is rapidly cleared from the body; however, accumulation occurs after repeated dosing [115]. Many studies indicated that bortezomib stabilized the inhibitor IκB in cytosol leading to reduced activation of NF-κB [116,117]. Bortezomib also inhibits cyclin turnover, which affects cyclin-dependent kinase (CDK) activity. This may be particularly relevant to the action of bortezomib for treating mantle cell lymphoma, as which often caused by a gene translocation that causes the overexpression of cyclin D1 [118]. In addition, bortezomib affects telomerase activity [119], kinases such as JNK, tumor suppressors such as p53, and the Bcl-2 family of proteins has been reported [106]. Several studies have investigated the potential of bortezomib for the treatment of fibrosis. In a mouse study of bile duct ligation-induced cirrhosis, a single dose of bortezomib was given three days after bile duct ligation, which significantly reduced the expressions of α-SMA and collagen, and attenuated the severity of histological fibrosis [120]. In a murine model of thrombopoietin-induced myelofibrosis, reduced levels of TGF-β1 in bone marrow fluid and impaired development of spleen fibrosis after bortezomib treatment for four weeks have also been demonstrated. Moreover, bortezomib treatment impaired the development of osteosclerosis and increased one year survival rate from 8 to 89% after 12 weeks of treatment [121]. In both human dermal fibroblasts and murine fibroblasts, bortezomib has been shown to reduce collagen I mRNA expression [7]. In addition, bortezomib effectively inhibit TGF-β1-mediated target gene expression by inhibiting Smads activated transcription in primary human lung fibroblasts from normal individuals and patients with IPF, and in skin fibroblasts from patients with scleroderma. This response is due to increased abundance and activity of peroxisome proliferator activated receptor γ, a Smad-mediated transcriptional repressor [122]. In addition, bortezomib inhibits the pro-fibrotic activity induced by BALF from patients with pulmonary fibrosis. Notably, bortezomib treatment is effective even with bleomycin-induced acute lung injury peaking and TGF-β1 activation in the lung, which differs from other therapeutic strategies shown to inhibit bleomycin-induced pulmonary fibrosis [122]. However, some studies have raised concerns. For example, bortezomib has been shown to inhibit the chymotryptic activity of proteasomes but to enhance JNK and TGF-β signaling, which has been shown to promote fibrosis in vivo. Moreover, bortezomib failed to prevent bleomycin-induced lung inflammation and fibrosis or attenuate skin fibrosis in TSK-1/1 mice [7]. Furthermore, another study indicated that the therapeutic administration of bortezomib could diminish the severity of pulmonary fibrosis, and that this effect was independent of proteasome inhibition, and rather attributable to the induction of dual-specificity protein phosphatase 1 [123]. 4.2.3. Carfilzomib Carfilzomib, originally derived from the naturally occurring epoxomicin, received initial FDA approval for relapsed and refractory myeloma in 2012, and it is the only approved drug with a reactive epoxide pharmacophore, a feature previously considered unsuitable for drug development. Carfilzomib, such as bortezomib, is administered intravenously and is a useful treatment to overcome some forms of bortezomib resistance [124]. Carfilzomib has been demonstrated to have fewer off-target effects and stronger proteasome inhibition effects relative to bortezomib [125,126]. In addition, the reported rates of peripheral neuropathy are >60% lower in patients receiving carfilzomib compared to those receiving bortezomib. In chronic lymphocytic leukemia cells, carfilzomib potently induces apoptosis by caspase-dependent and occurs irrespective of p53 status. In addition, carfilzomib promotes atypical activation of NF-κB, which is manifested by loss of cytoplasmic IkBα, phosphorylation of IκBα and DNA binding of NF-κB p50/p65, without subsequent increases in canonical NF-κB target gene transcription [127]. 4.2.4. Oprozomib Oprozomib is a truncated derivative of carfilzomib, and it is the first orally bioavailable epoxyketone-based proteasome inhibitor. Orally bioavailable proteasome inhibitors could allow for more flexible dosing and be more convenient for patients. In addition, oral oprozomib was shown to delay tumor growth in a myeloma xenograft with efficacy similar to intravenous carfilzomib [128]. Both oprozomib and carfilzomib have been shown to inhibit the chymotrypsin-like activity of proteasomes and induce cell death in myeloma cell lines and primary cells from patients. In addition, oprozomib has been shown to decrease the viability of multiple myeloma cell lines and primary tumor cells from patients without affecting the viability of normal hematopoietic cells [124]. One study reported that local lung-specific treatment with oprozomib resulted in an antifibrotic effect without systemic toxicity in a mouse model of pulmonary fibrosis. Oprozomib was less toxic than bortezomib and was highly selective for the chymotrypsin-like active site of proteasomes. In addition, oprozomib treatment eliminated the expression of collagen-I and α-SMA induced by TGF-β in primary mouse lung fibroblasts. However, locally applied oprozomib failed to reduce fibrosis in bleomycin-challenged mice, and resulted in accelerated weight loss and increased mortality [105]. Specifically targeting activated proteasome complexes in the fibrotic lung to the right degree and at the right time point may be necessary for the treatment of pulmonary fibrosis with proteasome inhibitors. 4.2.5. Ixazomib Ixazomib was the first oral proteasome inhibitor approved by the FDA for the treatment of relapsed multiple myeloma in 2015 [125]. It preferentially inhibits CT-L activities of the 20S proteasome, with 10- and 1000-fold less potency for C-L and T-L activities, respectively. Ixazomib is similar in selectivity and potency to bortezomib, however the proteasome binding kinetics of these two molecules are different. Both ixazomib and bortezomib exhibit time-dependent reversible proteasome inhibition, however, the proteasome dissociation half-life (t1/2) of ixazomib is about 6-fold faster than that of bortezomib (t1/2 of 18 and 110 min, respectively) [129]. In addition, preliminary pharmacokinetic results indicate that the fixed-dose administration of ixazomib is feasible, making oral administration of the drug very convenient. 4.2.6. Delanzomib As with bortezomib, delanzomib is a reversible proteasome inhibitor of the peptide boronic acid class, and it exhibits similar potency against proteolytic activities of proteasomes in human erythrocytes, multiple myeloma, and HeLa cancer cells. However, delanzomib has been shown to be active as an oral formulation in preclinical studies, and delanzomib has shown greater and more sustained dose-related inhibition of tumor proteasome activity than bortezomib following the maximum tolerated dose of bortezomib or delanzomib in severe combined immunodeficiency mice. In addition, delanzomib has shown similar or better single-agent antitumor activity in primary multiple myeloma plasma cells in vitro compared to bortezomib [130]. 4.2.7. Marizomib Marizomib (NPI-0052, Salinosporamide A) is an orally active, small molecule proteasome inhibitor derived from Salinospora tropica (marine actinomycete bacteria) [131]. Unlike other peptide-based proteasome inhibitors, marizomib has a β-lactone-γ-lactam bicyclic ring structure without a linear peptide backbone. In multiple myeloma cells and purified proteasomes, marizomib has been shown to irreversibly inhibit proteasome activity at nanomolar concentrations [132]. In addition, marizomib can target proteasomes more broadly, as it inhibits all three major proteolytic activities (preferentially inhibiting CT-L activity, followed by T-L activity and to a much lesser extent C-L activity) [133,134,135]. Marizomib has been tested in phase I, II, and III clinical trials in a variety of cancers, including refractory multiple myeloma, leukemia, lymphoma, glioblastoma, and malignant glioma. The results from these trials have shown that marizomib either as monotherapy or in combination with pomalidomide is well-tolerated and demonstrates promising activity in relapsed and refractory multiple myeloma [131]. Although the molecular mechanism of newly developed next generation of proteasome inhibitors still needs to be investigated. It has been reported that bortezomin, carfilzomib, and marizomib can inhibited the activity of non-canonical NF-κB signaling pathway and induced the apoptosis in cytarabine-resistant HL60 Cells [136]. Bortezomin and marizomib decrease the viability of pulmonary arterial smooth muscle cells by restoring mitofusin-2 expression under hypoxic conditions [137]. 5. Challenges in the Treatment of Pulmonary Fibrosis with Proteasome Inhibitors Peripheral neuropathy is a common and often dose-limiting toxic side effect of many active chemotherapeutic agents [138]. The National Cancer Institute lists chemotherapy-induced peripheral neuropathy as a reason for discontinuing treatment [139]. Peripheral neuropathy refers to damage, inflammation, or degeneration of peripheral nerves. The main symptoms of peripheral neuropathy are numbness, tingling, paresthesia, dysesthesia, pain, and weakness [140]. Bortezomib has been reported to induce autonomic peripheral neuropathy, causing neuropathic pain, orthostatic hypotension, bradycardia, sexual dysfunction, and constipation. Therefore, low toxicity is an important requirement for the development of the next generation of proteasome inhibitors [140,141]. In addition, proteasome inhibitors targeting a single active site have been shown to lead to compensatory activation of other active sites resulting in drug resistance, so that efficient inhibition of more than one active site is required to induce cell death [105,131,142]. The development of irreversible pan-proteasome inhibitors may be an effective way to overcome drug resistance. Currently, the only irreversible pan-proteasome inhibitor of T-L activity, CT-L activity, and C-L activity in development is marizomib [131], and clinical trials have indeed shown that marizomib is well-tolerated with promising activity in relapsed and refractory multiple myeloma [131,143]. In conclusion, current evidence indicates that proteasome inhibitors have anti-fibrosis effects, such as reducing fibroblast proliferation, differentiation into myofibroblasts, and collagen synthesis. However, the in vivo efficacy of proteasome inhibitors in pulmonary fibrosis and the dependence on proteasome inhibition have yet to be conclusively defined. Based on our review of the current research, the bottlenecks encountered in the use of proteasome inhibitors are as follows: (1) proteasome inhibitors cause anti-fibrosis effects through mechanisms other than proteosome inhibition [123]; (2) the activity of proteasome inhibitors leads to the accumulation of several proteins that are degraded by the proteasome machinery, but does not target a single protein [136]; (3) several proteasome inhibitors only inhibit one activity site of proteasomes, which causes compensatory activation of other activity sites, resulting in drug resistance [131,136]; and (4) toxicity of proteasome inhibitors causes side effects, making them difficult to apply in vivo [140,141]. At present, studies associated anti-fibrotic effect of proteasome inhibitors focus on fibroblasts, however, several studies demonstrated that the importance of proteasome function in maintaining ATIIs homeostasis [144,145]. In ATIIs of mice, partial deletion of RPT3, which promotes assembly of active 26S proteasome, leads to augmented cell stress and cell death. Acute loss of ATIIs resulted in alveolar surfactant depletion and alveolar epithelial barrier disruption leading to lethal acute respiratory distress syndrome [144]. These results point to the importance of proteasome function in maintaining ATIIs homeostasis and this issue requires attention in the development of proteasome inhibitor treatment for IPF. Understanding the complex mechanisms of proteasome inhibitors, developing irreversible pan-proteasome inhibitors, and reducing the toxicity of proteasome inhibitors are important issues that must be solved before proteasome inhibitors are used in the treatment of pulmonary fibrosis. An overview of risk factors and treatment for IPF is shown in Figure 2. Acknowledgments Not applicable. Author Contributions Conceptualization, I.-C.C., Y.-C.L., Y.-H.W., S.-H.L., Z.-K.D., J.-H.H. and Y.-H.T.; Funding acquisition, I.-C.C., Z.-K.D., J.-H.H. and Y.-H.T.; Visualization, Y.-C.L., Y.-H.W. and S.-H.L.; Writing—original draft, I.-C.C. and Y.-H.T.; Writing—review and editing, I.-C.C. and Y.-H.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Overview of wound healing leading to the development of fibrosis. Epithelial cell injury induces the secretion of inflammatory mediators and triggers platelet activation, thereby increasing vascular permeability and the recruitment of leukocytes. These inflammatory cells release pro-fibrotic cytokines, such as TGF-β, which mediate activation and recruitment of fibroblasts, differentiation of myofibroblasts, and release of ECM components, thereby promoting wound healing. Abnormal wound repair responses lead to the irreversible and excessive scar tissue within the lungs of patients with IPF. Figure 2 Overview of risk factors and treatments for idiopathic pulmonary fibrosis. The risk factors for idiopathic pulmonary fibrosis (IPF) include intrinsic risk factors (such as genetic susceptibility, aging, male sex, the lung microbiome, and comorbidities) and extrinsic risk factors (such as cigarette smoking and environmental exposure). Pirfenidone and nintedanib are the mainstay of medical therapy for IPF. Although the role of proteasome inhibitors in pulmonary fibrosis remains uncertain, they have been reported to potentially have anti-fibrotic effects. cells-11-01543-t001_Table 1 Table 1 Examples of proteasome inhibitor classes. Compound FDA Approval Class Effect Activity Administration MG-132 just used in laboratories peptide aldehydes reversible T-L, CT-L N/A Bortezomib FDA approval in 2003 boronic acid reversible CT-L IV, SC Carfilzomib FDA approval in 2012 epoxyketones irreversible CT-L IV Oprozomib currently in clinical trials epoxyketones irreversible CT-L Oral Ixazomib FDA approval in 2015 boronic acid reversible CT-L IV, Oral Delanzomib currently in clinical trials boronic acid reversible CT-L IV, Oral Marizomib currently in clinical trials salinosporamide irreversible T-L, CT-L, C-L IV, Oral T-L, trypsin-like activity; CT-L, chymotrypsin-like activity; C-L, caspase-like activity. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. García-Sancho C. Buendía-Roldán I. Fernández-Plata M.R. Navarro C. Pérez-Padilla R. Vargas M.H. Loyd J.E. Selman M. Familial pulmonary fibrosis is the strongest risk factor for idiopathic pulmonary fibrosis Respir. Med. 2011 105 1902 1907 10.1016/j.rmed.2011.08.022 21917441 2. Krishna R. Chapman K. Ullah S. Idiopathic Pulmonary Fibrosis StatPearls Publishing Treasure Island, FL, USA 2022 3. Phan T.H.G. Paliogiannis P. Nasrallah G.K. Giordo R. Eid A.H. Fois A.G. Zinellu A. Mangoni A.A. Pintus G. Emerging cellular and molecular determinants of idiopathic pulmonary fibrosis Cell. Mol. LifeSci. 2021 78 2031 2057 10.1007/s00018-020-03693-7 33201251 4. Bitterman P. Fibroblast-Matrix Cross-Talk in Idiopathic Pulmonary Fibrosis: Cross-Links at the Crossroads Am. J. Respir. Cell Mol. Biol. 2018 58 547 548 10.1165/rcmb.2017-0402ED 29714627 5. Kendall R.T. Feghali-Bostwick C.A. Fibroblasts in fibrosis: Novel roles and mediators Front. Pharmacol. 2014 5 123 10.3389/fphar.2014.00123 24904424 6. Weiss C.H. Budinger G.R. Mutlu G.M. Jain M. Proteasomal regulation of pulmonary fibrosis Proc. Am. Thorac. Soc. 2010 7 77 83 10.1513/pats.200906-055JS 20160152 7. Fineschi S. Bongiovanni M. Donati Y. Djaafar S. Naso F. Goffin L. Argiroffo C.B. Pache J.C. Dayer J.M. Ferrari-Lacraz S. In vivo investigations on anti-fibrotic potential of proteasome inhibition in lung and skin fibrosis Am. J. Respir. Cell Mol. Biol. 2008 39 458 465 10.1165/rcmb.2007-0320OC 18458239 8. Zaman T. Lee J.S. Risk factors for the development of idiopathic pulmonary fibrosis: A review Curr. Pulmonol. Rep. 2018 7 118 125 10.1007/s13665-018-0210-7 31588408 9. Kaur A. Mathai S.K. Schwartz D.A. Genetics in Idiopathic Pulmonary Fibrosis Pathogenesis, Prognosis, and Treatment Front. Med. 2017 4 154 10.3389/fmed.2017.00154 10. Fingerlin T.E. Murphy E. Zhang W. Peljto A.L. Brown K.K. Steele M.P. Loyd J.E. Cosgrove G.P. Lynch D. Groshong S. Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis Nat. Genet. 2013 45 613 620 10.1038/ng.2609 23583980 11. Noth I. Zhang Y. Ma S.F. Flores C. Barber M. Huang Y. Broderick S.M. Wade M.S. Hysi P. Scuirba J. Genetic variants associated with idiopathic pulmonary fibrosis susceptibility and mortality: A genome-wide association study Lancet Respir. Med. 2013 1 309 317 10.1016/S2213-2600(13)70045-6 24429156 12. Leuschner G. Klotsche J. Kreuter M. Prasse A. Wirtz H. Pittrow D. Frankenberger M. Behr J. Kneidinger N. Idiopathic Pulmonary Fibrosis in Elderly Patients: Analysis of the INSIGHTS-IPF Observational Study Front. Med. 2020 7 601279 10.3389/fmed.2020.601279 33313046 13. Stuart B.D. Lee J.S. Kozlitina J. Noth I. Devine M.S. Glazer C.S. Torres F. Kaza V. Girod C.E. Jones K.D. Effect of telomere length on survival in patients with idiopathic pulmonary fibrosis: An observational cohort study with independent validation Lancet Respir. Med. 2014 2 557 565 10.1016/S2213-2600(14)70124-9 24948432 14. Snetselaar R. van Batenburg A.A. van Oosterhout M.F.M. Kazemier K.M. Roothaan S.M. Peeters T. van der Vis J.J. Goldschmeding R. Grutters J.C. van Moorsel C.H.M. Short telomere length in IPF lung associates with fibrotic lesions and predicts survival PLoS ONE 2017 12 e0189467 10.1371/journal.pone.0189467 29281671 15. Voltz J.W. Card J.W. Carey M.A. Degraff L.M. Ferguson C.D. Flake G.P. Bonner J.C. Korach K.S. Zeldin D.C. Male sex hormones exacerbate lung function impairment after bleomycin-induced pulmonary fibrosis Am. J. Respir. Cell Mol. Biol. 2008 39 45 52 10.1165/rcmb.2007-0340OC 18276795 16. Lekgabe E.D. Royce S.G. Hewitson T.D. Tang M.L. Zhao C. Moore X.L. Tregear G.W. Bathgate R.A. Du X.J. Samuel C.S. The effects of relaxin and estrogen deficiency on collagen deposition and hypertrophy of nonreproductive organs Endocrinol. 2006 147 5575 5583 10.1210/en.2006-0533 17. Fang C. Huang H. Zhang Q. Wang N. Jing X. Guo J. Ferianc M. Xu Z. Relation between sex hormones and leucocyte telomere length in men with idiopathic pulmonary fibrosis Respirol. 2020 25 1265 1273 10.1111/resp.13871 18. Smith L.C. Moreno S. Robertson L. Robinson S. Gant K. Bryant A.J. Sabo-Attwood T. Transforming growth factor beta1 targets estrogen receptor signaling in bronchial epithelial cells Respir. Res. 2018 19 160 10.1186/s12931-018-0861-5 30165855 19. Ntolios P. Tzilas V. Bouros E. Avdoula E. Karakasiliotis I. Bouros D. Steiropoulos P. The Role of Microbiome and Virome in Idiopathic Pulmonary Fibrosis Biomed. 2021 9 442 10.3390/biomedicines9040442 20. Molyneaux P.L. Cox M.J. Willis-Owen S.A. Mallia P. Russell K.E. Russell A.M. Murphy E. Johnston S.L. Schwartz D.A. Wells A.U. The role of bacteria in the pathogenesis and progression of idiopathic pulmonary fibrosis Am. J. Respir. Crit. Care Med. 2014 190 906 913 10.1164/rccm.201403-0541OC 25184687 21. Fastrès A. Felice F. Roles E. Moermans C. Corhay J.L. Bureau F. Louis R. Clercx C. Guiot J. The Lung Microbiome in Idiopathic Pulmonary Fibrosis: A Promising Approach for Targeted Therapies Int. J. Mol. Sci. 2017 18 2735 10.3390/ijms18122735 22. Chioma O.S. Hesse L.E. Chapman A. Drake W.P. Role of the Microbiome in Interstitial Lung Diseases Front. Med. 2021 8 595522 10.3389/fmed.2021.595522 33604346 23. Seibold M.A. Wise A.L. Speer M.C. Steele M.P. Brown K.K. Loyd J.E. Fingerlin T.E. Zhang W. Gudmundsson G. Groshong S.D. A common MUC5B promoter polymorphism and pulmonary fibrosis New Engl. J. Med. 2011 364 1503 1512 10.1056/NEJMoa1013660 21506741 24. Noth I. Zangan S.M. Soares R.V. Forsythe A. Demchuk C. Takahashi S.M. Patel S.B. Strek M.E. Krishnan J.A. Patti M.G. Prevalence of hiatal hernia by blinded multidetector CT in patients with idiopathic pulmonary fibrosis Eur. Respir. J. 2012 39 344 351 10.1183/09031936.00099910 21737563 25. Lee J.S. Collard H.R. Anstrom K.J. Martinez F.J. Noth I. Roberts R.S. Yow E. Raghu G. Anti-acid treatment and disease progression in idiopathic pulmonary fibrosis: An analysis of data from three randomised controlled trials Lancet Respir. Med. 2013 1 369 376 10.1016/S2213-2600(13)70105-X 24429201 26. Kreuter M. Wuyts W. Renzoni E. Koschel D. Maher T.M. Kolb M. Weycker D. Spagnolo P. Kirchgaessler K.U. Herth F.J. Antacid therapy and disease outcomes in idiopathic pulmonary fibrosis: A pooled analysis Lancet Respir. Med. 2016 4 381 389 10.1016/S2213-2600(16)00067-9 27050871 27. Raghu G. Pellegrini C.A. Yow E. Flaherty K.R. Meyer K. Noth I. Scholand M.B. Cello J. Ho L.A. Pipavath S. Laparoscopic anti-reflux surgery for the treatment of idiopathic pulmonary fibrosis (WRAP-IPF): A multicentre, randomised, controlled phase 2 trial Lancet Respir. Med. 2018 6 707 714 10.1016/S2213-2600(18)30301-1 30100404 28. Gille T. Didier M. Boubaya M. Moya L. Sutton A. Carton Z. Baran-Marszak F. Sadoun-Danino D. Israël-Biet D. Cottin V. Obstructive sleep apnoea and related comorbidities in incident idiopathic pulmonary fibrosis Eur. Respir. J. 2017 49 1601934 10.1183/13993003.01934-2016 28596432 29. King T.E. Jr. Pardo A. Selman M. Idiopathic pulmonary fibrosis Lancet 2011 378 1949 1961 10.1016/S0140-6736(11)60052-4 21719092 30. Yang J. Xue Q. Miao L. Cai L. Pulmonary fibrosis: A possible diabetic complication Diabetes/Metab. Res. Rev. 2011 27 311 317 10.1002/dmrr.1175 31. Sato N. Takasaka N. Yoshida M. Tsubouchi K. Minagawa S. Araya J. Saito N. Fujita Y. Kurita Y. Kobayashi K. Metformin attenuates lung fibrosis development via NOX4 suppression Respir. Res. 2016 17 107 10.1186/s12931-016-0420-x 27576730 32. Rangarajan S. Bone N.B. Zmijewska A.A. Jiang S. Park D.W. Bernard K. Locy M.L. Ravi S. Deshane J. Mannon R.B. Metformin reverses established lung fibrosis in a bleomycin model Nat. Med. 2018 24 1121 1127 10.1038/s41591-018-0087-6 29967351 33. Tang Y.W. Johnson J.E. Browning P.J. Cruz-Gervis R.A. Davis A. Graham B.S. Brigham K.L. Oates J.A. Jr. Loyd J.E. Stecenko A.A. Herpesvirus DNA is consistently detected in lungs of patients with idiopathic pulmonary fibrosis J. Clin. Microbiol. 2003 41 2633 2640 10.1128/JCM.41.6.2633-2640.2003 12791891 34. Sides M.D. Klingsberg R.C. Shan B. Gordon K.A. Nguyen H.T. Lin Z. Takahashi T. Flemington E.K. Lasky J.A. The Epstein-Barr virus latent membrane protein 1 and transforming growth factor-β1 synergistically induce epithelial-mesenchymal transition in lung epithelial cells Am. J. Respir. Cell Mol. Biol. 2011 44 852 862 10.1165/rcmb.2009-0232OC 20693406 35. Malizia A.P. Keating D.T. Smith S.M. Walls D. Doran P.P. Egan J.J. Alveolar epithelial cell injury with Epstein-Barr virus upregulates TGFbeta1 expression Am. J. Physiol. Lung Cell. Mol. Physiol. 2008 295 L451 L460 10.1152/ajplung.00376.2007 18621908 36. Milara J. Peiró T. Serrano A. Guijarro R. Zaragozá C. Tenor H. Cortijo J. Roflumilast N-oxide inhibits bronchial epithelial to mesenchymal transition induced by cigarette smoke in smokers with COPD Pulm. Pharmacol. Ther. 2014 28 138 148 10.1016/j.pupt.2014.02.001 24525294 37. Huzen J. Wong L.S. van Veldhuisen D.J. Samani N.J. Zwinderman A.H. Codd V. Cawthon R.M. Benus G.F. van der Horst I.C. Navis G. Telomere length loss due to smoking and metabolic traits J. Intern. Med. 2014 275 155 163 10.1111/joim.12149 24118582 38. Tanjore H. Blackwell T.S. Lawson W.E. Emerging evidence for endoplasmic reticulum stress in the pathogenesis of idiopathic pulmonary fibrosis Am. J. Physiol. Lung Cell. Mol. Physiol. 2012 302 L721 L729 10.1152/ajplung.00410.2011 22287606 39. Jensen K. Nizamutdinov D. Guerrier M. Afroze S. Dostal D. Glaser S. General mechanisms of nicotine-induced fibrogenesis FASEBJ: Off. Publ. Fed. Am. Soc. Exp. Biol. 2012 26 4778 4787 10.1096/fj.12-206458 40. Hubbard R. Cooper M. Antoniak M. Venn A. Khan S. Johnston I. Lewis S. Britton J. Risk of cryptogenic fibrosing alveolitis in metal workers Lancet 2000 355 466 467 10.1016/S0140-6736(00)82017-6 10841131 41. Iwai K. Mori T. Yamada N. Yamaguchi M. Hosoda Y. Idiopathic pulmonary fibrosis. Epidemiologic approaches to occupational exposure Am. J. Respir. Crit. Care Med. 1994 150 670 675 10.1164/ajrccm.150.3.8087336 8087336 42. Kolahian S. Fernandez I.E. Eickelberg O. Hartl D. Immune Mechanisms in Pulmonary Fibrosis Am. J. Respir. Cell Mol. Biol. 2016 55 309 322 10.1165/rcmb.2016-0121TR 27149613 43. Chioma O.S. Drake W.P. Role of Microbial Agents in Pulmonary Fibrosis Yale J. Biol. Med. 2017 90 219 227 28656009 44. Tashiro J. Rubio G.A. Limper A.H. Williams K. Elliot S.J. Ninou I. Aidinis V. Tzouvelekis A. Glassberg M.K. Exploring Animal Models That Resemble Idiopathic Pulmonary Fibrosis Front. Med. 2017 4 118 10.3389/fmed.2017.00118 28804709 45. Degryse A.L. Lawson W.E. Progress toward improving animal models for idiopathic pulmonary fibrosis Am. J. Med. Sci. 2011 341 444 449 10.1097/MAJ.0b013e31821aa000 21613932 46. Redente E.F. Black B.P. Backos D.S. Bahadur A.N. Humphries S.M. Lynch D.A. Tuder R.M. Zemans R.L. Riches D.W.H. Persistent, Progressive Pulmonary Fibrosis and Epithelial Remodeling in Mice Am. J. Respir. Cell Mol. Biol. 2021 64 669 676 10.1165/rcmb.2020-0542MA 33406369 47. Degryse A.L. Tanjore H. Xu X.C. Polosukhin V.V. Jones B.R. McMahon F.B. Gleaves L.A. Blackwell T.S. Lawson W.E. Repetitive intratracheal bleomycin models several features of idiopathic pulmonary fibrosis Am. J. Physiol. Lung Cell. Mol. Physiol. 2010 299 L442 L452 10.1152/ajplung.00026.2010 20562227 48. Yu Q.Y. Tang X.X. Irreversibility of Pulmonary Fibrosis Aging Dis. 2022 13 73 86 10.14336/AD.2021.0730 35111363 49. Shu D.Y. Lovicu F.J. Myofibroblast transdifferentiation: The dark force in ocular wound healing and fibrosis Prog. Retin. Eye Res. 2017 60 44 65 10.1016/j.preteyeres.2017.08.001 28807717 50. Bamberg A. Redente E.F. Groshong S.D. Tuder R.M. Cool C.D. Keith R.C. Edelman B.L. Black B.P. Cosgrove G.P. Wynes M.W. Protein Tyrosine Phosphatase-N13 Promotes Myofibroblast Resistance to Apoptosis in Idiopathic Pulmonary Fibrosis Am. J. Respir. Crit. Care Med. 2018 198 914 927 10.1164/rccm.201707-1497OC 29727583 51. Pendyala S. Moitra J. Kalari S. Kleeberger S.R. Zhao Y. Reddy S.P. Garcia J.G. Natarajan V. Nrf2 regulates hyperoxia-induced Nox4 expression in human lung endothelium: Identification of functional antioxidant response elements on the Nox4 promoter Free. Radic. Biol. Med. 2011 50 1749 1759 10.1016/j.freeradbiomed.2011.03.022 21443946 52. Redente E.F. Chakraborty S. Sajuthi S. Black B.P. Edelman B.L. Seibold M.A. Riches D.W. Loss of Fas signaling in fibroblasts impairs homeostatic fibrosis resolution and promotes persistent pulmonary fibrosis JCI Insight 2020 6 e141618 10.1172/jci.insight.141618 33290280 53. Probst C.K. Montesi S.B. Medoff B.D. Shea B.S. Knipe R.S. Vascular permeability in the fibrotic lung Eur. Respir. J. 2020 56 1900100 10.1183/13993003.00100-2019 32265308 54. Caporarello N. Meridew J.A. Aravamudhan A. Jones D.L. Austin S.A. Pham T.X. Haak A.J. Moo Choi K. Tan Q. Haresi A. Vascular dysfunction in aged mice contributes to persistent lung fibrosis Aging Cell 2020 19 e13196 10.1111/acel.13196 32691484 55. Guan S. Zhou J. CXCR7 attenuates the TGF-β-induced endothelial-to-mesenchymal transition and pulmonary fibrosis Mol. Biosyst. 2017 13 2116 2124 10.1039/C7MB00247E 28820530 56. Rius-Pérez S. Torres-Cuevas I. Millán I. Ortega Á.L. Pérez S. PGC-1α, Inflammation, and Oxidative Stress: An Integrative View in Metabolism Oxidative Med. Cell. Longev. 2020 2020 1452696 10.1155/2020/1452696 32215168 57. Caporarello N. Meridew J.A. Jones D.L. Tan Q. Haak A.J. Choi K.M. Manlove L.J. Prakash Y.S. Tschumperlin D.J. Ligresti G. PGC1α repression in IPF fibroblasts drives a pathologic metabolic, secretory and fibrogenic state Thorax 2019 74 749 760 10.1136/thoraxjnl-2019-213064 31182654 58. Wang N. Zhu P. Huang R. Wang C. Sun L. Lan B. He Y. Zhao H. Gao Y. PINK1: The guard of mitochondria Life Sci. 2020 259 118247 10.1016/j.lfs.2020.118247 32805222 59. Singh K.K. Lovren F. Pan Y. Quan A. Ramadan A. Matkar P.N. Ehsan M. Sandhu P. Mantella L.E. Gupta N. The essential autophagy gene ATG7 modulates organ fibrosis via regulation of endothelial-to-mesenchymal transition J. Biol. Chem. 2015 290 2547 2559 10.1074/jbc.M114.604603 25527499 60. Liao S.X. Sun P.P. Gu Y.H. Rao X.M. Zhang L.Y. Ou-Yang Y. Autophagy and pulmonary disease Ther. Adv. Respir. Dis. 2019 13 1753466619890538 10.1177/1753466619890538 31771432 61. Aspal M. Zemans R.L. Mechanisms of ATII-to-ATI Cell Differentiation during Lung Regeneration Int. J. Mol. Sci. 2020 21 3188 10.3390/ijms21093188 62. Ding L. Tang S. Tang W. Mosley D.D. Yu A. Sil D. Romanova S. Bailey K.L. Knoell D.L. Wyatt T.A. Perfluorocarbon Nanoemulsions Enhance Therapeutic siRNA Delivery in the Treatment of Pulmonary Fibrosis Adv. Sci. 2022 9 e2103676 10.1002/advs.202103676 34994102 63. Zou J. Li Y. Yu J. Dong L. Husain A.N. Shen L. Weber C.R. Idiopathic pulmonary fibrosis is associated with tight junction protein alterations Biochim. Et Biophys. Acta Biomembr. 2020 1862 183205 10.1016/j.bbamem.2020.183205 32001212 64. Wu H. Yu Y. Huang H. Hu Y. Fu S. Wang Z. Shi M. Zhao X. Yuan J. Li J. Progressive Pulmonary Fibrosis Is Caused by Elevated Mechanical Tension on Alveolar Stem Cells Cell 2020 180 107 121.e17 10.1016/j.cell.2019.11.027 31866069 65. Shannon J.M. Hyatt B.A. Epithelial-mesenchymal interactions in the developing lung Annu. Rev. Physiol. 2004 66 625 645 10.1146/annurev.physiol.66.032102.135749 14977416 66. Selman M. Pardo A. Role of epithelial cells in idiopathic pulmonary fibrosis: From innocent targets to serial killers Proc. Am. Thorac. Soc. 2006 3 364 372 10.1513/pats.200601-003TK 16738202 67. Hadjicharalambous M.R. Lindsay M.A. Idiopathic Pulmonary Fibrosis: Pathogenesis and the Emerging Role of Long Non-Coding RNAs Int. J. Mol. Sci. 2020 21 524 10.3390/ijms21020524 68. Kasper M. Barth K. Potential contribution of alveolar epithelial type I cells to pulmonary fibrosis Biosci. Rep. 2017 37 BSR20171301 10.1042/BSR20171301 29026006 69. Camelo A. Dunmore R. Sleeman M.A. Clarke D.L. The epithelium in idiopathic pulmonary fibrosis: Breaking the barrier Front. Pharmacol. 2014 4 173 10.3389/fphar.2013.00173 24454287 70. Vockeroth D. Gunasekara L. Amrein M. Possmayer F. Lewis J.F. Veldhuizen R.A. Role of cholesterol in the biophysical dysfunction of surfactant in ventilator-induced lung injury Am. J. Physiol. Lung Cell. Mol. Physiol. 2010 298 L117 L125 10.1152/ajplung.00218.2009 19897745 71. Sunaga H. Matsui H. Ueno M. Maeno T. Iso T. Syamsunarno M.R. Anjo S. Matsuzaka T. Shimano H. Yokoyama T. Deranged fatty acid composition causes pulmonary fibrosis in Elovl6-deficient mice Nat. Commun. 2013 4 2563 10.1038/ncomms3563 24113622 72. Romero F. Hong X. Shah D. Kallen C.B. Rosas I. Guo Z. Schriner D. Barta J. Shaghaghi H. Hoek J.B. Lipid Synthesis Is Required to Resolve Endoplasmic Reticulum Stress and Limit Fibrotic Responses in the Lung Am. J. Respir. Cell Mol. Biol. 2018 59 225 236 10.1165/rcmb.2017-0340OC 29465261 73. Reyfman P.A. Walter J.M. Joshi N. Anekalla K.R. McQuattie-Pimentel A.C. Chiu S. Fernandez R. Akbarpour M. Chen C.I. Ren Z. Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis Am. J. Respir. Crit. Care Med. 2019 199 1517 1536 10.1164/rccm.201712-2410OC 30554520 74. Lv T. Jiang K. Wang J. Tang N. Dai H. Wang C. Single-cell RNA sequencing profiling of the effects of aging on alveolar stem cells Sci. China Life Sci. 2019 62 1028 1037 10.1007/s11427-019-9583-9 31321669 75. Xu X. Zheng L. Yuan Q. Zhen G. Crane J.L. Zhou X. Cao X. Transforming growth factor-β in stem cells and tissue homeostasis Bone Res. 2018 6 2 10.1038/s41413-017-0005-4 29423331 76. Kim K.K. Wei Y. Szekeres C. Kugler M.C. Wolters P.J. Hill M.L. Frank J.A. Brumwell A.N. Wheeler S.E. Kreidberg J.A. Epithelial cell alpha3beta1 integrin links beta-catenin and Smad signaling to promote myofibroblast formation and pulmonary fibrosis J. Clin. Investig. 2009 119 213 224 19104148 77. Velagacherla V. Mehta C.H. Nayak Y. Nayak U.Y. Molecular pathways and role of epigenetics in the idiopathic pulmonary fibrosis Life Sci. 2022 291 120283 10.1016/j.lfs.2021.120283 34998839 78. Hernandez D.M. Kang J.H. Choudhury M. Andrianifahanana M. Yin X. Limper A.H. Leof E.B. IPF pathogenesis is dependent upon TGFβ induction of IGF-1 FASEB J: Off. Publ. Fed. Am. Soc. Exp. Biol. 2020 34 5363 5388 10.1096/fj.201901719RR 79. Kolb M. Margetts P.J. Anthony D.C. Pitossi F. Gauldie J. Transient expression of IL-1beta induces acute lung injury and chronic repair leading to pulmonary fibrosis J. Clin. Investig. 2001 107 1529 1536 10.1172/JCI12568 11413160 80. Lappalainen U. Whitsett J.A. Wert S.E. Tichelaar J.W. Bry K. Interleukin-1beta causes pulmonary inflammation, emphysema, and airway remodeling in the adult murine lung Am. J. Respir. Cell Mol. Biol. 2005 32 311 318 10.1165/rcmb.2004-0309OC 15668323 81. Wilson M.S. Madala S.K. Ramalingam T.R. Gochuico B.R. Rosas I.O. Cheever A.W. Wynn T.A. Bleomycin and IL-1beta-mediated pulmonary fibrosis is IL-17A dependent J. Exp. Med. 2010 207 535 552 10.1084/jem.20092121 20176803 82. Kinder B.W. Brown K.K. Schwarz M.I. Ix J.H. Kervitsky A. King T.E. Jr. Baseline BAL neutrophilia predicts early mortality in idiopathic pulmonary fibrosis Chest 2008 133 226 232 10.1378/chest.07-1948 18071016 83. Baroni G.S. D’Ambrosio L. Curto P. Casini A. Mancini R. Jezequel A.M. Benedetti A. Interferon gamma decreases hepatic stellate cell activation and extracellular matrix deposition in rat liver fibrosis Hepatol. 1996 23 1189 1199 10.1002/hep.510230538 8621153 84. Chiaramonte M.G. Donaldson D.D. Cheever A.W. Wynn T.A. An IL-13 inhibitor blocks the development of hepatic fibrosis during a T-helper type 2-dominated inflammatory response J. Clin. Investig. 1999 104 777 785 10.1172/JCI7325 10491413 85. Heukels P. Moor C.C. von der Thüsen J.H. Wijsenbeek M.S. Kool M. Inflammation and immunity in IPF pathogenesis and treatment Respir. Med. 2019 147 79 91 10.1016/j.rmed.2018.12.015 30704705 86. Caminati A. Cassandro R. Torre O. Harari S. Severe idiopathic pulmonary fibrosis: What can be done? Eur. Respir.Rev.: Off. J. Eur. Respir. Soc. 2017 26 170047 10.1183/16000617.0047-2017 87. Miles T. Hoyne G.F. Knight D.A. Fear M.W. Mutsaers S.E. Prêle C.M. The contribution of animal models to understanding the role of the immune system in human idiopathic pulmonary fibrosis Clin. Transl. Immunol. 2020 9 e1153 10.1002/cti2.1153 88. Kolb M. Bonniaud P. Galt T. Sime P.J. Kelly M.M. Margetts P.J. Gauldie J. Differences in the fibrogenic response after transfer of active transforming growth factor-beta1 gene to lungs of “fibrosis-prone” and “fibrosis-resistant” mouse strains Am. J. Respir. Cell Mol. Biol. 2002 27 141 150 10.1165/ajrcmb.27.2.4674 12151305 89. Kolb M. Bonella F. Wollin L. Therapeutic targets in idiopathic pulmonary fibrosis Respir. Med. 2017 131 49 57 10.1016/j.rmed.2017.07.062 28947042 90. Saito S. Alkhatib A. Kolls J.K. Kondoh Y. Lasky J.A. Pharmacotherapy and adjunctive treatment for idiopathic pulmonary fibrosis (IPF) J. Thorac. Dis. 2019 11 S1740 S1754 10.21037/jtd.2019.04.62 31632751 91. Lancaster L.H. de Andrade J.A. Zibrak J.D. Padilla M.L. Albera C. Nathan S.D. Wijsenbeek M.S. Stauffer J.L. Kirchgaessler K.U. Costabel U. Pirfenidone safety and adverse event management in idiopathic pulmonary fibrosis Eur. Respir.Rev.: Off. J. Eur. Respir. Soc. 2017 26 170057 10.1183/16000617.0057-2017 92. Cottin V. Maher T. Long-term clinical and real-world experience with pirfenidone in the treatment of idiopathic pulmonary fibrosis Eur. Respir.Rev.: Off. J. Eur. Respir. Soc. 2015 24 58 64 10.1183/09059180.00011514 25726556 93. Corte T. Bonella F. Crestani B. Demedts M.G. Richeldi L. Coeck C. Pelling K. Quaresma M. Lasky J.A. Safety, tolerability and appropriate use of nintedanib in idiopathic pulmonary fibrosis Respir. Res. 2015 16 116 10.1186/s12931-015-0276-5 26400368 94. Wollin L. Wex E. Pautsch A. Schnapp G. Hostettler K.E. Stowasser S. Kolb M. Mode of action of nintedanib in the treatment of idiopathic pulmonary fibrosis Eur. Respir. J. 2015 45 1434 1445 10.1183/09031936.00174914 25745043 95. Lederer D.J. Martinez F.J. Idiopathic Pulmonary Fibrosis New Engl. J. Med. 2018 379 797 798 10.1056/NEJMra1705751 96. Kato M. Sasaki S. Nakamura T. Kurokawa K. Yamada T. Ochi Y. Ihara H. Takahashi F. Takahashi K. Gastrointestinal adverse effects of nintedanib and the associated risk factors in patients with idiopathic pulmonary fibrosis Sci. Rep. 2019 9 12062 10.1038/s41598-019-48593-4 31427707 97. Luedtke D. Marzin K. Jungnik A. von Wangenheim U. Dallinger C. Effects of Ketoconazole and Rifampicin on the Pharmacokinetics of Nintedanib in Healthy Subjects Eur. J. Drug Metab. Pharmacokinet. 2018 43 533 541 10.1007/s13318-018-0467-9 29500603 98. Richeldi L. Cottin V. du Bois R.M. Selman M. Kimura T. Bailes Z. Schlenker-Herceg R. Stowasser S. Brown K.K. Nintedanib in patients with idiopathic pulmonary fibrosis: Combined evidence from the TOMORROW and INPULSIS(®) trials Respir. Med. 2016 113 74 79 10.1016/j.rmed.2016.02.001 26915984 99. Nathan S.D. Albera C. Bradford W.Z. Costabel U. Glaspole I. Glassberg M.K. Kardatzke D.R. Daigl M. Kirchgaessler K.U. Lancaster L.H. Effect of pirfenidone on mortality: Pooled analyses and meta-analyses of clinical trials in idiopathic pulmonary fibrosis Lancet Respir. Med. 2017 5 33 41 10.1016/S2213-2600(16)30326-5 27876247 100. Grześk G. Woźniak-Wiśniewska A. Błażejewski J. Górny B. Wołowiec Ł. Rogowicz D. Nowaczyk A. The Interactions of Nintedanib and Oral Anticoagulants-Molecular Mechanisms and Clinical Implications Int. J. Mol. Sci. 2020 22 282 10.3390/ijms22010282 101. Richeldi L. Fletcher S. Adamali H. Chaudhuri N. Wiebe S. Wind S. Hohl K. Baker A. Schlenker-Herceg R. Stowasser S. No relevant pharmacokinetic drug-drug interaction between nintedanib and pirfenidone Eur. Respir. J. 2019 53 1801060 10.1183/13993003.01060-2018 30442716 102. Ogura T. Taniguchi H. Azuma A. Inoue Y. Kondoh Y. Hasegawa Y. Bando M. Abe S. Mochizuki Y. Chida K. Safety and pharmacokinetics of nintedanib and pirfenidone in idiopathic pulmonary fibrosis Eur. Respir. J. 2015 45 1382 1392 10.1183/09031936.00198013 25504994 103. Landis-Piwowar K.R. Milacic V. Chen D. Yang H. Zhao Y. Chan T.H. Yan B. Dou Q.P. The proteasome as a potential target for novel anticancer drugs and chemosensitizers Drug Resist. Updates: Rev. Comment. Antimicrob. Anticancer. Chemother. 2006 9 263 273 10.1016/j.drup.2006.11.001 17197231 104. Teicher B.A. Tomaszewski J.E. Proteasome inhibitors Biochem. Pharmacol. 2015 96 1 9 10.1016/j.bcp.2015.04.008 25935605 105. Semren N. Habel-Ungewitter N.C. Fernandez I.E. Königshoff M. Eickelberg O. Stöger T. Meiners S. Validation of the 2nd Generation Proteasome Inhibitor Oprozomib for Local Therapy of Pulmonary Fibrosis PLoS ONE 2015 10 e0136188 10.1371/journal.pone.0136188 26340365 106. Fricker LD: Proteasome Inhibitor Drugs Annu. Rev. Pharmacol. Toxicol. 2020 60 457 476 10.1146/annurev-pharmtox-010919-023603 31479618 107. Juvekar A. Manna S. Ramaswami S. Chang T.P. Vu H.Y. Ghosh C.C. Celiker M.Y. Vancurova I. Bortezomib induces nuclear translocation of IκBα resulting in gene-specific suppression of NF-κB--dependent transcription and induction of apoptosis in CTCL Mol. Cancer Res. 2011 9 183 194 10.1158/1541-7786.MCR-10-0368 21224428 108. Wu X. Chen Z. Yang Y. Dong Y. Liu H. Kuang S. Luo K. Impact of proteasome inhibitor MG-132 on expression of NF-κB, IL-1β and histological remodeling after myocardial infarction Exp. Ther. Med. 2018 16 1365 1372 10.3892/etm.2018.6308 30112065 109. Zhang J. Yang C. Zhou F. Chen X. PDK1 inhibitor GSK2334470 synergizes with proteasome inhibitor MG-132 in multiple myeloma cells by inhibiting full AKT activity and increasing nuclear accumulation of the PTEN protein Oncol. Rep. 2018 39 2951 2959 10.3892/or.2018.6369 29658600 110. Meiners S. Hocher B. Weller A. Laule M. Stangl V. Guenther C. Godes M. Mrozikiewicz A. Baumann G. Stangl K. Downregulation of matrix metalloproteinases and collagens and suppression of cardiac fibrosis by inhibition of the proteasome Hypertens. 2004 44 471 477 10.1161/01.HYP.0000142772.71367.65 111. Han L. Zhu B. Chen H. Jin Y. Liu J. Wang W. Proteasome inhibitor MG132 inhibits the process of renal interstitial fibrosis Exp. Ther. Med. 2019 17 2953 2962 10.3892/etm.2019.7329 30936965 112. Szeto S.G. Narimatsu M. Lu M. He X. Sidiqi A.M. Tolosa M.F. Chan L. De Freitas K. Bialik J.F. Majumder S. YAP/TAZ Are Mechanoregulators of TGF-β-Smad Signaling and Renal Fibrogenesis J. Am. Soc.Nephrol. 2016 27 3117 3128 10.1681/ASN.2015050499 26961347 113. Aravamudhan A. Haak A.J. Choi K.M. Meridew J.A. Caporarello N. Jones D.L. Tan Q. Ligresti G. Tschumperlin D.J. TBK1 regulates YAP/TAZ and fibrogenic fibroblast activation Am. J. Physiol. Lung Cell. Mol. Physiol. 2020 318 L852 L863 10.1152/ajplung.00324.2019 32159970 114. Bross P.F. Kane R. Farrell A.T. Abraham S. Benson K. Brower M.E. Bradley S. Gobburu J.V. Goheer A. Lee S.L. Approval summary for bortezomib for injection in the treatment of multiple myeloma Clin. Cancer Res. 2004 10 3954 3964 10.1158/1078-0432.CCR-03-0781 15217925 115. Orlowski R.Z. Stinchcombe T.E. Mitchell B.S. Shea T.C. Baldwin A.S. Stahl S. Adams J. Esseltine D.L. Elliott P.J. Pien C.S. Phase I trial of the proteasome inhibitor PS-341 in patients with refractory hematologic malignancies J. Clin.Oncol. 2002 20 4420 4427 10.1200/JCO.2002.01.133 12431963 116. Gandolfi S. Laubach J.P. Hideshima T. Chauhan D. Anderson K.C. Richardson P.G. The proteasome and proteasome inhibitors in multiple myeloma Cancer Metastasis Rev. 2017 36 561 584 10.1007/s10555-017-9707-8 29196868 117. Hatake K. Mishima Y. Terui Y. Proteasome inhibitors Cancer Chemother. 2004 31 999 1002 118. Jares P. Colomer D. Campo E. Molecular pathogenesis of mantle cell lymphoma J. Clin. Investig. 2012 122 3416 3423 10.1172/JCI61272 23023712 119. Uziel O. Cohen O. Beery E. Nordenberg J. Lahav M. The effect of Bortezomib and Rapamycin on Telomerase Activity in Mantle Cell Lymphoma Transl. Oncol. 2014 7 741 751 10.1016/j.tranon.2014.09.004 25500084 120. Pan X. Hussain F.N. Iqbal J. Feuerman M.H. Hussain M.M. Inhibiting proteasomal degradation of microsomal triglyceride transfer protein prevents CCl4-induced steatosis J. Biol. Chem. 2007 282 17078 17089 10.1074/jbc.M701742200 17405876 121. Wagner-Ballon O. Pisani D.F. Gastinne T. Tulliez M. Chaligné R. Lacout C. Auradé F. Villeval J.L. Gonin P. Vainchenker W. Proteasome inhibitor bortezomib impairs both myelofibrosis and osteosclerosis induced by high thrombopoietin levels in mice Blood 2007 110 345 353 10.1182/blood-2006-10-054502 17374740 122. Mutlu G.M. Budinger G.R. Wu M. Lam A.P. Zirk A. Rivera S. Urich D. Chiarella S.E. Go L.H. Ghosh A.K. Proteasomal inhibition after injury prevents fibrosis by modulating TGF-β(1) signalling Thorax 2012 67 139 146 10.1136/thoraxjnl-2011-200717 21921091 123. Penke L.R.K. Speth J. Wettlaufer S. Draijer C. Peters-Golden M. Bortezomib Inhibits Lung Fibrosis and Fibroblast Activation without Proteasome Inhibition Am. J. Respir. Cell Mol. Biol. 2022 66 23 37 10.1165/rcmb.2021-0112OC 34236953 124. Allegra A. Alonci A. Gerace D. Russo S. Innao V. Calabrò L. Musolino C. New orally active proteasome inhibitors in multiple myeloma Leuk. Res. 2014 38 1 9 10.1016/j.leukres.2013.10.018 24239172 125. Yang Y. Li Y. Gu H. Dong M. Cai Z. Emerging agents and regimens for multiple myeloma J. Hematol. Oncol. 2020 13 150 10.1186/s13045-020-00980-5 33168044 126. Wang J. Fang Y. Fan R.A. Kirk C.J. Proteasome Inhibitors and Their Pharmacokinetics, Pharmacodynamics, and Metabolism Int. J. Mol. Sci. 2021 22 11595 10.3390/ijms222111595 34769030 127. Gupta S.V. Hertlein E. Lu Y. Sass E.J. Lapalombella R. Chen T.L. Davis M.E. Woyach J.A. Lehman A. Jarjoura D. The proteasome inhibitor carfilzomib functions independently of p53 to induce cytotoxicity and an atypical NF-κB response in chronic lymphocytic leukemia cells Clin. Cancer Res. 2013 19 2406 2419 10.1158/1078-0432.CCR-12-2754 23515408 128. Chauhan D. Singh A.V. Aujay M. Kirk C.J. Bandi M. Ciccarelli B. Raje N. Richardson P. Anderson K.C. A novel orally active proteasome inhibitor ONX 0912 triggers in vitro and in vivo cytotoxicity in multiple myeloma Blood 2010 116 4906 4915 10.1182/blood-2010-04-276626 20805366 129. Kupperman E. Lee E.C. Cao Y. Bannerman B. Fitzgerald M. Berger A. Yu J. Yang Y. Hales P. Bruzzese F. Evaluation of the proteasome inhibitor MLN9708 in preclinical models of human cancer Cancer Res. 2010 70 1970 1980 10.1158/0008-5472.CAN-09-2766 20160034 130. Dorsey B.D. Iqbal M. Chatterjee S. Menta E. Bernardini R. Bernareggi A. Cassarà P.G. D’Arasmo G. Ferretti E. De Munari S. Discovery of a potent, selective, and orally active proteasome inhibitor for the treatment of cancer J. Med. Chem. 2008 51 1068 1072 10.1021/jm7010589 18247547 131. Raninga P.V. Lee A. Sinha D. Dong L.F. Datta K.K. Lu X. Kalita-de Croft P. Dutt M. Hill M. Pouliot N. Marizomib suppresses triple-negative breast cancer via proteasome and oxidative phosphorylation inhibition Theranostics 2020 10 5259 5275 10.7150/thno.42705 32373211 132. Park J.E. Miller Z. Jun Y. Lee W. Kim K.B. Next-generation proteasome inhibitors for cancer therapy Transl.Res. 2018 198 1 16 10.1016/j.trsl.2018.03.002 29654740 133. Manasanch E.E. Orlowski R.Z. Proteasome inhibitors in cancer therapy Nat. Rev. Clin. Oncol. 2017 14 417 433 10.1038/nrclinonc.2016.206 28117417 134. Levin N. Spencer A. Harrison S.J. Chauhan D. Burrows F.J. Anderson K.C. Reich S.D. Richardson P.G. Trikha M. Marizomib irreversibly inhibits proteasome to overcome compensatory hyperactivation in multiple myeloma and solid tumour patients Br. J. Haematol. 2016 174 711 720 10.1111/bjh.14113 27161872 135. Chauhan D. Catley L. Li G. Podar K. Hideshima T. Velankar M. Mitsiades C. Mitsiades N. Yasui H. Letai A. A novel orally active proteasome inhibitor induces apoptosis in multiple myeloma cells with mechanisms distinct from Bortezomib Cancer Cell 2005 8 407 419 10.1016/j.ccr.2005.10.013 16286248 136. Wang S.Y. Shih Y.H. Shieh T.M. Tseng Y.H. Proteasome Inhibitors Interrupt the Activation of Non-Canonical NF-κB Signaling Pathway and Induce Cell Apoptosis in Cytarabine-Resistant HL60 Cells Int. J. Mol. Sci. 2021 23 361 10.3390/ijms23010361 35008789 137. Chen I.-C. Liu Y.-C. Wu Y.-H. Lo S.-H. Wang S.-C. Li C.-Y. Dai Z.-K. Hsu J.-H. Yeh C.-Y. Tseng Y.-H. Proteasome Inhibitors Decrease the Viability of Pulmonary Arterial Smooth Muscle Cells by Restoring Mitofusin-2 Expression under Hypoxic Conditions Biomed. 2022 10 873 138. Visovsky C. Chemotherapy-induced peripheral neuropathy Cancer Investig. 2003 21 439 451 10.1081/CNV-120018236 12901290 139. Areti A, Yerra VG, Naidu V, Kumar A: Oxidative stress and nerve damage: Role in chemotherapy induced peripheral neuropathy Redox Biol. 2014 2 289 295 10.1016/j.redox.2014.01.006 24494204 140. Kaplan G.S. Torcun C.C. Grune T. Ozer N.K. Karademir B. Proteasome inhibitors in cancer therapy: Treatment regimen and peripheral neuropathy as a side effect Free. Radic. Biol. Med. 2017 103 1 13 10.1016/j.freeradbiomed.2016.12.007 27940347 141. Alé A. Bruna J. Navarro X. Udina E. Neurotoxicity induced by antineoplastic proteasome inhibitors Neurotoxicology 2014 43 28 35 10.1016/j.neuro.2014.02.001 24525285 142. Meiners S. Ludwig A. Stangl V. Stangl K. Proteasome inhibitors: Poisons and remedies Med. Res. Rev. 2008 28 309 327 10.1002/med.20111 17880010 143. Spencer A. Harrison S. Zonder J. Badros A. Laubach J. Bergin K. Khot A. Zimmerman T. Chauhan D. Levin N. A phase 1 clinical trial evaluating marizomib, pomalidomide and low-dose dexamethasone in relapsed and refractory multiple myeloma (NPI-0052-107): Final study results Br. J. Haematol. 2018 180 41 51 10.1111/bjh.14987 29076150 144. Sitaraman S. Na C.L. Yang L. Filuta A. Bridges J.P. Weaver T.E. Proteasome dysfunction in alveolar type 2 epithelial cells is associated with acute respiratory distress syndrome Sci. Rep. 2019 9 12509 10.1038/s41598-019-49020-4 31467330 145. Katzen J. Beers M.F. Contributions of alveolar epithelial cell quality control to pulmonary fibrosis J. Clin. Investig. 2020 130 5088 5099 10.1172/JCI139519 32870817

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092644 jcm-11-02644 Article Comparison of the Oncological Outcomes of Open versus Laparoscopic Surgery for T2 Gallbladder Cancer: A Propensity-Score-Matched Analysis Cho Jin-Kyu 1 https://orcid.org/0000-0001-6865-1350 Kim Jae-Ri 2 Jang Jae-Yool 2 Kim Han-Gil 1 Kim Jae-Myung 1 Kwag Seung-Jin 1 Park Ji-Ho 1 Kim Ju-Yeon 1 Ju Young-Tae 1 https://orcid.org/0000-0002-6877-7620 Jeong Chi-Young 1* Isayama Hiroyuki Academic Editor 1 Department of Surgery, Gyeongsang National University Hospital, Gyeongsang National University College of Medicine, 79, Gangnam-ro, Jinju 52727, Korea; hbpcjk@naver.com (J.-K.C.); drkhg@naver.com (H.-G.K.); jmjidia@hanmail.net (J.-M.K.); drksj77@naver.com (S.-J.K.); goodgsdr@gmail.com (J.-H.P.); juyeon0910@hanmail.net (J.-Y.K.); drjyt@naver.com (Y.-T.J.) 2 Department of Surgery, Gyeongsang National University Changwon Hospital, Gyeongsang National University College of Medicine, 11, Samjeongja-ro, Changwon-si 51472, Korea; jaripo@gmail.com (J.-R.K.); alitaalita@naver.com (J.-Y.J.) * Correspondence: rett0322@naver.com; Tel.: +82-10-9360-8294 08 5 2022 5 2022 11 9 264418 3 2022 06 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Although laparoscopic treatment for T1 gallbladder cancer (GBC) has been described previously, the differences in oncologic outcomes between laparoscopic and conventional open surgery for T2 GBC have not been investigated. We aimed to assess the role of laparoscopic surgery using retrospectively collected data for 81 patients with T2 GBC who underwent surgical resection between January 2010 and December 2017. Eligible patients were classified into “laparoscopic” and “open” groups. Propensity-score matching was performed in a 1:1 ratio. The effects of surgery type on surgical and oncological outcomes were investigated. After propensity-score matching, 19 patients were included in the open and laparoscopic surgery groups. The median follow-up durations were 70 and 26 months in the open and laparoscopic groups, respectively. The operative time (316.8 ± 80.3 vs. 218.9 ± 145.0 min, p = 0.016) and length of postoperative hospital stay (14.4 ± 6.0 vs. 8.4 ± 5.9 days, p = 0.004) were significantly shorter in the laparoscopic group. The three-year overall (86.3% vs. 88.9%, p = 0.660) and disease-free (76.4% vs. 60.2%, p = 0.448) survival rates were similar between the groups. Propensity-score matching showed that laparoscopic surgery for T2 GBC yielded similar long-term oncological outcomes and favorable short-term outcomes in comparison with open surgery. Laparoscopic treatment should be considered in patients with T2 GBC. gallbladder carcinoma oncological outcome laparoscopy This research received no external funding. ==== Body pmc1. Introduction Gallbladder cancer (GBC) is the fifth most common carcinoma of the gastrointestinal tract and the most common carcinoma of the biliary tract [1], with an overall incidence of 3 per 100,000 persons [2]. Curative resection is the only effective treatment for GBC [3,4]. Conventional open extended cholecystectomy, including dissection of the regional lymph node (LN) and wedge resection of the gallbladder bed, is the standard curative resection technique for GBC [5,6]. Laparoscopic surgery was originally associated with a risk of inadequate curative resection and tumor cell spread during surgery [3,4,7]. However, with advancements in laparoscopic instruments and accumulation of surgical skills, laparoscopic surgical treatment has gained acceptance as a standard treatment method with oncological outcomes comparable to those of conventional open treatment. Moreover, laparoscopic surgery is widely used for various cancers, including stomach, colon, and rectal cancer [8,9,10,11]. With the increased use of laparoscopic techniques for gallbladder disease treatment, cases of incidentally discovered GBC after laparoscopic surgery are steadily increasing [12,13]. Additionally, with an increase in the number of laparoscopic approaches for GBC, the oncological adequacy of laparoscopic surgery, specifically for patients with T2 GBC, has become an important topic of debate [14]. Several recent studies have reported the feasibility of laparoscopic treatment for GBC [14,15,16,17,18]. However, these studies were retrospective and nonrandomized, and included only small numbers of cases [15,16,17,18]. Therefore, their findings were debatable, and the use of laparoscopic treatment for T2 GBC remains controversial, with oncological outcomes being challenging to determine. Retrospective studies can analyze large sample sizes but excluding selection and severity biases in such studies can be difficult. Using a propensity score (PS) to compare the two groups can reduce such biases by adjusting the observed pretreatment characteristics [19]. Accordingly, we used PS-matching analysis to evaluate and compare the feasibility and oncological outcomes of laparoscopic and open surgeries for T2 GBC. 2. Materials and Methods The need to obtain informed consent from participants was waived owing to the retrospective nature of the study, and the study was conducted in accordance with the Declaration of Helsinki. The institutional review board of Gyeongsang National University Hospital approved this retrospective study (approval number: GNUH 2017-03-018). 2.1. Patient Selection We retrospectively analyzed the medical data of patients who underwent laparoscopic or open surgery for GBC at Gyeongsang National University Hospital from January 2010 to December 2017. Patients with pathologically proven T2 GBC who underwent curative resection were included. The exclusion criteria were (1) a history of another primary malignancy, (2) incomplete resection, (3) combined resection with other organs, or (4) incomplete medical records. Patients were classified into laparoscopic and open surgery groups according to the type of surgery they underwent. Patients who underwent open surgery after laparoscopic surgery were considered as having undergone open surgery. 2.2. Surgical Procedure for GBC The surgical procedure selected for GBC was based on the recommendations of the Korean Association of Hepatobiliary and Pancreas Surgery: Simple cholecystectomy for T1a GBC, simple or extended cholecystectomy for T1b GBC, and extended cholecystectomy for T2 GBC or above. The use of cholecystectomy alone was defined as simple cholecystectomy. Cholecystectomy with further resection included LN dissection, liver resection, and/or bile duct resection. Patients who refused additional extended resection after simple cholecystectomy were followed-up without further intervention. At our institution, laparoscopic surgery is recommended for cases of suspected T1 or T2 GBC identified by preoperative abdominal computed tomography (CT) (no liver infiltration and no involvement of extrahepatic adjacent organs), based on the 26th World Congress of the International Association of Surgeons, Gastroenterologists, and Oncologists expert consensus [20]. Open surgery is recommended for patients showing extensive liver infiltration on CT, extrahepatic bile duct or adjacent organ involvement, and incidental diagnosis of GBC after open cholecystectomy. Open surgery is also recommended for patients who refuse to undergo laparoscopic treatment. 2.3. PS-Matching Analysis To achieve balance in the baseline variables between the laparoscopic and open surgery groups, PS matching was performed [21]. Patients in the laparoscopic surgery group were PS-matched in a 1:1 ratio with patients in the open surgery group. Many propensity models were tested with various covariates such as age, gender, preoperative American Society of Anesthesiologists (ASA) score, combined GB stone, pathologic T stage, pathologic N stage, simple cholecystectomy versus cholecystectomy with further resection, elevated carcinoembryonic antigen, elevated carbohydrate antigen 19-9, and adjuvant chemotherapy. After propensity score matching, we calculated the C-statistic and the standardized difference to get the best model. We chose the best-balanced PS matching model, which contained five covariates: Age, preoperative ASA score, pathologic T stage, simple cholecystectomy versus cholecystectomy with further resection, and adjuvant chemotherapy. After matching, all covariates had reduced standardized differences and were well balanced between the two groups (C-statistic = 0.808). 2.4. Measurements The following patient data were collected: Age, sex, body mass index, ASA score, presence of combined gallbladder stones, laboratory findings, preoperative tumor markers (carcinoembryonic antigen [CEA] and carbohydrate antigen 19-9), operative time, Clavien–Dindo classification [22,23], pathologic tumor size, pathologic tumor stage, pathologic LN stage, number of metastatic LNs, number of retrieved LNs, adjuvant chemotherapy, postoperative hospital stay, recurrence site, date of recurrence, and date of death. Pathological TN stage was defined according to the 8th edition of the American Joint Committee on Cancer. We compared the disease-free survival (DFS) and cancer-specific overall survival (OS) rates between the two groups. DFS was defined as the time from diagnosis to first recurrence. OS was defined as the time from diagnosis to death owing to a cancer-specific cause. 2.5. Statistical Analysis Statistical analysis was performed using SPSS version 22.0 (Released 2013; IBM Corp., Armonk, NY, USA). Statistical significance was set at p < 0.05. Categorical variables were expressed as the number of cases and percentage (%), and the chi-square test or Fisher’s exact test was used for univariate analysis. Univariate and multivariate analyses were performed using the Cox proportional hazards model to identify the factors associated with survival. The risks were expressed as hazard ratios (HRs) and 95% confidence intervals (Cis). CA19-9 and CEA were considered elevated if they were greater than 37 U/mL and greater than 5 ng/mL, respectively, according to the laboratory cut-off values often used in our center. Previous studies have routinely employed the cut-off age and tumor size of 60 years and greater than 1 cm. The Kaplan–Meier method was used to analyze survival, and variables were examined using a log-rank test. 3. Results 3.1. Patient Characteristics Between January 2010 and December 2017, 92 patients were diagnosed with T2 GBC and underwent surgical treatment. Of these, 11 were excluded from the analysis because of a history of another primary malignancy (n = 4), incomplete resection (n = 3), combined resection of other organs (n = 3), or incomplete medical records (n = 1). Ultimately, 81 patients were included in the analysis. 3.2. Before PS Matching Data on surgery type, baseline characteristics, and short-term surgical outcomes in the laparoscopic and open surgery groups before PS matching are shown in Table 1, Table 2 and Table 3, respectively. Laparoscopic and open surgeries were performed in 37 and 44 patients, respectively. The two groups showed no significant differences in surgery types. Simple cholecystectomy and cholecystectomy with LN dissection were predominant in the laparoscopic surgery group, whereas cholecystectomy with LN dissection and liver resection were predominant in the open surgery group (Table 1). Significant differences were observed between the groups in terms of age and ASA scores (Table 2). The surgical outcomes also differed between the laparoscopic and open surgery groups. The operative time was significantly shorter in the laparoscopic group than in the open surgery group (165.8 ± 128.8 vs. 332.3 ± 93.3 min, p < 0.001). The open surgery group had more retrieved LNs, had more metastatic LNs, showed a more advanced N stage, and had longer hospital stays than the laparoscopic surgery group (Table 3). The median follow-up durations in the laparoscopic and open surgery groups were 21 and 48 months, respectively. The Kaplan–Meier curves for DFS and OS are shown in Figure 1 and Figure 2, respectively. The two groups showed no significant differences in the three-year DFS and OS rates (DFS: 65.0% vs. 66.7%, p = 0.721; cancer-specific OS: 78.0% vs. 82.4%, p = 0.782). 3.3. Comparison of the Laparoscopic and Open Surgery Groups after PS Matching Nineteen patients in each group were selected for PS-matching analyses. All covariates were well-balanced between the two groups (C-statistic = 0.808). The surgery types were matched between the two groups (Table 4). The baseline characteristics of the PS-matched patients are presented in Table 2. Preoperative conditions, laboratory findings, and tumor markers were not significantly different between the two groups. However, with regard to surgical outcomes, the laparoscopic group had a significantly shorter operative time and hospital stay than the open surgery group (218.9 ± 145.0 vs. 316.8 ± 80.3 min, p = 0.016; 8.4 ± 5.9 vs. 14.4 ± 6.0 days, p = 0.004, respectively; Table 3). No significant differences were observed in the other clinicopathological factors, including metastatic LNs (0.4 ± 0.9 vs. 0.4 ± 1.0, p > 0.999), retrieved LNs (5.3 ± 6.3 vs. 7.3 ± 5.5, p = 0.319), and complication rate (21.1% vs. 10.5%, p = 0.660). Postoperative complications occurred in four (21.1%) patients in the laparoscopic surgery group, including wound infection (n = 3) and bile leakage (n = 1). In comparison, two (10.5%) patients in the open surgery group had postoperative complications, including symptomatic fluid collection in the gallbladder bed (n = 1) and wound infection (n = 1). No gallbladder perforation occurred during surgery, and no deaths were observed in either group. The median follow-up durations in the laparoscopic and open surgery groups were 26 and 70 months, respectively. The Kaplan–Meier curves for DFS and OS are shown in Figure 3 and Figure 4, respectively. The two groups showed no significant differences in the three-year DFS and OS rates (DFS: 60.2% vs. 76.4%, p = 0.448; cancer-specific OS: 88.9% vs. 86.3%, p = 0.660). 3.4. Prognostic Factors for T2 GBC To identify the prognostic factors of survival in T1–T2 GBC, we used univariate Cox regression analysis, and the results are presented in Table 5. In the univariate analysis, LN metastasis and elevated CEA levels (>5 ng/mL) were significantly associated with poorer oncologic outcomes in T2 GBC. In the multivariate Cox regression analysis, LN metastasis was independently associated with T2 GBC survival (HR = 9.336, 95% CI = 2.295–37.985, p = 0.002). The type of surgery (laparoscopic vs. open surgery) was not a prognostic factor (HR = 1.130, 95% CI = 0.247–5.167, p = 0.875). 4. Discussion This study compared the surgical outcomes associated with laparoscopic and open surgery using PS-matching analysis for T2 GBC. Our results showed that the effectiveness of laparoscopic surgery for T2 GBC was not inferior to that of open surgery in terms of perioperative outcomes and the three-year DFS and OS rates. Additionally, laparoscopic surgery offers significant functional advantages, such as a shorter operative time and length of hospital stay. Improvements in instrumentation and advanced surgical skills have led to the widespread use of laparoscopic treatment for gastrointestinal tract cancers [24]. Laparoscopic treatment has been accepted as a standard method for early-stage tumors, with oncological and surgical outcomes comparable to those of open surgery [8,9,10,11]. Several studies have reported that laparoscopic surgery for patients with T1 GBC leads to similar or better treatment outcomes than open surgery [17,24,25,26]. Recently, laparoscopic surgery has become feasible at selected high-volume referral centers and has shown outcomes similar to those of open surgery in patients with T2 GBC [15,16,27,28,29]. However, the clinical value of laparoscopic surgery for T2 GBC remains controversial, and current guidelines such as those by the National Comprehensive Cancer Network and the Japanese Society of Hepato-Biliary-Pancreatic Surgery do not recommend laparoscopic surgery for T1 and T2 GBC because it is associated with a higher risk of tumor dissemination and port-site recurrence than open surgery [3,5,6,30]. Port-site recurrence and tumor dissemination due to gallbladder perforation have been observed after laparoscopic cholecystectomy, even in patients with early-stage GBC [7,31]. However, these reports were based on older studies, and gallbladder perforation occurred predominantly in patients with suspected benign pathology, with dissection in the thin cystic plate [29]. Moreover, tumor dissemination is not a specific complication of laparoscopic surgery and can also occur in open surgery. Appropriate use of a plastic endo-bag and careful management of the gallbladder can prevent port-site recurrence and tumor dissemination [14,20]. In this study, we found that laparoscopy was associated with oncological outcomes comparable to those in open treatment, with the additional advantages of shorter operative time and length of hospital stay. Similarly, Cho et al. [17], Gumbs et al. [28], and Agarwal et al. [29] reported that radical laparoscopic surgery is a feasible treatment modality with oncologic outcomes comparable to those of open surgery. However, these studies had several limitations, including the use of a non-randomized design, which may have led to a selection bias between the laparoscopic and open surgery groups [15,16,17,18,29]. Consequently, we used PS matching to reduce the possibility of selection bias and obtain high-quality evidence. To the best of our knowledge, the present study is the first to compare the surgical and long-term oncological outcomes of laparoscopic and open surgery for T2 GBC using PS-matching analysis. LN dissection is necessary for curative resection because LN metastasis is an independent prognostic factor for GBC [32], and LN metastasis occurs at a rate of up to 62% in GBC [33,34,35,36,37]. This study reported that the only independent prognostic factor affecting oncological outcomes in T2 GBC was LN metastasis. The surgical approach did not affect the oncological outcomes. However, this study has some limitations. First, only a small number of patients were included in this study. Second, the retrospective single-center design of the study may limit the generalizability of the results. Larger prospective studies are required to verify our findings. 5. Conclusions In conclusion, laparoscopic surgery could become the standard treatment modality for T2 GBC patients owing to its favorable short-term and long-term outcomes. Author Contributions J.-K.C., conceptualization, data curation, formal analysis, investigation, methodology software, and writing of the original draft; C.-Y.J., conceptualization, methodology, supervision, writing of the original draft, and reviewing and editing the manuscript; J.-Y.J., J.-R.K., conceptualization, methodology, data curation and formal analysis; H.-G.K., J.-M.K., S.-J.K., J.-H.P., J.-Y.K., Y.-T.J., formal analysis, reviewed the manuscript and edited the draft. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal care and experimental procedures were approved by the Ethics of Animal Experiments Committee of Gyeongsang National University (GNUH 2017-03-018). Informed Consent Statement The need to obtain informed consent from participants was waived owing to the retrospective nature of the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Disease-free survival in the T2 GBC patients by surgery type. The disease-free survival rate in the propensity-score-matched patients at three years was 65.0% and 66.7% in the laparoscopic and open surgery groups, respectively. The two groups showed no significant difference in recurrence (p = 0.721). Figure 2 The cancer-specific survival rate in T2GBC patients by surgery type. The cancer-specific survival rates in the propensity-score-matched patients at three years were 78.0% and 82.4% in the laparoscopic and open surgery groups, respectively. No significant differences were observed between the laparoscopic and open surgery groups (p = 0.782) in terms of survival. Figure 3 Disease-free survival in the propensity-score-matched patients by surgery type. The disease-free survival rate in the propensity-score-matched patients at three years was 60.2% and 76.4% in the laparoscopic and open surgery groups, respectively. The two groups showed no significant difference in recurrence (p = 0.448). Figure 4 The cancer-specific survival rate in the propensity-score-matched patients by surgery type. The cancer-specific survival rates in the propensity-score-matched patients at three years were 88.9% and 86.3% in the laparoscopic and open surgery groups, respectively. No significant differences were observed between the laparoscopic and open surgery groups (p = 0.660) in terms of survival. jcm-11-02644-t001_Table 1 Table 1 Comparison of surgery type in patients before propensity-score matching. Type of Surgery Laparoscopic (n = 37) Open (n = 44) p-Value Simple cholecystectomy 18 (48.6%) 5 (11.4%) <0.001 Cholecystectomy + LND 11 (29.7%) 2 (4.5%) Cholecystectomy + LND + HR 7 (18.9%) 31 (70.5%) Cholecystectomy + LND + BDR 0 (0%) 1 (2.3%) Cholecystectomy + LND + HR + BDR 1 (2.7%) 5 (11.4%) LND, dissection of regional lymph nodes; HR, gallbladder bed wedge resection; BDR, common bile duct resection. jcm-11-02644-t002_Table 2 Table 2 Baseline characteristics of the patients. Before PS Matching PS-Matched Variable Lap. (n = 37) * Open (n = 44) * p-Value Lap. (n = 19) * Open (n = 19) * p-Value Age (years) 72.1 ± 9.3 63.7 ± 9.6 <0.001 69.9 ± 9.1 66.7 ± 7.8 0.251 Sex (M:F) 16:21 26:18 0.184 8:11 12:7 0.330 BMI (kg/m2) 23 ± 3.1 22.6 ± 2.9 0.591 22.9 ± 3.1 23.0 ± 3.1 0.933 ASA (1/2/3/4) 1/16/18/1 2/33/9/0 0.009 0/14/5/0 0/14/5/0 >0.999 Combined GB stone 11 (29.7%) 5 (11.4%) 0.051 4 (21.1%) 1 (5.3%) 0.340 Total bilirubin (mg/dL) 1.2 ± 1.8 1.2 ± 1.2 0.924 1.6 ± 2.4 1.4 ± 1.4 0.794 AST (U/L) 23.6 ± 18 41.1 ± 70.2 0.144 21.4 ± 17.7 27.1 ± 22.7 0.400 ALT (U/L) 22.2 ± 14.9 47.7 ± 73.8 0.042 22.1 ± 14.5 30.0 ± 25.4 0.253 CEA (ng/mL) 4.5 ± 7.7 4.1 ± 6.4 0.827 3.3 ± 4.0 1.81 ± 0.6 0.152 CA19-9 (U/mL) 44 ± 87.3 55.3 ± 108.9 0.657 33.7 ± 32.2 38.1 ± 37.0 0.747 * Categorical variables are expressed as percentages and continuous variables are expressed as mean ± standard deviation. PS, propensity score; Lap, laparoscopic; BMI, body mass index; ASA, American Society of Anesthesiologists physical status classification system; GB, gallbladder; AST, aspartate aminotransferase; ALT, alanine aminotransferase; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9. jcm-11-02644-t003_Table 3 Table 3 Surgical outcomes of the patients. Before PS Matching After PS Matching Variable Lap. (n = 37) * Open (n = 44) * p-Value Lap. (n = 21) * Open (n = 21) * p-Value Operative time (min) 165.8 ± 128.8 332.3 ± 93.3 <0.001 218.9 ± 145.0 316.8 ± 80.3 0.016 Complication rate 5 (13.5%) 11 (25%) 0.265 4 (21.1%) 2 (10.5%) 0.660 Clavien–Dindo classification (I, II, IIIa/IIIb, IV, V) 5/0 (13.5%/0%) 10/1 (22.7%/2.3%) 0.392 4/0 (21.1%/0%) 2/0 (10.5%/0%) 0.660 Tumor size (mm) 24.6 ± 14 31.8 ± 18.6 0.052 23.1 ± 11.2 27.4 ± 15.6 0.341 T2a 15 (40.5%) 21 (47.7%) 0.654 7 (33.3%) 7 (33.3%) >0.999 T2b 22 (59.5%) 23 (52.3%) 12 (57.1%) 12 (57.1%) N0 16 (43.2%) 27 (61.4%) <0.001 12 (63.2%) 14 (73.7%) 0.693 N1 6 (16.2%) 14 (31.8%) 4 (21.1%) 4 (21.1%) N2 0 (0%) 2 (4.5%) 0 (0%) 0 (0%) Nx 15 (40.5%) 1 (2.3%) 3 (15.8%) 1 (5.3%) No. of positive LNs 0.3 ± 0.7 1.1 ± 2.1 0.024 0.4 ± 0.9 0.4 ± 1.0 >0.999 No. of retrieved LNs 3.4 ± 5.4 8.2 ± 5.2 <0.001 5.3 ± 6.6 7.3 ± 5.5 0.319 Adjuvant chemotherapy 11 (29.7%) 22 (50%) 0.074 7 (36.8%) 7 (36.8%) >0.999 Length of hospital stay (day) 6.8 ± 4.9 15 ± 7.5 <0.001 8.4 ± 5.9 14.4 ± 6.0 0.004 * Categorical variables are expressed as percentages and continuous variables are expressed as mean ± standard deviation. PS, propensity score; Lap, laparoscopic. jcm-11-02644-t004_Table 4 Table 4 Comparison of surgery type in the propensity-score-matched patients. Type of Surgery Laparoscopic (n = 19) Open (n = 19) Simple cholecystectomy 4 (21.1%) 4 (21.1%) Cholecystectomy with further resection 15 (78.9%) 15 (78.9%) jcm-11-02644-t005_Table 5 Table 5 Prognostic factors in T2 gallbladder cancer patients (n = 81). Variables Univariate Analysis Multivariate Analysis HR 95% CI p-Value HR 95% CI p-Value Female sex 1.403 0.376–5.232 0.514 Age >60 years 1.489 0.308–7.205 0.621 Overweight (BMI > 25 kg/m2) 1.632 0.437–6.093 0.466 CEA (>5 ng/mL) 6.328 1.134–35.320 0.035 3.608 0.556–23.395 0.179 CA19-9 (>37 U/mL) 26.762 0.010–68,340.593 0.412 Further resection 0.700 0.175–2.801 0.614 GB stone 1.625 0.203–13.005 0.647 Tumor size (>1 cm) 24.395 0.003–202,140.970 0.488 T stage (T2a vs. T2b) 6.515 0.814–52.138 0.077 Node metastasis 9.336 2.295–37.985 0.002 9.336 2.295–37.985 0.002 Complication 1.467 0.303–7.095 0.634 Adjuvant chemotherapy 1.717 0.426–6.925 0.447 Laparoscopic surgery 0.822 0.204–3.309 0.783 1.130 0.247–5.167 0.875 HR, hazard ratio; CI, confidence interval; BMI, body mass index; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; GB, gallbladder. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Varshney S. Butturini G. Gupta R. Incidental Carcinoma of the Gallbladder Eur. J. Surg. Oncol. 2002 28 4 10 10.1053/ejso.2001.1175 11869005 2. Shindoh J. de Aretxabala X. Aloia T.A. Roa J.C. Roa I. Zimmitti G. Javle M. Conrad C. Maru D.M. Aoki T. Tumor Location Is a Strong Predictor of Tumor Progression and Survival in T2 Gallbladder Cancer: An International Multicenter Study Ann. Surg. 2015 261 733 739 10.1097/SLA.0000000000000728 24854451 3. Steinert R. Nestler G. Sagynaliev E. Müller J. Lippert H. Reymond M.A. Laparoscopic Cholecystectomy and Gallbladder Cancer J. Surg. Oncol. 2006 93 682 689 10.1002/jso.20536 16724350 4. Weiland S.T. Mahvi D.M. Niederhuber J.E. Heisey D.M. Chicks D.S. Rikkers L.F. Should Suspected Early Gallbladder Cancer Be Treated Laparoscopically? J. Gastrointest. Surg. 2002 6 50 56 10.1016/S1091-255X(01)00014-2 11986018 5. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidlines®) Hepatobiliary Cancers. 2.2018 Version Available online: www.NCCN.org (accessed on 23 February 2018) 6. Kondo S. Takada T. Miyazaki M. Miyakawa S. Tsukada K. Nagino M. Furuse J. Saito H. Tsuyuguchi T. Yamamoto M. Guidelines for the Management of Biliary Tract and Ampullary Carcinomas: Surgical Treatment J. Hepatobiliary Pancreat. Surg. 2008 15 41 54 10.1007/s00534-007-1279-5 18274843 7. Reddy Y.P. Sheridan W.G. Port-Site Metastasis Following Laparoscopic Cholecystectomy: A Review of the Literature and a Case Report Eur. J. Surg. Oncol. 2000 26 95 98 10.1053/ejso.1999.0750 10718188 8. Han H.S. Yoon Y.S. Cho J.Y. Hwang D.W. Laparoscopic Liver Resection for Hepatocellular Carcinoma: Korean Experiences Liver Cancer 2013 2 25 30 10.1159/000346224 24159593 9. Guerrieri M. Campagnacci R. De Sanctis A. Lezoche G. Massucco P. Summa M. Gesuita R. Capussotti L. Spinoglio G. Lezoche E. Laparoscopic Versus Open Colectomy for TNM stage III Colon Cancer: Results of a Prospective Multicenter Study in Italy Surg. Today. 2012 42 1071 1077 10.1007/s00595-012-0292-8 22903270 10. Cai J. Wei D. Gao C.F. Zhang C.S. Zhang H. Zhao T. A Prospective Randomized Study Comparing Open Versus Laparoscopy-Assisted D2 Radical Gastrectomy in Advanced Gastric Cancer Dig. Surg. 2011 28 331 337 10.1159/000330782 21934308 11. Nelson H. Sargent D.J. Wieand H.S. Fleshman J. Anvari M. Stryker S.J. Beart R.W. Jr. Hellinger M. Flanagan R. Jr. Peters W. Clinical Outcomes of Surgical Therapy Study Group). A Comparison of Laparoscopically Assisted and Open Colectomy for Colon Cancer N. Engl. J. Med. 2004 350 2050 2059 10.1056/NEJMoa032651 15141043 12. Goetze T. Paolucci V. Does Laparoscopy Worsen the Prognosis for Incidental Gallbladder Cancer? Surg. Endosc. 2006 20 286 293 10.1007/s00464-005-0121-x 16362480 13. Shih S.P. Schulick R.D. Cameron J.L. Lillemoe K.D. Pitt H.A. Choti M.A. Campbell K.A. Yeo C.J. Talamini M.A. Gallbladder Cancer: The Role of Laparoscopy and Radical Resection Ann. Surg. 2007 245 893 901 10.1097/SLA.0b013e31806beec2 17522515 14. Yoon Y.S. Han H.S. Cho J.Y. Choi Y. Lee W. Jang J.Y. Choi H. Is Laparoscopy Contraindicated for Gallbladder Cancer? A 10-Year Prospective Cohort Study J. Am. Coll. Surg. 2015 221 847 853 10.1016/j.jamcollsurg.2015.07.010 26272017 15. Shirobe T. Maruyama S. Laparoscopic Radical Cholecystectomy With Lymph Node Dissection for Gallbladder Carcinoma Surg. Endosc. 2015 29 2244 2250 10.1007/s00464-014-3932-9 25303926 16. Itano O. Oshima G. Minagawa T. Shinoda M. Kitago M. Abe Y. Hibi T. Yagi H. Ikoma N. Aiko S. Novel Strategy for Laparoscopic Treatment of pT2 Gallbladder Carcinoma Surg. Endosc. 2015 29 3600 3607 10.1007/s00464-015-4116-y 25740638 17. Cho J.Y. Han H.S. Yoon Y.S. Ahn K.S. Kim Y.H. Lee K.H. Laparoscopic Approach for Suspected Early-Stage Gallbladder Carcinoma Arch. Surg. 2010 145 128 133 10.1001/archsurg.2009.261 20157079 18. De Aretxabala X. Oppliger F. Solano N. Rencoret G. Vivanco M. Carvajal D. Hepp J. Roa I. Laparoscopic Management of Incidental Gallbladder Cancer Surg. Endosc. 2018 32 4251 4255 10.1007/s00464-018-6173-5 29926166 19. McCaffrey D.F. Griffin B.A. Almirall D. Slaughter M.E. Ramchand R. Burgette L.F. A Tutorial on Propensity Score Estimation for Multiple Treatments Using Generalized Boosted Models Stat. Med. 2013 32 3388 3414 10.1002/sim.5753 23508673 20. Han H.S. Yoon Y.S. Agarwal A.K. Belli G. Itano O. Gumbs A.A. Yoon D.S. Kang C.M. Lee S.E. Wakai T. Laparoscopic Surgery for Gallbladder Cancer: An Expert Consensus Statement Dig. Surg. 2019 36 1 6 10.1159/000486207 29339660 21. Brookhart M.A. Wyss R. Layton J.B. Stürmer T. Propensity Score Methods for Confounding Control in Nonexperimental Research Circ. Cardiovasc. Qual. Outcomes. 2013 6 604 611 10.1161/CIRCOUTCOMES.113.000359 24021692 22. Dindo D. Demartines N. Clavien P.A. Classification of Surgical Complications: A New Proposal With Evaluation in a Cohort of 6336 Patients and Results of a Survey Ann. Surg. 2004 240 205 213 10.1097/01.sla.0000133083.54934.ae 15273542 23. Clavien P.A. Barkun J. de Oliveira M.L. Vauthey J.N. Dindo D. Schulick R.D. de Santibañes E. Pekolj J. Slankamenac K. Bassi C. The Clavien-Dindo Classification of Surgical Complications: Five-Year Experience Ann. Surg. 2009 250 187 196 10.1097/SLA.0b013e3181b13ca2 19638912 24. Jang J.Y. Heo J.S. Han Y. Chang J. Kim J.R. Kim H. Kwon W. Kim S.W. Choi S.H. Choi D.W. Impact of Type of Surgery on Survival Outcome in Patients With Early Gallbladder Cancer in the Era of Minimally Invasive Surgery: Oncologic Safety of Laparoscopic Surgery Medicine 2016 95 e3675 10.1097/MD.0000000000003675 27258495 25. Lee S.E. Jang J.Y. Lim C.S. Kang M.J. Kim S.W. Systematic Review on the Surgical Treatment for T1 Gallbladder Cancer World J. Gastroenterol. 2011 17 174 180 10.3748/wjg.v17.i2.174 21245989 26. Lee S.E. Kim K.S. Kim W.B. Kim I.G. Nah Y.W. Ryu D.H. Park J.S. Yoon M.H. Cho J.Y. Hong T.H. Practical Guidelines for the Surgical Treatment of Gallbladder Cancer J. Korean Med. Sci. 2014 29 1333 1340 10.3346/jkms.2014.29.10.1333 25368485 27. Machado M.A. Makdissi F.F. Surjan R.C. Totally Laparoscopic Hepatic Bisegmentectomy (s4b+s5) and Hilar Lymphadenectomy for Incidental Gallbladder Cancer Ann. Surg. Oncol. 2015 22 (Suppl. S3) S336 S339 10.1245/s10434-015-4650-9 26059653 28. Gumbs A.A. Hoffman J.P. Laparoscopic Completion Radical Cholecystectomy for T2 Gallbladder Cancer Surg. Endosc. 2010 24 3221 3223 10.1007/s00464-010-1102-2 20499105 29. Agarwal A.K. Javed A. Kalayarasan R. Sakhuja P. Minimally Invasive Versus the Conventional Open Surgical Approach of a Radical Cholecystectomy for Gallbladder Cancer: A Retrospective Comparative Study HPB 2015 17 536 541 10.1111/hpb.12406 25727091 30. Miyazaki M. Yoshitomi H. Miyakawa S. Uesaka K. Unno M. Endo I. Takada T. Clinical Practice Guidelines for the Management of Biliary Tract cancers 2015: The 2nd English edition J. Hepatobiliary Pancreat. Sci. 2015 22 249 273 10.1002/jhbp.233 25787274 31. Wullstein C. Woeste G. Barkhausen S. Gross E. Hopt U.T. Do Complications Related to Laparoscopic Cholecystectomy Influence the Prognosis of Gallbladder Cancer? Surg. Endosc. 2002 16 828 832 10.1007/s00464-001-9085-7 11997831 32. Yamaguchi K. Chijiiwa K. Saiki S. Nishihara K. Takashima M. Kawakami K. Tanaka M. Retrospective Analysis of 70 Operations for Gallbladder Carcinoma Br. J. Surg. 1997 84 200 204 10.1046/j.1365-2168.1997.02498.x 9052434 33. Goetze T.O. Paolucci V. Adequate Extent in Radical re-Resection of Incidental Gallbladder Carcinoma: Analysis of the German Registry Surg. Endosc. 2010 24 2156 2164 10.1007/s00464-010-0914-4 20177938 34. Sikora S.S. Singh R.K. Surgical Strategies in Patients With Gallbladder Cancer: Nihilism to Optimism J. Surg. Oncol. 2006 93 670 681 10.1002/jso.20535 16724356 35. Wakai T. Shirai Y. Hatakeyama K. Radical Second Resection Provides Survival Benefit for Patients With T2 Gallbladder Carcinoma First Discovered After Laparoscopic Cholecystectomy World J. Surg. 2002 26 867 871 10.1007/s00268-002-6274-z 11960212 36. Toyonaga T. Chijiiwa K. Nakano K. Noshiro H. Yamaguchi K. Sada M. Terasaka R. Konomi K. Nishikata F. Tanaka M. Completion Radical Surgery After Cholecystectomy for Accidentally Undiagnosed Gallbladder Carcinoma World J. Surg. 2003 27 266 271 10.1007/s00268-002-6609-9 12607049 37. Chijiiwa K. Nakano K. Ueda J. Noshiro H. Nagai E. Yamaguchi K. Tanaka M. Surgical Treatment of Patients With T2 Gallbladder Carcinoma Invading the Subserosal Layer J. Am. Coll. Surg. 2001 192 600 607 10.1016/S1072-7515(01)00814-6 11333097

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093308 materials-15-03308 Article Nonlinear Elasticity Assessment with Optical Coherence Elastography for High-Selectivity Differentiation of Breast Cancer Tissues https://orcid.org/0000-0001-5416-3241 Gubarkova Ekaterina V. 1* Sovetsky Aleksander A. 2 https://orcid.org/0000-0001-5736-820X Matveev Lev A. 2 https://orcid.org/0000-0001-9642-6580 Matveyev Aleksander L. 2 Vorontsov Dmitry A. 3 https://orcid.org/0000-0003-0301-5358 Plekhanov Anton A. 1 Kuznetsov Sergey S. 34 https://orcid.org/0000-0002-0223-0753 Gamayunov Sergey V. 3 Vorontsov Alexey Y. 3 Sirotkina Marina A. 1 Gladkova Natalia D. 1† https://orcid.org/0000-0002-2122-2943 Zaitsev Vladimir Y. 2† Wei Gang Academic Editor Duma Virgil-Florin Academic Editor 1 Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603950 Nizhny Novgorod, Russia; strike_gor@mail.ru (A.A.P.); sirotkina_m@mail.ru (M.A.S.); natalia.gladkova@gmail.com (N.D.G.) 2 Institute of Applied Physics of the Russian Academy of Sciences, 46 Ulyanova St., 603950 Nizhny Novgorod, Russia; alex.sovetsky@mail.ru (A.A.S.); lionnn52rus@mail.ru (L.A.M.); matveyev@ipfran.ru (A.L.M.); vyuzai@ipfran.ru (V.Y.Z.) 3 Nizhny Novgorod Regional Oncologic Hospital, 11/1 Delovaya St., 603126 Nizhny Novgorod, Russia; dr.vorontsovdmitriy@rambler.ru (D.A.V.); zunek@mail.ru (S.S.K.); gamajnovs@mail.ru (S.V.G.); doctorvorontsov@mail.ru (A.Y.V.) 4 Department of Pathology, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603950 Nizhny Novgorod, Russia * Correspondence: kgybarkova@mail.ru † These authors contributed equally to this work. 05 5 2022 5 2022 15 9 330824 2 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Soft biological tissues, breast cancer tissues in particular, often manifest pronounced nonlinear elasticity, i.e., strong dependence of their Young’s modulus on the applied stress. We showed that compression optical coherence elastography (C-OCE) is a promising tool enabling the evaluation of nonlinear properties in addition to the conventionally discussed Young’s modulus in order to improve diagnostic accuracy of elastographic examination of tumorous tissues. The aim of this study was to reveal and quantify variations in stiffness for various breast tissue components depending on the applied pressure. We discussed nonlinear elastic properties of different breast cancer samples excised from 50 patients during breast-conserving surgery. Significant differences were found among various subtypes of tumorous and nontumorous breast tissues in terms of the initial Young’s modulus (estimated for stress < 1 kPa) and the nonlinearity parameter determining the rate of stiffness increase with increasing stress. However, Young’s modulus alone or the nonlinearity parameter alone may be insufficient to differentiate some malignant breast tissue subtypes from benign. For instance, benign fibrous stroma and fibrous stroma with isolated individual cancer cells or small agglomerates of cancer cells do not yet exhibit significant difference in the Young’s modulus. Nevertheless, they can be clearly singled out by their nonlinearity parameter, which is the main novelty of the proposed OCE-based discrimination of various breast tissue subtypes. This ability of OCE is very important for finding a clean resection boundary. Overall, morphological segmentation of OCE images accounting for both linear and nonlinear elastic parameters strongly enhances the correspondence with the histological slices and radically improves the diagnostic possibilities of C-OCE for a reliable clinical outcome. compression optical coherence elastography (C-OCE) nonlinear elasticity breast cancer breast tissues Russian Science Foundation18-75-10068 The study was funded by the Russian Science Foundation, grant No. 18-75-10068. ==== Body pmc1. Introduction Compressional optical coherence elastography (C-OCE) is an emerging tool used to assess elastic properties of biological tissues with a resolution of a few tens of micrometers due to a fairly high (micrometer-scale) resolution of the basic visualization method, optical coherence tomography (OCT) [1,2]. The development of C-OCE has been strongly influenced by the elastographic modality in medical ultrasounds (US), where elastography based on the compression principle was proposed in 1991 [3], and in the last two decades the US-based elastography became routinely used in clinic. This new modality radically enhanced the contrast of ultrasonic detection of tumors and improved their assessment (see, e.g., [4,5,6]). In OCT, the elastography-related studies were triggered about a decade later than in ultrasound after a paper [7] published by Schmitt in 1998. The key point in the realization of C-OCE is the estimation of axial strains in the soft tissue, in which approximately uniaxial stress is created by compressing the studied region by the output window of the OCT probe [3]. The elastography method used in the present work is based on phase-sensitive OCT, the signal of which is highly sensitive to motions of scatterers in the tissue [8,9]. Appropriate processing of phase-sensitive OCT signals makes it possible to quantify and map local strains in the tissue [10,11,12,13]. Quantitative estimation of the tissue elasticity in compressional OCE is based on the comparison of strain in the examined tissue and the precalibrated reference layer, which is usually made of weakly scattering silicone. It is placed between the OCT probe and the compressed tissue and plays the role of optical stress sensor. Conventionally, the elasticity of biological tissue is characterized by the Young’s modulus (of shear modulus) [3,7] measured at small strains and described in the framework of the linear theory of elasticity. However, mechanical measurements of the elasticity of biological tissues (see, for example, [14]) indicated that the stress–strain dependence of these tissues can be pronouncedly nonlinear. In other words, the current elastic modulus of the tissue essentially depends on the applied stress and current strain. Recently, it was clearly demonstrated that silicones used as reference layers in C-OCE are highly linear materials in contrast to biological tissues [15,16]. Therefore, the strain of the reference silicone is linearly proportional to the applied stress [17], so that by simultaneously measuring strains in the reference silicone layer and the underlying compressed tissue, one can readily obtain and quantify the nonlinear stress–strain relationship for the tissue in a broad strain range. Examples of nonlinear stress–strain curves obtained by such a method with linear reference layers are given in [15,16,17]. Independently, similar nonlinear curves were demonstrated by combining OCT-based approximate estimates of strain with stress estimation by a force sensor [18]. Although in standard elastographic examinations based on US-platforms that enable compression elastography (also often called “strain elastography” [6]) the interpretations in terms of strain ratios ignore the tissue nonlinearity, there are some known strain-elastography-based demonstrations of pronounced nonlinearity of biological tissues [19,20]. In particular, it was shown that the spatial strain distributions in breast tissues may radically change depending on the degree of precompression of the tissue [21,22]. However, up to now, standard US-scanners based on measuring strain ratios do not enable quantitative control of precompression. The same relates to shear-wave US-elastography enabling quantitative estimates of the elastic modulus without accounting for possible tissue nonlinearity. Although both widely used variants of US-elastography (compression-based strain elastography and shear-wave realizations) have already proven their high utility in biomedical diagnostics, there are numerous examples of erroneous diagnostic conclusions that are based on estimations of the elastic modulus only. The point is that the characteristic ranges of either strain ratios or absolute values of the estimated elastic modulus may overlap for different tissue types (e.g., for benign and malignant lesions). Another closely related issue is that for the same tissue type, its elastic properties may pronouncedly (up to several times) vary depending on precompression. In this regard, utilization of quantitative C-OCE attracted much attention in recent years for examining very heterogeneous tissues such as cancerous lesions. OCE has been investigated for imaging the biomechanical (stiffness) properties of breast [23,24,25] and other cancers ex vivo [26], with potential applications in tumor-margin detection [27,28]. In some works [16,17,18], possibilities of quantitative C-OCE were demonstrated for obtaining nonlinear stress–strain dependencies for biological tissues. In particular, this ability of C-OCE was used for estimation of the tissue elastic modulus under controllable pressure [17]. Experimental results, such as in [25], in which quantitative C-OCE was combined with controllable precompression, demonstrated a high potential for differentiating subtypes of breast cancer tissues using differences in their elastic behavior, even if the elastic moduli of those tissues were pronouncedly pressure-dependent because of nonlinearity. Studies in this direction are of high importance because female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer [29]. It is known that typically breast cancer tumors exhibit increased stiffness, but at the same time such tumors are very mechanically heterogeneous and may strongly differ in their morphological and molecular genetic characteristics [30]. Despite the high utility of the abovementioned conventional US-based elastographic techniques, they do not utilize information about the tissue nonlinearity (and in standard examinations US scanners with elastographic modality are not able to obtain such information). In addition, the resolution of conventional US-based techniques is not sufficient to characterize the abovementioned rather fine mechanical heterogeneity of tumors. At the same time, significantly higher resolution OCE combined with the ability to differentiate grades and/or morphomolecular subtypes of tumors (which may be further improved by simultaneous accounting for the differences in their linear and nonlinear elastic properties) opens very promising prospects for solving such an important problem as the intraoperative detection of a clean boundary for tumor resection during surgical interventions. In what follows, we describe an advanced variant of quantitative OCE enabling access to previously unavailable important diagnostic information. The main novelty in the described OCE-based diagnostics is that we combined the estimations of the Young’s modulus and the nonlinearity parameter. The latter helps to discriminate the breast tissue’s components even if the ranges of their Young’s moduli significantly overlap. In this context, the aim of the present study was to demonstrate that the application of the developed, advanced variant of quantitative C-OCE enables quantification of tissue stiffness under controllable pressure, as well as quantitative characterization of the tissue nonlinearity. We demonstrated that the combined assessment of stiffness and elastic nonlinearity is very promising for enhancing the accuracy of differentiation of breast cancer subtypes, even if the characteristic ranges of the conventionally estimated Young’s modulus essentially overlaps for these lesions. It was also demonstrated that the combined usage of both linear stiffness values and nonlinear elastic parameters improves the reliability of tumor boundary visualization. Furthermore, in the development of the automated method of morphological segmentation of C-OCE images based on differences in the tissue stiffness [25,31], in the present study we demonstrated an advanced variant of the OCE-based automated morphological segmentation taking into account both linear and nonlinear elastic parameters. 2. Materials and Methods 2.1. OCE Imaging and Assessment of Tissue Nonlinearity OCE data were acquired with a custom-made 20 kHz spectral-domain OCT system with a central wavelength of 1.3 µm and spectral width of 100 nm, having an axial resolution of ∼10 μm, lateral resolution of ∼15 μm, and enabling a visualization depth of 2 mm in air. A similar system was described in [32,33], where it was used to realize optical coherence angiography. OCT scans 256 × 256 pixels in size covered 4 mm in the lateral direction (with the possibility of stitching several scans in the lateral direction to cover up to 20 mm). A variant of compressional OCE described in [15,16,17] was used to visualize local interframe strains, as well as cumulative strains produced in the tissue by compressing it with the OCT probe. The OCT probe diameter was 10 mm and the visualization depth was always an order of magnitude smaller, such that the condition of depth-independence of the compression-produced stress held quite well in the OCE measurements [15]. For estimating the axial strains required for reconstruction of the Young’s modulus in the compression approach proposed in [3], local gradients of interframe phase variations were calculated using a robust vector method developed in [11,12,34]. For quantification of tissue stiffness in compressional OCE, a calibration (silicone) layer with a preliminary calibrated stiffness was used as described in detail in [15,17]. The silicone with the Young’s modulus in the range of 50–100 kPa was found to be the most suitable for studying breast tissue stiffness variations in a range from 20 kPa to ~1000 kPa or even greater. As schematically shown in Figure 1a, the reference silicone layer with a known stiffness was placed on the tissue surface and used as a sensor of the local stress. The OCT probe attached to an automated positioning stage (Purelogic R&D PLRA4, Voronezh, Russia) was slightly pressed onto the studied tissue, and the resultant strain distribution under the OCT probe was reconstructed in the same manner in both the weakly scattering reference silicone and the examined tissue under the silicone. A typical example of the acquired structural OCT scan is shown in Figure 1b, where the silicone and underlying tissue are clearly seen. Figure 1c shows a color-coded example of interframe phase variations, the vertical gradient of which are proportional to the interframe strains. The next, Figure 1d, shows the reconstructed distribution of cumulative strains found by processing a series of several tens of OCT scans. It has been carefully verified in previous works [15,16] that the elastic behavior of silicones is highly linear, so that incremental strains in silicone can be considered linearly proportional to the applied pressure (stress) up to fairly large cumulative strains of several tens of percentage. Therefore, the reference silicone can serve as a full-optical sensor of the local stress [17]. The inhomogeneity of cumulative strain (and, therefore, stress) in homogeneous silicone is clearly seen in Figure 1d. Because of the high nonlinearity of the majority of real biological tissues, the stress variations over the visualized region may result in unpredictable variations in the elastic modulus. To exclude this nonlinearity-related ambiguity, we developed a procedure of pressure standardization based on analysis of several tens of OCT images of the monotonically compressed tissue and reference layer. Then interframe strains were calculated, as well as cumulative strains in both the tissue and reference layer as a function of frame number. By plotting cumulative strain in the silicone (in which it was linearly proportional to stress) against cumulative strain in the tissue we, obtained stress–stress dependences as illustrated in Figure 1e. Such dependences are usually pronouncedly nonlinear. In principle, such curves can be obtained for every point of the tissue within the OCE scan, although for reducing measurement noise and obtaining more stable results, the plotted strains were usually averaged over a fairly small processing window. For the described system, the averaging-window size was ~90–100 µm. One half of the window size defined the strain-mapping resolution ~45–50 µm. The current (also called tangent) Young’s modulus for nonlinear tissue is proportional to the slope of stress–strain curves similar to those shown in Figure 1e. Thus, by differentiating the initially measured stress–strain curve, one obtains the Young’s modulus as a function of the current strain in the tissue. In practice, the experimentally measured stress–strain curve was fitted to eliminate the influence of measurement noises, and then the approximating curve was differentiated. The result of such differentiation corresponding to Figure 1e is shown in Figure 1f. However, since the local strain in the tissue may vary even for the same lateral coordinate, it is reasonable to replot the current Young’s modulus as a function of pressure (Figure 1g) because the latter is nearly invariable at a given lateral position. The above-described procedure of obtaining spatially resolved stress–strain dependences and the derived stiffness–stress dependences makes it possible to reconstruct spatial distribution of the Young’s modulus for a chosen value of pressure, the same over the entire visualized region. Figure 1h–j corresponding to a standardized pressure of 1 kPa, 5 kPa, and 10 kPa clearly demonstrate that because of intrinsic nonlinearity of the tissue, the apparent distribution of the Young’s modulus may drastically differ for moderate variations in the pressure. These examples qualitatively illustrate the importance of nonlinearity manifestation. The next point was how to quantify the tissue nonlinearity to consider it as a useful informative characteristic rather than a complicating factor in the estimation of the Young’s modulus. The fact of nonlinearity is clearly seen in Figure 1e, where the stress–strain curves pronouncedly deviate from the linear dependences. In Figure 1f,g for the Young’s modulus, the nonlinearity manifests itself in the occurrence of the dependence of the tissue stiffness on strain and, consequently, on current stress. In the theory of elasticity, nonlinear stress–strain dependences are often represented as power-law expansions. In biomechanics, various more complex laws, in particular those containing exponential functions, are often used (for example, Neo-Hookean law or Verdona–Weston constitutive law and others [18,35,36]). However, different types of tissue may require different forms of constitutive law and their corresponding approximating functions. To enable a fairly universal interpretation for various form of nonlinear behavior in our approach, we adopted a local power-law approximation of the stress–strain curves around some chosen pressure value σ0. Thus, retaining only the lowest-order nonlinear correction this dependence takes the form:(1) σ=σ0+E(σ0)⋅(ε+βε2+…) where σ is the stress (pressure), ε is strain, σ0 is the chosen initial stress around which the nonlinear stress–strain dependence is expanded, E(σ0) is the current (tangent) Young’s modulus corresponding to the chosen stress σ0, and β is the dimensionless nonlinear parameter characterizing quadratic-in-strain nonlinearity. Next, the current value of the Young’s modulus by definition corresponds to the slope of the stress–strain dependence, such that at the chosen precompression one can write (2) E(σ0)=dσ/dε|σ=σ0 In other words, at any point σ0, the Young’s modulus is equal to the slope of the stress–strain dependence, examples of which are shown in Figure 1e. As is clear from Equation (1), in the vicinity of point σ0, the current Young’s modulus can be represented as (3) E(σ)=E(σ0)⋅(1+2βε) Next, for the quadratic nonlinearity parameter β near the stress point σ0, it follows from Equations (1)–(3) that (4) β|σ=σ0=12dEE(σ0)dε=12dEdσ|σ=σ0 In other words, Equation (4) indicates that the nonlinearity parameter β|σ=σ0 is equal to 1/2 of the slope of dependence E(σ) at point σ0 (examples of such slopes for the experimentally obtained curves E(σ) are shown in Figure 1g by dashed lines). It can be noted that such expansion can be made around arbitrarily chosen initial stress, in particular zero pressure σ0→0, may also be chosen as the initial point. The steps required for obtaining spatial distributions of the Young’s modulus E(σ0) (stiffness) and nonlinearity parameter β|σ=σ0 in the described variant of C-OCE can be summarized as schematically shown in the flowchart in Figure 2. 2.2. Principle of Segmentation of OCE-Images Using Linear and Nonlinear Elastic Parameters We applied the procedure of automated morphological segmentation of the OCE images using the preliminary determined ranges of both the linear Young’s modulus and nonlinear elastic parameter for different morphological components of the breast tissue. Our previous studies showed that, for a chosen “standardized” stress, various morphological components of tumorous tissues and peritumoral zones often exhibit quite well-separated characteristic stiffness ranges [25,31,37]. These characteristic stiffness ranges can be found by comparing OCE-based stiffness maps and conventional histological images obtained for the same locations. After determining the characteristic stiffness range for a certain morphological component of the tissue, we considered that every morphological component corresponds to those pixels in the OCE image, for which the stiffness falls in the respective characteristic stiffness range. In such a way, the areas corresponding to every component can be automatically segmented and marked by various colors in the OCE-based stiffness map. In study [31], such quite well-separated stiffness ranges were found for four mains constituents of model tumors (namely, regions of viable cancer cells, necrotic cancer cells, benign fibrosis or adipose in peritumoral zones, etc.). The results of segmentation of OCE maps of the Young’s modulus according to those four characteristic stiffness ranges demonstrated a very good agreement with manually performed segmentation of histological images. Similar segmentation of OCE images based only on the characteristic ranges of the Young’s modulus was efficiently applied in [37] to another type of model animal tumors, for which the same four main morphological components were also typical. However, in OCE studies of breast cancer samples of patients such as in [25,38] had some cases where histological examinations indicated the presence of morphologically different zones, for which the characteristic ranges of the Young’s modulus demonstrated a significant overlap. In such situations, however, one may expect that even if these tissue components are fairly similar in terms of their Young’s moduli, the nonlinear parameters for these components may differ, which can be additionally used for the differentiation. There is a general analogy of this idea with nonlinear-acoustic diagnostics of structural damage in mechanical engineering, where cracks and cavities may have similar scattering strength, but cracks may still be clearly differentiated because pronounced nonlinearity-generated sounding-signal components are specific only for cracks [39]. Therefore, in addition to consideration of only Young’s modulus maps, similar maps can be constructed for the nonlinearity parameter that can be determined as described in the previous section. Then the segmentation of the morphological components on OCE maps can be made much more reliably by simultaneously using their differences in both the Young’s modulus and the nonlinearity parameter. In the “Results” section, we will demonstrate the realization of this idea for improved diagnostics of breast-cancer samples. 2.3. Patient Selection and Data Collection The present study on human tissue samples was approved by the Institutional Review Board of the Privolzhsky Research Medical University (Nizhny Novgorod, Russia). All of the patients included in the study provided written informed consent. The research was carried out on 60 specimens of freshly excised breast tissue acquired from 50 patients post breast-conserving surgery with different histopathology diagnosis (see Section 2.4). During resection, tumorous tissue specimens were taken from different parts of the tumor—in the center and peritumoral (nontumoral) area. All specimens were studied within 1–2 h after resection. 2.4. Histopathology and Its Comparison with OCE-Based Segmentation After C-OCE imaging, the scanning area was marked on the specimen with histological ink for easier correlation with histology. Then, the specimens were fixed in 10% formalin for 24 h and were transferred to 70% ethanol and then paraffined for histological study. The paraffined specimen blocks were sliced through the marked area to match the plane of histological sections with the OCT B-scan position. To determine the disease type and collagen content, staining of the histological slides with hematoxylin and eosin (H&E) and Van-Gieson’s was performed. The histological slices were prepared using a Leica RM 2245 Rotary Microtome, described by a morphologist and photographed in transmitted light with a Leica DM2500 DFC (Leica Microsystems, Germany) microscope, equipped with a digital camera. The revealed histological types of breast tissue included adipose tissue with streaks of connective tissue (number of specimens n = 7); fibrous stroma (n = 9); area of invasive ductal carcinoma (IDC), which is characterized by individual tumor cells and dense fibrous stroma with hyalinosis of collagen fibers (n = 10); area of IDC, consisting of separate large clusters or nests of tumor cells distributed in the fibrous stroma (n = 11); agglomerates of tumor cells of IDC, which is characterized by solid growth with a small amount of stroma (n = 11); agglomerates of tumor cells of invasive lobular carcinoma (ILC), which is characterized by solid growth (n = 6); and large foci of hyalinosis (n = 6). The results of the histopathology were compared with the OCE findings. When performing such comparison/matching, one should bear in mind that neighboring OCE B-scan and histological slices may have variations in the visualized morphological tissue structure on a scale of a few tens of microns. Such small-scale features could not be colocated in OCE scans and histology because even for accurate labeling of the scanned zone with histological inks, colocation of OCE scans and histological images could be made with an accuracy of a few hundred microns at best. Furthermore, the applied compression deformed the sample during the OCE examination, and then the shape of the sample was additionally distorted during the procedures of its preparation for the histological examinations (fixation in formalin, dehydration, paraffining, etc.). In view of this, in this study, in order to obtain a good correlation between OCE-scans and histological sections, rather large regions of interest (~hundreds of microns or more) with fairly uniform histological properties were used for comparison and precalibration of the linear and nonlinear elastic parameters. Such larger regions did not exhibit significant variations from one histological slice to another, so that precalibration of the characteristic ranges of the Young’s modulus and the nonlinearity parameter was possible. Then the regions corresponding to the found characteristic ranges of the two parameters were easily automatically singled out on the initial continuous maps of the Young’s and nonlinear parameter. Therefore, for samples with more a complex structure, the correspondence of OCE-segmentation and histology mainly concerns similar zones’ topology and only an approximate similarity of geometrical forms, especially for smaller details in the images. 3. Results Ex vivo OCE imaging of excised breast cancer samples was performed using a motorized stage enabling the positioning of the OCT probe in the lateral plane and along the vertical axis to apply compression to the samples. The technique based on the application of reference silicone layers described in Section 2.1 made it possible to obtain stress–strain, stiffness–strain, and stiffness–stress curves for every type of the studied tissues, as shown in Figure 3. It was shown that there is a significant difference in the stiffness and the rate of increase in stiffness depending on strain (and stress) among nontumorous and various types of tumorous breast tissues. The latter were characterized by significantly differing rates of malignancy and the conventional way of differentiation of these cancer subtypes is based on laborious and time-consuming histological examination. In view of this, revealing clear differences using OCT-based examinations of freshly-excised samples has a high interest. Figure 3d–f show the results for six types of breast tissues demonstrating significantly different types of corresponding stress–strain dependences. It is clear that only nontumorous adipose (row 1 in Figure 3) exhibits very pronouncedly reduced Young’s modulus and weak nonlinearity of the stress–strain dependence. The four tissue types demonstrate much higher stiffness and higher nonlinearity (of which three types in rows 2, 4, 5 in Figure 3 are malignant lesions and hyalinosis shown in row 6). The elastic properties of fibrosis (row 1 in Figure 3) are intermediate between these two strongly differing types. The characteristic forms of stress–strains curves and the derived stiffness–strain and stiffness–stress curves are shown in column 4 of Figure 3 by different colors. It was observed that fairly large agglomerates of tumor cells (see images in the 3rd and 5th rows and red and pink curves in the Figure 3d–f), as well as large foci of hyalinosis (images in the 6th row in Figure 3 and black curves in the Figure 3d–f) are characterized by pronouncedly increased nonlinearity and stiffness in comparison with adipose (blue lines in Figure 3d–f). The light blue lines in Figure 3d–f) for the fibrous tissue clearly demonstrate the abovementioned intermediate behavior. Invasive ductal and lobular cancer is more than 20 times as stiff as normal adipose tissue at 0.1% strain and more than 200 times as stiff at 2% strain. Compared to normal fibrous tissue, those types of cancer are more than 10 times as stiff at 0.1% strain and nearly 100 times as stiff at 2% strain. Therefore, relative stiffness is a fairly good parameter for differentiating such tissue types, although not always. Indeed, the stiffness–strain and stiffness–stress curves in Figure 3e,f demonstrate that either at the lowest pressures or some intermediate pressure levels the Young’s modulus may coincide for different cancer types. Next, the targeted comparison of OCE images and histological ones shown in rows 4 and 5 in Figure 3 revealed regions in which small islands of cancer cells were embedded in fibrous stroma and dense fibrous stroma with hyalinosis and collagen fiber. These structures correspond to tumors with scirrhous and solid-scirrhous structure types. It was found that such regions are characterized by an intermediate nonlinearity and stiffness (green and orange lines in the Figure 3d–f) between regions with large agglomerates of cancer cells (“solid tumors”) and hyalinosis on the one hand and fibrous stroma and adipose on the other hand. It should be mentioned that scirrhous tumors with inclusions of individual cancer cells into fibrous stroma at the lower pressures may exhibit fairly low stiffness similar to that of nontumorous fibrous tissue, so that based on the similarity of stiffness values these two tissue types can be easily confused. However, despite the initially similar stiffness at low pressures, the dependence of the Young’s modulus on pressure is noticeably different for these tissue types, which can help to distinguish fibrosis from the tissue containing only sparsely distributed cancer cells visible in the histological images (Figure 3(b4,b5)). This is important for precise diagnostics of such scirrhous tumors, as well as for searching out a clear resection margin during organ-conserving surgical excision of breast cancer. In addition, the described method of OCE examination made it possible to clearly single out regions of stroma with pronounced hyalinosis (the presence of thick bundles of collagenous fibers corresponding to the histological images in row 6 of Figure 3). Occurrence of hyalinosis in stroma indicates the development of deep secondary degenerative alterations in the tissue, which is important for diagnosing the disease and its stage, as well as for planning the therapy. Our study revealed that hyalinosis is characterized by high stiffness values (similar to those for solid agglomerates of cancer cells), but the nonlinearity of hyalinosis is much higher (black line in Figure 3f). This extremely high nonlinearity can be attributed to rather high packing density of the collagen fibers resembling the hyaline cartilage, such that under very small strains (~0.1%) the residual gaps become closed and the stiffness of such hyalinosis zones drastically increases approaching the stiffness of cartilage. Therefore, the performed OCE-based study revealed that there is a significant difference both in the stiffness and in the rate of stiffness increase with strain among the examined tumorous and nontumorous breast tissues. In another form, the difference in the diagnostic information given by the Young’s modulus and the nonlinearity parameter is demonstrated in Figure 4 for benign and malignant breast lesions: benign fibrosis, solid-type malignant tumor, and scirrhous cancer, for which the histological images are shown in row 3. Rows 1 and 2 in Figure 4 show the color-coded spatial distributions of the Young’s modulus and the grey-level coded dimensionless nonlinearity parameters, respectively. These elastic parameters were calculated according to Equations (2) and (4) for the low applied pressures (about 0.5 ± 0.5 kPa). Figure 4 shows that for the solid-type tumor, both the Young’s modulus and the nonlinearity parameter are strongly elevated, whereas for fibrosis and the scirrhous tumor, the Young’s modulus demonstrates very similar fairly low values. However, Figure 4 also clearly shows that for the scirrhous tumor, the nonlinearity parameter (albeit smaller than for the solid tumor) is pronouncedly higher than for fibrosis. These examples clearly illustrate the statement that the estimation of the linear elastic modulus (i.e., its value conventionally estimated at fairly low pressures typical of conventional ultrasound elastography) may be insufficient for discrimination between malignant and benign breast lesions; whereas due to the additional estimation of the nonlinearity parameter, accurate discrimination becomes possible. Furthermore, the total set of results for OCE examination of 60 samples corresponding to seven different tissue types revealed in the histological images is represented in Figure 5 in the 2D form on the (E,β) plane, where the horizontal axis is for the nonlinearity parameter β and the vertical one is for the Young’s modulus E. Both quantities were estimated at lower pressures (about 0.5 ± 0.5 kPa), which was controlled using the reference silicone. The color correspondence to the tissue types is indicated in the legend. Figure 5 shows that on the 2D plane all these seven groups can be fairly well-separated (the dashed lines in Figure 5 show the corresponding boundaries of the characteristic ranges of parameters E and β). In contrast, in terms of E and β taken separately, there is a significant overlap in these parameters for several tissue types (the semitransparent ellipses in Figure 5 show some of such data with overlapping values of E or β). To more clearly show the abovementioned trend of the nonlinearity increase for tumors with increasing malignancy up to the maximal values typical of hyalinosis and nonmonotonic behavior of the Young’s modulus in Figure 6, the estimated values of E and β are shown separately for the same tissue types as in Figure 5. The empty white circles in each of the data clouds show the mean values and the vertical bars correspond to show the total scattering of the data within each cloud. It is clear that when only Young’s modulus or only nonlinearity parameter is considered, there may be a significant overlap in their values for the considered tissue subtypes. Nevertheless, on the two-dimensional (E,β) plane these tissue subtypes can be fairly well-separated in terms of the specific ranges of E and β indicated in the legend in Figure 5. When considering the data presented in Figure 5, it should be emphasized that both quantities E and β shown in the figure are estimated for lower pressures (in our case about 0.5 ± 0.5 kPa) and the statements about the monotonic ordering of the estimated nonlinearity parameters and nonmonotonic ordering for the Young’s modulus are made for these low-pressure results. It is clear from Figure 3 that for larger pressures, the nonlinear stress–strain curves may cross each other, for example, the red and magenta color stiffness–pressure curves shown in Figure 3f for IDC and ILC, respectively. This crossing means that one tissue type can be stiffer than the other at lower pressure, but the situation may change to the opposite at a higher pressure and vice versa. For this reason, we emphasize once again that for correct interpretation of relative stiffness values, as well as characteristic absolute values, it is critically important to enable local pressure control when the stiffness is estimated. The next step after determining the characteristic ranges of the Young’s modulus and the nonlinear elastic parameter based on a targeted comparison of OCE data and histological images is the application of the found characteristic values for automated morphological segmentation of the OCE images. The utilization of two parameters (Young’s modulus and nonlinearity parameter) for such segmentation is a further development of the automated morphological segmentation of OCE images that was first proposed in [25,31,37] using only the differences in the characteristic ranges of the Young’s modulus for various tissue subtypes. The combined utilization of both Young’s modulus and the nonlinearity parameter opens the possibility to distinguish the tissue types even if their characteristic stiffness significantly overlaps (as was demonstrated by comparing the 1st and 3rd columns in Figure 4). The additional information provided by the nonlinearity parameters opens the way for a more precise assessment of the breast cancer morphology. We demonstrated that it becomes possible not only to reliably delineate peritumoral adipose tissue, but also to automatically differentiate such important tissue subtypes as fibrous stroma and fibrous stroma with individual cancer cells, malignant areas of IDC and ILC, as well as zones of hyalinosis. This is made without any special preparation of freshly excised breast-tissue tissue samples. Such an example is given in Figure 7, which shows the histological image (Figure 7a), the structural OCT image (Figure 7b), the OCE-based stiffness map obtained at two different pressures of 0.5 ± 0.5 kPa and 4.0 ± 0.5 kPa (Figure 7c,d), and finally, the morphological segmentation map (Figure 7e). The latter was constructed using the characteristic ranges of both the Young’s modulus and the nonlinear elastic parameter. These characteristic ranges were obtained by targeted comparison of the histological images and OCE data using over 60 samples that were summarized in Figure 5. The OCE and histological images in Figure 7 were obtained by stitching several sequentially scanned sections, in which the boundary between normal (peritumoral) tissue (left part of the images) and an invasive tumor (nonluminal subtype) is clearly seen. In the conventional structural OCT images in Figure 7b, there are no clear differences between tumorous and nontumorous zones. In the OCE-based stiffness map plotted for the lowest pressures of 0.5 ± 0.5 kPa (Figure 7c), the central tumor zone becomes visible as a stiffer region, but there is still no clearly seen transition between the tumor and peritumoral zone. The stiffness map in Figure 7d is obtained at a higher precompression (4.0 ± 0.5 kPa) and clearly demonstrates the effect on nonlinearity-induced stiffening due to which the tumor zone grows significantly stiffer. Thus, in Figure 7d, one can see a much clearer contrast between the tumor in the central part and the peritumoral adipose and stroma because the nonlinearity of the latter is much lower and causes only insignificant stiffening. Unlike Figure 7c,d, in which the quantification of nonlinearity was not yet used, the next Figure 7e shows the results of morphological segmentation of the OCE-image based on the quantitative differences in both Young’s modulus and the nonlinearity parameter (these differences for seven tissue subtypes were shown in Figure 5). In Figure 7e, the OCE-based segmentation demonstrates much clearer correspondence with the histological slide for the structure of the transition between the tumor and peritumoral zone. Now, in addition to the large agglomerates of cancer cells with differentiation of IDC and ILC (red and magenta colors, respectively) in the central tumor zone in Figure 7e and soft adipose (dark-blue) at the periphery, even finer differentiation becomes possible. Namely, inclusions of hyalinosis (black color) in the central part of the tumor and in the transition to the peritumoral zone, finer tissue subtypes are segmented: fibrosis without cancer cells (light-blue), fibrosis with scattered individual cancer cells (green), and fibrosis with embedded small clusters of cancer cells (orange). Such a visualization with a high-sensitivity detection of even sparse amounts of cancer cells is very important for controlling a clean resection boundary and becomes possible due to the combined utilization of both the nonlinearity parameter and Young’s modulus of the tissue. However, for compared C-OCE-based images and histological images, the uncertainty of matching evidently may be significantly greater than the distance between neighboring histological slices (see Section 2.4). This important remark should be taken into account when comparing OCE and histological images: only larger (~hundreds of microns and greater) regions/components can be reasonably matched and compared on this scale, whereas smaller features (~tens of microns) may look significantly more distorted/displaced than for neighboring histological slices. Therefore, the correspondence mainly concerns similar topology and only approximate similarity of geometrical forms, especially for smaller details in the images. Thus, the rectangles in Figure 7a show only representative regions for various tissue subtypes and the color of these rectangles corresponds to the palette used in Figure 7e to denote the segmented tissue constituents of the seven types. The similarity in topology and geometry of the corresponding zones in the histological slice is quite clear. The automated OCE surprisingly revealed the same seven morphological components as the manual segmentation of histological images performed by an experienced histopathologist. 4. Discussion The majority of elastography-related studies (both in OCT and ultrasound) till now were focused on linear elastic properties (Young’s modulus) [6,8,23,25], so that interpretation of elastographic data was conventionally performed within the paradigm of the linear elasticity theory both in ultrasonic techniques widely used in clinic and in emerging OCT-based elastographic methods. However, there is an increasing number of demonstrations based on various techniques (mechanical indentation, ultrasound, OCE) which clearly indicate the pronounced nonlinearity of biological tissues (e.g., [13,15,17,18]). This nonlinearity can confound interpretation of elastographic images in both ultrasound elastography and OCE [40]. Thus, for meaningful interpretation and comparison of estimated stiffness values (for both various scan regions in one measurement and, furthermore, different measurements), one requires knowledge of pressure (stress), from which these estimates are obtained. We emphasize that even within a single scan it is necessary to know local values of the applied pressure for various lateral coordinates rather than merely an averaged stress over the entire scan, measurements of which are conventionally made by applying controllable force to the compressing probe. Thus, a key feature of the OCE method used here is that for estimating the tissue stiffness, the reference silicone layer acts as a spatially-resolved sensor, enabling knowledge of the local stress. Due to this, we were able to estimate the tissue stiffness for the same prechosen standardized range of the applied pressure, even if the instantaneous pressure distribution could unpredictably vary within a single scan (see details in [17]). It can be also noted that in our quasistatic compression OCE and compression ul-trasound elastography, the tissue is deformed fairly slowly (corresponding to frequencies of ~several Hz in the spectral domain). A similar rate of compressive strains is used in stiffness estimations based on the utilization of loading mechanical devices, the results of which often being accepted as ground truth when validating various elastographic techniques. In this context, a recent paper [41] demonstrated a good agreement between the results of wave-based OCE using waves in ~kHz frequency range and mechanical measurements that are quasistatic in the same sense as the compression OCE technique discussed here. Furthermore, in several previous works related to compression OCE, we demonstrated that the realization of pressure standardization in different experiments and within the visualized region in each experiment can eliminate the nonlinearity-related ambiguity in the interpretation of the estimated Young’s modulus [17,25,31,37]. In the present study, we took the next step and demonstrated that, alongside the Young’s modulus estimation under standardized loading conditions, quantification of the local nonlinear response of breast tissue can additionally provide valuable diagnostic information and enable unprecedented selectivity in elastographic differentiation of tissue subtypes. First, quantification of the nonlinear elastic parameter in combination with the Young’s modulus improves the reliability of discrimination between benign and malignant breast tissues. The point is that benign and malignant tissues may have significantly overlapping ranges of the Young’s modulus. For example, it is demonstrated in Figure 6 that strongly overlapping ranges of the Young’s modulus are typical for yet benign fibrosis (light blue dots in Figure 6), as well as for malignant areas of IDC, consisting of separate, fairly large clusters or nests of tumor cells distributed in the fibrous stroma, i.e., tumor with solid-scirrhous structure (orange dots in Figure 6). However, these tissue types demonstrate pronouncedly differing nonlinearity parameters and thus can be quite distinctly separated on the two-dimensional (E,β) plane as shown in Figure 5. Second, the estimates of stiffness combined with the quantification of the nonlinear elastic parameter enabled the possibility to distinguish even zones with sparsely scattered tumor cells scattered in the fibrous tissue (green dots in Figure 5 and Figure 6). We emphasize that such zones do not demonstrate clearly different stiffness from hyalinosis (black dots in Figure 5 and Figure 6) and from two other types of tumorous tissue (red and magenta dots in Figure 5 and Figure 6). To the best of our knowledge, previous detection of such tissue subtypes with sparsely distributed cancer cells was possible only using high-resolution histological images in which individual tumor cells are visible. However, the resolution of OCE is lower and OCE images do not literally resolve individual tumor cells. Nevertheless, OCE reveals that the presence of such subresolution individual cancer cells causes changes in the linear and nonlinear elastic properties of the tissue on larger scales of tens and hundreds of micrometers. In materials science, a very similar situation is known in nonlinear vibro-acoustic detection of microcracks in solids (e.g., metals or rocks). Such individual microcracks are not resolved, but the crack-induced changes in the material’s elastic nonlinearity can be easily observed, for example, via nonlinear vibro-acoustic modulation effects [39]. Returning to Figure 5 and Figure 6 and the example of OCE-segmentation in Figure 7, it is interesting to point out the possibility to clearly highlight areas of the hyalinized tumor stroma. This is possible due to the extremely high nonlinearity of hyalinosis, although its Young’s modulus strongly overlaps with that typical of zones containing large agglomerates of cancer cells. Another condition that is of key importance for the correct interpretation of OCE results is that, for fairly soft biological tissues, quantitative estimations of both the tangent Young’s modulus E and the quadratic nonlinearity parameter β should be performed for a chosen (“standardized”) pressure. For unambiguous and reliable interpretation, this pressure should be the same not only for various compared OCE images from different experiments, but also should be maintained the same within the visualized region in every particular experiment. To ensure this requirement, conventional methods based on force sensors that enable only spatially averaged estimates of pressure are not sufficient. The reason is that, physically, the stress is not uniform even within a single OCT scan because of the influence of uncontrollable fine geometrical factors and intrinsic mechanical inhomogeneity of the tissue. For this reason, one has to acquire a series of OCT scans of the deformed tissue and then choose scans with different numbers, for which the desired stress level is attained in every region of interest of the entire visualized region. In the above-described study, this requirement was satisfied using local control of stress by measuring local strains in reference silicone layers that act as a distributed optical pressure sensor. We restate that the results presented above were obtained for fairly low pressure 0.5 ± 0.5 kPa, although other “standardized” pressure values can also be used, for example, pressure ~4 kPa was used in [31,37] and was quite appropriate for performing OCE-based segmentation of model tumors in animal experiments using only Young’s modulus. Evidently, for different tissue types, different pressure levels may be more or less efficient for obtaining better accuracy of segmentation. In this direction, further studies are required. The results of determining the characteristic ranges of the Young’s modulus and the nonlinearity parameter in the present OCE study indicated that the relationship of the tissue malignancy and its low-pressure stiffness is neither straightforward, nor monotonic. This is clearly seen from Figure 6b showing the Young’s modulus for various tissue types including several tumors with various malignancy grades. The magnitude of the nonlinearity parameter β in Figure 6a appears more regularly varying, but may also demonstrate noticeable overlap, so that clearer separation requires simultaneous utilization of stiffness and nonlinearity as is clear from the two-dimensional Figure 5, in which fibrosis and IDC tumors with individual cancer cells or with larger clusters of cancer cells can be rather clearly delineated on the (E,β) plane, but may noticeably overlap along each of the two axes. Concerning the prognosis of the diagnostic accuracy of such OCE-based differentiation, it should be said that the considered set of 60 samples is still insufficiently large for a reliable conclusion. However, for the discussed set of 60 samples, the OCE-based differentiation of all seven types of tissues shown in Figure 5 and Figure 6 gave 100% correct results. Surely, the additional information about the tissue nonlinearity should further improve the accuracy of OCE-based diagnostics, although obtaining accurate statistically significant conclusions for discrimination of seven tissue types at once may require significant additional time for the accumulation of sufficient numbers of samples of each type and their detailed comparative OCE-based and histological examinations and analysis. In the present, actually pilot-type, study, our main goal was to demonstrate that the combined usage of linear and nonlinear elastic parameters of tissues enables unprecedented selectivity of breast tissue differentiation due to which it becomes possible to clearly discriminate seven subtypes of breast tissues. Conventional OCT imaging and even OCE based on the Young’s modulus only were not able perform such fine differentiation. Overall, it can be already stated that morphological segmentation of OCE images accounting for both linear and nonlinear elastic parameters showed very good similarity in topology and geometry with the corresponding zones in the histological slices. Therefore, combined utilization of linear and nonlinear elastic parameters has confirmed the expectation of many authors that nonlinear elastic behavior is a very important characteristic of breast tissues that can provide useful information having a critical importance for a reliable clinical outcome. In the general context of the development of elastographic techniques, in the recent review [42] presenting the development of elastography during the last three decades, there was a statement that, of high interest for elastography, is the “possibility that nonlinear parameters for normal tissues may differ from pathological cases, including cancers”. It was argued that differences in the structure and composition between tissues create a range of nonlinear parameters that can be used as a diagnostic tool [13,43,44,45]. In ultrasound elastography, the prospects of estimating nonlinear parameters attracted considerable attention in recent years [22,46,47,48,49,50,51,52,53,54,55,56,57,58]. Among promising directions of elastography development for the next decade, the abovementioned review [42] pointed out that “creating imaging strategies for estimating nonlinear parameters in a user-independent, accurate, ergonomic, and high resolution platform remains an important goal with many promising clinical applications”. In this regard, the OCE-approach proposed in a series of works [15,16,17] has already enabled an efficient and practically operable method for obtaining nonlinear stress–strain with a high spatial resolution. The above-presented results of OCE-based high-selectivity differentiation and automated segmentation of tumor tissue subtypes demonstrate that the combined usage of linear and nonlinear elastic parameters confers to OCE unprecedented diagnostic possibilities comparable to results of histological segmentation. However, in contrast to invasive, laborious, and time-consuming histology, the OCE examinations can be made in minutes, do not require special preparation of freshly excised samples or can even be feasible in vivo, at least in animal experiments with model tumors (like in [31]). The next remark relates to compression elastographic techniques in general, including OCE. From the general viewpoint of materials science, most biological tissues relate to the class of poroelastic materials. They are strongly saturated with water with typical mass content ~70–90%, but mostly this water is in a bounded state with some free water localized in macroscopic gaps and channels. The closing of these pores/gaps under compression leads to an increase in the Young’s modulus (i.e., nonlinearity of stress–strain curves). By combining OCE-based strain and elasticity assessment, it becomes possible to extract information about microstructural changes in biological materials (e.g., corneal tissue and cartilage as demonstrated in [59,60]), using analogies from the characterization of crack-containing rocks. The squeezing of water from the gaps/pores, generally speaking, is a relaxation process with a broad spectrum of relaxation times. However, both the OCE method and compression USE utilize quasistatic compression (with characteristic frequencies ~ several Hz). Direct tests in OCE and longtime successful usage of USE demonstrate that for such compression rates, the observed strains are fairly well reproducible and lead to reproducible diagnostic conclusions. However, for higher characteristic frequencies (for oscillations in the range of hundreds Hz and kHz range), there are known special studies focused on estimation of relaxation times that can also be used for diagnostic applications [61]. Finally, it can be mentioned that the robust approach to OCT visualization of local strains based on the vector method proposed in [11,12] used here, in addition to the assessment of tissue elasticity in compression OCE, also opened a broad range of possibilities for studying various kinds of deformation processes in biological tissues, e.g., fairly slowly varying strains caused by drying [62], internal stresses [63], heating (e.g., by laser irradiation) [64], and osmotic effects [65]. 5. Conclusions In this study, we proposed a method for the quantification of the Young’s modulus of the tissue and its nonlinear parameters. The performed study showed that different morphological components of breast cancer tissue (i.e., fibrosis without cancer cells, fibrosis with small amount of cancer cells, zones with large agglomerates of cancer cells typical of IDC and ILC cancers, as well as zones of hyalinosis) demonstrate distinctly different combinations of the Young’s modulus and nonlinear elastic parameter. Their combined usage enables clear differentiation of these tissue subtypes; whereas taken separately, the Young’s modulus and the nonlinearity parameter are not sufficient to reliably distinguish them. The obtained results indicate a high potential of the presented OCE technique for accurate intraoperatively feasible diagnosis of tumors and precise detection of a clean (“negative”) boundary for breast cancer resection during organ-conserving surgical operations. Certainly, in a more general sense, the developed technique can be used for a broad range of soft materials, first of all in further investigations of fundamental aspects of biomechanics including both linear and nonlinear elastic properties of various types of nontumoral and tumoral tissues. Author Contributions Conceptualization, E.V.G., N.D.G. and V.Y.Z.; methodology, E.V.G., A.A.S., V.Y.Z. and A.L.M.; software, A.A.S., A.L.M. and L.A.M.; validation, S.S.K., D.A.V. and A.Y.V.; investigation, E.V.G. and A.A.S.; writing, E.V.G. and V.Y.Z.; visualization, A.A.S., A.A.P. and E.V.G.; supervision, S.V.G., M.A.S., N.D.G. and V.Y.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Institutional Review Board of Privolzhsky Research Medical University (protocol No 10; 28 September 2018). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to proprietary rules. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Procedures of evaluating linear and nonlinear elastic properties based on C-OCE with reference layers of highly linear silicone. (a) schematically shown tissue sample compressed by the OCT probe through the intermediate layer of reference silicone; (b) an example of a typical structural image obtained in such measurements; (c) an example of the derived color-coded interframe phase variation; (d) spatial distribution of strain obtained by estimating axial gradients of the interframe phase variation; (e) dashed lines show nonlinear stress–strain curves for positions corresponding to labels “1” and “2” in panel (d), the approximating functions are shown by the solid curves; (f) dependences of the tangent Young’s modulus (stiffness) on strain found by differentiation of the fitting curves from panel (e); (g) stiffness–strain dependences from panel (f) recalculated in stiffness–stress dependences, for which the slopes (see the dashed straight lines coming from the low-stress points ~0.5 kPa) correspond to the dimensionless nonlinearity parameter defined by Equation (4); panels (h–j) show how the reconstructed stiffness distribution evolved with increasing pressure for 1 kPa, 5 kPa, and 10 kPa, respectively. Figure 2 Schematic of the main steps of signal processing to estimate stiffness and the nonlinearity parameter in the developed C-OCE. Figure 3 Illustration of different nonlinear elastic behaviors for seven different types of benign and malignant breast tissues, for which the representative zones are marked by different colored rectangles on histological and OCE images. Column (a1–a6) shows C-OCE images obtained for a standardized pressure of 4 kPa. Columns (b1–b6, c1–c6) show histological H&E-stained and Van-Gieson-stained images, respectively. Typical stress–strain curves for the seven tissue zones marked by different colored rectangles are shown the same color curves in panel (d). (e) shows the corresponding derived stiffness–strain curves and (f) is for the stiffness–stress curves. Notice that malignant tissues (red, pink, orange, and green lines) tend to exhibit larger nonlinearity than benign tissues (blue and light-blue lines). Blue lines—adipose tissue with layers of connective tissue; light blue lines—fibrous stroma; red lines –agglomerates of tumor cells of IDC; orange lines—area of IDC, consisting of separate large clusters or nests of tumor cells distributed in the fibrous stroma; green lines—area of IDC, which is characterized by scattered individual tumor cells and dense fibrous stroma with hyalinosis of collagen fibers; pink lines—agglomerates of tumor cells of ILC, which is characterized by solid growth; black lines—large foci of hyalinosis. (Abbreviations: IDC—invasive ductal carcinoma; ILC—invasive lobular carcinoma). Figure 4 OCE-based visualization of the Young’s modulus E0 (row (a)) and the nonlinearity parameter β (row (b)) obtained for low pressure 0.5 ± 0.5 kPa applied to the tissues, for which the corresponding histological images are shown in row (c). (a1–c1) is a benign fibroadenoma, (a2–c2) is a malignant tumor of solid type and (a3–c3) is a malignant tumor of scirrhous type. Notice that benign fibrosis and scirrhous tumor exhibit very similar stiffness (compare panels (a1,a3)), but distinctly different nonlinearity parameters (panels (b1,b3)). Figure 5 Two-dimensional plane (E,β) of the Young’s modulus and nonlinearity parameter for the same seven histologically different tissue types as in Figure 3 obtained using 60 samples taken from 50 patients. Notice that malignant tissues (green, orange, red, and magenta points) tend to exhibit stronger nonlinearity than benign tissues (blue and light-blue points); the strongest nonlinearity is typical of hyalinosis. Although the Young’s modulus of adipose is clearly the lowest, for the other tissue types, the dependence of the Young’s modulus on the malignancy degree is not that clear and strong overlap of stiffness ranges may occur. (Abbreviations: IDC—invasive ductal carcinoma; ILC—invasive lobular carcinoma). Figure 6 Nonlinear parameter β (a) and Young’s modulus E0 (b) for different types of breast tissues: blue dots—nontumor breast tissue (adipose tissue with layers of connective tissue); light-blue dots—benign fibroadenomatosis or fibroadenoma; green dots—area of IDC, which is characterized by individual tumor cells and dense fibrous stroma with hyalinosis of collagen fibers (scirrhous structure); orange dots—area of IDC, consisting of separate large clusters or nests of tumor cells distributed in the fibrous stroma (solid-scirrhous structure); red dots—area of IDC which is characterized by solid growth with a small amount of stroma; magenta dots—area of ILC, which is characterized by solid growth; black dots—large foci of hyalinosis. The inset in (a) shows the data for the first four tissue types in more detail. (Abbreviations: IDC—invasive ductal carcinoma; ILC—invasive lobular carcinoma). Figure 7 Visualization of a transitional zone between peritumoral (nontumoral) breast tissue and tumor region using structural OCT and C-OCE-based images with morphological segmentation of the OCE image. The segmentation is based on the combined usage of the Young’s modulus (E) and the nonlinearity parameter (β), for which the characteristic ranges are shown of (E,β) plane in Figure 5. (a) is the H&E-stained histological image; (b) is the structural OCT image which is obtained by stitching several scanned sections; (c) is the stiffness map obtained at a minimum pressure of 0.5 ± 0.5 kPa; (d) is the stiffness map obtained at a pressure of 4.0 ± 0.5 kPa demonstrating strong pressure-induced change in tumor stiffness; (e) is the automated morphological segmentation of the OCE image into zones of various tissue components. The corresponding regions in the histological image (a) are marked by rectangles of the same color as the segmented zones in panel (e). (Abbreviations: IDC—invasive ductal carcinoma; ILC—invasive lobular carcinoma). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kennedy K.M. Chin L. McLaughlin R.A. Latham B. Saunders C.M. Sampson D.D. Kennedy B.F. Quantitative Micro-Elastography: Imaging of Tissue Elasticity Using Compression Optical Coherence Elastography Sci. Rep. 2015 5 15538 10.1038/srep15538 26503225 2. Zaitsev V.Y. Matveyev A.L. Matveev L.A. Sovetsky A.A. Hepburn M.S. Mowla A. Kennedy B.F. Strain and Elasticity Imaging in Compression Optical Coherence Elastography: The Two-decade Perspective and Recent Advances J. Biophotonics 2021 14 e202000257 10.1002/jbio.202000257 32749033 3. Ophir J. Céspedes I. Ponnekanti H. Yazdi Y. Li X. Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues Ultrason. Imaging 1991 13 111 134 10.1177/016173469101300201 1858217 4. Itoh A. Ueno E. Tohno E. Kamma H. Takahashi H. Shiina T. Yamakawa M. Matsumura T. Breast Disease: Clinical Application of US Elastography for Diagnosis Radiology 2006 239 341 350 10.1148/radiol.2391041676 16484352 5. Faruk T. Islam M.K. Arefin S. Haq M.Z. The Journey of Elastography: Background, Current Status, and Future Possibilities in Breast Cancer Diagnosis Clin. Breast Cancer 2015 15 313 324 10.1016/j.clbc.2015.01.002 25858446 6. Seo M. Ahn H.S. Park S.H. Lee J.B. Choi B.I. Sohn Y.-M. Shin S.Y. Comparison and Combination of Strain and Shear Wave Elastography of Breast Masses for Differentiation of Benign and Malignant Lesions by Quantitative Assessment: Preliminary Study: Strain and Shear Wave Elastography of Breast Masses J. Ultrasound. Med. 2018 37 99 109 10.1002/jum.14309 28688156 7. Schmitt J.M. OCT Elastography: Imaging Microscopic Deformation and Strain of Tissue Opt. Express 1998 3 199 10.1364/OE.3.000199 19384362 8. Wang R.K. Ma Z. Kirkpatrick S.J. Tissue Doppler Optical Coherence Elastography for Real Time Strain Rate and Strain Mapping of Soft Tissue Appl. Phys. Lett. 2006 89 144103 10.1063/1.2357854 9. Wang R.K. Kirkpatrick S. Hinds M. Phase-Sensitive Optical Coherence Elastography for Mapping Tissue Microstrains in Real Time Appl. Phys. Lett. 2007 90 164105 10.1063/1.2724920 10. Kennedy B.F. Koh S.H. McLaughlin R.A. Kennedy K.M. Munro P.R.T. Sampson D.D. Strain Estimation in Phase-Sensitive Optical Coherence Elastography Biomed. Opt. Express 2012 3 1865 10.1364/BOE.3.001865 22876350 11. Zaitsev V.Y. Matveyev A.L. Matveev L.A. Gelikonov G.V. Sovetsky A.A. Vitkin A. Optimized Phase Gradient Measurements and Phase-Amplitude Interplay in Optical Coherence Elastography J. Biomed. Opt. 2016 21 116005 10.1117/1.JBO.21.11.116005 27824215 12. Matveyev A.L. Matveev L.A. Sovetsky A.A. Gelikonov G.V. Moiseev A.A. Zaitsev V.Y. Vector Method for Strain Estimation in Phase-Sensitive Optical Coherence Elastography Laser Phys. Lett. 2018 15 065603 10.1088/1612-202X/aab5e9 13. Li J. Pijewska E. Fang Q. Szkulmowski M. Kennedy B.F. Analysis of Strain Estimation Methods in Phase-Sensitive Compression Optical Coherence Elastography Biomed. Opt. Express 2022 13 2224 10.1364/BOE.447340 35519281 14. Krouskop T.A. Wheeler T.M. Kallel F. Garra B.S. Hall T. Elastic Moduli of Breast and Prostate Tissues under Compression Ultrason. Imaging 1998 20 260 274 10.1177/016173469802000403 10197347 15. Zaitsev V.Y. Matveyev A.L. Matveev L.A. Gubarkova E.V. Sovetsky A.A. Sirotkina M.A. Gelikonov G.V. Zagaynova E.V. Gladkova N.D. Vitkin A. Practical Obstacles and Their Mitigation Strategies in Compressional Optical Coherence Elastography of Biological Tissues J. Innov. Opt. Health Sci. 2017 10 1742006 10.1142/S1793545817420068 16. Sovetsky A.A. Matveyev A.L. Matveev L.A. Shabanov D.V. Zaitsev V.Y. Manually-Operated Compressional Optical Coherence Elastography with Effective Aperiodic Averaging: Demonstrations for Corneal and Cartilaginous Tissues Laser Phys. Lett. 2018 15 085602 10.1088/1612-202X/aac879 17. Sovetsky A.A. Matveyev A.L. Matveev L.A. Gubarkova E.V. Plekhanov A.A. Sirotkina M.A. Gladkova N.D. Zaitsev V.Y. Full-Optical Method of Local Stress Standardization to Exclude Nonlinearity-Related Ambiguity of Elasticity Estimation in Compressional Optical Coherence Elastography Laser Phys. Lett. 2020 17 065601 10.1088/1612-202X/ab8794 18. Qiu Y. Zaki F.R. Chandra N. Chester S.A. Liu X. Nonlinear Characterization of Elasticity Using Quantitative Optical Coherence Elastography Biomed. Opt. Express 2016 7 4702 10.1364/BOE.7.004702 27896009 19. Oberai A.A. Gokhale N.H. Goenezen S. Barbone P.E. Hall T.J. Sommer A.M. Jiang J. Linear and Nonlinear Elasticity Imaging of Soft Tissue in Vivo: Demonstration of Feasibility Phys. Med. Biol. 2009 54 1191 1207 10.1088/0031-9155/54/5/006 19182325 20. Latorre-Ossa H. Gennisson J. De Brosses E. Tanter M. Quantitative Imaging of Nonlinear Shear Modulus by Combining Static Elastography and Shear Wave Elastography IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 2012 59 833 839 10.1109/TUFFC.2012.2262 21. Sayed A. Layne G. Abraham J. Mukdadi O. Nonlinear Characterization of Breast Cancer Using Multi-Compression 3D Ultrasound Elastography in Vivo Ultrasonics 2013 53 979 991 10.1016/j.ultras.2013.01.005 23402843 22. Goenezen S. Dord J.-F. Sink Z. Barbone P.E. Jiang J. Hall T.J. Oberai A.A. Linear and Nonlinear Elastic Modulus Imaging: An Application to Breast Cancer Diagnosis IEEE Trans. Med. Imaging 2012 31 1628 1637 10.1109/TMI.2012.2201497 22665504 23. Allen W.M. Kennedy K.M. Fang Q. Chin L. Curatolo A. Watts L. Zilkens R. Chin S.L. Dessauvagie B.F. Latham B. Wide-Field Quantitative Micro-Elastography of Human Breast Tissue Biomed. Opt. Express 2018 9 1082 10.1364/BOE.9.001082 29541505 24. Chin L. Latham B. Saunders C.M. Sampson D.D. Kennedy B.F. Simplifying the Assessment of Human Breast Cancer by Mapping a Micro-scale Heterogeneity Index in Optical Coherence Elastography J. Biophotonics 2017 10 690 700 10.1002/jbio.201600092 27618159 25. Gubarkova E.V. Sovetsky A.A. Zaitsev V.Y. Matveyev A.L. Vorontsov D.A. Sirotkina M.A. Matveev L.A. Plekhanov A.A. Pavlova N.P. Kuznetsov S.S. OCT-Elastography-Based Optical Biopsy for Breast Cancer Delineation and Express Assessment of Morphological/Molecular Subtypes Biomed. Opt. Express 2019 10 2244 10.1364/BOE.10.002244 31143491 26. Wang S. Li J. Manapuram R.K. Menodiado F.M. Ingram D.R. Twa M.D. Lazar A.J. Lev D.C. Pollock R.E. Larin K.V. Noncontact Measurement of Elasticity for the Detection of Soft-Tissue Tumors Using Phase-Sensitive Optical Coherence Tomography Combined with a Focused Air-Puff System Opt. Lett. 2012 37 5184 10.1364/OL.37.005184 23258046 27. Kennedy K.M. Zilkens R. Allen W.M. Foo K.Y. Fang Q. Chin L. Sanderson R.W. Anstie J. Wijesinghe P. Curatolo A. Diagnostic Accuracy of Quantitative Micro-Elastography for Margin Assessment in Breast-Conserving Surgery Cancer Res. 2020 80 1773 1783 10.1158/0008-5472.CAN-19-1240 32295783 28. Allen W.M. Foo K.Y. Zilkens R. Kennedy K.M. Fang Q. Chin L. Dessauvagie B.F. Latham B. Saunders C.M. Kennedy B.F. Clinical Feasibility of Optical Coherence Micro-Elastography for Imaging Tumor Margins in Breast-Conserving Surgery Biomed. Opt. Express 2018 9 6331 10.1364/BOE.9.006331 31065432 29. Sung H. Ferlay J. Siegel R.L. Laversanne M. Soerjomataram I. Jemal A. Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries CA A Cancer J. Clin. 2021 71 209 249 10.3322/caac.21660 30. Rakha E.A. Reis-Filho J.S. Baehner F. Dabbs D.J. Decker T. Eusebi V. Fox S.B. Ichihara S. Jacquemier J. Lakhani S.R. Breast Cancer Prognostic Classification in the Molecular Era: The Role of Histological Grade Breast Cancer Res. 2010 12 207 10.1186/bcr2607 20804570 31. Plekhanov A.A. Sirotkina M.A. Sovetsky A.A. Gubarkova E.V. Kuznetsov S.S. Matveyev A.L. Matveev L.A. Zagaynova E.V. Gladkova N.D. Zaitsev V.Y. Histological Validation of in Vivo Assessment of Cancer Tissue Inhomogeneity and Automated Morphological Segmentation Enabled by Optical Coherence Elastography Sci. Rep. 2020 10 11781 10.1038/s41598-020-68631-w 32678175 32. Sirotkina M.A. Moiseev A.A. Matveev L.A. Zaitsev V.Y. Elagin V.V. Kuznetsov S.S. Gelikonov G.V. Ksenofontov S.Y. Zagaynova E.V. Feldchtein F.I. Accurate early prediction of tumour response to PDT using optical coherence angiography Sci. Rep. 2019 9 6492 10.1038/s41598-019-43084-y 31019242 33. Gubarkova E.V. Feldchtein F.I. Zagaynova E.V. Gamayunov S.V. Sirotkina M.A. Sedova E.S. Kuznetsov S.S. Moiseev A.A. Matveev L.A. Zaitsev V.Y. Optical Coherence Angiography for Pre-Treatment Assessment and Treatment Monitoring Following Photodynamic Therapy: A Basal Cell Carcinoma Patient Study Sci. Rep. 2019 9 18670 10.1038/s41598-019-55215-6 31822752 34. Zaitsev V.Y. Ksenofontov S.Y. Sovetsky A.A. Matveyev A.L. Matveev L.A. Zykov A.A. Gelikonov G.V. Real-Time Strain and Elasticity Imaging in Phase-Sensitive Optical Coherence Elastography Using a Computationally Efficient Realization of the Vector Method Photonics 2021 8 527 10.3390/photonics8120527 35. Fung Y.C. Biomechanics: Mechanical Properties of Living Tissues 2nd ed. Springer New York, NY, USA 1993 9780387979472 36. Ramião N.G. Martins P.S. Rynkevic R. Fernandes A.A. Barroso M. Santos D.C. Biomechanical Properties of Breast Tissue, a State-of-the-Art Review Biomech. Model Mechanobiol. 2016 15 1307 1323 10.1007/s10237-016-0763-8 26862021 37. Sirotkina M.A. Gubarkova E.V. Plekhanov A.A. Sovetsky A.A. Elagin V.V. Matveyev A.L. Matveev L.A. Kuznetsov S.S. Zagaynova E.V. Gladkova N.D. In Vivo Assessment of Functional and Morphological Alterations in Tumors under Treatment Using OCT-Angiography Combined with OCT-Elastography Biomed. Opt. Express 2020 11 1365 10.1364/BOE.386419 32206416 38. Gubarkova E.V. Kiseleva E.B. Sirotkina M.A. Vorontsov D.A. Achkasova K.A. Kuznetsov S.S. Yashin K.S. Matveyev A.L. Sovetsky A.A. Matveev L.A. Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study Diagnostics 2020 10 994 10.3390/diagnostics10120994 39. Zaitsev V.Y. Nonlinear Acoustics in Studies of Structural Features of Materials MRS Bulletin 2019 44 350 360 10.1557/mrs.2019.109 40. Gubarkova E.V. Sovetsky A.A. Vorontsov D.A. Buday P.A. Sirotkina M.A. Plekhanov A.A. Kuznetsov S.S. Matveyev A.L. Matveev L.A. Gamayunov S.V. Compression optical coherence elastography versus strain ultrasound elastography for breast cancer detection and differentiation: Pilot study Biomed. Opt. Express 2022 13 2859 2881 10.1364/BOE.451059 41. Rippy J.R. Singh M. Aglyamov S.R. Larin K.V. Ultrasound Shear Wave Elastography and Transient Optical Coherence Elastography: Side-by-Side Comparison of Repeatability and Accuracy IEEE Open J. Eng. Med. Biol. 2021 2 179 186 10.1109/OJEMB.2021.3075569 34179823 42. Ormachea J. Parker K.J. Elastography Imaging: The 30 Year Perspective Phys. Med. Biol. 2020 65 24TR06 10.1088/1361-6560/abca00 33181486 43. Varghese T. Ophir J. Krouskop T.A. Nonlinear Stress-Strain Relationships in Tissue and Their Effect on the Contrast-to-Noise Ratio in Elastograms Ultrasound Med. Biol. 2000 26 839 851 10.1016/S0301-5629(00)00199-X 10942831 44. Samani A. Plewes D. A Method to Measure the Hyperelastic Parameters of Ex Vivo Breast Tissue Samples Phys. Med. Biol. 2004 49 4395 4405 10.1088/0031-9155/49/18/014 15509073 45. O’Hagan J.J. Samani A. Measurement of the Hyperelastic Properties of 44 Pathological Ex Vivo Breast Tissue Samples Phys. Med. Biol. 2009 54 2557 2569 10.1088/0031-9155/54/8/020 19349660 46. Catheline S. Gennisson J.-L. Fink M. Measurement of Elastic Nonlinearity of Soft Solid with Transient Elastography J. Acoust. Soc. Am. 2003 114 3087 3091 10.1121/1.1610457 14714790 47. Erkamp R.Q. Emelianov S.Y. Skovoroda A.R. O’Donnell M. Nonlinear Elasticity Imaging:Theory and Phantom Study IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 2004 51 532 539 10.1109/TUFFC.2004.1302762 48. Gennisson J.-L. Rénier M. Catheline S. Barrière C. Bercoff J. Tanter M. Fink M. Acoustoelasticity in Soft Solids: Assessment of the Nonlinear Shear Modulus with the Acoustic Radiation Force J. Acoust. Soc. Am. 2007 122 3211 3219 10.1121/1.2793605 18247733 49. Mehrabian H. Campbell G. Samani A. A Constrained Reconstruction Technique of Hyperelasticity Parameters for Breast Cancer Assessment Phys. Med. Biol. 2010 55 7489 7508 10.1088/0031-9155/55/24/007 21098922 50. Koo T.K. Cohen J.H. Zheng Y. A Mechano-Acoustic Indentor System for In Vivo Measurement of Nonlinear Elastic Properties of Soft Tissue J. Manip. Physiol. Ther. 2011 34 584 593 10.1016/j.jmpt.2011.05.009 51. Guzina B.B. Dontsov E.V. Urban M.W. Fatemi M. The ‘Sixth Sense’ of Ultrasound: Probing Nonlinear Elasticity with Acoustic Radiation Force Phys. Med. Biol. 2015 60 3775 3794 10.1088/0031-9155/60/9/3775 25905553 52. Bernal M. Chammings F. Couade M. Bercoff J. Tanter M. Gennisson J.-L. In Vivo Quantification of the Nonlinear Shear Modulus in Breast Lesions: Feasibility Study IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 2016 63 101 109 10.1109/TUFFC.2015.2503601 53. Nazari N. Barbone P. Shear Wave Speed in Pressurized Soft Tissue J. Mech. Phys. Solids 2018 119 60 72 10.1016/j.jmps.2018.06.009 54. Napoli M.E. Freitas C. Goswami S. McAleavey S. Doyley M. Howard T.M. Hybrid Force/Velocity Control “With Compliance Estimation via Strain Elastography for Robot Assisted Ultrasound Screening Proceedings of the 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Enschede, The Netherlands 26–29 August 2018 IEEE Enschede, The Netherlands 2018 1266 1273 55. Rosen D.P. Jiang J. A Comparison of Hyperelastic Constitutive Models Applicable to Shear Wave Elastography (SWE) Data in Tissue-Mimicking Materials Phys. Med. Biol. 2019 64 055014 10.1088/1361-6560/ab0137 30673637 56. Osapoetra L.O. Watson D.M. McAleavey S.A. Intraocular Pressure–Dependent Corneal Elasticity Measurement Using High-Frequency Ultrasound Ultrason. Imaging 2019 41 251 270 10.1177/0161734619858386 31271117 57. Goswami S. Ahmed R. Doyley M.M. McAleavey S.A. Nonlinear Shear Modulus Estimation with Bi-Axial Motion Registered Local Strain IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 2019 66 1292 1303 10.1109/TUFFC.2019.2919600 31150340 58. Wang Y. Bayer M. Jiang J. Hall T.J. Large-Strain 3-D in Vivo Breast Ultrasound Strain Elastography Using a Multi-Compression Strategy and a Whole-Breast Scanning System Ultrasound Med. Biol. 2019 45 3145 3159 10.1016/j.ultrasmedbio.2019.08.013 31548103 59. Zaitsev V.Y. Matveyev A.L. Matveev L.A. Gelikonov G.V. Baum O.I. Omelchenko A.I. Shabanov D.V. Sovetsky A.A. Yuzhakov A.V. Fedorov A.A. Revealing structural modifications in thermomechanical reshaping of collagenous tissues using optical coherence elastography J. Biophotonics 2019 12 e201800250 10.1002/jbio.201800250 30417604 60. Matveev L.A. Sovetsky A.A. Matveyev A.L. Baum O. Omelchenko A. Yuzhakov A. Sobol E. Zaitsev V.Y. Optical Coherence Elastography for Characterization of Natural Interstitial Gaps and Laser-Irradiation-Produced Porosity in Corneal and Cartilaginous Samples Proc. SPIE Biomed. Spectrosc. Microsc. Imaging 2020 11359 113590G 10.1117/12.2554402 61. Zhang D. Li C. Huang Z. Relaxation Time Constant Based Optical Coherence Elastography J. Biophotonics 2020 13 e201960233 10.1002/jbio.201960233 32166913 62. Zaitsev V.Y. Matveev L.A. Matveyev A.L. Sovetsky A.A. Shabanov D.V. Ksenofontov S.Y. Gelikonov G.V. Baum O.I. Omelchenko A.I. Yuzhakov A.V. Optimization of Phase-Resolved Optical Coherence Elastography for Highly-Sensitive Monitoring of Slow-Rate Strains Laser Phys. Lett. 2019 16 065601 10.1088/1612-202X/ab183c 63. Alexandrovskaya Y.M. Baum O.I. Sovetsky A.A. Matveyev A.L. Matveev L.A. Sobol E.N. Zaitsev V.Y. Observation of Internal Stress Relaxation in Laser-Reshaped Cartilaginous Implants Using OCT-Based Strain Mapping Laser Phys. Lett. 2020 17 085603 10.1088/1612-202X/ab9446 64. Baum O.I. Zaitsev V.Y. Yuzhakov A.V. Sviridov A.P. Novikova M.L. Matveyev A.L. Matveev L.A. Sovetsky A.A. Sobol E.N. Interplay of Temperature, Thermal-stresses and Strains in Laser-assisted Modification of Collagenous Tissues: Speckle-contrast and OCT-based Studies J. Biophotonics 2020 13 e201900199 10.1002/jbio.201900199 31568651 65. Alexandrovskaya Y. Baum O. Sovetsky A. Matveyev A. Matveev L. Sobol E. Zaitsev V. Optical Coherence Elastography as a Tool for Studying Deformations in Biomaterials: Spatially-Resolved Osmotic Strain Dynamics in Cartilaginous Samples Materials 2022 15 904 10.3390/ma15030904 35160851

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095709 ijerph-19-05709 Article Mediterranean Style Dietary Pattern with High Intensity Interval Training in Men with Prostate Cancer Treated with Androgen Deprivation Therapy: A Pilot Randomised Control Trial https://orcid.org/0000-0003-3974-8107 Baguley Brenton J. 12* https://orcid.org/0000-0001-9327-6732 Adlard Kirsten 2 Jenkins David 234 Wright Olivia R. L. 25 https://orcid.org/0000-0002-5704-2741 Skinner Tina L. 2 Tchounwou Paul B. Academic Editor 1 Institute for Physical Activity and Nutrition, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia 2 School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD 4067, Australia; k.adlard@uq.edu.au (K.A.); djenkins@usc.edu.au (D.J.); o.wright@uq.edu.au (O.R.L.W.); t.skinner@uq.edu.au (T.L.S.) 3 School of Health and Behavioural Sciences, University of the Sunshine Coast, Maroochydore, QLD 4558, Australia 4 Applied Sports Science Technology and Medicine Research Centre, Swansea University, Swansea SA1 8EN, Wales, UK 5 Mater Research Institute, The University of Queensland, Brisbane, QLD 4101, Australia * Correspondence: b.baguley@deakin.edu.au; Tel.: +61-392-468-525 07 5 2022 5 2022 19 9 570928 2 2022 05 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Background: Androgen deprivation therapy (ADT) in prostate cancer has been shown to deteriorate body composition (reduced lean mass and increased body and fat mass) and increase the risk of cardiovascular morbidity. The Mediterranean style dietary pattern (MED-diet) and high intensity interval training (HIIT) may synergistically alleviate these side effects and improve quality of life in men treated with ADT. Methods: Twenty-three men (65.9 ± 7.8 years; body mass index: 29.6 ± 2.7 kg/m2; ADT duration: 33.8 ± 35.6 months) receiving ADT for ≥3 months were randomly assigned (1:1) to 20 weeks of usual care or the MED-diet (10 nutrition consults) with HIIT (4 × 4 min 85–95% heart rate peak, 3× week, starting at 12 weeks). Results: The MED-diet with HIIT significantly improved cardiorespiratory fitness (+4.9 mL·kg−1·min, p < 0.001), and body mass (−3.3 kg, p < 0.001) compared to the usual care group at 20 weeks. Clinically meaningful (≥3 points) improvements were seen in quality of life and cancer-related fatigue after 20 weeks. Conclusions: The MED-diet with HIIT increased cardiorespiratory fitness and reduced body weight in men with prostate cancer treated with ADT. Larger trials determining whether the MED-diet with HIIT translates to cardiovascular benefits are warranted. mediterranean diet high intensity interval training prostate cancer androgen deprivation therapy Sanofi AventisThis study was funded by an Advancing Care in Prostate Cancer Research Grant from Sanofi Aventis through the Clinical Oncological Society of Australia. ==== Body pmc1. Introduction Prostate cancer is the most diagnosed cancer in Australian men (excluding non-melanoma skin cancer) and by 2040 it is predicted that the number of men diagnosed, treated and living with prostate cancer will triple (~370,000) [1]. The use of androgen deprivation therapy (ADT) has coincided with improvements in disease control and improved overall survivorship in many men treated for prostate cancer [2]. ADT is however accompanied with persistent side effects, including an increase in body weight, fat mass and a reduction in lean muscle mass [3,4]. These changes have been associated with an increased risk of coronary heart disease, myocardial infarction and cardiac mortality [5]. Exercise and nutrition interventions during and/or after ADT are strongly recommended to mitigate or improve body composition and reduce cardiometabolic side effects [6,7,8,9]. Herein, lifestyle interventions (i.e., nutrition and exercise) that aim to improve cardiovascular health and body composition are clinically important for long-term health and quality of life in men treated with ADT. The health benefits from aerobic high intensity interval training (HIIT) in adults with cancer have been extensively reviewed and shown to significantly improve cardiorespiratory fitness ([V·O2peak]; MD 2.11 mL·kg−1·min−1, 95% CI 0.75–3.47, p = 0.002) compared to usual care when implemented prior to or after cancer treatment [10]. Compared to moderate-intensity continuous aerobic exercise (150 mins 50–70% maximum heart rate [HRmax]) HIIT offers similar adaptations in cardiorespiratory fitness in adults with cancer within a shorter time commitment [11]. In adults with colorectal cancer, 4 weeks of HIIT comprising of 4 × 4 min at 85–95% HRpeak, has been shown to elicit greater improvements in cardiorespiratory fitness compared to moderate-intensity continuous exercise training (+3.5 vs. 0.9 mL·kg−1·min−1; p = 0.016) [12]. These findings further indicate the physiological adaptations from HIIT appear central to the dose of exercise ≥80% HRmax [13]. Whilst the evidence showing benefits of HIIT is growing for adults with cancer, its efficacy in men with prostate cancer treated with ADT, where cardiovascular health is of clinical importance, is yet to be investigated. Meta-analysis of adherence to a Mediterranean diet (MED-diet) in cohort studies has determined that a 2-point increase in adherence score (range: 0–18, higher scores indicating higher adherence) is associated with an 8% reduction in total mortality (RR = 0.92, 95% CI; 0.91–0.93) and a 10% reduction in cardiovascular disease (RR = 0.90, 95% CI; 0.87–0.92) [14]. Furthermore, the MED-diet is associated with a 22% reduction in all-cause mortality in men with prostate cancer [15]. The diverse range of phytochemicals with antioxidant and anti-inflammatory properties within the MED-diet may at least in part contribute to cardiovascular and survivorship benefits for men with prostate cancer [16]. In women with breast cancer, the MED-diet compared to a usual care group following the World Cancer Research Fund healthy eating recommendations significantly reduced body weight (−2.4 vs. −0.9 kg), triglycerides (−14.0 vs. −8.2 mg/dL) and fasting glucose (−1.7 vs. −0.5 mg/dL) [17]. We have previously demonstrated that the MED-diet is safe, feasible and efficacious in reducing cancer-related fatigue, body weight and fat mass in men with prostate cancer treated with ADT [18], with similar findings seen in women with breast cancer [19]. Given the benefits of the MED-diet on body composition and cardiovascular health [18,19,20], and the substantial improvement in cardiorespiratory fitness from HIIT (typically 8-weeks duration) [10], the synergistic effect of the MED-diet and HIIT may offer targeted strategies to mitigate a number of well documented side-effects from ADT. Herein, this study aimed to examine the combined effects of a MED-diet and HIIT on cardiorespiratory fitness, body composition and quality of life, compared to usual care, in men with prostate cancer treated with ADT. 2. Materials and Methods 2.1. Study Design and Randomisation A two-arm randomised controlled trial was conducted in accordance with the CONSORT guidance for pilot clinical research study designs [21]. The protocol for this study has been reported elsewhere [22]. Eligibility included: (a) aged ≥18 years, (b) non-smoker, or have quit smoking for ≥3 months, (c) a diagnosis of prostate cancer and treated with ADT for ≥3 months, (d) BMI 18.5–34.9 kg/m2. After baseline testing, participants were randomly allocated to either an intervention or usual care group in a 1:1 ratio (Figure 1). Randomisation was completed by a person external to the study using a computerised random number generator with equal probability (Sealedenvelope Ltd., London, UK 2012). Participant concealment was revealed to the investigators only after baseline testing. Figure 1 shows that participants allocated to the intervention received the MED-diet for the entire 20 weeks, and at 12 weeks were asked to complete a HIIT program for 8 weeks. The results from baseline to 12 weeks for the MED-diet and usual care groups have been published elsewhere [18]. Ethical approval was granted by the Human Research Ethics Committee of The University of Queensland (2015001245), The Mater Health Services Human Research Ethics Committee (HREC/15/MHS/38) and was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12615000512527). 2.2. Intervention Nutrition and Exercise Prescription Participants randomised to the intervention group completed face-to-face, 30 to 45-min nutrition consultations with an Accredited Practising Dietitian every two weeks for 20 weeks. Participants were prescribed an individualised MED-diet outlined previously [22]. From weeks 12–20, participants allocated to the intervention group visited The University of Queensland’s School of Human Movement and Nutrition Sciences exercise laboratory three times per week to complete HIIT sessions. Prior to each exercise training session, each participant’s heart rate and blood pressure were measured and assessed for contraindications to commence exercising as outlined by the American College of Sports Medicine [23]. Exercise intensity was set at 85–95% HRpeak and each 4-min interval was interspersed with 3-min of active recovery at 50–70% HRpeak. Heart rate zones of 50–70% and 85–95% were individually determined from the highest HR recorded during a V·O2peak test at 12 weeks. The HIIT sessions commenced with 10 min of warm up at 50–70% HRpeak before participants completed 4 × 4-min bouts of cycling on an air- and magnetically braked cycle ergometer (Wattbike Ltd., Nottingham, UK). 2.3. Usual Care (Control Group) Participants randomised to the usual care group continued their usual medical care during this period. Participants in the usual care group were monitored for 20 weeks and completed testing for the primary and secondary outcome measures at the same time points as outlined below for the intervention group. 2.4. Outcomes Cardiorespiratory Fitness Cardiorespiratory fitness was assessed using a V·O2peak test; the test involved a modified ramp protocol described by Wasserman et al. [24] on a cycle ergometer. Participants began with 3 min of rest for respiratory normalisation, followed by 4 min of warm-up at a resistance of 50 Watts. The electrical resistance provided by the cycle ergometer then increased incrementally by 20–30 W·min−1 and participants cycled at a cadence between 60–70 revolutions per minute throughout the test. Heart rate was continuously recorded throughout the exercise using a heart rate monitor (Polar FT1; Polar, Kempele, Finland) and blood pressure (Durashock Sphygmomanometer; Welch Allyn, NY, USA) was recorded every 2 min throughout the test. At the conclusion of each minute, participants indicated their rating of perceived exertion (RPE) on the Borg 6–20 scale [25]. The test was terminated when the participant reached volitional fatigue or at the discretion of the researchers with consideration for exercise testing termination criteria as outlined by the American Association of Cardiovascular and Pulmonary Rehabilitation [26]. The gas analysers and ventilometer were calibrated prior to and verified after each test. Sampled expired air was measured every 15 s using a turbine ventilometer (Morgan, Model 096, Kent, UK). V·O2peak was recorded as the highest V·O2 reading averaged over two consecutive readings. 2.5. Physical Traits and Body Composition Height and body mass were measured according to the International Society for the Advancement of Kinanthropometry procedures [27]. Body composition (fat mass, lean mass and body fat mass) was assessed using dual energy X-ray absorptiometry (Hologic Discovery A, Waltham, MA, USA). 2.6. Intervention Fidelity Intervention fidelity was defined by four components: (a) intervention safety, (b) study completion rate, (c) consult attendance rate and (d) adherence to the MED-diet. (a) All intervention and usual care adverse events were reported to the primary investigator as a measure of intervention safety. Adverse events were defined as an untoward injury or medical occurrence from the intervention (MED-diet) or outcome measures which interfered with the capacity of the participant to carry out their usual activities. Adverse events were also monitored at each nutrition consultation for common signs and symptoms of dietary change (e.g., gastrointestinal tolerance). (b) Intervention completion was measured by the number of participants completing baseline, 12- and 20-week testing sessions. (c) Attendance at the MED-diet consultations was measured by the number of sessions attended, divided by the number of sessions prescribed. (d) Adherence to the MED-diet was measured by the Mediterranean-diet adherence screener (MEDAS) [28]; a 14-question (yes/no) response to the frequency of food groups was included in the MED-diet. The total responses of ‘yes’ were tallied to provide an overall dietary adherence to the MED-diet. Question 8 (how much wine do you drink; ≥7 glasses = adherence) was omitted from the MEDAS due to the intervention promoting a reduction in alcohol intake. High adherence was classified as meeting a priori cut point of ≥75% of the 13-question MEDAS. (e) Adherence to exercise intensity was quantified by two measures. Mean HR was calculated using a combination of data points collected throughout the exercise intervals and recovery periods. Mean HR was calculated using all data points collected at 1-s epochs throughout the designated interval or recovery period. Time to reach 85% of HRpeak was measured at the start of each interval and recorded in minutes: seconds. Adherence was determined by reaching 85% HRpeak and quantified by the time spent exercising ≥85% HRpeak for each interval. Rating of perceived exertion (RPE) for each interval was also used as a measure of exercise intensity. 2.7. Cancer-Related Fatigue and Quality of Life Cancer-related fatigue and quality of life were measured using the Functional Assessment of Chronic Illness Therapy: Fatigue (FACIT-F), FACIT-general (FACIT-G) questionnaire [29], and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF−36) [30]. The questionnaire instructions were read to the participant by a study investigator (B.J.B), and participants completed the questionnaires in a separate room to the study investigators. 2.8. Change in Dietary Intake Participants completed the Wollongong Dietary Inventory [31], a comprehensive dietary history of intake over the previous month, with cross-checking quantification from the dietitian. 2.9. Statistical Analysis All analyses were conducted in SPSS (version 23.0; Chicago, IL, USA). Intention to treat linear mixed models were used to determine changes in cardiorespiratory fitness, body composition and quality of life between the MED-diet and usual care groups at baseline, 12 weeks and 20 weeks. Models included group, time and group x time as fixed factors, and a random intercept term for each participant in the study to account for the correlation between repeated observations on an individual. All models also adjusted for baseline values by inclusion as a covariate. Model residuals were assessed for normality using the Shapiro–Wilk test and visual inspection of the histogram and quantile-quantile plots. Statistical significance was two-tailed and accepted at the p ≤ 0.05 level. For FACIT-F and FACIT-G questionnaires, a ≥3 point change in mean score was classified as a clinically important change [32]. 3. Results A total of 23 men with prostate cancer treated with ADT were randomised for this trial. Participant flow through the intervention is shown in Figure 1 and the participant characteristics are described in Table 1. As described elsewhere [18], time since diagnosis was longer in the MED-diet with HIIT group (77.1 ± 58.8 months) compared to the usual care group (51.3 ± 42.4 months); however, time on ADT was similar between groups (MED- diet: 36.4 ± 38.3 months; usual care: 31.0 ± 32.2 months). The mean Gleason score for all men in this trial was 8.4 and represents an ISUP (International Society of Urological Pathology) Grade group of 4. The MED-diet with HIIT completion rate was 75% (9/12), whilst 90% of participants completed usual care (10/11). Figure 2 shows two participants allocated to the MED-diet with HIIT were deemed ineligible for HIIT and only completed weeks 0–12 of the MED-diet intervention due to high cardiac risk (n = 1), and already performing HIIT (n = 1). Attendance at the nutrition consults and exercise sessions was 100%. On five occasions, only two HIIT sessions were completed within one week (instead of the allocated three HIIT sessions), with participants completing four HIIT sessions the following week. No adverse events occurred from the MED-diet and HIIT interventions or outcome measures across the 20 weeks. 3.1. Intervention Adherence MEDAS was superior in the MED-diet and HIIT group at 12 weeks [+4.9, (3.8, 5.9); p < 0.001] and 20 weeks [+2.8 (1.27, 4.45); p = 0.001) relative to the usual care group. The MED-diet and HIIT group showed high adherence to the nutrition prescription with 81% (n = 7/11) reaching ≥75% on the MEDAS at 12 weeks, and 66% (n = 6/9) at 20 weeks. The MED-diet and HIIT group showed significant reductions in energy intake [−1.7 MJ/day (−3.1, −0.2); p = 0.019], saturated fat [−14.2 g/day (−22.7, −5.6); p = 0.001], red meat [−0.5 servings/day (−0.9, −0.1); p = 0.016] and processed meat [−0.2 serves/day (−0.4, −0.1); p = 0.007], relative to the usual care group at 20 weeks (Table 2). The MED-diet and HIIT group significantly increased fibre [+7.8 g/day (1.9, 13.7); p = 0.010] and nuts and seeds [1.1 servings/day (0.2, 2.1); p = 0.013] relative to the usual care group at 20 weeks. Adherence to the prescribed 85–95% HRpeak (based on the HRpeak achieved during the 12-week V·O2peak test) was 93.4% for all four intervals over the 8-week training phase. Total time spent exercising at 85–95%% HRpeak was 86.5 ± 13.0% (13.8 ± 2.0 min) of the prescribed 16 min (4 × 4 min) across the 8 weeks. Average RPE was 15.6 ± 1.2 (equating to ~ “Hard”). HIIT performance outcomes revealed an average power output (80.4 ± 20.1 Watts), peak power output (225.4 ± 78.8 Watts), average revolutions per minute (RPM, 66.3 ± 7.3), peak RPM (87.3 ± 10.5), distance (16.0 ± 1.4 km) and estimated energy obtained from Wattbike (236.6 ± 67.2 kcal). 3.2. Cardiorespiratory Fitness Table 3 shows there were no significant between-group differences in V·O2peak (absolute and relative) at 12 weeks when the MED-diet and HIIT group was compared to usual care. However, after 20 weeks, the MED-diet and HIIT group showed a significant increase in absolute V·O2peak [+0.3 L/min (0.1, 0.5); p = 0.002] and relative V·O2peak [+4.9 mL·kg−1·min (2.5, 7.4); p < 0.001], compared to the usual care group. 3.3. Body Composition Total body mass was significantly reduced at 12 weeks [−2.97 kg (−4.71, −1.24); p = 0.001] and 20 weeks [−3.32 kg (−5.10, −1.54); p < 0.001] when the MED-diet and HIIT group was compared to usual care. MED-diet and HIIT reduced lean muscle mass at 12 weeks [−1.35 kg (−2.75, 0.55); p = 0.060) and 20 weeks [−1.22 kg (−2.69, 0.25); p = 0.102). Fat mass was reduced at 12 weeks [−1.57 kg (−3.42, 0.28); p = 0.096] and 20 weeks [−1.25 kg (−3.14, 0.64); p = 0.192) from the MED-diet and HIIT relative to the usual care group. 3.4. Quality of Life Quality of life as measured by the FACIT-G was significantly higher at 12 weeks when the MED-diet and HIIT group was compared to usual care [+9.2 points (2.7–15.8); p = 0.006]. After 20 weeks there was no significant differences between-groups in FACIT-G when the MED-diet and HIIT group was compared to usual care [+4.8 points (−2.0, 11.6); p = 0.167], yet these changes were clinically significant (i.e., ≥3 points). There were no further between-group differences in FACIT-G quality of life domains when the MED-diet and HIIT group was compared to usual care. Quality of life, as measured by the SF-36, showed no significant between-group differences in the general health domain when the MED-diet and HIIT group was compared to usual care at 12 weeks [+4.1 points (−10.9, 19.1); p = 0.588] and 20 weeks [−3.1 points (−18.7, 12.4); p = 0.688]. Both the vitality [+16.2 points (6.2, 26.2); p = 0.002] and mental health composite domains [+4.1 points (0.1, 8.0); p = 0.042] showed significant improvements in favour of the MED-diet and HIIT group after 20 weeks compared to the usual care group. 4. Discussion The present study has found that for men with prostate cancer undergoing ADT, a MED-diet with HIIT (i) significantly improves cardiorespiratory fitness relative to usual care at 20 weeks; (ii) reduces body weight relative to the usual care group at 20 weeks; (iii) maintains lean body mass despite achieving weight loss at 20 weeks; (iv) significantly improves vitality and mental health composite (SF-36) at 20 weeks, and clinical improvements were seen in prostate-cancer specific quality of life (FACIT-G) and cancer-related fatigue (FACIT-F) at 20 weeks relative to usual care; (v) is safe and feasible in men treated with ADT. The MED-diet with HIIT showed a significant increase in V·O2peak compared to the control group at 20 weeks (+4.9 mL·kg−1·min−1. p < 0.001; +0.3 L/min, p = 0.002). Given a 3.5 mL·kg−1·min−1 increase in cardiorespiratory fitness is associated with a 10% and 25% reduction in cancer specific mortality and cardiovascular-related mortality respectively [34], the increase of 4.9 mL·kg−1·min−1. in V·O2peak observed in our study potentially offers substantial cardiovascular health benefits. Our findings are consistent with a previous meta-analysis showing that HIIT is safe, feasible and efficacious in improving V·O2peak (MD 3.73 mL·kg−1·min−1; p < 0.001) in adults after cancer treatment [11]. In men with prostate cancer, aerobic exercise interventions have shown moderate improvements in V·O2peak (SMD 0.27 mL·kg−1·min−1.) [35], and recently, 12 weeks of HIIT (5–8 × 2 min 85–95% V·O2peak treadmill speed and grade, with 2-min active recovery) during active surveillance has shown to significantly improve V·O2peak compared to usual care (1.6 mL·kg−1·min−1; 95% CI, 0.3–2.9; p = 0.01) [36]. The substantial improvement in V·O2peak in our study is likely explained by the high adherence to HIIT (86.5% of each interval was ≥85%HRpeak), time spent exercise above ≥85%HRpeak (13.8 ± 2.0 min), and the low baseline V·O2peak. HIIT (4 × 4 min 85–95% HRpeak) is therefore effective in improving cardiorespiratory fitness to a magnitude that is clinically meaningful in men treated with ADT, however further investigations in a larger sample, that is adequately powered, are required. Combined nutrition and exercise interventions in men with prostate cancer have shown varied effects on reducing body weight; with weight loss ranging from 0.8kg to 6.1 kg [37]. The MED-diet significantly reduced weight (2.97 kg) and fat mass (1.57 kg); however, it also reduced lean mass (1.35 kg) after 12 weeks in this cohort of men treated with ADT [18]. The addition of HIIT to the MED-diet appears to preserve lean mass (−1.35 vs. −1.22 kg) and maintain total body mass (−2.97 vs. −3.32 kg) and fat mass (−1.57 vs. −1.25 kg) at 20 weeks. A recent systematic review in adults who have predominately finished cancer treatment suggests HIIT compared to moderate-intensity continuous training reduces body weight, but has no effect on lean mass [11]. Though two interventions (7 × 30 s > 85% HRmax [38] and 4 × 4 min 80–95% HRmax with 3 × 3 min active recovery [39]) have reported significant reductions in fat mass (ranging from 4 to 5.5%) following HIIT. In our study, it is likely that the significant reductions in body weight and fat mass from the MED-diet at 12 weeks, prior to the introduction of HIIT, diminished the potential changes in body composition from HIIT. Furthermore, our participants showed high adherence to the MED-diet and had similar energy intake across the 20 weeks. The MED-diet was hypocaloric, compared to habitual intake at baseline (−1.7 MJ at 12 weeks), with the MED-diet designed to meet individual estimated energy requirements. Herein, the fortnightly nutrition consultations progressive changed dietary intake to meet MED-diet targets and likely explains the substantial changes in body mass and composition occurring within the first 12 weeks and plateauing at 20 weeks when the participants are familiar with the MED-diet. The MED-diet with HIIT showed inconsistent findings in cancer-related fatigue (SF−36 Vitality: +16.2 points, p = 0.001; FACIT-F: +2.6 points, p = 0.312) and quality of life (SF-36: −3.1 points; FACIT-G +8.2 points) compared to usual care at 20 weeks. However, relative to baseline, clinical improvements in the present study were observed in cancer-related fatigue and quality of life (≥3 points in the FACIT-F and G scale) from the MED-diet with HIIT after 20 weeks, and this suggests the combined diet and exercise prescription may provide quality of life benefits. Our findings contrast previous systematic reviews assessing HIIT interventions in cancer survivors [40], and combined exercise with or without nutrition interventions in men with prostate cancer [41]. These reviews have concluded that quality of life and cancer-related fatigue improve in response to exercise-only and exercise-plus-nutrition interventions. The usual care group in our study also improved in quality of life (+5.2 points) and cancer-related fatigue (+3.1 points) between 12 and 20 weeks. Whilst the reason for these improvements is not clear, men in the usual care group were free to seek exercise and/or dietary advice from other health care professionals, which may have influenced these outcomes. Given exercise interventions in prostate cancer have shown to improve quality of life and reduce cancer-related fatigue, further investigations in fatigued men with prostate cancer treated with ADT are warranted. There are several strengths and limitations to our study. This is the first intervention to combine the MED-diet with HIIT and examine the synergistic effects on cardiorespiratory fitness, body composition and quality of life; all of which are known to be negatively impacted by ADT. This pilot study was highly supervised (fortnightly dietary interventions with 3 × 8 week supervised HIIT exercise) to ensure maximum safety and adherence across the 20-week intervention. However, there are some limitations worthy of comment. Our study failed to reach its sample size and experienced unique recruitment barriers which have been published elsewhere [18]. In addition, men in the intervention group had been diagnosed with prostate cancer longer than the control group (77.1 vs. 51.3 months) which may have influenced motivations and/or adherence to the intervention and the associated health benefits from face-to-face nutrition support and supervised exercise training. Although there were positive effects on body composition and quality of life measures from the MED-diet with HIIT relative to baseline, these results are masked by the efficacy of the 12-week MED-diet prior to starting HIIT. Thus, there was a ceiling effect on quality of life measures whereby the addition of HIIT to the MED-diet showed diminishing returns. Furthermore, it is unknown whether the MED-diet added any benefits when combined with HIIT for cardiorespiratory fitness. To test whether there are additive benefits from the MED-diet on HIIT, factorial 2 × 2 design RCT with four groups (MED-diet vs. HIIT vs. MED-diet with HIIT vs. usual care) would be required in future studies. Lastly, whether the improvements in cardiorespiratory fitness are associated with improvements in cardiovascular health (i.e., cholesterol, triglycerides) from the MED-diet with HIIT warrants investigation. 5. Conclusions In summary, the HIIT component of our intervention showed significant improvements in cardiorespiratory fitness to a magnitude that is associated with reduced cardiovascular-related morbidity and mortality in adults with cancer. Whilst the MED-diet likely offered cardiovascular benefits with HIIT, the physiological mechanism/s is/are unknown, and should be considered in future larger-scale investigations to extend our findings. The MED-diet with HIIT showed significant reductions in body weight, which is typically increased by ADT, and may be of clinical benefit for future weight loss interventions. Cancer-related fatigue and quality of life was improved after 12 weeks of the MED-diet; however, there were diminishing returns when measured at 20 weeks, after HIIT had been introduced. Future larger-scale trials examining the MED-diet with HIIT on cardiorespiratory fitness, body composition and quality of life are warranted to extend our findings. Acknowledgments The researchers acknowledge all the patients and research partners who dedicated their time to this study. Author Contributions Conceptualisation, B.J.B., O.R.L.W. and T.L.S.; methodology, B.J.B., K.A., O.R.L.W. and T.L.S., D.J.; formal analysis, B.J.B.; investigation, B.J.B. and K.A.; data curation, B.J.B. and K.A.; writing—original draft preparation, B.J.B.; writing—review and editing, B.J.B., O.R.L.W., T.L.S. and D.J.; project administration, B.J.B. and K.A.; funding acquisition, O.R.L.W. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of The University of Queensland (2015001245) and The Mater Health Services Human Research Ethics Committee (HREC/15/MHS/38). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data can be made available upon request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 CONSORT diagram and schematic representation of the study. Legend: MED-diet = Mediterranean-style dietary pattern; HIIT = high intensity interval training; Wk = week. Figure 2 CONSORT diagram illustrating participant flow through the intervention. ADT: androgen deprivation therapy; MED-diet: Mediterranean-style dietary pattern; HIIT: high intensity interval training. ijerph-19-05709-t001_Table 1 Table 1 Baseline participant characteristics. All (n = 23) Intervention (n = 12) Usual Care (n = 11) Age (years) 65.9 ± 7.8 66.6 ± 7.6 65.1 ± 7.9 Height (cm) 177.7 ± 6.7 177.2 ± 7.5 178.3 ± 5.7 BMI (kg/m2) 28.9 ± 3.4 27.4 ± 3.0 30.6 ± 2.9 Married (%) 56.5 54.5 58.3 Past smoker (%) 56.5 63.3 58.3 Meeting PA guidelines (%) 43.4 27.2 58.3 Gleason Score 8.4 ± 1.1 8.1 ± 0.9 8.7 ± 1.2 Prostate Specific Antigen concentration (ng/mL) 1.1 ± 1.3 1.3 ± 1.2 1.0 ± 1.3 Time since diagnosis (months) 64.8 ± 53.2 77.1 ± 58.8 51.3 ± 42.4 Time on ADT (months) 33.8 ± 35.6 36.4 ± 38.3 31.0 ± 32.2 Previous radiation (%) 65.2 66.6 63.6 Duration of radiation (months) 2.2 ± 1.6 2.4 ± 2.1 2.0 ± 0.1 Previous chemotherapy (%) 17.3 16.6 18.1 Duration of chemotherapy (months) 3.2 ± 1.6 4.0 ± 2.0 2.5 ± 0.5 Previous prostatectomy (%) 30.4 8.6 45.4 Data are presented as mean ± SD or %. ADT: androgen deprivation therapy; BMI: body mass index; PA: physical activity, as measured by the Godin Leisure-Time Physical Activity Questionnaire [33]. ijerph-19-05709-t002_Table 2 Table 2 The effects of the MED-diet and HIIT compared to usual care on energy, macronutrients and foods groups. Group n Baseline p Value n 12 Weeks p Value (0 vs. 12 Weeks) p Value a (INT vs. UC) n 20 Weeks p Value (0 vs. 20 Weeks) p Value (12 vs. 20 Weeks) p Value b (INT vs. UC) Energy (MJ/day) INT 12 10.3 (9.1, 10.9) 0.689 11 8.6 (7.6, 9.5) 0.032 0.057 9 8.2 (7.2, 9.2) 0.014 >0.999 0.019 UC 11 9.7 (8.8, 10.7) 10 9.9 (8.9, 10.9) >0.999 10 9.9 (8.9, 10.9) >0.999 >0.999 Protein (g/day) INT 12 110.1 (99.7, 120) 0.601 11 108.8 (97.9, 119) >0.999 0.850 9 103.7 (91.7, 115.7) >0.999 >0.999 0.211 UC 11 106.1 (95.2, 117) 10 107.3 (95.9, 118) >0.999 10 114.2 (102.8, 125.6) >0.999 >0.999 Fat (g/day) INT 12 91.7 (78.7, 104) 0.776 11 76.5 (63.0, 90.0) 0.316 0.048 9 79.8 (65.1, 94.5) 0.766 >0.999 0.190 UC 11 89.0 (75.4, 102) 10 96.3 (82.1, 110) >0.999 10 93.4 (79.2, 107.5) >0.999 >0.999 Saturated fat (g/day) INT 12 33.6 (28.7, 38.9) 0.477 11 17.2 (11.6, 22.8) <0.001 <0.001 9 20.6 (14.5, 26.7) 0.002 0.674 0.001 UC 11 30.8 (24.8, 36.4) 10 34.0 (28.1, 39.9) >0.999 10 34.8 (28.9, 40.7) >0.999 >0.999 Polyunsaturated fat (g/day) INT 12 15.9 (12.5, 19.2) 0.952 11 20.8 (17.4, 24.3) 0.043 0.065 9 18.4 (14.8, 22.1) 0.183 0.222 0.280 UC 11 16.0 (12.5, 19.5) 10 16.2 (12.6, 19.8) >0.999 10 15.6 (11.9, 19.3) 0.833 0.765 Monounsaturated fat (g/day) INT 12 39.2 (31.5, 47.0) 0.770 11 37.5 (29.5, 45.5) >0.999 0.442 9 36.0 (27.2, 44.7) 0.526 0.767 0.763 UC 11 40.9 (32.9, 48.9) 10 42.0 (33.6, 50.4) >0.999 10 34.1 (25.3, 42.9) 0.198 0.140 LCN3FA (g/day) INT 12 0.80 (0.43, 1.18) 0.800 11 1.42 (1.03, 1.81) 0.033 0.013 9 1.2 (0.7, 1.6) 0.090 0.344 0.145 UC 11 0.73 (0.34, 1.13) 10 0.69 (0.28, 1.10) >0.999 10 0.7 (0.3, 1.1) 0.943 0.803 ALA (g/day) INT 12 1.71 (0.80, 2.61) 0.984 11 2.68 (1.74, 3.62) 0.272 0.184 9 3.1 (2.1, 4.1) 0.013 0.483 0.587 UC 11 1.72 (0.78, 2.66) 10 1.77 (0.79, 2.75) >0.999 10 1.7 (0.7, 2.7) 0.933 0.998 Linoleic acid (g/day) INT 12 13.0 (10.4, 15.6) 0.917 11 15.4 (12.7, 18.0) 0.573 0.301 9 14.1 (11.2, 16.9) 0.479 0.392 0.490 UC 11 13.2 (10.5, 15.9) 10 13.3 (10.6, 16.1) >0.999 10 12.6 (9.7, 15.5) 0.725 0.648 Cholesterol (g/day) INT 12 338 (259, 417) 0.369 11 316 (233, 399) >0.999 0.834 9 244 (153, 335) 0.104 0.221 0.244 UC 11 286 (203, 368) 10 303 (217, 390) >0.999 10 320 (229, 412) 0.554 0.774 Carbohydrates (g/day) INT 12 238 (209, 267) 0.820 11 197 (167, 227) 0.064 0.231 9 180.0 (147.3, 212.6) 0.009 0.978 0.065 UC 11 233 (203, 264) 10 224 (192, 256) >0.999 10 222.9 (191.2, 254.6) >0.999 >0.999 Fibre (g/day) INT 12 34.6 (30.8, 38.4) 0.976 11 47.0 (43.0, 50.9) <0.001 <0.001 9 44.7 (40.5, 49.0) <0.001 0.330 0.010 UC 11 34.6 (30.6–38.5) 10 34.9 (30.8, 39.0) >0.999 10 36.9 (32.7, 41.0) >0.999 >0.999 Ethanol (g/day) INT 12 15.3 (9.26, 21.5) 0.401 11 4.9 (1.4, 11.3) 0.018 0.051 9 3.2 (1.3, 10.0) 0.002 0.635 0.012 UC 11 13.4 (6.96, 19.8) 10 14.2 (7.51, 20.9) >0.999 10 15.6 (8.9, 22.3) 0.551 0.706 Fruit (servings/day) INT 12 2.21 (1.68, 2.75) 0.960 11 2.46 (1.91, 3.01) >0.999 0.019 9 2.3 (1.7, 2.9) >0.999 >0.999 0.223 UC 11 2.23 (1.68, 2.79) 10 1.50 (0.92, 2.07) 0.122 10 1.7 (1.2, 2.3) 0.640 0.986 Vegetables (servings/day) INT 12 4.28 (3.33, 5.22) 0.943 11 8.22 (7.24, 9.20) <0.001 0.001 9 7.3 (6.3, 8.2) <0.001 0.328 0.061 UC 11 4.23 (3.42, 5.22) 10 4.84 (3.81, 5.87) 0.872 10 5.9 (4.9, 7.0) 0.020 0.223 Refined grain (servings/day) INT 12 3.35 (2.40, 4.30) 0.690 11 1.92 (0.93, 2.90) 0.090 0.011 9 2.0 (0.9, 3.1) 0.134 >0.999 0.487 UC 11 3.62 (2.64, 4.61) 10 3.81 (2.77, 4.85) >0.999 10 2.5 (1.5, 3.5) 0.391 >0.999 Nuts and seeds (servings/day) INT 12 0.92 (0.33, 1.51) 0.401 11 1.89 (1.28, 2.51) 0.114 0.717 9 1.7 (1.0, 2.3) 0.376 >0.999 0.013 UC 11 1.28 (0.67, 1.90) 10 1.73 (1.08, 2.37) 0.893 10 0.5 (0.1, 1.1) 0.336 0.036 Fish (servings/day) INT 12 0.61 (0.38, 0.84) 0.897 11 0.90 (0.67, 1.13) 0.121 0.006 9 0.7 (0.4, 0.9) 0.904 0.295 0.702 UC 11 0.59 (0.35, 0.83) 10 0.44 (0.20, 0.67) >0.999 10 0.6 (0.4, 0.8) >0.999 >0.999 Red meat (servings/day) INT 12 0.75 (0.48, 1.03) 0.398 11 0.33 (0.06, 0.61) 0.071 0.205 9 0.2 (0.0, 0.5) 0.038 >0.999 0.016 UC 11 0.59 (0.31, 0.86) 10 0.60 (0.30, 0.89) >0.999 10 0.8 (0.4, 1.1) >0.999 >0.999 Processed meat (servings/day) INT 12 0.36 (0.25, 0.47) 0.632 11 0.04 (0.01, 0.15) <0.001 <0.001 9 0.0 (0.0, 0.2) >0.999 0.001 0.007 UC 11 0.32 (0.21, 0.43) 10 0.38 (0.27, 0.49) >0.999 10 0.3 (0.2, 0.4) >0.999 >0.999 Poultry (servings/day) INT 12 0.43 (0.20, 0.65) 0.985 11 0.47 (0.25, 0.70) >0.999 0.669 9 0.6 (0.3, 0.8) >0.999 >0.999 0.078 UC 11 0.42 (0.20, 0.65) 10 0.40 (0.16, 0.64) >0.999 10 0.2 (0.0, 0.5) >0.999 >0.999 Dairy (servings/day) INT 12 2.84 (2.12, 3.56) 0.353 11 1.58 (0.83, 2.33) 0.033 0.508 9 1.7 (0.9, 2.6) 0.136 >0.999 0.248 UC 11 2.35 (1.60, 3.10) 10 1.95 (1.16, 2.74) >0.999 10 2.4 (1.6, 3.2) >0.999 >0.999 Intention to treat linear mixed modelling analysis; fixed factors: group, time, group × time; fixed covariates: baseline variable score; random factors: participants. Abbreviations: ALA, α-linoleic acid; LCN3FA, long chain ω-3 fatty acid. INT, Intervention; UC, Usual care. All values are mean (95%CI). a Between group comparisons at 12 weeks. b Between group comparisons at 20 weeks. ijerph-19-05709-t003_Table 3 Table 3 The effects of the MED-diet and HIIT compared to usual care on cardiorespiratory fitness, body composition and quality of life. Group n Baseline p Value n 12 Weeks p Value (0 vs. 12 Weeks) p Value a (INT vs. UC) n 20 Weeks p Value (0 vs. 20 Weeks) p Value (12 vs. 20 Weeks) p Value b (INT vs. UC) Cardiorespiratory fitness VO2peak (L/min) INT 12 2.02 (1.89, 2.16) 0.740 11 2.07 (1.94, 2.21) 0.521 0.492 9 2.34 (2.19, 2.48) <0.001 <0.001 0.002 UC 11 2.06 (1.93, 2.19) 10 2.00 (1.87, 2.14) 0.487 10 2.02 (1.88, 2.15) 0.608 0.857 VO2peak (mL·kg−1.min−1) INT 12 22.1 (20.4, 23.7) 0.961 11 23.6 (21.9, 25.2) 0.104 0.161 9 26.8 (25.0, 28.5) <0.001 <0.001 <0.001 UC 11 22.0 (20.5, 23.9) 10 21.9 (20.2, 23.5) 0.874 10 21.8 (20.1, 23.5) 0.821 0.947 400 m walk test (s) INT 12 260.6 (241.3, 279.8) 0.872 11 246.0 (226.2, 265.8) 0.103 0.945 9 241.0 (220.6, 261.4) 0.203 0.589 0.457 UC 11 268.6 (248.4, 288.8) 10 247.0 (226.8, 267.2) 0.106 10 251.9 (231.7, 272.1) 0.064 0.585 Body composition (kg) Total body mass INT 12 92.0 (90.9,93.1) 0.784 11 88.7 (87.5, 89.8) <0.001 0.001 9 87.8 (86.5, 89.0) <0.001 0.371 <0.001 UC 11 92.2 (91.1, 93.4) 10 91.6 (90.4, 92.8) >0.999 10 91.1 (89.9, 92.3) 0.461 >0.999 Lean muscle mass INT 12 53.2 (52.2, 54.1) 0.750 11 52.0 (51.0, 53.0) 0.397 0.060 9 52.0 (50.9, 53.0) 0.397 >0.999 0.102 UC 11 53.4 (52.4, 54.3) 10 53.4 (52.3, 54.4) >0.999 10 53.2 (52.2, 54.2) >0.999 >0.999 Fat mass INT 12 29.5 (28.3, 30.7) 0.696 11 27.8 (26.6, 29.0) 0.032 0.096 9 27.2 (25.9, 28.5) 0.005 0.796 0.192 UC 11 29.8 (28.6, 31.1) 10 29.3 (28.1, 30.6) >0.999 10 28.5 (27.2, 29.7) 0.206 0.178 FACIT 1 General (0–108) INT 12 83.1 (78.7, 87.4) 0.888 11 90.5 (85.9, 95.0) 0.038 0.006 9 91.3 (86.4, 96.3) 0.032 >0.999 0.167 UC 11 82.6 (78.1, 87.2) 10 81.2 (76.5, 86.0) >0.999 10 86.5 (81.8, 91.3) 0.569 0.343 Total (0–160) INT 12 120.3 (113.8, 26.9) 0.771 11 133.4 (126.6, 140.3) 0.013 0.002 9 133.8 (126.3, 141.3) 0.015 >0.999 0.141 UC 11 118.9 (112.1, 125.8) 10 117.1 (110.0, 124.3) >0.999 10 126.1 (118.9, 133.2) 0.515 0.270 TOI (0–108) INT 12 83.2 (77.1, 89.2) 0.762 11 91.9 (85.6, 98.2) 0.081 0.024 9 91.5 (84.7, 98.4) 0.132 >0.999 0.371 UC 11 81.8 (75.5, 88.2) 10 81.1 (74.5, 87.8) >0.999 10 87.1 (80.5, 93.8) 0.739 0.633 Fatigue (0–52) INT 12 37.1 (33.9, 40.3) 0.684 11 42.9 (39.6, 46.3) 0.025 0.005 9 42.5 (38.8, 46.1) 0.064 >0.999 0.312 UC 11 36.2 (32.8, 39.5) 10 35.7 (32.2, 39.3) >0.999 10 39.8 (36.3, 43.4) 0.378 0.317 Physical Wellbeing (0–28) INT 12 23.3 (21.9, 24.7) 0.614 11 25.1 (23.6, 26.6) 0.145 0.036 9 25.0 (23.4, 26.6) 0.206 >0.999 0.247 UC 11 22.8 (21.3, 24.6) 10 22.8 (21.3, 24.4) >0.999 10 23.7 (22.2, 25.3) >0.999 >0.999 Social Wellbeing (0–28) INT 12 19.7 (17.4, 22.1) 0.889 11 21.9 (19.5, 24.4) 0.666 0.052 9 23.1 (20.4, 25.7) 0.214 >0.999 0.078 UC 11 20.0 (17.5, 22.4) 10 18.4 (15.9, 21.0) >0.999 10 19.7 (17.2, 22.3) >0.999 >0.999 Emotional Wellbeing (0–24) INT 12 18.5 (17.3, 19.7) 0.964 11 20.8 (19.5, 22.0) 0.024 0.083 9 20.5 (18.6, 21.4) 0.256 0.798 0.320 UC 11 18.5 (17.2, 19.7) 10 19.1 (17.8, 20.5) 0.804 10 21.0 (19.7, 22.4) 0.015 0.125 Functional Wellbeing (0–28) INT 12 21.5 (19.8, 23.3) 0.747 11 22.5 (20.7, 24.4) >0.999 0.177 9 23.2 (21.1, 25.2) 0.894 >0.999 0.295 UC 11 21.1 (19.3, 23.0) 10 20.7 (18.7, 22.6) >0.999 10 21.7 (19.7, 23.6) >0.999 >0.999 SF-36 1 Physical Function (0–100) INT 12 80.8 (71.7, 89.9) 0.617 11 78.3 (68.8, 87.7) 0.680 0.571 9 89.7 (79.3, 100.1) 0.669 0.498 0.304 UC 11 77.4 (67.9, 87.0) 10 82.2 (72.2, 92.1) >0.999 10 82.2 (72.2, 92.1) >0.999 >0.999 Role Function (0–100) INT 12 72.6 (64.8, 80.4) 0.438 11 72.8 (64.7, 80.9) >0.999 0.685 9 80.7 (71.8, 89.6) 0.616 0.616 0.858 UC 11 68.1 (60.0, 76.3) 10 75.2 (66.7, 83.8) 0.510 10 79.6 (71.1, 88.2) 0.141 0.811 Bodily Pain (0–100) INT 12 76.5 (65.6, 87.3) 0.622 11 77.8 (66.3, 89.1) >0.999 0.895 9 80.3 (68.1, 92.5) >0.999 >0.999 0.407 UC 11 72.5 (61.2, 83.9) 10 76.8 (65.0, 88.6) >0.999 10 73.2 (61.4, 85.0) >0.999 >0.999 General (0–100) INT 12 57.2 (47.2, 67.3) 0.737 11 66.3 (55.9, 76.7) 0.710 0.588 9 59.7 (48.5, 70.9) >0.999 >0.999 0.688 UC 11 59.7 (49.2, 70.2) 10 62.2 (51.3, 73.1) >0.999 10 62.9 (52.0, 73.8) >0.999 >0.999 Vitality (0–100) INT 12 58.7 (52.4, 65.0) 0.966 11 71.6 (64.5, 77.7) 0.001 0.003 9 75.9 (68.7, 83.1) 0.015 0.838 0.002 UC 11 58.5 (51.9, 65.1) 10 56.5 (49.6, 63.4) 0.645 10 59.7 (52.8, 66.6) >0.999 >0.999 Social Functioning (0–100) INT 12 86.1 (79.0, 93.1) 0.733 11 87.1 (79.8, 94.4) >0.999 0.138 9 91.8 (83.9, 99.6) >0.999 >0.999 0.482 UC 11 84.3 (77.0, 91.7) 10 79.1 (71.4, 86.7) 0.820 10 87.8 (80.2, 95.5) >0.999 0.230 Role Emotion (0–100) INT 12 79.8 (73.4, 86.2) 0.893 11 85.4 (78.7, 92.1) 0.521 0.780 9 94.4 (87.0, 101.9) 0.024 0.385 0.230 UC 11 79.2 (72.5, 85.9) 10 84.1 (77.0, 91.1) >0.999 10 88.2 (81.2, 95.3) 0.407 >0.999 Mental Health (0–100) INT 12 80.3 (75.7, 84.8) 0.925 11 84.4 (79.6, 89.2) 0.748 0.071 9 88.1 (82.9, 93.4) 0.112 0.785 0.127 UC 11 80.0 (75.2, 84.7) 10 78.0 (73.0, 83.0) >0.999 10 82.5 (77.5, 87.5) >0.999 >0.999 PH Composite (0–100) INT 12 48.6 (45.1, 52.0) 0.649 11 48.7 (45.1, 52.3) >0.999 0.737 9 50.0 (46.1, 54.0) >0.999 >0.999 0.695 UC 11 47.4 (43.8, 51.0) 10 49.6 (45.8, 53.4) >0.999 10 49.0 (45.2, 52.8) >0.999 >0.999 MH Composite (0–100) INT 12 51.6 (49.1, 54.1) 0.923 11 55.2 (52.6, 57.8) 0.188 0.011 9 57.6 (54.7, 60.4) 0.015 0.704 0.042 UC 11 51.6 (49.0, 54.2) 10 50.3 (47.6, 53.0) >0.999 10 53.4 (50.7, 56.2) >0.999 0.656 Intention to treat linear mixed modelling analysis; fixed factors: group, time, group × time; covariates: baseline variable score; random factors: participants. Abbreviations: FACIT, functional assessment of chronic illness therapy; INT, Intervention; MH, Mental health; PH, Physical health; SF-36, The Medical Outcomes Study 36-Item Short-Form Health Survey; TOI, trial outcome index (sum of physical, functional, and ‘additional concerns’ subscales); UC = usual care. All values are mean (95%CI). 1 Note higher scores = higher quality of life; for symptom scales (i.e., fatigue), higher scores = less symptoms. a Between group comparisons at 12 weeks. b Between group comparisons at 20 weeks. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Australian Institute of Health and Welfare Cancer in Australia 2019 AIHW Canberra, Australia 2019 2. Lu-Yao G.L. Albertsen P.C. Moore D.F. Shih W. Lin Y. DiPaola R.S. Yao S.-L. Fifteen-year survival outcomes following primary androgen-deprivation therapy for localized prostate cancer JAMA Intern. Med. 2014 174 1460 1467 10.1001/jamainternmed.2014.3028 25023796 3. Galvão D.A. Spry N.A. Taaffe D.R. Newton R.U. Stanley J. Shannon T. Rowling C. Prince R. Changes in muscle, fat and bone mass after 36 weeks of maximal androgen blockade for prostate cancer BJU Int. 2008 102 44 47 10.1111/j.1464-410X.2008.07539.x 18336606 4. van Londen G.J. Levy M.E. Perera S. Nelson J.B. Greenspan S.L. Body composition changes during androgen deprivation therapy for prostate cancer: A 2-year prospective study Crit. Rev. Oncol. Hematol. 2008 68 172 177 10.1016/j.critrevonc.2008.06.006 18706829 5. Hu J.-R. Duncan M.S. Morgans A.K. Brown J.D. Meijers W.C. Freiberg M.S. Salem J.-E. Beckman J.A. Moslehi J.J. Cardiovascular Effects of Androgen Deprivation Therapy in Prostate Cancer: Contemporary Meta-Analyses Arterioscler. Thromb. Vasc. Biol. 2020 40 e55 e64 10.1161/ATVBAHA.119.313046 31969015 6. Hackshaw-McGeagh L.E. Perry R.E. Leach V.A. Qandil S. Jeffreys M. Martin R. Lane J.A. A systematic review of dietary, nutritional, and physical activity interventions for the prevention of prostate cancer progression and mortality Cancer Causes Control 2015 26 1521 1550 10.1007/s10552-015-0659-4 26354897 7. Rock C.L. Doyle C. Demark-Wahnefried W. Meyerhardt J. Courneya K.S. Schwartz A.L. Bandera E.V. Hamilton K.K. Grant B. McCullough M. Nutrition and physical activity guidelines for cancer survivors CA Cancer J. Clin. 2012 62 242 274 10.3322/caac.21142 22539238 8. Barnes K.A. Ball L.E. Galvão D.A. Newton R.U. Chambers S.K. Nutrition care guidelines for men with prostate cancer undergoing androgen deprivation therapy: Do we have enough evidence? Prostate Cancer Prostatic Dis. 2019 22 221 234 10.1038/s41391-018-0099-9 30279584 9. Owen P.J. Daly R.M. Livingston P.M. Fraser S.F. Lifestyle guidelines for managing adverse effects on bone health and body composition in men treated with androgen deprivation therapy for prostate cancer: An update Prostate Cancer Prostatic Dis. 2017 20 137 145 10.1038/pcan.2016.69 28117386 10. Wallen M.P. Hennessy D. Brown S. Evans L. Rawstorn J.C. Wong Shee A. Hall A. High-intensity interval training improves cardiorespiratory fitness in cancer patients and survivors: A meta-analysis Eur. J. Cancer Care 2020 29 e13267 10.1111/ecc.13267 11. Mugele H. Freitag N. Wilhelmi J. Yang Y. Cheng S. Bloch W. Schumann M. High-intensity interval training in the therapy and aftercare of cancer patients: A systematic review with meta-analysis J. Cancer Surviv. 2019 13 205 223 10.1007/s11764-019-00743-3 30806875 12. Devin J.L. Sax A.T. Hughes G.I. Jenkins D. Aitken J. Chambers S.K. Dunn J. Bolam K.A. Skinner T. The influence of high-intensity compared with moderate-intensity exercise training on cardiorespiratory fitness and body composition in colorectal cancer survivors: A randomised controlled trial J. Cancer Surviv. 2016 10 467 479 10.1007/s11764-015-0490-7 26482384 13. MacInnis M.J. Gibala M.J. Physiological adaptations to interval training and the role of exercise intensity J. Physiol. 2017 595 2915 2930 10.1113/JP273196 27748956 14. Sofi F. Macchi C. Abbate R. Gensini G.F. Casini A. Mediterranean diet and health status: An updated meta-analysis and a proposal for a literature-based adherence score Public Health Nutr. 2014 17 2769 2782 10.1017/S1368980013003169 24476641 15. Kenfield S.A. DuPre N. Richman E.L. Stampfer M.J. Chan J.M. Giovannucci E.L. Mediterranean diet and prostate cancer risk and mortality in the Health Professionals Follow-up Study Eur. Urol. 2014 65 887 894 10.1016/j.eururo.2013.08.009 23962747 16. Itsiopoulos C. Hodge A. Kaimakamis M. Can the Mediterranean diet prevent prostate cancer? Mol. Nutr. Food Res. 2009 53 227 239 10.1002/mnfr.200800207 19051189 17. Bruno E. Krogh V. Gargano G. Grioni S. Bellegotti M. Venturelli E. Panico S. de Magistris M.S. Bonanni B. Zagallo E. Adherence to Dietary Recommendations after One Year of Intervention in Breast Cancer Women: The DIANA-5 Trial Nutrients 2021 13 2990 10.3390/nu13092990 34578868 18. Baguley B.J. Skinner T.L. Jenkins D.G. Wright O.R.L. Mediterranean-style dietary pattern improves cancer-related fatigue and quality of life in men with prostate cancer treated with androgen deprivation therapy: A pilot randomised control trial Clin. Nutr. 2021 40 245 254 10.1016/j.clnu.2020.05.016 32534948 19. Skouroliakou M. Grosomanidis D. Massara P. Kostara C. Papandreou P. Ntountaniotis D. Xepapadakis G. Serum antioxidant capacity, biochemical profile and body composition of breast cancer survivors in a randomized Mediterranean dietary intervention study Eur. J. Nutr. 2018 57 2133 2145 10.1007/s00394-017-1489-9 28634625 20. Martínez-González M.A. Gea A. Ruiz-Canela M. The Mediterranean Diet and Cardiovascular Health Circ. Res. 2019 124 779 798 10.1161/CIRCRESAHA.118.313348 30817261 21. Eldridge S.M. Chan C.L. Campbell M.J. Bond C.M. Hopewell S. Thabane L. Lancaster G.A. CONSORT 2010 statement: Extension to randomised pilot and feasibility trials BMJ 2016 355 i5239 10.1136/bmj.i5239 27777223 22. Baguley B.J. Skinner T.L. Leveritt M.D. Wright O.R. Nutrition therapy with high intensity interval training to improve prostate cancer-related fatigue in men on androgen deprivation therapy: A study protocol BMC Cancer 2017 17 1 10.1186/s12885-016-3022-6 28049525 23. American College of Sports Medicine ACSM’s new preparticipation health screening recommendations from ACSM’s guidelines for exercise testing and prescription, ninth edition. Practice Guideline Curr. Sports Med. Rep. 2013 12 215 217 10.1249/JSR.0b013e31829a68cf 23851406 24. Wasserman K. Hansen J. Sue D. Casaburi R. Whipp B. Principles of Exercise Testing and Interpretation: Including Pathophysiology and Clinical Applications Wolters Kluwer Health/Lippincott Williams & Wilkins Amsterdam, The Netherlands 2012 25. Borg G.A. Psychophysical bases of perceived exertion Med. Sci. Sports Exerc. 1982 14 377 381 10.1249/00005768-198205000-00012 7154893 26. American Association of Cardiovascular Pulmonary Rehabilitation Guidelines for Cardiac Rehabilitation and Secondary Prevention Programs Human Kinetics Champaign, IL, USA 2004 27. Stewart A. Marfell-Jones M. Olds T. De Ridder J.H. International Standards of Anthropometric Assessment ISAK Potchefstroom, South Africa 2011 28. Martínez-González M.A. García-Arellano A. Toledo E. Salas-Salvadó J. Buil-Cosiales P. Corella D. Covas M.I. Schröder H. Arós F. Gómez-Gracia E. A 14-item Mediterranean diet assessment tool and obesity indexes among high-risk subjects: The PREDIMED trial PLoS ONE 2012 7 e43134 10.1371/journal.pone.0043134 22905215 29. Yellen S.B. Cella D.F. Webster K. Blendowski C. Kaplan E. Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. Research Support, Non-U.S. Gov’t J. Pain Symptom Manag. 1997 13 63 74 10.1016/S0885-3924(96)00274-6 30. Ware J.E. Jr. Sherbourne C.D. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S Med. Care 1992 30 473 483 10.1097/00005650-199206000-00002 1593914 31. Martin G.S. The Interviewer-Administered, Open-Ended Diet History Method for Assessing Usual Dietary Intakes in Clinical Research: Relative and Criterion Validation Studies The University of Wollongong Wollongong, Australia 2004 32. Cella D. Eton D.T. Lai J.-S. Peterman A.H. Merkel D.E. Combining Anchor and Distribution-Based Methods to Derive Minimal Clinically Important Differences on the Functional Assessment of Cancer Therapy (FACT) Anemia and Fatigue Scales J. Pain Symptom Manag. 2002 24 547 561 10.1016/S0885-3924(02)00529-8 33. Godin G. Shephard R.J. A simple method to assess exercise behavior in the community Can. J. Appl. Sport Sci. 1985 10 141 146 4053261 34. Lakoski S.G. Willis B.L. Barlow C.E. Leonard D. Gao A. Radford N.B. Farrell S.W. Douglas P.S. Berry J.D. Defina L.F. Midlife Cardiorespiratory Fitness, Incident Cancer, and Survival After Cancer in Men: The Cooper Center Longitudinal Study JAMA Oncol. 2015 1 231 237 10.1001/jamaoncol.2015.0226 26181028 35. Bourke L. Smith D. Steed L. Hooper R. Carter A. Catto J. Albertsen P.C. Tombal B. Payne H.A. Rosario D.J. Exercise for Men with Prostate Cancer: A Systematic Review and Meta-analysis Eur. Urol. 2016 69 693 703 10.1016/j.eururo.2015.10.047 26632144 36. Kang D.-W. Fairey A.S. Boulé N.G. Field C.J. Wharton S.A. Courneya K.S. Effects of Exercise on Cardiorespiratory Fitness and Biochemical Progression in Men With Localized Prostate Cancer Under Active Surveillance: The ERASE Randomized Clinical Trial JAMA Oncol. 2021 7 1487 1495 10.1001/jamaoncol.2021.3067 34410322 37. Mohamad H. McNeill G. Haseen F. N’Dow J. Craig L.C. Heys S.D. The effect of dietary and exercise interventions on body weight in prostate cancer patients: A systematic review Nutr. Cancer 2015 67 43 60 10.1080/01635581.2015.976313 25425328 38. Toohey K. Pumpa K.L. Arnolda L. Cooke J. Yip D. Craft P.S. Semple S. A pilot study examining the effects of low-volume high-intensity interval training and continuous low to moderate intensity training on quality of life, functional capacity and cardiovascular risk factors in cancer survivors PeerJ 2016 4 e2613 10.7717/peerj.2613 27781180 39. Devin J.L. Jenkins D.G. Sax A.T. Hughes G.I. Aitken J. Chambers S.K. Dunn J. Bolam K.A. Skinner T. Cardiorespiratory Fitness and Body Composition Responses to Different Intensities and Frequencies of Exercise Training in Colorectal Cancer Survivors Clin. Colorectal Cancer 2018 17 e269 e279 10.1016/j.clcc.2018.01.004 29397328 40. Lavín-Pérez A.M. Collado-Mateo D. Mayo X. Liguori G. Humphreys L. Copeland R.J. Jiménez A. Effects of high-intensity training on the quality of life of cancer patients and survivors: A systematic review with meta-analysis Sci. Rep. 2021 11 15089 10.1038/s41598-021-94476-y 34301995 41. Baguley B.J. Bolam K.A. Wright O.R.L. Skinner T.L. The Effect of Nutrition Therapy and Exercise on Cancer-Related Fatigue and Quality of Life in Men with Prostate Cancer: A Systematic Review Nutrients 2017 9 1003 10.3390/nu9091003 28895922

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091124 animals-12-01124 Article The Prophylactic Effect of Ivermectin Treatments on Nematode Infections of Mammals in a Faunistic Park (Northern Italy) https://orcid.org/0000-0002-5741-4023 Zanzani Sergio A. 1* https://orcid.org/0000-0003-2013-3997 Villa Luca 1 https://orcid.org/0000-0003-4293-0719 Gazzonis Alessia L. 1 Cartagena Daniel 2 https://orcid.org/0000-0003-0216-0326 Mortarino Michele 1 Bonacina Eleonora 2 Guadagnini Davide 2 https://orcid.org/0000-0002-0780-3637 Allievi Carolina 1 https://orcid.org/0000-0002-9623-9475 Manfredi Maria Teresa 1 De Waal Theo Academic Editor 1 Department of Veterinary Medicine and Animal Sciences, Università Degli Studi di Milano, Via Dell’ Università 6, 26900 Lodi, Italy; luca.villa@unimi.it (L.V.); alessia.gazzonis@unimi.it (A.L.G.); michele.mortarino@unimi.it (M.M.); carolina.allievi@unimi.it (C.A.); mariateresa.manfredi@unimi.it (M.T.M.) 2 “Le Cornelle” Faunistic Park, Via Cornelle 16, 24030 Valbrembo, Italy; danielc94@hotmail.com (D.C.); bonacina@lecornelle.it (E.B.); oltolina@lecornelle.it (D.G.) * Correspondence: sergio.zanzani@unimi.it; Tel.: +39-02-5033-4536 27 4 2022 5 2022 12 9 112414 4 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary Nematode infections can pose a health risk to mammals housed in zoos and faunistic parks, where they live in environmental conditions far away from those of conspecifics in nature. To manage nematode infections, it is often necessary to adopt group prophylactic strategies by anthelmintic drugs. With the present study, it was possible to observe the effects of two prophylactic treatments with ivermectin adopted in a faunistic park in northern Italy and highlight the differences according to the different taxonomic groups of hosts and parasites. Abstract Nematode infections of mammals can spread in zoos and faunistic parks and lead to disease in humans and animals. Group treatment strategies with anthelminthic drugs are common. Still, their effectiveness should be verified by sensitive and specific copromicroscopic analyses. This study assessed longitudinal parasitological monitoring, by FLOTAC® dual technique, in mammals housed in an Italian faunistic park, in order to verify the effectiveness of the two adopted ivermectin prophylactic treatments. Twenty-one species of herbivorous mammals from ten families were treated twice per year with ivermectin in an in-feed formulation (medicated feed containing 1.7 g/ton ivermectin daily, for 30 days in March and November), while 13 species of carnivores and primates from five families were treated once a month with oral or subcutaneous administrations of ivermectin (200 μg/kg body weight (b.w.), from March to November). Fecal samples were collected in June–July and October 2019 (late spring–early summer and autumn sampling groups, respectively). All nematode infections, sustained by Nematodirus spp., Capillaria spp., Trichuris spp., Parascaris spp. and Strongylida, were detected in samples collected from herbivores, presenting prevalence rates of infection of 17.3% (9/52), 15.4% (8/52), 15.4% (8/52), 5.8% (3/52), and 3.8% (2/52), respectively. All carnivores and primates tested negative. The general linear mixed model showed that nematode eggs’ excretion in herbivores were influenced by sampling and sampling-host family interaction. Results showed that frequency and dose of prophylactic treatments in herbivores should be improved according to host and parasite taxonomic groups. The treatment adopted in carnivores and primates, together with hygienic management, was effective in nematode control. parasitological monitoring endoparasites zoo mammals nematode infections ivermectin FLOTAC This research received no external funding. ==== Body pmc1. Introduction Mammals housed in zoos and faunistic parks deal with environmental and crowding conditions distinct from those of their wild conspecifics, supporting widespread nematode infections based on direct life cycles [1,2,3]. In these hosts, both imported species–specific parasites and nonspecific parasites occur [4,5,6]. Generally, nematode infections are asymptomatic in captive mammals; however, they can determine serious diseases or favor the onset of other pathologies [7,8,9,10,11]. Furthermore, a few nematode species that infect carnivores and primates can pose a risk to human health [12,13]. The control of parasitic nematodes in zoos and faunistic parks requires proper hygienic management, biosecurity plans, and group treatment strategies [14,15]. Among antiparasitic drugs, ivermectin, a macrocyclic lactone, is widely used in zoos and faunistic parks to control circulation of both nematodes and ectoparasites [16,17]. Its effectiveness has been verified in several species of mammals housed in zoos [18,19,20,21,22]. Despite its extensive use in such animals, few studies have monitored the effects of prophylactic treatments on the infection prevalence or egg fecal excretion by parasitic nematodes over time. The present study aimed to evaluate the effects of two different strategies, based on prophylactic treatments with ivermectin, to control endoparasitic infection in two groups of zoo mammals. Therefore, a longitudinal parasitological monitoring method was planned in selected species of mammals housed in a faunistic park sited in northern Italy. 2. Materials and Methods The study was carried out in a faunistic park sited in northern Italy (Latitude: 45°43′0.94″ N; Longitude: 9°35′50.16″ E) that housed 39 mammal species, in addition to 8 and 28 species of reptiles and birds, respectively. To control the circulation of endo- and ectoparasites, many mammals underwent prophylactic treatment with ivermectin according to their mammal groups [16]. Herbivores were treated twice/year (in March and November), daily for 15 days, with an in-feed ivermectin formulation (Ivomec® Premix, Boehringer Ingelheim Animal Health Italia S.p.A, Milan, Italy). The medicated feed, administered ad libitum and containing 1.7 q/ton of Ivomec® Premix (~10 g/ton ivermectin [19]), was produced for the faunistic park by a commercial feed mill (Agricola Italiana Alimentare S.p.A, Quinto di Valpantena, Italy). Carnivores and primates were treated once a month, from March to November, with oral or subcutaneous administrations of ivermectin (200 μg/kg b.w.; Ivomec®, Boehringer Ingelheim Animal Health Italia S.p.A, Milano, Italy), depending on animal behavior/compliance and operators’ safety. Thisparasitological study included 21 species of herbivores and 13 species of carnivores and primates. A comparison was made between these two prophylactic treatments because they involved most of the terrestrial mammals present in the faunistic park. Other species received targeted treatments for specific needs [23]. Individual or pooled fecal samples from these hosts were collected according to their housing (individual or in group); for grouped animals, single fecal masses were collected in plastic bags and pools were formed afterwards. Sampling was carried out in the morning with the assistance of animal keepers; cages, boxes, and enclosures where animals spent the night were cleaned the evening before sampling to ensure collection of fresh fecal samples. For both host groups, two samplings were performed from the second half of June through the first half of July 2019 (late spring–early summer sampling group) and in October 2019 (autumn sampling group). Overall, 52 (46 pooled samples and 6 individual samples) and 32 (28 pooled samples and 4 individual samples) fecal samples were collected from 153 herbivorous mammals and 28 carnivores and primates, respectively (Table 1 and Table 2). Animals that contributed to producing a certain pooled fecal sample were the same in both samplings. Carnivore and primate fecal samples were all negatives in both samplings (Table 2). Fecal samples were refrigerated and quantitative copromicroscopic exams were performed within 48 h by FLOTAC® dual technique with an analytic sensitivity of two eggs/larvae/oocysts per gram (EPG/LPG/OPG) of feces [24,25,26]. To obtain pooled samples from grouped animals, the same amount of feces (possibly at least 5 g, depending on species size) was used from each fecal mass of the group, and pooled feces were homogenized according to the FLOTAC® user manual. The flotation solutions FS2 (NaCl; s.g. = 1200) and FS7 (ZnSO4; s.g. = 1350)—useful for the detection of nematode, cestode and trematode eggs, nematode larvae and coccidian oocysts—were employed to process all the collected samples. The percentage of samples testing positive for nematode eggs was calculated and then compared in herbivores treated twice/year and in carnivores and primates treated monthly by chi-square test. To identify any association between nematode eggs’ excretion and selected variables, logarithmically transformed nematode EPG values (Log(EPG+1)) of each sample were introduced as the dependent variable in a generalized linear mixed model (GLMM) with repeated measures. Host family, time of sampling (late spring–early summer vs. autumn), and their interaction were introduced as independent categorical variables in the model. The identity of each fecal sample was included as a random intercept effect. The final model was determined by backward elimination of nonsignificant variables (p ≥ 0.05) and best corrected Akaike information criteria (AIC). Statistical analyses were implemented by SPSS 20.0 (IBM, Chicago, IL, USA). 3. Results Out of 84 fecal samples, 23 (27.4%, 95% Confidence Interval (CI): 18.2–38.2) were positive for at least one parasite taxon. Nematode larvae and cestode and trematode eggs were not found in any samples. The percent positivity was higher in autumn sampling (33.3%, 95% CI: 19.6–49.6; 14/42) than the late spring–early summer sampling (21.4%, 95% CI: 10.3–36.8; 9/42). In herbivores, the percentage of positivity was 40.4% (95% CI: 27–54.9; 21/52; Table 1). This differences in the percentage of infections were highly significant when compared by chi-square test (Pearson’s chi-square = 17.231; p-value = 0.00003). In herbivores, the following taxa were identified in fecal samples: Nematodirus spp. (17.3%, 95% CI: 8.2–30.3; 9/52), Capillaria spp. (15.4%, 95% CI: 6.8–28.1; 8/52), Trichuris spp. (15.4%, 95% CI: 6.8–28.1; 8/52), Parascaris spp. (5.8%, 95% CI: 1.2–16; 3/52), and Strongylida (3.8%, 95% CI: 0.5–13.2; 2/52). EPG values in positive samples ranged from two to 578. Eimeria spp. oocysts were also detected (13.5%, 95% CI: 5.6–25.8; 7/52) (Table 1). Since carnivores and primates all tested negative, GLMM was only implemented for copromicroscopic data from herbivores. In the final model, time of sampling and interaction time of sampling × host family were significant predictors of the logarithmically-transformed nematode EPG (Table 3). Values of logarithmically-transformed nematode EPG estimated by the model were significantly higher in the autumn sampling than the late spring–early summer sampling (p-value < 0.01) (Figure 1). Estimated nematode Log(EPG+1) of the two sampling points also differed by host family; pairwise comparisons showed significant differences between the two sampling points in two out of 10 herbivores families (Figure 2). Particularly, in Bovidae family, estimated Log(EPG+1) were 0.28 and 0.84 in late spring–early summer and autumn samplings, respectively (p < 0.01); in Equidae family, estimated Log(EPG+1) were 0 and 2.67 in late spring–early summer and autumn samplings, respectively (p < 0.001). 4. Discussion In the studied faunistic park, 181 mammals belonging to 15 different families received an anthelmintic prophylactic treatment with ivermectin. Nematode infections were detected only in herbivores that received a twice/year prophylactic treatment with an in-feed ivermectin formulation, while the carnivores and primates that received a monthly prophylactic treatment from March to November were negative in both samplings. Moreover, the implemented GLMM showed that the overall nematode eggs’ excretion increased in the autumn sampling. In herbivores, Strongylida eggs were identified only in two samples, and the egg excretion detected was very low. The circulation of these parasites seemed to be lower when compared to other Italian and European studies [1,2,27,28,29]. However, they were similar to what was observed by Pérez Cordon et al. [30] in a Spanish zoological garden, where Strongylida were not found; management and prophylactic treatments administered in the studied faunistic park seemed to be effective at controlling the circulation of gastrointestinal strongyles. As regards the other detected nematode taxa (Nematodirus spp., Capillaria spp., Trichuris spp., Parascaris spp.), all of them showed higher percentages of infection and EPG values than Strongylida. The reasons why these parasites circulated more than Strongylida could be different. First, environmental resistance to parasites’ free-living stages in paddocks with scarce grass cover must be considered. It could be hypothesized that, during the 30 days of prophylactic treatment with the in-feed ivermectin formulation, free-living stages of Strongylida did not find environmental conditions sufficient to survive and reinfect hosts, even if the prophylactic treatment was interrupted [31]. On the other hand, eggs of Nematodirus spp., Capillaria spp., Trichuris spp., and Parascaris spp., all having higher environmental resistance, probably persisted longer in the soil. To control the circulation of these parasite genera with resistant eggs, a more frequent administration or the use of anthelmintic formulations less prone to underdosing (e.g., oral or pour-on solutions for individual treatment) could be needed, together with suitable management strategies aiming to reduce soil contamination. Furthermore, data obtained in this study suggested that the anthelmintic efficacy of the prophylactic treatment should be specifically investigated for some nematode taxa in certain host species by fecal egg count reduction test (FECRT), following the World Association for the Advancement of Veterinary Parasitology guidelines [32,33]. Considering Parascaris spp. infections in Equidae, we postulated that the March ivermectin prophylaxis was effective without performing an FECRT. In fact, despite the presence of the parasite in the faunistic park, the three late spring–early summer fecal samples collected from Equus quagga tested negative (0 EPG) for nematodes within the 3-month prepatent period [34]. After this period, reinfections by embryonated eggs in soil determined the results of the autumn sampling; all samples tested positive for Parascaris spp., presenting an average value of 587 EPG. On the contrary, the late spring–early summer sampling fell outside (or borderline to) the prepatent period of Nematodirus spp., Capillaria spp. and Trichuris spp. Thus, without performing a rigorous FECRT, it was impossible to say whether samples tested positive for reinfection or it was a lack of efficacy of the treatment. It should also be considered that certain genera or species of parasites can represent the limiting taxonomic group for the dosage of an anthelmintic active ingredient [35]; therefore, the effectiveness of this prophylaxis should be tested on each one. However, the results of GLMM suggested that there was at least a partial efficacy of the treatment against these parasites. In fact, starting from a lower EPG level of the late spring–early summer sampling, closer to the March prophylactic treatment, the nematode EPG increased for reinfections in the autumn sampling. It is probable that the effects of prophylactic treatments against nematode circulation in the herbivores housed in the faunistic park could depend, not only on parasites’ life cycle or their susceptibility to drugs, but also on the host species. Indeed, the implemented GLMM showed that seasonal increases in nematode eggs excretion differed by host family. This result could have several explanations. First of all, different hosts may have different susceptibility to parasites able to circulate within the studied faunistic park. Indeed, Elephantidae, Hippopotamidae, Macropodidae, Rhinocerotidae, and Tapiridae were not suitable hosts for the Nematodirus spp., Capillaria spp., and Trichuris spp. that infected other animals housed in the park [36,37,38,39]. A few differences could also be attributed to physiology and metabolism between infected hosts. In domestic ruminants, it is well known that the detoxifying capacities toward xenobiotics are more significant in goats than in sheep, as a consequence of their feeding behavior [40]. The same could apply to herbivores housed in faunistic parks. In nature, Giraffidae are considered general browsers [41] and are probably more exposed to plant toxins. For these animals, the absence of a significant difference in nematode EPG between the late spring–early summer and autumn samplings could be due to the rapid detoxification of the administered ivermectin. Therefore, administration of specific dosages of anthelmintics should be further evaluated in different taxonomic groups of herbivores housed in faunistic parks, as required for goats when compared with sheep [42]. Possible underdosing due to both parasite (limiting taxonomic group for the dosage of an active anthelmintic ingredient) and host features could also determine the development of anthelmintic resistance, mainly when only one anthelminthic family is repeatedly used for treatments. The alternated or combined use of other anthelmintics (i.e., fenbendazole), belonging to different families, could be useful to slow down resistance development [43]. Nematode infections were not detected in any samples collected from carnivores and primates treated monthly with oral or subcutaneous ivermectin. Thus, this prophylactic treatment seemed to be particularly effective at controlling nematode circulation in the studied faunistic park. In other European studies, carnivores and primates of faunistic parks were infected by several nematode taxa (i.e., Toxocara spp., Toxascaris spp., Ancylostoma spp., Uncinaria spp., Strongyloides spp., Ascaris spp., Enterobius spp., Trichuris spp., Strongylida), often of zoonotic concern [1,2,3,24,26]. Proper management and prophylactic treatments are highly recommended to avoid circulation of those nematodes that pose a risk to animal and human health. The parasitological monitoring carried out in the present study was not without limits. We were unable to determine with certainty the efficacy of the prophylactic treatments against all the parasitological taxa detected. In the future, it would be advisable to verify their effectiveness by FECRT. Furthermore, the parasitological negativity observed in carnivores and primates should be confirmed in the winter period, during which they do not receive the prophylactic treatment. 5. Conclusions Circulation of nematodes in zoos and faunistic park poses a risk for the health of humans and animals. Results obtained in the present study showed that parasitological monitoring of animals housed in faunistic parks could provide both information on the efficacy of prophylactic treatments adopted and indications to limit or avoid parasite circulation. Considering the low EPG/OPG excretion detected in several samples in the present survey, parasitological monitoring should be conducted with sensitive and specific techniques, to collect the most detailed information possible. Efficacy of the adopted hygiene management and prophylactic treatments should be verified, both to further reduce the risk of nematode infection and to calibrate anthelmintic drug administration. Unsatisfactory protocols for frequency and dosage should be improved, and the use of more than one pharmacological family could be considered. Effective control of zoonotic nematodes is important; thus, methods to increase the effectiveness of available treatments should be considered. Acknowledgments We are grateful to Le Cornelle Faunistic Park for permitting and supporting the activities necessary to perform the present study. Author Contributions Conceptualization, S.A.Z., L.V. and M.M.; methodology, S.A.Z., L.V., A.L.G. and D.C.; software, S.A.Z. and A.L.G.; formal analysis, D.C., E.B., D.G. and C.A.; data curation, S.A.Z. and A.L.G.; writing—original draft preparation, S.A.Z. and M.T.M.; writing—review and editing, L.V., A.L.G., M.M. and C.A.; supervision, M.T.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical review and approval were waived for this study since the samples were collected after spontaneous defecation, without any animal handling or constraint. Informed Consent Statement Not applicable. Data Availability Statement The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Estimated nematode Log(EPG+1), by time of sampling, in herbivores housed in the studied faunistic park obtained by a generalized linear mixed model. Vertical bars: 95% confidence intervals; horizontal black bar: pairwise comparison between nematode eggs excretion in the two sampling points. Figure 2 Estimated nematode Log(EPG+1) by host family and time of sampling in herbivores housed in the studied faunistic park, obtained by a generalized linear mixed model. Vertical bars: 95% confidence intervals; horizontal black bar: significant pairwise comparison between nematode eggs excretion in the two samplings by family; n.s.: not significant. animals-12-01124-t001_Table 1 Table 1 Endoparasites detected by quali/quantitative copromicroscopic analyses (FLOTAC® dual technique) in herbivores from a faunistic park in northern Italy. When more than one sample for species is tested, EPG/OPG is the mean value. Family Species N. of Animals N. of Fecal Samples 1st Sampling (Late Spring/Early Summer) 2nd Sampling (Autumn) N. of Positives/Sampled Detected Parasites (EPG/OPG) N. of Positives/Sampled Detected Parasites (EPG/OPG) Bovidae Antilope cervicapra 10 1 1/1 Nematodirus spp. (20) 1/1 Nematodirus spp. (26) Kobus leche 10 1 0/1 --(0) 0/1 --(0) Kobus megaceros 11 1 0/1 --(0) 0/1 --(0) Oryx dammah 4 1 1/1 Eimeria spp. (126) 1/1 Strongylida (2) Capillaria spp. (32) Eimeria spp. (244) Ovis aries 20 1 1/1 Nematodirus spp. (4) Eimeria spp. (46) 1/1 Trichuris spp. (8) Eimeria spp. (134) Taurotragus oryx 2 1 0/1 --(0) 0/1 --(0) Tragelaphus eurycerus 3 2 1/2 Capillaria spp. (5) 2/2 Capillaria spp. (46) Tragelaphus spekii 7 1 0/1 --(0) 1/1 Capillaria spp. (8) Camelidae Camelus bactrianus 3 1 1/1 Strongylida (2) Nematodirus spp. (4) Trichuris spp. (110) Eimeria spp. (14) 1/1 Trichuris spp. (578) Eimeria spp. (112) Lama glama 3 1 0/1 --(0) 1/1 Nematodirus spp. (8) Vicugna pacos 3 1 0/1 --(0) 0/1 --(0) Cavidae Cavia porcellus 40 1 1/1 Eimeria spp. (40) 0/1 --(0) Dolichotis patagonum 5 1 1/1 Capillaria spp. (44) 1/1 Capillaria spp. (142) Trichuris spp. (2) Elephantidae Elaphas maximus 2 2 0/1 --(0) 0/1 --(0) Equidae Equus quagga 5 3 0/3 --(0) 3/3 Parascaris spp. (587) Giraffidae Giraffa camelopardalis 7 2 2/2 Nematodirus spp. (64) Trichuris spp. (6) 2/2 Nematodirus spp. (5) Capillaria spp. (1) Trichuris spp. (50) Hippopotamidae Hippopotamus amphibius 3 1 0/1 --(0) 0/1 --(0) Macropodidae Macropus rufogriseus 6 1 0/1 --(0) 0/1 --(0) Macropus rufus 5 1 0/1 --(0) 0/1 --(0) Rhinocerotidae Diceros bicornis 3 1 0/1 --(0) 0/1 --(0) Tapiridae Tapirus terrestris 1 1 0/1 --(0) 0/1 --(0) TOTAL 153 26 9/26 -- 14/26 -- N. = number. animals-12-01124-t002_Table 2 Table 2 Endoparasites detected by quali/quantitative copromicroscopic analyses (FLOTAC® dual technique) in carnivores and primates from a faunistic park in northern Italy. Family Species N. of Animals N. of Fecal Samples 1st Sampling (Late Spring/Early Summer) 2nd Sampling (Autumn) N. of Positives/Sampled Detected Parasites (EPG/OPG) N. of Positives/Sampled Detected Parasites (EPG/OPG) Cebidae Saguinus oedipus 4 1 0/1 --(0) 0/1 --(0) Saimiri sciureus 4 1 0/1 --(0) 0/1 --(0) Felidae Neofelis nebulosa 2 1 0/1 --(0) 0/1 --(0) Panthera leo 2 1 0/1 --(0) 0/1 --(0) Panthera pardus 2 1 0/3 --(0) 0/3 --(0) Panthera tigris 3 3 0/3 --(0) 0/3 --(0) Panthera uncia 2 1 0/1 --(0) 0/ --(0) Puma concolor 1 1 0/1 --(0) 0/1 --(0) Hyaenidae Hyaena hyaena 1 1 0/1 --(0) 0/1 --(0) Hylobatidae Hylobates lar 6 1 0/1 --(0) 0/1 --(0) Symphalangus syndactylus 5 2 0/2 --(0) 0/2 --(0) Lemuridae Lemur catta 6 1 0/1 --(0) 0/1 --(0) Varecia variegata 3 1 0/1 --(0) 0/1 --(0) TOTAL 28 16 0/16 -- 0/16 -- N. = number. animals-12-01124-t003_Table 3 Table 3 Effect of selected risk factors on nematode fecal egg count (logarithmically transformed) in herbivores housed in the studied faunistic park, obtained by a generalized linear mixed model. In bold: significant predictors of Log(EPG+1). Independent Variables F Degrees of Freedom p-Value Time of sampling 9.566 1 0.004 Host family 0.698 9 0.706 Time of sampling × host family 5.068 9 <0.0005 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Panayotova-Pencheva M.S. Parasites in Captive Animals: A Review of Studies in Some European Zoos Zool. Gart. 2013 82 60 71 10.1016/j.zoolgart.2013.04.005 2. Dǎrǎbuş G. Afrenie M. Hotea I. Imre M. Morariu S. Endoparasites in mammals from seven zoological gardens in Romania J. Zoo Wildl. Med. 2014 45 239 246 10.1638/2012-0170.1 25000683 3. Kvapil P. Kastelic M. Dovc A. Bártová E. Cížek P. Lima N. Štrus S. An eight-year survey of the intestinal parasites of carnivores, hoofed mammals, primates, ratites and reptiles in the Ljubljana zoo in Slovenia Folia Parasitol. 2017 64 13 10.14411/fp.2017.013 28443822 4. Rendón-Franco E. Romero-Callejas E. Villanueva-García C. Osorio-Sarabia D. Muñoz-García C.I. Cross transmission of gastrointestinal nematodes between captive neotropical felids and feral cats J. Zoo Wildl. Med. 2013 44 936 940 10.1638/2013-0015R2.1 24450052 5. Gillis-Germitsch N. Manser M.B. Hilbe M. Schnyder M. Meerkats (Suricata suricatta), a new definitive host of the canid nematode Angiostrongylus Vasorum Int. J. Parasitol. Parasites Wildl. 2017 6 349 353 10.1016/j.ijppaw.2017.10.002 29379713 6. Montalbano Di Filippo M. Berrilli F. De Liberato C. Di Giovanni V. D’Amelio S. Friedrich K.G. Cavallero S. Molecular characterization of Trichuris spp. from captive animals based on mitochondrial markers Parasitol. Int. 2020 75 102043 10.1016/j.parint.2019.102043 31881362 7. Patterson-Kane J.C. Gibbons L.M. Jefferies R. Morgan E.R. Wenzlow N. Redrobe S.P. Pneumonia from Angiostrongylus vasorum infection in a red panda (Ailurus fulgens fulgens) J. Vet. Diagn. Investig. 2009 21 270 273 10.1177/104063870902100219 19286513 8. Eleni C. Di Cesare A. Cavicchio P. Tonnicchia M.C. Meoli R. di Regalbono A.F. Paoletti B. Pietrobelli M. De Liberato C. Fatal Angiostrongylus dujardini infection in callitrichid monkeys and suricates in an Italian zoological garden Parasitol. Int. 2016 65 333 335 10.1016/j.parint.2016.04.005 27094227 9. Emikpe B.O. Morenikeji O.A. Jarikre T.A. Zoo animals’ disease pattern in a university zoological garden, Ibadan, Nigeria Asian Pac. J. Trop. Dis. 2016 6 85 89 10.1016/S2222-1808(15)60991-4 10. Eo K.-Y. Seo M.-G. Lee H.-H. Jung Y.-M. Kwak D. Kwon O.-D. Severe whipworm (Trichuris spp.) infection in the hamadryas baboon (Papio hamadryas) J. Vet. Med. Sci. 2019 81 53 56 10.1292/jvms.17-0568 30464076 11. Kumar R. Moudgil A.D. Sharma A. Sharma R. Masand R. Patil R.D. Asrani R.K. Concurrent helminthosis engendered gastroenteritis in a leopard Panthera pardus Helminthologia 2019 56 323 328 10.2478/helm-2019-0031 31708673 12. Lim Y.A.L. Ngui R. Shukri J. Rohela M. Mat Naim H.R. Intestinal parasites in various animals at a zoo in Malaysia Vet. Parasitol. 2008 157 154 159 10.1016/j.vetpar.2008.07.015 18723289 13. Li M. Zhao B. Li B. Wang Q. Niu L. Deng J. Gu X. Peng X. Wang T. Yang G. Prevalence of gastrointestinal parasites in captive non-human primates of twenty-four zoological gardens in China J. Med. Primatol. 2015 44 168 173 10.1111/jmp.12170 25851745 14. Reiss A.E. Woods R.W. National Zoo Biosecurity Manual Commonwealth of Australia: Department of Agriculture, Fisheries and Forestry Canberra, Australia 2011 64p 15. Delk K.W. Molter C.M. Group Treatment Strategies for Animals in a Zoologic Setting Vet. Clin. N. Am. Exot. Anim. Pract. 2018 21 297 309 10.1016/j.cvex.2018.01.007 16. Panayotova-Pencheva M.S. Experience in the Ivermectin Treatment of Internal Parasites in Zoo and Captive Wild Animals: A Review [Ivermectin-Behandlung von Endoparasiten bei Wildtieren in Menschenobhut: Eine Übersicht] Zool. Gart. 2016 85 280 308 10.1016/j.zoolgart.2016.04.001 17. Moreno Mañas E. Gonzálvez Juan M. Ruiz De Ybáñez Carnero M.D.R. Gilbert T. Ortiz J. Espeso G. Benzal J. Ibáñez B. Valera Hernández F. Survey of husbandry practices for bovidae in zoos: The importance of parasite management for reintroduction programmes Vet. Rec. 2019 184 282 10.1136/vr.104985 30819861 18. Sahoo N. Roy P.K. Samantaray R.K. Das A. Dehuri M. Bharati K.M.N. Therapeutic efficacy of antinematodal drugs in tigers Indian Vet. J. 2010 87 346 347 19. Lia R.P. Traversa D. Laricchiuta P. Dantas-Torres F. Paradies R. Alvinerie M. Krecek R.C. Otranto D. Efficacy of an in-feed formulation containing ivermectin for the control of intestinal strongyles in captive zebras (Equus burchelli (Gray, 1824)) Vet. Parasitol. 2010 169 133 137 10.1016/j.vetpar.2009.12.028 20071086 20. Kim K.-T. Lee S.-H. Kwak D. Sarcoptic mange in captive maras: The first known outbreak and complete recovery with colony-wide acaricide treatment J. Vet. Med. Sci. 2015 77 593 595 10.1292/jvms.14-0560 25648673 21. Kleinschmidt L.M. Kinney M.E. Hanley C.S. Treatment of disseminated Strongyloides spp. infection in an infant Sumatran orangutan (Pongo abelii) J. Med. Primatol. 2018 47 201 204 10.1111/jmp.12338 29493782 22. Moudgil A.D. Singla L.D. Molecular confirmation and anthelmintic efficacy assessment against natural trichurid infections in zoo-housed non-human primates J. Med. Primatol. 2018 47 388 392 10.1111/jmp.12358 29979810 23. Bagardi M. Rabbogliatti V. Bassi J. Gioeni D. Oltolina M. Villa L. Angiostrongylus vasorum in a Red Panda (Ailurus fulgens): Clinical Diagnostic Trial and Treatment Protocol Acta Parasitol. 2021 66 282 286 10.1007/s11686-020-00271-6 32840714 24. Cringoli G. Rinaldi L. Maurelli M.P. Utzinger J. FLOTAC: New multivalent techniques for qualitative and quantitative copromicroscopic diagnosis of parasites in animals and humans Nat. Protoc. 2010 5 503 515 10.1038/nprot.2009.235 20203667 25. Rinaldi L. Amadesi A. Dufourd E. Bosco A. Gadanho M. Lehebel A. Maurelli M.P. Chauvin A. Charlier J. Cringoli G. Rapid assessment of faecal egg count and faecal egg count reduction through composite sampling in cattle Parasites Vectors 2019 12 353 10.1186/s13071-019-3601-x 31311591 26. Lima V.F.S. Cringoli G. Rinaldi L. Monteiro M.F.M. Calado A.M.C. Ramos R.A.N. Meira-Santos P.O. Alves L.C. A comparison of mini-FLOTAC and FLOTAC with classic methods to diagnosing intestinal parasites of dogs from Brazil Parasitol. Res. 2015 114 3529 3533 10.1007/s00436-015-4605-x 26122998 27. Fagiolini M. Lia R.P. Laricchiuta P. Cavicchio P. Mannella R. Cafarchia C. Otranto D. Finotello R. Perrucci S. Gastrointestinal parasites in mammals of two Italian zoological gardens J. Zoo Wildl. Med. 2010 41 662 670 10.1638/2010-0049.1 21370648 28. Maesano G. Capasso M. Ianniello D. Cringoli G. Rinaldi L. Parasitic infections detected by FLOTAC in zoo mammals from Warsaw, Poland Acta Parasitol. 2014 59 343 353 10.2478/s11686-014-0249-8 24827109 29. Capasso M. Maurelli M.P. Ianniello D. Alves L.C. Amadesi A. Laricchiuta P. Silvestre P. Campolo M. Cringoli G. Rinaldi L. Use of Mini-FLOTAC and Fill-FLOTAC for rapidly diagnosing parasitic infections in zoo mammals [Utilização do Mini-FLOTAC e Fill-FLOTAC no diagnóstico rápido de infecções parasitárias de mamíferos em zoológicos] Rev. Bras. Parasitol. Vet. 2019 28 168 171 10.1590/s1984-296120180087 30785552 30. Pérez Cordón G. Hitos Prados A. Romero D. Sánchez Moreno M. Pontes A. Osuna A. Rosales M.J. Intestinal parasitism in the animals of the zoological garden “Peña Escrita” (Almuñecar, Spain) Vet. Parasitol. 2008 156 302 309 10.1016/j.vetpar.2008.05.023 18639383 31. Manfredi M.T. Biomorfologia dei nematodi gastrointestinali dei piccoli ruminanti Parassitologia 2006 48 397 402 17176950 32. Levecke B. Dobson R.J. Speybroeck N. Vercruysse J. Charlier J. Novel insights in the fecal egg count reduction test for monitoring drug efficacy against gastrointestinal nematodes of veterinary importance Vet. Parasitol. 2012 188 391 396 10.1016/j.vetpar.2012.03.020 22521979 33. Coles G.C. Bauer C. Borgsteede F.H.M. Geerts S. Klei T.R. Taylor M.A. Waller P.J. World Association for the Advancement of Veterinary Parasitology (W.A.A.V.P.) methods for the detection of anthelmintic resistance in nematodes of veterinary importance Vet. Parasitol. 1992 44 35 44 10.1016/0304-4017(92)90141-U 1441190 34. Taylor M.A. Coop R.L. Wall R.L. Veterinary Parasitology Wiley-Blackwell Hoboken, NJ, USA 2015 35. Jones R.M. Logan N.B. Weatherley A.J. Little A.S. Smothers C.D. Activity of doramectin against nematode endoparasites of cattle Vet. Parasitol. 1993 49 27 37 10.1016/0304-4017(93)90220-H 8236735 36. Abhijith T.V. Ashokkumar M. Dencin R.T. George C. Gastrointestinal parasites of Asian elephants (Elephas maximus L. 1798) in south Wayanad forest division, Kerala, India J. Parasit. Dis. 2018 42 382 390 10.1007/s12639-018-1012-0 30166785 37. Cripps J.K. Martin J.K. Coulson G. Anthelmintic Treatment Does Not Change Foraging Strategies of Female Eastern Grey Kangaroos, Macropus giganteus PLoS ONE 2016 11 e0147384 10.1371/journal.pone.0147384 26784582 38. Stringer A.P. Parasite Ecology and the Conservation Biology of Black Rhinoceros (Diceros bicornis) Ph.D. Thesis Open Access Te Herenga Waka-Victoria University of Wellington Wellington, New Zealand 2016 10.26686/wgtn.17019254.v1 39. Navas-Suárez P.E. Díaz-Delgado J. Fernandes-Santos R.C. Testa-José C. Silva R. Sansone M. Medici E.P. Catão-Dias J.L. Pathological Findings in Lowland Tapirs (Tapirus terrestris) Killed by Motor Vehicle Collision in the Brazilian Cerrado J. Comp. Pathol. 2019 170 34 45 10.1016/j.jcpa.2019.05.004 31375157 40. Hoste H. Sotiraki S. Landau S.Y. Jackson F. Beveridge I. Goat-Nematode interactions: Think differently Trends Parasitol. 2010 26 376 381 10.1016/j.pt.2010.04.007 20488752 41. Berry P.S.M. Bercovitch F.B. Seasonal and geographical influences on the feeding ecology of giraffes in the Luangwa Valley, Zambia: 1973–2014 Afr. J. Ecol. 2017 55 80 90 10.1111/aje.12324 42. Silvestre A. Leignel V. Berrag B. Gasnier N. Humbert J.-F. Chartier C. Cabaret J. Sheep and goat nematode resistance to anthelmintics: Pro and cons among breeding management factors [Résistance aux anthelminthiques des nématodes de chèvres et de moutons: Le rôle du mode d’élevage] Vet. Res. 2002 33 465 480 10.1051/vetres:2002033 12387484 43. Kaplan R.M. Biology, Epidemiology, Diagnosis, and Management of Anthelmintic Resistance in Gastrointestinal Nematodes of Livestock Vet. Clin. N. Am. Food Anim. Pract. 2020 36 17 30 10.1016/j.cvfa.2019.12.001

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093498 sensors-22-03498 Article Enhancing Cyber Security of LoRaWAN Gateways under Adversarial Attacks Mohamed Ali 1 https://orcid.org/0000-0003-3905-7437 Wang Franz 1 https://orcid.org/0000-0002-1723-5741 Butun Ismail 123* https://orcid.org/0000-0002-8456-8458 Qadir Junaid 34 https://orcid.org/0000-0003-3089-3885 Lagerström Robert 3 https://orcid.org/0000-0002-5748-3942 Gastaldo Paolo 4 https://orcid.org/0000-0002-2145-1869 Caviglia Daniele D. 4 Vasilakos Athanasios V. Academic Editor 1 Department of Computer Science and Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden; almoha@student.chalmers.se (A.M.); wfranz@student.chalmers.se (F.W.) 2 Department of Computer Engineering, Konya Food and Agriculture University, Konya 42080, Turkey 3 Department of Electrical Engineering and Computer Science, KTH Royal University of Technology, SE-100 44 Stockholm, Sweden; junaidq@kth.se or robertl@kth.se (R.L.) 4 Department of Electrical, Electronic and Telecommunications Engineering and Naval Architecture (DITEN), University of Genoa, 16145 Genoa, Italy; paolo.gastaldo@unige.it (P.G.); daniele.caviglia@unige.it (D.D.C.) * Correspondence: butun@kth.se 04 5 2022 5 2022 22 9 349811 3 2022 30 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The Internet of Things (IoT) has disrupted the IT landscape drastically, and Long Range Wide Area Network (LoRaWAN) is one specification that enables these IoT devices to have access to the Internet. Former security analyses have suggested that the gateways in LoRaWAN in their current state are susceptible to a wide variety of malicious attacks, which can be notoriously difficult to mitigate since gateways are seen as obedient relays by design. These attacks, if not addressed, can cause malfunctions and loss of efficiency in the network traffic. As a solution to this unique problem, this paper presents a novel certificate authentication technique that enhances the cyber security of gateways in the LoRaWAN network. The proposed technique considers a public key infrastructure (PKI) solution that considers a two-tier certificate authority (CA) setup, such as a root-CA and intermediate-CA. This solution is promising, as the simulation results validate that about 66.67% of the packets that are arriving from an illegitimate gateway (GW) are discarded in our implemented secure and reliable solution. cybersecurity LoRaWAN security vulnerabilities gateway attacks authentication KTH Royal Institute of Technology, SwedenThis research is supported by KTH Royal Institute of Technology, Sweden. ==== Body pmc1. Introduction The large pool of the Internet of Things (IoT) paradigm enables an extensive research community in industry and academia. IoT devices are being utilized in various applications at the domestic and industrial levels: for instance, they can find applications in machine-to-machine (M2M) communication, tactical surveillance, smart city, and smart grid. IoT devices rely on wireless communication including Bluetooth, ZigBee, WiFi, and NB-IoT [1]. However, such technologies are not able for long-distance communication. Therefore, LoRaWAN [2] was recently introduced as a promising technology that provides communication over long distances with the price of low data rates. LoRa is a proprietary physical layer protocol developed by Semtech Inc., Camarillo, CA, USA, which provides very long distance communication (20 km) over extremely low power consumption. LoRa makes use of a special modulation known as the Chirp Spread Spectrum (CSS) technique that may offer long-lasting communication (up to 10 years), even for a small battery (1.5V-AA). LoRa-based devices operate on industrial, scientific and medical (ISM) bands to put forward the packet about 2–5 km in and up to 45 km in rural areas [3]. The overall security in LoRaWAN is evolving and technically challenging [4]. It uses end-to-end encryption, with AES 128-bit-key operating in CTR mode; additionally, every message is signed. There are various papers available in the literature that consider the security vulnerabilities of LoRaWAN. For instance, Yang et al. [5] made a scientific study on security vulnerabilities in LoRaWAN published in 2018, which mentions several different malicious attacks that the LoRaWAN network is susceptible to due to the gateway vulnerability. It has then be verified again in 2018 by Butun et al. [6,7], who conducted a security risk survey of the LoRaWAN-specification and in their work compiled a list of attack vectors that assesses the likelihood and risk associated with each attack vector. In 2019, Eldefrawy et al. [8] further verified the inherent security problems by executing a formal security analysis. Several security breaches identified in above mentioned are summarized as follows:Man-in-the-Middle (MITM) Attacks: LoRaWAN is vulnerable to a specific MITM attack called bit-flipping attack, which changes the content of a message between the NS and AS. Network Flooding Attack: Here, the end device can be captured and made to attack the rest of the network by flooding it with packets. Network Traffic Analysis: Known as an eavesdropping attack, this is done with a rogue gateway to receive packets and deduce some information of its contents. It would still need a key to decode it, but other information such as the activity in a certain location can be observed. Physical Attack: Here, the node is physically compromised, either destroyed, stolen or cloned. It is thus of high importance to have adequate protection against firmware change that could lead to the reuse of key material. Radio Frequency (RF) Jamming Attack: It is possible to jam the reception of a signal in a node, which could be used for more advanced attacks such as a replay attack to be effective. Self-Replay Attack: An attack that exploits the join procedure by replicating a join request while jamming the original sender. It is thus able to look legitimate until the daily quota of the impersonating ED depletes. As mentioned above, many authors contributed in this field to improve overall network security of the LoRaWAN, especially seeking remedies to key management and distribution challenges. However, the network has overlooked one critical class of components, which is the gateways. LoRaWAN implementation is accomplished in five steps such as end devices, gateways, network server (NS), join server (JS), and application server (AS), which are further described in the upcoming section. The gateway constitutes the weakest point in the LoRaWAN implementation. Most of the deployments feature a small number of gateways, and in some cases, just one or two of them run the network. So, an attacker having gateway attacking motivation can capture or physically destroy the gateway, which can significantly affect the successful communication of the end device to the other entities, i.e., network and application server. The network server is dependent on the gateway, and the compromised gateway can falsely lead the packet toward the network server. The gateway cyber security breach is discussed in paper [9], and the authors argued that the attacker can capture the valid data during transmission and then alter or replicate it. The LoRaWAN gateway is susceptible to jamming attacks and results in denial-of-service that disrupts the communication between the node and the gateway. Having poorly secured gateways is a major flaw that can affects the vulnerability of the rest of the network. A lack of authentication and message authentication (MAC) between GW and the NS makes it possible for an attacker to execute various attacks targeting the network’s availability. If a gateway is not properly secured with an authentication mechanism, it would be susceptible to a variety of malicious rogue-GW attacks, which could disrupt its availability. This vulnerability could disrupt the traffic and increase collisions of transmitted packets. There could be dire consequence if not one but multiple gateways are either captured or replicated with malicious intent, which can cause disastrous disruptions in the traffic flow and result in the collapse of the network. This paper presents a novel technique that enhances the cyber security of the LoRaWAN gateway. The proposed technique consists of a public-key infrastructure (PKI) that constitutes a two-tier certificate authority (CA) solution. The two-tier CA solution tackles the single-point failure setup by employing the root-CA and intermediate-CA setup. The simulation results revealed that the proposed technique successfully mitigates malicious attacks such as Selective Forwarding Attacks. For a more detailed presentation of this work, please refer to the thesis by Mohamed and Wang, named “Rogue Gateway Attacks Against LoRaWAN and Their Mitigation” [10]. The rest of the paper is organized as follows. Section 2 discusses related work in the given field. Section 3 describes the network architecture and related basics of LoRaWAN. The design and implementation have been addressed in Section 4. The results from the proposed solution are explained in Section 5 and discussed thoroughly in Section 6. Finally, the overall work is concluded in Section 7, which also provides indications for future improvements. 2. Related Work This section deals with cyber security breaches of LoRaWAN gateways that have been recently introduced in the literature. Gateways are transparent, and they are not authenticated at any way. Therefore, the authors in [11] stated that rogue gateways can be harmful and introduce Beacon Attacks by bursting false beacons repeatedly. The same authors have presented a scenario of setting up a malicious gateway that captures and drops certain packets. The situation become a worse problem when there is only one gateway in the given range; therefore, the network server may not find any other way to get packets from the end device. The authors in [12] presented various radio jamming attacks that are associated with cheap hardware with a low capability radio module and a micro-controller. The first attack, such as a triggered jamming attack, happens when the packet is detected passing through the dedicated channel. The selective jamming attack is possible only when there is LoRaWAN packet activity in the channel. Forcing a class change breach is discussed in [12], where the authors stressed that when the gateway refrains from sending beacon messages, the end device goes back from class B to class A. The attack takes place when the whole network is dependent on a single gateway, which causes disruption between the end device and network server. Butun et al. [7] made a security analysis of LoRaWAN v1.1 with the aim to review and clarify its security aspects. Their results of security risks are then analyzed and compiled into a list, which is ranked on impact and threat level. The most highlighted discovered threats are end device physical capture, rogue gateway, and self-replay attacks. The more relevant part of this paper is the analysis regarding the potential rogue gateway vulnerability and attacks they discovered. Lin et al. [13] proposed an interesting solution based on blockchain technology to increase the trust value within the LoRaWAN network. It aims to build an open, trusted, decentralized, and tamper-proof system, which should be able to verify all the transactions that take place. Since LoRaWAN’s main aim is to be a low-cost network with a sufficiently adequate level of security, it is thus debatable whether the increase in cost with this kind of implementation would be the correct solution. Their proposed solution would introduce a lot of new elements, and their future work states that they will look to explore smart contract script technology to define an automated trading model or an automatic billing and roaming function. The authors in [14] pointed out that in LoRaWAN, when the number of nodes joining the network server is large, high latency may occur in processing requests from all devices. To cope with this challenge, the authors proposed a multi-device authentication-based join mechanism. They considered the exclusive-OR technique for a large number of devices’ authentication. Furthermore, the hash operation is implied to protect the proposed technique against several threats such as session keys’ revealing, the end device. and network server’s attacks. The proposed technique outperforms and achieves 33% low latency as compared to the original LoRa specification. Ribeiro et al. [15] proposed a secure architecture for key management in LoRaWAN. The proposed architecture is based on smart contracts and permission blockchain that enhances the security and availability of LoRaWAN infrastructure. The authors created a prototype using an open-source tool that achieves similar execution latency as compared to the traditional LoRaWAN system. The authors in [16] discussed that the LoRaWAN join procedure needs security protection, as it is susceptible to multiple security issues. In addition, to cope with the security issues associated with the network server, the authors presented a lightweight two-factor authentication mechanism. Their method is based on blockchain technology that secures the LoRa joins procedure. This blockchain-based approach secures the LoRa join procedure by providing an extra layer of security. This approach is validated using the Ethereum blockchain and revealed that the proposed system achieved good throughput with the cost of low latency. In [17], the authors proposed Ehpemeral Diffie–Hellman Over COSE (EDHOC) protocol for secure key provisioning in LoRaWAN, which is a lightweight protocol that provides a secure key establishment between the end device and network server. The EDHOC was used to derive the session keys, namely NwkSKey and AppSKey, which were used in the OTAA activation method. The proposed protocol can be supported by the spreading factors having the highest data rate i.e., SF7 and SF8. In [8], Eldefrawy et al. considered that all GWs in the network are trusted entities which could not create a single point of failure (SPOF). Hence, their formal analysis did not reveal any problem related to GWs. On the contrary, in the current version of LoRaWAN, GWs are not authenticated by the servers or another Trusted Third Party (TTP). As we prove in this work, GWs can create an SPOF for attackers and from which they can execute network-based attacks, including hole attacks such as black-hole or selective-forwarding. Haxhibeqiri et al. [18] presented an extensive analysis of LoRaWAN. The authors discussed the new version of LoRawAN v1.1 and came up with addressing several challenges and security vulnerabilities. However, the end-to-end MIC is missing, which makes payload integrity vulnerable. Furthermore, the node placed in the network can cause malicious activity between the network server and the application server. This malicious node leads the network to a bit-flipping attack. The authors in [19] conducted a comprehensive survey for LoRaWAN architecture, applications, and security analyses. The authors stressed that promising enhancements have been counted in the LoRaWAN v1.1 standard such as improved communication and availability. However, the session duration is not mentioned by the new standard, which causes ambiguity regarding for how long the session will remain to continue. This needs to be addressed in the upcoming specification. 3. Various Aspects of LoRaWAN 3.1. Network Architecture The LoRaWAN network architecture can be described in five layers such as end device, gateway, network server, join server, and application server, as elucidated in Figure 1. The end device operates via radio frequency and forwards the packet to the gateway using dedicated frequency e.g., (433.05–434.79 MHz—Asia, 863–870 MHz—Europe, 902–928 MHz—US) [20]. The gateways are transparent and extend the packets received from the end device toward the network server. The gateway and network server communicate through TCP/IP protocol. The join server is a trusted entity and is used for the end device’s root keys distribution. The application server collects and sends the packets toward the network server, which is further transmitted to the end node through the gateway. 3.2. Communication Gateways in LoRaWAN are tasked with demodulating LoRa packets using a packet forwarder, which forwards the packets to a LoRa NS. There exist several packet forwarders, most commonly: Message Queuing Telemetry Transport (MQTT) and Semtech User Datagram protocol (UDP). Semtech UDP: This forwarder was the first packet forwarder and still comes pre-compiled with most LoRa gateways. It uses the Semtech UDP protocol over TCP/UDP. Although over time, this protocol has acquired some flaws, it is still an easy way to test new gateways. MQTT: Is a lossless, bidirectional protocol designed for high-latency, low-bandwidth connections [21]. MQTT is a publish–subscribe protocol where clients subscribe to a set of topics for reading and writing. This makes the clients extremely lightweight and suitable for IoT connections, while the broker act as a gateway that handles all the transmissions to and from the servers of the relevant topics. 3.3. Message Format The messages transferred over the network can be divided into two types; the first one is an uplink message which is sent from an end-device to the network, using the gateways as relays. The other type is called a downlink message, which is the opposite direction, from the server to an end-device using a gateway. Uplink Message: Uses the LoRa radio packet explicit mode, which consists of a physical header (PHDR) and a cyclic redundancy check (CRC) header (PHDR_CRC). Another CRC is required to protect the integrity of the payload; these three are together inserted by the radio transceiver in the following way: Uplink PHY: Preamble PHDR PHDR_CRC PHYPayload CRC Downlink Message: Works very similar and also uses the LoRa radio packet explicit mode with a PHDR and a PHDR_CRC. Downlink PHY: Preamble PHDR PHDR_CRC PHYPayload As can be seen above in either the uplink or downlink message, both contain a PHY payload called PHYPayload. This PHYPayload starts with a single-octet MAC header (MHDR), followed by a MAC payload (MACPayload) and finishing with a 4-octet message integrity code (MIC), as seen below: PHYPayload: MHDR MACPayload MIC Here, the MHDR specifies what message type it is (MType), there are six different ones. There is join request, join accept, unconfirmed data up/down and confirmed data up/down, where confirmed means that it has to be acknowledged by the receiver, while unconfirmed does not require that. The MACPayload carries information regarding the data frame. MACPayload: FHDR FPort FRMPayload The MACPayload contains a frame header (FHDR), which is the device address of an end-device (DevAddr), followed by an optional port field (FPort) and an optional frame payload field (FRMPayload) [22]. 3.4. Security The LoRaWAN specification consists of two layers of cryptography. The first is at the network level, which handles mutual authentication and integrity protection. The second layer is on the application level for confidentiality with end-to-end encryption [18]. The first layer consists of:Mutual Authentication: This is established between the end device and the LoRaWAN network during the join procedure, which ensures that both the device and the network are genuine and authentic. Integrity Protection: LoRaWAN MAC and application messaging are origin authenticated, integrity protected, replay protected, and encrypted. Together with the mutual authentication, it will protect the network by preventing the alteration of messages and ensure that the sender is legitimate. In the second layer, we have:Confidentiality: For the application level, LoRaWAN employs end-to-end encryption for application packages that are transferred between an end device and application server. These mechanisms use the AES algorithm to provide authentication and integrity of packets to the network server and end-to-end encryption to the application server. Each layer uses a unique 128-bit key, a network session key between the end device and network server, and an application session key for end-to-end on the application level. Through the use of two levels, it is able to achieve a “multi-tenant” shared network, where the network operator has no visibility on the payload data [23]. The two unique AES 128-bit session keys are:Network Session Key: (NwkSKey) is used as identification between the end-device and the network server. Application Session Key: (AppSKey) is for payload encryption and decryption and is shared end-to-end on the application level. When an end device wants to access a network, it first has to be registered and then permitted to join the network. The corresponding keys can be generated in two ways:Activation By Personalization (ABP), this activation method already has the NwkSkey and AppSKey set up in advance and can thus access the network without requiring a join request. Over-The-Air Activation (OTAA), this method starts with a “Join Request” containing the device ID (DevEUI), the application server ID (AppEUI), and a random value called DevNonce [6]. It is signed with a message integrity code (MIC) using the AppKey. If the MIC is validated, then the node is authenticated, and the network sends back a “Join Accept” message, which is encrypted with the AppKey, and it includes the AppNonce and NetID parameters. Both activation methods are viable; however, OTAA is preferred, since it can generate new keys every new session and also allows easy re-key if necessary [24]. Meanwhile, ABP is hardcoded and not as flexible, making it vulnerable to physical attacks. 4. Design and Implementation This section discusses the practical demonstration of our proposed technique. The hardware that are used to replicate the LoRaWAN ecosystem, such as the end device and gateways, is done using a computing unit together with a LoRa radio chip. In this paper, the computational unit is the Raspberry Pi4 Model B (RPi4), as shown in Figure 2, with a 1.5 GHz quad-core processor and 4 GB RAM, together with complements such as a 16GB SD card, a breadboard, jumper cables to connect the different parts, and of course a power supply. The LoRa radio chip used is the Adafruit RFM96W LoRa Radio Transceiver 433 MHz, as shown in Figure 3, which is necessary in order to be able to use long-range communication in the LoRaWAN network. However, this chip is only able to provide a single channel at a time. A single channel is usually not enough for a LoRaWAN network and would cause a loss of messages, but for our experiments in a controlled environment, this is sufficient. For the antenna, we used a simple 22 AWG wire, where the length of the wire determines its frequency using this formula:(1) Wl=Wv×Fr where Wl represents the wavelength, Wv is the wave velocity, and Fr is the radio frequency. So, for the gateway, the computational unit and LoRa radio chip are connected. This was done by soldering the radio chip together with male header strip pins and then attaching it to a breadboard. When the chip is firmly set up on the breadboard, the breadboard is then wired with male-to-female wire cables to the Raspberry Pi, as seen in Figure 4 and the diagram in Figure 5. During our initial attempt, we did manage to set it up without the need of a breadboard; however, it did not feel sufficiently stable, and the wire antenna that was later soldered onto the chip could not be pointed upwards. The LoRa radio chip consists of multiple pins that control different functions. Starting from the left, we have the three power pins: VIN, GND, and EN. These pins handle the powering of the breakout and shutdown of the radio. VIN (Voltage Input): The power supply can handle 3.3 to 6 VDC with a peak current of 150 mA, making sure to supply that amount of current for everything to work. GND (Ground): The ground is for logic and power. EN (Enable): The enable pin of the regulator, which is pulled high to VIN by default; pulling it low to GND will cut off the power to the radio. The power pins are then followed by the six Serial Peripheral Interface (SPI) pins: G0, SCK, MISO, MOSI, CS, and RST. The SPI is a protocol that the microcontrollers use to communicate with peripheral devices. G0 (GPIO 0/IRQ): Is used for interrupt request notification from the radio to the microcontroller. SCK (SPI Clock): Is an input to the chip. MISO (Master In Slave Out/Microcontroller In Serial Out): Is for the data sent from the radio transceiver to the microcontroller/processor. MOSI (Master Out Slave In/Microcontroller Out Serial In): Is for the data sent from the micocontroller/processor to the radio transceiver. CS (Chip Select): Is an input to the chip. Drop it low to start an SPI transaction. RST (Reset): The reset pin is pulled high by default, which is reset. Pull it low to turn on the radio. Similarly, the Raspberry Pi also comes with two rows of 40 General-Purpose Input/Output (GPIO) pins; out of these, we connect the radio chip to the eight equivalent pins with wire cables, as seen in Table 1. 4.1. Proposed Technique OpenSSL software was installed on two Ubuntu 20.04.2 LTS in a virtual environment with two identical setups, except for the OpenSSL configuration files. Configuration files are necessary when using OpenSSL as a CA, as they contain more parameters than what is possible to specify in the terminal. OpenSSL configuration files provide two functions: template when issuing new certificates and enforce certificate policies in the configuration. A certificate policy contains a set of parameters such as countryName, commonName, etc., that must match corresponding fields in a Certificate Signing Request (CSR). Figure 6 illustrates the x509v3-certificate format that the proposed solution will issue. The certificate format corresponds to the bare minimum required by the standard RFC for the purpose of reducing size. The attribute Common Name <CN> will hold the LoRaWAN unique device identifier DEVEUI; moreover, RSA will provide digital signatures. To obtain a certificate, clients produce a CSR with their DEVEUI as the Subject Common <CN> and SHA256 as the message digest as seen in Listing 1. Listing 1. Certificate Signing Request (CSR) for GW. 1 Certificate Request 2     Data 3           Version 1 (0x0) 4           Subject : CN = 0xFFFFFFFFFFFF 5           Subject Public Key Info : 6               Public Key Algorithm : rsaEncryption 7                   RSA Public - Key : (2048 bit ) 8                   Modulus : 9                        00: af:e1 :3a:1a:d0 :7f:9c:c5:a9 :45:90:2 a:dc :88: 10                        … 11                   Exponent : 65537 (0 x10001 ) 12           Attributes : 13           Requested Extensions : 14               X509v3 Key Usage : critical Digital Signature , Key Encipherment 15           X509v3 Extended Key Usage : E- mail Protection ,TLS Web Client     Authentication 16               X509v3 Subject Key Identifier : 17                   67: FF :89:00:84: C7 :40: ED :54:33:05:74:75: DE:C1 :1E:4A :18:2 D:F4 18               X509v3 Subject Alternative Name : 19                   <EMPTY> 20 21     Signature Algorithm : sha1WithRSAEncryption 22           73: b4:c4:ed :93:9 e:f4 :9d:a7 :1f :90:40:71:07:5 d:3a:d9:f1: 23           … After this, the intermediate-CA issues a new certificate, which is illustrated by Listing 1, based on the CSR. The Certificate Revocation List (CRL) for the root-CA receives an update every seven days automatically or when a certificate is revoked. On the contrary, the CRL for the intermediate-CA receives an update every seven hours. The CRL is signed by the issuing entity and easily verified by recipients by comparing the signature with the signature generated from the issuing entity’s public key. Furthermore, the CRL from the issuing CA, i.e., intermediate-CA, will be placed beside the JS and accessed over MQTTv3 for LoRaWAN devices. 4.2. Attacker Model In this work, we are are aiming at devising a cyber-defense mechanism against GW-based attacks. In particular, Man-in-the-Middle (MITM) attacks are the focus of this work. This particular MITM attack is aimed at causing disturbances in availability. When LoRa packets are processed, the GW attaches information about itself for future downlink messages (may it be LoRa or application layer). Since the GWs are not verified, a potential rogue GW could attach malicious information such as the wrong sender IP, which causes future downlink messages not to get through. It is also possible that the rogue GW could attach correct metadata and then drop downlink messages, as shown in Figure 7. The network server (NS) must first ACK the LoRa-modulated packet forwarded by the rogue gateway to be efficient, since redundant messages are disregarded. Our proposal suggests to verify and authenticate GW <−−> NS, thus rendering these types of attack useless. 4.3. Verification of the Proposal Extensive experiments have been carried out in order to verify the solution. The goal of each of the tests is to see how the proposed solution, as illustrated in Figure 8, handles unauthorized transmissions. As can be seen in the flow chart, the JS receives requests from both the GW and NS and forwards them to the intermediate-CA. The root-CA then authenticates requests and provides acknowledgment to the GW and NS. This will be performed by collecting the Package Delivery Ratio (PDR) for each test scenario. The PDR is a metric used to show the percentage of packages that arrives out of the total number of packages sent in a network. Observing the PDR shows what happens when the network is either attacked by malicious attacks or when it is protected by the proposed solution and how that affects the network traffic. (2) PDR=PReceivedPSent A way to verify that our proposed solution is working would be to try and replicate a rogue gateway attack (executed as MITM attack), as seen in Figure 7. The attack that will be studied closely is the Selective Forwarding Attack, which exploits the frame counter. So, when an end-device would send out a certain amount of packages, these packages are registered in order and increments the frame counter. In other words, each device keeps track on all the messages it receives and thus only accepts messages with a larger frame counter. So, if it receives a message with a lower frame counter, then it is discarded. So, with Selective Forwarding Attack, a rogue actor could then withhold the majority of packages as long as it sends messages with a higher frame counter then the previous one, for example, just sending the first and the last package. Thus, if the rogue actor is faster than legitimate ones, either by being closer or outright disabling legitimate GWs in the vicinity, that would mean it could control the transmission flow and greatly reduce the network’s efficiency. This can be validated by deploying two gateways, where one is an authorized gateway, GW-A, and the other is not, GW-B. Then, an end-device transmits a series of messages that will be picked up and forwarded to the NS. Starting first in the vicinity of the authorized gateway, GW-A, the majority of packages will first go through GW-A before arriving at the NS, where they all would ultimately be accepted. By then, we slowly move the ED closer to the rogue gateway, GW-B, and messages should at a certain point start to arrive first at the GW-B. If then a number of messages manage to arrive first at the GW-B before reaching the legitimate GW-A, the rogue gateway can then drop some packages and send one with a higher frame counter. The network server will just see an acceptable frame counter, which is higher than the previous one and accept the transmission. However, when the packages from GW-A finally arrive, they will come in order with a lower frame counter, which the NS ultimately rejects for being duplicates, which in the end means that the NS would only receive a fraction of the whole message. 5. Results This section presents the results obtained from the verification and validation process; additionally, it presents the effectiveness of the proposed protocol for mutual authentication against attacks involving rogue gateways, as described by Butun et al. [7]. The verification process tests, and by extension determines, if the proposed protocol meets its specification for mutual authentication. Moreover, the verification process determines the effectiveness against rogue gateways attacks. RSSI of the Test Area The Received Signal Strength Indicator (RSSI) is a parameter aimed to mean how well a device can hear, detect, and receive transmissions. This is based on the relative quality of the signal and any potential loss due to the antenna or cable properties. The RSSI may be reported in many different ways, but a common method adopts decibel-milliWatts (dBm), for example the authors in [25] report indoor localization experiments based on RSSI evaluation, adopting a matching schema such as the one detailed in Table 2. By measuring the RSSI, data can be gathered that would give a rough estimate of the noise levels, which could affect the signal strength. This is valuable information that would give the reader sufficient insight in the RSSI of urban areas and to help understand the baseline scenario. It would also verify how solid the hardware setups performance is, as there were some concerns on the signal strength of the makeshift antenna. Figure 9 shows the same baseline scenario with the RSSI values collected and then plotted. As can be seen, the RSSI already starts past the −80 dBm value for the initial distance, which is a low rating according to Table 2. This continues to deteriorate as the end-device travels further away. At around 1000 m, there are no longer any packages being delivered to GW-A, which correlates to an RSSI value almost reaching −100 dBm, which seems reasonable from the literature study. A similar trend can be seen for GW-B: as the ED gets closer, the RSSI strength increases. Let us consider the implications of a Selective Forwarding Attack in critical infrastructure. Let us examine water height meters for flood embankments in the context of the smart city. Figure 10 depicts (a) a plot or potential dashboard over water height measurements during nine packets, whereas (b) shows the water height measurements during a Selective Forwarding Attack. In Figure 10a, the water level rises incrementally. Meanwhile, Figure 10b shows water rising from 1 m to over 35 m in two readings. If the system is autonomous, it may decide to open the flood gates and cause harm to the people and buildings in the immediate area. If the system instead is monitored by humans, a tedious and time-consuming task will take place to determine the fault of the problem. By using the low-cost and accessible RFM9x LoRa transceivers combined with the Raspberry Pi, our gateways practically became single-channel. Single-channel gateways can only receive payload on a specific spreading factor and channel. Additionally, single-channel gateways offer reduced coverage compared to higher-end LoRa chips [26]. In the baseline measurements, we noted a drastically reduced PDR after 200 m, in a moderate Line of Sight. After 1000 m, we did not receive any packets. Furthermore, we had only one end-device at our disposal, which greatly affected the type of setups we could simulate. The RSSI readings obtained from the RFM9x, which are crucial for determining the signal strength and quality, are not that accurate. It is also important to note that single-channel gateways are not LoRaWAN-compliant for the reasons stated above. Figure 11 showcases the results obtained from the proposed technique. As can be seen, the rogue gateway receives a higher number of packets than the legitimate gateway. It is because of the fixed position near the end device. Therefore, the rogue gateway instantly received the packets when broadcast from the end device. In other words, the legitimate gateway received fewer packets as of a long distance from the end device. The plot in Figure 12 shows the number of packets received by the network server. At 200 m, the network server received more than 4500 packets. However, due to our novel authentication algorithm, only the packets from the legitimate gateway were accepted (approx. 1500 packets), and the rest were discarded (approx. 3000 packets) by the network server. 6. Discussion LoRaWAN is an emergent technology that provides the connectivity facility over long distances with ultra-low power consumption. It brings a strong security feature as the AES-128 encryption technique that is used for the payload travels from the end device to the application server. However, previous research studies have noted that the gateway is the weak point, which provides an opportunity for attackers in the network. As discussed earlier, the whole network consists of end devices, gateways, and servers. The gateway plays the key role that collects the messages from the end devices and transmits the collected messages to the servers. The overall network relies on the gateway, and the malicious attacks can affect the network. To cope with malicious attacks, we present a novel certificate authentication technique to protect the gateway in the network. The proposed technique considers a PKI solution that consists of Certification Authority (CA), Registration Authority (RA), Validation Authority (VA), and key pairs. For security reasons, we kept the root-CA offline and used an intermediate certificate signed by root-CA. Moreover, ongoing research studies identified several vulnerabilities at LoRaWAN that circumvent the strong encryption process (the AES-128). As a solution, many researchers have introduced implicit certificates (such as Elliptic Curve Qu-Vanstone—ECQV) for authentication between nodes and the Application Server. These are cumbersome, to say the least. ECQV works by reconstructing values derived from a shared public key. ECQV does not support certificate revocation; hence, a physically compromised GW can be used to attack the network. Secondly, our proposal is overall best suited for time and security critical applications such as large enterprises, etc. Table 3 summarizes and compares unique features of related security solutions for LoRaWAN in the literature vs. our proposal. 7. Conclusions and Future Work LoRaWAN is a promising technology that enables long-range communication with extremely low power consumption. Gateways are one of the most important elements in LoRaWAN, in the case: “deal” with the transportation of packets from the end device to the network server and vice versa. However, recent studies have pointed out that the gateway constitutes the weakest point in the network and is susceptible to a variety of malicious attacks. Therefore, this paper proposes the latest technique to prevent the gateway from malicious attacks such as Selective Forwarding Attack. The proposed technique considers a PKI-solution that considers a two-tier CA setup, i.e., a root-CA and intermediate-CA. The simulation results reveal the effectiveness of the proposed work. In the future, a lightweight certificate-assigning technique might reduce the payload size during initial authentication. According to our experimentation, 66.67% of the packets that are arriving from an illegitimate GW are discarded in our devised secure and reliable solution. Future Work Future research may find a solution for reducing the certificate size that might be beneficial for the network server to keep the certificates for all authenticated gateways in the memory. Such small sizes can also help the throughput when many gateways are authenticated and forwarding payloads. Acknowledgments We would also thank the CSE department (Networks and Systems Division) at the Chalmers University of Technology for aiding and equipping us with the necessary hardware and resources. We are also thankful to Research Engineer Lars Norén for helping us acquire the necessary tools and hardware to make this research a success. Author Contributions Conceptualization, I.B.; methodology, A.M.; software, A.M. and F.W.; validation, A.M. and F.W.; formal analysis, I.B.; investigation, A.M. and F.W.; resources, I.B.; data curation, A.M. and F.W.; writing—original draft preparation, A.M. and F.W.; writing—review and editing, J.Q.; visualization, A.M. and F.W.; supervision, I.B., R.L., P.G. and D.D.C.; project administration, I.B. and D.D.C.; funding acquisition, I.B.; proofread, D.D.C.; all revisions and final editing, J.Q., A.M., D.D.C. and I.B. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Abbreviations The following abbreviations are used in this manuscript: AS Application Server AppSKey Application Session Key ABP Activation By Personalization CA Certificate Authority CRC Cyclic Redundancy Check CRL Certificate Revocation List CSS Chirp Spread Spectrum CSR Certificate Signing Request CTR Counter dBm decibel-milliWatts ECQV Elliptic Curve Qu-Vanstone EDHOC     Ehpemeral Diffie–Hellman Over COSE GW Gateway HDR Frame Header IoT Internet of Things ISM Industrial Scientific and Medical JS Join Server LoRa Long Range LoRaWAN Long Range Wide Area Network MQTT Message Queuing Telemetry Transport MITM Man-in-the-Middle MTyope Message Type MIC Message Integrity Code M2M Machine to Machine NwkSKey Network Session Key NS Network Server OTAA Over-The-Air Activation PDR Packet Delivery Ratio PKI Public Key Infrastructure RA Registration Authority RF Radio Frequency RSSI Received Signal Strength Indicator SPOF Single Point of Failure TTP Trusted Third Party VA Validation Authority Figure 1 Network architecture of LoRaWAN. Figure 2 Computing unit—Raspberry Pi4 Model B. Figure 3 LoRa radio chip—Adafruit RFM96W. Figure 4 Gateway hardware and wiring setup using RPi4 and RFM96W. Figure 5 Wire cable connections between the Raspberry Pi and LoRa radio chip. Figure 6 x.509v3 certificate format. Figure 7 Scenario of packet advancement under MITM attack. Figure 8 Flow chart of the certification process in the proposed work. Figure 9 The RSSI values of the baseline scenario, the first half being the RSSI of GW-A and the second half GW-B. Figure 10 (a) Water height values (indicated by triangles) gathered from end-device with no attack present, (b) water height values with a Selective Forwarding Attack present. Figure 11 Preliminary testing area with no line of sight. R-GW permanently placed at 200 m from the ED and L-GW placed at 200 m increments up to 800 m. Figure 12 Preliminary testing area with no line of sight. Data on packages received by the NS, total vs. accepted. sensors-22-03498-t001_Table 1 Table 1 Wire connection of the pins. Raspberry Pi 4 RFM96W 1 (3V3 Power) VIN 9 (Ground) GND 29 (GPIO 5) G0 23 (GPIO 11: SCLK) SCK 21 (GPIO 9: MISO) MISO 19 (GPIO 10: MOSI) MOSI 26 (GPIO 7:CE1) CS 22 (GPIO 25) RST sensors-22-03498-t002_Table 2 Table 2 Signal strength levels of RSSI [25]. Signal Strength Rating Info >−30 dBm Amazing Max signal strength, due to being right next to the client. Not reasonable in the real world. −50 dBm Excellent Almost perfect signal strength in the real world with ideal conditions. −60 dBm Very Good High latency, would most likely not feel any disturbance. −70 dBm Good Minimum signal strength for reliable packet delivery for menial tasks. −80 dBm Low Minimum signal strength for basic connectivity. Packet delivery is now unreliable. −90 dBm Very Low Terrible signal strength, with frequent package drops and connectivity issues. <−100 dBm No Signal Not much if anything is able to get through. sensors-22-03498-t003_Table 3 Table 3 Literature comparison of related security solutions for LoRaWAN. Related Work Authentication of End-Device with Server Improvements on End-Device Comm Improvements on Network Security Authentication of GW with Server Mårlind and Butun [4] ✔ ✔ ✔ ✖ Gresak and Voznak [9] ✖ ■ ✔ ✖ Fan et al. [14] ✔ ✔ ■ ✖ Ribeiro et al. [15] ✔ ✔ ✔ ✖ Danish et al. [16] ✔ ✔ ■ ✖ Sanchez et al. [17] ✔ ✔ ✔ ✖ Naoui et al. [27] ✖ ■ ✔ ✖ Proposed work ✖ ✔ ✔ ✔ Legend✖: Does not fulfill; ✔: Fulfills; ■: Inclusive. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Mekki K. Bajic E. Chaxel F. Meyer F. A comparative study of LPWAN technologies for large-scale IoT deployment ICT Express 2019 5 1 7 10.1016/j.icte.2017.12.005 2. LoRaWAN What Is LoRaWAN? Available online: https://lora-alliance.org/about-lorawan/ (accessed on 12 April 2022) 3. Sinha R.S. Wei Y. Hwang S.H. A survey on LPWA technology: LoRa and NB-IoT ICT Express 2017 3 14 21 10.1016/j.icte.2017.03.004 4. Mårlind F. Butun I. Activation of LoRaWAN End Devices by Using Public Key Cryptography Proceedings of the 2020 4th Cyber Security in Networking Conference (CSNet) Lausanne, Switzerland 21–23 October 2020 1 8 10.1109/CSNet50428.2020.9265530 5. Yang X. Karampatzakis E. Doerr C. Kuipers F. Security Vulnerabilities in LoRaWAN Proceedings of the 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI) Orlando, FL, USA 17–20 April 2018 129 140 10.1109/IoTDI.2018.00022 6. Butun I. Pereira N. Gidlund M. Analysis of LoRaWAN v1. 1 security Proceedings of the 4th ACM MobiHoc Workshop on Experiences with the Design and Implementation of Smart Objects Los Angeles, CA, USA 25 June 2018 1 6 7. Butun I. Pereira N. Gidlund M. Security risk analysis of LoRaWAN and future directions Future Internet 2018 11 3 10.3390/fi11010003 8. Eldefrawy M. Butun I. Pereira N. Gidlund M. Formal security analysis of LoRaWAN Comput. Netw. 2019 148 328 339 10.1016/j.comnet.2018.11.017 9. Gresak E. Voznak M. Protecting gateway from abp replay attack on lorawan Proceedings of the International Conference on Advanced Engineering Theory and Applications Ostrava, Czech Republic 11–13 September 2018 Springer Cham, Switzerland 2018 400 408 10. Mohamed A. Wang F. Rogue Gateway Attacks against LoRaWAN and Their Mitigation Mater’s Thesis Department Computer Science and Engineering, Chalmers University of Technology Gothenburg, Sweden 2021 1 75 11. Magnusson O. Teodorsson R. Wennerberg J. Knoph S.A. A Survey on Attacks and Defences on LoRaWAN Gateways Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities IGI Global Hershey, PA, USA 2021 19 38 12. Aras E. Small N. Ramachandran G.S. Delbruel S. Joosen W. Hughes D. Selective jamming of LoRaWAN using commodity hardware Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services Melbourne, VIC, Australia 7–10 November 2017 363 372 13. Lin J. Shen Z. Miao C. Using Blockchain Technology to Build Trust in Sharing LoRaWAN IoT Proceedings of the 2nd International Conference on Crowd Science and Engineering Beijing, China 6–9 July 2017 38 43 10.1145/3126973.3126980 14. Fan C.I. Zhuang E.S. Karati A. Su C.H. A Multiple End-Devices Authentication Scheme for LoRaWAN Electronics 2022 11 797 10.3390/electronics11050797 15. Ribeiro V. Holanda R. Ramos A. Rodrigues J.J. Enhancing key management in LoRaWAN with permissioned blockchain Sensors 2020 20 3068 10.3390/s20113068 32485791 16. Danish S.M. Lestas M. Asif W. Qureshi H.K. Rajarajan M. A lightweight blockchain based two factor authentication mechanism for LoRaWAN join procedure Proceedings of the 2019 IEEE International Conference on Communications Workshops (ICC Workshops) Shanghai, China 20–24 May 2019 1 6 17. Sanchez-Iborra R. Sánchez-Gómez J. Pérez S. Fernández P.J. Santa J. Hernández-Ramos J.L. Skarmeta A.F. Enhancing lorawan security through a lightweight and authenticated key management approach Sensors 2018 18 1833 10.3390/s18061833 29874839 18. Haxhibeqiri J. De Poorter E. Moerman I. Hoebeke J. A Survey of LoRaWAN for IoT: From Technology to Application Sensors 2018 18 3995 10.3390/s18113995 30453524 19. Noura H. Hatoum T. Salman O. Yaacoub J.P. Chehab A. LoRaWAN security survey: Issues, threats and possible mitigation techniques Internet Things 2020 12 100303 10.1016/j.iot.2020.100303 20. Rydell J.B. Otterlind O. Butun I. Delay Considerations for Reliable Communications in LoRaWAN Proceedings of the 2022 IEEE 19th Annual Consumer Communications Networking Conference (CCNC) Las Vegas, NV, USA 8–11 January 2022 1 6 10.1109/CCNC49033.2022.9700629 21. Light R.A. Mosquitto: Server and client implementation of the MQTT protocol J. Open Source Softw. 2017 2 265 10.21105/joss.00265 22. Alliance L. LoRaWAN 1.1 Specification Available online: https://lora-alliance.org/resource-hub/lorawanr-specification-v11 (accessed on 12 December 2020) 23. Committee L.A.T. LoRaWAN® Is Secure (but Implementation Matters) Available online: https://lora-alliance.org/resource_hub/lorawan-is-secure-but-implementation-matters/ (accessed on 28 May 2021) 24. Dönmez T.C. Nigussie E. Security of Join Procedure and its Delegation in LoRaWAN v1.1 Procedia Comput. Sci. 2018 134 204 211 10.1016/j.procs.2018.07.202 25. Luo X. O’Brien W.J. Julien C.L. Comparative evaluation of Received Signal-Strength Index (RSSI) based indoor localization techniques for construction jobsites Adv. Eng. Inform. 2011 25 355 363 10.1016/j.aei.2010.09.003 26. The Things Network Single-Channel Gateways Available online: https://www.thethingsnetwork.org/docs/gateways/start/single-channel/ (accessed on 28 May 2021) 27. Naoui S. Elhdhili M.E. Saidane L.A. Trusted third party based key management for enhancing LoRaWAN security Proceedings of the 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA) Hammamet, Tunisia 30 October–3 November 2017 1306 1313

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092580 jcm-11-02580 Article Sartans and ACE Inhibitors: Mortality in Patients Hospitalized with COVID-19. Retrospective Study in Patients on Long-Term Treatment Who Died in the Italian Hospitals of Area Vasta n.5—Marche Region Mazzoni Tony 1 Maraia Zaira 2 Ruggeri Benedetta 2 Polidori Carlo 1 https://orcid.org/0000-0002-8044-1206 Micioni Di Bonaventura Maria Vittoria 1 Armillei Laura 2 Pomilio Irene 2 Mazzoni Isidoro 2* Rodrigues Célia F. Academic Editor Cruz-Martins Natália Academic Editor 1 Pharmacology Unit, School of Pharmacy, University of Camerino, 62032 Camerino, Italy; tony.mazzoni@studenti.unicam.it (T.M.); carlo.polidori@unicam.it (C.P.); mariavittoria.micioni@unicam.it (M.V.M.D.B.) 2 ASUR Marche AV5, 63100 Ascoli Piceno, Italy; zaira.maraia@sanita.marche.it (Z.M.); benedetta.ruggeri@sanita.marche.it (B.R.); laura.armillei@sanita.marche.it (L.A.); irene.pomilio@sanita.marche.it (I.P.) * Correspondence: isidoro.mazzoni@sanita.marche.it; Tel.: +39-3396229445 05 5 2022 5 2022 11 9 258004 4 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Introduction: During the 2019 Coronavirus pandemic (COVID-19), a concern emerged regarding a possible correlation between the severe form of SARS-CoV-2 infection and administration of ACE-Inhibitors (ACE-I) and Sartans (ARB), since long-term use of these drugs may potentially result in an adaptive response with up-regulation of the ACE 2 receptor. Given the crucial role of ACE2, being the main target for virus entry into the cell, the potential consequences of ACE2 up-regulation have been a source of debate. The aim of this retrospective cohort study on COVID-19-positive patients who died is to investigate whether previous long-term exposure to ACE-I and/or ARB was associated with higher mortality due to COVID-19 infection, compared to all other types of drug treatment. Methods: We analysed the clinical and demographic data of 615 patients hospitalized for COVID-19 at the two hospitals of the Vasta Area n.5, between March 2020 and April 2021. Among them, 86 patients, treated with ACE-Is and/0 ARBs for about 12 months, died during hospitalization following a diagnosis of acute respiratory failure. Several quantitative and qualitative variables were recorded for all patients by reading their medical records. Results: The logistic model showed that the variables that increase mortality are age and comorbid diseases. There were no demonstrable mortality effects with ACE-I and ARB intake. Conclusions: The apparent increase in morbidity in patients with COVID-19 who received long-term treatment with ACE-I or ARB is not due to the drugs themselves, but to the conditions associated with their use. ACE-Inhibitors Sartans SARS-CoV-2 COVID-19 mortality This research received no external funding. The Pharmaceutical department of ASUR MARCHE AV5, for research projects and pharmacovigilance funds, provided support for open access. ==== Body pmc1. Introduction The Coronavirus Disease 19 (COVID-19) infection is a global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). In the Marche Region from 2019 to 2021, COVID-19 infected 112,470 people, causing the death of 3061 people. SARS-CoV-2 is genetically very similar to SARS-CoV-1, the virus that caused the epidemic in 2003, and both microorganisms use angiotensin-converting enzyme-2 (ACE-2) receptors for entry into the body’s cells [1]. The viral Spike protein, also called the S protein (target of antibodies produced by vaccines), located on the outer surface of the virus binds to the ACE-2 receptor. Binding appears to take place between residues 272 and 537 of the viral S protein [2]. The entry of the virus into the cell via the ACE-2 receptor would be much slower and more difficult if it were not ‘helped’ by certain proteases. Several studies suggest that certain proteases located on the cell surface, in very close proximity to the ACE-2 receptor, facilitate virus entry into the cell. In particular, the serine protease TMPRSS2 (transmembrane protease serine 2, a member of the Hep-sin-TMPRSS subfamily) is a transmembrane proteolytic enzyme, which structurally and functionally is part of the ACE-2 receptor (although it is stoichiometrically separated from the enzymatic site of the receptor itself). It is TMPRSS2 that ‘attacks’ the S1 unit of the viral S protein and, through its enzymatic activity, detaches it from the S2 unit. After detachment, the viral S2 unit fuses with the cell and the transfer of the viral content into the cell takes place via this unit [2,3,4]. This enzymatic activity (detachment of the S1 unit) increases virus entry into the cell via the ACE-2 receptor by a factor of almost 100. Based on this, it can be assumed that increased expression of surface proteases within the ACE-2 receptor in the pulmonary alveolar area could help explain the virus’ greater tendency to cause severe bronchioloalveolar infections compared to similar virus strains. 1.1. Up-Regulation of the ACE-2 Receptor in Patients Treated with ACE-I and ARBs The use of ACE-I and angiotensin II receptor blockers (ARBs) may increase the expression of ACE-2 receptors, thereby increasing vulnerability to SARS-CoV infection [5]. Other authors, however, suggest that these drugs may confer a protective effect, citing evidence that ACE-2 would reduce acute lung injury (ALI) [6]. ACE-2 is expressed in many systems, such as endothelial cells of the lung and the vascular system. [7]. ACE-I and ARB drugs are essential for the treatment of hypertension, chronic kidney disease, heart failure and myocardial infarction. In this clinical setting, strong concern has been raised about a potential detrimental effect of ACE-I and ARB, but similarly abrupt discontinuation of these drugs has been linked to worsening heart failure, dilated cardiomyopathy, destabilization of blood pressure control and increased mortality rates. During the first wave of the pandemic in Italy in March 2020, in the compilation of its weekly reports on the characteristics of patients who died, the Istituto Superiore di Sanità (ISS) drew attention to the use of ACE-I and ARB drugs, highlighting the problem of treatment interruption. The conclusion still indicated by the ISS is the following: “the current evidence does not support the interruption of drug treatment with ACE-I and ARB or the switch to other antihypertensives; therefore, treatment should be continued, as stressed by the various scientific societies and regulatory agencies”. The same problem, whether or not to suspend treatment, has been at the centre of numerous requests from hospital and territorial doctors in the Area Vasta n.5 to the local Pharmacovigilance Centre, since they represent the most widely used drugs in the treatment of hypertension and heart failure. The hypothesis that ACE-I and ARBs may increase patients’ vulnerability to SARS-CoV-2 infection is based on experimental models. Exposure to both ACE-I and ARBs increased ACE-2 expression in the kidney, myocardium and vessels of the rat [8,9,10]. In humans, it was observed that ACE-2 mRNA expression was higher in the myocardium and intestinal tissues of ACE-I users, but not in patients taking ARBs [11,12,13]. In contrast, urinary ACE-2 levels were elevated in ARB users, but not in patients taking ACE-I [14]. 1.2. Down-Regulation and Role of ACE-2 in Viral Infections Studies with SARS-CoV and MERS-CoV have shown that, as a result of virus binding, the ACE-2 receptor is down-regulated [15]. This is a biological phenomenon common to various situations of receptor stimulation (e.g., stimulation of beta-adrenergic receptors), which induces down-regulation of the same receptors. In other words, the ACE-2 receptor ‘attacked’ by the virus internalizes (we might say ‘locks itself in’ inside the cell) and thus almost stops ‘working’ [16]. The implications of ACE-2 down-regulation are potentially important. A non-functioning ACE-2 receptor, or a nearly non-functioning ACE-2 receptor, implies a reduced transformation of angiotensin II into angiotensin1–7. As is well known, the ACE-2 enzyme is a dipeptidyl-carboxypeptidase that breaks the bond between proline and the carboxy-terminal phenylalanine’s residue of angiotensin II, consequently transforming angiotensin II (8 amino acids) into angiotensin1–7 (7 amino acids). On the other hand, ACE breaks the bond between phenylalanine and histidine of angiotensin I, therefore transforming angiotensin I (10 amino acids) into angiotensin II (8 amino acids). Angiotensin1–7 has completely “opposite” effects (vasodilation, antiproliferative and anti-fibrotic effects) to those of angiotensin II at angiotensin II type 1 receptors (AT1 receptors). It is clear that a down-regulation of ACE-2 receptors would imply a lower synthesis of angiotensin1–7 and, in parallel, a greater availability of angiotensin II for binding to AT1 receptors. In order to understand the importance of the degradation of angiotensin II by ACE2 receptors, it is essential to review the biological effects of angiotensin II. Angiotensin II is not only a potent vasoconstrictor and stimulant of aldosterone release but has also been shown to be capable of causing adverse reactions such as endothelial dysfunction, myocardial hypertrophy, oxidative stress and increased coagulation. In the lungs, the downregulation of ACE2 receptors would facilitate the progression of the inflammatory and hypercoagulation processes exerted by angiotensin II, which is insufficiently counteracted by angiotensin1–7 [17]. Indeed, a study carried out in mice with acute respiratory distress syndrome induced by sepsis or acid aspiration clearly demonstrated that ACE-2 receptors, as well as angiotensin II type 2 receptors (AT2 receptors), protect these animals from lung injury (pulmonary oedema and reduced function) [18]. This study also showed that ARBs, by blocking AT1 receptors, reduce lung injury induced by sepsis or acid aspiration [18]. Furthermore, the administration of recombinant human ACE-2 attenuated lung injury [18]. Another important study in laboratory animals showed that SARS-CoV, via the S protein, clearly reduces the expression of the ACE-2 enzyme, which increases angiotensin II and worsens lung lesions [15]. These were significantly attenuated by the administration of ARB [15]. An Italian group has shown that angiotensin1–7, whose synthesis is blocked by down-regulation of ACE-2 receptors, significantly reduces inflammatory lung lesions and subsequent fibrosis in experimental models of lung damage. The same group also demonstrated in an animal model that the administration of angiotensin1–7 reduces the diaphragmatic damage (contractile dysfunction and atrophy) commonly observed during mechanical ventilation [19]. Overall, these data suggest that the downregulation of ACE-2 receptors due to virus contact induces a reduction in angiotensin1–7 and an increase in angiotensin II, with consequent deleterious pro-inflammatory effects, particularly in the lungs. We now know that age and the presence of comorbidities are important risk factors for the progression of COVID-19 disease into severe forms. Some conditions, such as heart failure and/or hypertension, are associated with dysregulation of the renin-angiotensin-aldosterone system (RAAS) and ACE2 deficiency. Downregulation of the ACE2 receptor is associated with alveolar wall thickening, edema and recruitment of inflammatory cells. These clinical events underlie the pathophysiological mechanism of SARS-CoV-2 [20]. The aim of this retrospective cohort study on COVID-positive patients that died in the hospitals of Area Vasta n.5 of the Marche Region is to investigate whether previous long-term exposure to ACE-I and/or ARB was associated with an increased mortality due to COVID-19 infection, compared to other drug treatments. 2. Materials and Methods We analyzed the clinical, demographic and pharmacological data of 615 hospitalized patients, COVID-19 positive, detected by the SARS-CoV-2 Real-time polymerase chain reaction (RT-PCR) laboratory test. All the patients studied were resident in the province of Ascoli Piceno, corresponding to the territory of Area Vasta n.5, Marche Region. The study population was characterized by 164 patients with SARS-CoV-2 who died during hospitalization from March 2020 to April 2021 with the diagnosis of death: “acute respiratory failure in SARS-CoV-2 positive patient”. COVID-19 positive patients who died of other causes (e.g., stroke, heart attack) were excluded. Among the deceased, 86 patients had been treated with ACE-Is and/or ARBs for 12 months. The clinical data were extracted from the “Primary Care” database available at the hospitals and territorial services of the Ascoli Piceno and San Benedetto del Tronto Vasta Area n.5. In addition to the medical records, “Primary Care” also indicated that the patient was positive for SARS-CoV-2 by RT-PCR. The pharmaceutical data relating to the use of drugs were extracted from the Apoteke Gold management system, which contains the records of all prescriptions over the last 10 years. Apoteke Gold also allows the data of conventionalized, distributed on account or direct pharmaceutical prescriptions to be processed, divided or aggregated, allowing routine epidemiological drug analysis, using the classification system Anatomical Therapeutic Chemical (ATC). Using the patients’ tax code, we extracted the pharmacological treatments from 1 January 2019 until the date of death. Additionally, through the pathology exemption code, we identified previous diseases. The data can be interlinked individually by identifying them with their tax code. The data were analysed by means of two types of statistical analysis: uni- and multivariate analyses. Firstly, descriptive analysis was carried out in order to give a concise representation of the results of the observations. For quantitative variables, counts and percentages were reported. To compare the distribution of the variables between the groups, the chi-square test was used. Finally, multivariate logistic regression was used to estimate the probability of death as a function of the other observed variables (age, the presence of one, two or three concomitant diseases, sex, use of ACE-I and ARB). Only coefficients with a p value below the 5% significance threshold were considered statistically significant. Statistical analyses were carried out using STATA software (Stata Corp. College Station, TX, USA). 3. Results During the pandemic, 615 patients were admitted to the hospitals of Vasta Area n.5 with a diagnosis of COVID-19 pneumonia (principal diagnosis) or COVID-19 respiratory distress syndrome (secondary diagnosis). The demographic and clinical characteristics of the study sample are shown in Table 1. We stratified the severity of the disease by subdividing the patients according to the department of hospital admission. As far as comorbidities are concerned, the sample is very heterogeneous and therefore includes a wide range of diseases. In Table 2, it is possible to observe that in the majority of cases at least one pathology was present in comorbidity. It is also interesting to note that those affecting the cardiovascular system were the most prevalent in the population under analysis (Table 2). By means of a multivariate logistic regression model, it was possible to identify which variables were correlated with an increased probability of death following SARS-CoV-2 infection. Using the linear logistic model, considering death as dependent factor and as explanatory variable age, the presence of one, two or three concomitant pathologies, gender and therapies, results are strongly dependent on presence of concomitant diseases and age. Therapies and sex do not explain the dependent response. In Table 3, it can be seen that those patients with two concomitant diseases are 2.5 times more likely to die (p = 0.006) and those with three concomitant diseases are 6.6 times more likely to die (p = 0.000). The model also shows that as age increases, the probability of dying increases by 1.08 (p = 0.000). Treatment, sex and a comorbid condition are irrelevant because the p value is not statistically significant. 4. Discussion At the beginning of the pandemic, there was concern that the use of ACE-I and ARBs could be harmful in patients with COVID-19, because these long-term drugs have the potential to increase ACE-2 receptor expression and thus lead to a greater likelihood of progression to severe COVID-19 and death [21]. Experimental evidence that ACE-Is and ARBs increase the expression of ACE-2 comes from preclinical studies. Ferrario et al. observed an up-regulation of ACE2 in the cardiac tissue of Lewis rats, while Soler et al. found an increased expression of ACE-2 in renal arterioles [22,23]. In addition to the up-regulation of ACE2, another concern for the use of these drugs in patients with COVID-19 relates to the potential increase in levels of bradykinin, which is knows to be metabolized by ACE. Bradykinin could contribute to the exacerbation of the inflammatory phase by increasing vascular permeability [21]. Data on the outcome of patients who died in the hospitals of Vasta Area n.5 showed a higher mortality rate among users of RAAS inhibitors than among all decedents. However, when other variables were taken into account, it became apparent that the main determinants of mortality might be the older age (p = 0.000) and the presence of two or three comorbid conditions (p = 0.006; p = 0.000), rather than RAAS inhibition itself. In agreement with recent positions taken by many scientific societies, including the European Society of Cardiology, the American Heart Association, the Italian Society of Cardiology, the Italian Society of Hypertension and the Italian Society of Pharmacology, it is possible to speculate that the discontinuation, even temporarily, of ACE-I or ARB in all patients, who are taking them to prevent possible future deaths from SARS-CoV-2, is not supported by convincing scientific evidence. The presence of previous chronic diseases influences the prognosis in people with COVID-19. However, it is not only chronic respiratory disease that determines progression to worse outcomes, but also comorbid diseases of other organs. COVID-19 is a condition that also affects the endothelium of pulmonary vessels, triggering thromboembolic events. Pulmonary inflammation can become systemic and involve other organs (heart, brain, kidneys) leading to multi-organ dysfunction and death. In this context, patients with cardiovascular diseases, diabetes and obesity are more vulnerable and the probability of death from COVID-19 increases among them. 5. Conclusions The results of our epidemiological analysis confirm that there is no correlation between COVID-19 mortality and treatment with ACE inhibitors or ARBs. The data presented above show that the higher mortality rate in patients treated with RAAS inhibitors is due to the presence of diseases for which these drugs are indicated. Our data support the recommendations of several scientific societies to continue these treatments in all patients and confirm the indications of the Pharmacovigilance Office of Area Vasta 5 not to suspend treatment in patients with COVID-19 infection. One of the main limitations of our analysis is the scale of the study; this study was conducted as a double-center study with a limited sample size, despite the apparently higher mortality rate in treated patients. However, this work can contribute, in agreement with other findings produced globally, to eliminate the empirical concern of clinical practitioners. Nevertheless, the strength of the present analysis includes the presence of patients treated for more than 12 months with these drugs compared to previous studies. Author Contributions All authors were involved in the planning and design of the study. All were involved in the interpretation of the results and revision of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement As this is a retrospective observational study, consensus is not required. Informed Consent Statement This study is retrospective research, conducted on already available data of deceased patients. Thus, it is not possible to obtain consent. The authors processed the data and publish the work ensuring the patient confidentiality and the data security using alphanumeric code for each subject. The authors are authorized to process sensitive data. Data Availability Statement Data and material are available from the corresponding author. Conflicts of Interest The authors state that there is no conflict of interest. jcm-11-02580-t001_Table 1 Table 1 Characteristics of the patients under study. Total Patients (n = 615) Deceased Untreated (n = 78) Deceased Treated (n = 86) Average age 70.9 68.2 74.6 Range age 31–100 31–100 46–97 Male Average age 366 (59.5%) 68.9 39 (43.3%) 77.7 51 (56.7%) 80 Female Average age 249 (40.5%) 73.7 39 (52.7%) 81.4 35 (47.3) 83.8 Intensive therapy 96 (15.6%) 20 (25.6%) 26 (30.2%) Semi-intensive therapy 128 (20.8%) 13 (16.7%) 25 (29.1%) Other ordinary department 391 (63.6%) 45 (57.7%) 35 (40.7%) jcm-11-02580-t002_Table 2 Table 2 Comorbid diseases in study sample. Total Patients (n = 615) Deceased Untreated (n = 78) Deceased Treated (n = 86) p No concomitant disease 140 (22.8%) 8 (10.3%) 7 (8.1%) 0.076 One concomitant disease 239 (38.9%) 32 (41%) 2 (2.3%) 0.263 Two concomitant diseases 172 (28%) 24 (31%) 34 (39.5%) 0.227 Three concomitant diseases 64 (39.5%) 14 (18%) 23 (26.7%) 0.456 Diabetes 107 (17.4%) 10 (13%) 20 (23.3%) Hypertension 86 (14%) 8 (10.3%) 6 (7%) Heart failure 59 (9.6%) 7 (9%) 27 (31.4%) Atrial fibrillation 54 (8.8%) 12 (15.4%) 12 (14%) Obesity 38 (6.2%) 5 (6.4%) 11 (12.8%) Renal failure 15 (2.4%) 6 (7.7%) 4 (4.6%) Chronic obstructive pulmonary disease 25 (4.1%) 1 (1.3%) 0 jcm-11-02580-t003_Table 3 Table 3 Logistic regression analysis. Variables Odd Ratio Std. Err. z p 95% Conf. Interval One concomitant disease 1.71 0.57 1.61 0.108 0.88 3.31 Two concomitant diseases 2.54 0.86 2.73 0.006 1.30 4.96 Three concomitant diseases 6.61 2.65 4.71 0.000 3.01 14.52 Age 1.08 0.01 8.04 0.000 1.06 1.11 Therapy 1.07 0.23 0.31 0.755 0.70 1.62 Sex 0.95 0.20 −0.22 0.826 0.63 1.44 Std. Err.: Standard Error; Conf.: Confidence. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Zhou P. Yang X.-L. Wang X.-G. Hu B. Zhang L. Zhang W. Si H.-R. Zhu Y. Li B. Huang C.-L. A pneumonia outbreak associated with a new coronavirus of probable bat origin Nature 2020 579 270 273 10.1038/s41586-020-2012-7 32015507 2. Wiersinga W.J. Rhodes A. Cheng A.C. Peacock S.J. Prescott H.C. Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review JAMA 2020 324 782 793 10.1001/jama.2020.12839 32648899 3. Hoffmann M. Kleine-Weber H. Schroeder S. Krüger N. Herrler T. Erichsen S. Schiergens T.S. Herrler G. Wu N.H. Nitsche A. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor Cell 2020 181 271 280.e8 10.1016/j.cell.2020.02.052 32142651 4. Shulla A. Heald-Sargent T. Subramanya G. Zhao J. Perlman S. Gallagher T. A Transmembrane Serine Protease Is Linked to the Severe Acute Respiratory Syndrome Coronavirus Receptor and Activates Virus Entry J. Virol. 2011 85 873 882 10.1128/JVI.02062-10 21068237 5. Diaz J.H. Hypothesis: Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers may increase the risk of severe COVID-19 J. Travel Med. 2020 27 taaa041 10.1093/jtm/taaa041 32186711 6. Imai Y. Kuba K. Rao S. Huan Y. Guo F. Guan B. Yang P. Sarao R. Wada T. Leong-Poi H. Angiotensin-converting enzyme 2 protects from severe acute lung failure Nature 2005 436 112 116 10.1038/nature03712 16001071 7. Hamming I. Timens W. Bulthuis M.L.C. Lely A.T. Navis G.J. van Goor H. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis J. Pathol. 2004 203 631 637 10.1002/path.1570 15141377 8. Sukumaran V. Veeraveedu P.T. Gurusamy N. Lakshmanan A.P. Yamaguchi K. Ma M. Suzuki K. Nagata M. Takagi R. Kodama M. Olmesartan attenuates the development of heart failure after experimental autoimmune myocarditis in rats through the modulation of ANG 1–7 mas receptor Mol. Cell. Endocrinol. 2011 351 208 219 10.1016/j.mce.2011.12.010 22200414 9. Sukumaran V. Tsuchimochi H. Tatsumi E. Shirai M. Pearson J.T. Azilsartan ameliorates diabetic cardiomyopathy in young db/db mice through the modulation of ACE-2/ANG 1-7/Mas receptor cascade Biochem. Pharmacol. 2017 144 90 99 10.1016/j.bcp.2017.07.022 28789938 10. Burchill L.J. Velkoska E. Dean R.G. Griggs K. Patel S.K. Burrell L.M. Combination renin-angiotensin system blockade and angiotensin-converting enzyme 2 in experi-mental myocardial infarction: Implications for future therapeutic directions Clin. Sci. 2012 123 649 658 10.1042/CS20120162 11. Luque M. Martin P. Martell N. Fernandez C. Brosnihan K.B. Ferrario C.M. Effects of captopril related to increased levels of prostacyclin and angiotensin-(1-7) in essential hyper-tension J. Hypertens. 1996 14 799 805 10.1097/00004872-199606000-00017 8793704 12. Nicin L. Abplanalp W.T. Mellentin H. Kattih B. Tombor L. John D. Schmitto J.D. Heineke J. Emrich F. Arsalan M. Cell type-specific expression of the putative SARS-CoV-2 receptor ACE2 in human hearts Eur. Heart J. 2020 41 1804 1806 10.1093/eurheartj/ehaa311 32293672 13. Vuille-Dit-Bille R.N. Camargo S.M. Emmenegger L. Sasse T. Kummer E. Jando J. Hamie Q.M. Meier C.F. Hunziker S. Forras-Kaufmann Z. Human intestine luminal ACE2 and amino acid transporter expression increased by ACE-inhibitors Amino Acids 2015 47 693 705 10.1007/s00726-014-1889-6 25534429 14. Furuhashi M. Moniwa N. Mita T. Fuseya T. Ishimura S. Ohno K. Shibata S. Tanaka M. Watanabe Y. Akasaka H. Urinary angiotensin-converting enzyme 2 in hypertensive patients may be increased by olmesartan, an angiotensin II receptor blocker Am. J. Hypertens. 2015 28 15 21 10.1093/ajh/hpu086 24842388 15. Kuba K. Imai Y. Rao S. Gao H. Guo F. Guan B. Huan Y. Yang P. Zhang Y. Deng W. A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury Nat. Med. 2005 11 875 879 10.1038/nm1267 16007097 16. Glowacka I. Bertram S. Herzog P. Pfefferle S. Steffen I. Muench M.O. Simmons G. Hofmann H. Kuri T. Weber F. Differential Downregulation of ACE2 by the Spike Proteins of Severe Acute Respiratory Syndrome Coronavirus and Human Coronavirus NL63 J. Virol. 2010 84 1198 1205 10.1128/JVI.01248-09 19864379 17. Verdecchia P. Cavallini C. Spanevello A. Angeli F. The pivotal link between ACE2 deficiency and SARS-COV-2 infection Eur. J. Intern. Med. 2020 76 14 20 10.1016/j.ejim.2020.04.037 32336612 18. Zambelli V. Sigurtà A. Rizzi L. Zucca L. DelVecchio P. Bresciani E. Torsello A. Bellani G. Angiotensin-(1–7) exerts a protective action in a rat model of ventilator-induced diaphragmatic dysfunction Intensive Care Med. Exp. 2019 7 8 10.1186/s40635-018-0218-x 30659381 19. Fang L. Karakiulakis G. Roth M. Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? Lancet Respir. Med. 2020 8 e21 10.1016/S2213-2600(20)30116-8 32171062 20. Verdecchia P. Cavallini C. Spanevello A. Angeli F. The pivotal link between ACE2 deficiency and SARS-COV-2 infection: One year later Eur. J. Intern. Med. 2021 93 28 34 34588140 21. Ferrario C.M. Jessup J. Chappell M.C. Averill D.B. Brosnihan K.B. Tallant E.A. Diz D.I. Gallagher P.E. Effect of Angiotensin-Converting Enzyme Inhibition and Angiotensin II Receptor Blockers on Cardiac Angiotensin-Converting Enzyme 2 Circulation 2005 111 2605 2610 10.1161/CIRCULATIONAHA.104.510461 15897343 22. Soler M.J. Ye M. Wysocki J. William J. Lloveras J. Batlle D. Localization of ACE2 in the renal vasculature: Amplification by angiotensin II type 1 receptor blockade using telmisartan Am. J. Physiol. Physiol. 2009 296 F398 F405 10.1152/ajprenal.90488.2008 19004932 23. Nussberger J. Cugno M. Amstutz C. Cicardi M. Pellacani A. Agostoni A. Early reports Plasma bradykinin in angio-oedema Lancet 1998 351 1693 1697 10.1016/S0140-6736(97)09137-X 9734886

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091839 nutrients-14-01839 Article Prevalence of Sarcopenia in Women with Breast Cancer https://orcid.org/0000-0002-3158-450X Morlino Delia 1 https://orcid.org/0000-0002-3258-7374 Marra Maurizio 1* https://orcid.org/0000-0002-1408-209X Cioffi Iolanda 1 https://orcid.org/0000-0003-2332-4836 Santarpia Lidia 1 De Placido Pietro 2 Giuliano Mario 2 De Angelis Carmine 2 Carrano Simone 2 Verrazzo Annarita 2 Buono Giuseppe 2 Naccarato Marianna 1 https://orcid.org/0000-0003-3152-3130 Di Vincenzo Olivia 1 https://orcid.org/0000-0002-3241-1897 Speranza Enza 1 De Placido Sabino 2 Arpino Grazia 2 https://orcid.org/0000-0003-4224-7821 Pasanisi Fabrizio 1 1 Internal Medicine and Clinical Nutrition Unit, Department of Clinical Medicine and Surgery, Federico II University Hospital, 80131 Naples, Italy; delia.morlino@unina.it (D.M.); iolanda.cioffi@unina.it (I.C.); lidia.santarpia@unina.it (L.S.); marianna.naccarato@unina.it (M.N.); olivia.divincenzo@unina.it (O.D.V.); enza.speranza@unina.it (E.S.); pasanisi@unina.it (F.P.) 2 Oncology Unit, Department of Clinical Medicine and Surgery, Federico II University Hospital, 80131 Naples, Italy; pietrodep91@gmail.com (P.D.P.); m.giuliano@unina.it (M.G.); carmine.deangelis1@unina.it (C.D.A.); sim1.carrano@gmail.com (S.C.); annarita.verrazzo@virgilio.it (A.V.); giuseppe.buono88@gmail.com (G.B.); deplacid@unina.it (S.D.P.); grazia.arpino@unina.it (G.A.) * Correspondence: marra@unina.it; Tel.: +39-081-746-2333; Fax: +39-081-746-2376 28 4 2022 5 2022 14 9 183928 3 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Sarcopenia is a common finding in patients with cancer and potentially influences the patient’s outcome. The aim of this study was to evaluate the prevalence of sarcopenia, according to the European Working Group on Sarcopenia in Older People, in a sample of women with breast cancer (BC) and a BMI lower than 30 kg/m2. This cross-sectional study was conducted in patients with BC, stage 0-III, and receiving therapy for BC; the women were recruited at the Department of Clinical Medicine and Surgery, Federico II University, Naples, Italy. A control group with similar age and BMI was selected from the internal database. Anthropometry, bioimpedance analysis (BIA) and hand grip strength (HGS) were measured to detect sarcopenia. A total of 122 patients (mean age 49.3 ± 11.0 years, BMI 24.6 ± 3.0 kg/m2) and 80 healthy controls were analyzed. Sarcopenia was found in 13.9% patients with BC, while none of the subjects in the control group was sarcopenic. By comparing BC patients with and without sarcopenia and the control group, the fat-free mass of sarcopenic BC patients were significantly lower than those of both non-sarcopenic BC patients and the control (p < 0.05). The phase angle was also significantly lower in sarcopenic patients (−0.5 degrees, p = 0.048) than in the control group. Considering the prevalence of sarcopenia in patients with BC, our findings suggest the usefulness of body composition and HGS evaluation for early screening of sarcopenia to reduce the risk of associated complications. breast cancer sarcopenia body composition bioimpedance analysis (BIA) hand grip strength (HGS) phase angle (PhA) This research received no external funding. ==== Body pmc1. Introduction Breast cancer (BC) is the most frequently diagnosed carcinoma and the second leading cause of cancer death among females worldwide [1]. According to a recent publication by the American Cancer Society, BC incidence rate has been increasing by 0.3% per year, but its death rate continues to decline, falling 40% over the last thirty years [2]. According to the Italian Society of Medical Oncology, BC incidence has increased slightly, also in Italy; in 2020, approximately 55,000 new cases of BC were recorded (+0.3% per year), whereas mortality decreased (−0.8%) thanks to the improved screening programs and high-quality multidisciplinary treatment of the disease [3]. In the last decade, body composition measurements have gained greater attention in oncology research, since sarcopenia is a common finding in patients with cancer, potentially influencing chemotherapy toxicity and the patient outcome [4]. Different parameters can be evaluated to assess body composition by bioimpedance analysis (BIA), such as fat-free mass (FFM), fat mass (FM) and phase angle (PhA). The latter is a raw BIA parameter, inversely correlated with disease severity, inflammation and malnutrition in several clinical conditions, as well as in cancer patients. PhA is claimed to be a good nutritional marker, especially for cancer patients [5], and also represents an indicator of sarcopenia [6]. Sarcopenia is a syndrome characterized by the progressive reduction in both muscle mass and muscle strength, which is accompanied by a reduction in the quality of life and an increased risk of adverse outcomes [7]. Despite being typical of the elderly population, sarcopenia also occurs earlier in life due to the presence of acute or chronic diseases [8,9]. In 2010, the European consensus [10] distinguished primary sarcopenia from secondary sarcopenia. The first condition occurs when no other clear etiologies are found, and advanced aging is the main cause, whereas secondary sarcopenia is associated with some chronic clinical conditions (inflammatory and chronic diseases, cancer, obesity, malnutrition). Recently, the European Working Group on Sarcopenia in Older People (EWGSOP2) published a revised consensus on the definition and diagnosis of sarcopenia, by focusing on low muscle strength, also called dynapenia, as a key characteristic of sarcopenia that is measured by hand grip strength (HGS) [8,11,12]. Indeed, the diagnosis of sarcopenia is confirmed by reduced appendicular skeletal muscle mass (ASM), in addition to dynapenia. Different techniques can be used for the evaluation of muscle mass, such as dual X-ray absorptiometry (DXA) [13], computed tomography (CT) scanning [14] or (BIA) [15,16,17,18,19]. In the literature, sarcopenia is described as an unfavorable condition for patients with cancer disease because its presence is associated with more severe clinical conditions and longer hospital stays following surgery [20]. Additionally, it has been reported that the presence of sarcopenia can be used as a prognostic factor for mortality in both non-metastatic and metastatic patients with BC [21]. In a recent meta-analysis by Zhang et al. [22], BC patients, classified as sarcopenic had a greater mortality risk than non-sarcopenic BC patients. Therefore, it is crucial to evaluate the presence of sarcopenia before starting cancer treatment in all patients, since it is strongly associated with chemotherapy-induced toxicity, post-operative complications and poor survival [23]. Indeed, low muscle mass at cancer diagnosis is associated with poor survival in patients with solid tumors [24]. To our knowledge, there are only a few studies in the literature that have specifically screened the presence of sarcopenia in Italian women with BC, according to the EWGSOP2. Thus, the objective of this study was to evaluate the prevalence of sarcopenia in a sample of Italian women with BC and a BMI lower than 30 kg/m2. 2. Patients and Methods 2.1. Patients This is a cross-sectional study of baseline data collected from an ongoing randomized controlled trial in pre-and postmenopausal Italian women with stage 0-III BC, candidates for surgery and adjuvant/neoadjuvant therapy. Patients were consecutively recruited at the Oncology Unit, Department of Clinical Medicine and Surgery, Federico II University, Naples Italy, from September 2018 to June 2021. Caucasian patients were consecutively included according to the following criteria: women, age ≥ 18 years, 18.5 ≤ BMI < 30 kg/m2 and available past medical history. Patients with metastatic cancer, BMI ≥ 30 kg/m2 and severe clinical conditions were excluded. In addition, a control group with similar age and BMI was selected from our database (Caucasian healthy women underwent a nutritional evaluation, aged between 35 and 75 years) with anthropometric and body composition data from the last two years. The study was conducted in accordance with the Declaration of Helsinki, and it was approved by the local Ethics Committee of Federico II University (prot. n. 280/17). All patients gave their informed consent to participate in the study. 2.2. Anthropometry, Body Composition and Muscle Strength Assessment Body weight and stature were measured according to standardized methods. Body weight was measured to the nearest 0.1 kg using a platform beam scale and stature to the nearest 0.5 cm using a stadiometer (Seca 709; Seca, Hamburg, Germany). Body weight and stature were used to calculate BMI (weight in kilograms divided by stature in meters squared). Body composition was evaluated by the BIA method. BIA was performed using Human Im Plus II (DS Medica-Milan, Italy) at a room temperature of 22–25 °C in the 12 h fasted state after voiding the bladder and cleaning the surface of the skin to adhere the electrodes. Participants were asked to remain in the supine position for at least 10–15 min before starting the measurement, with lower limbs and upper limbs slightly abducted at 45° and 30°, respectively, to avoid any contact between the extremities and the trunk. Resistance (R) and reactance (Xc) were measured at 50 kHz; PhA (degrees) = arctan (Xc/R) × (180/π) was calculated. Body composition assessment, namely, FFM and FM, was estimated using the Sun BIA equation [25]. ASM was calculated using the Sergi BIA equation [26]. Muscle strength was assessed by HGS, measured in both the dominant and nondominant hands with a Jamar dynamometer (JAMAR, Roylan, UK). Patients performed the test standing with their upper limbs by their sides, and they were instructed to squeeze a dynamometer at maximal voluntary isometric contraction. The measurement was repeated three times alternately on both sides (dominant and nondominant hand), with 1 min apart to avoid fatigue, and the dominant hand was determined by asking subjects if they were right- or left-handed. The mean value was recorded in kilograms [27]. 2.3. Definition of Sarcopenia Sarcopenia was diagnosed according to the EWSGOP2 criteria. This new revised consensus suggests that the first parameter of sarcopenia is dynapenia evaluated with the HGS method (recorded in kilograms). The diagnosis of sarcopenia is confirmed by reduced ASM in addition to dynapenia and/or low physical performance. According to the cutoff points of Dodds RM et al. [28], dynapenia was diagnosed if HGS < 16 kg for females [8]. Low ASM was defined using the Studenski cutoffs: <15 kg for women [29]. Both conditions (dynapenia + low ASM) were considered for the diagnosis of sarcopenia. Instead, pre-sarcopenia was considered in the presence of either HGS value < 16 kg or ASM < 15 kg. 3. Statistical Analysis The data obtained were analyzed by the SPSS (Version 27.0, IBM Corp, Armonk, NY, USA) software. Results are presented as the mean ± standard deviation (SD), and statistical significance was defined as p < 0.05. Differences between two groups (patients with BC and control group) were assessed by unpaired t-tests, while data were compared between four groups (sarcopenic BC patients, pre-sarcopenic BC patients, non-sarcopenic BC patients and control group) by using non-parametric analysis (Mann–Whitney test); the false discovery rate approach was performed to account for the multiple comparisons, and significant level (p < 0.05) was adjusted according to Benjamini and Hochberg [30]. HGS and ASM were adjusted for age, body weight and stature (UNIANOVA test). Categorical variables were compared by using the chi-square test. 4. Results A total of 142 patients with BC participated in this study, but 20 were ruled out for the following reasons: 3 subjects did not meet the inclusion criteria and 17 left for personal reasons. Thus, 122 patients, were included in this analysis. The anthropometric characteristics of patients with BC are summarized in Table 1. Patients with BC showing a mean age of 49.3 ± 11.0 years, an average body weight of 63.4 ± 7.4 kg. A total of 66 (54%) out of 122 patients had a BMI varying from 18.5 to 24.9 kg/m2, while 56 (46%) had a BMI range from 25 to 30 kg/m2. Additionally, as reported above, a control group with similar age and BMI to the patients was selected. In detail, healthy women aged between 35 and 75 years, with a body weight between 46 and 89 kg, of whom 45 (56.2%) were normal weight and 35 (43.8%) were overweight (Table 1). A total of 45.9% of patients with BC were in the postmenopausal state, while 45.1% were pharmacologically induced. The histological characteristics of the tumor are reported in Table 2. Regarding cancer stage, 2.5% were stage 0, 41.2% were stage I, 39.5% were stage II, and 16.8% were stage III. A total of 69.6% of patients underwent quadrantectomy, and 30.4% underwent mastectomy. A total of 77% were estrogen receptor (ER) positive and 70.5% progesterone receptor (PR) positive, while 50.8% were human epidermal growth factor receptor 2 (HER2) positive. A total of 18.9% and 37.7% of the patients had started neoadjuvant and adjuvant chemo-radiotherapy, respectively, and 13.9% of women were in hormone therapy. Muscle mass and muscle strength parameters, as well as PhA, are described in Table 3. Differences were observed between patients with BC and controls in terms of both quantitative (FM) and qualitative parameters (PhA). As such, patients with BC had lower values of PhA and HGS, and higher percentage of FM than controls. Based on the EWGSOP2 guidelines, the prevalence of sarcopenia in the patients with BC was 13.9% (17/122), while none of the subjects in the control group had sarcopenia. In addition, among patients with BC, 31.1% (38/122) were pre-sarcopenic due to the presence of either HGS value < 16 kg or ASM < 15 kg. The remaining 54.9% (67/122) of patients were classified as non-sarcopenic, having both values in the normal ranges. Data concerning anthropometry, body composition, PhA, muscle mass and strength between sarcopenic, pre-sarcopenic, non-sarcopenic BC patients and controls are shown in Table 4. By comparing the results among the four groups, we found that sarcopenic patients with BC were older than non-sarcopenic and control group patients and had significantly lower body weight than in the other groups (Table 4). Regarding body composition, differences were observed between sarcopenic BC patients compared to non-sarcopenic BC patients and control group in terms of both quantitative (FFM) and qualitative muscle parameters (PhA); in detail, the differences of PhA in sarcopenic BC patients compared to non- sarcopenic BC patients and control group were (−0.4 degrees, p = 0.045 and −0.5 degrees, p = 0.048), respectively. Instead, the FM expressed in kilograms was significantly lower in sarcopenic BC patients than in non-sarcopenic BC (−4.4 kg, p = 0.024). As in patients with sarcopenia, the group with pre-sarcopenia had both lower FFM and ASM than non-sarcopenic patients (−4.91 kg, p < 0.001) and control group (−3.47 kg, p < 0.001), respectively. Additionally, after adjusting for age, body weight and stature, both HGS and ASM remain confirmed to be significantly lower in patients with sarcopenia than in other groups. Finally, menopausal state, tumor stage and therapy do not influence the presence and the grade of sarcopenia. 5. Discussion The presence of sarcopenia in patients with cancer has been associated with reduced effectiveness of anti-neoplastic therapies, post-operative complications and poorer overall survival [23]. The poor outcomes may be related to higher drug toxicity rates in sarcopenic patients, which in turn may lead to dose reductions and delivering lower doses of effective cancer treatments. These phenomena could possibly be explained by the well-known association between lean and muscle mass and pharmacokinetics parameters, such as drug distribution, metabolism and the clearance of chemotherapeutic agents [24]. Due to the negative impact of sarcopenia on the outcome of cancer patients [24], we evaluated its prevalence in a population of women with early-stage BC cancer, by measuring body composition by BIA and muscle strength by HGS. BIA is a portable, easy-to-use and inexpensive method for estimating fat mass (FM) and fat-free mass (FFM) in clinical settings [31,32,33,34]. The PhA, the most clinically relevant impedance parameter, is an index of cell membrane integrity and vitality, and it provides crucial information on cellular health and soft tissue hydration [35,36,37]. Low PhA values are generally associated with impaired muscle function, poor physical performance and low survival in different acute and chronic diseases, including cancer [36,37,38,39]. The compromised conditions of our patients with BC are also confirmed by the lower PhA values than in the controls. Given its non-invasivity, BIA can be performed whenever necessary, without the limitations of other exams using radiation, such as DXA or CT scan, thus allowing a strict monitoring of the patient body composition. On the other hand, abdominal CT scan is not recommended for early stages of BC [40]. For this reason, the use of CT scan would not have allowed the inclusion of a large population of patients with BC [41]. The prevalence of sarcopenia in patients with BC was assessed according to the EWGSOP2 criteria. Sarcopenia was found in 13.9% of patients with BC and was absent in the control group. Moreover, a considerable number (31.1%) of patients with BC were pre-sarcopenic, showing similar characteristics to sarcopenic patients. These prevalence data are not irrelevant if we consider that the evaluated patients are relatively young, normal or overweight and with early-stage BC. The influencing factors, such as tumor stage, breast surgery, physical activity, may play a significant role [42]. Based on a recent systematic review [23], the prevalence of sarcopenia in patients with different types of cancer, evaluated before starting the treatment, was 38.6% of patients; unfortunately, only three studies [43,44,45] focused on a consensual definition of sarcopenia based on the EWGSOP published in 2010. To our knowledge, the presence of sarcopenia according to the new EWGSOP2 guidelines in Italian patients with early-stage BC was evaluated only in one study by Bellieni et al. [46]. The study assessed sarcopenia in Italian older women with early-stage BC, obtaining a prevalence of 43%; the higher values found in that population can probably be explained by the older age of patients. In the literature, many studies analyzed the prevalence of sarcopenia in patients with cancer using different validated techniques for body composition analysis (DXA, CT or BIA) [8]. Previously, Oflazoglu et al. evaluated the prevalence of sarcopenia using the BIA method in a Turkish population with different types of cancers: breast, colorectal, pancreaticobiliary, genitourinary, lung, and head and neck [47]. The prevalence of sarcopenia was 16.7% in all patients (77/461), and it was 11.5% for those with BC (17/148). These results are similar to our data, but they considered the EWGSOP guidelines [10] and not the updated ones [8]. Similarly, the prevalence of sarcopenia using the previous criteria was evaluated in 98 survivors of BC (age > 60 years) among residents in Bogotà [48], showing a percentage of 22.4%. Another study conducted in a Brazilian population and using both BIA and HGS showed that the prevalence of sarcopenia was 18.6% in 60 oncologic patients and 10% in patients with BC using EWGSOP [49]. Recently, Ueno et al. [50] found a prevalence of sarcopenia of 12.2% in Asian patients with BC, by using the CT scan to measure skeletal muscle mass index. The prevalence of sarcopenia was similar to our study, although the method to assess body composition was different, and HGS was not evaluated. Based on these controversial results and considering the widespread use of the previous guidelines for diagnosing sarcopenia, we analyzed our data according to the EWGSOP criteria as well [10]; sarcopenia was detected in 24 patients with BC, with a prevalence of 19.7%, which was higher than that observed by the EWGSOP2 definition [8]. Interestingly, this result was similar to the study conducted by Benavides-Rodríguez et al. [48], although the patients were older, but higher than Oflazoglu et al. [47] and Harter et al. [49]. Less is known about the body composition of women with early-stage BC, probably because the absolute recurrence and mortality rate in this population, to date, remains extremely low [51]. Considering the prevalence of sarcopenia observed in our patients, in our view, it is important to define the nutritional needs and physical activity programs to improve skeletal quality and strength (FFM, HGS and PhA). Body composition and the levels of physical activity should be assessed at baseline and periodically re-evaluated during the entire course of the treatment and over time, in the long-term follow-up, to suggest specific strategies (physical activity programs, aerobic exercise, strength training, resistance exercise therapy), which have been shown to reverse sarcopenia and were associated with improved quality of life [16,52,53,54]. Our study had some limitations. Firstly, this is a cross-sectional study, thus only baseline results are reported; follow-up data are ongoing and will be shortly available. Secondly, although BIA is a valid and reliable tool for body composition analysis in clinical practice [16], it is not a gold-standard method; however, as already discussed, BIA allowed us to evaluate a larger group of patients with early-stage BC and to accurately follow up the possible changes of body composition during the therapeutic course, thereby guaranteeing the best chemotherapy dosing and tolerance. Finally, patients BC with BMI ≥ 30 kg/m2 were excluded according to the study protocol, and the control group was retrospectively obtained from our dataset, and these may be considered further limitations. 6. Conclusions In conclusion, we found that the overall proportion of sarcopenic and pre-sarcopenic patients in our population was somewhat higher than expected in a healthy population of women [41]. The use of BIA in association with HGS is relevant for identifying sarcopenia in BC patients, playing an important role for the patient’s outcome, in particular for early recognition, prompt intervention and periodical reassessment of the risk of sarcopenia and its associated complications. Author Contributions Conceptualization, M.M. and D.M.; Methodology, M.M. and I.C.; Formal Analysis, D.M. and M.M.; Investigation, D.M., I.C., M.N., O.D.V., E.S., S.C., P.D.P., M.G., C.D.A., A.V. and G.B.; Data Curation, D.M., I.C. and M.N.; Writing—Original Draft Preparation, D.M.; Writing—Review and Editing, I.C. and L.S.; Visualization, F.P.; Supervision, G.A., S.D.P. and F.P. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted in accordance with the Declaration of Helsinki and approved by the Medical Ethics Committee of Federico II University (prot. n. 280/17). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors report no conflict of interest in this work. nutrients-14-01839-t001_Table 1 Table 1 Characteristics of breast cancer (BC) patients and the control group. BC Patients (n = 122) Control Group (n = 80) Age years 49.4 ± 11.0 48.2 ± 10.0 Weight kg 63.4 ± 7.4 63.5 ± 12.1 Stature cm 161 ± 7 161 ± 6 BMI kg/m2 24.6 ± 3.0 24.5 ± 4.1 Data are expressed as the mean ± SD. BMI = Body mass index. p values non-significant for all variables. nutrients-14-01839-t002_Table 2 Table 2 Clinical characteristics of patients with BC. Tumor Stage n (%) * 0 3 2.5 I 49 41.2 II 47 39.5 III 18 16.8 Axillary lymph node metastasis (%) ** Yes 48 41.7 No 67 58.3 Estrogen receptor status (%) + Positive 91 77.1 Negative 27 22.9 Progesterone receptor status (%) & Positive 79 70.5 Negative 33 29.5 Human epidermal growth factor receptor 2 (%) § Positive 60 50.8 Negative 58 49.2 Type of therapy (%) No therapy yet 36 29.5 Neoadjuvant chemotherapy 23 18.9 Adjuvant chemotherapy 46 37.7 Hormone therapy 17 13.9 Type of surgery (%) $ Quadrantectomy 80 69.6 Mastectomy 35 30.4 Menopausal status (%) Premenopausal 11 9.0 Postmenopausal 56 45.9 Induced menopause 55 45.1 Data unavailable for n (%):* 3 (2.4%); ** 7 (5.7%); + 4 (3.2%); & 10 (8.1%); § 4 (3.2%); $ 7 (5.7%). nutrients-14-01839-t003_Table 3 Table 3 Body composition and hand grip strength measurements. BC Patients (n = 122) Control Group (n = 80) FFM kg 42.7 ± 3.8 43.7 ± 4.9 FM kg 20.7 ± 5.1 19.8 ± 8.6 FM % 32.3 ± 5.1 * 29.9 ± 8.2 ASM kg 15.8 ± 1.5 16.3 ± 2.1 PhA degrees 5.5 ± 0.5 * 5.7 ± 0.6 HGS kg 19.2 ± 5.6 * 21.0 ± 4.2 Data are expressed as the mean ± SD. * p < 0.05 FFM = Fat-Free Mass; FM = Fat Mass; PhA = Phase Angle; HGS = Hand Grip Strength; ASM = Appendicular Skeletal Muscle Mass. nutrients-14-01839-t004_Table 4 Table 4 Individual characteristics and body composition of sarcopenic, pre-sarcopenic and non-sarcopenic patients and the control group. BC Patients Control Group Sarcopenic n = 17 Pre-Sarcopenic n = 38 Non-Sarcopenic n = 67 n = 80 Age years 55.8 ± 12.5 a 51.4 ± 11.3 b 46.6 ± 9.1 48.2 ± 10.0 Weight kg 56.1 ± 4.8 c 60.4 ± 5.5 b 67.0 ± 6.8 d 63.5 ± 12.1 Stature cm 155 ± 7 a 158 ± 6 a 164 ± 6 d 161 ± 6 BMI kg/m2 23.4 ± 2.8 24.4 ± 3.1 25.0 ± 2.9 24.5 ± 4.1 FFM kg 38.6 ± 1.9 c 40.2 ± 2.5 a 45.1 ± 2.9 d 43.7 ± 4.9 FM kg 17.5 ± 4.2 b 20.2 ± 4.7 21.9 ± 5.2 19.8 ± 8.6 FM % 30.8 ± 5.3 33.0 ± 5.2 32.3 ± 5.0 29.9 ± 8.2 ASM kg 14.1 ± 0.8 c 14.9 ± 0.9 a 16.8 ± 1.2 16.3 ± 2.1 PhA degrees 5.2 ± 0.5 a 5.5 ± 0.5 5.6 ± 0.5 5.7 ± 0.6 HGS kg 13.0 ± 2.0 c 16.9 ± 4.1 a 22.0 ± 4.2 21.0 ± 4.2 Data are expressed as the mean ± SD. Non-parametric test was used for statistical analysis a p < 0.05 vs. non-sarcopenic BC and control group; b p < 0.05 vs. non-sarcopenic BC; c p < 0.05 vs. pre-sarcopenic BC, non-sarcopenic BC and control group, d p < 0.05 vs. control group; FFM = Free-Fat Mass; FM = Fat Mass; PhA = Phase Angle; HGS = Hand Grip Strength; ASM = Appendicular Skeletal Muscle Mass. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Torre L.A. Bray F. Siegel R.L. Ferlay J. Lortet-Tieulent J. Jemal A. Global cancer statistics, 2012 CA Cancer J. Clin. 2015 65 87 108 10.3322/caac.21262 25651787 2. DeSantis C.E. Ma J. Gaudet M.M. Newman L.A. Miller K.D. Goding Sauer A. Jemal A. Siegel R.L. Breast cancer statistics, 2019 CA Cancer J. Clin. 2019 69 438 451 10.3322/caac.21583 31577379 3. AIOM-Associazione Italiana di Oncologia Medica Available online: https://snlg.iss.it/wp-content/uploads/2021/11/LG_260_mammella_agg2021.pdf (accessed on 1 March 2022) 4. Muss H.B. Berry D.A. Cirrincione C. Budman D.R. Henderson I.C. Citron M.L. Norton L. Winer E.P. Hudis C.A. Cancer and Leukemia Group B Experience. Toxicity of older and younger patients treated with adjuvant chemotherapy for node-positive breast cancer: The Cancer and Leukemia Group B Experience J. Clin. Oncol. 2007 25 3699 3704 10.1200/JCO.2007.10.9710 17704418 5. Da Silva B.R. Mialich M.S. Cruz L.P. Rufato S. Gozzo T. Jordao A.A. Performance of functionality measures and phase angle in women exposed to chemotherapy for early breast cancer Clin. Nutr. ESPEN 2021 42 105 116 10.1016/j.clnesp.2021.02.007 33745563 6. Hirose S. Nakajima T. Nozawa N. Katayanagi S. Ishizaka H. Mizushima Y. Matsumoto K. Nishikawa K. Toyama Y. Takahashi R. Phase Angle as an Indicator of Sarcopenia, Malnutrition, and Cachexia in Inpatients with Cardiovascular Diseases J. Clin. Med. 2020 9 2554 10.3390/jcm9082554 7. Goodpaster B.H. Park S.W. Harris T.B. Kritchevsky S.B. Nevitt M. Schwartz A.V. Simonsick E.M. Tylavsky F.A. Visser M. Newman A.B. The loss of skeletal muscle strength, mass, and quality in older adults: The health, aging and body composition study J. Gerontol. A Biol. Sci. Med. Sci. 2006 61 1059 1064 10.1093/gerona/61.10.1059 17077199 8. Cruz-Jentoft A.J. Bahat G. Bauer J. Boirie Y. Bruyère O. Cederholm T. Cooper C. Landi F. Rolland Y. Sayer A.A. Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended Group for EWGSOP2. Sarcopenia: Revised European consensus on definition and diagnosis Age Ageing 2019 48 16 31 Erratum in Age Ageing 2019, 48, 601 10.1093/ageing/afy169 30312372 9. Sammarco R. Marra M. Di Guglielmo M.L. Naccarato M. Contaldo F. Poggiogalle E. Donini L.M. Pasanisi F. Evaluation of Hypocaloric Diet with Protein Supplementation in Middle-Aged Sarcopenic Obese Women: A Pilot Study Obes. Facts 2017 10 160 167 10.1159/000468153 28528340 10. Cruz-Jentoft A.J. Baeyens J.P. Bauer J.M. Boirie Y. Cederholm T. Landi F. Martin F.C. Michel J.-P. Rolland Y. Schneider S.M. European Working Group on Sarcopenia in Older People. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People Age Ageing 2010 39 412 423 10.1093/ageing/afq034 20392703 11. Ibrahim K. May C. Patel H.P. Baxter M. Sayer A.A. Roberts H.C. A feasibility study of implementing grip strength measurement into routine hospital practice (GRImP): Study protocol Pilot Feasibility Stud. 2016 2 27 10.1186/s40814-016-0067-x 27965846 12. Alley D.E. Shardell M.D. Peters K.W. McLean R.R. Dam T.-T.L. Kenny A.M. Fragala M.S. Harris T.B. Kiel D. Guralnik J.M. Grip strength cutpoints for the identification of clinically relevant weakness J. Gerontol. Ser. A 2014 69 559 566 10.1093/gerona/glu011 13. Schaap L.A. van Schoor N.M. Lips P. Visser M. Associations of Sarcopenia Definitions, and Their Components, With the Incidence of Recurrent Falling and Fractures: The Longitudinal Aging Study Amsterdam J. Gerontol. Ser. A 2018 73 1199 1204 10.1093/gerona/glx245 29300839 14. Beaudart C. McCloskey E. Bruyère O. Cesari M. Rolland Y. Rizzoli R. Araujo De Carvalho I. Amuthavalli Thiyagarajan J. Bautmans I. Bertière M.-C. Sarcopenia in daily practice: Assessment and management BMC Geriatr. 2016 16 170 10.1186/s12877-016-0349-4 27716195 15. Aleixo G.F. Shachar S.S. Nyrop K.A. Muss H.B. Battaglini C.L. Williams G.R. Bioelectrical Impedance Analysis for the Assessment of Sarcopenia in Patients with Cancer: A Systematic Review Oncologist 2019 25 170 182 10.1634/theoncologist.2019-0600 32043785 16. Marra M. Sammarco R. De Lorenzo A. Iellamo F. Siervo M. Pietrobelli A. Donini L.M. Santarpia L. Cataldi M. Pasanisi F. Assessment of Body Composition in Health and Disease Using Bioelectrical Impedance Analysis (BIA) and Dual Energy X-Ray Absorptiometry (DXA): A Critical Overview Contrast Media Mol. Imaging 2019 2019 3548284 10.1155/2019/3548284 31275083 17. Marra M. Sammarco R. De Filippo E. Caldara A. Speranza E. Scalfi L. Contaldo F. Pasanisi F. Prediction of body composition in anorexia nervosa: Results from a retrospective study Clin. Nutr. 2018 37 1670 1674 10.1016/j.clnu.2017.07.016 28847608 18. De Rosa E. Santarpia L. Marra M. Sammarco R. Amato V. Onufrio M. de Simone G. Contaldo F. Pasanisi F. Preliminary evaluation of the prevalence of sarcopenia in obese patients from Southern Italy Nutrition 2015 31 79 83 10.1016/j.nut.2014.04.025 25441590 19. Di Vincenzo O. Marra M. Di Gregorio A. Pasanisi F. Scalfi L. Bioelectrical impedance analysis (BIA) -derived phase angle in sarcopenia: A systematic review Clin. Nutr. 2021 40 3052 3061 10.1016/j.clnu.2020.10.048 33183880 20. Pérez Camargo D.A. Allende Pérez S.R. Verastegui Avilés E. Rivera Franco M.M. Meneses García A. Herrera Gómez Á. Urbalejo Ceniceros V. Assessment and Impact of Phase Angle and Sarcopenia in Palliative Cancer Patients Nutr. Cancer 2017 69 1227 1233 10.1080/01635581.2017.1367939 29083245 21. Villaseñor A. Ballard-Barbash R. Baumgartner K. Baumgartner R. Bernstein L. McTiernan A. Neuhouser M.L. Prevalence and prognostic effect of sarcopenia in breast cancer survivors: The HEAL Study J. Cancer Surviv. 2012 6 398 406 10.1007/s11764-012-0234-x 23054848 22. Zhang X.-M. Dou Q.-L. Zeng Y. Yang Y. Cheng A.S.K. Zhang W.-W. Sarcopenia as a predictor of mortality in women with breast cancer: A meta-analysis and systematic review BMC Cancer 2020 20 172 10.1186/s12885-020-6645-6 32131764 23. Pamoukdjian F. Bouillet T. Levy V. Soussan M. Zelek L. Paillaud E. Prevalence and predictive value of pre-therapeutic sarcopenia in cancer patients: A systematic review Clin. Nutr. 2018 37 1101 1113 10.1016/j.clnu.2017.07.010 28734552 24. Shachar S.S. Williams G. Muss H.B. Nishijima T.F. Prognostic value of sarcopenia in adults with solid tumours: A meta-analysis and systematic review Eur. J. Cancer 2016 57 58 67 10.1016/j.ejca.2015.12.030 26882087 25. Sun G. French C.R. Martin G.R. Younghusband B. Green R.C. Xie Y.-G. Mathews M. Barron J.R. Fitzpatrick D.G. Gulliver W. Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population Am. J. Clin. Nutr. 2005 81 74 78 10.1093/ajcn/81.1.74 15640463 26. Sergi G. De Rui M. Veronese N. Bolzetta F. Berton L. Carraro S. Bano G. Coin A. Manzato E. Perissinotto E. Assessing appendicular skeletal muscle mass with bioelectrical impedance analysis in free-living Caucasian older adults Clin. Nutr. 2015 34 667 673 10.1016/j.clnu.2014.07.010 25103151 27. Lim J.P. Yew S. Tay L. Chew J. Yeo A. Ismail N.H. Ding Y.Y. Lim W.S. Grip Strength Criterion Matters: Impact of Average Versus Maximum Handgrip Strength on Sarcopenia Prevalence and Predictive Validity for Low Physical Performance J. Nutr. Health Aging 2020 24 1031 1035 10.1007/s12603-020-1515-0 33155633 28. Dodds R.M. Syddall H.E. Cooper R. Benzeval M. Deary I.J. Dennison E.M. Der G. Gale C.R. Inskip H.M. Jagger C. Grip strength across the life course: Normative data from twelve british studies PLoS ONE 2014 9 e113637 10.1371/journal.pone.0113637 25474696 29. Studenski S.A. Peters K.W. Alley D.E. Cawthon P.M. McLean R.R. Harris T.B. Ferrucci L. Guralnik J.M. Fragala M.S. Kenny A.M. The FNIH sarcopenia project: Rationale, study description, conference recommendations, and final estimates J. Gerontol. A Biol. Sci. Med. Sci. 2014 69 547 558 10.1093/gerona/glu010 24737557 30. Benjamini Y. Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing J. R. Stat. Soc. Ser. B 1995 57 289 300 10.1111/j.2517-6161.1995.tb02031.x 31. Lukaski H.C. Kyle U.G. Kondrup J. Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: Phase angle and impedance ratio Curr. Opin. Clin. Nutr. Metab. Care 2017 20 330.e9 10.1097/MCO.0000000000000387 28548972 32. Norman K. Wirth R. Neubauer M. Eckardt R. Stobäus N. The bioimpedance phase angle predicts low muscle strength, impaired quality of life, and increased mortality in old patients with cancer J. Am. Med. Dir. Assoc. 2015 16 173.e17 173.e22 10.1016/j.jamda.2014.10.024 25499428 33. Marra M. Cioffi I. Sammarco R. Montagnese C. Naccarato M. Amato V. Contaldo F. Pasanisi F. Prediction and evaluation of resting energy expenditure in a large group of obese outpatients Int. J. Obes. 2017 41 697 705 10.1038/ijo.2017.34 28163316 34. Santarpia L. Marra M. Montagnese C. Alfonsi L. Pasanisi F. Contaldo F. Prognostic significance of bioelectrical impedance phase angle in advanced cancer: Preliminary observations Nutrition 2009 25 930 931 10.1016/j.nut.2009.01.015 19500944 35. Cioffi I. Marra M. Imperatore N. Pagano M.C. Santarpia L. Alfonsi L. Testa A. Sammarco R. Contaldo F. Castiglione F. Assessment of bioelectrical phase angle as a predictor of nutritional status in patients with Crohn’s disease: A cross sectional study Clin. Nutr. 2020 39 1564 1571 10.1016/j.clnu.2019.06.023 31303525 36. Morlino D. Cioffi I. Marra M. Di Vincenzo O. Scalfi L. Pasanisi F. Bioelectrical Phase Angle in Patients with Breast Cancer: A Systematic Review Cancers 2022 14 2002 10.3390/cancers14082002 35454908 37. Cioffi I. Imperatore N. Di Vincenzo O. Santarpia L. Rispo A. Marra M. Testa A. Contaldo F. Castiglione F. Pasanisi F. Association between Health-Related Quality of Life and Nutritional Status in Adult Patients with Crohn’s Disease Nutrients 2020 12 746 10.3390/nu12030746 32168964 38. Morlino D. Marra M. Cioffi I. Sammarco R. Speranza E. Di Vincenzo O. De Caprio C. De Filippo E. Pasanisi F. A proposal for reference values of hand grip strength in women with different body mass indexes Nutrition 2021 87–88 111199 10.1016/j.nut.2021.111199 39. Gupta D. Lammersfeld C.A. Vashi P.G. King J. Dahlk S.L. Grutsch J.F. Lis C.G. Bioelectrical impedance phase angle as a prognostic indicator in breast cancer BMC Cancer 2008 8 249 10.1186/1471-2407-8-249 18727837 40. Gradishar W.J. Anderson B.O. Abraham J. Aft R. Agnese D. Allison K.H. Blair S.L. Burstein H.J. Dang C. Elias A.D. Breast Cancer, Version 3. 2020, NCCN Clinical Practice Guidelines in Oncology J. Natl. Compr. Cancer Netw. 2020 18 452 478 10.6004/jnccn.2020.0016 41. Fukui J. White K. Frankland T.B. Oshiro C. Wilkens L. Weight changes according to treatment in a diverse cohort of breast cancer patients BMC Cancer 2021 21 1005 10.1186/s12885-021-08740-5 34496789 42. Tankó L.B. Movsesyan L. Mouritzen U. Christiansen C. Svendsen O.L. Appendicular lean tissue mass and the prevalence of sarcopenia among healthy women Metabolism 2002 51 69 74 10.1053/meta.2002.28960 11782875 43. Fukuda Y. Yamamoto K. Hirao M. Nishikawa K. Nagatsuma Y. Nakayama T. Tanikawa S. Maeda S. Uemura M. Miyake M. Sarcopenia is associated with severe postoperative complications in elderly gastric cancer patients undergoing gastrectomy Gastric Cancer 2016 19 986 993 10.1007/s10120-015-0546-4 26407875 44. Huang D. Wang S. Zhuang C. Zheng B.S. Lu J. Chen F. Zhou C. Shen X. Yu Z. Sarcopenia, as defined by low muscle mass, strength and physical performance, predicts complications after surgery for colorectal cancer Color. Dis. 2015 17 O256 O264 10.1111/codi.13067 26194849 45. Wang S.-L. Zhuang C.-L. Huang D.-D. Pang W.-Y. Lou N. Chen F.-F. Zhou C.-J. Shen X. Yu Z. Sarcopenia Adversely Impacts Postoperative Clinical Outcomes Following Gastrectomy in Patients with Gastric Cancer: A Prospective Study Ann. Surg. Oncol. 2015 23 556 564 10.1245/s10434-015-4887-3 26668085 46. Bellieni A. Fusco D. Sanchez A. Franceschini G. Di Capua B. Allocca E. Di Stasio E. Marazzi F. Tagliaferri L. Masetti R. Different Impact of Definitions of Sarcopenia in Defining Frailty Status in a Population of Older Women with Early Breast Cancer J. Pers. Med. 2021 11 243 10.3390/jpm11040243 33810556 47. Oflazoglu U. Alacacioglu A. Varol U. Kucukzeybek Y. Salman T. Taskaynatan H. Yildiz Y. Ozdemir O. Tarhan M. Prevalence and related factors of sarcopenia in newly diagnosed cancer patients Support. Care Cancer 2019 28 837 843 10.1007/s00520-019-04880-4 31161438 48. Benavides-Rodríguez L. García-Hermoso A. Rodrigues-Bezerra D. Izquierdo M. Correa-Bautista J.E. Ramírez-Vélez R. Relationship between Handgrip Strength and Muscle Mass in Female Survivors of Breast Cancer: A Mediation Analysis Nutrients 2017 9 695 10.3390/nu9070695 49. Härter J. Orlandi S.P. Gonzalez M.C. Nutritional and functional factors as prognostic of surgical cancer patients Support. Care Cancer 2017 25 2525 2530 10.1007/s00520-017-3661-4 28303380 50. Ueno A. Yamaguchi K. Sudo M. Imai S. Sarcopenia as a risk factor of severe laboratory adverse events in breast cancer patients receiving perioperative epirubicin plus cyclophosphamide therapy Support. Care Cancer 2020 28 4249 4254 10.1007/s00520-019-05279-x 31900607 51. Weinberg M.S. Shachar S.S. Muss H.B. Deal A.M. Popuri K. Yu H. Nyrop K.A. Alston S.M. Williams G.R. Beyond sarcopenia: Characterization and integration of skeletal muscle quantity and radiodensity in a curable breast cancer population Breast J. 2018 24 278 284 10.1111/tbj.12952 29139618 52. Klassen O. Schmidt M.E. Ulrich C.M. Schneeweiss A. Potthoff K. Steindorf K. Wiskemann J. Muscle strength in breast cancer patients receiving different treatment regimes J. Cachex-Sarcopenia Muscle 2016 8 305 316 10.1002/jcsm.12165 27896952 53. De Luca V. Minganti C. Borrione P. Grazioli E. Cerulli C. Guerra E. Bonifacino A. Parisi A. Effects of concurrent aerobic and strength training on breast cancer survivors: A pilot study Public Health 2016 136 126 132 10.1016/j.puhe.2016.03.028 27161493 54. Meneses-Echávez J.F. Correa-Bautista J.E. González-Jiménez E. Río-Valle J.S. Elkins M.R. Lobelo F. Ramírez-Vélez R. The Effect of Exercise Training on Mediators of Inflammation in Breast Cancer Survivors: A Systematic Review with Meta-analysis Cancer Epidemiol. Biomark. Prev. 2016 25 1009 1017 10.1158/1055-9965.EPI-15-1061 27197276

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095161 ijms-23-05161 Editorial The Role of Sugars in Plant Responses to Stress and Their Regulatory Function during Development https://orcid.org/0000-0003-3023-4871 Jeandet Philippe 1* Formela-Luboińska Magda 2 https://orcid.org/0000-0001-8014-1644 Labudda Mateusz 3 https://orcid.org/0000-0003-4186-0202 Morkunas Iwona 2* 1 Research Unit “Induced Resistance and Plant Bioprotection”, Department of Biology and Biochemistry, Faculty of Sciences, University of Reims, EA 4707–USC INRAe 1488, SFR Condorcet FR CNRS 3417, P.O. Box 1039, CEDEX 02, 51687 Reims, France 2 Department of Plant Physiology, Poznań University of Life Sciences, Wołynska 35, 60-637 Poznań, Poland; magda.formela-luboinska@up.poznan.pl 3 Department of Biochemistry and Microbiology, Institute of Biology, Warsaw University of Life Sciences-SGGW, Nowoursynowska 159, 02-776 Warsaw, Poland; mateusz_labudda@sggw.edu.pl * Correspondence: philippe.jeandet@univ-reims.fr (P.J.); iwona.morkunas@up.poznan.pl (I.M.) 05 5 2022 5 2022 23 9 516128 4 2022 04 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This research received no external funding. ==== Body pmcDue to their role as energy and carbon sources and their regulatory functions, sugars influence all phases of the plant life cycle, interact with other signaling molecules, including phytohormones, and control plant growth and development [1,2,3]. The levels of sugars in plant cells, their transport, utilization, and storage are precisely regulated and strongly dependent on cell physiological activity, plant organs, environmental conditions, circadian rhythms, and plant developmental stages [4]. The perception of the signals induced by sugars can take place in the apoplast and during transport across membranes or inside the cell, e.g., in the cytosol, and may involve glucose and sucrose membrane transporters, invertases, and hexokinases (HXK) as conserved glucose sensors, and changes in the AMP to ATP ratio [5,6,7]. Rolland et al. [1] reported that sugar signals activate multiple HXK-dependent and HXK-independent pathways and provided evidence of the effects of sugar signals on transcription, translation, protein stability, and enzymatic activity. In turn, Snf1-related kinases (SnRKs), calcium-dependent protein kinases (CDPKs), the mitogen-activated protein kinase (MAPK) cascade, specific protein phosphatases (PPs), phytohormones, and calcium ions are involved in sugar-induced signal transduction [1]. The plant’s ability to monitor and respond to sugar cellular levels may act as a controlling mechanism, integrating the influence of environmental conditions with internal developmental programs directly regulated by phytohormones [8,9]. Many environmental stimuli, the intensity of which may vary according to climate change, may influence various biochemical processes, frequently interfering with the balanced partitioning of sugars within plant cells and their transport from source organs to sink organs. The main currency in sugar exchanges in higher plants is represented by sucrose, the major product of photosynthesis in the leaves, which is transported throughout the plant, which involves sucrose uptake transporters (SUT/SUC: active sucrose/H+ symporters) and export transporters SWEETs (hexose and sucrose transporters) [10,11]. Sucrose can be degraded by several enzymes (invertases and sucrose synthase) or resynthesized from its degradation products in the so-called “sucrose cycle” [12]. Numerous studies have also shown that sugars play a key role in plant defense responses to various abiotic and biotic stress factors [13,14]. It is well documented that sugars are not only the main substrates utilized in respiration processes supplying energy for cellular defense responses against pathogens, but also provide the carbon skeleton for the synthesis of defense compounds including secondary metabolites such as flavonoids, stilbenes, and lignins [15,16]. In addition, saccharides such as sucrose, glucose, fructose, and trehalose represent metabolic signaling molecules in host plant cells, which induce the expression of many genes, namely defense genes [17,18,19]. A high level of sugars in plant tissues enhances the plant immune response against fungal pathogens. Sugars probably function as priming molecules, leading to pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) and effector-triggered immunity (ETI) in plants [20]. It has been demonstrated that the presence of sucrose and monosaccharides enables plants to stimulate efficient defense mechanisms against fungal pathogens. This is consistent with the novel concepts of “sweet immunity” and “sweet priming” [21,22], postulating that saccharides play a key role as priming agents, inducing the resistance of higher plants to both biotic and abiotic stresses. Recent progress made by Van den Ende’s group in sugar research has also provided important evidence regarding the contribution of fructans in the adaptation of plants to abiotic stress and in plant immune responses to pathogens (see this Special Issue). The papers presented hereafter in this Special Issue thus illustrate the central role of sugars in plant development and in the improvement of crop yields as well as in the defense responses to stresses and the impact of environmental and climatic conditions on the relationship between sugar metabolism and yielding. Other papers regarding the involvement of sugars as signaling molecules in the processes regulating growth and development are also presented. Sucrose is one of the main products of photosynthesis in leaves. Once synthesized, it is transported through the phloem from leaves to all parts of the plant. Sucrose not only plays the role of a carbon carrier between source and sink tissues, but also acts as a long-distance signal for the control of many processes involved in plant development such as apical dominance and root growth. It also intervenes in the production/consumption balance of plant carbohydrates. In their review article, Aluko et al. [23] discussed the utilization of sucrose for crop yield improvement, analyzed how alterations of the source to sink sugar balance may impede physiological and developmental processes, and explored factors that control photoassimilate partitioning within the entire plant, that is, translocation mechanisms and the utilization of sucrose, at the sink organs. The influence of various environmental parameters on sugar transport (CO2, light, temperature, drought, and nutrient availability) was also discussed. Sugar transporters (SUTs and SWEETs) and sucrose are involved in mitigating environmental stresses such as elevated CO2, cold, and drought. A significant part of this article also described the strategies dedicated to increasing the efficiency of photosynthetic assimilation and integrated approaches to crop-yield improvement. The adjustment of plant growth and development goes through sophisticated regulatory processes involving intricate crosstalk between sugars and hormones. In their paper, Wang et al. [24] described the complex convergent and divergent inter-relationships that take place between cytokinin signaling and sugars in many aspects of the plant life cycle, including seed development and germination, leaf senescence, root and shoot branching, as well as flowering. The interplay between sugars and cytokinins may lead to antagonistic or synergistic interactions depending on the morphogenetic and the developmental phases of the plant. Synergistic effects were described in flowering, shoot branching, and functioning of the shoot meristem though antagonistic interactions occurred between sugars and cytokinins in the functioning of the root meristem. The complexity of the crosstalk between sugars and cytokinins in controlling plant development and morphogenesis was thus analyzed in this paper. Grape berries can accumulate exceptionally high sugar contents, rising from 10 g/kg of fresh weight at the beginning of the maturation time to hundreds of grams per kilogram at full maturity. In their review article, Walker et al. [25] paid attention to both sucrose metabolism and transport in grapevines. The role of various enzymes involved in sucrose breakdown and sucrose resynthesis such as sucrose synthase, neutral and acid invertases within the so-called “sucrose cycle”, sucrose translocation within and between organs, as well as its associated metabolism in grape pericarp during ripening, were described thoroughly in the light of a cross-species comparison including tomato, potato, carrot, maize, and apple. The accumulation, metabolism, and transport of sugars, and especially those of sucrose, are strongly dependent on both environmental and physical parameters such as temperature, CO2, photoperiod, and the circadian rhythm as well as interactions with plant hormones. Four articles discussed the implication of cold, photoperiod, and hormonal control in soluble sugar and sucrose contents in relation to plant development phases [26,27,28,29]. Acclimation to cold exposure requires changes in carbohydrate metabolism such as the accumulation of soluble sugars and starch hydrolysis in chloroplasts. The work of Orzechowski et al. [26] discussed the very early response of leaves of potato plants exposed to cold stress (2 °C for 12 h), decoupling the effects of light and temperature. The expression of enzymes involved in starch degradation, starch-related dikinases (StGND and StPWD) acting on starch turnover, as well as glucan phosphorylase, amylase, invertase, and disproportioning enzyme 2 activities were increased following adaptation to cold exposure. A modification of the carbohydrate metabolism in leaves leading to an augmentation of soluble sugar accumulation was also demonstrated. Morphological and developmental features in plants imply complex sugar regulation processes. Li et al. [27] showed that the exogenous application of the synthetic plant cytokinin 6-benzyladenine but not the natural gibberellin GA3, and a long-day photoperiod, but not temperature, induce runner formation in an octaploid cultivated strawberry variety from South Korea. This asexual propagation trait was mediated through the upregulation of the soluble sugar content. A proteomic analysis also revealed that a total of 16 proteins were differentially expressed in the runner-activated strawberry plants versus plants without runners, of which, the major protein group related to carbohydrate metabolism and photosynthesis (sucrose synthase 2 and glucan endo-1,3-β-glucosidase). This study thus clearly evidenced the positive correlation that exists between soluble sugar content and runner induction in strawberry. Micro RNA172 (miR172) as well as micro RNA156 (miR156) are involved in the regulation of the transitions that occur between different developmental stages in plants. Garg et al. [28] demonstrated that tomato plants silenced in the sucrose transporter gene StSUT4 display higher levels of miR172 as compared to the wild type and display similar phenotypical traits regarding flowering induction and tuberization as miR172-overexpressing plants. Moreover, the contents of miR172 were increased by high levels of sucrose, suggesting the sucrose-inducible character of miR172 expression. A strong interlink was described between the sugar status of potato plants and the downstream pathways regulating flowering induction and tuberization, including miR172 and StSUT4. Improving grain yield represents a challenge in wheat production. Thus, addressing the diurnal patterns of sugar transport in wheat during the period of grain filling is of major concern. Al-Sheikh Ahmed et al. [29] investigated the possible diurnal changes in water-soluble carbohydrates that occur in correlation with different expression levels of the sucrose transporter TaSUT1 gene in two different wheat varieties, Kauz and Westonia. It was suggested that a higher expression of TaSUT1 in leaves that correlates well with the high sucrose levels observed in the variety Kauz can contribute to a grain weight increase in this variety. The first identification of the sucrose transporter family from pomegranate (Punica granatum L.) was reported in the work of Poudel et al. [30]. From a phylogenetic tree analysis, pomegranate SUT genes were found to be divided into three major groups varying in the number of exons and introns. The promoter regions of these genes were characterized by their richness in MYB cis-elements. Finally, a functional analysis of the SUT gene PgL0145810-1 revealed its involvement in the regulation of the seed developmental process, especially the seed hardness trait in pomegranate, likely playing a role in lignin synthesis. In addition to their fundamental roles as donors of carbon skeletons and substrates for respiration processes, sugars are also implicated in intricated plant network responses to biotic and abiotic stresses. Briefly, sugars intervene in the regulation of signaling molecules related with plant defenses, plant immunity, the phenomena of priming, and sweet immunity. Several papers published in this Special Issue are dedicated to these aspects [31,32,33,34]. The Morkunas group published two successive works on the role of sugars both in the mechanisms of pathogenicity of Fusarium oxysporum f. sp. lupini to yellow lupine and in the regulation of the levels of endogenous signaling molecules during the defense responses of that plant to F. oxysporum. In a first approach, Formela-Luboińska et al. [31] showed that the production of ergosterol, a membrane fungal sterol taken here as a fungal indicator of the mycelial growth of F. oxysporum as well as levels of the mycotoxin moniliformin, were decreased in embryo axes of yellow lupine infected with this fungus and cultured in media under a sugar deficit. In addition, soluble sugars were found to provoke an inhibition of the sporulation of this pathogen, showing they can intervene in limiting the development and spread of systemic pathogens such as F. oxysporum. The interplay of sugars in the mechanisms of pathogenicity on yellow lupine, such as a possible catabolic repression by sugars of fungal polygalacturonase gene expression, was also discussed. In a second article, Formela-Luboińska et al. [32] emphasized the role of sucrose and various monosaccharides as signaling compounds for the regulation of phytohormones, abscisic acid (ABA), ethylene, salicylic acid (SA), and its glucoside (SAG), as well as phenylalanine ammonia lyase (PAL), benzoic acid 2-hydroxylase (BA2H), and superoxide dismutase (SOD) activities in embryo axes of yellow lupine challenged with the hemibiotrophic fungus, F. oxysporum. Positive correlations were observed between the sugar levels and the post-infectious production of SA, SAG, ABA, and ethylene, as well as the increased activity of PAL, BA2H, and SOD, with all of these parameters participating in the defense responses of yellow lupine to F. oxysporum. Sugars contribute to plant immunity, with the so-called “sweet immunity” concept inferring that sugar metabolism and signaling are capable of boosting the defense responses of plants. Exogenous applications of structural carbohydrates were shown to improve plants’ resistance to pathogens, directly or through the stimulation of the defense mechanisms of plants themselves. The concept of sweet immunity was established via the effect of exogenous fructans regarding apple (Malus x domestica Borkh.) susceptibility to apple scab (Venturia inaequalis) in the work of Svara et al. [33]. The exogenous application of specific fructans and levans on apple leaves was shown to be able to reduce the development of this pathogen through a significant decrease in its sporulation. In addition, the direct inhibition of the fungal growth was observed in vitro on peptone dextrose agar plates supplemented with fructans. Levans thus boost the resistance of apple leaves to apple scab, although the mechanisms involved in this resistance remain unelucidated. A possible application of this technique for use in apple scab management in orchards was also discussed. Chitinases are known as crucial components of plant innate immunity. A CaChiIII7 chitinase gene, which takes part in the regulation of the hypersensitive response and defense of pepper (Capsicum annulum L.) to anthracnose (Colletotrichum acutatum) infection, was newly identified in the article of Ali et al. [34]. This gene, which possesses repeated chitin-binding domains, encodes a chitinase transcriptionally stimulated upon infection by C. acutatum. Moreover, this CaChiIII7 putative chitinase gene was shown to share high sequence homology with other chitinase families. The functional characterization of this chitinase was achieved through knockdown experiments of the CaChiIII7 gene in pepper plants, resulting in their increased susceptibility to C. acutatum and demonstrating the involvement of this new chitinase in pepper responses to anthracnose. All of these articles thus illustrate the central role played by sugars in the physiology, the development, and the defense responses of plants. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Rolland F. Baena-Gonzalez E. Sheen J. Sugar sensing and signaling in plants: Conserved and novel mechanisms Annu. Rev. Plant Biol. 2006 57 675 709 10.1146/annurev.arplant.57.032905.105441 16669778 2. Smeekens S. Ma J. Hanson J. Rolland F. Sugar signals and molecular networks controlling plant growth Curr. Opin. Plant Biol. 2010 13 273 278 10.1016/j.pbi.2009.12.002 20056477 3. Ciereszko I. Regulatory roles of sugars in plant growth and development Acta Soc. Bot. Pol. 2018 87 3583 10.5586/asbp.3583 4. Lemoine R. La Camera S. Atanassova R. Dédaldéchamp F. Allario T. Pourtau N. Bonnemain J.-L. Laloi M. Coutos-Thévenot P. Maurousset L. Source-to-sink transport of sugar and regulation by environmental factors Front. Plant Sci. 2013 4 272 10.3389/fpls.2013.00272 23898339 5. Halford N.G. Purcell P.C. Hardie D.G. Is hexokinase really a sugar sensor in plants? Trends Plant Sci. 1999 4 117 120 10.1016/S1360-1385(99)01377-1 10322544 6. Yu S.-M. Cellular and genetic responses of plants to sugar starvation Plant Physiol. 1999 121 687 693 10.1104/pp.121.3.687 10557216 7. Smeekens S. Sugar-induced signal transduction in plants Annu. Rev. Plant Physiol. Plant Mol. Biol. 2000 51 49 81 10.1146/annurev.arplant.51.1.49 15012186 8. León P. Sheen J. Sugar and hormone connections Trends Plant Sci. 2003 8 110 116 10.1016/S1360-1385(03)00011-6 12663220 9. Sakr S. Wang M. Dédaldéchamp F. Perez-Garcia M.D. Ogé L. Hamama L. Atanassova R. The sugar-signaling hub: Overview of regulators and interaction with the hormonal and metabolic network Int. J. Mol. Sci. 2018 19 2506 10.3390/ijms19092506 10. Chen L.-Q. Qu X.-Q. Hou B.-H. Sosso D. Osorio S. Fernie A.R. Frommer W.B. Sucrose efflux mediated by SWEET proteins as a key step for phloem transport Science 2012 335 207 211 10.1126/science.1213351 22157085 11. Xu Q. Chen S. Yunjuan R. Chen S. Liesche J. Regulation of sucrose transporters and phloem loading in response to environmental cues Plant Physiol. 2018 176 930 945 10.1104/pp.17.01088 29158330 12. Nguyen-Quoc B. Foyer C.H. A role for ‘futile cycles’ involving invertase and sucrose synthase in sucrose metabolism of tomato fruit J. Exp. Bot. 2001 52 881 889 10.1093/jexbot/52.358.881 11432905 13. Chen L.-Q. Hou B.-H. Lalonde S. Takanaga H. Hartung M.L. Qu X.-Q. Guo W.-J. Kim J.-G. Underwood W. Chaudhuri B. Sugar transporters for intercellular exchange and nutrition of pathogens Nature 2010 468 527 532 10.1038/nature09606 21107422 14. Keunen E. Peshev D. Vangronsveld J. Van Den Ende W. Cuypers A. Plant sugars are crucial players in the oxidative challenge during abiotic stress: Extending the traditional concept Plant Cell Environ. 2013 36 1242 1255 10.1111/pce.12061 23305614 15. Nabavi S. Samec D. Tomczyk M. Milella L. Russo D. Habtemariam S. Suntar I. Rastrelli L. Daglia M. Xiao J. Flavonoid biosynthetic pathways in plants: Versatile targets for metabolic engineering Biotechnol. Adv. 2020 39 107461 10.1016/j.biotechadv.2018.11.005 31678221 16. Jeandet P. Vannozzi A. Sobarzo-Sanchez E. Uddin M.S. Bru R. Martinez-Marquez A. Clément C. Cordelier S. Manayi A. Nabavi S.F. Phytostilbenes as agrochemicals: Biosynthesis, bioactivity, metabolic engineering and biotechnology Nat. Prod. Rep. 2021 28 1282 1329 10.1039/D0NP00030B 17. Morkunas I. Bednarski W. Kozłowska M. Response of embryo axes of germinating seeds of yellow lupine to Fusarium oxysporum Plant Physiol. Biochem. 2004 42 493 499 10.1016/j.plaphy.2004.05.007 15246062 18. Morkunas I. Marczak Ł. Stachowiak J. Stobiecki M. Sucrose stimulated accumulation of isoflavonoids as a defense response of lupine to Fusarium oxysporum Plant Physiol. Biochem. 2005 43 363 373 10.1016/j.plaphy.2005.02.011 15907688 19. Morkunas I. Narożna D. Nowak W. Samardakiewicz W. Remlein-Starosta D. Cross-talk interactions of sucrose and Fusarium oxysporum in the phenylpropanoid pathway and the accumulation and localization of flavonoids in embryo axes of yellow lupine J. Plant Physiol. 2011 168 424 433 10.1016/j.jplph.2010.08.017 21056513 20. Morkunas I. Ratajczak L. The role of sugar signaling in plant defense responses against fungal pathogens Acta Physiol. Plant. 2014 36 1607 1619 10.1007/s11738-014-1559-z 21. Bolouri Moghaddam M.R. Van den Ende W. Sugars and plant innate immunity J. Exp. Bot. 2012 63 3989 3998 10.1093/jxb/ers129 22553288 22. Bolouri Moghaddam M.R. Van den Ende W. Sweet immunity in the plant circadian regulatory network J. Exp. Bot. 2013 64 1439 1449 10.1093/jxb/ert046 23564957 23. Aluko O.O. Li C. Wang Q. Liu H. Sucrose utilization for improved crop yields: A review article Int. J. Mol. Sci. 2021 22 4704 10.3390/ijms22094704 33946791 24. Wang M. Le Gourrierec J. Jiao F. Demotes-Mainard S. Perez-Garcia M.-D. Ogé L. Hamama L. Crespel L. Bertheloot J. Chen J. Convergence and divergence of sugar and cytokinin signaling in plant development Int. J. Mol. Sci. 2021 22 1282 10.3390/ijms22031282 33525430 25. Walker R.P. Bonghi C. Varotto S. Battistelli A. Burbidge C.A. Castellarin S.D. Chen Z.-H. Darriet P. Moscatello S. Rienth M. Sucrose metabolism and transport in grapevines, with emphasis on berries and leaves, and insights gained from a cross-species comparison Int. J. Mol. Sci. 2021 22 7794 10.3390/ijms22157794 34360556 26. Orzechowski S. Sitnicka D. Grabowska A. Compart J. Fettke J. Zdunek-Zastocka E. Effect of short-term cold treatment on carbohydrate metabolism in potato leaves Int. J. Mol. Sci. 2021 22 7203 10.3390/ijms22137203 34281256 27. Li Y. Hu J. Wei H. Jeong B.R. A long-day photoperiod and 6-benzyladenine promote runner formation through upregulation of soluble sugar content in strawberry Int. J. Mol. Sci. 2020 21 4917 10.3390/ijms21144917 32664642 28. Garg V. Hackel A. Kühn C. Expression level of mature miR172 in wild type and StSUT4-silenced plants of Solanum tuberosum is sucrose-dependent Int. J. Mol. Sci. 2021 22 1455 10.3390/ijms22031455 33535646 29. Al-Sheikh Ahmed S. Zhang J. Farhan H. Zhang Y. Yu Z. Islam S. Chen J. Cricelli S. Foreman A. Van den Ende W. Diurnal changes in water soluble carbohydrate components in leaves associated TaSUT1 gene expression during grain development in wheat Int. J. Mol. Sci. 2020 21 8276 10.3390/ijms21218276 33167324 30. Poudel K. Luo X. Chen L. Jing D. Xia X. Tang L. Li H. Cao S. Identification of the SUT gene family in pomegranate (Punica granatum L.) and functional analysis of PgL0145810.1 Int. J. Mol. Sci. 2020 21 6608 10.3390/ijms21186608 31. Formela- Luboińska M. Remlein-Starosta D. Waskiewicz A. Karolewski Z. Bocianowski J. Stepien L. Labudda M. Jeandet P. Morkunas I. The role of saccharides in the mechanisms of pathogenicity of Fusarium oxysporum f. sp lupini in yellow lupine (Lupinus luteus L.) Int. J. Mol. Sci. 2020 21 7258 10.3390/ijms21197258 32. Formela-Luboińska M. Chadzinikolau T. Drzewiecka K. Jelen H. Bocianowski J. Kesy J. Labudda M. Jeandet P. Morkunas I. The role of sugars in the regulation of the level of endogenous signaling molecules during defense response of yellow lupine to Fusarium oxysporum Int. J. Mol. Sci. 2020 21 4133 10.3390/ijms21114133 32531938 33. Savra A. Tarkowski L.P. Janse van Rensburg H.C. Deleye E. Vaerten J. De Storme N. Keulemans W. Van den Ende W. Sweet immunity: The effect of exogenous fructans on the susceptibility of apple (Malus × domestica Borkh.) to Venturia inaequalis Int. J. Mol. Sci. 2020 21 5885 10.3390/ijms21165885 32824325 34. Ali M. Li Q.-H. Zou T. Wei A.-M. Gombojav G. Lu G. Gong Z.-H. Chitinase gene positively regulates hypersensitive and defense responses of pepper to Colletotrichum acutatum infection Int. J. Mol. Sci. 2020 21 6624 10.3390/ijms21186624 32927746

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095658 ijerph-19-05658 Article Physical Persistency across Game Quarters and during Consecutive Games in Elite Junior Basketball Players Portes Rubén 1* Navarro Barragán Rafael Manuel 1* Calleja-González Julio 2 https://orcid.org/0000-0002-9585-3158 Gómez-Ruano Miguel Ángel 3 https://orcid.org/0000-0002-5069-6099 Jiménez Sáiz Sergio Lorenzo 1 Sousa Antonio Academic Editor 1 Faculty of Sport Sciences, Universidad Europea De Madrid, 28670 Madrid, Spain; sergio.jimenez.saiz@urjc.es 2 Faculty of Education and Sport, University of the Basque Country (UPV/EHU), 01007 Vitoria, Spain; julio.calleja@ehu.eus 3 Faculty of Physical Activity and Sport Sciences, Technical University of Madrid, 28040 Madrid, Spain; miguelangel.gomez.ruano@upm.es * Correspondence: rubenportes@gmail.com (R.P.); rafaelmanuel.navarro@universidadeuropea.es (R.M.N.B.) 06 5 2022 5 2022 19 9 565815 3 2022 05 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Given the intermittent nature of basketball and the different demands that occur during playing time that are specific to every level of competition, the ratio of accelerations/decelerations and the intensity level across quarters were evaluated in female elite junior basketball players (n = 48; age: 16.8 ± 0.7 years; height: 1.76 ± 0.07 cm; body mass: 67.2 ± 6.2 kg). The following variables were analyzed to determine physical persistency across game quarters:(a) total distance covered (m), (b) high-intensity running (HIR) (14–21 km·h−1) distance covered (m), (c) sprint (21–30 km·h−1) distance covered (m), (d) total accelerations (n), (e) total decelerations (n), (f) relative accelerations (n·min−1), (g) relative decelerations (n·min−1), (h) ratio of acceleration/deceleration (A/D), (i) total jumps (j) relative jumps (n·min−1) (k) player load (AU). using the WIMU PRO® system. Higher but shorter acceleration intensity occurred during the last quarters due to the tight results of the matches. The results suggest that high-intensity efforts such as sprints and HIR seem to increase the A/D ratio (guard and forward positions). Therefore, specific conditioning, as well as eccentric strength training, could be included by practitioners in training programs to improve the performance of these positions during competition, especially as a prior preparation to a game-congested event. Centers seem to have a more variable performance through quarters than do other positions, perhaps highlighting the need for specific conditioning strategies. basketball ratio acceleration deceleration women This research received no external funding. ==== Body pmc1. Introduction Basketball is one of the most famous team sports worldwide [1], where optimal performance is highly complex as it requires a combination of technical and tactical abilities and a high degree of physical fitness, among other abilities [2]. Besides, the preparation of this type of players involves developing other physical and psychological attributes [3], given that the games are characterized by repeated explosive activities, such as sprints, jumps, shuffles, and rapid changes of direction [4]. This is the main reason why physical fitness is one of the most important performance factors in basketball [5], playing a “key” role during practice and competitions [6] in a typical congested schedule (a high number of games in a short period of time) [7]. In particular, some studies have evaluated the examined the attributes of female basketball players’ performance [8,9]. In this sense, the periodization plan implemented could improve the physical performance capacity of elite female basketball players [10], with the inclusion of personal physical fitness sessions in order to develop the skills required by each position to improve players’ physical performance [11]. For that reason, a physical fitness profile is dynamically developed over the entire period of growth [12]. The analysis of adolescent basketball players’ capacities is important as it forms the basis for the transition to an established senior category [11]. When analyzing the adolescent players’ performance, the impact of maturation must be accounted for [13]. The development of anthropometrical parameters in U-18 players, including the greatest rate of change in body mass, occurs approximately one year after the growth spurt (peak height velocity). Thus, the time surrounding peak height velocity is considered a potential window of opportunity for strength development [14]. On the other hand, external load represents the variables manipulated to induce internal load [15] and provide an objective assessment of the players’ workload. In that line, IMU’s have been used extensively in the general population as a measure of physical activity level [16]. The monitoring of the external load measurements derived from these triaxial accelerometers is currently considered a valid and reliable tool in team sports [17]. This device allows the recording of data in three planes, reproducing the specific movements performed in basketball, as the combination of defensive and offensive movements forward, backward, and lateral [18]. The type of observed actions includes acceleration and deceleration movements [15]. The current available research evaluated the number of accelerations and decelerations across quarters (first quarter, second quarter, third quarter, and fourth quarter) and playing positions (guard, forward and center). In fact, more intense accelerations were performed in the last quarter, involving faster movements. In addition, guard players performed more accelerations, and their intensity was greater than that of other positions (i.e., forward and center). Particularly, when the acceleration profile was established for the quarters of a basketball game, results were different for guards, forwards and centers in U-18 women’s basketball games, and there was also a lower degree of persistency between quarters [19,20]. Previous studies have found fluctuations in the persistency of demands between quarters in professional male basketball as well [21,22]. The knowledge of the specific persistency of performance during basketball games is a tool of great value for coaches when prescribing training stimulus to analyze persistency (consistency of data registered to analyze performance) of performance across quarters. We studied different variables that were useful to improve this process (Total distance, A/D, and high-intensity distances). Due to the dynamic nature of basketball, the impact of the acceleration/deceleration (A/D) ratio [23] (accelerations minus decelerations as a measure of how efficient in game-specific actions a player is on the court, as well as an indicator of strength deficiencies that could lead to overuse injuries in the lower body) could be very useful to the programing of the training process. This study intends to clarify which variables affect this ratio. Furthermore, this analysis could clarify the impact of the A/D ratio on physical performance during competitive matches [24], and to the best of the authors’ knowledge, no previous scientific evidence has been reported regarding performance persistency among quarters. This is the main reason why this A/D ratio could predict final performance in this population based on positions during congested tournaments. Therefore, the main goal was to analyze the persistency of performance across quarters and games of the A/D ratio in three different playing positions (guard, forward, and center) of women junior basketball players during a game-congested event. Finally, we hypothesize that persistence of performance would decrease in the second or third game of the event and that it would also vary during the quarters of a single game. 2. Methods 2.1. Subjects A total of 48 female elite junior basketball players from four different teams (age: 16.8 ± 0.7 years; height: 1.76 ± 0.07 cm; body mass: 67.2 ± 6.2 kg) (Somatic measures obtained with Tanita WB3000, Tanita Company, Tokyo, Japan). The number of players who volunteered to participate in the study broken down by specific position are as follows: guards: n = 22; forwards: n = 13; and centers: n = 13. Players were classified by coaches as guards (point guards and shooting guards), forwards (small forwards and power forwards), and centers. All players were competing in an elite junior competition (the Madrid-Spain Junior Basketball Final Four), which is Madrid´s state tournament, which is played just prior to the Spanish national tournament. All players in this study performed approximately 10 hours of team training (5 total sessions) and six hours of gym-based conditioning per week during the season leading into competition. All players were informed of the aim, risks, and benefits of the study before signing written consent to allow the collection of data for scientific purposes. The study was designed in compliance with the recommendations for clinical research of the Declaration of Helsinki of the World (2008) [25]. The local institutional human research ethics committee approved the study protocol (CIPI/18/195). 2.2. Observation Period The competition was played over the course of 3 days (Thursday, Saturday, and Sunday) in the same arena, with 4 female teams playing each of the other female teams. The schedule of the competition for each team is shown in Table 1. Each match consisted of 4 10-minute quarters, with one min separating each quarter and 15 min separating each half (i.e., between quarters 2 and 3). At least 10 min of actual playing time (while the match clock was running) had to be completed in the match being analyzed for player data to be included in the final sample for analysis. Consequently, 133 individual female match samples were included in the final analyses. 2.3. Procedures The external load (EL) was monitored using WIMU PRO® devices (Realtrack Systems SL, Almería, Spain). These devices include an accelerometer, a gyroscope, and a magnetometer sampling at 100 Hz, and they were attached to the upper back of participants during matches with an adjustable harness. The system also uses 6 portable ultra-wideband (UWB) antennae placed within 5 meters of each corner and middle line of the court, collecting positioning data at 20 Hz. The system operates using triangulations between the antennae and the units every 50 Ms. The time required to receive the signal is calculated by the device and the unit position (X, Y, and Z) and derived using one of the antennae as a reference. The antennae remained in the same position across the entire observation period to ensure consistency in the acquired data. The data were analyzed using the WIMU PRO® software (Realtrack Systems SL, Almería, Spain). Dependent Variables The variables used to indicate EL were: (a) total distance covered (m); (b) high-intensity running (HIR) (14–21 km·h−1) distance covered (m); (c) sprint (21–30 km·h−1) distance covered (m); (d) total accelerations (n); (e) total decelerations (n); (f) relative accelerations (n·min−1); (g) relative decelerations (n·min−1); (h) ratio of A/D; (i) total jumps (j); relative jumps (n·min−1); (k) player load (arbitrary units (AU) calculated using the following equation: player load n = [(ACxn−ACxn−1) 2+(ACyn−ACyn−1) 2+(ACzn−ACzn−1) 2]/100 , where AC(x,y,z) = AC_Body (acceleration minus gravity), ACy is the lateral–medial axis acceleration, ACx is the vertical axis acceleration, ACz is the anteroposterior axis acceleration, and (l) is the relative player load (AU·min−1). The WIMU PRO® has shown adequate reliability to measure team-sport-specific movements [26,27]. Specifically, the UWB (ultra-wideband) technology showed better accuracy (bias: 0.57–5.85%), test–retest reliability (% technical error of measurement (TEM): 1.19), and interunit reliability (bias: 0.18%) in determining distance covered than GPS technology (bias: 0.69–6.05%; %TEM: 1.47; bias: 0.25%) during intermittent, team-sport activity [27]. Also, UWB showed better results (bias: 0.09%; intraclass correlation (ICC): 0.979; bias: 0.01%) in measuring mean movement velocity than GPS technology (bias: 0.18%; ICC: 0.951; bias: 0.03%) during walking (<6 km·h−1) and running (>16 km·h−1) [27]. The accuracy of the UWB technology has also been tested indoors, showing high sensitivity to relative positioning on the court [28]. 2.4. Statistical Analysis The descriptive analysis was conducted using the mean and standard deviation of physical demands according to the game number and game quarter for each playing position. Secondly, the autocorrelation function (ACF), the measurement between the relationship of a variable current value and its past values, was run to calculate the persistency of each physical demand measured within each game (across game quarters) and across the games [29]. This statistical model allows for the defining of the relationships between a series of events (e.g., consecutive games or game quarters within a game). For this analysis, the use of lag 1 was considered to analyze the relationship of each physical demand in each specific game (between games)/game quarter (within game) regarding to the next game/game quarter. This statistical model provides positive or negative (correlation) values that may indicate the performance persistence between and within games for each specific variable. The higher the value, the stronger the persistence in subsequent games/game quarters. All analyses were run using the statistical software IBM SPSS® version 23.0 for Windows (IBM Corp.: Armonk, NY, USA). The statistical significance was established at p < 0.05. 3. Results Descriptive results for each physical performance of guards, forwards, and centers during each game quarter for all games are included in Table 2, Table 3 and Table 4, respectively. The results of ACF for guards showed that their physical performance was persistent across the three games (see Table 2) for all variables except the A/D ratio. However, when analyzing the persistency of their performance quarter by quarter in each independent game, the results showed the stable performance of decelerations/min and player load/min during game 1, sprints, accelerations/min, decelerations/min, and jumps/min during game 2, and jumps/min during game 3. The results of ACF for forwards showed that physical performance was consistent across the three games (see Table 3) for all variables. Their performance was highly consistent quarter by quarter during games 1, 2, and 3 (for all variables except sprints and ratio A/D). The results of ACF for centers showed that their physical performance was consistent across the three games (see Table 4) for all variables except sprints. However, when analyzing the persistency of their performance quarter by quarter in each independent game, the results showed the stable performance only of total distance and jumps during game 1, accelerations and accelerations/min during game 2, and all variables during game 3. 4. Discussion The main goal was to analyze the persistency of performance across quarters and games and identify the best predictors of the A/D ratio in three different playing positions (guards, forwards, and centers) of women junior basketball players during a game-congested event. The main results of ACF indicated that, when comparing performance across games, the three positions showed similarly persistent performance, with guards showing the highest persistency (A/D ratio), forwards also showing differences in sprint performance, and centers showing lower persistency. When analyzing performance across quarters in each different game, the results show more differences among positions than when across-game performance was analyzed, as forwards seemed to be the only players performing consistently across both games and quarters in all variables. The monitoring of the exposure and intensities in competition via IMUs helps in determining performance and fatigue responses, as well as future training strategies [18,21,30,31]. In this regard, the results of our study show variations of activity demands during competition among the different playing positions; this indicates that training programs could be oriented specifically to each playing position although there are general capacities that all positions should develop. Based on the differences of the overall demands among playing positions, it was shown that guards perform a higher number of sprints and undergo more high-intensity shuffling movements compared with forwards and centers [32,33,34,35,36]. This study found differences in the A/D ratio among the guards and the rest of playing positions across games, highlighting the need for specific, eccentric strength training to cope with a higher number of decelerations in this age group. Furthermore, Conte et al. (2015) [37] observed that repeated sprint activity, especially short sprints, is a relevant component of elite women’s basketball. Data collected in this study shows differences in sprint performance across games in centers’ playing positions. According to existing evidence, players in these positions present lower specific physical fitness compared to the other playing positions [11,36]. Our analysis of high-intensity variables over different quarters showed different results than those observed for elite EuroLeague women players [37], partly because of the difference in playing levels, a fact that highlights the specific applicability of results to only the studied age group. Under-18 women’s basketball players present lower persistency in performance over quarters than do professional women basketball players according to the existing literature [20,38]. Evidence found in studies of male basketball players highlighted differences in demands between different playing levels, as Ben Abdelkrim et al. (2010) [39] observed higher decreases in high-intensity activity demands in U−18 male players compared to international players of the same category. The authors attributed these findings to the higher physical fitness of the international players although this study did not investigate the physical capabilities of the participants. The ability to perform decelerations and changes of direction has shown large correlations to eccentric strength in different studies [40,41,42]. Related to this matter, guards have shown a better-developed capability of generating greater relative strength compared to other playing positions in female basketball [11]. Additionally, elite women basketball back-court players seem to elicit more high-intensity activity and shuffling than do front-court players [36], and guards seem to have lower A/D ratios than do forwards and centers during match play in male basketball [43]. Results for this study showed that, for this particular group and in this competition format, there are also differences between the three studied groups of playing positions, and different demands that are affected by in-game factors that vary depending on specific competition circumstances that highlight the need for analyses to plan and prescribe effective training programs. This study provides interesting outcomes to the investigation of external load in U-18 women’s basketball players, but there are some limitations encountered in this process. First, the study collected and analyzed only external load data, while comparison of these variables to internal load is recommended to interpret influencing factors of the players performance outcomes [44]. Second, the games were played on consecutive days, which could influence the physical variable outcomes, given the accumulated fatigue in the positions that require lower fitness levels, such as centers [11]; it could also be related to basketball competition factors, such as foul trouble, flow of the game, or playing time. Lastly, more work is required to analyze U-18 women’s basketball players during the season, when games are played once or twice a week; this could affect the periodization of the training suggested in the conclusions, including the same content to cope with training and competition demands, but with adaptable periodization to meet the specific schedule. The conclusions in this study apply only to the studied teams and may not be applicable to players of different playing levels or ages. Future studies could focus on a more holistic approach regarding players’ loads, considering internal and external load in order to control for a more comprehensive approach to the players’ fatigue mechanisms. 5. Conclusions In summary, these results suggest that high-intensity efforts, such as sprints and HIR, seem to affect the A/D ratio (for guard and forward positions). Therefore, specific conditioning, such as repeated sprint ability (RSA), as well as eccentric strength training in the form of eccentric overload, as an evolution of previous general strength training adapted to specific age and gender, could be included by practitioners in training programs to improve the performance of players in these positions in this specific competition format and in this specific age group. In addition, centers seem to have a more variable performance over quarters than do other positions, perhaps highlighting the need for specific conditioning strategies for players in this position in order to maintain high performance throughout the games. Acknowledgments The authors would like to thank all of the participants, as well as their legal guardians. Author Contributions Conceptualization, R.P., J.C.-G., M.Á.G.-R., S.L.J.S. and R.M.N.B.; Methodology, R.P., J.C.-G. and M.Á.G.-R.; Software, M.Á.G.-R.; Data collection, R.P.; Writing—original draft preparation, R.P., J.C.-G. and S.L.J.S.; Visualization, M.Á.G.-R., S.L.J.S. and R.M.N.B.; Writing—review and editing, R.P. and J.C.-G.; Supervision, J.C.-G., M.Á.G.-R., S.L.J.S. and R.M.N.B. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The local institutional human research ethics committee approved the study protocol (CIPI/18/195). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Conflicts of Interest The authors declare no conflict of interest. ijerph-19-05658-t001_Table 1 Table 1 Match schedule of the tournament. Time (hh:mm) Day 1 Day 2 Day 3 10:30 FEMALE 2 vs. 4 FEMALE 1 vs. 4 12:30 FEMALE 1 vs. 3 FEMALE 2 vs. 3 18:30 FEMALE 1 vs. 2 20:30 FEMALE 3 vs. 4 ijerph-19-05658-t002_Table 2 Table 2 Descriptive statistics for physical demands during games and quarters for guard players (persistency of performances via ACF and p-values). Guards Game 1 Game 2 First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 409.0 494.7 435.7 420.77 296.2 375.8 394.6 562.7 −0.22 0.53 373.3 393.5 446.3 446.3 380.3 405.6 485.6 409.1 0.17 0.12 HIR 50.78 64.22 47.21 48.99 29.72 37.50 44.82 70.81 −0.24 0.49 44.09 56.50 43.03 48.36 32.19 39.27 33.88 39.95 0.18 0.11 Sprint 5.77 14.03 1.94 3.85 0.36 1.05 1.98 4.22 0.01 0.93 1.49 3.71 5.52 9.26 5.28 11.64 6.12 15.15 0.22 0.04 * Acc 34.48 42.72 37.13 35.32 32.00 35.76 32.70 46.80 0.03 0.94 51.55 77.90 57.95 60.66 57.70 72.92 71.55 83.33 0.19 0.08 Dec 35.43 42.58 37.35 34.64 31.00 34.48 32.04 46.95 0.04 0.91 32.25 33.24 37.50 36.59 35.10 38.41 46.10 42.05 0.16 0.14 Rel Acc 3 18 3.07 5. 10 3.59 3.88 3.71 2.89 3.49 −0.64 0.07 6.50 6.39 7.89 6.67 7.02 7.17 7.77 7.44 0.32 0.01 * Rel Dec 3.27 3.03 5.22 3.74 3.71 3.56 3.02 3.37 −0.75 0.03 * 4.88 3.77 4.67 3.27 4.30 3.73 4.89 3.54 0.33 0.01 * Ratio A/D −0.48 2.37 −0.35 1.97 −0.48 1.12 −0.74 1.42 −0.08 0.81 −0.90 2.69 0.40 2.14 −0.95 2.91 −1.40 3.07 0.09 0.41 TJ 10.17 14.97 10.43 11.24 8.65 10.46 12.83 18.56 −0.07 0.84 5.40 7.86 5.65 7.16 7.85 8.70 9.00 1204 0.17 0.11 Rel Jumps 0.86 0.93 1.55 1.58 1.05 1.16 1.33 2.11 −0.54 0.13 0.63 0.68 0.55 0.64 0.95 0.93 0.91 0.94 0.34 0.01 * PL 7.20 8.26 7.47 6.62 5.60 6.46 7.11 9.12 −0.20 0.57 4.94 5.97 5.57 5.48 5.10 5.50 6.29 5.73 0.10 0.36 Rel PL 0.69 0.54 1.10 0.54 0.65 0.59 0.74 0.62 −0.71 0.04 * 0.67 0.55 0.71 0.53 0.64 058 0.67 0.50 0.21 0.06 Game 3 All Games First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 5691 468.1 510.5 430.6 508.6 499.2 513.7 534.8 0.14 0.21 448.5 456.7 462.8 426.4 390.3 429.8 461.3 503.9 0.24 0.01 * HIR 5003 58.82 33.02 46.83 29.23 44.71 25.61 36.25 0.13 0.24 48.42 59.25 41.38 47.71 3035 39.82 35.25 52.30 0.23 0.01 * Sprint 0.85 1.52 0.96 2.70 0.22 0.61 1.71 3.78 −0.03 0.76 2.85 8.94 2.77 6.13 1.88 6.89 3.21 9.22 0.15 0.01 * Acc 111.75 87.98 104.65 94.22 128.55 134.00 119.00 124.83 0.16 0.14 64.43 77.38 65.17 71.43 70.81 96.31 72.43 94.69 0.30 0.01 * Dec 49.85 38.86 44.05 41.56 47.95 46.26 48.70 53.08 0.14 0.22 39.00 38.76 39.52 37.08 37.68 39.78 41.79 47.37 0.22 0.01 * Rel Acc 13.30 7.98 12.61 7.66 11.36 8.66 11.08 9.16 0.20 0.07 7.45 7.31 8.37 6.78 7.25 7.30 7.04 7.67 0.38 0.01 * Rel Dec 6.11 3.86 5.19 3.23 5.24 4.77 4.51 4.03 0.21 0.05 4.69 3.69 5.03 3.39 4.38 4.02 4.09 3.68 0.29 0.01 * Ratio A/D −2.15 2.35 −1.35 2.37 −1.10 2.90 −0.35 3.33 −0.07 0.55 −1.14 2.53 −0.43 2.23 −0.83 2.39 −0.83 2.68 0.11 0.07 TJ 13.60 10.63 12.65 16.74 14.60 15.55 15.20 18.69 0.21 0.05 9.75 12.00 9.62 12.44 10.29 12.04 12.37 16.73 0.25 0.01 * Rel Jumps 1.72 1.40 1.30 1.20 1.50 1.51 1.46 1.48 0.27 0.01 * 1.06 1.12 1.15 1.28 1.16 1.23 1.24 1.60 0.31 0.01 * PL 9.63 7.72 8.58 7.61 8.81 8.81 9.04 9.56 0.13 0.25 7.25 7.55 7.22 6.63 6.46 7.11 7.46 8.30 0.22 0.01 * Rel PL 1.14 0.70 1.06 0.66 0.82 0.62 0.85 0.72 0.17 0.13 0.83 0.63 0.96 0.60 0.70 0.59 0.75 0.61 0.25 0.01 * * p < 0.05; Note: TDC: total distance covered (m); HIR: high-intensity running (m); Sprint: sprint distance covered (m); Acc: total accelerations (n); Dec: total decelerations (n); Rel Acc: relative accelerations (n·min−1); Rel Dec: relative decelerations (n·min−1); Ratio A/D: ratio of accelerations/decelerations; TJ: total jumps (n); Rel Jumps: relative jumps (n·min−1); PL: player load (AU); Rel PL: relative player load (AU·min−1). ijerph-19-05658-t003_Table 3 Table 3 Descriptive statistics for physical demands during games and quarters for forward players (persistency of performances via ACF and p-values). Forwards Game 1 Game 2 First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 746.38 377.98 742.49 431.34 842.25 515.89 875.59 545.20 0.48 0.01 * 598.56 590.57 716.93 485.03 776.60 529.41 527.33 487.58 0.48 0.01 * HIR 95.00 56.65 85.66 56.88 86.28 61.13 88.50 72.97 0.56 0.01 * 58.49 69.99 51.92 57.73 54.44 61.73 38.29 53.88 0.53 0.01 * Sprint 3.03 4.78 2.39 4.99 1.00 1.72 5.05 5.74 0.26 0.05 6.53 11.91 2.62 4.44 2.75 4.33 3.05 5.69 0.02 0.85 Acc 64.31 33.49 63.69 34.83 77.46 48.93 74.15 47.69 0.43 0.01 * 78.92 105.41 92.92 85.26 102.92 90.48 64.46 78.26 0.52 0.01 * Dec 64.54 33.13 62.62 34.87 76.85 49.19 75.23 48.60 0.46 0.01 * 49.31 49.67 64.00 43.74 69.62 47.06 50.31 46.61 0.47 0.01 * Rel Acc 5.36 2.83 6.37 3.01 5.89 2.83 5.61 2.88 0.42 0.01 * 6.82 6.30 8.37 6.96 8.42 6.71 7.39 5.63 0.63 0.01 * Rel Dec 5.40 2.64 6.23 2.95 5.56 2.64 5.66 2.83 0.38 0.01 * 4.77 3.38 5.66 3.30 5.69 3.37 5.76 3.51 0.67 0.01 * Ratio A/D −0.31 2.81 −0.92 2.53 −0.77 2.42 −0.77 2.83 0.07 0.62 −0.38 2.02 0.00 2.52 −0.15 2.44 −0.15 2.67 0.19 0.16 TJ 18.08 15.79 21.00 18.48 30.23 23.10 27.85 21.81 0.36 0.01 * 11.92 16.57 13.54 12.33 17.23 14.21 12.00 15.13 0.37 0.01 * Rel Jumps 1.47 1.20 2.18 1.68 2.26 1.55 2.08 1.49 0.30 0.03 * 1.01 1.02 1.26 1.14 1.47 1.13 1.47 1.20 0.44 0.01 * PL 12.20 6.26 12.22 7.01 14.52 8.70 14.59 9.51 0.40 0.01 * 7.54 8.54 8.68 6.14 9.73 7.00 6.48 6.52 0.45 0.01 * Rel PL 1.03 0.48 1.27 0.46 1.14 0.58 1.10 0.49 0.27 0.05 0.70 0.53 0.79 0.54 0.80 0.51 0.77 0.52 0.59 0.01 * Game 3 All Games First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 609.04 638.58 569.29 514.95 635.98 599.07 573.00 501.28 0.34 0.01 * 651.33 537.30 676.24 471.98 751.61 541.74 658.64 522.30 0.51 0.01 * HIR 64.60 78.17 66.15 73.99 47.85 58.56 39.45 48.07 0.45 0.01 * 72.70 68.93 67.91 63.24 62.86 61.28 55.41 62.37 0.55 0.01 * Sprint 3.26 7.29 3.37 9.64 0.03 0.10 2.41 5.72 0.26 0.05 4.27 8.45 2.79 6.60 1.26 2.86 3.51 5.68 0.32 0.01 * Acc 121.00 127.31 126.00 113.14 166.38 158.56 140.85 121.09 0.37 0.01 * 88.08 97.85 94.21 85.94 115.59 112.76 93.15 92.01 0.47 0.01 * Dec 51.85 55.54 48.92 42.72 60.38 57.53 56.54 52.66 0.36 0.01 * 55.23 46.32 58.51 40.15 68.95 50.55 60.69 49.22 0.50 0.01 * Rel Acc 9.64 9.30 11.99 8.40 11.26 9.29 12.33 8.82 0.66 0.01 * 7.27 6.75 8.91 6.78 8.52 7.00 8.44 6.75 0.58 0.01 * Rel Dec 4.10 4.01 4.83 3.62 5.15 5.42 4.81 3.69 0.48 0.01 * 4.76 3.35 5.57 3.27 5.47 3.89 5.41 3.31 0.53 0.01 * Ratio A/D 0.38 2.90 −0.08 1.12 −0.69 1.75 0.15 1.28 −0.02 0.90 −0.10 2.56 −0.33 2.14 −0.54 2.19 −0.26 2.34 0.14 0.08 * TJ 13.92 15.68 15.08 14.96 16.62 19.29 18.62 22.67 0.33 0.01 * 14.64 15.81 16.54 15.40 21.36 19.75 19.49 20.69 0.42 0.01 * Rel Jumps 1.05 1.09 1.41 1.11 1.10 1.08 1.54 1.71 0.52 0.01 * 1.18 1.09 1.62 1.36 1.61 1.33 1.70 1.47 0.43 0.01 * PL 9.76 10.30 9.64 8.83 10.37 9.44 9.84 8.47 0.34 0.01 * 9.83 8.52 10.18 7.37 11.54 8.49 10.30 8.72 0.46 0.01 * Rel PL 0.78 0.75 0.90 0.65 0.73 0.63 0.86 0.64 0.65 0.01 * 0.84 0.60 0.99 0.58 0.89 0.59 0.91 0.56 0.54 0.01 * * p < 0.05; Note: TDC: total distance covered (m); HIR: high-intensity running (m); Sprint: sprint distance covered (m); Acc: total accelerations (n); Dec: total decelerations (n); Rel Acc: relative accelerations (n·min−1); Rel Dec: relative decelerations (n·min−1); Ratio A/D: ratio of accelerations/decelerations; TJ: total jumps (n); Rel Jumps: relative jumps (n·min−1); PL: player load (AU); Rel PL: relative player load (AU·min−1). ijerph-19-05658-t004_Table 4 Table 4 Descriptive statistics for physical demands during games and quarters for center players (persistency of performances via ACF and p-values). Centers Game 1 Game 2 First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 466.58 391.25 568.87 406.67 486.91 408.42 466.16 359.29 0.29 0.04 * 330.39 463.54 442.73 347.73 422.59 376.31 445.35 458.60 0.07 0.62 HIR 66.86 53.69 81.95 69.97 52.96 53.94 58.29 48.88 0.17 0.22 44.27 75.64 35.96 42.43 37.06 47.20 29.76 43.58 0.01 0.93 Sprint 5.14 12.91 2.76 3.96 2.11 7.30 9.71 31.87 −0.04 0.79 1.59 2.34 4.94 10.73 3.99 9.24 3.16 5.79 0.07 0.59 Acc 41.08 32.12 48.00 30.55 37.00 35.99 43.00 34.40 0.18 0.19 43.31 78.80 50.69 47.50 44.38 43.63 55.38 74.55 0.28 0.04 * Dec 41.58 33.50 48.25 31.76 35.83 34.11 43.08 34.32 0.18 0.19 26.85 39.13 39.62 29.25 37.15 33.99 38.62 36.33 0.05 0.70 Rel Acc 4.48 2.71 5.60 2.75 4.25 3.34 5.73 2.97 0.26 0.06 6.23 5.58 6.67 4.99 5.66 4.88 5.30 5.33 0.34 0.01 * Rel Dec 4.56 2.67 5.56 2.88 4.19 3.24 5.68 2.82 0.28 0.05 6.29 7.99 5.34 3.16 4.73 3.41 4.07 3.50 0.13 0.32 Ratio A/D −0.08 1.38 0.08 1.68 0.75 1.22 0.58 0.67 0.05 0.75 −0.54 1.27 1.08 1.98 −0.38 0.65 −0.31 2.29 0.07 0.58 TJ 15.17 13.33 21.83 17.83 17.50 18.17 21.83 21.88 0.29 0.04 * 5.62 9.66 8.23 7.13 8.31 9.44 9.92 10.82 0.20 0.14 Rel Jumps 1.59 1.24 2.60 1.93 2.04 1.93 2.72 1.98 0.26 0.06 0.61 0.71 1.08 0.77 1.01 1.03 1.18 1.52 0.19 0.15 PL 7.88 6.48 9.56 6.43 7.02 6.67 8.32 6.57 0.19 0.18 4.13 6.36 5.19 3.97 4.85 4.30 5.38 6.09 0.13 0.32 Rel PL 0.84 0.52 1.13 0.46 0.82 0.64 1.16 0.50 0.21 0.12 0.51 0.48 0.70 0.40 0.62 0.47 0.53 0.47 0.22 0.10 Game 3 All Games First Second Third Fourth First Second Third Fourth M SD M SD M SD M SD ACF p M SD M SD M SD M SD ACF p TDC 392.28 444.93 528.59 516.41 427.18 506.45 405.19 475.68 0.55 0.01 * 394.57 427.24 511.94 421.55 444.47 423.75 438.18 425.00 0.42 0.01 * HIR 38.35 53.17 57.06 59.06 36.10 58.25 29.78 39.64 0.45 0.01 * 49.38 61.48 57.70 59.40 41.75 52.42 38.77 44.90 0.29 0.01 * Sprint 2.65 5.13 2.43 4.52 0.06 0.18 1.40 5.05 0.31 0.02 * 3.08 7.88 3.39 7.07 2.05 6.80 4.62 18.27 0.04 0.59 Acc 83.77 96.81 114.54 116.21 99.85 119.87 98.85 115.19 0.55 0.01 * 56.45 75.89 71.68 79.82 61.03 80.48 66.34 83.95 0.56 0.01 * Dec 32.92 37.00 43.00 40.61 34.46 41.50 33.77 37.83 0.55 0.01 * 33.58 36.21 43.50 33.54 35.82 35.78 38.37 35.45 0.38 0.01 * Rel Acc 9.84 9.52 10.30 8.56 7.62 8.59 9.50 9.20 0.47 0.01 * 6.91 6.84 7.57 6.19 5.89 6.07 6.87 6.56 0.46 0.01 * Rel Dec 4.02 3.95 4.07 3.41 2.65 3.02 3.35 3.32 0.41 0.01 * 4.96 5.37 4.97 3.15 3.85 3.26 4.33 3.30 0.30 0.01 * Ratio A/D −1.46 2.30 −0.69 2.29 −0.15 0.38 −0.46 0.97 0.41 0.01 * −0.71 1.77 0.16 2.09 0.05 0.93 −0.08 1.53 0.25 0.01 * TJ 14.46 18.90 22.85 28.35 16.08 20.60 13.00 15.04 0.49 0.01 * 11.66 14.78 17.53 20.45 13.87 16.78 14.74 16.71 0.45 0.01 * Rel Jumps 1.85 2.20 2.20 2.35 1.28 1.67 1.33 1.52 0.47 0.01 * 1.34 1.58 1.94 1.87 1.42 1.60 1.72 1.77 0.49 0.01 * PL 6.67 7.61 9.62 9.15 7.15 8.51 6.73 7.79 0.56 0.01 * 6.18 6.84 8.09 7.00 6.32 6.62 6.77 6.78 0.44 0.01 * Rel PL 0.83 0.85 0.93 0.82 0.55 0.63 0.66 0.65 0.41 0.01 * 0.72 0.64 0.91 0.60 0.66 0.57 0.77 0.60 0.41 0.01 * * p < 0.05; Note: TDC: total distance covered (m); HIR: high-intensity running (m); Sprint: sprint distance covered (m); Acc: total accelerations (n); Dec: total decelerations (n); Rel Acc: relative accelerations (n·min−1); Rel Dec: relative decelerations (n·min−1); Ratio A/D: ratio of accelerations/decelerations; TJ: total jumps (n); Rel Jumps: relative jumps (n·min−1); PL: player load (AU); Rel PL: relative player load (AU·min−1). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Mazic S. Ostojic S.M. Dikic N. Profiling in Basketball profiling in basketball: Physical and physiological characteristics of elite players J. Strength Cond. Res. 2006 20 740 744 17149984 2. Ziv G. Lidor R. Physical Attributes, Physiological Characteristics, On-Court Performances and Nutritional Strategies of Female and Male Basketball Players Sports Med. 2009 39 547 568 10.2165/00007256-200939070-00003 19530751 3. Bompa T.O. Total Training for Young Champions Available online: https://books.google.es/books?hl=en&lr=&id=OBwrLnc3DiwC&oi=fnd&pg=PP11&dq=bompa+2000&ots=jDw8LTN4kF&sig=TkIGuxnTVaQMddRsDqav0DZrXWw&redir_esc=y#v=onepage&q=bompa%202000&f=false (accessed on 2 February 2022) 4. McKeag D.B. Handbook of Sports Medicine and Science: Basketball John Wiley & Sons Hoboken, NJ, USA 2008 1 225 10.1002/9780470693896 5. Mancha-Triguero D. García-Rubio J. Calleja-González J. Ibáñez S.J. Physical fitness in basketball players: A systematic review J. Sports Med. Phys. Fit. 2019 59 1513 1525 10.23736/S0022-4707.19.09180-1 31610639 6. Delextrat A. Trochym E. Gonzalez J.M.C. Effect of a typical in-season week on strength jump and sprint performances in national-level female basketball players J. Sports Med. Phys. Fit. 2012 52 128 136 7. Ortega J.P. Rojas-Valverde D. Gómez-Carmona C.D. Bastida-Castillo A. Hernández-Belmonte A. García-Rubio J. Nakamura F.Y. Ibáñez S.J. Impact of Contextual Factors on External Load During a Congested-Fixture Tournament in Elite U’18 Basketball Players Front. Psychol. 2019 10 1100 10.3389/fpsyg.2019.01100 31156514 8. Rodríguez-Alonso M. Fernández-García B. Pérez-Landaluce J. Terrados N. Blood lactate and heart rate during national and international women’s basketball J. Sports Med. Phys. Fit. 2003 43 432 436 9. Carter J. Ackland T. Kerr D. Stapff A. Somatotype and size of elite female basketball players J. Sports Sci. 2005 23 1057 1063 10.1080/02640410400023233 16194982 10. Nunes J.A. Moreira A. Crewther B.T. Nosaka K. Viveiros L. Aoki M.S. Monitoring Training Load, Recovery-Stress State, Immune-Endocrine Responses, and Physical Performance in Elite Female Basketball Players During a Periodized Training Program J. Strength Cond. Res. 2014 28 2973 2980 10.1519/JSC.0000000000000499 24736768 11. Delextrat A. Cohen D. Strength, Power, Speed, and Agility of Women Basketball Players According to Playing Position J. Strength Cond. Res. 2009 23 1974 1981 10.1519/JSC.0b013e3181b86a7e 19855320 12. Karpowicz K. Karpowicz M. Strzelczyk R. Structure of Physical Fitness Among Young Female Basketball Players (Trends of Changes in 2006–2013) J. Strength Cond. Res. 2015 29 2745 2757 10.1519/JSC.0000000000000943 25785700 13. Croix M.D.S. Advances in paediatric strength assessment: Changing our perspective on strength development J. Sports Sci. Med. 2007 6 292 304 24149415 14. Lloyd R.S. Oliver J.L. The Youth Physical Development Model: A New Approach to Long-Term Athletic Development Strength Cond. J. 2012 34 61 72 10.1519/SSC.0b013e31825760ea 15. Lovell T. Sirotic A.C. Impellizzeri F. Coutts A.J. Factors Affecting Perception of Effort (Session Rating of Perceived Exertion) During Rugby League Training Int. J. Sports Physiol. Perform. 2013 8 62 69 10.1123/ijspp.8.1.62 23302138 16. Trost S.G. Loprinzi P.D. Moore R. Pfeiffer K.A. Comparison of Accelerometer Cut Points for Predicting Activity Intensity in Youth Med. Sci. Sports Exerc. 2011 43 1360 1368 10.1249/MSS.0b013e318206476e 21131873 17. Leicht A.S. Fox J. Connor J. Sargent C. Sinclair W. Stanton R. Scanlan A. External Activity Demands Differ Between Referees and Players During a Sub-Elite, Men’s Basketball Match Res. Q. Exerc. Sport 2019 90 720 725 10.1080/02701367.2019.1645268 31479399 18. Montgomery P.G. Pyne D.B. Minahan C.L. The Physical and Physiological Demands of Basketball Training and Competition Int. J. Sports Physiol. Perform. 2010 5 75 86 10.1123/ijspp.5.1.75 20308698 19. Reina M. García-Rubio J. Pino-Ortega J. Ibáñez S.J. The Acceleration and Deceleration Profiles of U-18 Women’s Basketball Players during Competitive Matches Sports 2019 7 165 10.3390/sports7070165 20. Reina M. García-Rubio J. Esteves P.T. Ibáñez S.J. How external load of youth basketball players varies according to playing position, game period and playing time Int. J. Perform. Anal. Sport 2020 20 917 930 10.1080/24748668.2020.1818973 21. Fox J.L. Salazar H. Garcia F. Scanlan A.T. Peak External Intensity Decreases across Quarters during Basketball Games Montenegrin J. Sports Sci. Med. 2021 10 25 29 10.26773/mjssm.210304 22. Garcia F. Salazar H. Fox J.L. Differences in the Most Demanding Scenarios of Basketball Match-Play between Game Quarters and Playing Positions in Professional Players Montenegrin J. Sports Sci. Med. 2022 11 15 28 10.26773/mjssm.220302 23. Newans T. Bellinger P. Dodd K. Minahan C. Modelling the Acceleration and Deceleration Profile of Elite-level Soccer Players Int. J. Sports Med. 2019 40 331 335 10.1055/a-0853-7676 30887482 24. Fort-Vanmeerhaeghe A. Montalvo A. Latinjak A.T. Unnithan V. Physical characteristics of elite adolescent female basketball players and their relationship to match performance J. Hum. Kinet. 2016 53 167 178 10.1515/hukin-2016-0020 28149421 25. Giordano S. The 2008 Declaration of Helsinki: Some reflections J. Med. Ethics 2010 36 598 603 10.1136/jme.2009.034132 20813718 26. Castillo A.B. Carmona C.D.G. Sánchez E.D.L.C. Ortega J.P. Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer Eur. J. Sport Sci. 2018 18 450 457 10.1080/17461391.2018.1427796 29385963 27. Castillo A.B. Carmona C.D.G. Ortega J.P. Sánchez E.D.L.C. Validity of an inertial system to measure sprint time and sport task time: A proposal for the integration of photocells in an inertial system Int. J. Perform. Anal. Sport 2017 17 600 608 10.1080/24748668.2017.1374633 28. Bastida-Castillo A. Gómez-Carmona C.D. De la Cruz-Sánchez E. Reche-Royo X. Ibáñez S.J. Ortega J.P. Accuracy and Inter-Unit Reliability of Ultra-Wide-Band Tracking System in Indoor Exercise Appl. Sci. 2019 9 939 10.3390/app9050939 29. Shafizadeh M. Taylor M. Peñas C.L. Performance Consistency of International Soccer Teams in Euro 2012: A Time Series Analysis J. Hum. Kinet. 2013 38 213 226 10.2478/hukin-2013-0061 24235996 30. Hader K. Rumpf M.C. Hertzog M. Kilduff L.P. Girard O. Silva J.R. Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis Sports Med.-Open 2019 5 48 10.1186/s40798-019-0219-7 31820260 31. Portes R. Jiménez S.L. Navarro R.M. Scanlan A.T. Gómez M. Comparing the External Loads Encountered during Competition between Elite, Junior Male and Female Basketball Players Int. J. Environ. Res. Public Health 2020 17 1456 10.3390/ijerph17041456 32. Scanlan A.T. Tucker P.S. Dascombe B.J. Berkelmans D.M. Hiskens M.I. Dalbo V.J. Fluctuations in Activity Demands Across Game Quarters in Professional and Semiprofessional Male Basketball J. Strength Cond. Res. 2015 29 3006 3015 10.1519/JSC.0000000000000967 25932983 33. McInnes S.E. Carlson J.S. Jones C.J. McKenna M.J. The physiological load imposed on basketball players during competition J. Sports Sci. 1995 13 387 397 10.1080/02640419508732254 8558625 34. Scanlan A.T. Dascombe B.J. Reaburn P. Dalbo V. The physiological and activity demands experienced by Australian female basketball players during competition J. Sci. Med. Sport 2012 15 341 347 10.1016/j.jsams.2011.12.008 22244965 35. Stojanović E. Stojiljković N. Scanlan A.T. Dalbo V.J. Berkelmans D.M. Milanović Z. The Activity Demands and Physiological Responses Encountered During Basketball Match-Play: A Systematic Review Sports Med. 2018 48 111 135 10.1007/s40279-017-0794-z 29039018 36. Staunton C. Wundersitz D. Gordon B. Kingsley M. Accelerometry-Derived Relative Exercise Intensities in Elite Women’s Basketball Endoscopy 2018 39 822 827 10.1055/a-0637-9484 37. Conte D. Favero T.G. Lupo C. Francioni F.M. Capranica L. Tessitore A. Time-Motion Analysis of Italian Elite Women’s Basketball Games: Individual and Team Analyses J. Strength Cond. Res. 2015 29 144 150 10.1519/JSC.0000000000000633 25051006 38. Reina M. García-Rubio J. Ibáñez S.J. Training and Competition Load in Female Basketball: A Systematic Review Int. J. Environ. Res. Public Health 2020 17 2639 10.3390/ijerph17082639 39. Ben Abdelkrim N. Castagna C. Jabri I. Battikh T. El Fazaa S. El Ati J. Activity Profile and Physiological Requirements of Junior Elite Basketball Players in Relation to Aerobic-Anaerobic Fitness J. Strength Cond. Res. 2010 24 2330 2342 10.1519/JSC.0b013e3181e381c1 20802281 40. Spiteri T. Nimphius S. Hart N.H. Specos C. Sheppard J.M. Newton R.U. Contribution of Strength Characteristics to Change of Direction and Agility Performance in Female Basketball Athletes J. Strength Cond. Res. 2014 28 2415 2423 10.1519/JSC.0000000000000547 24875426 41. Spiteri T. Newton R.U. Binetti M. Hart N.H. Sheppard J.M. Nimphius S. Mechanical Determinants of Faster Change of Direction and Agility Performance in Female Basketball Athletes J. Strength Cond. Res. 2015 29 2205 2214 10.1519/JSC.0000000000000876 25734779 42. Spiteri T. Binetti M. Scanlan A. Dalbo V.J. Dolci F. Specos C. Physical Determinants of Division 1 Collegiate Basketball, Women’s National Basketball League, and Women’s National Basketball Association Athletes: With Reference to Lower-Body Sidedness J. Strength Cond. Res. 2019 33 159 166 10.1519/JSC.0000000000001905 28368952 43. Vázquez-Guerrero J. Suarez-Arrones L. Gómez D.C. Rodas G. Comparing external total load, acceleration and deceleration outputs in elite basketball players across positions during match play Kinesiology 2018 50 228 234 10.26582/k.50.2.11 44. Halson S.L. Monitoring training load to understand fatigue in athletes Sports Med. 2014 44 139 147 10.1007/s40279-014-0253-z 25200666

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091915 nutrients-14-01915 Article Informing the Co-Development of Culture-Centered Dietary Messaging in the Inuvialuit Settlement Region, Northwest Territories https://orcid.org/0000-0002-5543-7141 Gyapay Julia 1 Noksana Kanelsa 2 Ostertag Sonja 1 Wesche Sonia 3 Laird Brian Douglas 1 https://orcid.org/0000-0003-0989-8841 Skinner Kelly 1* Christensen Dirk Lund Academic Editor Murphy Rachel Academic Editor 1 School of Public Health Sciences, University of Waterloo, Waterloo, ON N2L 3G1, Canada; jgyapay@uwaterloo.ca (J.G.); sonja.ostertag@uwaterloo.ca (S.O.); brian.laird@uwaterloo.ca (B.D.L.) 2 Independent Researcher, Tuktoyaktuk, NT X0E 1C0, Canada; kanelsajade15@gmail.com 3 Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, ON K1N 6N5, Canada; swesche@uottawa.ca * Correspondence: kskinner@uwaterloo.ca 03 5 2022 5 2022 14 9 191528 2 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Northern Indigenous communities require collaborative approaches to health communication about food that are grounded in Indigenous knowledges and cultures; however, preferences and best methods for this process remain understudied. This participatory study discusses how Inuvialuit (Inuit from the Western Arctic) knowledge and the perspectives of territorial, regional, and local dietary message stakeholders can inform the co-development of culture-centered dietary messaging to support healthy, safe, and culturally appropriate diets in Tuktoyaktuk, NWT. A community researcher in Tuktoyaktuk conducted storytelling interviews with country food knowledge holders (n = 7) and community members (n = 3), and a talking circle with local public health dietary message disseminators (n = 2) in June–July 2021. The lead author conducted key informant telephone and videoconference interviews with territorial and regional dietary message disseminators (n = 5) in June 2021. Interviews were coded and analyzed thematically. Our findings indicate that participants at all levels support increased inclusion of cultural and community perspectives about food to develop regionally and locally tailored dietary messaging. While most dietary message stakeholders wish to be involved in co-development processes, some country food knowledge holders in Tuktoyaktuk expressed a desire to lead local communications about country foods. Informed by participants’ experiences and needs, we provide recommendations for future community-led approaches to further (co-)develop and communicate effective, culturally meaningful dietary messaging that promotes Inuvialuit food sovereignty. Indigenous health communication Indigenous knowledge food communication dietary messaging country foods store-bought foods Inuit community-based research Canadian Institutes of Health ResearchNorthern Scientific Training ProgramNorthern Contaminants ProgramHH-08 Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC)Canadian Institutes of Health Research (CIHR)166443 Global Water FuturesJ.G. was funded by scholarships from the Canadian Institutes of Health Research and the Northern Scientific Training Program. This work is part of two larger projects, Country Foods for Good Health and Community Capacity for Climate Change and Food Security (C4FS) Action in the NWT. Funding from these projects was provided by the Northern Contaminants Program (NCP) (S.O., B.L., K.S., grant number HH-08), a program of Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC), and a Canadian Institutes of Health Research (CIHR) Team Grant (K.S., S.W., grant number 166443). J.G. was also funded as a Research Assistant from the Northern Water Futures project from Global Water Futures funding. The funding sources had no role in the study design, data collection, analysis or interpretation of data. The views are those of the authors and not necessarily those of the Canadian Institutes of Health Research or the Northern Contaminants Program. ==== Body pmc1. Introduction Nutrition communication is a mechanism for improving a population’s nutritional well-being via the transmission of nutritional information to influence knowledge, attitudes, or behaviors [1,2]. In Canada, nutrition communication is primarily developed and disseminated federally by Health Canada via dietary guidance, information, and advice about making healthy food choices [3]. Federally-developed messaging is further transmitted and acted upon by provincial/territorial/regional governments, health professionals, academics, and non-governmental organizations to support healthy living among Canadians [3,4]. The most prominent example of Canadian dietary guidance is Canada’s Food Guide (CFG), a policy and educational tool designed to promote healthy food choices and reduce the risk of nutrition-related chronic diseases [3]. The CFG was adapted in 2007 to reflect the food systems of Indigenous peoples in Canada (“Eating Well with Canada’s Food Guide-First Nations, Inuit and Métis”), yet this Indigenous Food Guide (IFG) was criticized for adopting a pan-Indigenous approach and prescriptively focusing on food groups and portion sizes [5,6]. Overall, Indigenous-focused federal dietary guidance is greatly lacking, perpetuating dominant, Western biomedical narratives of food in Canada [7]. In the context of Indigenous communities, nutrition communication studies emphasize the importance of partnering with Indigenous peoples in the development and communication of messages [8,9]. Likewise, they recognize the importance of grounding messages in cultural and community knowledge, skills, values, and worldviews in a way that provides culturally sensitive information and approaches to foster healthy food choices [2,8,9]. This culture-centered approach helps empower communities to make healthy and safe food choices informed by both science and Indigenous knowledge, improving the effectiveness of communication efforts to initiate behavior change [10]. Health risk communication scientists working in the Canadian Arctic have called for improved participatory approaches and better inclusion of local Indigenous culture and knowledges in message development and communication about country (wild-harvested) food risks to ensure that messages are relevant, trusted, culturally appropriate, and respectful [10,11,12,13,14,15]. Despite this call, existing studies have not addressed the best methods for including local and Indigenous knowledges in such messaging. Further, it remains unknown whether involvement in the co-development of culturally relevant dietary messaging is desired by territorial, regional and local dietary message disseminators in the Canadian Arctic and if so, what these approaches and co-development processes should look like. Likewise, no studies have sought to determine desired aspects of Indigenous knowledge and local perspectives about the food system to be included in messaging in Arctic Indigenous communities, how this knowledge should be collected and utilized, and by whom. Our transdisciplinary Country Foods for Good Health (CFGH) study addresses some of these issues in the Inuvialuit Settlement Region (ISR), a land claim area located primarily within the northern Northwest Territories (NWT). The ISR is the land of the Inuvialuit (Inuit of Canada’s western Arctic), one of four Inuit regions in Canada which collectively comprise Inuit Nunangat, the Inuit homeland [16]. Present-day governance and policymaking in the ISR are largely influenced by the terms stipulated in the 1984 Inuvialuit Final Agreement (IFA), the first comprehensive land claim agreement signed north of the 60th parallel [17,18]. The IFA does not include self-government, therefore political authority and healthcare delivery in the ISR are administered jointly by the Government of Canada and the Government of the Northwest Territories [18]. Our CFGH study includes a focus on dietary messages, which include information and advice that addresses the health benefits and risks of country food (‘country food’ refers to animals, game birds, fish, and plants harvested from the environment for human consumption; ‘country food’ is the term preferred by Inuvialuit, whereas ‘traditional food’ is often used by First Nations, and ‘wild food’ or ‘game’ may be used in policy contexts; several study participants referred to ‘traditional food’ or ‘native food’; these terms appear verbatim in the quote) and store-bought food (the terms ‘store-bought food’ and ‘market food’ were used interchangeably by study researchers and participants, referring to retail food sold in grocery stores) choices and processes (harvesting, trapping, fishing, buying, preserving, storing, preparing, cooking and consuming food) communicated by dietary message disseminators, (e.g., public health professionals, government health representatives, academic researchers, and Indigenous knowledge holders) to residents in the ISR with the goal of reducing harm and improving health. We have established that territorial and regional health departments, local health professionals, and allied health professionals in the ISR generally communicate dietary messages that are primarily informed by federal dietary guidance; this results in a lack of inclusion of Inuvialuit country food knowledges, cultural values and perspectives in current messaging [19]. In addition to public health departments, local country food knowledge holders (Elders and harvesters) also communicate dietary messaging to relatives and members of their community through the practice and sharing of traditional food skills and knowledge [19]. Our findings and current research gaps point to a need to address the best methods to collaboratively co-develop and communicate culturally relevant dietary messages among territorial, regional and local dietary message disseminators, researchers, and country food knowledge holders in northern contexts. Accordingly, the aim of this community-based participatory study was to determine how Inuvialuit knowledge and the perspectives of territorial, regional, and local dietary message disseminators, local country food knowledge holders, and the adult public (‘adult public’ refers to adult community members aged 18+ residing in Tuktoyaktuk) can inform the co-development of culture-centered dietary messaging to support healthy, safe, and culturally appropriate diets in Tuktoyaktuk, NWT and the ISR. The objectives were to (1) characterize existing gaps in culture-centered dietary messaging in the ISR; (2) identify public awareness of current dietary messages in the ISR; and (3) provide recommendations to further improve the development and dissemination of effective and culturally relevant dietary messaging for, in, and with the ISR. 2. Methodology and Methods 2.1. Research Approach This study employed Community Based Participatory Research (CBPR) and decolonizing approaches. The CBPR approach supported active and equitable collaboration with Inuvialuit community research partners, recognizing the legitimacy of Inuvialuit perspectives and knowledge systems [20]. The decolonizing approach involved collaborative research activities with Indigenous communities focusing on Indigenous perspectives and epistemologies [21], with the aim of “uphold(ing) the pedagogical, political, moral and ethical principles that resist oppression and contribute to strategies that reposition research to reflect the unique knowledge, beliefs, and values of Indigenous communities” [22] (p. 30). Our choice of research approaches reflects our intention to support Inuvialuit self-determination, a prerequisite for Inuvialuit food sovereignty. Following initial discussions about project directions and interests, the Tuktoyaktuk Community Corporation provided a letter of support for the CFGH project. Once funding was obtained, Gyapay involved community leaders and regional and territorial research partners from the initial stages of this study. For example, meetings with local leadership were held in person in Tuktoyaktuk in February 2020 and virtually in September 2020 to plan the study, receive feedback, and co-develop research materials. Given our inability to collaboratively complete in-person research activities during the COVID-19 pandemic, Gyapay developed a qualitative interview training toolkit and virtually hired, trained, and mentored an Inuvialuk community researcher, Kanelsa Noksana, in Tuktoyaktuk in April–May 2021. Together, Gyapay and Noksana reviewed and amended the ethics forms, interview guide questions, and research methods for clarity and cultural appropriateness. Importantly, by hiring a community researcher to lead in-person research activities, our team fostered research capacity and Indigenous self-determination for research activities in Tuktoyaktuk, which we hope to see continue post-pandemic. Research updates were shared with our research and community partners via quarterly newsletters and virtual group meetings in 2020 and 2021. 2.2. Participant Sample and Recruitment Three methods were used in this study: (1) storytelling interviews (Group A) with Tuktoyaktuk country food knowledge holders (Elders and harvesters knowledgeable about the local food system and country food practices); storytelling interviews (Group B) with Tuktoyaktuk adult community members aged 18+ interested in improving messages about healthy and safe food choices in their community; (2) a talking circle with local public health dietary message developers and disseminators in Tuktoyaktuk (health professionals, community health workers); and (3) key informant interviews with territorial and regional dietary message developers and disseminators (representatives of the Government of the Northwest Territories (GNWT) Department of Health and Social Services (DHSS) and Environment and Natural Resources (ENR) in Yellowknife, representataives of the Inuvialuit Regional Corporation (IRC) in Inuvik, regional allied health professionals of the Northwest Territories Health and Social Services Authority (NTHSSA) Beaufort Delta Region in Inuvik) who had been interviewed for a previous project component in 2020. These three participant categories were selected to increase the diversity of perspectives, in light of the findings and gaps identified during the 2020 interviews. 2.2.1. Storytelling Interviews Storytelling interviews are an effective and culturally appropriate Indigenous research method that privilege Indigenous worldviews, values, and voices [23,24]. Oral storytelling is central to many Indigenous cultures, and is intricately connected with Indigenous ontologies, epistemologies, and relational ways of knowing [23,25,26]. Storytelling interviews are a useful method to resist dominant, Western research methods by honoring Indigenous voices and legitimizing Indigenous stories as a form of scientific knowledge [23,27]. We employed storytelling interviews to enact our CBPR and decolonizing approaches, bridge Western and Indigenous ways of knowing, and foster relational engagement with participants [23,27,28]. Given that our research blends Inuvialuit knowledge and public health messaging, the latter half of the storytelling interviews involved semi-structured interview questions about the desirability of including Inuvialuit knowledge in future public health messages and if so, what this process should look like. 2.2.2. Talking Circles Talking circles (also known as sharing circles) promote respectful, reciprocal, and culturally appropriate dialogue in a circular format; for many Indigenous cultures, circles are sacred and symbolize cycles in the natural world [29,30]. When sharing Indigenous knowledge, a talking circle is viewed as a more culturally appropriate research method than methods such as focus groups, given that participants have the flexibility to share stories relating to the research questions [27]. Talking circles involve introducing oneself, speaking one person at a time, listening respectfully to the person speaking, talking ‘from the heart’, and keeping what is shared in the circle in confidence [29]. We employed talking circles led by the community researcher to resist Western epistemology and research methods and to enact participatory, decolonizing research. 2.2.3. Key Informant Interviews Key informant interviews are qualitative, in-depth interviews of a non-random group of experts selected for their knowledge of their organization or the subject matter [31]. Given that participant selection is not random, a variety of key informants must be selected to obtain a nuanced understanding [31]. Key informant interviews typically employ closed- and open-ended questions and are often used in conjunction with other data collection methods to learn about an organization, program, problem, or topic [31]. We conducted key informant interviews with territorial and regional dietary message stakeholders to gain a detailed understanding of their current involvement in co-developing culture-centered dietary messaging in, with, and for the ISR and preferences for such processes in future. 2.3. Data Sources and Procedures A list of potential participants for the storytelling interviews and talking circles was developed in collaboration with the primary community researcher, and supplemented via purposive, snowball sampling with another community researcher and a local health professional in Tuktoyaktuk. Gyapay developed a list of potential participants for the key informant interviews based on their prior involvement in the CFGH study, and an additional participant was invited to increase sample diversity. Participants were recruited by telephone and email. Noksana conducted 10 storytelling interviews (A and B) in June 2021 and a talking circle with two participants in July 2021 in Tuktoyaktuk. Gyapay conducted 5 key informant telephone and videoconference interviews in June 2021. Storytelling and talking circle pilot interviews (n = 2) were initially completed by Noksana with Gyapay as part of the community researcher training. Open-ended questions were asked throughout the interviews, and probes were utilized to elicit further information and clarify participant responses. Storytelling interviews (A and B) lasted approximately 30 minutes each and the talking circle and key informant interviews lasted approximately 60 minutes each. Participants provided either verbal or written consent, and all interviews were audio-recorded with permission. All interviews were guided by an interview guide, developed by Gyapay and reviewed by Noksana (Supplementary Materials). Demographic information (gender and self-identified ethnicity) was collected with participant consent to understand the relationship between demographics and preferences for dietary message development and dissemination. Inuvialuktun interpretation services were offered, but not requested by any participants. Storytelling interview and talking circle participants received a $50 grocery gift card in appreciation of their time and commitment. The audio recordings were transcribed, reviewed, and analyzed utilizing Braun and Clarke’s guide to thematic analysis [32] and Saldaña’s first and second cycle coding methods [33], combining inductive and deductive approaches. Descriptive coding was conducted using NVivo® version 12 qualitative analysis software [33,34]. Since Noksana was no longer in the community, a second community researcher returned transcribed data to country food knowledge holder participants in person and Gyapay returned transcribed data to key stakeholders by email. Member checking enabled participants to approve the publication of their quotations, further developing trusting relationships and actively engaging participants in the research analysis process [35,36,37]. Findings were reviewed with the community researcher and our territorial and regional partners and were returned to all participants via infographic posters. All audio files of the storytelling interviews were provided to the Inuvialuit Regional Corporation to honor OCAP® principles, enabling the data to be owned and controlled by an Inuvialuit organization. This study received ethical approval from the University of Waterloo (ORE#42948) and a Scientific Research License (#16832) from the Aurora Research Institute. 3. Results Here, we provide an overview of participant characteristics, followed by a discussion of seven major themes and sub-themes that emerged from the data (Table 1). We begin with a summary of the Inuvialuit food system and current practices of culture-centered dietary messaging in, for, and with the ISR from the perspective of all participants. We then discuss residents’ awareness of public health dietary messages in Tuktoyaktuk. We describe the successes and challenges of collaborative culture-centered dietary messaging efforts in the ISR and end with a summary of preferences and recommendations for collaboratively developing and disseminating culture-centered dietary messaging in Tuktoyaktuk and the ISR. We include participant quotations that are reflective of the overarching themes. 3.1. Participant Characteristics The research involved 17 participants (Storytelling interviews A, n = 7; Storytelling interviews B, n = 3; Talking circle, n = 2; Key informant interviews, n = 5) (Table 2). Participation of men and women varied by method as did the participation of Inuvialuit and non-Inuvialuit. 3.2. The Inuvialuit Food System Tuktoyaktuk country food knowledge holders described their understanding of the healthfulness and safety of country and store-bought foods, indicating their preference for country foods. Most participants recounted growing up eating country foods if they did not attend residential school, and all described healthy food as country food, as reflected by this statement: “Healthy foods mean traditional food, just more useful to us because we grew up with it. And I know that it works because everybody’s going back to traditional foods. Processed foods are not very good as we know, but fruits and vegetables are good too, but traditional food is the most important that we grow up with. So we’re still using it as of today.” (SIA6) One participant noted that consuming country foods is both healthy and safe. They explained that the health benefits of consuming whale, particularly muktuk, and seal outweigh potential contaminant risks and that these country foods are healthier than store-bought foods: “…these native foods [country foods] are way more healthy to eat than store-bought food. It outweighs the contaminants that are in animals that we eat…you’re better off eating it than to not eat it.” (SIA2) In contrast, most participants noted that processed store-bought foods are unhealthy and some indicated that chronic diseases, such as obesity and diabetes, stem from the consumption of unhealthy store-bought foods. 3.3. Dietary Challenges in the ISR Most participants noted that climate change is challenging the safe preparation of country foods, requiring them to change the timing of harvesting and food preparation due to warmer weather. A commonly discussed example was the need to harvest beluga and prepare muktuk later in the summer to prevent spoilage and botulism, as explained here: “It’s really changing because summertime it gets too hot and you’ve got to do the whale a lot quicker than when it used to be kind of cold. Usually we’d keep it hanging up for two days, but when it gets too hot we leave it up for one day. And that’s no good… With the sun up 24 hours a day you’ve got to do it a lot quicker and it, and you leave a tarp on it too long it spoils right away so you’ve got to really watch because the sun is the one that really causes botulism or something on the whale and it gets really poisonous. So you’ve really got to take care of your whale.” (SIA7) Two country food knowledge holders described how they became severely ill with botulism poisoning as a result of improper storage in hot temperatures, causing the muktuk to spoil. They described subsequently learning how to properly prepare muktuk safely in warmer weather and then sharing this knowledge with others, as recounted here: “…it did just about take my life, but I still continue to make it. You know, after a while we continued to make it and we still eat it. So it’s important, especially muktuk, like I said you know, you have to be really careful.” (SIA2) Relating to store-bought food challenges, one participant noted that healthy store-bought foods are often unavailable or unaffordable in the ISR, challenging residents’ ability to make healthy food choices: “Because unfortunately in those smaller communities their healthiest option just isn’t an option… Like often there’s not any [store-bought foods] that aren’t unsweetened or there’s things that aren’t unsalted or you know it’s just, you just have to work with what’s there and it’s maybe not necessarily the healthiest or the best…” (KII4) 3.4. ISR Culture-Centered Dietary Messaging Underscoring the need for the present study, several territorial and regional dietary message disseminators noted that current messaging in the NWT focuses heavily on nutrients and nutritional benefits of foods rather than adopting a more holistic and high-level perspective, as expressed in the following: “So messaging around food, especially from government entities, tends to be very nutrient focused. “Meat has iron, milk has vitamin D, vitamin A and calcium.” And I’m not entirely sure we need to be that specific. I think diet messaging should start, and I think it is, I think Health Canada and dietitians in Canada are starting to get on board with this, is use more general concepts when we’re talking about diet. So, what that might look like here is “country food is superior meat”, or “it’s equal or superior to store-bought meats”… You know, “eat a balanced diet that includes country food as well as plants”. Like getting a more general approach to messaging, emphasizing above all else that country food is both nutritious and safe, specifically from a contaminants perspective. That is number one thing that people always, always ask.” (KII2) Regional and local dietary message disseminators expressed support for tailoring messages to specific ISR communities given their knowledge of local culture, food availability, and needs. However, territorial dietary message disseminators do not typically develop messages specific to the ISR, creating challenges with representation and inclusion of Inuvialuit culture in messaging. One participant did note that the GNWT has made efforts to better represent Inuvialuit communities, culture, and country foods in their general food security messaging after being informed of this omission by an Indigenous advisory board. A country food knowledge holder highlighted the harm done by territorial messaging that lacked Inuvialuit input. Messages warning about contaminants in country foods have increased fears among residents about consuming muktuk and seal. Inuvialuit have advocated for messaging to be modified to reflect the health benefits of consuming country foods. This reflects a clear need for collaboration among local Community Corporations, Hunters and Trappers Committees, IRC, harvesters, researchers, and public health workers in the NWT when developing and communicating messaging to ensure that it is balanced and takes into consideration local culture and values: “I think it’s just important that the government have to start listening to what, you know when Elders speak about our traditional food because I’ve seen them try to put the fear in people, you know, and I felt it was really wrong at the time, you know, people wondering whether it’s still safe to eat our food, which is full of crap as far as I can see. You know, we shouldn’t be afraid to eat our native food, we shouldn’t. You know, even if they do have contaminants, it outweighs the benefits that we get from other parts of it…” (SIA2) Relating to climate change, participants described how messaging typically does not address the safety of country foods themselves but rather focuses on the safety of harvesters when out hunting or fishing. Similarly, messaging from the GNWT DHSS about the safety and nutrition of country foods tends not to address climate change directly. Rather, messaging addresses harvester safety or the availability of new species in communities given changing habitat or migration patterns. 3.5. Current Practices of Culture-Centered Dietary Messaging Next, drawing on all interviews, we describe the involvement of territorial, regional and local dietary message stakeholders in developing and/or disseminating culture-centered dietary messaging in, for, and with the ISR to contextualize current practices. Involvement in Culture-Centered Dietary Messaging We found that territorial and regional dietary message stakeholders from the GNWT DHSS, GNWT ENR, NTHSSA Beaufort-Delta Region, and IRC and local dietary message stakeholders from Tuktoyaktuk, including country food knowledge holders and community nutrition program coordinators, are involved in developing and/or disseminating messages about food in/for the ISR that include traditional knowledge and local perspectives (Table 3). nutrients-14-01915-t003_Table 3 Table 3 Role of territorial (NWT), regional (ISR), and local (Tuktoyaktuk) stakeholders in the development and/or dissemination of dietary messages that incorporate community and cultural perspectives about food in/for the ISR, and approaches employed. Dietary Message Department/Stakeholder Role in Culture-Centered Dietary Messaging and Target Audience Methods for Including Community and Cultural Perspectives in Current Messaging GNWT Department of Health and Social Services (DHSS) Office of the Chief Public Health Officer (OCPHO), Advisor (Yellowknife) Develops and disseminates country food consumption guidelines and health messages about contaminants in country foods to NWT public No ISR-specific messages Consults with Indigenous community leadership to inform message development and communication based on Indigenous knowledges and preferences Example: Fish Consumption Guidance [38] Office of the Chief Public Health Officer (OCPHO), Health professional (Yellowknife) Develops nutrition messaging about country foods and store-bought foods to NWT public No ISR-specific messages Develops and reviews messages with GNWT Indigenous advisory board to include Indigenous knowledge about country foods, traditional harvesting and preparation skills and determine best methods of communication Develops messages about country foods with country food knowledge holders and local health professionals across the NWT Example: Traditional Food Fact Sheets [39] GNWT Department of Environment and Natural Resources (ENR) On-the-Land Unit (Yellowknife) Develops and disseminates messaging about safe and culturally respectful country food harvesting practices to NWT public No ISR-specific messages Works collaboratively with Indigenous governments, organizations, and other partners to include Indigenous knowledge about safe and respectful harvesting practices Example: Hunter Education Program [40] Northwest Territories Health and Social Services Authority (NTHSSA)- Beaufort-Delta Region Regional allied health professionals (Inuvik) Develops and disseminates messaging about nutrition, healthy country and store-bought food choices, and healthy cooking to ISR public through programming and client appointments ISR-specific messages Develops and modifies messages to promote country foods and healthy store-bought food choices available in ISR communities Collaborates with country food knowledge holders to disseminate messages and organizes workshops for country food knowledge holders to share their traditional country food knowledge with the public Example: “Beaufort Delta Food Guide”, a modified Canada’s Food Guide ‘healthy plate’ poster incorporating Inuvialuit country foods (Figure 1) Local health professionals and community health workers (Tuktoyaktuk) Develops and disseminates messaging about nutrition, healthy country and store-bought food choices, and healthy cooking to ISR public through health promotion programming and patient assessments ISR-specific messages Develops and modifies messages to promote country foods and healthy store-bought food choices available in ISR communities Organizes workshops for country food knowledge holders to share their traditional country food knowledge with the public Example: Promoting country food consumption during Well Child clinic visits with mothers [41] Inuvialuit Regional Corporation (IRC) Health and Wellness Division (Inuvik) Does not develop dietary messaging Supports dissemination of ISR-specific messages developed by communities Provides opportunities for Inuvialuit to disseminate their knowledge about healthy, safe and traditional country food practices through workshops and programs in the ISR Example: Country food preparation workshops led by Elders Tuktoyaktuk Tuktoyaktuk country food knowledge holders (Elders, harvesters, fishers, trappers) Disseminates Inuvialuit knowledge about healthy and safe country food choices and safe harvesting and food preparation skills to the public ISR and Tuktoyaktuk-specific messages Draws on personal experience and Inuvialuit knowledge learned from relatives and others in the community Example: Personal country food preparation demonstrations and harvesting trips Tuktoyaktuk community nutrition program coordinators (health professionals and community health workers) Develops and disseminates messaging about healthy country and store-bought food choices through recipes and cooking programming to the public ISR and Tuktoyaktuk-specific messages Develops and modifies messages and resources to promote country foods and healthy store-bought food choices available in ISR communities Organizes workshops for country food knowledge holders to share their traditional country food knowledge with the public Example: Healthy Family Collective Kitchen program incorporating country foods in recipes [42] At the territorial level, the GNWT DHSS develops messages in partnership with Indigenous communities and the GNWT’s Indigenous advisory board. These stakeholders provide direction as to how the GNWT should engage with communities to develop messaging, who should be involved, what messages should address, and preferred methods for message dissemination. The GNWT also consults communities to record Indigenous knowledge about harvesting and food preparation practices about specific country foods when developing country food dietary messaging. For example, the GNWT DHSS contacted harvesters and cooks across the NWT when developing the Traditional Food Fact Sheet series to include their Indigenous knowledge about country foods. Connections were facilitated by the Community Health Representatives (CHRs), trained liaisons who provide community health services in collaboration with local health practitioners. Unlike the GNWT DHSS, the IRC does not formally gather and share community and cultural perspectives about food since they do not develop or disseminate dietary messages to beneficiaries. Rather, the IRC employs Inuvialuit and invites Elders to share knowledge about the Inuvialuit food system during programming. Thus, reflecting its larger purpose, the IRC supports Inuvialuit in directly sharing their knowledge with their community about healthy and safe food practices through cultural teachings. At the local level, one health professional indicated that they utilize Canada’s Food Guide for First Nations, Inuit and Métis to encourage clients to incorporate country foods into their diet. Complementarily, they discussed searching online for information about which types of country food to consume for specific health profiles, so as to tailor their advice to clients: “So, if I’m talking with a patient that maybe needs a little bit more fibre in their diet, I can help them just Google it and we, you know, we look for credible websites and then we’ll come up with a list of foods… and so you can actually find traditional foods online that are more specific to the northern diet, right… we have access to Canada’s Food Guide, but the northern version as well. So, it includes traditional foods… there’s seal meat on there, and there’s char, and caribou, and muktuk and that kind of stuff. So, it’ll show you which part of the food guide it’s part of and then how to kind of incorporate that into your diet as well.” (TC2) Importantly, local country food knowledge holders (Elders, hunters, fishers, and trappers) disseminate dietary messages in their community when sharing their knowledge about the Inuvialuit food system, most often when harvesting, trapping, fishing, preserving, storing, preparing, and cooking country foods. Participants described knowing which country foods are healthy and safe to harvest and consume by drawing on their Inuvialuit knowledge, which has been passed down to them by parents, grandparents, and other relatives, and learned from experience. Inuvialuit knowledge holders teach younger relatives how to determine the health of animals and safely harvest and prepare country foods through demonstrations and hands-on practice during harvesting trips and when preparing foods at home. As one participant explained: “I learn [teach] them… with my relatives, or take them out hunting or camping. And as we do down here, we invite anybody to come and watch and learn as we do.” (SIA6) 3.6. Awareness of Public Health Dietary Messages in Tuktoyaktuk To better understand the current state of dietary messaging in the ISR, we asked about participant awareness of such messages. Some, but not all country food knowledge holders were aware of dietary messages promoting healthy and safe food in Tuktoyaktuk. Those who indicated awareness described seeing posters at the local health center or at Healthy Babies and Healthy Families programs and hearing or seeing messages about healthy food choices from doctors, commercials on TV, and Facebook posts. Importantly, one participant identified Elders as important local dietary message disseminators, highlighting the reality that dietary messages in Tuktoyaktuk are not solely developed and communicated by public health departments; Inuvialuit knowledge offers another form of dietary messaging. The participant explained: “And then from our knowledge too, our Elders have a lot of knowledge of that too, so don’t forget about them.” (SIA6) Of the dietary messages seen and heard, some but not all included messages promoting country foods. As one participant described: “The doctors always say the, you know the traditional foods is more healthier to have than our processed foods.” (SIA6) Similar to the country food knowledge holders interviewed, some but not all residents recalled seeing and hearing dietary messaging in Tuktoyaktuk. One referred to posters promoting healthy store-bought food choices developed by the CHR and another described hearing messages promoting eating healthy store-bought foods through the Healthy Family program and Prenatal Nutrition program, and seeing posters from Nutrition North Canada and IRC explaining how to safely prepare muktuk. Another resident described messages from the Nunavut Food Guide promoting the consumption of country foods that were shared during the Healthy Babies program. They also described messages promoting harvesting, fishing, and trapping that they had seen on the TV, radio, posters, and newspapers over the past decades from a range of sources, including the federal government, GNWT, and the Government of Nunavut. Importantly, an Inuvialuk participant noted that they receive messages about country foods primarily from their family, similar to the perspective articulated by a country food knowledge holder. One participant mentioned hearing fewer messages that encourage the consumption of country foods in Tuktoyaktuk compared to messages that encourage the consumption of healthy store-bought foods and indicated the need for further messaging that promotes country foods. 3.7. Collaborative Culture-Centered Dietary Messaging Successes and Challenges 3.7.1. Existing Collaborations with Communities Territorial and regional dietary message disseminators collaborate with communities about messaging in various ways. The GNWT DHSS OCPHO collaborates with community leadership when developing country food consumption guidance to determine the frequency of consumption and whether the issuing of a consumption notice is required. As one participant described: “So one of the important parts […is] seeking out the Indigenous traditional knowledge… for example… when we’re given data on certain contaminants and we run the quantitative risk analysis, one of the input factors in those calculations is consumption frequency. And that’s where we definitely do consult with… the relevant Indigenous communities and their representatives on that particular matter.” (KII1) Several territorial and regional dietary message disseminators noted that they collaborate closely with CHRs in the ISR to seek out local perspectives and knowledge about food when developing messaging and to disseminate dietary messaging on their behalf. Nevertheless, they described numerous messaging-related challenges when working across scales. For example, one participant described encountering difficulties when country food knowledge holders disseminated dietary messaging of their choosing without input from territorial and regional counterparts, creating confusing messaging. One participant noted that high turnover rates among local health professionals, such as nurses, impede collaboration with local message disseminators. CHRs in the ISR may be better-poised as collaborators, since they have lower turnover rates compared to nurses and physicians, given that many are from the community. A regional allied health professional expressed a lack of collaboration with counterparts in other NWT regions around the development of dietary messages and resources, particularly about country foods, citing regional differences: “Like we, up here in the Beaufort Delta, are really unique; like we don’t do, there’s nobody else that does the same type of work that we do. So I’ve never honestly asked anybody about what they do for resource development, but I kind of don’t think there is much else being done… So sometimes we’ll reach out to each other to be like “oh does anybody have anything for this or that?”, but yeah as far as collaborating for resource development there’s not been any of that.” (KII4) Several participants noted that the time, resources, and communications required to improve and develop new messaging and programs focusing on country foods and Inuvialuit knowledge are a barrier, given that local and regional dietary message disseminators are strained by other job demands. Another barrier raised was the disconnect between community, government, and academic timelines and budgets, impeding the building of trusting relationships between researchers and local, regional, and territorial dietary message disseminators to collaborate on message development. A participant expressed this challenge: “I think again is that collaboration from the very beginning and the conversations. I don’t think, not everyone realizes the importance of those conversations and what they mean to building relationships and doing the work. And you have to have that time to allow for that negotiation and that back and forth and the figuring things out together. And of course, on the flip side, as a challenge you know, both communities and governments have very specific deadlines or time frames for things or you know, money runs out or all of that kind of stuff. So balancing that openness, that flexibility, that building from the ground up with needing to show deliverables and progress is certainly a challenge.” (KII5) 3.7.2. Difficulties Collecting and Communicating Cultural Food Knowledge Participants highlighted challenges related to the reality that non-Inuvialuit professionals are often in the position of creating dietary messages for the ISR, and may lack knowledge of the local culture and food system. When seeking to include cultural knowledge in dietary messaging, some experienced resistance among Inuvialuit to communicate their knowledge in written form. Further, country food knowledge holders often have different preferences for methods of harvesting and preparing country foods, making it difficult to determine the most appropriate knowledge to communicate when developing a message. When discussing community interests in accessing country food recipes, one participant noted that it is difficult for non-Inuvialuit health professionals to develop such resources. They also highlighted the lack of cultural awareness training and mentorship available to non-Indigenous health professionals working in the ISR: “… I sometimes wish like as [a health professional], I wish there was just more… like training or orientation provided in regards to that because they really don’t get any introduction to that when we come into these roles… I know we have a new cultural awareness training online… but yeah or even like having someone that you can connect with when you’re in these roles to kind of guide you through it. Yeah it’s tough, it’s just kind of like when you start these positions like you’re kind of on your own to kind of like figure it out and sort it out and learn.” (KII4) Regarding access to appropriate information, a local health professional noted they would benefit from access to scientific research articles that discuss the nutritional benefits of country foods compared to store-bought foods to support their work and dietary recommendations to patients: “… there’s a lot of studies about non-traditional foods, like the healthy ones, the unhealthy ones, but I find like there isn’t too many actual studies that I can refer to, to back up my evidence, right. A lot of the stuff is just some stuff that I’ve heard from other [health professionals] or even Elders and it does make sense. But it’s, like I wish that there were actual studies that would show us, like OK like, why is caribou that much better, like does it, you know, how much iron does it have compared to beef or, you know. What is the, you know, what are the benefits for your health from eating traditional foods versus non-traditional foods and actually looking at numbers…” (TC1) 3.8. Recommendations for Culture-Centered Messaging in the ISR Participants made numerous recommendations for co-developing and disseminating culture-centered dietary messaging in the ISR, including who should be involved in message development and dissemination, how community and cultural perspectives should be incorporated in messaging, and which types of messages they would like to see communicated. All participants agreed that they would like to see more Indigenous knowledge and community perspectives about country food included in future dietary messaging in the NWT and ISR. Local country food knowledge holders described the importance of promoting country foods in messaging given their nutritional and cultural benefits and the importance of transmitting country food preparation skills and knowledge to youth for cultural continuity and safety, and the teaching of Inuvialuit values. One resident explained further, saying: “Yes. Because it’s a part of the culture and in order for culture to continue then people need to understand the—how the food fits into it and how the culture fits into the food.” (SIB2) Several participants reflected on the importance of collaborations with local dietary message disseminators and community members as a means of developing messages that are more culturally relevant and respectful. A participant summarized this sentiment: “Well I think it’s inherently important to work together, you know and when we have representatives from the relevant stakeholders group, then it makes for basically a product that comes out that I think is much, much better at the end of the day than you know, doing it with one set of lens as opposed to multiple lens… So this is why having that sort of more grounded and realistic understanding and you know, this understanding can only be reached in consultation with our partners, Indigenous partners” (KII1) 3.8.1. Effective Collaborations for Culture-Centered Messaging At the local scale, all participating residents and local health professionals agreed that the IRC and GNWT DHSS should collaborate with them or other community members when developing messages about healthy foods. One identified Elders and health professionals in the community as trusted sources. Importantly, it was recommended that IRC and GNWT DHSS communicate with communities to determine which dietary messaging projects they can support and fund. Several country food knowledge holders felt that the GNWT should transfer leadership to communities to develop and disseminate dietary messages themselves rather than relying on prescriptive government messaging. Similarly, participants commonly recognized that collaborations with Indigenous communities are needed to shift away from the development of messages for the ISR to the development of messages with, or better yet, by, the ISR, with the aim of decolonizing this process: “I think my experience is that working collaboratively and working together to identify the key questions, challenges, concerns, all of that and then you know respond accordingly, I think has to happen with multiple knowledge systems together or needs to be grounded in Indigenous knowledge systems. I think we often kind of try to figure out how to fit it in versus starting from place as a site of meaning right, and then building outwards how we do that.” (KII5) Several ideas for future collaborations were recommended by local health professionals. For example, one participant noted that increased collaborations between nurses and allied health professionals in Tuktoyaktuk are needed to improve message reception by the public. Another participant suggested holding a seminar for all CHRs in the ISR to learn more about nutritional information related to country foods, which they can then share with the public: “And so, I wonder if the Community Health Reps in the Beaufort Delta or the ISR were able to sit on a seminar that teaches them a little bit more about traditional foods and just gives them a few good pointers. Then they could pass that information onto the patients that they see…” (TC1) Another participant proposed hiring a dietitian specializing in country foods to travel to the ISR communities to provide local health professionals with additional knowledge and resources to inform messaging. A health professional described their interest in partnering with an Inuvialuit cultural coordinator and connecting with more country food knowledge holders during the development of messaging and programming to better include Inuvialuit knowledge about country foods. Another participant explained how IRC is already doing some of this work by hiring Inuvialuit knowledge holders to deliver country food programming and messaging in a culturally appropriate way: “…our department seems to rely on recruiting kind of people who have a strong reputation in the communities who are around, to come join our services and we don’t really prescribe or tell them what they say, they just kind of know what to say, or they have their own bit that they’re going to say. So you don’t see us being too prescriptive with that messaging, but we know the right people to get to deliver the message.” (KII2) Several participants suggested collaborating with students when developing messages to provide youth with a sense of agency: “And I think, like the young people need, you know, sort of they need to be included, so that it doesn’t seem like something that’s dictated to them, but something rather that they’ve participated in the development of. I mean it’s really hard to get young people to buy into something that they haven’t been part of. So, I think any time we can include not just the Elders, but you know, so the collaboration between the Elders and youth is a good strategy.” (SIB2) 3.8.2. Collecting and Communicating Local Perspectives and Knowledge about Food Participants highlighted the importance of acknowledging that Indigenous communities hold collective expertise about their country food system, and that they have been hubs of healthy food communication since time immemorial through the sharing of Inuvialuit knowledge about harvesting and food preparation practices. Participants stressed the importance of acknowledging the historical traumas that Indigenous peoples have faced when developing dietary messaging about food, particularly surrounding the content and quantity of information provided: “But I think that’s something we miss is… really creating that space for messaging is so important. And I think recognizing too… that how we share and communicate information with people who are, who’ve gone through a lot of trauma is very different… the idea that we need to be meeting people where they are, but also sharing it in a way where they get the information they need without being overwhelmed and recognizing that if you’re, you know if you’re trying to survive, you don’t want a lot of information on what the arsenic levels in moose kidneys are. You know? You need to know, ‘can I eat that kidney’?” (KII5) A suggested method for territorial, regional and local dietary message disseminators to collaboratively gather Inuvialuit knowledge is to ask a question to multiple community members and then verify the content through local leadership. Incorporating questions within existing nutrition and cooking programming was also suggested as a useful method to collect community perspectives. Public engagement sessions were discouraged, given the elevated volume of ongoing community sessions about any number of topics. At the territorial level, having Indigenous guidance, (e.g., from those on the GNWT’s Indigenous advisory board) was deemed necessary for DHSS to develop effective and culturally appropriate dietary messages about country foods. Preferred methods for gathering and sharing Inuvialuit knowledge and local perspectives in dietary messages by territorial, regional and local dietary message disseminators include: creating simple, high-level messages; incorporating visuals; delivering messages orally, in person, and through Facebook; holding meetings, events, or workshops on the land when collecting and sharing local knowledge and perspectives about food; and involving communities, especially youth, in the development and communication of messages. Participants indicated the following preferred approaches for communicating dietary messages about country foods: cookbooks, posters, and brochures with local art and photos; Facebook posts; and public service announcements on CBC radio, the CBC North TV station, and the bingo channel. Effective methods of disseminating messaging in Tuktoyaktuk included posters displayed in public locations, (e.g., schools, community halls, grocery stores, hamlet and community corporation offices, and youth centers), radio, TV announcements, and Facebook posts. A local health professional suggested creating pamphlets for the CHR to distribute at the school, community hall, and grocery stores. Several participants mentioned the importance of translating dietary messages into the local Indigenous language(s). Further, oral communication of Inuvialuit knowledge about food was noted as a culturally appropriate and effective method. Finally, a territorial government representative described the importance of taking time to develop trusting relationships, familiarizing oneself with local community protocols, utilizing data management or sharing agreements directed by community preferences, and securing funding to hire community members as mechanisms for improving the inclusion of Indigenous knowledge and local perspectives in current dietary messages. 3.8.3. Communicators of Cultural Perspectives and Knowledge about Food Country food knowledge holders identified community members, especially Elders, as the primary mechanism by which Inuvialuit knowledge about country foods should be communicated to the public, including knowledge and skills related to harvesting and food preparation. Similarly, both local health professionals and the public believed that Elders should be involved in sharing their food-related knowledge with the community. Some participants suggested that IRC, GNWT DHSS, academic researchers, and local health professionals should work with Elders, via individual interviews or a knowledge circle, to develop and review messages about country food. In contrast, a country food knowledge holder expressed dismay that the GNWT and IRC are at all involved in communicating information about country foods, explaining that it should be Elders themselves who communicate their knowledge orally and experientially, following Inuvialuit tradition: “To me, it’s so sad we have the government and IRC helping us to promote on what we have learnt, we could pass it on like this—like you asking me questions and I’m telling you the answers. This is the way it should be taught, face to face and to do it out there you have the means to have a smoke house and stuff. That’s the way to learn. That’s how I see it.” (SIA6) Participants commonly highlighted the need for non-Indigenous government health representatives and health professionals to provide opportunities for communities to develop and deliver messaging themselves, or at minimum to collaborate with Inuvialuit stakeholders when developing and delivering messaging promoting country foods and Inuvialuit knowledge. Inuvialuit residents understand their culture, food system, and local needs, and are trusted by their community to communicate health information, as explained here: “I mean people trust members of their own community more than folks from outside right? …Particularly with… colonization, residential schools and all of that, you know there is a huge trust gap. So wherever possible, you know working with those champions in the communities who can be the ones delivering messages is so critical.” (KII5) 3.8.4. Types of Culture-Centered Messages Several country food knowledge holders expressed an interest in increased messaging about traditionally-used food preparation techniques and safe methods for country food preparation. More specifically, they identified a need for knowledge sharing about preparing whale, dried meat, and dried fish. Most advocated for such messaging to be developed and delivered by Elders through hands-on workshops with youth and interested community members, as explained here: “First hand, watching people or even getting knowledge from the Elders. Sitting with an Elder, you get a lot of knowledge from the Elders. Like hands on or speaking with them because you know there’s a proper way and not a proper way of doing things so you have to know how to do it from the Elders because they know what they’re doing.” (SIA6) Country food knowledge holders identified youth as a particularly important target group for teaching safe country food harvesting and preparation methods, given their perceived disinterest in Inuvialuit practices and susceptibility to health risks posed by improper food preparation and preservation stemming from their relative inexperience as harvesters. Responding to this gap, another knowledge holder recommended increasing on-the-land programming and Inuvialuit food preparation workshops with students and Elders. One resident explained that youth lack exposure to sufficient country food dietary messaging in their community, and advocated for the development of new youth-targeted posters for Tuktoyaktuk, for use at the school and elsewhere. Residents agreed that they would like to see more information about the nutritional and cultural benefits of country foods included in dietary messaging; this could include promoting country foods as healthier than store-bought foods, given their nutritional benefits and association with Inuvialuit cultural values and procurement practices: “I think it’s important for the message to get out there that it’s healthy, that it’s healthy fats, that’s it doesn’t contain sugars and salts and it’s not, doesn’t contain preservatives. And just those messages that these are really healthy foods, they’re from the earth, you know, and these animals give their lives to us and the hunters, the traditional hunters thank them for that… and I think that’s really important.” (SIB1) Further, a health professional recognized the importance of plant knowledge in the community. They suggested creating a resource outlining the traditional uses of plants; which varieties are safe to harvest, eat and use; how to identify these varieties; and how to safely prepare them for consumption. Similarly, regional and local health professionals expressed an interest in receiving support to partner with local knowledge holders to incorporate country foods in the development of food and medicine guides as well as nutrition workshops. Participants suggested improving the inclusion of Indigenous perspectives about food in messaging, particularly relating to the cultural benefits of harvesting and consuming country foods. This would enable a more holistic approach to dietary messaging that bridges both Western scientific and Indigenous knowledge systems, as noted here: “I mean I think the one important one and I think some do this really well and some don’t, I think is, like identifying the importance of the food we’re talking about. You know and not just sort of a fact sheet, like not just something that says you know, “you can eat this much and blah, blah, blah”. Like you know you need more cultural context to it about why the food is important and what it means and also recognizing its holistic role in things. Again and sort of Western worldviews, you know we’re very good at separating things into you know, discrete components and so I think we missed some of that sometimes.” (KII5) One concrete suggestion for engaging youth in creating locally tailored and culturally meaningful dietary messaging was to work with students at Mangilaluk School in Tuktoyaktuk: “I think it’s important to show the harvesters too, like we have, we’re really privileged here to have really young harvesters… And they’re out and the community knows them and they know that they go out hunting and it would be nice to see them pictured doing what they’re doing, you know. And it’s encouraging to the little guys, who look up to them and their kids as well… it’s just super positive for people to see people doing stuff here… And like I was thinking in the school, it would be a fun project for a photographer, a student photographer to go out with the harvest, the young harvesters that we have and take pictures of them harvesting and, or fishing or whatever. And you know, to do some posters with pictures and then for drawings, you know, the kids could do drawings, like those are things that attract people’s attention…” (SIB1) 3.8.5. Messaging about Store-Bought Foods While country foods were a key focus of discussions, participants also commonly identified the need for more ISR community perspectives and realities to be included in public health dietary messaging about store-bought foods. For example, they highlighted the need for messaging about the detrimental health effects of regularly consuming unhealthy foods, such as pop, junk food, and ready-made foods. One resident felt that sufficient messaging exists regarding the nutritional benefits of healthy store-bought foods, and health professionals identified the need for messaging promoting healthy store-bought food alternatives since produce is often unavailable or too expensive to purchase in Tuktoyaktuk. Local health professionals recommended building on successful knowledge sharing initiatives previously organized by community health workers and cooking program coordinators. For example, household visits by the CHR to share information about healthy food choices were highlighted as another useful mechanism for communication. Likewise, pop-up displays at local grocery stores with visuals of amounts of sugar and sodium found in processed foods and sugary beverages were deemed an effective way of communicating nutritional information to the public. Finally, one health professional suggested partnering with the grocery stores to create a ‘stop light’ labeling system based on healthfulness to suggest appropriate levels of consumption. 4. Discussion This study was designed to inform the co-development of culture-centered dietary messaging in Tuktoyaktuk, drawing from the perspectives of territorial, regional and local dietary message disseminators, local country food knowledge holders, and interested residents. Our findings confirm the need for increased inclusion of cultural and community perspectives about healthy and safe food choices and processes in dietary messaging communicated in the ISR, particularly related to the holistic health benefits of harvesting, preparing and consuming country foods. As shown by Arctic environmental health risk communication studies and Indigenous health communication studies, our findings confirm the importance of tailoring and developing messages in partnership with communities, to ensure that they are grounded in cultural and community knowledge, skills, values, and worldviews [11,12,13,14,15,44,45]. Likewise, our findings support the need for a distinctions-based approach to messaging, acknowledging the different contexts and diversity of Indigenous peoples across geographies [45]. This contrasts with messaging approaches that are meant to serve all Indigenous peoples across a diverse region, as is presently the case for most federal and territorial dietary messaging in the NWT [45]. For example, Health Canada’s 2007 Indigenous Food Guide (IFG), “Eating Well with Canada’s Food Guide- First Nations, Inuit and Métis”, adopts a pan-Indigenous approach, overlooking the diversity of Indigenous peoples and their food systems in Canada [6]. In response, numerous population-specific IFGs and healthy food guidelines [46] have been created by Indigenous communities and health organizations in Canada, (e.g., the First Nations Health Authority’s “Healthy Food Guidelines for First Nations Communities” in British Columbia, and the Government of the Northwest Territories’ “Traditional Food Fact Sheet Series”), reflecting distinctions-based and participatory approaches to message development [39,47]. Our findings also indicate a need to increase communications and collaborations among dietary message stakeholders at all levels (territorial, regional and local), especially among Inuvialuit country food knowledge holders (Elders and harvesters), youth, the GNWT DHSS, ENR, and regional/local health professionals, to co-create regionally and locally tailored dietary messages for the ISR. This finding is consistent with other research calling for participatory message development with experts from varying backgrounds, recognizing and legitimizing Indigenous knowledge holders as dietary message disseminators [8,11,15,48]. Through this ‘two-way sharing’ of Inuvialuit and Western knowledge about healthy and safe food choices and processes, dietary message stakeholders can better learn from each other and engage in a participatory process of communication combining multiple knowledge systems [44]. An example of dietary messaging combining Inuit and Western knowledge systems is the Government of Nunavut’s 2001 “Nunavut Food Guide”, promoting country foods, healthy store-bought foods, and traditional food practices [4]. As the first study of its kind with Inuvialuit, our findings have important implications for dietary message stakeholders across the NWT. Our study advances understanding of current barriers and facilitators to participatory, culturally meaningful dietary message development and dissemination in the ISR, with the aim of informing future health communication efforts in the region. Further, this research extends our knowledge of territorial, regional and local preferences for who should be involved in the collaborative development of culture centered dietary messaging in the ISR, how such processes should take place, which types of messages are needed, and what methods may be best suited to collecting and sharing community and cultural knowledge and perspectives. Notably, our findings indicate that country food knowledge holders are the preferred communicators—through observation-based teachings—of country food harvesting and preparation knowledge and skills in Tuktoyaktuk, given their wealth of empirical and hands-on experience. This approach recognizes Inuit culture as being relationship-based and observation-based, compared to Western culture, which is information-based [49]. Therefore, we call on public health dietary message stakeholders to recognize the legitimacy of country food knowledge holders as effective dietary message disseminators and to support them in communicating dietary information in the ISR through oral, visual, and hands-on teaching, to promote Inuvialuit worldviews, culture, and values. Increasing opportunities for country food knowledge holders to share their Inuvialuit knowledge about food both honors local priorities and reflects key NCCIH recommendations for the development of culturally relevant public health messaging for northern Indigenous communities during COVID-19. The NCCIH ([45] (pp. 11–12)) recommends using ‘wise practices’—namely “Indigenous ways of knowing, principles and solutions”—to inform messaging, and adopting a strength-based approach, acknowledging that “people have the knowledge and expertise to identify and address their own concerns”. These recommendations translate to the dietary messaging context in the ISR, where continued support is required to ensure that Inuvialuit have spaces to share their knowledge about healthy and safe country food practices, for messaging to be developed for communities by communities, and for enhanced intergenerational transfer of Inuvialuit knowledge. Despite strong participant interest in collaborative approaches to messaging, our findings highlight challenges regarding limited resources and time to develop trusting, respectful and collaborative relationships among dietary message stakeholders, particularly among government health representatives, health professionals, academic researchers, and country food knowledge holders. Informed by the culture-centered dietary messaging needs identified by participants, Table 4 presents recommendations for co-developing culture-centered dietary messaging in the ISR, organized by stakeholder group. Further, sufficient resources are required to foster trusting, respectful relationships; therefore, we call on academic researchers and federal, territorial, and regional governments to fund and support projects that foster collaborations among youth, harvesters, Elders, schools, and local health professionals to co-develop locally tailored and culture-centered dietary messages in, for, and with the ISR, as desired by communities. Given that territorial and regional governments often have limited budgets, we recommend that health professionals and government health representatives partner with academic researchers on funded research projects to support the development and evaluation of ISR culture-centered dietary messages. Drawing on the successes of collaborative COVID-19 health communication initiatives grounded in Indigenous culture, (e.g., the co-development of COVID-19 posters by Hotıì Ts’eeda and GNWT DHSS), we recommend that NWT dietary message stakeholders partner with Indigenous health organizations such as Hotıì Ts’eeda to reduce the burden of engagement for all involved stakeholders and build on existing initiatives [45,50,51]. Given our finding that some country food knowledge holders prefer communicating dietary messages directly to their community rather than collaborating with regional or territorial public health departments, we recommend a second, more decolonized approach to dietary messaging whereby communities are supported as needed by federal, territorial and regional public health departments to take leadership in message transmission. This finding has important implications for the future of public health communication in the ISR, whereby communities shift from ‘engagement in’ to ‘leadership of’ dietary message development and dissemination, ultimately fostering Inuit food sovereignty. This aligns closely with actions outlined by Inuit Tapiriit Kanatami [52] (p. 34) in their Inuit Nunangat Food Security Strategy, calling for “Inuit-defined healthy diets that meets Inuit cultural and nutritional needs”. Health Canada’s “Brighter Futures” program is a noteworthy example of an existing federally funded program supporting Indigenous-led dietary messaging in the NWT and ISR [53]. The program funds community-led “Healthy Babies” cooking and nutrition activities for parents of young children and country food harvesting trips with Elders and youth in the ISR, promoting healthy, safe, and culturally appropriate food choices and skills [53]. Further, the school curriculum in the NWT and ISR incorporates country food harvesting, preparation, and cooking programming with youth and Elders, (e.g., GNWT ENR “Take a Kid Trapping” program and school-led country food workshops), reflecting successful partnerships for community-led food programming and dietary messaging [54]. Future research is needed with country food knowledge holders, local public health dietary message disseminators, and community members from all ISR communities to compare culture-centered dietary message perspectives and priorities across the ISR, in addition to other regions in the NWT. Furthermore, there is a need for research to examine the perspectives of federal dietary message disseminators, academic researchers, and ISR youth regarding the development of culture-centered messaging to establish a greater understanding of their experiences and needs. Finally, further research is needed to evaluate participatory, culture-centered dietary messaging initiatives in the ISR and NWT to determine messaging effectiveness as well as barriers and facilitators experienced by stakeholders, with the goal of improving communication policies and practices. Our recommendations for the collaborative development and dissemination of ISR-tailored culture-centered messaging, especially messaging promoting country foods that bridges both Western scientific and Inuvialuit knowledge, have important implications for the ISR, NWT, and Inuit Nunangat given the identified interest in more culturally meaningful messaging grounded in local and regional culture and knowledge. This research makes several noteworthy contributions to Arctic health communication literature by providing a new understanding of preferences for how culturally inclusive dietary messaging should be (co-)developed in the ISR, by whom, and which topics should be addressed to support healthy, safe, and culturally appropriate food choices and processes. 5. Conclusions This participatory study employed a combination of Indigenous and Western qualitative research methods to describe how the perspectives and Inuvialuit knowledge of territorial, regional, and local dietary message stakeholders can inform the (co-)development of culture centered dietary messaging to support healthy, safe, and culturally appropriate diets in Tuktoyaktuk, NWT. As the first study of its kind examining the best methods for culture-centered dietary messaging in the ISR, our findings confirm the need for increased inclusion of cultural and community perspectives about food for the development of culturally inclusive, regionally, and locally tailored dietary messaging. Our study provides a new understanding of territorial, regional and local preferences for the (co-)development of culture-centered dietary messaging in, for, and with the ISR and offers recommendations for future collaborations and independent, community-led dietary message initiatives, promoting Inuvialuit food sovereignty through effective, culturally meaningful health communication. Acknowledgments We thank all participants who took part in this research and our territorial, regional, and community partners at the Government of the Northwest Territories Department of Health and Social Services, Environment and Natural Resources, Inuvialuit Regional Corporation Health and Wellness Division, and community leadership in Tuktoyaktuk, including the Tuktoyaktuk Community Corporation. We appreciate the funding provided by the Northern Contaminants Program and the Canadian Institutes for Health Research, which made this project possible. Supplementary Materials https://www.mdpi.com/article/10.3390/nu14091915/s1, Interview Guide S1: Sample interview guide from Storytelling B interviews with Tuktoyaktuk community members Click here for additional data file. Author Contributions J.G. drafted the manuscript, coordinated the methodological design, and conducted the data analysis. K.N., S.O. and K.S. provided input on the methods. K.S. provided input on the analysis. J.G. coordinated the fieldwork and collected data with K.N., S.O., S.W., B.D.L.; K.S., S.O., S.W. and B.D.L. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Research Ethics Board of the University of Waterloo (ORE#42948) and the Aurora Research Institute (Scientific Research License #16832). Informed Consent Statement Written and verbal informed consent was obtained from all subjects involved in the study, including for the publication of this paper. Data Availability Statement Data is contained within this paper, and no further information about qualitative data can be shared due to ethical/privacy reasons as we worked with vulnerable communities. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Beaufort Delta Food Guide [43]. nutrients-14-01915-t001_Table 1 Table 1 Summary of major themes and sub-themes emerging from multiple research methods. Themes Methods * 3.2. The Inuvialuit Food System SIA 3.3. Dietary Challenges in the ISR SIA, SIB, TC, KII 3.4. ISR Culture-Centered Dietary Messaging SIA, SIB, TC, KII 3.5. Current Practices of Culture-Centered Dietary Messaging3.5.1. Involvement in culture-centered dietary messaging SIA, SIB, TC, KII 3.6. Awareness of Public Health Dietary Messages in Tuktoyaktuk SIA, SIB 3.7. Collaborative Culture-Centered Dietary Messaging Successes and Challenges3.7.1. Existing Collaborations with Communities 3.7.2. Difficulties Collecting and Communicating Cultural Food Knowledge TCC, KII 3.8. Recommendations for Culture-Centered Messaging in the ISR 3.8.1. Effective Collaborations for Culture-Centered Messaging 3.8.2. Collecting and Communicating Local Perspectives and Knowledge about Food 3.8.3. Communicators of Cultural Perspectives and Knowledge about Food 3.8.4. Types of Culture-Centered Messages 3.8.5. Messaging about Store-Bought Foods SIA, SIB, TC, KII * SIA = Storytelling Interviews A; SIB = Storytelling Interviews B; TC = Talking Circle; KII = Key Informant Interviews. nutrients-14-01915-t002_Table 2 Table 2 Participant characteristics and reference codes categorized by research method. Method Number of Participants (n) Gender Self-Identified Ethnicity Stakeholder Type Reference Code * Female Male Inuvialuit Non-Inuvialuit Storytelling interviews A 7 n = 2 n = 5 n = 7 n = 0 Tuktoyaktuk country food knowledge holders (harvesters and Elders) SIA 1–7 Storytelling interviews B 3 n = 3 n = 0 n = 1 n = 2 Tuktoyaktuk community members aged 18+ SIB 1–3 Talking circle 2 n = 1 n = 1 n = 1 n = 1 Tuktoyaktuk health professionals and allied health professionals TC 1–2 Key informant interviews 5 n = 3 n = 2 n = 0 n = 5 Territorial (GNWT DHSS and ENR) and Regional (IRC and NTHSSA Beaufort-Delta) dietary message developers and disseminators KII 1–5 * SIA 1–7 (Storytelling interviews A, participants 1–7); SIB 1–3 (Storytelling interviews B, participants 1–3); TC 1–2 (Talking circle, participants 1–2); KII 1–5 (Key informant interviews, participants 1–5). nutrients-14-01915-t004_Table 4 Table 4 Recommendations for collaboratively developing dietary messages in, for, and with the Inuvialuit Settlement Region (ISR), by stakeholder group. Dietary Message Stakeholders Recommendations for (Co-)Developing Culture-Centered Dietary Messaging in the ISR GNWT Department of Health and Social Services (DHSS) Office of the Chief Public Health Officer (OCPHO) Collaborate with local health professionals, country food knowledge holders, and researchers to develop culture-centered and ISR-tailored messaging, incorporating Inuvialuit knowledge of country food processes and climate change adaptation considerations Fund and support dietary message development and communication projects led by communities, (e.g., student-harvester country food photo project to design posters). Partnerships with academic researchers can provide funding sources to support and facilitate such projects Develop and deliver a country food nutrition training workshop for regional and local health professionals and community health workers in the ISR GNWT Department of Environment and Natural Resources (ENR) On-the-Land Unit Collaborate with local health professionals, country food knowledge holders, and researchers to develop culture-centered and ISR-tailored messaging, incorporating Inuvialuit knowledge of country food processes and climate change adaptation considerations Fund and support dietary message development and communication projects led by communities, (e.g., country food preparation workshops led by Elders, traditional edible plant identification resources) Northwest Territories Health and Social Services Authority (NTHSSA), Beaufort-Delta Region NTHSSA Beaufort-Delta Region administrators Develop cultural training resources and mentorship opportunities with local country food knowledge holders for non-Inuvialuit (allied) health professionals Improve local health professionals’ and community health workers’ access to scientific information about the nutritional benefits of country foods through communications with researchers and the GNWT DHSS Regional allied health professionals (Inuvik) Increase partnerships with local country food knowledge holders and cultural coordinators to deliver dietary messaging and nutrition programming about country foods Develop a country food position to advise dietary message development in the ISR Establish communications between regional allied health professionals to share dietary message resources and develop partnerships across the NWT Local health professionals and community health workers (Tuktoyaktuk) Collaborate with other local health professionals and community health workers across the ISR, local leadership, schools, and Elders when developing dietary messages Establish communications between regional allied health professionals to share dietary message resources and develop partnerships Inuvialuit Regional Corporation (IRC) Health and Wellness Division Increase country food harvesting and preparation workshops and programs led by Elders, especially for youth Fund country food harvesting and preparation workshops and programs led by Elders Community of Tuktoyaktuk Tuktoyaktuk country food knowledge holders (Elders, harvesters, fishers, trappers) Increase country food harvesting and preparation workshops and programs led by Elders, especially for youth Collaborate with local health professionals and cooking programs to deliver hands-on workshops on the land Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Gavaravarapu S.M. Nutrition communication—Rhetoric & reality Indian J. Med. Res. 2019 149 333 344 10.4103/ijmr.IJMR_1772_18 31249198 2. Mayfield B.J. Communicating Nutrition: The Authoritative Guide Academy of Nutrition and Dietetics Chicago, IL, USA 2020 8 3. Health Canada Evidence Review for Dietary Guidance: Summary of Results and Implications for Canada’s Food Guide Available online: https://www.canada.ca/en/health-canada/services/publications/food-nutrition/evidence-review-dietary-guidance-summary-results-implications-canada-food-guide.html (accessed on 20 September 2021) 4. Government of Nunavut Nunavut Food Guide Available online: https://livehealthy.gov.nu.ca/en/healthy-eating/nunavut-food-guide (accessed on 20 September 2021) 5. Health Canada Eating Well with Canada’s Food Guide—First Nations, Inuit and Métis Available online: https://www.canada.ca/en/health-canada/services/food-nutrition/reports-publications/eating-well-canada-food-guide-first-nations-inuit-metis.html (accessed on 20 September 2021) 6. Wilson T. Shukla S. Pathways to revitalization of Indigenous food systems J. Agric. Food Syst. Community Dev. 2020 9 201 208 10.5304/jafscd.2020.094.003 7. Settee P. Shukla S. Indigenous Food Systems: Concepts, Cases, and Controversies Canadian Scholars Toronto, ON, Canada 2020 2 92 8. Colles S.L. Maypilama E. Brimblecombe J. Food, food choice and nutrition promotion in a remote Australian Aboriginal community Aust. J. Prim. Health 2014 20 365 372 10.1071/PY14033 25053144 9. Verrall T. Napash L. Leclerc L. Mercure S. Gray-Donald K. Community-based communication strategies to promote infant iron nutrition in northern Canada Int. J. Circumpolar Health 2006 65 65 78 10.3402/ijch.v65i1.17892 16544649 10. Dutta-Bergman M.J. Cultural context, structural determinants, and global health inequities: The role of communication Front. Commun. 2016 1 1 9 10.3389/fcomm.2016.00005 11. Arctic Monitoring and Assessment Programme AMAP Assessment 2015: Human Health in the Arctic Available online: https://www.amap.no/documents/doc/amap-assessment-2015-human-health-in-the-arctic/1346 (accessed on 28 October 2020) 12. Arctic Monitoring and Assessment Programme Human Health in the Arctic 2021—Summary for Policy-Makers Available online: https://www.amap.no/documents/doc/human-health-in-the-arctic-2021.-summary-for-policy-makers/3509 (accessed on 28 October 2020) 13. Boyd A.D. Furgal C.M. Communicating environmental health risks with Indigenous populations: A systematic literature review of current research and recommendations for future studies J. Health Commun. 2019 34 1564 1574 10.1080/10410236.2018.1507658 14. Judd N.L. Drew C.H. Acharya C. Mitchell T.A. Donatuto J.L. Burns G.W. Burbacher T.M. Faustman E.M. Marine Resources for Future Generations. Framing scientific analyses for risk management of environmental hazards by communities: Case studies with seafood safety issues Environ. Health Perspect. 2005 113 1502 1508 10.1289/ehp.7655 16263503 15. Krümmel E.M. Gilman A. An update on risk communication in the Arctic Int. J. Circumpolar Health 2016 75 33822 10.3402/ijch.v75.33822 27974140 16. Inuvialuit Regional Corporation Who We Are Available online: https://irc.inuvialuit.com/ (accessed on 20 June 2020) 17. Inuvialuit Regional Corporation About IFA-101 Available online: http://ifa101.com/about-ifa-101 (accessed on 20 June 2020) 18. Wilson G.N. Rodon T. Alcantara C. Nested Federalism and Inuit Governance in the Canadian Arctic UBC Press Vancouver, BC, Canada 2020 19. Gyapay J. Ostertag S. Wesche S. Laird B. Skinner K. Characterizing the development and dissemination of dietary messaging in the Inuvialuit Settlement Region, Northwest Territories Can Food Stud. 2022 under review 20. Jull J. Giles A. Graham I.D. Community-based participatory research and integrated knowledge translation: Advancing the co-creation of knowledge Implement. Sci. 2017 12 150 10.1186/s13012-017-0696-3 29258551 21. Datta R. Decolonizing both researcher and research and its effectiveness in Indigenous research Res. Ethics 2018 14 1 24 10.1177/1747016117733296 22. Martin D. Two-eyed seeing: A framework for understanding indigenous and non-Indigenous approaches to Indigenous health research Can. J. Nurs. Res. 2012 44 20 42 22894005 23. Datta R. Traditional storytelling: An effective Indigenous research methodology and its implications for environmental research Altern. Int. J. Indig. Peoples 2018 14 35 44 10.1177/1177180117741351 24. Rieger K.L. Gazan S. Bennett M. Buss M. Chudyk A.M. Cook L. Copenace S. Garson C. Hack T.F. Hornan B. Elevating the uses of storytelling approaches within Indigenous health research: A critical and participatory scoping review protocol involving Indigenous people and settlers Syst. Rev. 2020 9 257 10.1186/s13643-020-01503-6 33148328 25. Bird S. Wiles J.L. Okalik L. Kilabuk J. Egeland G.M. Methodological consideration of Storytelling in qualitative research involving Indigenous Peoples Glob. Health Promot. 2009 16 16 26 10.1177/1757975909348111 20028665 26. Smith L. Decolonizing Methodologies: Research and Indigenous Peoples 2nd ed. Zed Books ProQuest Ebook Central London, UK 2012 214 290 27. Kovach M. Indigenous Methodologies: Characteristics, Conversations, and Contexts ProQuest Ebook Central, University of Toronto Press Toronto, ON, Canada 2009 21 175 28. Wilson S. Research Is Ceremony: Indigenous Research Methods Fernwood Publishing Black Point, NS, Canada 2008 7 125 29. First Nations Pedagogy Talking Circles Available online: http://firstnationspedagogy.ca/circletalks.html (accessed on 28 October 2020) 30. Lavallée L.F. Practical application of an Indigenous research framework and two qualitative Indigenous research methods: Sharing circles and Anishnaabe symbol-based reflection Int. J. Qual. Methods 2009 8 21 40 10.1177/160940690900800103 31. Parsons J.A. Key informant Encyclopedia of Survey Research Methods SAGE Publications, Inc. London, UK 2011 10.4135/9781412963947 32. Braun V. Clarke V. Using thematic analysis in psychology Qual. Res. Psychol. 2006 3 77 101 10.1191/1478088706qp063oa 33. Saldaña J. The Coding Manual for Qualitative Researchers 3rd ed. SAGE Publications Ltd. London, UK 2016 1 366 34. Bradley E. Curry L. Devers K. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory Health Serv. Res. 2007 42 1758 1772 10.1111/j.1475-6773.2006.00684.x 17286625 35. Carlson J. Avoiding traps in member checking Qual. 2014 15 1102 1113 10.46743/2160-3715/2010.1332 36. Creswell J.W. Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research 2nd ed. Pearson Upper Saddle River, NJ, USA 2005 1 672 37. Green J. Thorogood N. Qualitative Methods for Health Research 4th ed. SAGE London, UK 2018 1 440 38. Government of the Northwest Territories Fish Consumption Guidance Available online: https://www.hss.gov.nt.ca/en/services/fish-consumption-guidance (accessed on 4 October 2021) 39. Government of the Northwest Territories Nutritional Food Fact Sheet Series Available online: https://www.hss.gov.nt.ca/en/services/nutritional-food-fact-sheet-series (accessed on 4 October 2021) 40. Government of the Northwest Territories Hunter Education Available online: https://www.enr.gov.nt.ca/en/services/hunter-education (accessed on 4 October 2021) 41. Government of the Northwest Territories 2021 NWT Well Child Record Handbook Available online: https://www.hss.gov.nt.ca/professionals/en/2021-well-child-record-handbook (accessed on 4 October 2021) 42. Government of the Northwest Territories Healthy Family Program Collective Kitchen—Recipe Book for Northern Cooks 2013 Available online: https://www.hss.gov.nt.ca/sites/hss/files/resources/northern-cookbook.pdf (accessed on 4 October 2021) 43. Kaufman C. Northwest Territories Health and Social Services Authority Personal communication 2021 44. Colles S. Maypilama E.L. Menzies School of Health Research Food and Health Communication Across Cultures: Considerations for Health Professionals Working with Remote ABORIGINAL Communities Available online: https://www.menzies.edu.au/page/Research/Projects/Nutrition/Food_and_health_communication_across_cultures/ (accessed on 4 October 2021) 45. National Collaborating Centre for Indigenous Health Core Principles for Good Health Living Messages in First Nations, Inuit and Métis Remote and Isolated Northern Communities—Recommendations from the Task Group on Healthy Living Available online: https://www.nccih.ca/634/Core_Principles_for_Good_Healthy_Living_Messages_in_First_Nations,_Inuit_and_M%C3%A9tis_Remote_and_Isolated_Northern_Communities.nccih?id=7 (accessed on 4 October 2021) 46. Skinner K. Neufeld H.T. Murray E. Hajto S. Andrews L. Garrett A. Sharing Indigenous foods through stories and recipes Can. J. Diet Pract. Res. 2020 82 11 15 10.3148/cjdpr-2020-020 32902310 47. First Nations Health Authority Eating Healthy Available online: https://www.fnha.ca/wellness/wellness-for-first-nations/wellness-streams/eating-healthy (accessed on 4 October 2021) 48. Kuhnlein H.V. Food system sustainability for health and well-being of Indigenous Peoples Health Nutr. 2015 18 2415 2424 10.1017/S1368980014002961 25522932 49. Myers H. Furgal C. Long-range transport of information: Are Arctic residents getting the message about contaminants? Arctic 2006 59 47 60 10.14430/arctic363 50. Hotıì Ts’eeda COVID-19 Resources for the NWT Available online: https://nwtspor.ca/supported-projects/covid-19-resources-nwt (accessed on 12 October 2021) 51. Inuit Tapiriit Kanatami COVID-19 Infographics Available online: https://www.itk.ca/covid19-infographics/ (accessed on 12 October 2021) 52. Inuit Tapiriit Kanatami Inuit Nunangat Food Security Strategy Available online: https://www.itk.ca/inuit-nunangat-food-security-strategy/ (accessed on 12 October 2021) 53. Inuvialuit Regional Corporation Brighter Futures Available online: https://irc.inuvialuit.com/program/brighter-futures (accessed on 19 October 2021) 54. Kenny T.-A. Wesche S. Fillion M. MacLean J. Chan H.M. Supporting Inuit food security: A synthesis of initiatives in the Inuvialuit Settlement Region, Northwest Territories Can. Food Stud. 2018 5 73 110 10.15353/cfs-rcea.v5i2.213

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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091141 plants-11-01141 Article Dependence on Nitrogen Availability and Rhizobial Symbiosis of Different Accessions of Trifolium fragiferum, a Crop Wild Relative Legume Species, as Related to Physiological Traits Jēkabsone Astra 1 Andersone-Ozola Una 1 Karlsons Andis 2 Neiceniece Lāsma 1 Romanovs Māris 1 https://orcid.org/0000-0002-5542-886X Ievinsh Gederts 1* Pipan Barbara Academic Editor Meglič Vladimir Academic Editor 1 Department of Plant Physiology, Faculty of Biology, University of Latvia, 1 Jelgavas Str., LV-1004 Rīga, Latvia; astra.jekabsone@lu.lv (A.J.); una.andersone-ozola@lu.lv (U.A.-O.); las.neic8@gmail.com (L.N.); maris.romanovs@lu.lv (M.R.) 2 Institute of Biology, University of Latvia, 4 Ojāra Vācieša Str., LV-1004 Rīga, Latvia; andis.karlsons@lu.lv * Correspondence: gederts.ievins@lu.lv 22 4 2022 5 2022 11 9 114125 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Biological nitrogen fixation by legume-rhizobacterial symbiosis in temperate grasslands is an important source of soil nitrogen. The aim of the present study was to characterize the dependence of different accessions of T. fragiferum, a rare crop wild relative legume species, from their native rhizobia as well as additional nitrogen fertilization in controlled conditions. Asymbiotically cultivated, mineral-fertilized T. fragiferum plants gradually showed signs of nitrogen deficiency, appearing as a decrease in leaf chlorophyll concentration, leaf senescence, and a decrease in growth rate. The addition of nitrogen, and the inoculation with native rhizobia, or both treatments significantly prevented the onset of these symptoms, leading to both increase in plant shoot biomass as well as an increase in tissue concentration of N. The actual degree of each type of response was genotype-specific. Accessions showed a relatively similar degree of dependence on nitrogen (70–95% increase in shoot dry mass) but the increase in shoot dry mass by inoculation with native rhizobia ranged from 27 to 85%. In general, there was no correlation between growth stimulation and an increase in tissue N concentration by the treatments. The addition of N or rhizobial inoculant affected mineral nutrition at the level of both macronutrient and micronutrient concentration in different plant parts. In conclusion, native rhizobial strains associated with geographically isolated accessions of T. fragiferum at the northern range of distribution of the species represent a valuable resource for further studies aimed at the identification of salinity-tolerant N2-fixing bacteria for the needs of sustainable agriculture, as well as in a view of understanding ecosystem functioning at the level of plant-microorganism interactions. biological nitrogen fixation biomass partitioning crop wild relatives legumes nitrogen fertilization photosynthesis-related characteristics rhizobial symbiosis ==== Body pmc1. Introduction Nitrogen is a limiting factor for plant growth in many ecosystems, including coastal dunes [1] and salt marshes [2,3]. In the context of coastal habitats, experimental evidence, based on studies in dune grassland models containing legume species, shows that in addition to plant productivity and nitrogen nutrition, legume-rhizobia interaction also determines plant community structure [4]. In turn, biological nitrogen fixation by legume-rhizobacterial symbiosis in temperate grasslands is an important source of soil nitrogen, benefiting non-leguminous species and increasing soil sustainability [5]. For example, the clover species Trifolium repens is able to fix 100 to 350 kg N ha−1 per year [6]. Due to rising anthropogenic pressure and in the light of global climate changes, research leading to the development of new pasture crops and cultivars having high resilience against unfavorable conditions is of special importance. Crop wild relative (CWR) species represent an invaluable resource for the increase in genetic diversity of crops aiming at the incorporation of resilience-enhancing adaptations [7,8]. It can be proposed that in the case of legume CWRs, both host plant and symbiotic rhizobacterial diversity needs to be assessed at the functional as well as genetic level because this interaction determines nodulation efficiency and N2-fixing ability of a legume-rhizobia symbiosis. However, this important aspect is not usually dissected when analyzing legume CWR resources [9]. Besides, a large practical interest in studies on the legume-rhizobia symbiosis of wild plants native to marginal habitats is related to the need for selecting efficient and durable bacterial strains useful for improving the sustainability of vulnerable agroecosystems [10,11]. Trifolium fragiferum L. is a CWR legume species, which, being relatively rare in northern Europe, is associated with the European protected habitat ‘Baltic coastal meadow’ [12]. T. fragiferum has a number of resilience-related characteristics. Stoloniferous growing habits allow vegetative spread and are associated with the extremely high trampling and cutting tolerance of the species [13]. T. fragiferum accessions have considerable tolerance to soil salinity and alkalinity [14,15] as well as can withstand soil waterlogging and flooding [13,16]. In natural conditions, T. fragiferum can be found also in soils with relatively low plant-available N concentrations (16–21 mg L−1), but the N concentration in plant tissues was at optimum or close to optimum levels, indicating an efficient N2-fixing ability of the rhizobial symbiont [17]. Consequently, wild accessions of the species at the northern edge of the distribution range together with their symbiotic bacteria represent a valuable resource for further exploration of the economically valuable characteristics in the context of sustainable agriculture. In the last decades, emphasis has been given to the characterization of the genetic and functional diversity of a bacterial counterpart of wild legume-rhizobia symbiosis [18,19,20], with significant efforts also in the field of ecosystem functioning [21]. However, plant-related functional aspects of rhizobial symbiosis and symbiotic nitrogen fixation in wild legume species have been only seldom assessed so far. Recently, we showed that rhizobial symbiosis affects adaptation-related physiological processes of coastal dune plant species Anthyllis maritima on the background of sand burial and salinity [22]. In addition, rhizobial symbiosis affected the interaction between individuals of T. fragiferum and T. repens, cocultivated in different substrate salinities, and there was a significant interaction between these factors with respect to plant growth and morphology, including the type of rhizobial bacteria used for inoculation [23]. Photosynthesis-related parameters, such as leaf chlorophyll concentration and chlorophyll-a fluorescence-derived indices of the photochemistry of photosynthesis, have been frequently used to characterize the physiological performance of plants in heterogeneous or unfavorable environmental conditions [24,25,26], including nutrient deficiency [27]. In Anthyllis maritima, photosynthesis-related parameters were good indicators of the presence of nodules on plants, as inoculation with native rhizobia led to a significant increase in both leaf chlorophyll concentration as well as fluorescence parameters, such as the Performance Index [22]. In T. fragiferum, growth inhibition of asymbiotically cultivated plants was accompanied by a significant decrease in leaf chlorophyll concentration as well as lowered photochemical activity of photosystem II [23]. Legumes can obtain necessary N, either in an inorganic form from soil, or as organic N through symbiotic nitrogen fixation. An actual contribution of each type of N acquisition seems to be both genotype, as well as environment-dependent characteristics [28]. Many studies can be found in the literature comparing the efficiency of rhizobial inoculation vs. nitrogen fertilization on growth and physiological indices of legume crop species [29,30,31,32]. However, there is no comparable information available on the characteristics of functional interactions between different combinations of plant accessions and their native rhizobia in the case of T. fragiferum. As a first step to fill this knowledge gap, the aim of the present study was to characterize the dependence of different accessions of T. fragiferum from their native rhizobia as well as their response to additional nitrogen fertilization. Changes in growth, biomass partitioning, photosynthesis-related traits and mineral nutrition were used for functional characterization of the outcome of rhizobial symbiosis. 2. Materials and Methods 2.1. Plants and Microorganisms Seeds of T. fragiferum from eight geographically isolated Latvian micropopulations were used for plant propagation (Table 1). Rhizobia were isolated from nodules collected from roots of two naturally grown plants at the respective micropopulation as described previously [23]. Bacteria were isolated from root nodules of all wild accessions of T. fragiferum used in the present study. Seeds of cv. ‘Palestine’ pre-treated with a commercial rhizobial inoculant was obtained from Sheffield’s Seeds Company (Locke, NY, USA) and used for comparison. 2.2. Plant Propagation, Cultivation and Treatments All seed material except part of the seeds of cv. ‘Palestine’ was surface sterilized using a half-diluted commercial bleach (ACE, Procter & Gamble, Warszawa, Poland) for 10 min, followed by three rinses with deionized water (10 min each). Seeds were imbibed in deionized water for 48 h and scarified with a scalpel. Sterilized seeds and part of the seeds of cv. ‘Palestine’ not sterilized were placed in 1 L plastic tissue culture containers on autoclaved garden soil (Biolan, Eura, Finland), closed with lids and cultivated for two weeks in a growth cabinet at 15/20 °C (night/day), photoperiod of 16 h (100 μmol m−2 s−1 of photosynthetically active radiation). Further transplantation and cultivation in an automated greenhouse were performed as described previously [13]. Fully acclimatized four week-old plants were randomly divided into four treatments, five plants per treatment as biological replicates. Asymbiotically cultivated plants were used as controls (C) or were treated with N fertilizer (N) in a form of NH4NO3 (0.15 g N per container) every even week. Plants inoculated with respective rhizobial suspension were used as symbiotic control (R) or were treated with N fertilizer (RN) in the form of NH4NO3 (0.15 g N per container) every even week. Each container was inoculated with 6 mL of bacterial suspension (about 109 cells per mL) applying 1 mL of the suspension in six points evenly over the surface of the substrate. Plants from each accession were inoculated with native nodule isolates from wild plants from the same accession. Plants grown from sterilized seeds of cv. ‘Palestine’ were used as an asymbiotic control and for the asymbiotic N-fertilizer treatment, but those grown from non-sterilized seeds were used for rhizobia-inoculated and rhizobia-inoculated + N-fertilized treatments. Every odd week all plants were fertilized with Yara Tera Kristalon Red and Yara Tera Calcinit fertilizers (Yara International, Oslo, Norway). All plants were cultivated in a substrate with 38 mg L−1 plant-available N and received additional N from Yara Tera fertilizers (in total, 82.5 mg L−1). An individual watering system of containers was used to decrease possible contamination with rhizobial bacteria, with each container having a plastic plate under it for accumulation of excessive water. Additionally, inoculated plants were located on a separate greenhouse table, restricting the chance of physical contact of stolons between individual plants. 2.3. Measurement Measurement of Photosynthesis-Related Parameters Analysis of photosynthesis-related parameters was started one week after rhizobial inoculation (week 1) and was performed weekly for the next five weeks. For each individual plant, three fully grown photosynthetically active leaves were selected for analysis. Chlorophyll concentration in plant leaves was measured by a chlorophyll meter CCM-300 (Opti-Sciences, Hudson, NH, USA). Results on chlorophyll concentration in week 2 were lost due to technical problems. Chlorophyll a fluorescence was measured in leaves dark-adapted for at least 20 min by Handy PEA fluorometer (Hansatech Instruments, King’s Lynn, UK). For the characterization of photochemical activity, the chlorophyll a fluorescence parameter Performance Index (total) was used. Performance Index is a complex indicator of photochemical efficiency combining three function-related (trapping of an absorbed exciton, electron transport between the photosystems, reduction of end-electron acceptors) and structure-related (antenna chlorophyll per reaction center chlorophyll) parameters [33]. 2.4. Termination of the Experiment and Measurements After inoculation with rhizobia, plants were cultivated for seven weeks. Plants were separated into different parts (roots, stolons, leaf petioles, leaf blades, flower stalks, inflorescences). Plant roots were washed individually and the relative degree of nodule presence was evaluated according to the four point scale (0, no nodules; 1, a few nodules (1–5) at only one point; 2, small groups of nodules (<10) at several points on roots; 3, a large number of nodules (>10) throughout the root length). One individual from the asymbiotic control group from each of TF1, TF3, TF4 and TF8 accessions had high presence of nodules and was excluded from further analysis (Table 2). Stolons, leaves and inflorescences were counted, and the length of individual stolons was measured. Plant material was weighed separately before and after drying in an oven at 60 °C for 72 h. Mineral element analysis in dry-ashed plant material was performed as described previously [17]. After mineralization of the plant samples and dissolving of the mineral fraction in 3% HCl, chemical analyses were conducted using the following methods: the levels of K, Ca, Mg, Fe, Cu, Zn and Mn were estimated by a microwave plasma atomic emission spectrometer Agilent 4200. Levels of P were analyzed by colorimetry with ammonium molybdate in an acid-reduced medium using a spectrophotometer Jenway 6300. All analyses were performed in triplicate, using representative tissue samples from individual biological replicates. 2.5. Data Analysis Results were analyzed by KaleidaGraph (v. 5.0, Synergy Software, Reading, PA, USA). Statistical significance of differences was evaluated by one-way ANOVA using posthoc analysis with a minimum significant difference. Principal component analysis, heat map generation and cluster analysis were performed by a freely available web program ClustVis (http://biit.cs.ut.ee/clustvis/; accessed on 19 March 2022) [34]. For principal component analysis, prediction ellipses were such that with a probability of 0.95, a new observation from the same group will fall inside the ellipse. Unit variance scaling was applied to rows; singular value decomposition with imputation was used to calculate principal components. Hierarchical clusters were generated by the average linkage method with correlation distance. 3. Results Root inspection after the experiment revealed that despite precautions taken to sterilize seeds and to prevent bacterial contamination during plant cultivation, several individual asymbiotically grown plants in all T. fragiferum accessions except TF6 had nodules on their roots (Table 2). One plant for each of the accessions TF1, TF3, TF45 and TF8 had a large number of nodules throughout the root length. Therefore, these individual plants were excluded from further analysis. No nodules were evident on roots of asymbiotically grown plants receiving N fertilizer except one individual of TF8. All rhizobia-inoculated plants had a relatively high presence of nodules except for one individual of TF1. However, the number of nodules was highly variable for rhizobia-inoculated plants treated with N fertilizer. Asymbiotically cultivated, mineral-fertilized T. fragiferum plants gradually showed signs of nitrogen deficiency, appearing as leaf yellowing, leaf senescence, and a decrease in growth rate. This effect was partially genotype-dependent. The addition of nitrogen, inoculation with native rhizobia, or both treatments significantly prevented the onset of these symptoms. Treatment with additional N fertilizer significantly increased total shoot biomass for all T. fragiferum accessions (Table 3). Rhizobial inoculation also had a similar effect for all accessions except TF8. The relative stimulative effect of added N on shoot dry matter accumulation was comparatively similar and ranged from 70% (TF5) to 95% (TF2b) (Figure 1A). However, the stimulative effect of rhizobial inoculation on shoot biomass was rather variable, ranging from 27–35% (TF1, TF5, TF8) to 85% (TF6). Response in biomass changes to rhizobial inoculation of T. fragiferum plants receiving N fertilizer was relatively negligible and was not significant for all accessions except TF5 (Table 3), which showed an 18% biomass increase (Figure 1B). Response to N fertilizer of plants inoculated with rhizobia was more variable, ranging from 5 to 57% (Figure 1B), and this effect was significant for TF1, TF2b, TF3, TF4, TF5 and TF8 (Table 3). Root growth of T. fragiferum plants was relatively less affected by treatments in comparison to shoot growth. Nitrogen treatment resulted in a significant increase of root biomass only for TF2 and TF2b (Table 3). However, rhizobial inoculation or combined treatment did not result in a significant increase in root biomass. Besides the increase in shoot biomass, another characteristic response of T. fragiferum plants to N fertilizer and rhizobial inoculation were changes in biomass partitioning (Figure 2). There were significant differences with respect to the inflorescence number between the accessions already for control plants, ranging from only three in TF7 and TF8 to 26 in TF4 (Table 4). The number of inflorescences significantly increased for all accessions by N fertilizer treatment except TF8, which showed extreme variability between the individual plants. The same effect was evident also for rhizobial inoculation, but it was not statistically significant for TF3 and TF5. For several accessions (TF5, TF6) rhizobial inoculation + N resulted in a higher number of inflorescences in comparison to N fertilization alone. Accordingly, there was an increase in the proportion of biomass in flower stalks and inflorescences by the treatments, which was less pronounced for TF4, which already has high biomass of generative organs in control conditions, and for TF8 with the smallest biomass in generative organs (Figure 2). An increase in partitioning in generative parts was associated with a decrease in biomass proportion in all vegetative parts. However, the tendency to increase the number of leaves was a characteristic response to the treatments, but this effect was not statistically significant for TF2b, TF6 and TF8, due to high variability between individual plants (Table 4). The number of stolons and total stolon length also increased, and the effect was especially pronounced for the plants receiving N fertilizer (Table 5). A decrease in leaf chlorophyll concentration with time was a characteristic feature of asymbiotic T. fragiferum plants of all accessions (Figure 3). In general, performed treatments prevented this decrease, but the effect varied between accessions and particular treatments. Thus, rhizobial inoculation alone did not prevent a decrease in chlorophyll concentration for TF4 (Figure 3E), TF5 (Figure 3F), and TF8 (Figure 3I). Additionally, for TF2b, a decrease in chlorophyll concentration was more pronounced in rhizobia-inoculated plants in comparison to N-treated plants (Figure 3C). The chlorophyll-a fluorescence parameter Performance Index showed lower resolution ability for different treatments in comparison to that for leaf chlorophyll concentration (Figure 4). In general, the Performance Index tended to be higher for N-fertilized plants, especially, at an early stage of cultivation (week 2), but these differences diminished at the later stages. Only TF2 and TF3 rhizobia-inoculated plants had higher Performance Index values on week 5 in comparison to asymbiotic plants, but N-fertilized plants of several accessions (TF1, TF2, TF3, TF4, TF8) had higher Performance Index values in comparison to control plants at that time. Multivariate analysis was performed to find similarities between accessions in terms of morphological and physiological responses to rhizobial inoculation and N fertilization. It is evident from the results of the principal component analysis that similar responses were characteristic for accessions TF2b, TF3 and TF7; as well as for accessions TF1, TF4, TF5 and TF6 (Figure 5). TF2 had an intermediate position between the two groups, but TF8 showed a unique position. Hierarchical cluster analysis confirmed the similarity of responses between TF2b, TF3 and TF7; as well as between TF1 and TF4; and TF5 and TF8 (Figure 6). It is evident that the tightest association between TF2b and TF7 was related to the close similarity of control plants and, to a lesser extent, N-fertilized and rhizobia-treated plants (Figure 7). The further similarity of TF3 to the previous group was at the level of both control plants and rhizobia-inoculated plants. Association between TF1 and TF4 was justified by a close similarity of rhizobia-inoculated N-treated plants as well as similarity of control and N-treated plants. The connection between TF5 and TF8 predominantly was at the level of both rhizobia-inoculated and control plants. Nitrogen concentration in different parts of T. fragiferum plants grown in asymbiotic conditions was relatively low, and some accession-specific differences were evident (Figure 8). Thus, TF6 had the lowest N concentration among all accessions both in leaf blades and in leaf petioles, while TF1 had the highest concentration in all parts. In general, all treatment types led to an increase in tissue concentration of N, but to various degrees for different accessions (Table 6). The increase was not statistically significant for leaf blades and petioles of TF5 as well as for several other accessions for some treatments. While there was a tendency for increased N concentration in N-treated plants of TF8, the effect was not statistically significant due to extremely high individual variability with respect to this parameter. Moreover, N concentration in symbiotic TF8 plants tended to be lower than in control plants. When the response of average N concentration in plants of different accessions to N fertilizer and rhizobial inoculation was compared, it appeared that the response to N treatment ranged from 48% in TF6 to 86% in TF2b (Figure 9A). The response to rhizobial inoculation ranged from −15% in TF8 to 83% in TF3. Inoculation of N-fertilized plants was relatively ineffective in increasing plant N concentration, with a 28% increase only in TF4 (Figure 9B). Besides, N-fertilization of rhizobia-inoculated plants led to a 38% and 55% increase in average N concentration in TF4 and TF8, respectively. N concentration in leaf blades in general had a moderately tight correlation with leaf chlorophyll concentration (Figure 10A). However, when results were grouped according to different treatments, it appeared that only a low positive correlation was evident for the control group (R = 0.308) and rhizobia-inoculated group (R = 0.387), but correlation for the N-fertilized group, as well as for rhizobia-inoculated N-fertilized group was negative (R = −0.377 and R = −0.173, respectively) (Figure 10B). Mineral nutrient concentrations for different parts of control plants are presented in Table S1. Both genotype- and organ-specific changes in mineral nutrient concentration were evident in T. fragiferum plants receiving additional N fertilization or inoculated with rhizobia, or by both treatments (Figure 11). Looking at the changes in particular elements, it was seen that some of them were characterized by a predominant decrease in concentration (as for macronutrients P and K) or by a predominant increase in concentration, although to a lesser extent (as for macronutrients Ca and Mg). The concentration of micronutrients Zn and Fe showed a predominant decrease by treatments in all accessions except one (TF1 in the case of Zn and TF3 in the case of Cu responded by increased concentration). Changes for micronutrient Fe were relatively less pronounced, and mostly an increase in concentration was evident. For micronutrient Mn, the effect was rather controversial. Organ specificity of changes was extremely pronounced for P concentration, as no decrease occurred in leaf blades, and, partially, for K concentration. Similarly, Zn concentration did not decrease in roots. There were also some treatment-specific changes in mineral nutrient concentration. Thus, in several accessions, decreases in P and K were less intense in some parts of rhizobia-inoculated plants in comparison to these receiving N fertilizer, or combined treatment. Genotype-specific changes were evident as differences in intensity of changes in concentration of particular mineral element or even as the nature of the change, as for TF1 in the case of Zn and TF3 in the case of Cu, showing an increasing trend of these nutrients in opposite to the rest of genotypes. Multivariate analysis revealed that diversity in mineral nutrient concentration among different accessions increased with performed treatments, resulting in a rather unique mineral element response profile for each plant genotype-rhizobia combination (data not shown). 4. Discussion 4.1. Dependence of Growth and N supply on Nitrogen and Rhizobia In contrast to the majority of plant species, relying on uptake of inorganic soil N, legumes can obtain necessary N, either in an inorganic form, or as organic N through symbiotic nitrogen fixation. In general, the higher amount of N supplied by rhizobial symbiosis affects resource partitioning, resulting in the stimulated growth of symbiotic plants [35]. For T. fragiferum, plant nitrogen addition and symbiotic status significantly, and in a genotype-dependent manner, affected biomass partitioning. Most importantly, generative development was highly stimulated, especially, by combination treatment for TF1, TF2b, TF5 and TF6, but this characteristic was not affected in TF8 (Figure 2). For some genotypes, rhizobia inoculation was less effective to increase plant biomass and/or tissue N concentration in comparison to N fertilizer treatment, suggesting the existence of differences in the N2-fixing efficiency of the native rhizobia. N2-fixation efficiency of the established symbiosis can be related to strain genotype [36]. Strain selection (specificity of nodulation) in field conditions can occur at multiple phases of interaction and could be related to infection efficiency at the level of bacterial recognition and nodule development (specificity of nodulation) due to differences in rhizobial competitiveness [37,38,39]. It is important to note, that the level of symbiotic compatibility between clover genotypes and different strains of rhizobia depend on the involvement of multiple genes in both symbiotic partners [40]. In the present study, the two types of treatment, rhizobial inoculation and inorganic nitrogen fertilization led to both increase in plant shoot biomass as well as an increase in tissue concentration of N. The actual degree of each type of response was genotype-specific, but in general, there was no correlation between growth stimulation and increase in tissue N concentration by the treatments. Only TF2 showed a high increase of both shoot biomass and N concentration by rhizobial inoculation. Accessions TF6 and TF7, both with a characteristic low increase of rhizobia-dependent N accumulation (Figure 9A), had a high increase in shoot biomass as a result of rhizobial inoculation (Figure 1A). It seems that these differences in biomass increase vs. N concentration between various accessions of T. fragiferum are related to variation in nodule efficiency leading to differences in N metabolism. It is logical to assume that plants from accessions, which growth was most stimulated by rhizobia (TF2, TF6, TF7), had higher demand for N, leading also to a higher total amount of N in plant tissues. It seems that N supply from nodules in TF6 and TF7 was relatively less intense than in TF2, resulting in comparatively lower tissue N concentration. In T. repens, additional N fertilization of symbiotic plants resulted in increased biomass accumulation, but total N concentration did not change [41]. In contrast, nodulated Cicer arietinum plants that had the largest increase in shoot N, showed an increase in root growth [42]. As T. fragiferum plants from all these accessions showed better physiological status due to rhizobial inoculation, as evidenced by leaf chlorophyll concentration, it seems that TF2 plants accumulated surplus N in a form of storage compounds, such as nitrate and ammonia in vacuoles or proteins in chloroplasts [43]. N remobilization from storage pools is an important feature for perennial plant survival and resilience [44]. Due to the high proportion of biomass allocated in stolons (Figure 2) and the high potential of rhizobia-dependent N accumulation (Table 6), stolons seem to be a major storage site for N in T. fragiferum plants. Were there any morphological and physiological differences evident depending on the type of N supply, biological N2 fixation vs. inorganic N? Some responses indeed showed treatment-specific characteristics, such as those in total shoot biomass (Figure 1), leaf chlorophyll concentration (Figure 3), and biomass partitioning (Figure 2), of mineral nutrient concentration (Figure 11). From a quantitative point of view, at least for some T. fragiferum genotypes, rhizobial symbiosis appeared to be less efficient in comparison to N treatment. In a similar study, rhizobia-inoculated plants of Trifolium pratense produced the same biomass as plants receiving additional N fertilizer in a form of ammonium nitrate [45]. It is still not entirely clear what are additional physiological effects of active rhizobial symbiosis on host plants besides N acquisition, but it is established that, at the genetic level, genes responsible for the control of root nodulation intensity, also are involved in the control of root architecture in response to nitrogen [46]. It is well-known that a high N supply reduces root nodule formation and/or nitrogen fixation efficiency through the reduction of nitrogenase activity in legumes [11,41,47]. Negative effects of nitrogen have been observed in several stages of symbiosis [48]. In field conditions, additional N fertilizer to dairy pastures had negative effects on the morphology of T. repens plants and significantly decreased N2-fixation activity [49]. In addition, even symbiotic legume plants favor uptake of mineral N from the soil, as it is an energetically less demanding process [50]. It has been suggested that the lower biomass of N2-fixing plants as compared to N-fertilized plants is attributed to larger respiratory costs in comparison to nitrate assimilation [41]. In contrast, the growth and N uptake rate of T. repens cultivars were independent of the availability of mineral N, except at very low N availability levels, with a < 10% biomass reduction [51]. 4.2. Physiological Changes Leaf chlorophyll content has been already used for the prediction of nodulation efficiency in soybean [52]. It was shown previously that both leaf chlorophyll concentration, as well as chlorophyll-a fluorescence parameter Performance Index, were reliable physiological indicators of rhizobial inoculation in T. fragiferum, T. repens [23] and Anthyllis maritima [22]. In the present study, chlorophyll concentration seemed to be an especially good indicator of physiological changes in T. fragiferum plants under the effect of rhizobial inoculation and N fertilizer (Figure 3) in comparison to the Performance Index (Figure 4). However, T. fragiferum accessions TF1, TF5 and TF8 showed the least increase in shoot biomass by rhizobial inoculation (Figure 1A). Both TF5 and TF8 indeed did not have differences in leaf chlorophyll concentration between asymbiotic and rhizobia-inoculated plants (Figure 3F,I), but such differences were seen for TF1 (Figure 3A). Moreover, TF4 responded to rhizobial inoculation by a 50% increase in biomass (Figure 1A) but did not show differences in chlorophyll concentration between control and inoculated plants (Figure 3E). It might be suggested that changes in leaf chlorophyll concentration do not reflect the degree of growth stimulation but rather changes in leaf N concentration, as has been proposed for many plant species [53,54,55], including legumes [56]. However, the degree of correlation between N and chlorophyll concentration was only moderate (Figure 10), and several accessions with only a low increase in tissue N concentration by rhizobial inoculation, as TF6 and TF7 (Figure 9A), showed significant differences in leaf chlorophyll concentration between control and rhizobia-inoculated plants (Figure 3G,H). It appears that chlorophyll concentration can be used to predict N concentration only in the case of single genotypes or for groups of little diverse genotypes, as has been proposed earlier [57]. It is a widely accepted opinion that inoculation with efficient rhizobia, in general, increases the uptake of other mineral nutrients besides N in legume species, as indicated by a rise in the total amount of a particular nutrient on the plant basis [58]. In general, it reflects an increase in demand for mineral elements under conditions of growth intensification. However, when the nutrient concentration in plant tissues is considered, rhizobial inoculation may cause different changes. It needs to be emphasized that apart from the physiological effects of symbiosis on nutrient uptake, rhizobia can affect nutrient availability to plants in the rhizosphere through P and Fe solubilization by acidification as well as siderophore release for Fe3+ absorption [35]. In the leaves of Trifolium pratense, the concentration of Mg, Fe, Mn, and Cu increased, but that of P decreased [59]. In the leaves of Vigna unguiculata, the concentration of all macro and micronutrients increased, but the degree of increase was bacterial strain-dependent [60]. In the leaves of Vicia faba, the concentration of Mg, P, K, Ca, Zn increased; and in leaves of Glycine max, the concentration of Mg, K, Ca, Fe, Cu, Zn increased, but that of Mn decreased [61]. The decrease in macronutrient P and K concentration in T. fragiferum plants noted in the present study was largely organ-specific, as for a majority of accessions, the concentration of these elements in leaf blades remained unaffected by rhizobial inoculation and N treatment (Figure 11). Consequently, the level of these two essential nutrients was tightly regulated and redistributed to photosynthetic tissues, and leaf blades, but their decrease in other plant parts reflected the dilution of these nutrients due to an increase in total biomass. Interestingly, these effects were also treatment-specific, as symbiotic plants without additional N fertilization showed a less intense decrease in P and K concentration, at least, for several accessions (Figure 11). Variation in mineral nutrient concentrations in tissues of T. fragiferum was highly increased by rhizobia inoculation and N treatment. In the cultivated legumes Vicia faba and Glycine max, inoculation with a commercial preparation of rhizobia resulted in significant changes in the concentration of several mineral elements in plant leaves, but the observed changes were usually only up to 20% [61]. In contrast, in the present study, the increase in the concentration of several nutrients exceeded 200%, and the decrease for several nutrients was more than 50% (Figure 11). These differences could be related to the fact that wild legume species, like T. fragiferum, could be more dependent on rhizobial symbiosis in comparison to legume crop species. Expansion of the mineralome in T. fragiferum plants was observed also as a result of increasing salinity, leading to the establishment of a genotype-specific mineral element response trend within a plant, and it was suggested to reflect homeostasis maintenance-related adaptive response [15]. 4.3. Ecological Implications Environmental factors are significant modifiers of legume-rhizobia interactions. Thus, both light intensity and level of mineral nutrient availability are important for the regulation of biomass accumulation in symbiotic Glycine max plants [62]. When the light was a limiting factor, rhizobial symbiosis did not affect above-ground biomass and even decreased root biomass. In addition, rhizobia increased plant biomass only in low nutrient conditions. However, in this type of study, the total level of mineral nutrients was manipulated instead of adding surplus nitrogen on the background of optimum (or low) mineral availability level. The critical importance of light in the modulation of rhizobial symbiosis has been associated with the fact that light-dependent photosynthesis-driven carbon acquisition represents a resource invested in nodule development further leading to a higher N supply from symbiosis [28]. It is generally believed that the growth of legumes in saline conditions is more sensitive than rhizobial growth, but usually, nodulation, as well as N2-fixation activity, is reduced at near 0.3% salinity [63]. It is possible that increased salinity also indirectly negatively affects symbiotic nitrogen fixation, associated with decreased transport rate of photosynthates from the host plant to nodules as a result of inhibition of photosynthesis and/or growth by salinity. However, usually a negative response of photosynthesis to salinity is less pronounced than that of nitrogen fixation [64]. In natural conditions under high salinity, which is characteristic also for T. fragiferum habitats in Northern Europe, effective salt-tolerant nodules are expected to be found, reflecting the role of rhizobial symbiosis in adaptation to particular environmental conditions [65]. Effective salt-tolerant bacterial strains isolated from T. fragiferum need to be further explored for their potential to improve agricultural sustainability in saline soils. It has been already shown that the presence of rhizobial symbiosis modulates the interaction between T. fragiferum and T. repens on the background of increased soil salinity [23]. Moreover, in natural conditions, legume plants are involved in tripartite interaction with both rhizobial bacteria, as well as arbuscular mycorrhizal fungi, with mycorrhizal symbiosis having strong effects on nodulation [66]. It seems to be important that the degree of mycorrhizal symbiosis in T. fagiferum plants is affected by changes in soil salinity [67]. Biomass allocation is a characteristic plastic response of both stoloniferous and rhizomatous clonal plants to changing resource availability [68]. For stoloniferous plants, an increase in nutrient availability usually results in increased clonal growth without a decrease in sexual reproduction, which is in striking contrast with the results of the present study, showing that allocation to generative structures is a typical response to increased N availability. However, genotype-dependent variation in this trait was evident, even among accessions with high growth stimulation by N fertilization and rhizobial inoculation, as accession TF6 had the highest contribution of generative organs in increasing total biomass by N treatment + rhizobia inoculation (31.5%), but TF2 reached only 8.0% (Figure 2). 4.4. Limitations of the System and Future Perspectives In this type of experiment, it is important that control plants do not develop rhizobial symbiosis for as long as possible. How efficient was the exclusion of rhizobial symbiosis in control, “asymbiotic” plants? For all accessions except TF6, at least one individual of control plants had symbiotic nodules on roots, but there were four plants of cv. ‘Palestine’ (TF8) having small groups of nodules at several points or even a large number of nodules throughout the root length (Table 2). It is most likely that the sterilization procedure used was not efficient enough to get rid of all bacterial cells from the seed surface, as this seed material was preinoculated. However, these bacteria seemed to be inefficient in N2 fixing, as evidenced by decreasing trend of leaf chlorophyll concentration in both control and inoculated plants of TF8 (Figure 3I), as well as a lack of significant effect of rhizobia on shoot biomass (Table 3). For other accessions, the presence of nodules on roots of non-inoculated plants most likely resulted from accidental bacterial contamination at the late stages of cultivation and most likely had little effect on plant nitrogen supply. Usually, plant genotype dependence on symbiotic performance is evaluated for plants grown in an N-free medium, allowing to estimate of the amount of fixed N directly from N analysis in shoots [40]. In the present study, for practical reasons, control plants received a near-optimal level of full mineral fertilizer, and it was revealed that the addition of surplus nitrogen could completely replace rhizobial inoculation. On the other hand, strain genotype effects cannot be excluded. Additional studies aimed at revealing of genetic and functional diversity of rhizobial symbionts are necessary in order to fully understand differences found in different T. fragiferum accessions with respect to their native bacterial symbionts, as one of the most important factors shaping their characteristic growth responses in highly heterogeneous conditions. The extremely important ecophysiological aspect of the rhizobial symbiosis of T. fragiferum is related to interspecies competition in saline habitats, as shown by a previous study [23]. One of the prominent features of wild legume species is the ability to establish a symbiosis with bacterial strains belonging to different taxonomic groups [18]. However, it is usually suggested that clover species have developed a symbiosis with highly specific strains of rhizobia. Thus, a strain isolated from Trifolium repens were able to induce root nodule formation on T. repens, but not on Lotus corniculatus or Ononis repens [4]. In contrast, several strains of Rhizobium leguminosarum, Bradyrhizobium japonicum and Mesorhizobium sp. have been isolated from root nodules of T. fragiferum growing in subtropical zones of China [69] pointing to the existence of a large diversity of symbiotic rhizobia associated with the species. Similarly, nodules of Trifolium pratense plants growing in a close vicinity contained Rhizobium isolates with high genetic diversity (eight genetically distinct groups) and metabolic variability with respect to carbon and energy sources [70]. As rhizobia were isolated from root nodules of a limited number of T. fragiferum plants per accession in the present study, the obtained results on differences in the degree of symbiotic dependence may not fully reflect the efficacy of symbiotic interactions in the natural population. Particular rhizobial strains could differ both in their competitiveness as well as N2-fixing efficiency. Competition for nodule colonization can be tough, with metabolically more versatile strains (being able to use a wider range of energy-providing substrates) usually being more competitive [71]. However, the metabolic versatility of a particular bacterial strain does not at the same time provide the efficiency of symbiosis [70]. For Trifolium species, bacterial strains with effective N2 fixation have been shown to be also more competitive for nodule occupancy [72]. The same relationship was found also for other legume species [73]. Additionally, the effects of active symbiosis on plant responses to abiotic stress can be dependent on rhizobia genotype [23]. Consequently, further studies need to address the problem of taxonomic and biological relatedness of native bacterial strains found in geographically isolated T. fragiferum accessions. 5. Conclusions All tested combinations of crop wild relative T. fragiferum accessions vs. their native rhizobial types were relatively specific with respect to plant functional responses to N availability and inoculation. The dependence of biomass accumulation on N fertilization was similarly high in all accessions (70 to 95%), but the dependence of inoculation with native rhizobia was more variable (27 to 85%). Based on the similarity of morphophysiological responses, three groups of plant/rhizobia combinations were evident, but most of the relationships were at the level of control plant and N-treated plant characteristics. Native rhizobial strains associated with geographically isolated accessions of T. fragiferum at the northern range of distribution of the species represent a valuable resource for further studies aimed at the identification of stress-tolerant symbiotic N2-fixing bacteria for the needs of sustainable agriculture as well as in a view of understanding of ecosystem functioning at the level of plant-microorganism interactions. Acknowledgments Participation of Līva Purmale (University of Latvia) in part of the study is sincerely acknowledged. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants11091141/s1, Table S1: Mineral nutrient concentration in different parts of control Trifolium fragiferum plants from different accessions. Click here for additional data file. Author Contributions U.A.-O. and G.I. proposed the research. U.A.-O., A.J., A.K., L.N., M.R. and G.I. performed the experiments and analyzed the data. G.I. drafted the manuscript. U.A.-O. and A.J. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Funding The study was supported by the Latvian Science Council project lzp-2020/2-0349 “Molecular, physiological and ecological evaluation of Latvian genetic resources of valuable wild legume species, Trifolium fragiferum, in a context of sustainable agriculture“. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement All data reported here is available from the authors upon request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Relative effect of different treatments on shoot dry matter in Trifolium fragiferum plants of different accessions. (A), effect of separate treatments of N and R; (B), effect of N treatment in addition to R and R treatment in addition to N. N, nitrogen; R, rhizobia. Figure 2 Biomass partitioning in Trifolium fragiferum plants of different accessions in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) treatments. Figure 3 Time course of leaf chlorophyll concentration in Trifolium fragiferum plants of different accessions in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) treatments. (A) TF1; (B) TF2; (C) TF2b; (D) TF3; (E) TF4; (F) TF5; (G) TF6; (H) TF7; (I) TF8. Each data point represents mean from 15 independent measurements from five plants ± SE. Different letters of respective color for week 5 results indicate statistically significant differences. Results on week 2 were lost due to technical problems. Figure 4 Time course of chlorophyll-a fluorescence parameter Performance Index in Trifolium fragiferum plants of different accessions in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) treatments. (A) TF1; (B) TF2; (C) TF2b; (D) TF3; (E) TF4; (F) TF5; (G) TF6; (H) TF7; (I) TF8. Each data point represents mean from 15 independent measurements from five plants ± SE. Different letters of respective color for week 5 results indicate statistically significant differences. Figure 5 Principal component analysis on the effect of different treatments on morphology, biomass partitioning and physiological indices (chlorophyll concentration and Performance Index on week 5) of Trifolium fragiferum plants of different accessions. C, control; N, N-fertilized; R, rhizobia-inoculated; RN, rhizobia inoculated + N-fertilized plants. Prediction ellipses are such that with a probability of 0.95, a new observation from the same group will fall inside the ellipse. Unit variance scaling was applied to rows; singular value decomposition with imputation was used to calculate principal components. X and Y axes show principal component 1 and principal component 2 which explain 51.7% and 20.7% of the total variance, respectively. Figure 6 Generated heat map and cluster analysis on effect of different treatments on morphology, biomass partitioning and physiological indices (chlorophyll concentration and Performance Index on week 5) of Trifolium fragiferum plants of different accessions. Hierarchical clusters were generated by average linkage method with correlation distance. Color scale shows relative intensity of normalized parameter values. Chl, chlorophyll; F, inflorescences; FS, flower stalks; L, length; LB, leaf blades; LP, leaf petioles; n, number; PI, Performance Index; R, roots; ST, stolons. Figure 7 Comparison of results of cluster analysis on morphology, biomass partitioning and physiological indices (chlorophyll concentration and Performance Index on week 5) computed using data from all treatments (C + N + R + RN, the same data set as in Figure 6) or only data from asymbiotic control plants (C), asymbiotic N-fertilized plants (N), rhizobia-inoculated plants (R) or rhizobia-inoculated N-fertilized plants (RN). Hierarchical clusters were generated by average linkage method with correlation distance. Figure 8 N concentration in various parts of control Trifolium fragiferum plants from different accessions. Different letters for a particular plant part indicate statistically significant differences for each plant part. Figure 9 The relative effects of different treatments on average N concentration in Trifolium fragiferum plants of different accessions. (A) effect of separate treatments of N and R; (B) effect of N treatment in addition to R and R treatment in addition to N. N, nitrogen; R, rhizobia. Figure 10 Correlation between leaf blade nitrogen concentration and leaf chlorophyll concentration at day 5. Results are means from three measurements for N analysis and 15 measurements for chlorophyll-analysis. (A), unsorted data; (B), data sorted by treatments and accessions. Figure 11 Relative effect of N treatment of asymbiotic plants (N), rhizobial inoculation (R), and N treatment of rhizobia-inoculated plants (RN) on mineral element concentrations in leaf blades (LB), leaf petioles (LP), stolons (ST) and roots (R) of Trifolium fragiferum plants of different accessions in comparison to asymbiotic control plants. Only statistically significant effects are taken into the account. plants-11-01141-t001_Table 1 Table 1 Geographically isolated micropopulations (accessions) of Trifolium fragiferum in Latvia were analyzed in the present study. Code Associated Water Reservoir Habitat Location Coordinates TF1 Lake Liepājas Salt-affected wet shore meadow City of Liepāja 56°29′29″ N, 21°1′38″ E TF2 River Lielupe Salt-affected shore meadow City of Jūrmala, Lielupe, River Lielupe Estuary 57°0′11″ N, 23°55′56″ E TF2b River Lielupe Shore meadow City of Jūrmala, Majori 56°57′29″ N, 23°49′11″ E TF3 River Buļļupe Shore meadow City of Rīga, Kurzeme District, Island of Buļļu Sala, Vakarbuļļi 56°59′53″ N, 23°57′21″ E TF4 – Degraded urban land City of Rīga, Vidzeme Suburb 56°57′46″ N, 24°7′2″ E TF5 The Gulf of Riga of the Baltic Sea Salt-affected wet coastal meadow Salacgrīva Parish, Randu Meadows 57°49′51″ N, 24°20′12″ E TF6 The Gulf of Riga of the Baltic Sea Salt-affected wet coastal meadow Salacgrīva Parish, Randu Meadows 57°50′9″ N, 24°20′15″ E TF7 The Gulf of Riga of the Baltic Sea Dry coastal meadow Town of Ainaži 57°52′8″ N, 24°21′10″ E TF8 cv. ‘Palestine’ na na na na na, not available. plants-11-01141-t002_Table 2 Table 2 Relative degree of nodule presence on roots of individual plants of Trifolium fragiferum by treatments. C N R RN Accession By Replicates Mean ± SE By Replicates Mean ± SE By Replicates Mean ± SE By Replicates Mean ± SE TF1 2-0-0-0-3 1.0 ± 0.6 0-0-0-0-0 0 3-1-3-3-3 2.6 ± 0.4 0-0-3-0-0 0.6 ± 0.6 TF2 0-2-0-0-1 0.6 ± 0.4 0-0-0-0-0 0 3-3-2-3-3 2.8 ± 0.2 1-1-0-1-0 0.6 ± 0.3 TF2b 0-1-0-0-0 0.2 ± 0.2 0-0-0-0-0 0 3-3-3-3-3 3.0 ± 0.0 3-2-1-1-1 1.6 ± 0.4 TF3 2-0-3-1-0 1.2 ± 0.6 0-0-0-0-0 0 3-3-3-3-3 3.0 ± 0.0 2-1-1-1-2 1.4 ± 0.3 TF4 3-0-0-0-0 0.6 ± 0.6 0-0-0-0-0 0 3-3-3-3-2 2.8 ± 0.2 0-0-0-0-0 0 TF5 0-2-1-0-0 0.6 ± 0.4 0-0-0-0-0 0 2-2-3-3-3 2.6 ± 0.3 0-2-1-0-0 0.6 ± 0.4 TF6 0-0-0-0-0 0 0-0-0-0-0 0 3-2-3-3-2 2.6 ± 0.3 0-0-1-1-2 0.8 ± 0.4 TF7 2-0-0-1-2 1.0 ± 0.5 0-0-0-0-0 0 3-2-3-3-2 2.6 ± 0.3 0-0-0-0-0 0 TF8 2-2-0-3-2 1.8 ± 0.5 0-0-1-0-0 0.2 ± 0.2 3-2-2-3-3 2.6 ± 0.3 0-0-0-0-0 0 0, no nodules; 1, a few nodules at only one point; 2, small groups of nodules at several points on roots; 3, a large number of nodules throughout the root length. C, asymbiotic control; N, asymbiotic N-fertilized; R, rhizobia-inoculated; RN, rhizobia-inoculated N-fertilized plants. plants-11-01141-t003_Table 3 Table 3 Total dry mass (DM) of above-ground parts and roots in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) plants of Trifolium fragiferum. Shoot DM (g Plant−1) Root DM (g Plant−1) Accession C N R RN C N R RN TF1 11.4 ± 0.3 c 21.6 ± 0.4 a 15.2 ± 0.5 b 21.6 ± 0.7 a 1.48 ± 0.14 a 1.72 ± 0.25 a 1.36 ± 0.13 a 1.21 ± 0.14 a TF2 10.7 ± 0.7 b 19.9 ± 1.1 a 18.6 ± 0.4 a 20.0 ± 1.6 a 1.96 ± 0.20 b 3.01 ± 0.19 a 2.42 ± 0.16 ab 2.63 ± 0.28 ab TF2b 12.2 ± 0.3 c 23.4 ± 0.9 a 19.7 ± 0.8 b 23.8 ± 0.4 a 1.93 ± 0.15 b 2.65 ± 0.14 a 2.34 ± 0.16 ab 1.97 ± 0.14 b TF3 14.8 ± 0.7 c 27.4 ± 0.7 a 21.9 ± 1.1 b 26.7 ± 0.7 a 1.51 ± 0.11 a 2.06 ± 1.12 a 1.84 ± 0.25 a 2.18 ± 0.17 a TF4 12.8 ± 0.7 c 23.3 ± 0.4 a 19.4 ± 0.9 b 22.9 ± 0.9 a 2.06 ± 0.19 a 2.49 ± 0.12 a 2.07 ± 0.20 a 2.02 ± 0.17 a TF5 12.0 ± 0.3 d 20.3 ± 1.5 b 15.4 ± 0.6 c 24.1 ± 0.4 a 2.20 ± 0.20 a 2.73 ± 0.26 a 2.27 ± 0.08 a 2.96 ± 0.25 a TF6 10.0 ± 0.2 b 18.7 ± 0.7 a 18.4 ± 0.3 a 20.0 ± 0.7 a 1.88 ± 0.17 a 1.93 ± 0.07 a 1.96 ± 0.07 a 1.89 ± 0.16 a TF7 9.9 ± 0.6 b 17.7 ± 0.9 a 17.0 ± 0.6 a 18.0 ± 1.0 a 1.69 ± 0.24 a 1.69 ± 0.20 a 1.69 ± 0.14 a 1.72 ± 0.04 a TF8 10.2 ± 0.7 b 19.1 ± 1.3 a 13.3 ± 1.7 b 20.6 ± 1.3 a 3.38 ± 0.42 a 4.74 ± 0.12 a 3.12 ± 0.40 a 4.68 ± 0.63 a Different letters indicate statistically significant differences (p < 0.05) between treatments. plants-11-01141-t004_Table 4 Table 4 Number of flowers and number of leaves in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) plants of Trifolium fragiferum. Flowers (n Plant−1) Leaves (n Plant−1) Accession C N R RN C N R RN TF1 6. 0 ± 1.2 c 38.4 ± 4.3 ab 22.5 ± 5.1 b 51.8 ± 9.1 a 293 ± 15 b 489 ± 43 a 427 ± 42 ab 390 ± 25 ab TF2 8.6 ± 1.4 b 32.0 ± 4.6 a 33.0 ± 5.4 a 34.2 ± 7.8 a 339 ± 19 c 489 ± 25 b 590 ± 29 a 587 ± 8 a TF2b 6.4 ± 1.9 b 63.8 ± 8.4 a 45.4 ± 9.2 a 83.0 ± 14.1 a 531 ± 22 a 612 ± 56 a 756 ± 81 a 635 ± 78 a TF3 14.5 ± 4.8 c 81.6 ± 6.0 a 30.4 ± 7.6 bc 48.4 ± 9.1 b 470 ± 36 b 687 ± 51 ab 709 ± 71 ab 854 ± 89 a TF4 26.3 ± 3.3 c 58.6 ± 2.0 a 38.4 ± 2.2 b 54.0 ± 5.3 a 277 ± 19 c 485 ± 12 a 412 ± 22 b 461 ± 11 ab TF5 10.0 ± 2.7 c 39.0 ± 5.0 b 15.6 ± 2.4 c 74.2 ± 5.5 a 361 ± 16 b 544 ± 27 a 479 ± 30 a 515 ± 31 a TF6 11.0 ± 1.7 c 54.6 ± 6.5 b 55.8 ± 3.3 b 80.0 ± 6.9 a 384 ± 32 a 465 ± 9 a 472 ± 20 a 469 ± 37 a TF7 3.0 ± 1.0 b 31.8 ± 3.9 a 42.2 ± 5.0 a 47.8 ± 8.5 a 462 ± 26 b 631 ± 26 a 584 ± 35 a 561 ± 15 ab TF8 3.0± 3.0 a 10.8± 5.5 a 1.6± 1.6 a 15.8± 7.8 a 233± 18 a 578± 87 a 367± 88 a 501 ± 87 a Different letters indicate statistically significant differences (p < 0.05) between treatments. plants-11-01141-t005_Table 5 Table 5 Number of stolons and total stolon length in control (C), N-fertilized (N), rhizobia-inoculated (R) and rhizobia inoculated + N-fertilized (RN) plants of Trifolium fragiferum. Stolons (n Plant−1) Stolon Length (m Plant−1) Accession C N R RN C N R RN TF1 27.7 ± 1.4 b 57.8 ± 4.1 a 37.8 ± 4.6 b 43.0 ± 3.4 ab 10.7 ± 0.7 c 18.2 ± 0.6 a 13.8 ± 1.2 bc 14.5 ± 0.6 b TF2 31.4 ± 0.9 b 57.8 ± 2.1 a 52.6 ± 1.8 a 61.2 ± 2.7 a 9.0 ± 0.7 b 18.9 ± 1.4 a 15.0 ± 0.8 a 18.1 ± 0.9 a TF2b 42.2 ± 4.4 c 73.5 ± 3.1 a 53.0 ± 3.1 bc 67.8 ± 5.4 ab 13.9 ± 0.9 c 24.9 ± 1.1 a 18.8 ± 0.8 b 22.0 ± 1.3 ab TF3 34.0 ± 2.1 c 59.0 ± 3.4 ab 41.4 ± 3.8 bc 67.8 ± 7.4 a 12.5 ± 0.2 c 21.6 ± 2.3 ab 15.7 ± 1.1 bc 22.7 ± 1.5 a TF4 23.2 ± 2.6 c 41.0 ± 1.3 a 34.2 ± 1.6 b 42.6 ± 0.9 a 6.7 ± 0.3 c 13.1 ± 0.4 a 11.2 ± 0.4 b 14.5 ± 0.5 a TF5 30.6 ± 1.2 b 49.4 ± 3.6 a 36.2 ± 2.3 b 49.4 ± 3.2 a 8.8 ± 0.6 b 15.4 ± 2.2 a 12.7 ± 1.0 ab 14.2 ± 1.4 ab TF6 40.0 ± 2.9 b 61.0 ± 5.0 a 48.4 ± 2.0 ab 56.8 ± 4.9 a 10.3 ± 0.3 b 16.1 ± 0.6 a 14.0 ± 0.3 a 14.5 ± 0.9 a TF7 43.6 ± 1.8 c 61.8 ± 1.4 ab 56.8 ± 2.3 b 66.4 ± 1.8 a 11.9 ± 0.1 b 16.8 ± 0.5 a 16.0 ± 0.8 a 16.5 ± 1.0 a TF8 15.3± 1.8 b 32.8± 4.1 a 18.0± 3.1 b 25.8± 1.7 ab 3.3± 0.7 b 9.3± 1.4 a 5.8± 1.1 ab 6.2± 1.3 ab Different letters indicate statistically significant differences (p < 0.05) between treatments. plants-11-01141-t006_Table 6 Table 6 Changes in concentration of nitrogen (% in comparison to asymbiotic control) in various parts of different accessions of Trifolium fragiferum plants, treated asymbiotically with nitrogen(N), incolutaed with rhizobia (R), inoculated with rhizobia and treated with nitrogen (RN). Leaf Blades Leaf Petioles Stolons Roots Accession N R RN N R RN N R RN N R RN TF1 141 * 135 * 129 * 127 * 128 * 131 * 207 * 170 * 257 * 131 148 * 155 * TF2 152 * 156 * 141 * 122 * 130 143 * 221 * 228 * 222 * 158 * 163 * 141 * TF2b 222 * 194 * 178 * 181 * 156 * 148 * 167 * 153 * 224 * 174 * 170 * 170 * TF3 208 * 208 * 229 * 173 * 182 * 178 * 151 * 181 * 147 * 130 * 161 * 131 * TF4 170 * 151 * 183 * 147 * 116 153 * 252 * 237 * 485 * 132 144 * 139 * TF5 135 123 123 113 111 120 211 * 156 * 163 * 153 * 152 * 156 * TF6 156 * 122 141 * 106 98 102 156 * 102 168 * 175 * 148 * 158 * TF7 152 * 125 143 * 142 * 101 118 150 * 92 123 167 * 144 * 169 * TF8 135 76 119 156 96 158 220 100 134 134 67 109 Significant changes from the respective control values are indicated by *. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Skiba V. Wainwright M. Nitrogen transformation in coastal sands and dune soils J. Arid Environ. 1984 7 1 8 10.1016/S0140-1963(18)31398-3 2. van Wijnen H.J. Bakker J.P. Nitrogen and phosphorus limitation in a coastal barrier salt marsh: The implications for vegetation succession J. Ecol. 1999 87 265 272 10.1046/j.1365-2745.1999.00349.x 3. Crain C.M. Silliman B.R. Bertness S.L. Bertmness M.D. Physical and biotic drivers of plant distribution across estuarine salinity gradients Ecology 2004 85 2539 2549 10.1890/03-0745 4. van der Heijden M.G.A. Bakker R. Verwaal J. Scheublin T.R. Rutten M. van Logtestjin R. Staehelin C. Symbiotic bacteria as a determinant of plant community structure and plant productivity in dune grassland FEMS Microbiol. Ecol. 2006 56 178 187 10.1111/j.1574-6941.2006.00086.x 16629748 5. Nichols P.G.H. Revell C.K. Humphries A.W. Howie J.H. Hall E.J. Sandral G.A. Ghamkhar K. Harris C.A. Temperate pasture legumes in Australia-their history, current use, and future prospects Crop Pasture Sci. 2012 63 691 725 10.1071/CP12194 6. Whitehead D.C. Grassland Nitrogen CABI International Wallingford, UK 1995 397 7. Warschefsky E. Penmetsa R.W. Cook D.R. von Wettberg E.J.B. Back to the wilds: Tapping evolutionary adaptations for resilient crops through systematic hybridization with crop wild relatives Amer. J. Bot. 2014 101 1791 1800 10.3732/ajb.1400116 25326621 8. Prohens J. Gramazio P. Plazas M. Dempewolf H. Kilian B. Diez M.J. Fita A. Herraiz F.J. Rodríguez-Burruezo A. Soler S. Introgressiomics: A new approach for using crop wild relatives in breeding for adaptation to climate change Euphytica 2017 213 158 10.1007/s10681-017-1938-9 9. Zhang H. Yasmin F. Song B.-H. Neglected treasures in the wild-legume wild relatives in food security and human health Curr. Opin. Plant Biol. 2019 49 17 26 10.1016/j.pbi.2019.04.004 31085425 10. Ohyama T. The role of legume-Rhizobium symbiosis in sustainable agriculture Legume Nitrogen Fixation in Soils with Low Phosphorus Availability: Adaptation and Regulatory Implication Sulieman S. Phan Tran L.-S. Springer Cham, Switzerland 2017 1 20 11. Sindhu S. Dahiya A. Gera R. Sindhu S.S. Mitigation of abiotic stress in legume-nodulationg rhizobia for sustainable crop production Agric. Res. 2020 9 444 459 10.1007/s40003-020-00474-3 12. Janssen J.A.M. Rodwell J.S. European Red List of Habitats: Part 2. Terrestrial and Freshwater Habitats European Union Brussels, Belgium 2016 13. Andersone-Ozola U. Jēkabsone A. Purmale L. Romanovs M. Ievinsh G. Abiotic stress tolerance of coastal accessions of a promising forage species, Trifolium fragiferum Plants 2021 10 1552 10.3390/plants10081552 34451597 14. Rumbaugh M.D. Pendery B.M. James D.W. Variation in the salinity tolerance of strawberry clover (Trifolium fragiferum L.) Plant Soil 1993 153 265 271 10.1007/BF00012999 15. Jēkabsone A. Andersone-Ozola U. Karlson S.A. Romanovs M. Ievinsh G. Effect of salinity on growth, ion accumulation and mineral nutrition of different accessions of a crop wild relative legume species, Trifolium fragiferum Plants 2022 11 797 10.3390/plants11060797 35336679 16. Townsend C.E. Miscellaneous perennial clovers Clover Science and Technology Taylor J.L. ASA/CSSA/SSSA Madison, WI, USA 1985 563 578 17. Andersone-Ozola U. Jēkabsone A. Karlsons A. Romanovs M. Ievinsh G. Soil chemical properties and mineral nutrition of Latvian accessions of Trifolium fragiferum, a crop wild relative plant species Environ. Exp. Biol. 2021 19 245 254 18. Zahran H.H. Rhizobia from wild legumes: Diversity, taxonomy, ecology, nitrogen fixation and biotechnology J. Biotechnol. 2001 91 143 153 10.1016/S0168-1656(01)00342-X 11566386 19. Stępkowski T. Banasiewicz J. Granada C.E. Andrews M. Passaglia L.M. Phylogeny and phlogeography of rhizobial symbionts nodulating legumes of the tribe Genisteae Genes 2018 9 163 10.3390/genes9030163 20. Rejili M. Abderrahim A.B. Mars M. Phylogenomic review of root nitrogen-fixing symbiont population nodulating Northwestern Africal wild legumes Nitrogen Fixation Rigobelo E. Serra A. Blumenberg M. Intech Open London, UK 2019 10.5772/intechopen.87082 21. Taylor B.N. Simms E.L. Komatsu K.J. More than a functional group: Diversity within the legume-rhizobia mutualism and its relationship with ecosystem functioning Diversity 2020 12 50 10.3390/d12020050 22. Gaile L. Andersone-Ozola U. Samsone I. Elferts D. Ievinsh G. Modification of growth and physiological response of coastal dune species Anthyllis maritima to sand burial by rhizobial symbiosis and salinity Plants 2021 10 2584 10.3390/plants10122584 34961054 23. Dūmiņš K. Andersone-Ozola U. Samsone I. Elferts D. Ievinsh G. Growth and physiological performance of a coastal species Trifolium fragiferum as affected by a coexistence with Trifolium repens, NaCl treatment and inoculation with rhizobia Plants 2021 10 2196 10.3390/plants10102196 34686005 24. Carter G.A. Knapp A.K. Leaf optical properties in higher plants: Linking spectral characteristics to stress and chlorophyll concentration Am. J. Bot. 2001 88 677 684 10.2307/2657068 11302854 25. Touchette B.W. Adams E.C. Laimbeer P. Age-specific responses to elevated salinity in the coastal marsh plant black needlerush (Juncus roemerianus Scheele) as determined through polyphasic chlorophyl a fluorescence transients (OJIP) Mar. Biol. 2012 159 2137 2147 10.1007/s00227-012-2000-z 26. Badr A. Brüggemann W. Comparative analysis of drought stress response of maize genotypes using chlorophyll fluorescence measurements and leaf relative water content Photosynthetica 2020 58 638 645 10.32615/ps.2020.014 27. Latifinia E. Eisvand H.R. Soybean physiological properties and grain quality responses to nutrients, and predicting nutrient deficiency using chlorophyll fluorescence J. Soil Sci. Plant Nutr. 2022 1 3 10.1007/s42729-022-00785-0 35528198 28. Friel C.A. Friesen M.L. Legumes modulate allocation to rhizobial nitrogen fixation in response to factorial light and nitrogen manipulation Front. Plant Sci. 2019 10 1316 10.3389/fpls.2019.01316 31749816 29. Zhou X.-J. Liang Y. Chen H. Shen S.-H. Jing Y.-X. Effects of rhizobia inoculation and nitrogen fertilization on photosynthetic physiology of soybean Photosynthetica 2006 44 530 535 10.1007/s11099-006-0066-x 30. Bambara S. Ndakidemi P.A. Effects of Rhizobium inoculation, lime and molybdenum on photosynthesis and chlorophyll content of Phaseolus vulgaris L. Afr. J. Microbiol. Res. 2009 3 791 798 31. Namvar A. Seyed Sharifi R. Khandan T. Jafari Moghadam M. Seed inoculation and inorganic nitrogen fertilization effects on some physiological and agronomical traits of chickpea (Cicer arietinum L.) in irrigated conditions J. Central Eur. Agric. 2013 14 28 40 10.5513/JCEA01/14.3.1281 32. Singh G. Virk H.K. Aggarwal N. Gupta R.K. Growth, symbiotic traits, productivity and nutrient uptake as influenced by dose and time of nitrogen application and Rhizobium inoculation in mungbean [Vigna radiata (L.) Wilczek] J. Plant Nutr. 2021 44 1982 1992 10.1080/01904167.2021.1884709 33. Strasser R.J. Srivastava A. Tsimilli-Michael M. The fluorescence transient as a tool to characterise and screen photosynthetic samples Probing Photosynthesis: Mechanisms, Regulation and Adaptation Yunus M. Pathre U. Mohanty P. Taylor & Francis London, UK 2000 445 483 34. Metsalu T. Vilo J. ClustVis: A web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap Nucleic Acids Res. 2015 43 W566 W570 10.1093/nar/gkv468 25969447 35. Concha C. Doerner P. The impact of the rhizobia-legume symbiosis on host root system architecture J. Exp. Bot. 2020 71 3902 3921 10.1093/jxb/eraa198 32337556 36. Montealegre C.M. Van Kessel C. Blumenthal J.M. Hur H.G. Hartwig U.A. Sadowsky M.J. Elevated atmospheric CO2 alters microbial population structure in a pasture ecosystem Glob. Chang. Biol. 2000 6 475 482 10.1046/j.1365-2486.2000.00326.x 37. Denton M.D. Reeve W.G. Howieson J.G. Coventry D.R. Competitive abilities of common field isolates and a commercial strain of Rhizobium leguminosarum bv. trifolii for clover nodule occupancy Soil Biol. Biochem. 2003 35 1039 1048 10.1016/S0038-0717(03)00146-9 38. Melino V.J. Drew E.A. Ballard R.A. Reeve W.G. Thomson G. White R.G. O’Hara G.W. Identifying abnormalities in symbiotic development between Trifolium spp. and Rhizobium leguminosarum bv. trifolii leading to sub-optimal and ineffective nodule phenotypes Ann. Bot. 2012 110 1559 1572 10.1093/aob/mcs206 22989463 39. Wang D. Yang S. Tang F. Zhu H. Symbiosis specificity in the legume-rhizobial mutualism Cell. Microbiol. 2012 14 334 342 10.1111/j.1462-5822.2011.01736.x 22168434 40. Drew E.A. Ballard R.A. Improving N2 fixation from the plant down: Compatibility of Trifolium subterraneum L. cultivars with soil rhizobia can influence symbiotic performance Plant Soil 2010 327 261 277 10.1007/s11104-009-0052-8 41. Davidson I.A. Robson M.J. Effect of contrasting patterns of nitrate application on the nitrate uptake, N2-fixation, nodulation and growth of white clover Ann. Bot. 1986 57 331 338 10.1093/oxfordjournals.aob.a087114 42. Solaiman A. Talukder M.S. Rabbani M.M. Influence of some Rhizobium strains on chickpea: Nodulation, dry matter yield and nitrogen uptake Bangladesh J. Microbiol. 2011 27 61 64 10.3329/bjm.v27i2.9174 43. Tegeder M. Masclaux-Daubresse C. Source and sink mechanisms of nitrogen transport and use New Phytol. 2017 217 35 53 10.1111/nph.14876 29120059 44. Masclaux-Daubresse C. Daniel-Vedele F. Dechorgnat J. Chardon F. Gaufichon L. Suzuki A. Nitrogen uptake, assimilation and remobilization in plants: Challenges for sustainable and productive agriculture Ann. Bot. 2010 105 1141 1157 10.1093/aob/mcq028 20299346 45. Dincă N. Dunea D. The influence of Rhizobium inoculation and nitrogen/molybdenum fertilization on the growth characteristics of red clover AgroLife Sci. J. 2017 6 83 88 46. Goh C.-H. Nicotra A.B. Mathesius U. Genes controlling legume nodule numbers affect phenotypic plasticity responses to nitrogen in the presence and absence of rhizobia Plant Cell Environ. 2019 42 1747 1757 10.1111/pce.13498 30512188 47. Streeter J. Inhibition of legume nodule formation and N2 fixation by nitrate Crit. Rev. Plant Sci. 1988 7 1 22 10.1080/07352688809382257 48. Dogra R.C. Dudeja S.S. Fertilizer N and nitrogen fixation in legume-Rhizobium symbiosis Ann. Biol. 1993 9 149 164 49. Harris S.L. Clark D.A. Effect of high rates of nitrogen fertiliser on white cover growth, morphology, and nitrogen fixation activity in grazed dairy pasture in northern New Zealand N. Z. J. Agric. Res. 1996 39 149 158 10.1080/00288233.1996.9513173 50. Moustafa E. Ball R. Field T.R.O. The use of acetylene reduction to study the effect of nitrogen fertiliser and defoliation on nitrogen fixation by field-grown white clover N. Z. J. Agric. Res. 1969 12 691 696 10.1080/00288233.1969.10421220 51. Griffith G.S. Cresswell A. Jones S. Allen D.K. The nitrogen handling characteristics of white clover (Trifolium repens L.) cultivars and a perennial ryegrass (Lolium perenne L.) cultivar J. Exp. Bot. 2000 51 1879 1892 10.1093/jexbot/51.352.1879 11113166 52. Vollmann J. Walter H. Sato T. Schweiger P. Digital image analysis and chlorophyll metering for phenotyping the effects of nodulation in soybean Comp. Electron. Agric. 2011 75 190 195 10.1016/j.compag.2010.11.003 53. Fridgen J.L. Varco J.J. Dependency of cotton leaf nitrogen, chlorophyll, and reflectance on nitrogen and potassium availability Agron. J. 2004 96 63 69 10.2134/agronj2004.0063 54. Zhao B. Ata-Ul-Karim S.T. Liu Z. Zhamg J. Xiao J. Liu Z. Qin A. Ning D. Yang Q. Zhang Y. Simple assessment of nitrogen nutrition index in summer maize by using chlorophyll meter readings Front. Plant Sci. 2018 9 11 10.3389/fpls.2018.00011 29403521 55. Fiorentini M. Zenobi S. Giorgini E. Basil D. Conti C. Pro C. Monaci E. Orsini R. Nitrogen and chlorophyll status determination in durum wheat as influenced by fertilization and soil management: Preliminary results PLoS ONE 2019 14 e0225126 10.1371/journal.pone.0225126 31725780 56. Kashiwagi J.K. Upadhyaya H.D. Krishnamurthy L. Significance and genetic diversity of SPAD chlorophyll meter reading in chickpea germplasm in the semi-arid environments J. Food Legumes 2010 23 99 105 57. Fritschi F.B. Ray J.D. Soybean leaf nitrogen, chlorophyll content, and chlorophyll a/b ratio Photosynthetica 2007 45 92 98 10.1007/s11099-007-0014-4 58. Ndakidemi P. Bambara S. Makoi J.H.J.R. Micronutrient uptake in common bean (Phaseolus vulgaris L.) as affected by Rhizobium inoculation, and the supply of molybdenum and lime Plant Omics J. 2011 4 40 52 59. Stajković-Srbinović O. Delić D. Rasulić N. Čakmak D. Kuzmanović D. Sikirić B. Mineral composition of red clover under Rhizobium inoculation and lime application in acid soil Notulae Bot. Horti Agrobot. 2015 43 554 560 10.15835/nbha43210007 60. Belane A.K. Pule-Meulenberg F. Makhubedu T.I. Dakora F.D. Nitrogen fixation and symbiosis-induced accumulation of mineral nutrients by cowpea (Vigna unguiculata L. Walp.) Crop Pasture Sci. 2014 65 250 258 10.1071/CP13283 61. Bērtiņš M. Klūga A. Dubova L. Petrēvics P. Alsiņa I. Vīksna A. Study of rhizobia impact on nutritional element concentration in legumes Proc. Latv. Acad. Sci. B 2021 75 457 462 10.2478/prolas-2021-0068 62. Lau J.A. Bowling E.J. Gentry L.E. Glasser P.A. Monarch E.A. Olesen W.M. Waxmonsky J. Young R.T. Direct and interactive effects of light and nutrients on the legume-rhizobia mutualism Acta Oecol. 2012 39 80 86 10.1016/j.actao.2012.01.004 63. Al-Falih A.M.K. Factors affecting the efficiency of symbiotic nitrogen fixation by Rhizobium Pak. J. Biol. Sci. 2002 5 1277 1293 64. Manchanda G. Garg N. Salinity and its effects on the functional biology of legumes Acta Physiol. Plant. 2008 30 595 618 10.1007/s11738-008-0173-3 65. Zahran H.H. Conditions for successful Rhizobium-legume symbiosis in saline environments Biol. Fertil. Soils 1991 12 73 80 10.1007/BF00369391 66. Zhang Y. Ju X. Hong T. Li Z. Nodule numbers, colonization rates, and carbon accumulations of white clover response of nitrogen and phosphorus starvation in the dual symbionts of rhizobial and arbuscular mycorrhizal fungi J. Plant Nutr. 2019 42 2259 2268 10.1080/01904167.2019.1655048 67. Karlsons A. Druva-Lusite I. Osvalde A. Necajeva J. Andersone-Ozola U. Samsone I. Ievinsh G. Adaptation strategies of rare plant species to heterogeneous soil conditions on a coast of a lagoon lake as revealed by analysis of mycorrhizal symbiosis and mineral constituent dynamics Environ. Exp. Biol. 2017 15 113 126 68. Xie X.-F. Hu Y.-K. Pan X. Liu F.-H. Song Y.-B. Dong M. Biomass allocation of stoloniferous and rhizomatous plant in response to resource availability: A phylogenetic meta-analysis Front. Plant Sci. 2016 7 603 10.3389/fpls.2016.00603 27200071 69. Liu X.Y. Wang E.T. Li Y. Chen W.X. Diverse bacteria isolated from root nodules of Trifolium, Crotalaria and Mimosa grown in the subtropical regions of China Arch. Microbiol. 2007 188 1 14 10.1007/s00203-007-0209-x 17497134 70. Wielbo J. Marek-Kozaczuk M. Mazur A. Kubik-Komar A. Skorupska A. Genetic and metabolic divergence within a Rhizobium leguminoosarum bv. trifolii population from clover nodules Appl. Environ. Microbiol. 2010 76 4593 4600 10.1128/AEM.00667-10 20472725 71. Wielbo J. Marek-Kozaczuk M.A. Kubik-Komar A. Skorupska A. Increased metabolic potential of Rhizobium spp. is associated with bacterial competitiveness Can. J. Microbiol. 2007 53 957 967 10.1139/W07-053 17898852 72. Blanco A.R. Sicardi M. Frioni L. Competition for nodule occupancy beyween introduced and native strains of Rhizobium leguminosarum biovar trifolii Biol. Fertil. Soils 2010 46 419 425 10.1007/s00374-010-0439-y 73. Simms E.L. Taylor D.L. Povich J. Shefferson R. Sachs J.L. Urbina M. Tausczik Y. An empirical test of partner choice mechanisms in a wild legume-rhizobium interaction Proc. R. Soc. B 2006 273 77 81 10.1098/rspb.2005.3292 16519238

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094885 ijms-23-04885 Review Dendritic Cells and Their Immunotherapeutic Potential for Treating Type 1 Diabetes Khan Farhan Ullah Khongorzul Puregmaa Raki Ahmed Aziz Rajasekaran Ashwini https://orcid.org/0000-0003-1215-2434 Gris Denis Amrani Abdelaziz * Gregori Silvia Academic Editor Department of Pediatrics, Immunology Division, Faculty of Medicine and Health Sciences, Centre de Recherche du CHUS, Université de Sherbrooke, 3001, 12th Avenue North, Sherbrooke, QC J1H 5N4, Canada; farhan.ullah.khan@usherbrooke.ca (F.U.K.); puregmaa.khongorzul@usherbrooke.ca (P.K.); ahmed.aziz.raki@usherbrooke.ca (A.A.R.); ashwini.rajasekaran@usherbrooke.ca (A.R.); denis.gris@usherbrooke.ca (D.G.) * Correspondence: abdelaziz.amrani@usherbrooke.ca; Tel.: +1-(819)-346-1110 (ext. 14854); Fax: +1-(819)-564-5215 28 4 2022 5 2022 23 9 488517 3 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Type 1 diabetes (T1D) results from the destruction of pancreatic beta cells through a process that is primarily mediated by T cells. Emerging evidence suggests that dendritic cells (DCs) play a crucial role in initiating and developing this debilitating disease. DCs are professional antigen-presenting cells with the ability to integrate signals arising from tissue infection or injury that present processed antigens from these sites to naïve T cells in secondary lymphoid organs, thereby triggering naïve T cells to differentiate and modulate adaptive immune responses. Recent advancements in our knowledge of the various subsets of DCs and their cellular structures and methods of orchestration over time have resulted in a better understanding of how the T cell response is shaped. DCs employ various arsenal to maintain their tolerance, including the induction of effector T cell deletion or unresponsiveness and the generation and expansion of regulatory T cell populations. Therapies that suppress the immunogenic effects of dendritic cells by blocking T cell costimulatory pathways and proinflammatory cytokine production are currently being sought. Moreover, new strategies are being developed that can regulate DC differentiation and development and harness the tolerogenic capacity of these cells. Here, in this report, we focus on recent advances in the field of DC immunology and evaluate the prospects of DC-based therapeutic strategies to treat T1D. type 1 diabetes dendritic cells tolerance immunity immunotherapy Natural Sciences and Engineering Research Council of Canada (NSERC)RGPIN-2015-03671 Canadian Institute of Health Research (CIHR)MOP-300762 This work was supported by grants to Abdelaziz Amrani from the Natural Sciences and Engineering Research Council of Canada (NSERC) (RGPIN-2015-03671) and the Canadian Institute of Health Research (CIHR) (MOP-300762). ==== Body pmc1. Introduction Type 1 diabetes (T1D) is an autoimmune disease that mainly affects children and young adults but can develop at any age. This disease arises from the selective destruction of insulin-producing pancreatic beta cells through a process that is mediated by an autoimmune response resulting from the breakdown of autoimmune tolerance. Approximately 5–10% of all diabetic patients have T1D, including more than 500,000 children worldwide, mostly in Europe and North America [1]. Moreover, epidemiological data have demonstrated that the T1D incidence has amplified significantly in recent years [2]. In 2019, Diabetes Research and Clinical Practice declared 128,900 newly diagnosed T1D cases globally in individuals under 20 years of age [3]. Both environmental elements and genetic susceptibility play crucial roles in advancing T1D. Polymorphisms in the HLA region of the major histocompatibility complex (MHC) broadly define the genetic risk of emerging T1D. The most prevalent loci are HLA-DQ8 and HLA-DQ2, which are found in 90% of type 1 diabetic patients [4]. These HLA molecules are associated with an enhanced presentation of various beta-cell-derived peptides by antigen-presenting cells (APCs). In addition to the HLA region, the insulin (INS), cytotoxic T lymphocyte-associated protein 4 (CTLA-4), IL-2 receptor (IL2RA), and protein tyrosine phosphatase N 22 (PTPN22) genes have the most significant influences on the etiopathogenesis of T1D [5,6]. A variety of immune cells participate in the pathogenesis of T1D, involving innate and adaptive immune systems and leading to the expansion of self-reactive, antigen-specific B and T lymphocytes. These immune cells can trigger islet inflammation to induce insulitis, which evolves into diabetes. Dendritic cells (DCs) are the body’s sentinels par excellence, which act as “conductors” of the immune response by “coordinating” signals from different parts of the immune system. Dendritic cells are motile cells with a stellate morphology that express high levels of MHC molecules and the integrin CD11c and are characterized by their ability to migrate from nonlymphoid to lymphoid organs and their superior ability to activate T lymphocytes [7]. DCs can take up various antigens, including micro-organisms released by dead cells, extracellular fluid, and apoptotic cells, which can be processed and present on MHC class I and class II molecules to naïve T cells in the form of peptides. DCs can be found throughout the human body. They can form a diverse network to sense homeostatic discrepancies and process antigens for presentation to T cells, thereby establishing an interface between innate and adaptive immune systems. In addition, DCs can secrete growth factors and cytokines that modulate ongoing immune responses and are influenced by their connections with other immune cells, such as natural killer (NK) cells and innate lymphoid cells (ILCs) [8,9]. At present, DCs are believed to be a diverse cell population whose members vary in ontogeny, anatomical locality, relocation, cytokine production pattern, and immunological responses. They are situated in nonlymphoid tissues, where they screen the surrounding environment via their pattern recognition receptors (PRRs) and identify pathogen-associated molecular patterns (PAMPs) [10]. Once DCs capture antigens, they travel to lymphoid organs and then dispose of the antigens to T lymphocytes. Thus, DCs contribute to the regulation of immune responses through effector T cell lineages and immune tolerance by producing different patterns of cytokines [11,12]. 2. Dendritic Cell Ontogeny The classic model of DC development mainly comes from mouse research. DCs originate from bone marrow (BM) CD34+ hematopoietic stem cells (HSCs), which transit into the common myeloid progenitor (CMP) displaying a Lin− c-Kit high Sca1− IL-7R alpha− subset and a common lymphoid progenitor (CLP) (Figure 1). The CMP differentiates into a bipotent progenitor called a macrophage and DC progenitor (MDP), giving rise to monocytes and DCs [13,14]. The MDP then begins to reduce the expression of c-Kit, an indication of differentiation into common dendritic cell progenitors (CDPs) displaying the Lin−c-Kitint, Flt3+ M-CSFR+ phenotype. Similar to CDPs, a common monocyte progenitor cell (cMoP) was recently discovered downstream of the MDP that produces monocytes but not DCs [15]. CDPs can differentiate into precursors of classical or conventional DCs (Pre-cDCs) with the manifestation of the zinc finger and BTB domain containing 46 (ZBTB46) and ID2, while the expression of transcription factor 4 (TCF4) results in the generation of plasmacytoid DC precursors (Pre-pDCs) [16,17]. Pre-cDCs are recognized by the expression of Siglec-H, CD11c, SIRP alphalow, and MHC-IIint, while Pre-pDCs can be identified by low expression of M-CSFR [18]. Pre-cDCs then further branch into cDC1 and cDC2 subsets, depending on the expression of key transcription factors related to each type (IRF8 and BATF3 for cDC1 or KLF4 and IRF4 for cDC2) [19,20,21]. In short, CDPs can differentiate into cDCs and pDCs (Figure 1). It is important to mention that Pre-cDC, Pre-pDC, CDP, MDP, and CMP cells are situated in the BM, while cDC1s, cDC2s, and pDCs are positioned in the periphery, such as in the lymphoid organs or blood [22]. During DC development and differentiation, growth factors, such as granulocyte-macrophage colony-stimulating factor (GM-CSF), Fms-like tyrosine kinase 3 ligand (Flt3-L), and macrophage colony-stimulating factor (M-CSF), are needed [23] (Figure 1). Flt3-L, which binds to the receptor Flt3, a protein tyrosine kinase receptor expressed especially in DC progenitors in the BM, is the most important growth factor involved in DC lineage diversification. Previously, it was shown that Flt3-L/Flt3 signaling is vital for developing and differentiating pDCs and cDCs in vitro [14,24,25]. Moreover, the in vivo role of Flt3 in DC development was demonstrated in Flt3-L deficient mice that showed severe insufficiency in DCs, and, to a lesser extent but also apparent, in mice deficient in their receptor CD135 (Flt3) or challenged with inhibitors of CD135 [26,27]. GM-CSF is another growth factor that is also involved in DC differentiation (Figure 1). GM-CSF is not necessary for steady-state DC differentiation, as demonstrated by a slight reduction in the number of DCs in mice lacking GM-CSF or GM-CSF receptors [28]. However, GM-CSF plays a crucial role in developing CD103+ CD11b+ DCs in the lamina propria, which is severely compromised in GM-CSF and GM-CSFR deficient mice [29]. In vitro, GM-CSF is a key factor for DC development from BM in mice and human monocytes while hindering the growth of pDCs in a STAT5-dependent manner [30]. On the other hand, M-CSF, which has a significant role in developing macrophages and monocytes, also participates in pDC differentiation from MCSFR+ precursor cells in the BM [31] (Figure 1). Nevertheless, despite the reduced levels of Langerhans cells (LCs) and monocytes in mice deficient in M-CSF and its receptor, no variations in the DC levels of lymphoid organs were noticed [32]. Moreover, M-CSF is necessary for the normal development of CD103–CD11b+ DCs in nonlymphoid tissues and can sustain the differentiation of pDCs and cDCs in the absence of FLT3 in cell culture [33]. 3. Dendritic Cell Subsets DCs were initially categorized into lymphoid and myeloid subsets, but this taxonomy does not precisely replicate each DC subgroup’s developmental origins (discussed previously [34]). Later, DC subgroups were classified based on their function, but DC plasticity, once again, defies rigid functional categories. In recent years, a new and simpler ontogeny classification scheme has emerged (reviewed previously in [35]), which is often associated with function (Figure 1). This categorizes DCs and related myeloid lineages into plasmacytoid DCs (pDCs), conventional (also identified as classical) DCs (cDCs), monocyte-derived DCs (MoDCs), and Langerhans cells (LCs). See Table 1 for details of the phenotypic markers that can be used to distinguish the different DC subtypes (Table 1). As the center of this report is DC-dependent type 1 diabetes treatment, here, we do not discuss the different DC subtypes, as the details are presented elsewhere [36,37,38]. 4. Dendritic Cell Plasticity Besides discovering DCs in 1973, Ralph Steinman and colleagues also highlighted their function in innate and adaptive immunity [39]. DCs are the most professional cell types that acquire and process antigens from pathogens and present them to the immune system [40,41]. The maturation status (immature, semimature, or fully mature) of DCs (Figure 2) governs the type of immune response generated to the presented antigen/peptide [42]. These three DC states have a series of independent special functions that enable them to exert different outcomes on the immune system. Most DCs reside within the body in a so-called immature state (Figure 2). These immature DCs (iDCs) are usually regarded as tolerogenic DCs (tDCs). In this state, iDCs lack many features and processes that lead to a strong T cell response, such as increased MHC presentation, the expression of costimulatory molecules (CD80, and CD86), and the production of inflammatory cytokines, like IL-12, IL-23, and TNF-α, whereas they are efficient at detecting and sequestering antigens [43]. They can accumulate MHC class II molecules in the late endosome-lysosomal compartment and have their own set of chemokine receptors (for example, CCR7), anabling them to home to lympoide tissues [44,45]. Antigen recognition is carried out through different PRRs, such as Toll-like receptors (TLRs) and NOD-like receptors (NLRs), or indirectly through FcRs and complement receptors (CRs), which recognize antigen–antibody complexes and complements, respectively [46,47,48]. The main functional feature of iDCs is their endocytic and phagocytic ability, which occurs continuously under steady-state conditions [49]. As iDCs have reduced surface expression of costimulatory molecules, little chemokine receptor expression, and are deficient in releasing immunostimulatory cytokines, they induce immune tolerance through T effector cell anergy and the expansion of regulatory T cells. This immune tolerance is actively initiated and sustained by a combination of immune checkpoint pathways and the absence of costimulatory signals induced by DCs [50]. Immune checkpoint pathways are multiple inhibitory cascades that are essential for maintaining self-tolerance and regulating the duration/magnitude of the immune reaction. For example, DC-based ligands, such as CTLA-4 and programmed cell death protein ligand 1 (PD-L1), result in T cell unresponsiveness or immunosuppressive T cell differentiation [51]. Under steady-state conditions, most DCs in peripheral tissues display an immature phenotype in the absence of inflammatory or microbial signals. However, under certain conditions, such as in the presence of lactobacilli from the gut flora [52], intranasally applied ovalbumin (OVA) [53], apoptotic cells [54], or TNF-α [55], immature DCs can differentiate into an intermediate subset of DC maturation, called the semimature state (Figure 2). This subset of DCs has high expression of costimulatory molecules and MHC-class II; however, they are deficient in producing elevated levels of proinflammatory cytokines, such as TNF-α, IL-1β, IL-6, IL-12p40, and IL-12p70. In one study, it was shown that semimature DCs can be generated in an IL-6 dependent manner by treating bone-marrow-derived DCs (BMDCs) with the commensal bacterial strain Bacteroides vulgatus [56]. In line with this finding, similar outcomes have been observed with DNA-matured DCs in experimental collagen-induced arthritis [57], TNF-α-matured DCs in a murine model of thyroiditis [55], MyD88-silenced DCs, and LPS-matured DCs following intestinal allograft transplantation in a rat model [58]. In contrast to immature and semimature DCs, dangerous environmental signals (including inflammatory cytokines and microbial ligands) transform immature and semimature DCs into a fully mature state, where they are known as mature DCs (mDCs) (Figure 2). Maturation is related to a reduced antigen-capture ability, increased antigen processing and presentation via elevated expression of MHC class II, greater capacity to migrate to T-cell-rich areas, such as draining lymph nodes through the acquisition of the chemokine receptor CCR7, and increased ability to prime naïve T cells via enhanced cytokine production and costimulatory molecule expression [59]. The production of cytokines by mDCs is a vital component of the immune response, because these signaling molecules are indispensable to the differentiation of T cells. Moreover, ligation of the costimulatory receptor CD40 (also known as TNFRSF5) on DCs to CD40L on T cells is an important signal used to differentiate iDCs into full mDCs that can initiate adaptive T-cell-mediated immunity [60]. The interaction of antigen-specific T cells with mDCs leads to naïve T cell priming and subsequent differentiation into effector T cells with unique functions and cytokine profiles capable of initiating antigen-specific responses [61]. The crosstalk between mDCs and CD4+ T cells may result in the differentiation of CD4+ T cells into diverse T helper (Th) subpopulations, such as Th1 [62], Th2 [63], Th17 [64], or other CD4+ T cell subsets [65]. 5. Metabolic Changes in DC during Development, Rest, and Activation Growing evidence has emerged over recent years to support the notion that cellular metabolism is not only required to fulfill the energetic and biosynthetic demands that arise when immune cells switch from a quiescent to an activated state, but it also impacts or even dictates immune cell subset and function, activation, and differentiation, including DCs [66]. ATP, the main carrier of energy in cells, is generated by glycolysis and oxidative phosphorylation (OXPHOS), a process that involves metabolite intermediates. The latter are not only substrates for downstream biochemical reactions but can also act as signals that influence gene expression and, therefore, the outcome of the immune response. The generation of DCs from progenitor cells is linked to lipid metabolism and mitochondrial biogenesis, which are triggered by the peroxisome proliferator-activated receptor (PPAR) and PPAR co-activator 1 (PGC1) and aided by PPAR, mTOR, and MYC signaling [67,68]. Although pre-cDC1s and pre-cDC2s differentiate into immature cDC1s and cDC2s with unique transcriptional patterns, little was known about the metabolic distinction between cDC1s and cDC2s until recently. Studies of conventional DCs showed that the mitochondrial mass and membrane potential of cDC1s are greater than those of cDC2s [69] and that cDC1s display much greater oxidative phosphorylation (OXPHOS) than DC2s [70]. Overall, these data indicate that cDC1s and cDC2s have different metabolic profiles that are reflective of their distinct immune functions. Interestingly, during Flt3L-induced differentiation of bone-marrow-derived DCs (BMDCs), inhibition of AMP-activated kinase (AMPK) or fatty acid oxidation (FAO) was shown to promote cDC2 differentiation. However, DC differentiation was tilted toward the generation of cDC1s when reactive oxygen species (ROS) were inhibited [69]. Another research group found that depleting Tsc1 (a negative regulator of mTOR signaling) lowers the levels of cDCs and pDCs in vivo and leads to the differentiation of FLT3L-stimulated bone marrow cells into cDCs and pDCs, which is associated with dysregulated mitochondrial respiration, fatty acid synthesis, and glycolysis [71]. Differentiated DCs reside in peripheral tissues in a relatively quiescent or immature state (iDCs). Fatty acid oxidation (FAO) is the core metabolic pathway involved in iDCs. When triggered by immunosuppressive signals such as IL-10 [72] or IL-27 [73], tissue-resident iDCs can differentiate into tol-DCs. There is increasing evidence that metabolic programming underlies the tolerance of DCs. However, in tol-DCs, in contrast to the iDCs, cellular metabolism switches toward active oxidative phosphorylation (OXPHOS) with a reduction in glycolysis and maintenance of a high level of catabolic metabolism [74]. Previously, it was shown that tol-DCs’ regulatory activities are disrupted by FAO and OXPHOS inhibition and partially restore their immunostimulatory function [75]. On the other hand, activation of DCs (maturation) by Toll-like receptor (TLR) agonists, such as lipopolysaccharide (LPS), CpG or Poly(I:C), or by type I interferon (IFN), induces a metabolic switch from OXPHOS to glycolysis [76,77]. This results in an immediate increase in glycolytic flux via the associated pentose phosphate pathway, which is accompanied by increases in the spare respiratory capacity and fatty acid synthesis. Pharmacological blockade of glycolysis with 2-deoxyglucose (2-DG) results in the inhibition of DC maturation, as demonstrated by lower expression of costimulatory molecules (CD40 and CD86) and MHC-II as well as reduced DC survival [78]. Therefore, tolerogenic properties of DCs seem to rely less on glycolysis and more on OXPHOS. Moreover, this switch to glycolytic metabolism was found to be initiated by the activation of TANK-binding kinase 1 (TBK1), IκB kinase-ε (IKKε), and AKT, a pathway downstream of TLRs, which is crucial for DC migration and activation [79]. After being activated, DCs remain glycolytic by increasing the glycolysis components, including pyruvate kinase 2 (PKM2), lactate dehydrogenase (LDH), and phosphofructokinase (PFK). Other reports have shown that, in IL-10-induced tolerogenic DCs, the activation of AMPK by IL-10 impedes LPS-induced DC glycolysis and maturation, raising the notion that extrinsic paracrine signaling pathways might promote the formation of an immunotolerant milieu by altering DC metabolism [76]. Taken together, these studies imply that different metabolic profiles in DCs are crucial drivers of differential DC functions. Since therapy is a promising avenue to treat autoimmune diseases such as T1D, dissection of the immunometabolic mechanisms underlying DC immunogenic versus tolerogenic functions will open new tolerogenic DC-based therapeutic avenues for the treatment of autoimmune diseases like T1D. 6. Type 1 Diabetes and Dendritic Cells Although beta cell dysfunction and beta-cell-targeted autoimmune processes are known to be involved in T1D, the precise etiology and pathological mechanisms are still largely yet to be elucidated. There are substantial data indicating that, in both humans and animal models of T1D, T cells are the major player involved in the development and progression of this disease. The loss of insulin-producing beta cells is mainly facilitated and orchestrated by CD8+ and CD4+ T cells specific to beta-cell antigens [80]. These T cells employ an array of processes to induce beta-cell destruction. CD8+ T cells can eliminate pancreatic beta cells via MHC class-I mediated cytotoxicity, while both CD8+ and CD4+ T cells secrete the inflammatory cytokine IFN-γ, thereby inducing the expression of the death receptor FAS (also called CD95) and the beta-cell production of chemokines [81]. Activation of FAS signaling through its binding to the FAS ligand expressed by activated diabetogenic CD4+ T cells can trigger beta-cell apoptosis [82]. Moreover, IFN-γ can induce macrophages to augment their secretion of proinflammatory cytokines, such as TNF-α and IL-1β. Compared with other endocrine cells in islets, beta cells express excessive levels of IL-1 receptors and tend to be more vulnerable to IL-1β-induced apoptosis through FAS induction. This crosstalk between macrophages and T cells undoubtedly aggravates immune-mediated beta cell stress and adds to their destruction. In the early stages of diabetes, however, inflammation is characterized by an influx of DCs [83] into the islets in response to an anomaly that has yet to be identified, such as impaired islet architecture remodeling via apoptosis, cross-presentation of endogenous peptides in response to viral pathogens, or superantigen-driven immune responses [36,84]. Several studies have unveiled that DCs are responsible for inducing pathogenic beta-cell-specific T cells by presenting beta-cell antigens [85,86]. DCs and macrophages are the earliest detectable immune cells in the islets of the T1D animal model nonobese diabetic (NOD) mice at the age of 3 to 4 weeks [81,87]. Diana et al. demonstrated that IFN-γ producing plasmacytoid dendritic cells are recruited to the pancreas where they initiate diabetogenic T cell responses and the development of T1D in NOD mice [88]. Another study showed that NOD mice engineered to express TNF-α specifically in beta-cells using the rat insulin promoter exhibit increased DC accumulation in the islets which, in turn, present beta-cell antigens to CD4+ T cells, followed by massive destructive insulitis and the promotion of diabetes onset [89]. Several other studies also reported the pathological relevance of DCs in the induction and maintenance of T1D [90,91,92] (previously reviewed in [93]). Numerous lines of evidence have revealed DC defects in the immunopathogenesis of T1D. It was shown that DCs derived from NOD mice and bio-breeding (BB) rats are dysfunctional in aspects ranging from the overactivation of DCs [85,94,95] to DC hypofunctionality [96,97]. Despite some recent studies indicating that possible deficiencies may also exist in humans [98,99], the response of diabetic patients to infection, recall to vaccine antigens, or capacity to induce hypersensitivity does not display any significant impairment [100,101], thereby creating more obscurity about potential defects in the development and function of DCs. 7. Dendritic Cell-Targeted Therapies for Treating T1D In recent decades, our understanding of the immune system has made great strides and powerful therapeutic tools have been developed, notably targeted antigen delivery to DCs, fusion proteins, and monoclonal antibodies against countless receptors expressed on T cells and a series of cytokine milieus that have begun the era of targeted immune therapy. The fact that DCs play a pivotal role in inducing and maintaining self-tolerance makes them a desirable target for therapeutic intervention. Interestingly, a variety of immunosuppressive agents have been explored to treat T1D (reviewed previously in [102]). In this review report, we only highlight those interventions that have been examined for their effects on DC maturation and ability to treat T1D, which will likely broaden our knowledge in the field. 7.1. Costimulation Blockade Costimulation is a crucial second signal that primes T cells after the first exposure to an antigen and is the link between adaptive and innate immunity. APCs, such as DCs, process and display antigen-derived peptides to the T-cell receptor (TCR) through the MHC peptide complex. However, in the absence of costimulation, T cells become unresponsive or may undergo apoptosis (Figure 3). DC surface receptor costimulatory molecules, for example, CD80/CD86 (also identified as B7-1 and B7-2), produce the necessary signals to initiate the induction and differentiation of naïve T cells and may inhibit immune tolerance, as occurs in T1D. CD80/CD86 can bind to CD28 on T cells (for autoregulation and intercellular association) as well as CTLA-4 produced by T cells (to attenuate immune suppression and cellular disassociation). The first drug targeting the binding of the CD80/CD86 costimulatory pair to CD28 was the fusion protein CTLA4-Ig, later identified as abatacept [103], a drug that has already been approved for treating rheumatoid arthritis patients [104,105]. Abatacept is a chimeric protein made up of the human CTLA-4 receptor conjugated with the modified Fc part of human IgG1 that is used as a decoy receptor for CD80/86 and prevents CD28-induced coactivation. The TrialNet research team studied the efficacy of abatacept in newly onset T1D patients (6–45 years old), in which the treatment group received 27 infusions of abatacept within a 2-year period [106] (Table 2). At the end of the treatment period, patients receiving abatacept showed significant C-peptide preservation compared with the placebo group (59% higher, p = 0.0029) after 24 months. However, after 6 months, preservation of the C-peptide declined, reaching the placebo level despite continuous treatment for 2 years. Investigation of peripheral T cell subpopulations by flow cytometry showed that naïve CD4+ T cells of abatacept-treated patients were moderately but significantly amplified, while the concentration of central memory CD4+ T cells decreased, and this seemed to be related to the preservation of the C peptide [107] (Table 2). Of some concern was a parallel and considerable reduction in the Treg cell percentage from baseline at 6, 12, and 24 months [107], which may have contributed to the finding that C-peptide responses started to decline soon after treatment began but at a slower rate than in the placebo group [106]. This decrease in Tregs can be attributed to the fact that Tregs, like other T cells, require costimulation to develop and exert their suppressive function [108]. Recently, it was demonstrated that this reduction in C-peptide preservation was associated with the transient elevation of activated B cells (that bind to abatacept) and reduced inhibition of anti-insulin antibodies [109] (Table 2). Similarly, since CTLA-4 on the cell surface may be the main mechanism by which Tregs regulate APC function [110], there are still unresolved issues regarding the outcome of continuous therapy with soluble CTLA4-Ig on Treg functionality. Nonetheless, the abatacept trial conducted in T1D patients provided essential preliminary insights into the potential costimulatory blockade in T1D and is worthy of further investigation. A trial assessing the ability of abatacept in combination with rituximab (anti-CD20 monoclonal antibody) to prevent T1D in at-risk patients is currently ongoing (ClinicalTrials.gov identifier NCT03929601). 7.2. Blocking Cytokine Production Cytokines produced by DCs activate and educate T cell differentiation and migration. When mature, DCs release a series of potent proinflammatory molecules, such as IL-12, IL-1, TNF-α, and IL-6 (Figure 3), which have been shown to have potent roles in T1D development [110]. Inhibiting the secretion of these molecules can induce noticeable changes in the preservation of pancreatic beta cell function [111]. The proinflammatory cytokines IL-1α and IL-1β, produced by DCs and/or macrophages, are potent immunomodulators that play key roles in pancreatic beta cell destruction [112,113]. IL-1 acts directly on beta cells, damaging the production and release of insulin and promoting cytokine- and hyperglycemia-induced beta-cell death [114]. In rodent models, it has been shown that IL-1 blockade results in slow progression and impairs the initiation of T1D [115]. IL-1 has been therapeutically targeted in a clinical trial in children newly diagnosed with T1D [116] (Table 2). In this clinical trial, fifteen children within 1 week of diagnosis of T1D received a daily IL-1 antagonist (Anakinra) for 28 days and were monitored for 6 months. The results demonstrated some significant outcomes in the protection against newly diagnosed T1D. Additional clinical trials in T1D patients also showed that IL-1 inhibition can induce pancreatic beta-cell preservation [117] (Table 2). TNF-α is another well-known cytokine produced by DCs that acts as an intermediate molecule in autoimmune diseases. This cytokine is produced during the inflammation process and can trigger signaling cascades related to cell survival, the inflammatory response, apoptosis, and cell differentiation. The cytokine TNF-α binds to the receptor’s TNF-R1 and TNF-R2 to initiate its responses. The TNF-R1 receptor has a death domain, while TNF-R2 does not, but it can exacerbate the cytotoxic effect of TNF-R1. As a result of infection and inflammation, TNF-α is mainly released by immune cells, such as lymphocytes and DCs [118,119]. The binding of TNF-α with the TNF-R1 receptor can enhance NF-κB activation or activate the caspase pathway, which plays an essential role in the execution of programmed cell death or apoptosis [120]. NF-κB triggers the expression of genes that code for cytokines (e.g., INF-γ, IL-1, TNF-α, IL-6, IL-12, and IL-2) as well as the expression of molecules that regulate cell cycle progression, cell proliferation, and apoptosis, such as TNF-receptor-associated factor 1 (TRAF-1), TRAF-2, cellular inhibitor of apoptosis protein 1 (c-IAP1), c-IAP2, B-cell lymphocyte/leukemia-2 (Bcl-2), Fas, c-myc, and cyclin D1 [121,122]. Therefore, the blockage of TNF-α has been investigated as a therapeutic target in a clinical trial aimed at prolonging the endogenous release of insulin in pediatric patients newly diagnosed with T1D [123] (Table 2). This clinical trial was a randomized, double-blind, and placebo-controlled 24-week study in which eighteen patients (11 males and 7 females, aged 7.8–18.2 years) were randomly assigned to receive either etanercept (recombinant TNF-α receptor–IgG fusion protein) or a placebo. This pilot study demonstrated improved beta cell mass preservation (measured by the C-peptide levels) and reduced glycated hemoglobin levels. One of the other important cytokines involved in autoimmune inflammation is IL-6. IL-6 can be released by a variety of cell types, including dendritic cells [124]. The pathological function of IL-6 in T1D is related to the IL-6R–gp130–STAT3 signaling axis. Signal transduction through this pathway is crucial for the differentiation of Th17 cells and inhibition of Treg cell development by inhibiting FOXP3 expression [125]. In a subset of T1D patients, IL-6 was found to be overexpressed [126], and as a result, anti-IL-6 therapy was initiated. The clinical trial EXTEND (clinical trial NCT02293837) investigated whether blocking IL-6 signaling (tocilizumab, anti-IL-6 receptor antibody) can provide improved beta-cell function in T1D patients. They found that, in newly diagnosed T1D patients, tocilizumab lowered T cell IL-6R signaling but unfortunately did not prevent the loss of residual beta cell function [127] (Table 2). Another proinflammatory cytokine produced by antigen-presenting cells in response to PAMPs and DAMPs is IL-12. It is mainly released by DCs and phagocytes (monocytes/macrophages and neutrophils) in response to pathogens (viruses, bacteria, intracellular parasites, and yeast-like fungi) [128,129]. It induces immune response polarization toward the Th1 profile by inducing IFN-γ expression [130,131]. This cytokine is also considered a possible target for T1D therapy. In a clinical trial, T1D patients were tested for the application of Ustekinumab (IL12/23 blocking molecule) (ClinicalTrials.gov identifier NCT02117765) [132] (Table 2). 7.3. In Vivo Targeting of DCs Generally, these types of therapy involve the use of agents that are deliberately targeted to a specific subset of DCs, but these methods can also include approaches that work by altering the local DC environment, although not directly targeting DCs (Figure 3). Treatment of NOD mice with nanoparticles (NPs) containing short antisense primary transcripts of the costimulatory molecules CD40, CD80, and CD86 has been shown to downregulate targeted receptors, induce a tolerogenic phenotype in DC populations, and prevent and/or reverse T1D [133]. The use of antigen-linked antibodies against the endocytic receptor DEC-205 (Figure 3) to deliver islet-specific antigens to DCs has been proven to be a promising strategy for treating T1D in NOD mice. Previously, DEC-205 was used to supply an IGRP206–214 mimotope to DCs to investigate its impact on highly diabetogenic T cells in NOD mice [134]. This study showed that IGRP206–214-loaded DCs significantly reduced the percentage and absolute number of diabetogenic IGRP-specific CD8+ T cells in pancreatic islets independently of the PD-1/PD-L1 pathway, resulting in the protection against T1D. In a recent study, ~1 µm phagocytosable polylactic acid-glycolic acid ethanol (PLGA) microparticles (MPs) (Figure 3) were used to deliver tolerance-promoting factors such as vitamin D3, TGF-β1, GM-CSF, and T1D-specific autoantigen insulin to DCs to reprogram autoimmune responses and prevent autoimmunity [135]. This MP system successfully prevented 60% of prediabetic NOD mice from developing T1D by increasing the number of tDCs and the Treg cell population. Similarly, in another recent study, a targeted nanoparticle delivery system was used to deliver the antigen heat shock protein 65-6 × P277 (H6P) directly to the intestinal DCs of NOD mice through oral vaccination. This delivery system facilitated increased H6P uptake by DCs in gut Peyer’s patches and promoted the induction of the Th2 immune response and Treg upregulation, resulting in full protection from diabetes [136]. 7.4. Ex Vivo Generation of Tolerogenic DC Various methods aimed at controlling DC phenotypes have been explored to ensure that they retain a tolerogenic function and drive tolerance rather than immunity (reviewed previously [137]). These methods include challenging DCs with cytokines such as IL-10 [138], IL-10/TGF-β [139], TSLP [140], GM-CSF [141], pharmacological agents such as dexamethasone and vitamin D3 [142], carbon monoxide (CO) [143], anti-CTLA-4 antibody [144], and secretory IgA [145], among others. Generally, treating DCs with these agents results in an immature or semimature phenotype characterized by lowered expression of costimulatory molecules, and reduced production of inflammatory cytokines. These tolerogenic DCs secrete anti-inflammatory cytokines, like IL-10 and TGF-β, and a metabolite called IDO that inhibits effector T cell activation and DC maturation. They are also involved in the induction of the Treg differentiation (Figure 4). We previously reported that, in comparison with immunogenic BMDCs generated with GM-CSF and IL-4 (IL-4/DCs), BMDCs generated with GM-CSF (GM/DCs) acquire the signature of tolerogenic IL-10-producing DCs [146]. These GM/DC populations display an immature phenotype with a slight upregulation in CD80 but not CD86, CD40, or MHC-II expression and produce high levels of IL-10 and lower amounts of IL-12p70. GM/DCs also show a diminished ability to trigger diabetogenic CD8+ T cells to proliferate and effectively induce Treg conversion and expansion. Further research from our laboratory showed that, compared with immunogenic IL-4/DCs, the tolerogenic GM/DC subset alters the cytokine environment from Th1 toward Th2 cytokines and effectively prevents diabetes when injected into NOD mice [146,147,148]. In line with these results, we further confirmed, through in vitro studies, that NOD DCs genetically modified to express the active form of the Stat5b TF that mediates GM-CSF/GM-CSFR signaling acquire the signature of tolerogenic DCs [149,150]. These tolerogenic DCs were shown to be efficient at providing protection against T1D through an increase in the Treg pool and suppressive activity as well as through the promotion of Th2 and Tc2 immune responses. Tolerogenic DCs have also been used in vitro to expand Treg cells, which can be adoptively transferred into patients to suppress or prevent inflammatory responses and autoimmunity. Tregs constitutively expresses the surface marker CTLA-4, which can interact with the DC costimulatory molecules CD80 and CD86 to block the CD28-dependent activation of effector T cells and activate the DC expression of IDO, TGF-β, and IL-10 (Figure 4), thereby further strengthening the tolerogenic phenotype of DCs [151]. Another approach using tolerogenic DCs for the prevention/treatment of T1D is to use antisense oligonucleotides to downregulate costimulatory molecule expression (CD40, CD80, and CD86) in DCs [152]. This approach has been found to substantially delay the onset of diabetes in NOD mice by increasing the concentration of Tregs [152]. Based on these encouraging data, a phase 1 clinical trial was initiated, which demonstrated the safety and tolerability of these tailored tolerogenic DCs in established T1D patients [153] (Table 2). A phase II follow-up clinical trial (ClinicalTrials.gov identifier NCT02354911) is currently underway that uses tolerogenic DCs isolated from patients with newly diagnosed T1D. A similar ongoing clinical study (ClinicalTrials.gov identifier NCT01947569) using tDCs with impaired costimulation has also been registered. ijms-23-04885-t002_Table 2 Table 2 Summary of the clinical trials mentioned in the text. NCT Number Recruitment Status Study Date Completion Date Groups Outcomes Reference NCT00505375 Completed February 2008 May 2012 Interventional At the end of the treatment, patients receiving abatacept showed significant C-peptide preservation compared with the placebo group (59% higher, p = 0.0029) at 24 months. However, after 6 months, C-peptide preservation declined to the placebo level, despite continuous treatment for 2 years. [106,107,108,109] NCT03929601 Suspended February 2020 Ongoing Interventional Result not published. NCT00645840 Completed March 2008 September 2009 Interventional Anakinra-treated patients had similar glycated hemoglobin and MMTT responses but lower insulin requirements 1 and 4 months after diagnosis compared with controls and lower insulin-dose-adjusted glycated hemoglobin 1 month after diagnosis. [116,117] NCT00730392 Completed October 2002 January 2008 Interventional Treatment of pediatric patients newly diagnosed with type 1 diabetes with etanercept resulted in lower glycated hemoglobin and increased endogenous insulin production, suggesting the preservation of beta-cell function. [123] NCT02293837 Completed March 2015 August 2020 Interventional Tocilizumab reduced T cell IL-6R signaling but did not modulate CD4+ T cell phenotypes or slow the loss of residual β cell function in newly diagnosed individuals with type 1 diabetes. [127] NCT02117765 Unknown March 2015 June 2017 Interventional Ustekinumab was deemed safe to progress to efficacy studies at doses used to treat psoriasis in adults with T1D. A 90 mg maintenance dosing schedule reduced proinsulin-specific IFN-γ and IL-17A-producing T cells. Further studies are warranted to determine whether Ustekinumab can prevent C-peptide AUC decline and induce a clinical response. [132] NCT00445913 Completed March 2007 February 2016 Interventional Treatment with autologous dendritic cells in a native state or directed ex vivo toward a tolerogenic immunosuppressive state is safe and well-tolerated. Dendritic cells upregulated the frequency of a potentially beneficial B220+ CD11c2 B-cell population, at least in type 1 diabetes autoimmunity. [153] NCT02354911 Unknown October 2015 January 2019 Interventional Result not published NCT01947569 Unknown October 2013 November 2013 Interventional Result not published NCT04590872 Recruiting April 2022 Ongoing Interventional Result not published Previously, it was shown that naturally derived proinsulin peptide C19-A3 is safe and capable of eliciting the immunoregulatory responses, such as the stimulation of IL-10 production and the increase of Tregs Foxp3 expression in type 1 diabetic patients [154]. Further studies showed that tolDCs presenting this peptide can induce proinsulin-specific regulatory T cells [155]. Based on these exciting outcomes, a phase 1 clinical trial was conducted in the Netherlands to assess the clinical safety and feasibility of proinsulin peptide-loaded tolDCs in nine patients with longstanding type 1 diabetes [156]. After tolDC therapy, all patients maintained tight glycemic control with constant HbA 1c levels and unaltered insulin needs. Most importantly, there was no induction of allergic reaction to insulin, no signs of systemic immune suppression, and no interference with insulin therapy, suggesting that this immune intervention therapy is feasible and safe. A complementary phase 1 follow-up clinical trial will also be conducted in the United States to investigate its therapeutic potential and side effects in T1D patients who use insulin and have no other diabetes-related health complications (Clinicaltrials.gov identifier: NCT04590872). 8. Future Views and Concluding Remarks Given the exclusive nature of DCs found at the interface between innate and adaptive immune responses, they provide target cells for clinical intervention in T1D patients. Diverse DC subtypes use different transcription factors [157] so that these DC subtypes can be embattled differently for immunomodulation. One can think of the possibility of combining tDCs and Tregs as coimmunization or the serial administration of cellular immunotherapy in autoimmunity, especially in newly onset T1D. The use of autologous tDCs in conjunction with patient Tregs can stabilize Foxp3 expression and its genomic locus. Because tDCs are often seen to release IL-10, TGF-β, and retinoic acid [158,159], stable Tregs will, in turn, affect the tDC tolerance status through intercellular interactions and paracrine immunomodulatory cytokines, which may result in much more effective and long-term protection from diabetes. Moreover, in cancer research, the area of DC-based vaccines is much more advanced, and several clinical studies have already been carried out. Many characteristics of cancer DC vaccines have been investigated, and it is obvious that features, such as the conditioning regime of DCs, the antigen form used to pulse DCs, and the means of administration all play vital roles in defining the end result of DC-based therapy. These features need to be considered as more DC-based therapies for T1D treatment are proposed. Several clinical trials have been conducted to induce antigen-specific tolerance in T1D patients [160]. These trials employ islet-specific antigens, for example, GAD65, insulin, or hsp70, and have tested multiple administration routes, such as oral, intranasal, and intradermal administration. To date, despite the evidence of immune tolerance observed in some cases, these trials have not had a significant impact on the disease [160]. It is predicted that the success of these trials will depend on APCs, most likely DCs, targeted by these antigen formulations. At present, in these trials, less attention has been given to the nature of antigen-presenting DCs; therefore, a deeper understanding of how DCs affect the development of T1D will aid in the advancement of novel therapeutic approaches. Acknowledgments Farhan Ullah Khan is a recipient of a scholarship from the Centre de Recherche Médicale de l’Université de Sherbrooke (CRMUS). Puregmaa Khongorzul is a recipient of a scholarship from the programme de bourses aux etudes superieures du CRCHUS-Hors FMSS. Author Contributions F.U.K., P.K., A.A.R. and A.R. retrieved the literature and drafted the paper. D.G. and A.A. conceived the idea and critically revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors have no relevant financial or non-financial interests to disclose. Figure 1 Ontogeny of functionally specialized dendritic cell subsets. Dendritic cells (DCs) originate from hematopoietic stem cells (HSCs) in the bone marrow (BM) that transit into lymphoid-primed multipotent progenitors (LMPPs). LMPPs differentiate into common myeloid progenitors (CMPs) and common lymphoid progenitors (CLPs). CMPs then branch into common DC progenitors (CDPs), which give rise to plasmacytoid DCs (pDCs), a major producer of type I interferons, and conventional DC (cDCs), whose primary function is to prime naïve T cells into common monocyte progenitors (CMoPs), which are committed to the monocyte, macrophage, and Langerhans cell (LC) lineages. CLPs give rise to pDCs and lymphocytes, such as T cells, B cells, and NK cells. A distinct macrophage lineage is derived from embryonic precursors and mainly generates tissue-resident macrophages and Langerhans cells, which can also be replaced over time by bone marrow monocyte-derived macrophages in different tissues, especially under inflammatory conditions. Tissue-resident macrophages maintain tissue homeostasis and are poor inducers of naïve T cells but are potent activators of B cells and are efficient at clearing apoptotic cells. Although LCs are categorized with macrophages on an ontogeny basis, they display many functional activities that overlap with cDCs. Monocyte-derived DCs (MoDCs), also known as inflammatory DCs (iDCs), are potent producers of TNF/iNOS (TIP) and are prominent at the site of inflammation. They typically execute functions in the tissues, such as antigen presentation to T effector cells, eradication of pathogens, and cytokine production. Stages at which key growth factors have been determined to be essential are indicated. MDP, macrophage and DC progenitor; Pre-pDC, pre-plasmacytoid DC; Pre-cDC, pre-conventional DC; cDC1, conventional type I DC; cDC2, conventional type II DC; GM-CSF, granulocyte-macrophage colony-stimulating factor; M-CSF, macrophage colony-stimulating factor; FLT3-L, Fms-like tyrosine kinase 3 ligand. Figure 2 The classical scheme of different dendritic cell states in T cell tolerance and immunity. Dendritic cells (DCs) in the steady-state, i.e., in the absence of microbial or inflammatory signals, are immature and can internalize exogenous antigens and process them for MHC class-II-mediated presentation. However, they are devoid of strong upregulation of costimulatory molecules (CD80, CD86), MHC-class II, and proinflammatory cytokines; therefore, they cannot prime immune responses. Partial maturation results in elevated levels of costimulatory molecules and MHC-class II, but a lack or reduced level of proinflammatory cytokines gives rise to a DC population called semi-mature DCs. This population of DCs can be induced by lactobacilli from the gut flora, apoptotic cells, IL-6, or TNF-α. Both immature and semimature DCs prompt T-cell immune tolerance. Full DC maturation can be induced by extraneous factors, such as microbial or inflammatory signals, leading to downregulation of antigen acquisition and the antigen-processing ability, increased expression of CD80, CD86, and MHC-class II, and elevated levels of proinflammatory cytokines. All of these events result in T-cell priming and an increase in immunogenicity. TNF-α, tumor necrosis factor-alpha; IL-6, interleukin-6; MHC, major histocompatibility complex; PAMPS, pathogen-associated molecular patterns; DAMPS, damage-associated molecular patterns; CCR7, C-C chemokine receptor type 7. Figure 3 Dendritic-cell-targeted therapies for treating type 1 diabetes. Therapies targeting dendritic cells support the tolerogenic potential of dendritic cells. DCs can be made tolerogenic by targeted delivery of self-antigens by coupling them to antibodies raised against specific dendritic cell receptors, such as the DEC-205, or by targeted delivery via microparticles. Other potential therapeutic strategies aim to limit the immunogenicity of DCs by impeding their production of inflammatory cytokines or by reducing their expression levels of costimulatory molecules and, therefore, the induction of effector T cell responses. Most of these approaches implicate the usage of monoclonal antibodies, which target molecules that are selectively expressed by DCs. DEC-205, decalectin-205; MHC, major histocompatibility; TCR, T cell receptor; Tregs, regulatory T cells; Teff, T effector cells; IL, interleukin; TNF-α, tumor necrosis factor-alpha. Figure 4 Schematic representation of dendritic cells and regulatory T cell interactions. Immature/semimature DCs secrete IDO impeding DC maturation as well as anti-inflammatory cytokines, such as IL-10 and TGF-β, inhibiting effector T cell activation. Immature/semimature DCs also give rise to Tregs, which contribute to immune tolerance by blocking the priming of effector T cells directly via IL-10 and TGF- β or indirectly through interactions with DCs and by blocking their maturation with the help of CTLA-4. CTLA-4 expressed on Treg has a higher affinity for CD80/86 molecules expressed on DCs than CD28 molecules expressed on effector T cells, meaning that Tregs competes with the effector T cells to bind CD80/CD86. DC CD80/CD86 and Treg-CTLA-4 interaction also results in the secretion of IL-10 and IDO, which contributes to the restraint of DC maturation. Treg can also preferentially sequester the T-cell proliferation factor IL-2 due to the high expression of constitutive IL-2R (CD25). The dotted line is used to emphasize that some differentiated Tregs use the above mechanisms to suppress effector T cells activation and balance immunity and tolerance. Tregs, regulatory T cells; IL-10, interleukin-10; TGF-β, tumor growth factor-beta; IDO, Indoleamine 2,3-dioxygenase. ijms-23-04885-t001_Table 1 Table 1 Phenotypic markers of dendritic cell subsets. DC Subset DC Type Human Mouse Transcriptional TLR Antigen Major Markers Markers Factors Presentation Cytokines pDC Lymphoid- CD123+ CD11b− TCF4 1, 2, 4 Poor Type I IFN resident DC CD303+ CD11c+ IRF8 6, 7, 8, 9 CD304+ CD45RA+ E2.2 ILT3+ SIGLEC-H+ ILT7+ CD8α+ DR6 CCR7+ cDC1 Lymphoid- CD141+ CD11b− BATF3 1, 2, 3, 4 Cross presentation L-12p70 resident DC Clec9a+ CD11c+ IRF8 6, 8, 9, 10 on MHC-class I IFN-λ CADM1+ CD103+ ID2 CXR1+ CD45RA− NFIL3 BTLA+ CD8α+ CD11b− CXR1+ cDC2 Migratory DC CD11b+ CD11b+ IRF4 2, 4, 5 Presentation on ? CD11c+ CD11c+ PU.1 6, 7, 8, 9 MHC-class II CD1c+ CD45RA− Notch2 SIRPα+ SIRPα+ Clec4a+ CD4+ Clec10a+ CD8α− CX3CR1+ CX3CR1+ Monocyte- Induced by CD11c+ CD11b+ KLF4 1, 2, 3 Cross presentation TNF/iNOS derived DC inflammation CD1a+ CD11c+ IRF8 4, 5,7, 8 CD1c+ LY6C+ PU.1 SIRPα+ CD8α− CD206+ CCR2+ Langerhans Migratory DC CD1a+ CD11b+ ID2 1, 2, 3 Presentation of IL-10 cells CD207+ CD45RA− RUNX3 5, 6, 10 self-antigens for CD123+ CD8α− β-catenin tolerance induction TROP2+ CXCL10+ DC, dendritic cell; TLR, toll-like receptor; pDC, plasmacytoid DC; ILT3, Immunoglobulin-like transcript 3; DR6, Death receptor 6; SIGLEC-H, sialic acid-binding immunoglobulin-like lectin H; CCR7, C-C motif chemokine receptor 7; TCF4, transcription factor 4, IRF8, interferon regulatory factor 8; IFN, interferon; cDC1, conventional DC1; clec9a, C-type lectin-like receptor member (Clec) 9a; CADM1, Cell adhesion molecule 1 gene; CXR1, CX- chemokine receptor 1; BTLA, B- and T-lymphocyte attenuator; BATF3, basic leucine zipper transcription factor ATF-like 3; ID2, DNA binding protein inhibitor 2; NFIL3, nuclear factor interleukin 3 regulatory protein; MHC, major histocompatibility complex; IL-12, interleukin 12, cDC2, conventional DC2; SIRPα, signal regulatory protein alpha; CX3CR1, CX3C- chemokine receptor 1; Notch2, neurogenic locus notch homolog protein 2; KLF4, kruppel-like factor 4; TNF/iNOS, tumor necrosis factor/induced nitric oxide synthase; TROP2, Trophoblast cell surface antigen 2; CXCL10, C-X-C motif chemokine ligand 10; ID2, Inhibitor of DNA binding 2; RUNX3, RUNX family transcription factor 3. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Patterson C. Guariguata L. Dahlquist G. Soltész G. Ogle G. Silink M. Diabetes in the young—A global view and worldwide estimates of numbers of children with type 1 diabetes Diabetes Res. Clin. Pract. 2014 103 161 175 10.1016/j.diabres.2013.11.005 24331235 2. Maahs D.M. West N.A. Lawrence J.M. Mayer-Davis E.J. Epidemiology of type 1 diabetes Endocrinol. Metab. Clin. N. Am. 2010 39 481 497 10.1016/j.ecl.2010.05.011 20723815 3. Patterson C.C. Karuranga S. Salpea P. Saeedi P. Dahlquist G. Soltesz G. Ogle G.D. Worldwide estimates of incidence, prevalence and mortality of type 1 diabetes in children and adolescents: Results from the International Diabetes Federation Diabetes Atlas, 9th edition Diabetes Res. Clin. Pract. 2019 157 107842 10.1016/j.diabres.2019.107842 31518658 4. Ilonen J. Lempainen J. Veijola R. The heterogeneous pathogenesis of type 1 diabetes mellitus Nat. Rev. Endocrinol. 2019 15 635 650 10.1038/s41574-019-0254-y 31534209 5. Gianchecchi E. Palombi M. Fierabracci A. The putative role of the C1858T polymorphism of protein tyrosine phosphatase PTPN22 gene in autoimmunity Autoimmun. Rev. 2013 12 717 725 10.1016/j.autrev.2012.12.003 23261816 6. Robertson C.C. Rich S.S. Genetics of type 1 diabetes Curr. Opin. Genet. Dev. 2018 50 7 16 10.1016/j.gde.2018.01.006 29453110 7. Schraml B.U. Reis e Sousa C. Defining dendritic cells Curr. Opin. Immunol. 2015 32 13 20 10.1016/j.coi.2014.11.001 25553392 8. Münz C. Steinman R.M. Fujii S. Dendritic cell maturation by innate lymphocytes: Coordinated stimulation of innate and adaptive immunity J. Exp. Med. 2005 202 203 207 10.1084/jem.20050810 16027234 9. Halim T.Y.F. Hwang Y.Y. Scanlon S.T. Zaghouani H. Garbi N. Fallon P.G. McKenzie A.N.J. Group 2 innate lymphoid cells license dendritic cells to potentiate memory TH2 cell responses Nat. Immunol. 2016 17 57 64 10.1038/ni.3294 26523868 10. Schmid M. Wege A.K. Ritter U. Characteristics of ‘Tip-DCs and MDSCs’ and Their Potential Role in Leishmaniasis Front. Microbiol. 2012 3 74 10.3389/fmicb.2012.00074 22416241 11. Heath W.R. Carbone F.R. Dendritic cell subsets in primary and secondary T cell responses at body surfaces Nat. Immunol. 2009 10 1237 1244 10.1038/ni.1822 19915624 12. Fucikova J. Palova-Jelinkova L. Bartunkova J. Spisek R. Induction of Tolerance and Immunity by Dendritic Cells: Mechanisms and Clinical Applications Front. Immunol. 2019 10 2393 10.3389/fimmu.2019.02393 31736936 13. Auffray C. Fogg D.K. Narni-Mancinelli E. Senechal B. Trouillet C. Saederup N. Leemput J. Bigot K. Campisi L. Abitbol M. CX3CR1+ CD115+ CD135+ common macrophage/DC precursors and the role of CX3CR1 in their response to inflammation J. Exp. Med. 2009 206 595 606 10.1084/jem.20081385 19273628 14. Waskow C. Liu K. Darrasse-Jèze G. Guermonprez P. Ginhoux F. Merad M. Shengelia T. Yao K. Nussenzweig M. The receptor tyrosine kinase Flt3 is required for dendritic cell development in peripheral lymphoid tissues Nat. Immunol. 2008 9 676 683 10.1038/ni.1615 18469816 15. Hettinger J. Richards D.M. Hansson J. Barra M.M. Joschko A.-C. Krijgsveld J. Feuerer M. Origin of monocytes and macrophages in a committed progenitor Nat. Immunol. 2013 14 821 830 10.1038/ni.2638 23812096 16. Meredith M.M. Liu K. Darrasse-Jeze G. Kamphorst A.O. Schreiber H.A. Guermonprez P. Idoyaga J. Cheong C. Yao K.H. Niec R.E. Expression of the zinc finger transcription factor zDC (Zbtb46, Btbd4) defines the classical dendritic cell lineage J. Exp. Med. 2012 209 1153 1165 10.1084/jem.20112675 22615130 17. Cisse B. Caton M.L. Lehner M. Maeda T. Scheu S. Locksley R. Holmberg D. Zweier C. den Hollander N.S. Kant S.G. Transcription factor E2-2 is an essential and specific regulator of plasmacytoid dendritic cell development Cell 2008 135 37 48 10.1016/j.cell.2008.09.016 18854153 18. Merad M. Sathe P. Helft J. Miller J. Mortha A. The dendritic cell lineage: Ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting Annu. Rev. Immunol. 2013 31 563 604 10.1146/annurev-immunol-020711-074950 23516985 19. Schlitzer A. McGovern N. Teo P. Zelante T. Atarashi K. Low D. Ho A.W.S. See P. Shin A. Wasan P.S. IRF4 transcription factor-dependent CD11b+ dendritic cells in human and mouse control mucosal IL-17 cytokine responses Immunity 2013 38 970 983 10.1016/j.immuni.2013.04.011 23706669 20. Sichien D. Scott C.L. Martens L. Vanderkerken M. Van Gassen S. Plantinga M. Joeris T. De Prijck S. Vanhoutte L. Vanheerswynghels M. IRF8 Transcription Factor Controls Survival and Function of Terminally Differentiated Conventional and Plasmacytoid Dendritic Cells, Respectively Immunity 2016 45 626 640 10.1016/j.immuni.2016.08.013 27637148 21. Besin G. Gaudreau S. Dumont-Blanchette E. Ménard M. Guindi C. Dupuis G. Amrani A. IFN regulatory factors 4 and 8 expression in the NOD mouse Clin. Dev. Immunol. 2011 2011 374859 10.1155/2011/374859 21647406 22. Perié L. Naik S.H. Toward defining a ‘lineage’—The case for dendritic cells Semin. Cell Dev. Biol. 2015 41 3 8 10.1016/j.semcdb.2015.02.004 25701440 23. Naik S.H. Proietto A.I. Wilson N.S. Dakic A. Schnorrer P. Fuchsberger M. Lahoud M.H. O’Keeffe M. Shao Q.X. Chen W.F. Cutting edge: Generation of splenic CD8+ and CD8− dendritic cell equivalents in Fms-like tyrosine kinase 3 ligand bone marrow cultures J. Immunol. 2005 174 6592 6597 10.4049/jimmunol.174.11.6592 15905497 24. Kirkling M.E. Cytlak U. Lau C.M. Lewis K.L. Resteu A. Khodadadi-Jamayran A. Siebel C.W. Salmon H. Merad M. Tsirigos A. Notch Signaling Facilitates In Vitro Generation of Cross-Presenting Classical Dendritic Cells Cell Rep. 2018 23 3658 3672.e6 10.1016/j.celrep.2018.05.068 29925006 25. Nobs S.P. Schneider C. Dietrich M.G. Brocker T. Rolink A. Hirsch E. Kopf M. PI3-Kinase-γ Has a Distinct and Essential Role in Lung-Specific Dendritic Cell Development Immunity 2015 43 674 689 10.1016/j.immuni.2015.09.006 26453378 26. McKenna H.J. Stocking K.L. Miller R.E. Brasel K. De Smedt T. Maraskovsky E. Maliszewski C.R. Lynch D.H. Smith J. Pulendran B. Mice lacking flt3 ligand have deficient hematopoiesis affecting hematopoietic progenitor cells, dendritic cells, and natural killer cells Blood 2000 95 3489 3497 10.1182/blood.V95.11.3489 10828034 27. Whartenby K.A. Calabresi P.A. McCadden E. Nguyen B. Kardian D. Wang T. Mosse C. Pardoll D.M. Small D. Inhibition of FLT3 signaling targets DCs to ameliorate autoimmune disease Proc. Natl. Acad. Sci. USA 2005 102 16741 16746 10.1073/pnas.0506088102 16272221 28. Edelson B.T. Bradstreet T.R. Kc W. Hildner K. Herzog J.W. Sim J. Russell J.H. Murphy T.L. Unanue E.R. Murphy K.M. Batf3-Dependent CD11b low/− Peripheral Dendritic Cells Are GM-CSF-Independent and Are Not Required for Th Cell Priming after Subcutaneous Immunization PLoS ONE 2011 6 e25660 10.1371/journal.pone.0025660 22065991 29. Bogunovic M. Ginhoux F. Helft J. Shang L. Hashimoto D. Greter M. Liu K. Jakubzick C. Ingersoll M.A. Leboeuf M. Origin of the lamina propria dendritic cell network Immunity 2009 31 513 525 10.1016/j.immuni.2009.08.010 19733489 30. Esashi E. Wang Y.H. Perng O. Qin X.F. Liu Y.J. Watowich S.S. The signal transducer STAT5 inhibits plasmacytoid dendritic cell development by suppressing transcription factor IRF8 Immunity 2008 28 509 520 10.1016/j.immuni.2008.02.013 18342552 31. Geissmann F. Manz M.G. Jung S. Sieweke M.H. Merad M. Ley K. Development of monocytes, macrophages, and dendritic cells Science 2010 327 656 661 10.1126/science.1178331 20133564 32. Onai N. Obata-Onai A. Schmid M.A. Ohteki T. Jarrossay D. Manz M.G. Identification of clonogenic common Flt3+M-CSFR+ plasmacytoid and conventional dendritic cell progenitors in mouse bone marrow Nat. Immunol. 2007 8 1207 1216 10.1038/ni1518 17922016 33. Ginhoux F. Liu K. Helft J. Bogunovic M. Greter M. Hashimoto D. Price J. Yin N. Bromberg J. Lira S.A. The origin and development of nonlymphoid tissue CD103+ DCs J. Exp. Med. 2009 206 3115 3130 10.1084/jem.20091756 20008528 34. Villadangos J.A. Schnorrer P. Intrinsic and cooperative antigen-presenting functions of dendritic-cell subsets in vivo Nat. Rev. Immunol. 2007 7 543 555 10.1038/nri2103 17589544 35. Satpathy A.T. Wu X. Albring J.C. Murphy K.M. Re(de)fining the dendritic cell lineage Nat. Immunol. 2012 13 1145 1154 10.1038/ni.2467 23160217 36. Morel P.A. Dendritic cell subsets in type 1 diabetes: Friend or foe? Front. Immunol. 2013 4 415 10.3389/fimmu.2013.00415 24367363 37. Sichien D. Lambrecht B.N. Guilliams M. Scott C.L. Development of conventional dendritic cells: From common bone marrow progenitors to multiple subsets in peripheral tissues Mucosal Immunol. 2017 10 831 844 10.1038/mi.2017.8 28198365 38. Anderson D.A. Dutertre C.-A. Ginhoux F. Murphy K.M. Genetic models of human and mouse dendritic cell development and function Nat. Rev. Immunol. 2021 21 101 115 10.1038/s41577-020-00413-x 32908299 39. Moberg C.L. An appreciation of Ralph Marvin Steinman (1943–2011) J. Exp. Med. 2011 208 2337 2342 10.1084/jem.20112294 22216460 40. Chang S.-Y. Ko H.-J. Kweon M.-N. Mucosal dendritic cells shape mucosal immunity Exp. Mol. Med. 2014 46 e84 10.1038/emm.2014.16 24626170 41. Shortman K. Liu Y.J. Mouse and human dendritic cell subtypes Nat. Rev. Immunol. 2002 2 151 161 10.1038/nri746 11913066 42. Dudek A. Martin S. Garg A. Agostinis P. Immature, Semi-Mature, and Fully Mature Dendritic Cells: Toward a DC-Cancer Cells Interface That Augments Anticancer Immunity Front. Immunol. 2013 4 438 10.3389/fimmu.2013.00438 24376443 43. Comabella M. Montalban X. Münz C. Lünemann J.D. Targeting dendritic cells to treat multiple sclerosis Nat. Rev. Neurol. 2010 6 499 507 10.1038/nrneurol.2010.112 20717105 44. Watarai H. Hinohara A. Nagafune J. Nakayama T. Taniguchi M. Yamaguchi Y. Plasma membrane-focused proteomics: Dramatic changes in surface expression during the maturation of human dendritic cells Proteomics 2005 5 4001 4011 10.1002/pmic.200401258 16152658 45. Embgenbroich M. Burgdorf S. Current Concepts of Antigen Cross-Presentation Front. Immunol. 2018 9 1643 10.3389/fimmu.2018.01643 30061897 46. Jang J.-H. Shin H.W. Lee J.M. Lee H.-W. Kim E.-C. Park S.H. An Overview of Pathogen Recognition Receptors for Innate Immunity in Dental Pulp Mediat. Inflamm. 2015 2015 794143 10.1155/2015/794143 47. Kelly R.M. Chen J. Yauch L.E. Levitz S.M. Opsonic requirements for dendritic cell-mediated responses to Cryptococcus neoformans Infect. Immun. 2005 73 592 598 10.1128/IAI.73.1.592-598.2005 15618199 48. Guilliams M. Bruhns P. Saeys Y. Hammad H. Lambrecht B.N. The function of Fcγ receptors in dendritic cells and macrophages Nat. Rev. Immunol. 2014 14 94 108 10.1038/nri3582 24445665 49. Hammer G.E. Ma A. Molecular control of steady-state dendritic cell maturation and immune homeostasis Annu. Rev. Immunol. 2013 31 743 791 10.1146/annurev-immunol-020711-074929 23330953 50. Audiger C. Rahman M.J. Yun T.J. Tarbell K.V. Lesage S. The Importance of Dendritic Cells in Maintaining Immune Tolerance J. Immunol. 2017 198 2223 2231 10.4049/jimmunol.1601629 28264998 51. Qin S. Xu L. Yi M. Yu S. Wu K. Luo S. Novel immune checkpoint targets: Moving beyond PD-1 and CTLA-4 Mol. Cancer 2019 18 155 10.1186/s12943-019-1091-2 31690319 52. Steimle A. Frick J.-S. Molecular Mechanisms of Induction of Tolerant and Tolerogenic Intestinal Dendritic Cells in Mice J. Immunol. Res. 2016 2016 1958650 10.1155/2016/1958650 26981546 53. Akbari O. DeKruyff R.H. Umetsu D.T. Pulmonary dendritic cells producing IL-10 mediate tolerance induced by respiratory exposure to antigen Nat. Immunol. 2001 2 725 731 10.1038/90667 11477409 54. Huang F.P. Platt N. Wykes M. Major J.R. Powell T.J. Jenkins C.D. MacPherson G.G. A discrete subpopulation of dendritic cells transports apoptotic intestinal epithelial cells to T cell areas of mesenteric lymph nodes J. Exp. Med. 2000 191 435 444 10.1084/jem.191.3.435 10662789 55. Verginis P. Li H.S. Carayanniotis G. Tolerogenic semimature dendritic cells suppress experimental autoimmune thyroiditis by activation of thyroglobulin-specific CD4+CD25+ T cells J. Immunol. 2005 174 7433 7439 10.4049/jimmunol.174.11.7433 15905592 56. Frick J.S. Zahir N. Müller M. Kahl F. Bechtold O. Lutz M.B. Kirschning C.J. Reimann J. Jilge B. Bohn E. Colitogenic and non-colitogenic commensal bacteria differentially trigger DC maturation and Th cell polarization: An important role for IL-6 Eur. J. Immunol. 2006 36 1537 1547 10.1002/eji.200635840 16708404 57. Jaen O. Rullé S. Bessis N. Zago A. Boissier M.-C. Falgarone G. Dendritic cells modulated by innate immunity improve collagen-induced arthritis and induce regulatory T cells in vivo Immunology 2009 126 35 44 10.1111/j.1365-2567.2008.02875.x 18754812 58. Yang X.J. Meng S. Zhu C.F. Jiang H. Wu W.X. Semi-mature MyD88-silenced bone marrow dendritic cells prolong the allograft survival in a rat model of intestinal transplantation Chin. Med. J. 2011 124 268 272 21362379 59. Sabado R.L. Balan S. Bhardwaj N. Dendritic cell-based immunotherapy Cell Res. 2017 27 74 95 10.1038/cr.2016.157 28025976 60. Sia J.K. Bizzell E. Madan-Lala R. Rengarajan J. Engaging the CD40-CD40L pathway augments T-helper cell responses and improves control of Mycobacterium tuberculosis infection PLoS Pathog. 2017 13 e1006530 10.1371/journal.ppat.1006530 28767735 61. Curato C. Bernshtein B. Zupancič E. Dufner A. Jaitin D. Giladi A. David E. Chappell-Maor L. Leshkowitz D. Knobeloch K.-P. DC Respond to Cognate T Cell Interaction in the Antigen-Challenged Lymph Node Front. Immunol. 2019 10 863 10.3389/fimmu.2019.00863 31073301 62. Tong C. Cui Z. Sun X. Lei L. Feng X. Sun C. Gu J. Han W. Mannan Derivatives Instruct Dendritic Cells to Induce Th1/Th2 Cells Polarization via Differential Mitogen-Activated Protein Kinase Activation Scand. J. Immunol. 2016 83 10 17 10.1111/sji.12369 26332129 63. Kim B. Kim T.H. Fundamental role of dendritic cells in inducing Th2 responses Korean J. Intern. Med. 2018 33 483 489 10.3904/kjim.2016.227 29502361 64. Agalioti T. Villablanca E.J. Huber S. Gagliani N. TH17 cell plasticity: The role of dendritic cells and molecular mechanisms J. Autoimmun. 2018 87 50 60 10.1016/j.jaut.2017.12.003 29371049 65. Eisenbarth S.C. Dendritic cell subsets in T cell programming: Location dictates function Nat. Rev. Immunol. 2019 19 89 103 10.1038/s41577-018-0088-1 30464294 66. Wculek S.K. Khouili S.C. Priego E. Heras-Murillo I. Sancho D. Metabolic Control of Dendritic Cell Functions: Digesting Information Front. Immunol. 2019 10 775 10.3389/fimmu.2019.00775 31073300 67. Pearce E.J. Everts B. Dendritic cell metabolism Nat. Reviews. Immunol. 2015 15 18 29 10.1038/nri3771 68. Hanley T.M. Blay Puryear W. Gummuluru S. Viglianti G.A. PPARgamma and LXR signaling inhibit dendritic cell-mediated HIV-1 capture and trans-infection PLoS Pathog. 2010 6 e1000981 10.1371/journal.ppat.1000981 20617179 69. Kratchmarov R. Viragova S. Kim M.J. Rothman N.J. Liu K. Reizis B. Reiner S.L. Metabolic control of cell fate bifurcations in a hematopoietic progenitor population Immunol. Cell Biol. 2018 96 863 871 10.1111/imcb.12040 29570858 70. Du X. Wen J. Wang Y. Karmaus P.W.F. Khatamian A. Tan H. Li Y. Guy C. Nguyen T.M. Dhungana Y. Hippo/Mst signalling couples metabolic state and immune function of CD8α+ dendritic cells Nature 2018 558 141 145 10.1038/s41586-018-0177-0 29849151 71. Wang Y. Huang G. Zeng H. Yang K. Lamb R.F. Chi H. Tuberous sclerosis 1 (Tsc1)-dependent metabolic checkpoint controls development of dendritic cells Proc. Natl. Acad. Sci. USA 2013 110 E4894 E4903 10.1073/pnas.1308905110 24282297 72. Moore K.W. de Waal Malefyt R. Coffman R.L. O’Garra A. Interleukin-10 and the interleukin-10 receptor Annu. Rev. Immunol. 2001 19 683 765 10.1146/annurev.immunol.19.1.683 11244051 73. Mascanfroni I.D. Yeste A. Vieira S.M. Burns E.J. Patel B. Sloma I. Wu Y. Mayo L. Ben-Hamo R. Efroni S. IL-27 acts on DCs to suppress the T cell response and autoimmunity by inducing expression of the immunoregulatory molecule CD39 Nat. Immunol. 2013 14 1054 1063 10.1038/ni.2695 23995234 74. Sim W.J. Ahl P.J. Connolly J.E. Metabolism Is Central to Tolerogenic Dendritic Cell Function Mediat. Inflamm. 2016 2016 2636701 10.1155/2016/2636701 26980944 75. Malinarich F. Duan K. Hamid R.A. Bijin A. Lin W.X. Poidinger M. Fairhurst A.M. Connolly J.E. High mitochondrial respiration and glycolytic capacity represent a metabolic phenotype of human tolerogenic dendritic cells J. Immunol. 2015 194 5174 5186 10.4049/jimmunol.1303316 25917094 76. Krawczyk C.M. Holowka T. Sun J. Blagih J. Amiel E. DeBerardinis R.J. Cross J.R. Jung E. Thompson C.B. Jones R.G. Toll-like receptor-induced changes in glycolytic metabolism regulate dendritic cell activation Blood 2010 115 4742 4749 10.1182/blood-2009-10-249540 20351312 77. Everts B. Amiel E. Huang S.C. Smith A.M. Chang C.H. Lam W.Y. Redmann V. Freitas T.C. Blagih J. van der Windt G.J. TLR-driven early glycolytic reprogramming via the kinases TBK1-IKKε supports the anabolic demands of dendritic cell activation Nat. Immunol. 2014 15 323 332 10.1038/ni.2833 24562310 78. Everts B. Pearce E.J. Metabolic control of dendritic cell activation and function: Recent advances and clinical implications Front. Immunol. 2014 5 203 10.3389/fimmu.2014.00203 24847328 79. Guak H. Al Habyan S. Ma E.H. Aldossary H. Al-Masri M. Won S.Y. Ying T. Fixman E.D. Jones R.G. McCaffrey L.M. Glycolytic metabolism is essential for CCR7 oligomerization and dendritic cell migration Nat. Commun. 2018 9 2463 10.1038/s41467-018-04804-6 29941886 80. Di Lorenzo T.P. Peakman M. Roep B.O. Translational mini-review series on type 1 diabetes: Systematic analysis of T cell epitopes in autoimmune diabetes Clin. Exp. Immunol. 2007 148 1 16 10.1111/j.1365-2249.2006.03244.x 17349009 81. Lehuen A. Diana J. Zaccone P. Cooke A. Immune cell crosstalk in type 1 diabetes Nat. Rev. Immunol. 2010 10 501 513 10.1038/nri2787 20577267 82. Amrani A. Verdaguer J. Thiessen S. Bou S. Santamaria P. IL-1alpha, IL-1beta, and IFN-gamma mark beta cells for Fas-dependent destruction by diabetogenic CD4+ T lymphocytes J. Clin. Investig. 2000 105 459 468 10.1172/JCI8185 10683375 83. Magnuson A.M. Thurber G.M. Kohler R.H. Weissleder R. Mathis D. Benoist C. Population dynamics of islet-infiltrating cells in autoimmune diabetes Proc. Natl. Acad. Sci. USA 2015 112 1511 1516 10.1073/pnas.1423769112 25605891 84. Hotta-Iwamura C. Tarbell K.V. Type 1 diabetes genetic susceptibility and dendritic cell function: Potential targets for treatment J. Leukoc. Biol. 2016 100 65 80 10.1189/jlb.3MR1115-500R 26792821 85. Creusot R.J. Postigo-Fernandez J. Teteloshvili N. Altered Function of Antigen-Presenting Cells in Type 1 Diabetes: A Challenge for Antigen-Specific Immunotherapy? Diabetes 2018 67 1481 1494 10.2337/db17-1564 30030289 86. Boldison J. Wong F.S. Immune and Pancreatic b Cell Interactions in Type 1 Diabetes Trends Endocrinol. Metab. 2016 27 856 867 10.1016/j.tem.2016.08.007 27659143 87. Unanue E.R. Ferris S.T. Carrero J.A. The role of islet antigen presenting cells and the presentation of insulin in the initiation of autoimmune diabetes in the NOD mouse Immunol. Rev. 2016 272 183 201 10.1111/imr.12430 27319351 88. Diana J. Simoni Y. Furio L. Beaudoin L. Agerberth B. Barrat F. Lehuen A. Crosstalk between neutrophils, B-1a cells and plasmacytoid dendritic cells initiates autoimmune diabetes Nat. Med. 2013 19 65 73 10.1038/nm.3042 23242473 89. Green E.A. Eynon E.E. Flavell R.A. Local Expression of TNFalpha in Neonatal NOD Mice Promotes Diabetes by Enhancing Presentation of Islet Antigens Immunity 1998 9 733 743 10.1016/S1074-7613(00)80670-6 9846494 90. Burke S.J. Lu D. Sparer T.E. Karlstad M.D. Collier J.J. Transcription of the gene encoding TNF-α is increased by IL-1β in rat and human islets and β-cell lines Mol. Immunol. 2014 62 54 62 10.1016/j.molimm.2014.05.019 24972324 91. Zóka A. Műzes G. Somogyi A. Varga T. Szémán B. Al-Aissa Z. Hadarits O. Firneisz G. Altered Immune Regulation in Type 1 Diabetes Clin. Dev. Immunol. 2013 2013 254874 10.1155/2013/254874 24285974 92. Klementowicz J.E. Mahne A.E. Spence A. Nguyen V. Satpathy A.T. Murphy K.M. Tang Q. Cutting Edge: Origins, Recruitment, and Regulation of CD11c+ Cells in Inflamed Islets of Autoimmune Diabetes Mice J. Immunol. 2017 199 27 32 10.4049/jimmunol.1601062 28550204 93. Sandor A.M. Jacobelli J. Friedman R.S. Immune cell trafficking to the islets during type 1 diabetes Clin. Exp. Immunol. 2019 198 314 325 10.1111/cei.13353 31343073 94. Wheat W. Kupfer R. Gutches D.G. Rayat G.R. Beilke J. Scheinman R.I. Wegmann D.R. Increased NF-kappa B activity in B cells and bone marrow-derived dendritic cells from NOD mice Eur. J. Immunol. 2004 34 1395 1404 10.1002/eji.200324490 15114673 95. Sen P. Bhattacharyya S. Wallet M. Wong C.P. Poligone B. Sen M. Baldwin A.S. Jr. Tisch R. NF-kappa B hyperactivation has differential effects on the APC function of nonobese diabetic mouse macrophages J. Immunol. 2003 170 1770 1780 10.4049/jimmunol.170.4.1770 12574341 96. Nikolic T. Bunk M. Drexhage H.A. Leenen P.J. Bone marrow precursors of nonobese diabetic mice develop into defective macrophage-like dendritic cells in vitro J. Immunol. 2004 173 4342 4351 10.4049/jimmunol.173.7.4342 15383563 97. Welzen-Coppens J.M. van Helden-Meeuwsen C.G. Drexhage H.A. Versnel M.A. Abnormalities of dendritic cell precursors in the pancreas of the NOD mouse model of diabetes Eur. J. Immunol. 2012 42 186 194 10.1002/eji.201141770 22002898 98. Burns S.O. Dendritic cell defects in primary immunodeficiency disorders LymphoSign J. 2015 3 1 12 10.14785/lpsn-2015-0001 99. Collin M. Bigley V. Haniffa M. Hambleton S. Human dendritic cell deficiency: The missing ID? Nat. Rev. Immunol. 2011 11 575 583 10.1038/nri3046 21852794 100. Casqueiro J. Casqueiro J. Alves C. Infections in patients with diabetes mellitus: A review of pathogenesis Indian J. Endocrinol. Metab. 2012 16 (Suppl. 1) S27 S36 10.4103/2230-8210.94253 22701840 101. Knapp S. Diabetes and Infection: Is There a Link?—A Mini-Review Gerontology 2013 59 99 104 10.1159/000345107 23182884 102. Cabello-Olmo M. Araña M. New Insights into Immunotherapy Strategies for Treating Autoimmune Diabetes Int. J. Mol. Sci. 2019 20 4789 10.3390/ijms20194789 31561568 103. Linsley P.S. Wallace P.M. Johnson J. Gibson M.G. Greene J.L. Ledbetter J.A. Singh C. Tepper M.A. Immunosuppression in vivo by a soluble form of the CTLA-4 T cell activation molecule Science 1992 257 792 795 10.1126/science.1496399 1496399 104. Genovese M.C. Pacheco-Tena C. Covarrubias A. Leon G. Mysler E. Keiserman M. Valente R.M. Nash P. Simon-Campos J.A. Box J. Longterm Safety and Efficacy of Subcutaneous Abatacept in Patients with Rheumatoid Arthritis: 5-year Results from a Phase IIIb Trial J. Rheumatol. 2018 45 1085 1092 10.3899/jrheum.170344 29657147 105. Cagnotto G. Willim M. Nilsson J.-Å. Compagno M. Jacobsson L.T.H. Saevarsdottir S. Turesson C. Abatacept in rheumatoid arthritis: Survival on drug, clinical outcomes, and their predictors—data from a large national quality register Arthritis Res. Ther. 2020 22 15 10.1186/s13075-020-2100-y 31969172 106. Orban T. Bundy B. Becker D.J. DiMeglio L.A. Gitelman S.E. Goland R. Gottlieb P.A. Greenbaum C.J. Marks J.B. Monzavi R. Co-stimulation modulation with abatacept in patients with recent-onset type 1 diabetes: A randomised, double-blind, placebo-controlled trial Lancet 2011 378 412 419 10.1016/S0140-6736(11)60886-6 21719096 107. Orban T. Beam C.A. Xu P. Moore K. Jiang Q. Deng J. Muller S. Gottlieb P. Spain L. Peakman M. Reduction in CD4 central memory T-cell subset in costimulation modulator abatacept-treated patients with recent-onset type 1 diabetes is associated with slower C-peptide decline Diabetes 2014 63 3449 3457 10.2337/db14-0047 24834977 108. Fife B.T. Bluestone J.A. Control of peripheral T-cell tolerance and autoimmunity via the CTLA-4 and PD-1 pathways Immunol. Rev. 2008 224 166 182 10.1111/j.1600-065X.2008.00662.x 18759926 109. Linsley P.S. Greenbaum C.J. Speake C. Long S.A. Dufort M.J. B lymphocyte alterations accompany abatacept resistance in new-onset type 1 diabetes JCI Insight 2019 4 e126136 10.1172/jci.insight.126136 110. Wing K. Sakaguchi S. Regulatory T cells exert checks and balances on self tolerance and autoimmunity Nat. Immunol. 2010 11 7 13 10.1038/ni.1818 20016504 111. Lopes M. Kutlu B. Miani M. Bang-Berthelsen C.H. Størling J. Pociot F. Goodman N. Hood L. Welsh N. Bontempi G. Temporal profiling of cytokine-induced genes in pancreatic β-cells by meta-analysis and network inference Genomics 2014 103 264 275 10.1016/j.ygeno.2013.12.007 24462878 112. Cabrera S.M. Wang X. Chen Y.-G. Jia S. Kaldunski M.L. Greenbaum C.J. the Type 1 Diabetes TrialNet Canakinumab Study Group Mandrup-Poulsen T. the AIDA Study Group Hessner M.J. Interleukin-1 antagonism moderates the inflammatory state associated with Type 1 diabetes during clinical trials conducted at disease onset Eur. J. Immunol. 2016 46 1030 1046 10.1002/eji.201546005 26692253 113. Ainscough J.S. Frank Gerberick G. Zahedi-Nejad M. Lopez-Castejon G. Brough D. Kimber I. Dearman R.J. Dendritic cell IL-1α and IL-1β are polyubiquitinated and degraded by the proteasome J. Biol. Chem. 2014 289 35582 35592 10.1074/jbc.M114.595686 25371210 114. Donath M.Y. Dinarello C.A. Mandrup-Poulsen T. Targeting innate immune mediators in type 1 and type 2 diabetes Nat. Rev. Immunol. 2019 19 734 746 10.1038/s41577-019-0213-9 31501536 115. Cucak H. Hansen G. Vrang N. Skarsfeldt T. Steiness E. Jelsing J. The IL-1β Receptor Antagonist SER140 Postpones the Onset of Diabetes in Female Nonobese Diabetic Mice J. Diabetes Res. 2016 2016 7484601 10.1155/2016/7484601 26953152 116. Sumpter K.M. Adhikari S. Grishman E.K. White P.C. Preliminary studies related to anti-interleukin-1β therapy in children with newly diagnosed type 1 diabetes Pediatric Diabetes 2011 12 656 667 10.1111/j.1399-5448.2011.00761.x 21518168 117. Dinarello C.A. van der Meer J.W.M. Treating inflammation by blocking interleukin-1 in humans Semin. Immunol. 2013 25 469 484 10.1016/j.smim.2013.10.008 24275598 118. Psarras A. Antanaviciute A. Alase A. Carr I. Wittmann M. Emery P. Tsokos G.C. Vital E.M. TNF-α Regulates Human Plasmacytoid Dendritic Cells by Suppressing IFN-α Production and Enhancing T Cell Activation J. Immunol. 2021 206 785 796 10.4049/jimmunol.1901358 33441439 119. Xu J. Eastman A.J. Flaczyk A. Neal L.M. Zhao G. Carolan J. Malachowski A.N. Stolberg V.R. Yosri M. Chensue S.W. Disruption of Early Tumor Necrosis Factor Alpha Signaling Prevents Classical Activation of Dendritic Cells in Lung-Associated Lymph Nodes and Development of Protective Immunity against Cryptococcal Infection mBio 2016 7 e00510-16 10.1128/mBio.00510-16 27406560 120. Shi J.-H. Sun S.-C. Tumor Necrosis Factor Receptor-Associated Factor Regulation of Nuclear Factor κB and Mitogen-Activated Protein Kinase Pathways Front. Immunol. 2018 9 1849 10.3389/fimmu.2018.01849 30140268 121. Joyce D. Albanese C. Steer J. Fu M. Bouzahzah B. Pestell R.G. NF-κB and cell-cycle regulation: The cyclin connection Cytokine Growth Factor Rev. 2001 12 73 90 10.1016/S1359-6101(00)00018-6 11312120 122. Yamamoto Y. Gaynor R.B. IκB kinases: Key regulators of the NF-κB pathway Trends Biochem. Sci. 2004 29 72 79 10.1016/j.tibs.2003.12.003 15102433 123. Mastrandrea L. Yu J. Behrens T. Buchlis J. Albini C. Fourtner S. Quattrin T. Etanercept Treatment in Children With New-Onset Type 1 Diabetes. Pilot randomized, placebo-controlled, double-blind study Diabetes Care 2009 32 1244 1249 10.2337/dc09-0054 19366957 124. Krishnamoorthy N. Oriss T. Paglia M. Ray A. Ray P. A critical role for IL-6 secretion by dendritic cells promoting Th2 and limiting Th1 response (95.24) J. Immunol. 2007 178 S181 125. Korn T. Mitsdoerffer M. Croxford A.L. Awasthi A. Dardalhon V.A. Galileos G. Vollmar P. Stritesky G.L. Kaplan M.H. Waisman A. IL-6 controls Th17 immunity in vivo by inhibiting the conversion of conventional T cells into Foxp3+ regulatory T cells Proc. Natl. Acad. Sci. USA 2008 105 18460 18465 10.1073/pnas.0809850105 19015529 126. Hundhausen C. Roth A. Whalen E. Chen J. Schneider A. Long S.A. Wei S. Rawlings R. Kinsman M. Evanko S.P. Enhanced T cell responses to IL-6 in type 1 diabetes are associated with early clinical disease and increased IL-6 receptor expression Sci. Transl. Med. 2016 8 356ra119 10.1126/scitranslmed.aad9943 127. Greenbaum C.J. Serti E. Lambert K. Weiner L.J. Kanaparthi S. Lord S. Gitelman S.E. Wilson D.M. Gaglia J.L. Griffin K.J. IL-6 receptor blockade does not slow β cell loss in new-onset type 1 diabetes JCI Insight 2021 6 e150074 10.1172/jci.insight.150074 34747368 128. Gaudino S.J. Kumar P. Cross-Talk Between Antigen Presenting Cells and T Cells Impacts Intestinal Homeostasis, Bacterial Infections, and Tumorigenesis Front. Immunol. 2019 10 360 10.3389/fimmu.2019.00360 30894857 129. Zheng H. Ban Y. Wei F. Ma X. Regulation of Interleukin-12 Production in Antigen-Presenting Cells Adv. Exp. Med. Biol. 2016 941 117 138 10.1007/978-94-024-0921-5_6 27734411 130. Powell M.D. Read K.A. Sreekumar B.K. Jones D.M. Oestreich K.J. IL-12 signaling drives the differentiation and function of a TH1-derived TFH1-like cell population Sci. Rep. 2019 9 13991 10.1038/s41598-019-50614-1 31570752 131. Yu S. Jia L. Zhang Y. Zhong J. Yang B. Wu C. IL-12 induced the generation of IL-21- and IFN-γ-co-expressing poly-functional CD4+ T cells from human naive CD4+ T cells Cell Cycle 2015 14 3362 3372 10.1080/15384101.2015.1093703 26566861 132. Marwaha A.K. Chow S. Pesenacker A.M. Cook L. Sun A. Long S.A. Yang J.H.M. Ward-Hartstonge K.A. Williams E. Domingo-Vila C. A phase 1b open-label dose-finding study of ustekinumab in young adults with type 1 diabetes Immunother. Adv. 2022 2 ltab022 10.1093/immadv/ltab022 35072168 133. Phillips B. Nylander K. Harnaha J. Machen J. Lakomy R. Styche A. Gillis K. Brown L. Lafreniere D. Gallo M. A Microsphere-Based Vaccine Prevents and Reverses New-Onset Autoimmune Diabetes Diabetes 2008 57 1544 1555 10.2337/db07-0507 18316361 134. Mukherjee G. Geliebter A. Babad J. Santamaria P. Serreze D.V. Freeman G.J. Tarbell K.V. Sharpe A. DiLorenzo T.P. DEC-205-mediated antigen targeting to steady-state dendritic cells induces deletion of diabetogenic CD8⁺ T cells independently of PD-1 and PD-L1 Int. Immunol. 2013 25 651 660 10.1093/intimm/dxt031 24021877 135. Lewis J.S. Stewart J.M. Marshall G.P. Carstens M.R. Zhang Y. Dolgova N.V. Xia C. Brusko T.M. Wasserfall C.H. Clare-Salzler M.J. Dual-Sized Microparticle System for Generating Suppressive Dendritic Cells Prevents and Reverses Type 1 Diabetes in the Nonobese Diabetic Mouse Model ACS Biomater. Sci. Eng. 2019 5 2631 2646 10.1021/acsbiomaterials.9b00332 31119191 136. Chen Y. Wu J. Wang J. Zhang W. Xu B. Xu X. Zong L. Targeted delivery of antigen to intestinal dendritic cells induces oral tolerance and prevents autoimmune diabetes in NOD mice Diabetologia 2018 61 1384 1396 10.1007/s00125-018-4593-3 29546475 137. Funda D.P. Palová-Jelínková L. Goliáš J. Kroulíková Z. Fajstová A. Hudcovic T. Špíšek R. Optimal Tolerogenic Dendritic Cells in Type 1 Diabetes (T1D) Therapy: What Can We Learn From Non-obese Diabetic (NOD) Mouse Models? Front. Immunol. 2019 10 967 10.3389/fimmu.2019.00967 31139178 138. Schülke S. Induction of Interleukin-10 Producing Dendritic Cells As a Tool to Suppress Allergen-Specific T Helper 2 Responses Front. Immunol. 2018 9 455 10.3389/fimmu.2018.00455 29616018 139. Zhong M. Zhong C. Cui W. Wang G. Zheng G. Li L. Zhang J. Ren R. Gao H. Wang T. Induction of tolerogenic dendritic cells by activated TGF-β/Akt/Smad2 signaling in RIG-I-deficient stemness-high human liver cancer cells BMC Cancer 2019 19 439 10.1186/s12885-019-5670-9 31088527 140. Tahaghoghi-Hajghorbani S. Ajami A. Ghorbanalipoor S. Hosseini-khah Z. Taghiloo S. Khaje-Enayati P. Hosseini V. Protective effect of TSLP and IL-33 cytokines in ulcerative colitis Autoimmun. Highlights 2019 10 1 10.1186/s13317-019-0110-z 141. Gaudreau S. Guindi C. Ménard M. Besin G. Dupuis G. Amrani A. Granulocyte-macrophage colony-stimulating factor prevents diabetes development in NOD mice by inducing tolerogenic dendritic cells that sustain the suppressive function of CD4+CD25+ regulatory T cells J. Immunol. 2007 179 3638 3647 10.4049/jimmunol.179.6.3638 17785799 142. Navarro-Barriuso J. Mansilla M.J. Naranjo-Gómez M. Sánchez-Pla A. Quirant-Sánchez B. Teniente-Serra A. Ramo-Tello C. Martínez-Cáceres E.M. Comparative transcriptomic profile of tolerogenic dendritic cells differentiated with vitamin D3, dexamethasone and rapamycin Sci. Rep. 2018 8 14985 10.1038/s41598-018-33248-7 30297862 143. Campbell N.K. Fitzgerald H.K. Malara A. Hambly R. Sweeney C.M. Kirby B. Fletcher J.M. Dunne A. Naturally derived Heme-Oxygenase 1 inducers attenuate inflammatory responses in human dendritic cells and T cells: Relevance for psoriasis treatment Sci. Rep. 2018 8 10287 10.1038/s41598-018-28488-6 29980703 144. Sekiya T. Takaki S. RGMB enhances the suppressive activity of the monomeric secreted form of CTLA-4 Sci. Rep. 2019 9 6984 10.1038/s41598-019-43068-y 31061392 145. Tezuka H. Ohteki T. Regulation of IgA Production by Intestinal Dendritic Cells and Related Cells Front. Immunol. 2019 10 1891 10.3389/fimmu.2019.01891 31456802 146. Guindi C. Ménard M. Cloutier A. Gaudreau S. Besin G. Larivée P. McDonald P.P. Dupuis G. Amrani A. Differential role of NF-κB, ERK1/2 and AP-1 in modulating the immunoregulatory functions of bone marrow-derived dendritic cells from NOD mice Cell. Immunol. 2012 272 259 268 10.1016/j.cellimm.2011.10.005 22070873 147. Guindi C. Cloutier A. Gaudreau S. Zerif E. McDonald P.P. Tatsiy O. Asselin C. Dupuis G. Role of the p38 MAPK/C/EBPβ Pathway in the Regulation of Phenotype and IL-10 and IL-12 Production by Tolerogenic Bone Marrow-Derived Dendritic Cells Cells 2018 7 256 10.3390/cells7120256 148. Gaudreau S. Guindi C. Ménard M. Benabdallah A. Dupuis G. Amrani A. GM-CSF induces bone marrow precursors of NOD mice to skew into tolerogenic dendritic cells that protect against diabetes Cell. Immunol. 2010 265 31 36 10.1016/j.cellimm.2010.06.010 20637454 149. Zerif E. Maalem A. Gaudreau S. Guindi C. Ramzan M. Véroneau S. Gris D. Stankova J. Rola-Pleszczynski M. Mourad W. Constitutively active Stat5b signaling confers tolerogenic functions to dendritic cells of NOD mice and halts diabetes progression J. Autoimmun. 2017 76 63 74 10.1016/j.jaut.2016.09.001 27634616 150. Zerif E. Khan F.U. Raki A.A. Lullier V. Gris D. Dupuis G. Amrani A. Elucidating the Role of Ezh2 in Tolerogenic Function of NOD Bone Marrow-Derived Dendritic Cells Expressing Constitutively Active Stat5b Int. J. Mol. Sci 2020 21 6453 10.3390/ijms21186453 151. Strauss L. Bergmann C. Szczepanski M. Gooding W. Johnson J.T. Whiteside T.L. A unique subset of CD4+CD25highFoxp3+ T cells secreting interleukin-10 and transforming growth factor-beta1 mediates suppression in the tumor microenvironment Clin. Cancer Res. 2007 13 4345 4354 10.1158/1078-0432.CCR-07-0472 17671115 152. Machen J. Harnaha J. Lakomy R. Styche A. Trucco M. Giannoukakis N. Antisense oligonucleotides down-regulating costimulation confer diabetes-preventive properties to nonobese diabetic mouse dendritic cells J. Immunol. 2004 173 4331 4341 10.4049/jimmunol.173.7.4331 15383562 153. Giannoukakis N. Phillips B. Finegold D. Harnaha J. Trucco M. Phase I (safety) study of autologous tolerogenic dendritic cells in type 1 diabetic patients Diabetes Care 2011 34 2026 2032 10.2337/dc11-0472 21680720 154. Alhadj Ali M. Liu Y.F. Arif S. Tatovic D. Shariff H. Gibson V.B. Yusuf N. Baptista R. Eichmann M. Petrov N. Metabolic and immune effects of immunotherapy with proinsulin peptide in human new-onset type 1 diabetes Sci. Transl. Med. 2017 9 eaaf7779 10.1126/scitranslmed.aaf7779 28794283 155. Gibson V.B. Nikolic T. Pearce V.Q. Demengeot J. Roep B.O. Peakman M. Proinsulin multi-peptide immunotherapy induces antigen-specific regulatory T cells and limits autoimmunity in a humanized model Clin. Exp. Immunol. 2015 182 251 260 10.1111/cei.12687 26206289 156. Nikolic T. Zwaginga J.J. Uitbeijerse B.S. Woittiez N.J. de Koning E.J. Aanstoot H.J. Roep B.O. Safety and feasibility of intradermal injection with tolerogenic dendritic cells pulsed with proinsulin peptide-for type 1 diabetes Lancet Diabetes Endocrinol. 2020 8 470 472 10.1016/S2213-8587(20)30104-2 32723484 157. Belz G.T. Nutt S.L. Transcriptional programming of the dendritic cell network Nat. Rev. Immunol. 2012 12 101 113 10.1038/nri3149 22273772 158. Di Caro V. Phillips B. Engman C. Harnaha J. Trucco M. Giannoukakis N. Retinoic acid-producing, ex-vivo-generated human tolerogenic dendritic cells induce the proliferation of immunosuppressive B lymphocytes Clin. Exp. Immunol. 2013 174 302 317 10.1111/cei.12177 23865694 159. Phillips B.E. Garciafigueroa Y. Engman C. Trucco M. Giannoukakis N. Tolerogenic Dendritic Cells and T-Regulatory Cells at the Clinical Trials Crossroad for the Treatment of Autoimmune Disease; Emphasis on Type 1 Diabetes Therapy Front. Immunol. 2019 10 148 10.3389/fimmu.2019.00148 30787930 160. Coppieters K.T. Harrison L.C. von Herrath M.G. Trials in type 1 diabetes: Antigen-specific therapies Clin. Immunol. 2013 149 345 355 10.1016/j.clim.2013.02.002 23490422

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091735 nutrients-14-01735 Article Addressing Weight Bias in the Cisgender Population: Differences between Sexual Orientations https://orcid.org/0000-0003-3323-6071 Meneguzzo Paolo 12* https://orcid.org/0000-0002-6730-1778 Collantoni Enrico 12 Meregalli Valentina 12 Favaro Angela 12 Tenconi Elena 12 Pataky Zoltan Academic Editor 1 Department of Neuroscience, University of Padova, 35121 Padova, Italy; enrico.collantoni@unipd.it (E.C.); valentina.meregalli@gmail.com (V.M.); angela.favaro@unipd.it (A.F.); elena.tenconi@unipd.it (E.T.) 2 Padova Neuroscience Center, University of Padova, 35129 Padova, Italy * Correspondence: paolo.meneguzzo@unipd.it 22 4 2022 5 2022 14 9 173528 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). (1) Background: Weight bias (WB) is an implicit psychological construct that can influence attitudes, beliefs, body experience, and evaluation of specific psychopathology relationships. Sexual orientation has played a crucial role in developing and maintaining psychiatric conditions linked to body evaluation, but few studies have evaluated possible connected biases. Thus, the paper aims to assess potential relationships between sexual orientation and WB, looking at potential roles in specific psychopathology; (2) Methods: A total of 836 cisgender subjects participated in an online survey, aged between 18 and 42 years old. Two specific aspects of WB were evaluated with validated scales about beliefs about obese people and fat phobia. Demographic variables, as well as depression and eating concerns were evaluated; (3) Results: Gay men and bisexual women showed higher levels of fat phobia, depression, and eating concerns. Regression analysis showed that sexual orientation significantly predicted fat phobia (p < 0.001) and beliefs about obese people (p = 0.014); (4) Conclusions: This study confirms the vulnerability of gay men and bisexual women to cognitive bias about their own bodies, showing a potential vulnerability about body and weight concerns. weight bias gay lesbian bisexual obesity cisgender heterosexual ==== Body pmc1. Introduction Weight bias (WB) is defined as negative weight-related attitudes, beliefs, assumptions, and judgmental stereotypes that negatively influence body experience and evaluation [1]. This bias can be a crucial element in evaluating one’s own body, distorting real perceptions of body shape and weight, as well as reinforcing negative emotions with implicit biases that could influence one’s judgment [2,3]. The literature has shown that WB leads to negative emotions and concerns about one’s body and weight, and may correlate to unhealthy eating behaviors, low quality of life, depression, and maladaptive behaviors [4]. A recent “call to action” paper has shown the role of WB across the weight spectrum, encouraging an integrative perspective on obesity and eating disorders and the need to reduce the influence of weight standards in society in order to increase the quality of life and mental wellbeing [5]. The same has been seen in people with higher weight, where WB has been shown to be related to body weight misperceptions after bariatric surgery [6], with possible negative surgery outcomes. Indeed, WB is linked to adverse mental health outcomes and may play a crucial role in the development or maintenance of body image dissatisfaction and pathological eating behaviors [7], with a possible negative impact on the outcome of treatments [8]. Data have shown that WB differs with respect to individual characteristics such as age, sex, and body weight [9], suggesting different strategies for its reduction. Looking only to gender differences, women reported higher levels of WB, with a higher connection to eating disorders and depression [10,11]. Only a few studies about WB have considered sexual orientation, with various methodologies focusing mainly on differences between gay men and heterosexual peers [12,13]. Weight stigma is a result of WB, and it is defined as discriminatory acts and thoughts targeted towards individuals because of their weight [14]. Weight stigma is a common experience in sexual minority people, and it is linked to poorer quality of life and higher levels of internalization of weight bias ideas, with consequent psychological distress [1,14,15]. Even if the weight stigma phenomenon derives from cognitive bias and is equally harmful to all men despite their sexual orientation, gay and bisexual men displayed heightened WB levels compared to their heterosexual peers [13,16]. Weight stigma is something that gay and bisexual men reported both from others and for themselves [13], but few studies are available about their judgment style about themselves. Few studies are available on WB in sexual minority women, perhaps because body image and related cognitive features were for many years not considered a problem within this group [17]. New evidence has shown, however, that bisexual women (BIW) frequently experience adverse thoughts about their bodies [18] as well as misperceive their weight status with health-related consequences. Moreover, a growing body of literature has shown the presence of differences between BIW and lesbians regarding body image concerns, body misperception, and eating behaviors [17,18], indicating that WB should be investigated in this population as well. Moreover, sexual minority people who reported weight-based victimization also reported lower levels of quality of life and lower own-health perceived [19], showing the need for a deeper understanding of the possible role of sexual orientation in WB. Converging evidence has shown that minorities’ stress due to sexual orientation could have a role in dysfunctional eating behaviors [18,20], but no specific conclusion about the relationship between these aspects has been drawn. Data are still preliminary, but recent studies have found both in sexual minority men and women the presence of higher BMI, higher levels of binge eating, and higher internalization of weight biases [21,22]. Thus, considering the role of WB in the quality of life and wellbeing [23], more studies are needed in the sexual minority population that could explain the presence and the relationship of WB with eating concerns and general wellbeing. For all these reasons, our primary goal was to evaluate the role of WB across the sexual orientation spectrum, looking for a specific connection to eating concerns and correlated behaviors which we hypothesized to differ across specific sexual orientations. Moreover, we hypothesized that due to the disparities that emerged in WB between genders and sexual orientations, BIW and lesbians could be the subgroups with worse scores. 2. Materials and Methods The participants were recruited via online invitations through social media (i.e., Italian Facebook groups related to gender, physical activities, and cultural associations linked to civil rights; both open and close groups) and LGBTQ+ group mailing lists from the area of the Veneto Region (Italy), through those responsible for managing personal data, without the involvement of researchers. The invitation consisted of a request to complete voluntary and spontaneous questionnaires on body image and body experiences and indicated that the questionnaires would be used for research purposes, as suggested by the previous literature [24]. The online survey was devised in such a way as to prevent multiple responses from the same IP addresses, but the IP addresses were hidden from investigators. The online survey did not allow multiple responses from the same IP address, and IP addresses were not linked to the answers. No participants received any remuneration for their participation. The data, collected between September 2019 and March 2020, explore the role of specific cognitive aspects such as fat phobia, defined as a pathological fear of fatness, and beliefs about obesity in the cisgender population, looking for these constructs’ function in the psychopathology linked to eating behaviors and thoughts, as well as their relationships to different sexual orientations. The inclusion criteria were: (1) written informed consent obtained before the questionnaires; (2) ≥18 years of age; (3) fluent understanding of written Italian. No specific exclusion criteria were applied. Each participant provided written informed consent agreeing to participate in the survey. The research was in accordance with the Declaration of Helsinki, its later amendments, and local legislation about anonymous questionnaires, according to the local Ethics Committee. 2.1. Measures We asked the participants to provide demographic information such as age, race, education, height, and weight. The body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared, using the data given by participants. The gender of participants was determined by specific items asking them to self-identify as “cisgender,” “transgender,” or “non-binary”. The sexual orientation was self-identified by each participant as “heterosexual,” “bisexual,” “gay/lesbian,” or “asexual”, as previously applied [18]. Other psychological constructs that were evaluated according to the previous literature data and the aim of the study were depression and eating concerns as general psychological factors correlated with WB, and fat phobia and beliefs about obese people as specific elements of WB. The Patient Health Questionnaire-9 (PHQ-9) is a screening tool for depression, with robust evidence of sensibility and sensitivity [25]. It is a nine-item scale, where each item evaluates the presence of one of the DSM criteria for a depressive episode in the prior two weeks. Answers were forced into a Likert scale with four possible choices: 0 (“not at all”), 1 (“a few days”), 2 (“more than half the days”), and 3 (“almost every day”), with higher scores indicating higher depressive symptomatology. In this study, Cronbach’s α = 0.79. The Eating Attitudes Test (EAT-26) is a widely used self-reported questionnaire that collects information about symptomatology and eating disorder-related concerns [26]. It is composed of 26 items, rated on a six-point Likert scale ranging from 1 (“never”) to 6 (“always”). Higher scores indicate higher eating concerns, with a clinical cut-off score at 20 points. In this study, Cronbach’s α = 0.91. The Beliefs About Obese Persons Scale (BAOP) is a validated, self-administered eight-item questionnaire used to evaluate beliefs about the causes of obesity [27]. Higher scores imply a stronger belief that obesity is not under the person’s control, indicating a lack of negative judgment of people at higher body weight and less WB. In this study, Cronbach’s α = 0.75. The Fat Phobia Scale (FPS) is a 14-item questionnaire measuring negative attitudes toward higher weight [28]. The participants are asked to imagine a specific person characterized by a high weight, and they must indicate on a scale from 1 to 5 which adjective they feel best describes that person’s feelings and beliefs (e.g., “no will power” versus “will power”), showing the degree of their stereotypical assumptions about being fat. Scores lower than 2.5 denote negative attitudes. In this study, Cronbach’s α = 0.77. 2.2. Statistical Analysis An a-priori power analysis for a 2 (gender)  ×  3 (sexual orientation) MANOVA was conducted using G*Power vers. 3.1.9.7 (Universität Düsseldorf, Düsseldorf, Germany) [29], assuming f2  =  0.0625, α = 0.05, 1-β = 0.95, indicating that the total sample size should be 213. The variance analyses were performed with the Kruskal–Wallis test, due to the non-parametric nature of most of the study’s data. Post hoc comparisons were performed using Bonferroni correction. Correlation analyses were performed by Spearman’s ρ. Regression analyses were conducted with sexual orientation as an independent variable using heterosexual subgroup results as dummy variables and setting FPS and BAOP as dependent variables. The alpha was set at p < 0.05 for all of the analyses, and the effect sizes were calculated with partial eta squared. Bonferroni corrections for multiple testing have been applied by dividing 0.05 by the overall number (4) of questionnaire comparisons, with the level of significance set at 0.013. The entire analysis was conducted with IBM SPSS Statistics 25.0 (SPSS, Chicago, IL, USA). 3. Results A total sample of 940 people decided to open the online survey. We excluded all the incomplete responders and all the responders faster than 5 min to exclude bot responders (n = 90, 9.6% of the responders). We also excluded all the responders who identified themselves as transgender or non-binary (n = 12), due to the low number of responders. Only eight women identified themselves as asexual, and for statistical reasons, were excluded, while no men identified themselves as asexual. We obtained a total sample of 830 cisgender individuals. The sample was then composed of 506 women (53.8% of the participants). Most of the sample described themselves as white (98.3%) and engaged a relationship of any kind (78.5% of the participants). Due to the nature of the questionnaire, the totality of the participants were Italian speakers. Please see Table 1 for the demographic details of the participants. No significant differences emerged between subgroups regarding age (F (824,5) = 1.720, p = 0.127), but BMI showed a significant difference between subgroups (F (824,5) = 2.406, p = 0.035), with heterosexual women (HEW) having a lower BMI than bisexual men (BIM, p = 0.003) and heterosexual men (HEM, p < 0.001) at the post-hoc analysis with Bonferroni correction. The psychometric assessment showed significant differences in specific psychological domains across the sexual orientation spectrum, as shown in Table 2. Graphical representation of the FPS scores showed the different distribution of the results across the sexual orientation spectrum (see Figure 1). Several correlation analyses were performed seeking relationships between the included constructs. Table 3 reports the results of the correlations. Regression analysis was performed for both of the constructs linked to WB included in this survey, looking for significant relationships between constructs and demographic data and considering genders separately. In women, we found no significant regression for both FPS and BAOP using PHQ-9, EAT26 TOT, BMI and age as predictors. In the male subsample, we found that both FPS and BAOP were significantly predicted by EAT-26 TOT alone [FPS: R2 = 0.17, F (1,322) = 9.90, p = 0.002; BAOP: R2 = 0.21, F (1,322) = 14.72, p < 0.001] and also with BMI [FPS: R2 = 0.22, F (1,321) = 8.41, p < 0.001; BAOP: R2 = 0.17, F (1,322) = 10.92, p < 0.001]. Regarding the role of sexual orientations, different regressions were performed using heterosexual scores as comparison using dummy variables, showing different regression coefficients in sexual minority groups, see Table 4 for details. 4. Discussion The primary goal of the paper was to evaluate the presence of different levels of weight bias (WB) across the sexual orientation spectrum in both genders. In particular, we were interested in data about BIW and reinforcing previous evidence about gay men’s body and weight concerns. Our analyses showed that gay men had the highest levels of fat phobia, a particular aspect of WB, and the lowest scores on the BAOP scale, which indicates higher levels of negative beliefs and more blaming of people at higher body weights. The same occurred in women, where sexual minority individuals showed higher weight biases than heterosexual women. To the best of our knowledge, this is the first time that WB has been investigated across different sexual orientations in women. Our investigation focused on the cognitive aspects of the evaluation of a person’s body weight. Data in the literature have shown that sexual minority men perceive higher levels of weight stigma [13,30], and the same has been found for lesbians [31]; however, to our knowledge, no studies have investigated the role of WB. Weight bias is a construct that may play a role in the management of body image and could be linked to unhealthy eating behaviors [6,7,32]. Moreover, WB has a role in poor interpersonal relationships and quality of life and could be linked to the physical health impairment of the individuals [23]. Recently, however, the literature has shown that it is possible to modify implicit and explicit biases with specific WB modification interventions [5], thereby pointing to new clinical applications. Our data confirmed the previously shown relationship between gay men and body shape and weight concerns, calling for specific assessments regarding body image in gay patients [33]. Indeed, bisexual women and gay men appeared as the subgroups with the highest level of weight stigma. This aspect is likely due to stress resulting from social stigmatization, which plays a significant role in developing an eating disorder in sexual minorities [34]. This should be considered when devising campaigns for body confidence to improve the wellbeing of gay men and BIW and reduce their body dissatisfaction [35]. Another notable result showed that a similar approach to body weight in BIW and gay men is the absence of a positive correlation between age and BMI present in all other sexual orientation groups. This data may corroborate the idea that there is an active control over one’s own body weight in BIW and gay men, showing the effects of a cognitive vulnerability to specific body shapes and weights that maybe be driven by WB [1,36]. Indeed, BIW and gay men are the two groups with the highest body weight dissatisfaction across the sexual orientation spectrum, and this concern could lead to weight control behaviors [18]. Depression and eating concerns have been pointed out as risk factors for body image disturbances and WB [37]. Our data showed the highest score for both these psychological domains in bisexual and lesbian women, corroborating the previous findings of the impaired psychological wellbeing in sexual minority women [38]. Moreover, we found significant relationships between fat phobia and depression scores in bisexual women, showing that this could be a vulnerability aspect that could explain previous results about body image evaluation [39] and therefore should be deeply evaluated. There are some limitations to this study that need to be considered and which could be a starting point for necessary future research. Firstly, this study’s sample is from an online survey, and we must be careful not to overgeneralize the results to the whole population. Future studies could employ a double recruitment channel, using a statistical approach to limit sample size differences. Moreover, no robust data are available about the distribution of sexual minority population over the general population, limiting the generalization of our results. Secondly, we did not consider all of the possible constructs that the literature has shown to be potentially important aspects of socio-cultural pressure on sexual minority groups, such as internalized stigma, stress minority evaluation, and lack of social support. These should be investigated in future studies to examine their role on levels of weight stigma. 5. Conclusions Despite the limits of this study, our WB evaluation across the sexual orientation spectrum has shown convergent evidence about the role of body weight and shape concerns in gay men and bisexual women. This study confirms the vulnerability of gay men and bisexual women in cognitive bias about their own bodies, showing a potential vulnerability about body and weight concerns. Due to the implicit role of body judgment, WB should be taken under serious consideration in treating body image concerns according to the sexual orientation of the clients. More studies concerning the relationship between WB and other cultural constructs are needed to achieve a better understanding of its function in the interpersonal domain, psychopathological constructs, and mental health. Author Contributions Conceptualization, P.M., A.F. and E.T.; methodology, P.M.; software, P.M.; validation, P.M., E.C., A.F. and E.T.; formal analysis, P.M.; investigation, P.M., V.M. and E.C.; resources, A.F.; data curation, P.M.; writing—original draft preparation, P.M., E.C. and V.M.; writing—review and editing, E.T. and A.F.; visualization, P.M.; supervision, A.F. and E.T.; project administration, P.M.; funding acquisition, A.F. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by the “Department of excellence 2018–2022” initiative of the Italian Ministry of education (MIUR) awarded to the Department of Neuroscience—University of Padova. Institutional Review Board Statement All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee, the 1964 Helsinki Declaration and its later amendments, and comparable ethical standards. Ethics approval was not required for this kind of survey as per local legislation and national guidelines. Informed Consent Statement Written informed consent has been obtained from the participants to publish this paper. Data Availability Statement The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request due to the institutional regulations. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The figure shows the FPS results divided by sexual orientations. It is possible to appreciate how differently the results are distributed in the sexual minority groups of both genders compared to heterosexual peers. Gay men showed the highest scores for fat phobia in all groups included in the study, see Table 2 for data. nutrients-14-01735-t001_Table 1 Table 1 Demographic description of the participants. HEW n = 382 BIW n = 74 Lesbian n = 50 HEM n = 236 BIM n = 40 Gay n = 48 Age 26.69 (4.89) (18–40) 25.47 (3.94) (18–42) 26.42 (5.79) (18–38) 27.30 (5.50) (18–40) 26.43 (5.58) (18–35) 27.46 (5.49) (18–40) BMI 22.56 (7.30) (15.57–58.60) 24.29 (6.10) (16.56–60.55) 24.92 (6.88) (16.90–41.50) 23.33 (3.53) (15.23–36.93) 22.48 (2.09) (20.01–28.21) 22.52 (3.40) (18.50–32.12) Education Lower secondary 2.3% 2.0% 7.0% 5.4% 2.0% 2.5% Upper secondary 25.9% 49.0% 39.5% 35.4% 40.5% 39.6% Degree 31.5% 30.6% 20.9% 27.7% 20.0% 11.8% Master or Doctorate 40.2% 18.4% 32.6% 31.5% 37.5% 46.1% Relationship Yes 76.4% 75.5% 79.1% 80.8% 77.9% 74.8% No 23.6% 24.5% 20.9% 19.2% 22.1% 25.2% Means and standard deviations are reported, with minimum and maximum scores between brackets. HEW: heterosexual women; BIW: bisexual women; HEM: heterosexual men; BIM: bisexual men; BMI: body mass index, kg/m2. nutrients-14-01735-t002_Table 2 Table 2 Psychological evaluation of the sample. HEW n = 382 BIW n = 74 Lesbian n = 50 HEM n = 236 BIM n = 40 Gay n = 48 H p η2p Post-Hoc PHQ9 8.77 (4.84) 11.13 (5.02) 9.70 (4.75) 6.98 (4.49) 7.65 (4.55) 6.85 (3.90) 56.797 <0.001 0.067 BIW > HEW (p = 0.001) HEW > HEM (p < 0.001) BIW > HEM (p < 0.001) BIW > BIM (p = 0.002) BIW > Gay (p < 0.001) EAT26 tot 9.14 (10.17) 12.74 (13.19) 10.94 (9.25) 5.26 (4.57) 4.22 (3.67) 7.65 (4.57) 73.780 <0.001 0.073 HEW > HEM (p < 0.001) HEM > BIM (p = 0.011) BIW > HEM (p < 0.001) BIW > BIM (p < 0.001) Lesbian > HEM (p < 0.001) FPS 3.57 (0.47) 3.82 (0.39) 3.73 (0.36) 3.52 (0.60) 3.90 (0.55) 4.36 (0.32) 112.111 <0.001 0.144 BIW > HEW (p = 0.003) BIW > HEM (p < 0.001) BIM > HEW (p = 0.002) Gay > HEW (p < 0.001) Gay > BIW (p < 0.001) Gay > Lesbian (p < 0.001) Gay > HEM (p < 0.001) Gay > BIM (p < 0.001) BAOP 19.72 (3.73) 20.68 (3.64) 20.42 (4.08) 20.37 (4.46) 20.77 (1.94) 18.69 (2.36) 22.251 0.014 0.017 Gay < HEM (p = 0.004) HEW: heterosexual women; BIW: bisexual women; HEM: heterosexual men; BIM: bisexual men; PHQ9: physical health questionnaire; EAT: eating attitude test; FPS: fat phobia scale, BAOP: beliefs about obese person. H: Kruskal–Wallis test for the evaluation of the distribution of variables with Pairwise Comparisons with Bonferroni correction. nutrients-14-01735-t003_Table 3 Table 3 Correlation analyses in different sexual orientation subgroups. Women HEW BIW Lesbian 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 Age - - - 2 BMI 0.11 - 0.04 - 0.672 ** - 3 PHQ 9 −0.19 ** 0.08 - 0.01 0.03 - −0.112 0.216 - 4 EAT 26 tot −0.10 0.08 0.48 ** - 0.10 0.15 0.43 ** - 0.191 0.160 0.33 - 5 FPS 0.07 −0.07 −0.04 −0.08 - −0.04 −0.05 −0.35 ** −0.08 - −0.005 −0.086 0.10 −0.25 - 6 BAOP 0.06 −0.08 −0.04 −0.09 0.91 ** 0.15 −0.05 −0.43 ** −0.14 0.83 ** −0.002 0.048 0.24 −0.18 0.68 ** Men HEM BIM Gay 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 Age - - - 2 BMI 0.26 ** - 0.55 ** - 0.05 - 3 PHQ 9 −0.01 −0.07 - −0.37 0.13 - −0.37 0.06 - 4 EAT 26 tot −0.03 0.22 ** 0.24 ** - −0.65 ** −0.34 0.61 ** - −0.28 0.09 0.55 ** - 5 FPS 0.08 −0.03 0.07 0.25 ** - 0.01 0.01 0.01 −0.01 - −0.32 0.07 −0.02 0.03 - 6 BAOP −0.21 ** −0.01 −0.03 −0.22 ** −0.93 ** 0.24 0.52 ** 0.26 −0.46 ** 0.09 0.19 0.07 −0.29 −0.51 ** −0.21 HEW: heterosexual women; BIW: bisexual women; HEM: heterosexual men; BIM: bisexual men; PHQ9: physical health questionnaire; EAT: eating attitude test; FPS: fat phobia scale, BAOP: beliefs about obese person. Spearman’s ρ is reported for each pair of variables. The significances are reported as = **: p < 0.01. nutrients-14-01735-t004_Table 4 Table 4 Regression analysis. Unstandardized Coefficients Standardized Coefficient FPS R2 p B SE β t p 0.039 <0.001 3.577 0.023 154.380 <0.001 BIW compared to HEW 0.238 0.058 0.183 4.144 <0.001 Lesbian compared to HEW 0.156 0.068 0.101 2.292 0.022 0.224 <0.001 3.528 0.036 96.681 <0.001 BIM compared to HEM 0.370 0.096 0.192 3.859 <0.001 Gay compared to HEM 0.827 0.089 0.464 9.315 <0.001 BAOP 0.010 0.085 19.720 0.192 102.634 <0.001 BIW compared to HEW 0.956 0.477 0.090 2.004 0.046 Lesbian compared to HEW 0.700 0.565 0.056 1.240 0.216 0.025 0.017 20.369 0.259 78.733 <0.001 BIM compared to HEM 0.406 0.680 0.033 0.598 0.550 Gay compared to HEM −1.681 0.629 −0.149 −2.672 0.008 Regression analysis with sexual orientation as an independent variable. FPS: fat phobia scale, BAOP: beliefs about obese person. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. O’Brien K.S. Latner J.D. Puhl R.M. Vartanian L.R. Giles C. Griva K. Carter A. The Relationship between Weight Stigma and Eating Behavior Is Explained by Weight Bias Internalization and Psychological Distress Appetite 2016 102 70 76 10.1016/j.appet.2016.02.032 26898319 2. Cazzato V. Makris S. Implicit Preference towards Slim Bodies and Weight-Stigma Modulate the Understanding of Observed Familiar Actions Psychol. Res. 2019 83 1825 1835 10.1007/s00426-018-1030-7 29948182 3. Pearl R.L. Puhl R.M. The Distinct Effects of Internalizing Weight Bias: An Experimental Study Body Image 2016 17 38 42 10.1016/j.bodyim.2016.02.002 26927688 4. Barnes M. Abhyankar P. Dimova E. Best C. Associations between Body Dissatisfaction and Self-Reported Anxiety and Depression in Otherwise Healthy Men: A Systematic Review and Meta-Analysis PLoS ONE 2020 47 e0229268 10.1371/journal.pone.0229268 32097427 5. Alberga A.S. Russell-Mayhew S. von Ranson K.M. McLaren L. Weight Bias: A Call to Action J. Eat. Disord. 2016 4 34 10.1186/s40337-016-0112-4 27826445 6. Meneguzzo P. Behrens S.C. Favaro A. Tenconi E. Vindigni V. Teufel M. Skoda E.M. Lindner M. Quiros-Ramirez M.A. Mohler B. Body Image Disturbances and Weight Bias After Obesity Surgery: Semantic and Visual Evaluation in a Controlled Study, Findings from the BodyTalk Project Obes. Surg. 2021 31 1625 1634 10.1007/s11695-020-05166-z 33405179 7. Behrens S.C. Meneguzzo P. Favaro A. Teufel M. Skoda E.M. Lindner M. Walder L. Quiros Ramirez A. Zipfel S. Mohler B. Weight Bias and Linguistic Body Representation in Anorexia Nervosa: Findings from the BodyTalk Project Eur. Eat. Disord. Rev. 2020 29 204 215 10.1002/erv.2812 33252835 8. Pellizzer M.L. Waller G. Wade T.D. Body Image Flexibility: A Predictor and Moderator of Outcome in Transdiagnostic Outpatient Eating Disorder Treatment Int. J. Eat. Disord. 2018 51 368 372 10.1002/eat.22842 29457252 9. Flint S.W. Hudson J. Lavallee D. UK Adults’ Implicit and Explicit Attitudes towards Obesity: A Cross-Sectional Study BMC Obes. 2015 2 31 10.1186/s40608-015-0064-2 26351567 10. Boswell R.G. White M.A. Gender Differences in Weight Bias Internalisation and Eating Pathology in Overweight Individuals Adv. Eat. Disord. 2015 3 259 268 10.1080/21662630.2015.1047881 27042387 11. Fikkan J.L. Rothblum E.D. Is Fat a Feminist Issue? Exploring the Gendered Nature of Weight Bias Sex Roles 2012 66 575 592 10.1007/s11199-011-0022-5 12. Calzo J.P. Masyn K.E. Corliss H.L. Scherer E.A. Field A.E. Austin S.B. Patterns of Body Image Concerns and Disordered Weight- and Shape-Related Behaviors in Heterosexual and Sexual Minority Adolescent Males Dev. Psychol. 2015 51 1216 1225 10.1037/dev0000027 26098578 13. Austen E. Greenaway K.H. Griffiths S. Differences in Weight Stigma between Gay, Bisexual, and Heterosexual Men Body Image 2020 35 30 40 10.1016/j.bodyim.2020.08.002 32829093 14. Panza E. Olson K. Goldstein C.M. Selby E.A. Lillis J. Characterizing Lifetime and Daily Experiences of Weight Stigma among Sexual Minority Women with Overweight and Obesity: A Descriptive Study Int. J. Environ. Res. Public Health 2020 17 4892 10.3390/ijerph17134892 15. Puhl R.M. Himmelstein M.S. Pearl R.L. Wojtanowski A.C. Foster G.D. Weight Stigma Among Sexual Minority Adults: Findings from a Matched Sample of Adults Engaged in Weight Management Obesity 2019 27 1906 1915 10.1002/oby.22633 31689008 16. Puhl R. Suh Y. Stigma and Eating and Weight Disorders Curr. Psychiatry Rep. 2015 17 10 10.1007/s11920-015-0552-6 17. Meneguzzo P. Collantoni E. Gallicchio D. Busetto P. Solmi M. Santonastaso P. Favaro A. Eating Disorders Symptoms in Sexual Minority Women: A Systematic Review Eur. Eat. Disord. Rev. 2018 26 275 292 10.1002/erv.2601 29708623 18. Meneguzzo P. Collantoni E. Bonello E. Vergine M. Behrens S.C. Tenconi E. Favaro A. The Role of Sexual Orientation in the Relationships between Body Perception, Body Weight Dissatisfaction, Physical Comparison, and Eating Psychopathology in the Cisgender Population Eat. Weight Disord. 2020 26 1985 2000 10.1007/s40519-020-01047-7 33090374 19. Puhl R.M. Himmelstein M.S. Watson R.J. Weight-Based Victimization among Sexual and Gender Minority Adolescents: Implications for Substance Use and Mental Health Health Psychol. 2019 38 727 737 10.1037/hea0000758 31157534 20. Panza E. Fehling K.B. Pantalone D.W. Dodson S. Selby E.A. Multiply Marginalized: Linking Minority Stress Due to Sexual Orientation, Gender, and Weight to Dysregulated Eating among Sexual Minority Women of Higher Body Weight Psychol. Sex. Orientat. Gend. Divers. 2020 8 420 428 10.1037/sgd0000431 34926715 21. Eliason M.J. Ingraham N. Fogel S.C. McElroy J.A. Lorvick J. Mauery D.R. Haynes S. A Systematic Review of the Literature on Weight in Sexual Minority Women Women’s Health Issues 2015 25 162 175 10.1016/j.whi.2014.12.001 25747521 22. Grunewald W. Convertino A.D. Safren S.A. Mimiaga M.J. O’Cleirigh C. Mayer K.H. Blashill A.J. Appearance Discrimination and Binge Eating among Sexual Minority Men Appetite 2021 156 104819 10.1016/j.appet.2020.104819 32853713 23. Latner J.D. Barile J.P. Durso L.E. O’Brien K.S. Weight and Health-Related Quality of Life: The Moderating Role of Weight Discrimination and Internalized Weight Bias Eat. Behav. 2014 15 586 590 10.1016/j.eatbeh.2014.08.014 25215477 24. Wright B. Schwager P.H. Online Survey Research: Can Response Factors Be Improved? J. Internet Commer. 2008 7 253 269 10.1080/15332860802067730 25. Kroenke K. Spitzer R.L. The PHQ-9: A New Depression Diagnostic and Severity Measure Psychiatr. Ann. 2002 32 509 515 10.3928/0048-5713-20020901-06 26. Garner D.M. Olmsted M.P. Bohr Y. Garfinkel P.E. The Eating Attitudes Test: Psychometric Features and Clinical Correlates Psychol. Med. 1982 12 871 878 10.1017/S0033291700049163 6961471 27. Allison D.B. Basile V.C. Yuker H.E. The Measurement of Attitudes toward and Beliefs about Obese Persons Int. J. Eat. Disord. 1991 10 599 607 10.1002/1098-108X(199109)10:5<599::AID-EAT2260100512>3.0.CO;2-# 28. Bacon J.G. Scheltema K.E. Robinson B.E. Fat Phobia Scale Revisited: The Short Form Int. J. Obes. 2001 25 252 257 10.1038/sj.ijo.0801537 29. Faul F. Erdfelder E. Lang A.-G. Buchner A. G*Power 3: A Flexible Statistical Power Analysis Program for the Social, Behavioral, and Biomedical Sciences Behav. Res. Methods 2007 39 175 191 10.3758/BF03193146 17695343 30. Puhl R.M. Himmelstein M.S. Watson R.J. Weight-Based Victimization among Sexual and Gender Minority Adolescents: Findings from a Diverse National Sample Pediatr. Obes. 2019 14 e12514 10.1111/ijpo.12514 30729734 31. Puhl R. Brownell K.D. DePierre J.A. Bias, Discrimination, and Obesity Handbook of Obesity CRC Press Boca Raton, FL, USA 2014 Volume 9 461 470 10.3109/9781420051452-6 32. Durso L.E. Latner J.D. Understanding Self-Directed Stigma: Development of the Weight Bias Internalization Scale Obesity 2008 16 (Suppl. 2) S80 S86 10.1038/oby.2008.448 18978768 33. Dahlenburg S.C. Gleaves D.H. Hutchinson A.D. Coro D.G. Body Image Disturbance and Sexual Orientation: An Updated Systematic Review and Meta-Analysis Body Image 2020 35 126 141 10.1016/j.bodyim.2020.08.009 32987246 34. Bell K. Rieger E. Hirsch J.K. Eating Disorder Symptoms and Proneness in Gay Men, Lesbian Women, and Transgender and Non-Conforming Adults: Comparative Levels and a Proposed Mediational Model Front. Psychol. 2019 9 2692 10.3389/fpsyg.2018.02692 30671007 35. Jankowski G.S. Diedrichs P.C. Halliwell E. Can Appearance Conversations Explain Differences between Gay and Heterosexual Men’s Body Dissatisfaction? Psychol. Men Masculinity 2014 15 68 77 10.1037/a0031796 36. Puhl R.M. Moss-Racusin C.A. Schwartz M.B. Internalization of Weight Bias: Implications for Binge Eating and Emotional Well-Being Obesity 2007 15 19 23 10.1038/oby.2007.521 17228027 37. Pearl R.L. Puhl R.M. Weight Bias Internalization and Health: A Systematic Review Obes. Rev. 2018 19 1141 1163 10.1111/obr.12701 29788533 38. Nagata J.M. Ganson K.T. Austin S.B. Emerging Trends in Eating Disorders among Sexual and Gender Minorities Curr. Opin. Psychiatry 2020 33 562 567 10.1097/YCO.0000000000000645 32858597 39. Mason T.B. Lewis R.J. Heron K.E. Disordered Eating and Body Image Concerns among Sexual Minority Women: A Systematic Review and Testable Model Psychol. Sex. Orientat. Gend. Divers. 2018 5 397 422 10.1037/sgd0000293

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095310 ijerph-19-05310 Review What Social Supports Are Available to Self-Employed People When Ill or Injured? A Comparative Policy Analysis of Canada and Australia Khan Tauhid Hossain 12* MacEachen Ellen 1 Dunstan Debra 3 Luo Xiaowei Academic Editor Wu Xiang Academic Editor Yang Hao Academic Editor Ji Huaijun Academic Editor 1 School of Public Health Sciences, University of Waterloo, Waterloo, ON N2L 3G1, Canada; ellen.maceachen@uwaterloo.ca 2 Department of Sociology, Jagannath University, Dhaka 1100, Bangladesh 3 School of Psychology, University of New England, Armidale, NSW 2350, Australia; ddunstan@une.edu.au * Correspondence: th3khan@uwaterloo.ca 27 4 2022 5 2022 19 9 531023 3 2022 24 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Self-employment (SE) is a growing precarious work arrangement internationally. In the current digital age, SE appears in configurations and contours that differ from the labor market of 50 years ago and is part of a ‘paradigm shift’ from manufacturing/managerial capitalism to entrepreneurial capitalism. Our purpose in this paper is to reflect on how a growing working population of self-employed people accesses social support systems when they are not working due to injury and sickness in the two comparable countries of Canada and Australia. We adopted ‘interpretive policy analysis’ as a methodological framework and searched a wide range of documents related to work disability policy and practice, including official data, legal and policy texts from both countries, and five prominent academic databases. Three major themes emerged from the policy review and analysis: (i) defining self-employment: contested views; (ii) the relationship between misclassification of SE and social security systems; (iii) existing social security systems for workers and self-employed workers: Ontario and NSW. Our comparative discussion leads us toward conclusions about what might need to be done to better protect self-employed workers in terms of reforming the existing social security systems for the countries. Because of similarities and differences in support available for SE’d workers in the two countries, our study provides insights into what might be required to move the different countries toward sustainable labour markets for their respective self-employed populations. precarious work self-employed work injury work disability social security social support Australia Canada SSHRC/CIHR Healthy Productive Workforce Partnership Grant# 895-2018-4009 and #159064 Mitacs Globalink Research Award-Abroad#IT13779 This research was funded by the SSHRC/CIHR Healthy Productive Workforce Partnership Grant (# 895-2018-4009 and #159064) and Mitacs Globalink Research Award-Abroad (#IT13779). ==== Body pmc1. Introduction Self-employment (SE) has emerged as a non-standard, precarious, and contingent work relationship internationally [1,2,3]. The proportion of precarious work, including SE, has been growing rapidly in recent decades due to globalization, dramatic technological advances, the information revolution, and the decline of manufacturing industries [2,4,5]. It has been estimated that non-standard employment accounts for more than 60% of workers worldwide [6,7]. This trend is accelerated by the rising ‘gig’ economy, which is undermining traditional employment relations with secure jobs, predictable, advancement, and stable pay [8,9,10,11]. Of importance, Self-employed (SE’d) workers now comprise 15% of employment in Europe [12] and 10% of the Australian workforce [13]. In Canada, 2.9 million people were SE’d in 2018, double the number in 1976 [14], although this increasing trend has remained stable in Canada for the last decade. In general, women, recent immigrants, and other visible minorities tend to choose SE to meet their needs that derives from traditional social roles (e.g., women as a caregiver and to earn money to support their families, immigrants due to lack of suitable paid jobs) [2]. Mounting international evidence stresses that precarious employment conditions are having profound adverse effects on workers’ safety, health, and wellbeing [15,16,17]. Despite this, SE’d workers are one of the ambiguous categories of working groups who are largely excluded from the workers’ compensation coverage internationally [4]. However, research on SE’d people in terms of their access to social supports systems when they are not working due to injury and sickness is scarce, and, as a consequence, policies geared towards building inclusive workers’ compensation policies, upgrading the social safety net programs, and reforming statuary/legal frameworks often ignore complex interactions and responses within them. Our purpose in this paper is to reflect on how a growing working population of SE’d people access welfare state social support systems when they are away from work due to injury and sickness in the two comparable countries of Canada and Australia- in terms of social, political, and cultural contexts. We take the cases of Canada and Australia, as both countries have key similarities in terms of comparable economies and liberal welfare states [18]. As well, both have social welfare policies that differ by state/province, and each addresses occupational illness and injury via workers’ compensation systems. They also have a similar penetration of the new ‘gig’ economy and a similar proportion of SE’d workers, accounting for around 8–10% of employed people in 2016 [19]. Because of these similarities, a comparative analysis is useful for understanding actions that can support greater sustainability of labour markets and economies of their respective SE’d populations. In this paper, we make three distinct contributions. First, we explore how challenges to defining the status of a worker/SE are connected to accessibility to social supports in general and comparative analysis of two jurisdictions of Australia and Canada that recognize differences (similarities as well) in their social support policies and legal protocols. Second, we unpack the debates around the definitions, classifications, and misclassifications of SE, shedding light on differences between the two countries, convergence and divergence of different stakeholders’ views and perspectives, showing how they define, redefine, and reform the status of SE for the sake of their socio-political interest. Third, we make a snapshot of the social support systems available for workers for the said jurisdictions, where the status and position of SE’d workers are conspicuously designated, by analysing when SE’d workers are entitled to the available support systems, can opt out or opt into the supports; this analysis demonstrates the relative strengths and limitations, and gaps of the existing systems, which provides lessons for both jurisdictions for further policy formulation and reformations. Finally, the paper concludes with policy implications, as this study is prescriptive in nature, that is, it follows a method of analysis aimed at new policy ideas in order to improve the social welfare of SE’d workers in Canada and Australia [20]. In the context, mentioned above, our analysis was guided by ‘interpretive policy analysis’, focusing on meaning-making processes that are contextual, and situation-specific, instead of focusing on general laws or universal principles [21,22]. 2. Literature Review 2.1. Dynamics of SE’d Workers SE’d workers are generally depicted as a special group of homogenous people [5], who possess good health, enjoy the freedom of being their own boss and flexible working hours, do not rely on social security protection, and enjoy greater job satisfaction and improved quality of life [12,23]. They are also described as taking on a high level of personal risk to grow their businesses and creating employment opportunities for others [5,9,12,17]. However, these depictions do not reflect the recent reality of the SE’d [12]. Surprisingly, very few attempts have been made in order to investigate systematically how these new forms of employment impact the SE’d in the face of occupational injury and disease [4]. This is despite a growing body of research that argues that the rise of precarious employment, including outsourcing, downsizing, and small business, adversely affects workers’ occupational health and safety [24,25,26,27,28]. A clear dark side of this SE labour market exists in that a significant number of SE’d workers are compelled to undertake this type of work due to unemployment, scarcity of alternatives, and everyday financial hardships [2,5,12]. As argued by The Law Commission of Ontario [2], all SE’d workers should not be treated in the same manner: “The experiences and vulnerabilities of this group range from billionaire entrepreneurs to taxi drivers working 90 h a week simply to pay their bills and includes many people who are gaining income from self-employment activity alongside their main job” (p.75). As such, SE does not always mean self-sufficiency. Instead, some SE’d workers, with low earnings, are precarious workers at risk of poverty and social exclusion [29]. In addition to income-based poverty, a key challenge facing SE’d workers is what happens when they are unable to work due to illness or injury/disabilities, whether on a short- or long-term basis. This is also connected to poverty but in a different fashion. Some SE’d workers do not expect sick pay, paid annual leave, or a future pension because they are well-off and have adequate savings for the future [17]. Some literature stresses that low-income SE can have a considerable impact on workers’ physical, social, and personal lives (e.g., family relations), promoting a greater risk of injury, illness, stress, and challenges to health care access [2,11,30,31]. Mounting evidence also shows a strong relationship between the precarious job and poorer health outcomes [32], and greater social costs such as the undermining of intimate relationships [15,33]. As well, SE’d workers are at higher risk for certain diseases compared to salaried workers [17]. However, SE’d workers are less likely to purchase health insurance policies in the USA, which may affect their health and wellbeing if they use little or inappropriate medical care [17,34]. 2.2. Social Security Systems Protecting SE’d Workers: The Inclusion/Exclusion Game Globally, many policies and much legislation, such as workers’ compensation, employment insurance, and state pension plans, exclude SE’d workers. Indeed, Quinlan [4] noted that SE’d workers are fully excluded from most countries’ workers’ compensation coverage policies. In some countries (e.g., Estonia, Latvia, Portugal, and the Slovick Republic), 40–50% of precarious workers are less likely to receive any form of income support when they are out of work due to injury, sickness, or any form of impairment [10]. The ILO’s (2020) study of G20 countries found a social protection coverage gap for SE’d workers in many of the countries [19]. This report recommended several measures to protect the SE’d, including preventing the false classification of workers as SE’d and reducing the ‘grey zone’ of vague employment status [19]. However, some welfare states play pivotal roles in terms of protecting SE’d workers. For example, Finland provides a broad support system to workers regardless of employment status, in which SE’d workers are covered with earnings-related pension schemes (old-age pension, disability pension, survivors’ pension) and have access to a universal basic social security system (parental and sickness benefits, housing, and unemployment benefits) [35]. In the UK, there was a ‘policy vacuum’ observed in social security policy for SE’d people in the 1980s; however, SE’d people were included in state insurance systems and mainstream income-related benefits as of the 1990s [36]. Despite this, they are still excluded from many benefits systems in the UK, such as income supports, housing benefits, council tax benefits, family credit, and disability working allowances, due to administrative weakness [36]. The British perspectives are consistent with Finland’s estimation that there is a gulf between tax declared-income and pension declared-income scheme for self-employed workers (under-insurance) within the statutory pension; they pay too little to contributions, leading to inadequate protection against personal risks [35]. Spasova, et al. [37] illustrated an interesting correlation between SE’d people’s access to statuary social protection systems and types of welfare regimes in 35 European countries. They reveal that in countries with social democratic regimes (e.g., Finland, Denmark, Iceland, Norway, Sweden) where social protections depend on ‘general taxation’, the SE’d workers have access to all statuary schemes and are treated as salaried workers. They are also treated in a similar manner in the Liberal regime countries (e.g., Ireland and UK) in terms of social protection for the self-employed worker. However, the countries whose schemes rely on ‘heavy taxations’ make distinctions between salaried and self-employed workers in terms of access to social protections; while salaried workers can access both means-tested benefits and insurance-based benefits, SE’d workers can access means-tested, but often at a low level. Interestingly, some countries, such as the Corporatist (Austria, Belgium, and Germany) and Southern European regimes (Italy, Spain), show a variance in statutory access to social protections, including insurance schemes, and these differences not only exist between SE’d and salaried, but also within different SE’d patterns. In our view, this study shed new light on (which previous studies had not addressed), the uneven access to statutory social protections being brought about by the complicated and robust dynamics of SE’d themselves in terms of their actions and nomenclature. Overall, Spasova et al.’s analysis shows that although the welfare countries show comparatively comprehensive social protection for self-employed people in terms of the access to (basic) pension and (basic) health insurance, they still have social protection coverage gaps for SE’d in countries [38]. To put it another way, although welfare economies are supportive of protecting SE’d workers, they still struggle with administrative and bureaucratic shortcomings in terms of supporting SE’d workers with social protections. As such, this exclusion of SE’d workers advances a central question to the agencies, employers, policymakers, government stakeholders, and workers: how do the established norms and existing legislative protocols fit with the changing labour market [39], with the special reference to SE? However, without social safety nets, many lower-income SE’d workers are unable to ensure their house rent, medical costs, food, and future security (e.g., retirement pension). Similar to employees in standard employment, they may encounter the same level of anxiety, stress, and illness due to being in work or when out of work. In this context, the absence of a social safety net can perpetuate their distress. Although a growing body of research sheds light on SE’d workers in terms of their health and well-being, social mobility, and racial and gender discrimination [1,31,40,41,42,43], very few research or policy reports consider SE’d workers in terms of their social security and supports [2,5,44]. Moreover, with some exceptions [45], a focus on work disability of SE’d workers in legislation (e.g., labour laws), policy (e.g., workers ‘compensation), and academic research has been largely ignored. As such we know little about the role of government and policymakers in terms of providing supports to SE’d workers [45]. 3. Methods We adopted ‘interpretive policy analysis’ [21] as a methodological framework, which is a widely used approach for policy analysis or policy research [22,46,47] and involves analyzing public policies, as a form of text or representation of social actions. This approach focuses on contexts and meaning-making processes that are situation-specific, instead of focusing on general laws or universal principles [22]. This approach then helps us to interpret and establish relationships between different issues, develop arguments, and eventually draw a cogent conclusion. We collected and analysed a range of secondary data related to work disability policy and practice in Canada and Australia. We focused on ‘work disability policy’, which is diverse policies connected to workers’ compensation, sickness and disability policy, and the legal and regulatory protocols and frameworks of social security [39]. The search for documents was performed in several phases. Official data, legal, and policy texts from both countries were used (i.e., material generated by governments and their agencies). These were identified using the Google search engine and by visiting libraries of the two universities—the University of Waterloo and the University of New England in Canada and Australia (Table 1). Apart from the established databases, Google was used because it is a popular tool for seeking specific information and relevant outcomes for a typical query [48]. In addition, observations and commentaries (e.g., updated statistics) from global agencies such as the World Health Organization, the World Bank, and the International Labour Organisation were utilized (Table 2). Then, the lead author identified possible peer-reviewed literature through a systematic search of five databases including PubMed, SCOPUS, PSYCHINFO, ABI/INFORM, AND CINAHL (See Appendix A for Keywords). A review of titles and abstracts for articles relevant to SE, work injury, and return to work was conducted. In all, 22 articles were identified as relevant (Table 2). Of these, three articles (one for Canada, two for Australia) focused on Australia and Canada. After that, the lead author searched (the second search) the SCOPUS database separately, focusing on Australia and Canada (See Appendix A for keywords). Of 93 documents identified, three articles were relevant to our study. Finally, we also searched ‘Google scholar’ and ‘google.com’ separately using refined and specific key terms related to Canada, Ontario, Australia, and NSW, including SE in Canada/Australia, SE in Ontario/NSW, workers compensation in Canada/Australia, employment Insurance in Canada/Ontario, personal accident insurance in NSW, in order to get more specific peer-reviewed articles and grey literature related to Canada and Australia. This resulted in seven relevant documents (out of 144) for inclusion in our synthesis (Table 1). The final selected documents obtained from both searches-systematic and non-systematic were examined following Dixon-Woods and colleagues’ processes of quality assessment, data extraction, and data synthesis [58,59]. They underline the importance of assessing the quality of the articles to be included in the review and analysis in terms of their overall relevance to facilitating understanding of the topic under study [3]. Systematic data extraction focused on demographic information, research questions, the purpose of the study/report/review, year of publication, place of publication, methods, main findings, and sector of SE. This approach resulted in a comprehensive overview of the selected articles and documents and facilitated analytical exchanges between the authors. A summary description of the documents is in Table 1 and Table 2. Data were synthesized by recurring concepts, which ultimately contributed to themes. A process of constant comparison and negative case analysis guided the synthesis, which involved assembling issues and grouping topics under common areas. For example, authors might use dissimilar words, but be addressing a similar general concept (e.g., SE, independent contractor). The negative case analysis focused on studies that appeared to contradict each other. For instance, the Canada Employment Insurance Commission (2014) reported that SE’d women (25 and 44 years) made 90.4% of all special benefits claims, mostly for maternity and parental benefits. However, according to Hilbrecht [30], a significant number of entitled SE’d workers, irrespective of gender, do not seek and claim compensation mainly due to a lack of information about the supports [30]. In these cases, we attempted to reconcile these contradictions by noting contexts and methods. In this example, the negative case analysis directed attention to the reasons why poor benefit claimant rates among SE’d exist, which provided insight into weaknesses in existing policies with supporting SE’d workers in both Canada and Australia. This research followed three phases of synthesis leading to the final themes. First, an open-coding system was used to analyze the documents. This helped us to reflect on the overall patterns of our data, including identifying the repeated and common themes. In the second phase, open codes were re-reviewed and focused codes were generated. A focused code is a pattern or category that groups two or more open codes [77]. Our focused codes then led to three major themes, together with sub-themes, focused on: (i) defining self-employment: contested views; (ii) the relationship between misclassification of SE and social security systems; (iii) existing social security systems for workers and SE’d workers: Ontario and NSW. The lead author met and consulted with senior authors on a regular basis to discuss ongoing analyses of findings and to challenge preliminary interpretations, which facilitated thorough interpretations of the findings. ijerph-19-05310-t002_Table 2 Table 2 Description of literature identified by the systematic search. Articles, Year (Reference) Country Method Major Findings McNaughton, et al. [78] USA Quantitative -Vocational rehabilitation counselors and support personnel should advocate for an appropriately challenging educational program -Vocational rehabilitation and support personnel can offer an important work-place perspective on the individual’s communication skills and priorities for intervention -Vocational rehabilitation counsellors and support personnel should help identify a wide variety of part-time or ‘work-experience’ jobs while the individual who uses AAC is still in school. Arnold and Ipsen [79] USA Policy analysis -Unlike in the past, when counsellors assumed a great deal of responsibility for developing the business or writing the plan, now the counsellor usually facilitates the process, and the consumer develops the business and business plan with the help of external business developers. Most state agencies will not support development of a nonprofit business. Larson and Hill [80] USA Quantitative -SE’d adults and those working in small establishments are less likely to be offered insurance. -Only in the most rural area does working in agriculture, fishing, and forestry have a statistically significant effect, controlling for other factors such as self-employment. Hartman, et al. [81] Netherlands Quantitative -In the Netherlands, there is no social insurance for SE’d persons during the first year of sick leave. After 1 year of sick leave, social insurance provides compensation for loss of income to a maximum of 70% of the statutory minimum income. -This financial gap can be bridged by an insurance policy. -An estimated 63% of self-employed farmers take out an insurance policy with a private insurance company, which provides supplementary compensation for loss of income if they are unable to work due to illness or an accident. Rizzo [82] USA Policy analysis -Identifying the supports an individual may need in the employment setting requires a critical and unabashed look at skills and capacities. Essential to this process is the inclusion of the consumer in all aspects of need-assessment, decision-making, and plan development. -Opportunities to manage the business and perform business-related tasks allows the consumer to develop SE skills, as long as these are truly managerial and decision-making in nature. Fossen and König [83] Germany Quantitative -Those who enter into SE are more often male, have had a SE’d father, and are more willing to take risks than the other paid employees. -They are more often active in the business services and construction industries and less often in manufacturing and public and personal services. -The health insurance system may provide incentives to enter SE for persons whose income is not high enough to opt out of the SHI as a paid employee. For them, self-employment lifts the barrier to PHI. Hilbrecht [30] Canada Qualitative -Many were unaware of EI special benefit program, which provided maternity leave, parental leave, compassionate care leave, sickness benefits, and benefits for parents of critically ill children to self-employed people. -Different types of informal support often existed simultaneously: family support, spousal support (emotional and income support). -Some women expressed gendered assumptions about men as providers who could offer a financial safety net if their business floundered. Barber III and Moffett [84] USA Quantitative -The probability that a SE’d individual in a state that had implemented a subsidy would be covered by private insurance increased by about 4 percentage points after the subsidies were implemented when compared to the self-employed in the control states. -The subsidies were not enough to increase the probability that an individual in the treatment states after the policies would decide to become SE’d. -The determinants of the choice to become SE’d involve much more than the cost of health insurance. Grégoris, et al. [85] France Quantitative -SE’d workers have a higher morbidity than employees. Conversely, the SE’d group had greater task variation, which might reduce morbidity effects. -The lack of occupational health services also contributes to this difference. -Need for occupational health services for self-employed workers, with occupational health surveillance and prevention strategies in order to reduce occupational risks. Sharp, Torp, Van Hoof and de Boer [12] European region Commentary Evidence is lacking on how best to support SE’d survivors to (re-)engage with work or business after cancer. Most interventions to enhance cancer survivors’ work outcomes have been pertinent (only) for salaried employees and have focused on return to work. Wijnvoord, et al. [86] Netherlands Quantitative -Higher educated SE’d showed that the hazard of experiencing a new period of sickness absence increased with every previous period. This effect was found for both sexes and also for most diagnostic categories of the first period of sickness absence. -Musculoskeletal disorders and mental and behavioural disorders were the most frequent causes of long-term sickness absence. -Locomotor disorders were more frequent, but mental disorders lead to longer duration of sickness absence. Ashley and Graf [87] USA Quantitative -Causes for choosing SE: a lack of decent wages and promotion opportunities, for intolerance of mental illness symptoms such as panic attacks, anxiety, and depression; difficulty in obtaining work accommodations; long hours; and being let go due to disability. -Participants noted their health challenges were easier to manage when self-employed, and they experience lower levels of stress and greater flexibility. Ostrow, et al. [88] USA Quantitative -SE is acting as a financial bridge or means of exploring career opportunities. -Most respondents had not accessed Social Security’s back to work programs. -While SE’d individuals struggle to access these benefits, they also have better access, or find these programs more attractive, than individuals with psychiatric disabilities seeking wage employment. Quinlan [15] Australia Qualitative -17.7% of the workforce mainly are SE’d (two-thirds of whom are concentrated in four industries: agriculture, fishing and forestry; construction; retail; and property and business services), unpaid helpers and volunteers–were not covered by workers’ compensation. -Where workers were deemed to be SE’d subcontractors by industrial relations and taxation law, they presumed they were denied workers’ compensation. -Another problem determining eligibility occurred where workers changed employment status (e.g., from employee to self-employed or small employer and then back) on a regular basis (in response to aspirations or bankruptcy, principal contractor demands or shifts in the business cycle). Rietveld, Van Kippersluis and Thurik [17] USA Quantitative -SE is, to a certain extent, influenced by genetic factors. It is perceivable that the same genetic factors influence both SE and health (such a mechanism is called pleiotropy genetics) Gevaert, De Moortel, Wilkens and Vanroelen [31] European regions Quantitative -Farmers and dependent freelancers and own account workers have worse mental well-being than medium to big employers. -Entrepreneurial characteristics are able to explain mental well-being differences between types of SE’d -Country-level perception of entrepreneurs influences their mental well-being. Beattie, et al. [89] Australia Qualitative SE’d farmers are often not covered by workers’ compensation insurance and therefore, if they have not purchased their own income protection policy, have no means for receiving financial assistance during the recovery phase. Yoon and Bernell [16] USA Quantitative SE’d individuals in the US are physically healthy, or healthier than wage-earners, despite the relative lack of health insurance among SE’d persons as compared to wage-earning persons. -No significant relationship between SE and mental health. -Individuals do not experience a greater barrier of access to necessary health care, despite a higher rate of being uninsured among SE’d individuals in the US, the SE’d may be able to finance their own health care using their incomes or accumulated savings. -SE’d are more likely than wage-earning individuals to engage in health- promoting activities, perhaps due to greater flexibility in making room for health promotion activities into their schedule. 4. Findings 4.1. Defining Self-Employment: Contested Views Prevailing definitions and conceptualizations of SE are contested and vary, which reflects that there is not one type or state of SE. Additionally, the existing legal protocols, in Canada and Australia, dealing with employee and employment minimally defines SE, as is shown in the Table 3. There is a debate around SE and whether it brings benefits or barriers for sustainability in terms of health [17], facilitates life-work balance [30] and is adequate in terms of income [90]. Different stakeholders pertinent to employment, tax and revenue management, workers’ compensation management, social supports agencies, judiciaries, politicians, public policy makers, researchers, and academics have been defining SE and naming this employment system from a variety of perspectives. The intentions and motivations differ behind these differing views, as they are derived from political (e.g., political public policy), ethical (e.g., social justice), and philosophical (e.g., neoliberal agenda) grounds. Thus, available literature [4,49,54,62,91,92] uses different names for SE interchangeably as depicted in Table 4. These multiple terms make SE challenging to define, both conceptually and empirically [30]. According to Cohen, Hardy and Valdez (2019), SE is not a fixed category/pattern and is contingent on changing structural relationships, which are subject to the mode of production and economy (e.g., manufacturing, service, and digital economy, or labour market, and economic status of society) [92]. For example, during the (2007/2008) global economic recession, three patterns of SE emerged [92]. First, while it is decreasing globally, the rate of SE’d workers is increasing in developed countries [92]. Second, SE appeared with new space (e.g., digital platforms), names (e.g., disguised wage work, ‘gig’ work, and contracting), sectors, and industries (e.g., creative industries). Third, there is an emerging ambiguity observed in the legal definition of SE as much as this term is increasingly popular [92]. This ambiguity or complexity of classification/misclassification is reinforced by newly emerging labour market traits and sectors, such as ICT based labour market, globalized labour market, and neoliberal labour market. For example, traditionally, ‘own account’ workers, such as agriculture, forestry, fishing, retail trade, and crafts are common SE’d workers over the world. Similarly, SE’d workers from the sectors, such as building and construction, road and transport, media (e.g., journalist and photographer), actors, musicians and performers in the entertainment industry are also common sectors of SE. However, the non-traditional sectors for SE’d workers, such as graphic design, music composition, and information technology (IT) specialist, and software developer are recent developments due to the advent of globalization and technological advancement. These ever-changing work arrangements make it difficult to identify who is SE’d. On the one hand, the Australian Bureau of Statistics tried to draw a line between independent contractors and other business operators in order to paint a simple picture for SE: they can either be employing or non-employing. According to the Australian Bureau of Statistics (ABS), the ‘independent contractors’ are owner operators who personally provide a service for clients under a commercial contract (e.g., a courier owner-driver contracted to perform a specific delivery run). The ‘other business operators’ are different from ‘independent contractors’ in terms of two factors: they provide the service directly to the public rather than under a client contract (e.g., a taxi operator); and/or they manage others to perform the service rather than provide the service personally (e.g., an owner-operator of a trucking fleet that spends more of their time managing other drivers than driving trucks). Despite these demarcations of definition, the ABS still argues that these categories remain unclear. For instance, if the courier owner-driver, mentioned above, worked in an ad hoc manner with different daily changing clients, they can be identified as both an independent contractor and an other business operator. In Australia, ultimately the status of worker–whether he/she is employee, self-employed, or independent contractor–has evolved into disputed and contestable cases before the courts. Small business or solo traders are also often understood as SE’d. In practice, the smallest businesses are likely to be operated and/or managed by someone who is SE’d. However, it is unclear what percentage of small business owners regard themselves as SE’d, and there is no agreed standard to define their size and traits to be SE. According to Australian Business Statistics, small businesses include firms that are non-employing, microbusinesses employing less than five people, and other small businesses employing less than 20 people. On the other hand, Statistics Canada (2015) has more clear-cut distinctions in this context: owners of incorporated and unincorporated business, farm, and professional practices are deemed as SE’d. The latter groups are also SE’d, though they do not own a business, such as babysitters. Incorporated groups may be of two types: those who have paid helping hands and those do not have such helpers. Statistics Canada (2015) also includes in SE’d groups those who help other family members’ business, farm or professional practices, without receiving salary/wages. The self-employed include working owners of an incorporated business, farm or professional practice, or working owners of an unincorporated business, farm or professional practice. The latter group also includes self-employed workers who do not own a business (such as babysitters and newspaper carriers). Self-employed workers are further subdivided by those with or without paid help. Also included among the self-employed are unpaid family workers. They are persons who work without pay on a farm or in a business or professional practice owned and operated by another family member living in the same dwelling. They represented in 2011 about 1% of the self-employed. To put the analysis succinctly, Australia seems conservative in demarcating the multidimensional features of SE. Although it distinguished independent contractor from the business operator, it still remains unclear. However, Statistics Canada is liberal to fragments the SE, by clearly defining incorporated and unincorporated SE. Finally, we view, across all the national contexts and differences, the SE through a broader lens, as individuals who work for themselves instead of working for others like paid workers. Many may work alone, but others may have their own small business with or without employees. In this sense, there is an inevitable overlap between employers, self-employees, and employees. In short, SE is a diverse work arrangement, encompassing occupations ranging from highly paid professionals or billionaire entrepreneurs to low-skilled workers operating a business on their own. 4.2. Relationship between Misclassification of SE and Social Security Systems SE’d workers are often misclassified because employers seek to reduce legal commitments and compensation. The potential (mis)classification of workers in dependent employment relationships such as SE’d has been described by socio-legal scholars, as well as the European Commission and the International Labour Organization, due to the rising ‘gig’ economy in certain industries, such as construction industries [44,93]. Not surprisingly, rights and obligations are less entertaining for SE’d workers than for regular employees [10,44,93,94]. In addition, sham contractors is a term which is widely used to misclassify SE’d workers. This refers to people who are wrongly regarded as independent contractors and who are identical to employees [93]. This problem is recognised by some authorities. For instance, the Australian NSW Road Transport Authority has prescribed a substantive system of collective rights in order to resolve disputes overcompensations, introducing a new Road Safety Remuneration Tribunal, where minimum standards can be set for all truck drivers, whether they are employees or SE’d [95]. In a nutshell, if employers misclassify employees as self-employed/independent contractors, in turn, they are denied access to critical benefits and protections in Ontario, Canada, and workers agree because they want to ensure certain income [2]. The Australian (NSW) labour market encounters similar experiences. 4.3. Existing Social Security Systems for Workers and SE’d Workers: Ontario and NSW Both Ontario and NSW have multiple mediums to support their citizens as well as workers in terms of government and non-government agencies by involving different stakeholders, such as hospital, ministries of governments, insurance boards and companies (Table 5). Generally, Australian and Canadian social security systems are different from each other because, unlike Canada, Australian systems do not depend on social insurance or the workers’ previous contributions, and their system relies on general government revenue [76]. 4.3.1. Supports Available to People Regardless of Employment Status In Ontario, Canada, people, regardless of prior employment status, are entitled to get support from the Ontario Disability Support Program (ODSP), if they are 18 years and older, disabled and need support to meet living expenses, and their family income and assets are below a cut-off line. As such, eligibility is assessed both financially and medically. ODSP offers financial assistance to claimants and their family for essential living expenses, prescription drugs, vision care, help to find jobs and training to continue their jobs. Similarly, ‘Ontario Works’ provides financial and employment assistance to people, regardless of the nature of the jobs, who are 16 years and older, and in need of meeting basic living expenses for themselves or their family (Ontario Ministry of Children, Community and Social Services, 2019). They are provided with financial assistance, including income support to help with the costs of basic needs, health benefits for clients and their families, and employment assistance to help clients find, prepare for, and keep a job. In terms of Medicare, citizens and permanent residents in Ontario are entitled to the Ontario Health Insurance Plan (OHIP) in order to use medical facilities, cover appointments with doctors, hospital emergency rooms, medical tests and surgeries. Every Canadian citizen and permanent resident including their families, except people from Québec, which has its own plan, are entitled to have a Canada Pension Plan (CPP), covering partial replacement of earnings during retirement, disability or death. Benefits include a retirement pension, disability benefits, survivor’s pension, death benefits, and children’s benefits. To sum up, ODSP does not require contributions from workers, but it is means-tested, whereas OHIP and CPP are not means-tested. Workers have to contribute to a fund to be eligible for CPP, but not for OHIP. Regardless of place of injury either in the course of work or outside of work, in NSW, Australia, anyone can have access to supports from icare, self-insurance, and specialised insurance, which are managed/implemented by SIRA (State Insurance Regulatory Authority). These supports are provided to all Australian residents across social assistance and mandatory occupational pension systems, such as old age pension, disability pension, survivor’s pension. The social assistance (cash sickness benefits) and universal (medical benefits) systems cover sickness and maternity benefits, temporary disability benefits, permanent disability benefits, and workers’ medical benefits, and unemployment and family allowances, involving compulsory insurance with a public or private carrier under different schemes established and run by state and territory governments. However, people in NSW, including the SE’d, are required to pay a Compulsory Third Party Premium (CTP) when a vehicle is registered for motor accident insurance, which is managed by SIRA under a Compulsory Third Party (CTP) scheme, which covers injury involving motor vehicles. The benefits coverage of this scheme includes compensation for people who are killed or injured. Compensation can also include hospital, medical and rehabilitation costs, loss of earnings, and pain and suffering. Some aspects of compensation are reliant on establishing fault by another party and some are payable regardless of fault. The third-party insurance component of the scheme (CTP) is underwritten by five insurers. Insurer pricing and behaviour is monitored and regulated by SIRA. Finally, the National Disability Insurance Scheme (NDIS) is also a federal government funded program for disabled (irrespective of causes) people from 7 to 64 years old living in Australia with permanent and significant disability, and it may be the main supplier of benefits, or additional to other state funded supports. Overall, most government benefits are income-tested and asset-tested, implying that workers’ entitlements reduce as resources increase [76]. 4.3.2. Supports Available That Self-Employed Can Opt into In Ontario, an Employment Insurance special benefits (EI) exist, which SE’d workers in Ontario can opt into if they choose to register with CEIS (Canada Employment Insurance Commission). This provides benefits, one year after registering and paying monthly premiums, including maternity, parental, sickness, compassionate care, family caregiver for children, and family caregiver for adults (Government of Canada, 2013). In this case, a SE’d worker who claims for compensation may receive up to 55% of his/her average weekly pay up to a maximum annual limit. However, if business revenue is generated during their leave, the funds are reduced accordingly (Service Canada, 2014). According to a report by the Canada Employment Insurance Commission (2014), SE’d women between the ages of 25 and 44 years old made 90.4% of all special benefits claims, mostly for maternity and parental benefits. According to Hilbrecht [30], there are some evidence that a significant number of entitled SE’d workers do not seek and claim compensations mainly due to lack of information about the supports [30]. In Australia, including NSW, SE’d workers can opt into the work injury scheme if they voluntarily participate by paying premiums for self-insurance. This covers temporary and permanent disability benefits, and workers’ medical benefits as well as unemployment and family allowances. In addition, SE’d workers in NSW can buy personal injury/accident insurance, though it is not connected to CTP. In addition to other injury, it may cover insurer for injury in the event of a motor vehicle accident, regardless the fault. It may also cover gaps or limitations in the private health insurance shows. Generally, it is still challenging to define how many SE’d workers are under coverage of government and private supports because the existing evidence pertinent to SE and compensation regimes is scarce, conflicting, and partial [17]. There is evidence that precarious workers, including SE’d, are less likely to make compensations claims, compared to regular employees [4]. SE is one of the four categories of employment-unskilled workers, occupationally mobile, SE’d, and geographically isolated-in terms of the highest underreporting for compensation claims, while 27% injured workers did not submit claims for compensation, as found in a study in Queensland, Australia, for example [4]. The Australian Bureau of Statistics also investigated why a large number of injured workers do not claim for compensations, and fund that 14.4% of workers are SE’d and they think they are not eligible for compensations [96]. In some Australian jurisdictions, there are very uneven systems of coverage for SE. For example, some SE’d workers are included in compulsory coverage, but other forms of SE have the option of voluntary cover, private accident insurance, or nothing. Of importance, around 20% of SE’d workers have no coverage, whatever their pattern of work [4]. The situation is more complicated in Queensland where compulsory coverage for some SE’d workers and a voluntary option for others was curtailed in 1997 [4]. In addition, occupational health and safety statistics mask the statistics of SE’d workers in mining industry in Australia [4]. Thus, SE’d workers are excluded from workers compensation claims, as well as those who have coverage but do not lodge claims because of ignorance, lack of information, financial pressure to keep the job [24]. Some studies also found that under-insurance and non-payment are responsible for being reported in the documents (e.g., NSW, Australia), and it is done intentionally in order to manipulate the classification of work and evade the tax and compensation [4]. To sum up, SE’d workers in NSW have more access to schemes based on voluntary participation than do these workers in Ontario. As such, supports are provided in Ontario irrespective of workers’ employment status, whereas some are means-tested (e.g., ODSP) and some schemes requires contributions from the workers (e.g., CPP). Similarly, workers in NSW regardless of their employment status have also access to several types of social supports. Of these, some of the schemes expect contributions from the workers (e.g., motor accident insurance). However, Ontario has limited provisions including the EI special benefits program, which provides SE’d people with a significant number of benefits in return for paying a premium, though it fails to attract low-earning SE’d workers because they cannot afford it with the high rate of premiums. In terms of mandatory schemes, both jurisdictions have multiple alternatives, but each provide limited provisions for SE’d due largely to complicated eligibility criteria. 5. Discussion Currently, key challenges with SE are in its definition, conceptualization, and classification. Mounting evidence shows that SE is often misclassified and mistakenly defined [2,4,49,54,62,91,92,97]. Consistent specification of the status of SE across employment frameworks and classifications is needed in order to design eligibility requirements for social supports and compensation for a work injury or disability. At the same time, the heterogeneity of SE’s needs to be recognised [53]. For instance, a growing problem exists with organisations, such as digital employment platforms, classifying their workers as SE’d for purposes of tax and insurance premium evasion. Our study reaffirms the need to reconsider the ambiguous position of SE’d in the current labour market, as the SE’d include a range from low-income digital platform workers to successful entrepreneurs [98]. As most government bodies have homogenised support systems wherein SE’d are recognised as only one category of worker, deserving SE’d workers become deprived of government supports when they are in need. Our study found that the current ‘objective’ evidence framing who is SE’d overlooks the push/pull factors that are critical to understanding their positioning in the SE labour market. For instance, workers may be ‘pushed’ in by lack of employment alternatives; and they might be ‘pulled’ in by the lure of neoliberal notions of freedom and autonomy [3]. In this way, the labels of ‘autonomy’ and ‘healthier’ are not realistic for SE’d workers because the conventional measurement and assessment of well-being of SE’d workers overlooks the diversity of SE and self-exploitation [53,99]. Against this backdrop, a central question is ubiquitous: who seeks government supports? The answer to this question lies in a robust understanding of the diversity of SE’d workers, as paramount for better (re)form policies in order to provide appropriate social protection for SE’d [10,100]. However, a barrier to accomplishing this work is a dearth of data related to SE. To date, it seems that policies in Canada and Australia continue to visualize SE’d workers as the highly paid variety who may not need financial support when ill or injured. However, many studies have documented that this assertion about SE’d workers is an over-generalization and refers to a group of people who are financially prosperous, younger and highly educated, and who became SE’d for opportunity rather than necessity [7,53,100]. In this context, we argue that a significant number of SE’d workers living in Canada, Australia, and elsewhere are poorly paid and need income support during their absence from work due to injury and sickness. The invisibility of these precarious SE’d workers in policy is amplified by their vague status in policy formulations [3,100,101]. In addition, our study illustrates a strong relationship between precarious jobs and poorer health outcomes [32,102], and numerous social costs [15,33]. For example, SE’d workers are at higher risk for certain diseases compared to salaried workers [3,7,17]. However, this ‘employment type and health’ interplay is not always straightforward; rather, it is subject to the type of welfare state. For example, a systematic review suggests that Scandinavian welfare regimes show better or equal health outcomes for precarious workers compared to their counterparts (salaried, permanent employees), whereas precarious workers from other welfare regimes (e.g., Bismarckian, Southern European, Anglo-Saxon, Eastern European, and East Asian) show worse health outcomes compared to salaried and permanent employees [37,69,103]. Although Canada and Australia are well-developed welfare states, several studies demonstrate that precarious employment, including SE, plays a pivotal adverse role on people’s health and well-being [31,104,105,106]. Our review reveals that both Ontario and NSW have limited social security provisions for SE’d workers when injured, ill or out of work (Table 6). In Ontario, SE’d workers are supported under the systems of the Ontario Disability Support Program, Ontario Works, Ontario Health Insurance Plan (OHIP), Workplace Safety and Insurance (for construction workers only), Canada Pension Plan, and Employment Insurance special benefits. However, there is uneven accessibility to available supports. For example, ODSP is means-tested, whereas OHIP and CPP are not. Because people in Ontario have to contribute to a fund to be eligible for CPP and EI special benefits, in practice this means that many low-earning SE’d workers, such as ‘gig’ workers, do not participate because they cannot afford the premiums [100]. As such, these ‘gig’ workers are neither able to pay the premium nor be eligible for government accommodations [69]. This is a potential threat to the Canadian welfare state. Similar challenges exist elsewhere. For example, in Spain, according to Corujo [107], ‘Uberisation’ of work devastated labour and social security regulation, making the state powerless to undermine the political, legal, and financial foundations of welfare states. One more gap identified in our review is that SE’d employed people are not always aware of existing government provided support [2,30]. Indeed, other Canadian studies found that when SE’d workers need extra support, they rely heavily on informal support systems, such family members and friends [30,100,108]. Although some SE’d rely on personal savings [30,98], many lower earning SE’d workers cannot save enough to support non-working time [30]. In NSW, most of the supports, such as old age benefits, disability benefits, unemployment allowance etc., include SE’d workers, together with compulsory premiums to access work injury and personal injury/accident insurance. Overall, the Australian social security systems for workers, including SE, is remarkably different from other OECD countries, including Canada because Australian systems do not depend on workers’ previous contributions to be eligible for supports [76]. In our view, these differences might create bureaucratic complications for Canadian claimants, irrespective of employment status. Both jurisdictions, NSW and Ontario, have strengths and drawbacks in terms of support systems available for SE’d workers. On one hand, Ontario’s SE’d- focused special EI is comprehensive, and covers maternity, parental, sickness, compassionate care, family caregiver for children, and family caregiver for adults (Government of Canada, 2013). On the other hand, most of NSW’s systems are narrow and constrained by multiple conditions. For example, NSW’s workers’ compensation and work injury covers only injury, not sickness or disease, and the injury needs to be caused by work. It is noteworthy that proving benefits for work-related injury for SE’d people is challenging because their working relationships and arrangements often blur, unlike those of many regular employees. For example, a SE’d person with a home office may have difficulty distinguishing a home-related versus a work-related accident. Another important difference between the two jurisdictions is that SE’d workers in NSW are entitled to apply for unemployment allowance, which is solely provided by government, whereas this is not possible for SE’d workers in Ontario. Similarly, SE’d people in NSW who have limited income can apply for sickness and maternity benefits, and family allowances. However, SE’d workers in NSW are excluded from other supports, such as old age pension, disability pension, survivor’s pension. SE’d workers can pay for private insurance with sickness and injury coverage in Ontario. However, when the WSIB imposed mandatory insurance on the SE’d construction workers in Ontario in 2013, they encountered protests from independent contractors who did not want to be required to pay this insurance premium that was more costly than what they had been paying for private insurance and that did not cover non-work-related illness and injury [109]. In our view, however, this overlooks the reality that increasing numbers of SE’d workers are low earning and need income and health protection [109]. Government provided schemes provide stronger protection than private ones, such as workers’ compensation providing income support through the course of life, if needed. Further, several Eurocentric reports expressed concern that private insurance may exacerbate poverty and inequality, including gender gaps, because it has a limited capacity for ‘risk pooling and redistribution’ compared to social insurance [7,98,100,110,111]. In this context, where support systems are lacking for SE’d workers, they can encounter very adverse situations. In addition, studies show that the precarious employment position of SE’d workers adversely affects their important life decisions, such as marriage and childbearing [98]. Overall, there are ample drawbacks of SE that may outweigh the benefits (e.g., economic growth, flexible schedule), that can affect the quality of family life (e.g., work-life balance, irregular or anti-social work hours, fewer vacation and sick days, negotiating workload), if they have limited access to statutory and social benefits [30]. These concerns, pertinent to social protections, and the future of SE, have also been raised in empirical research in Canada [3,7,100]. 6. Conclusions and Recommendations Regardless of the segment of SE, be it independent contractor, entrepreneurship, small business, startup, unlike employees, the issue of supporting SE’d workers during injury and sickness is an ignored discourse in Canada and Australia. There is a gulf between how the number of SE’d workers are ballooning against the backdrop of the ‘gig’ economy and how these rising working populations lack attention in social security systems in Ontario and NSW. Policies in both jurisdictions appear to be based on the traditional picture of prosperous, well-organized SE’d workers not needing support from the state. However, this is an overgeneralization and a hyper-reality because at present tens of thousands of low paying SE’d workers strive to lead a decent life. Undoubtedly, they face very difficult circumstances when they have to be away from work due to injury or sickness, as this strata of the SE’d population generally cannot afford private insurance. In fact, at present, compensation for SE’d workers in both Ontario and NSW remains deceptive. Work is needed at both the policy and practice level to incorporate the voices of SE’d workers into compensation. Our comparative discussion leads us toward conclusions about what might need to be done to continue with unmasking the illusion of the traditional well-to-do self-employed worker:(i) Although ‘Employment Insurance special benefits’ in Canada are not always used by SE’d workers in Canada due to the financial burden of premium payments, it nonetheless provides an example of a coverage system for SE’d workers that provides temporary income supports for parental, sickness or compassionate support leave etc. This is one way in which SE’d workers are recognized as a cohort. Hence, in the sense of equity, SE’d workers in NSW, Australia, might be treated in a similar manner, but after revisiting the issue of premiums. (ii) Basic income policies may be a solution to providing a basic social safety net to SE’d people, among others. An advantage of this approach is that it draws on the general tax fund rather than relying on taxing incomes of low-wage SE’d people, who are already income insecure [71,112]. (iii) All workers, whether SE’d or not, should be covered by workers’ compensation regimes. Digital platforms such as Uber should be required to pay into this scheme. (iv) For both jurisdictions, emergency income supports can be introduced for SE’d workers so that they can be supported when facing emergency circumstances, including but not limited to natural disaster, pandemic, injury/sickness. In this context, for example, COVID emergency benefits in Canada (CERB, Canada) was a successful program to address and protect SE’d workers. (v) Against the backdrop of a changing labour market in the digital age, SE is inevitable and obvious. A premise guiding policymaking is that SE’d workers should not be at a social security disadvantage relative to employees. (vi) Governments should create explicit policy to deal with SE’d and precarious workers to remove grey zones and clarify eligibility for compensation. (vii) As women and recent immigrants are more prone to be SE’d workers in recent years, childcare for the SE’d deserves special policy attention. (viii) Underreporting of compensation claims is a big issue for the labour market and social safety net policies. A strong social mobilization program may be required in order to reduce underreporting. (ix) A social supports literacy campaign may be introduced by both jurisdictions, using mass media or social media, because most of the SE’d workers in practice are not aware of the available supports systems to which they are entitled. However, there are still some support systems available for the SE’d workers in both jurisdictions. (x) In the case of both jurisdictions, SE’d workers, irrespective of the sector of work, platforms (digital or offline), structure of working relations (solo or paid employees), size of the business/professional clients (small or solo traders) need to be given access to ‘collective bargaining’. These rights should be granted whenever necessary to prevent the contracting party with the dominant bargaining position from exercising a compression of labour standards [70]. In this context, both jurisdictions need to become ‘open’ to reforming the existing employment standards or other regulatory protocols pertinent to employment if necessary. As such, trade unions and businesses agree on a series of workers’ prerogatives, leading to the creation of a level playing field in terms of labour costs and ensuring clients that a company’s success does not depend on lowering working conditions [70]. We are aware of a number of limitations of our study. First, we were dogged by the dearth of data around SE’d workers for both countries. It was a challenge to sort the data for SE’d workers from other precarious workers because most of the documents overlap these segments of employment. In short, we agree with several researchers that SE is poorly documented and understood. Second, in both Ontario and NSW, the labour market is undergoing rapid change and development at both policy and practice levels. Therefore, what we have written about in both places is not static; nevertheless, we argue that the broad themes emerging from our work will be relevant in both places for a significant time to come. Apart from the established databases for scholarly articles and documents, we relied on Google’s search engine to capture grey literature and ongoing government data. As the outcome of Google searches are filtered, we worked diligently to sort out the relevant documents. Despite these limitations, consideration of the issues that emerged from our description and analysis of identifying SE’d workers and compensation or supports for absence for work due to sickness and injury policy and practice in both countries will, we hope, support policy makers, people working in administering workers and compensations, researchers in their task of moving toward a sustainable compensation policy, and the imperative of tackling the gaps in the existing systems. Acknowledgments Authors would like to commemorate late Katherine Lippel, Faculty of Law–Civil Law section, University of Ottawa, Canada, for her precious comments and feedback on the draft of this paper. Author Contributions Conceptualization, T.H.K. and E.M.; methodology, T.H.K. and E.M.; validation, T.H.K.; data extraction T.H.K.; formal analysis, T.H.K.; resources, T.H.K., E.M. and D.D.; writing—original draft preparation, T.H.K.; writing—review and editing, T.H.K., E.M. and D.D.; supervision, E.M. and D.D.; project administration, T.H.K., E.M. and D.D.; funding acquisition, T.H.K. and E.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Appendix A (italic terms were used for the second search): Self employ, independent operator, ‘gig’ Work, ‘gig’ employ, entrepreneur, employment without employ, independent contract, dependent contract, disguised work, bogus work, false work, own account self-employ, solo self employ, solo self-employ, stable own account self-employ, own boss employ, own boss work, unincorporated self-employ, dependent self-employ, economically dependent self-employ, health, injury, disability, impairment, stress, well-being, wellness, long and irregular working, flexible working schedule, work-life Balance, access to care, access to health care, body mass index, physical health, mental health, diabetes, high blood pressure, high cholesterol, arthritis, return to work, RTW, work reintegration, sick leave, pension, insurance, vocational rehabilitation, disability insurance, sickness absence, retirement disability pension, and public health insurance. work disability policy, workers rehabilitate, occupational safety regulations, social safety net programs, Australia, Ontario, Canada. ijerph-19-05310-t001_Table 1 Table 1 Description of literature identified by the non-systematic search. Author, Year (Reference) Main Focus Method Country, Sector L.C.O., Ontario [2] Providing comprehensive provincial strategy and recommendations based on Identifying vulnerable and precarious workers, employment standards, and related legislative reformations Review/policy analysis/classical legal analysis Canada, any type Wall [1] Examining the experiences of SE’d nurses as self-employment in professional caring work. Qualitative Canada, Nurse Bögenhold [49] Elaborating the heterogeneity of SE Review Global, any type Weil [50] Providing an overview of core elements comprising fissuring workplaces. Review Global, any type Yssad [14] Providing statistical overview of SE Review Canada, any type (ASFA) [13] Providing demographic and economic characteristics of SE’d workers. Review Australia, any type Facey and Eakin [9] Developing a framework for conceptualizing contingent work and its relationship to health. Review Global, any type OECD [10] Discussing how labour market regulations can protect non-standard workers. Review OECD countries Any type Apouey [11] Examining the effect of both self and temporary employment on mental health in the UK. Review UK, any type Taylor, Marsh, Nicol and Broadbent [5] Providing a comprehensive overview/review of modern working practices. Review UK, any type Nordenmark, et al. [51] Showing linkage between job control and demands, the work-life balance, and wellbeing among SE’d men and women. Quantitative 26 European countries, any type Kautonen, Kibler and Minniti [23] Examining how late-career transitions from org employment to entrepreneurship impact the returns from the monetary and quality of life. Quantitative UK, any type Nordenmark, et al. [52] Examining the occurrence of sickness presenteeism among the organizationally employed SE and any differences can be explained by higher work demands among the SE’d. Quantitative European Union, any type Bujacz, et al. [53] Examining and identifying the profiles of the SE’d taking into account different well-being indicators. Quantitative Europe, any type Vermeylen, Wilkens, Biletta and Fromm [44] Identifying heterogeneity of SE’d in terms of wide-ranging attitudes, income levels, and health and well-being among this diverse group. Review European Union, any type Fudge [54] Reviewing labour protection for SE’d workers Review Canada, any type Dahl, Nielsen and Mojtabai [33] Investigating how entering entrepreneurship affects the people involved. Quantitative Denmark, any type Stephan and Roesler [55] Comparing entrepreneurs’ health with employees’ health in a national representative sample. Quantitative German, any type Bennaars [56] Assessing the EU concept of a worker, self-employed, dependent self-employment, and false self-employment, EU legislation providing social protection for the SE’d. Review European Union, any type Boeri, et al. [57] Documenting features of solo SE, SE with employees, employment, and unemployment. Review OECD countries, any type Dixon-Woods, et al. [58] Focusing on a reflexive account of an attempt to conduct an interpretive review of the literature on access to healthcare by vulnerable groups in the UK. Review UK, any type Hudon, et al. [59] Comparing critical literature on the practices of first-line providers for workers with musculoskeletal injuries. Review Canada, United States, Australia, any type Cassidy [60] Understanding how to deal with the solitude of SE. Newspaper article UK, any type MacEachen [61] Examining occupational health and safety conditions of Uber work. Qualitative Canada, Uber drivers Thörnquist [62] Discussing the problem of false (bogus) SE and other precarious forms of employment in the ‘grey area’ between genuine SE and subordinate employment. Review Sweden, construction, & cleaning Behling and Harvey [48] Examining how the co-evolution of employment status law and a sector-specific fiscal regime maps tightly onto the emergence of mass SE, as evidenced by the comparative labour market and sectoral statistics. Quantitative UK, construction Bartel, et al. [63] Focuses on ride-share drivers’ health risks on the job Qualitative Canada, rideshare Tran and Sokas [64] Addressing the needs of workers in non-traditional employment relationships. Review USA, Physicians Bajwa, et al. [65] Presenting a commentary on the implications of a globalized online platform labour market on the health of ‘gig’ workers in Canada and globally. Review Canada, gig workers Browne [66] Review on reform to worker compensation systems of NSW. Review Australia, any type Lippel [67] Identifying the impacts of compensation system characteristics on doctors in Quebec and Ontario. Qualitative, Legal analysis Canada, any type Purse [68] Identifying the trajectory of workers’ compensation in Australia. Review Australia, any type Spasova, et al. [69] Synthesising both statutory and effective access to social protection for people in non-standard employment and self-employment in Europe. Review Europe, any type Rainone and Countouris [70] This policy report discusses a possible reconfiguration of the coexistence between collective bargaining and competition law. Policy brief Europe, any type Pasma and Regehr [71] Constructing a model for basic income that is fair, effective, and feasible in Canada. Policy analysis Canada, any type Busby and Muthukumaran [72] Looking at the common meanings of precarious work in academic and policy research, by examining the trends in non-standard work in Canada. Policy analysis Canada, any type Laflamme [73] Examining how the new working relationships and related protection systems are addressed in the province of Canada) and the Australian OHS regimes. Policy analysis Canada, Australia, Any type May [74] Developing a definition of precarious employment and its indicators and identifying the role that precarious employment plays in the economy. Policy analysis Canada, any type Lippel and Lötters [75] A comparison of cause-based and disability-based income support systems Review Global, any type Whiteford and Heron [76] Assessing social protection systems for workers. Review Australia, any type ijerph-19-05310-t003_Table 3 Table 3 Legal Frameworks addressing Self-employment. Ontario, Canada Labour Relations Act. 1995 The definition of employee under the Labour Relations Act includes dependent contractor: “dependent contractor” means a person, whether or not employed under a contract of employment, and whether or not furnishing tools, vehicles, equipment, machinery, material, or any other thing owned by the dependent contractor, who performs work or services for another person for compensation or reward on such terms and conditions that the dependent contractor is in a position of economic dependence upon, and under an obligation to perform duties for, that person more closely resembling the relationship of an employee than that of an independent contractor” WSIB, Ontario Independent operators (in construction): WSIB consider a person an independent operator in construction sector if he/she is sole proprietor or sole executive officer of a corporation, and subject to performing Class G construction work, no employees, working as contractor or subcontractor for more than one person during an 18-month period, reporting as ‘self-employed’ to a government agency, like the Canada Revenue Agency. Workplace Safety and Insurance Act, 1997 It defines “Worker” and “Employer”. “Worker means a person who has entered into or is employed under a contract of service or apprenticeship”. Employment Standards Act (ESA), 2000 It defines “Employee” and “Employer”. “Employee” includes, (a) a person, including an officer of a corporation, who performs work for an employer for wages, (b) a person who supplies services to an employer for wages, (c) a person who receives training from a person who is an employer, if the skill in which the person is being trained is a skill used by the employer’s employees, or (d) a person who is a homeworker, and includes a person who was an employee”. No information provided about dependent contractor or self-employment. NSW, Australia Workplace Injury Management and Workers Compensation Act. 1998 No definition of SE Workers Compensation Regulation. 2003 Define two categories of employers. But no definition of SE. Workers Compensation Act. 1987 No definition of SE. The Fair Work Act. 2009 The National Employment Standards (NES) cover 11 types of employees under National workplace relations system, but these talk nothing of SE. The Industrial Relations Act. 1996, NSW It broadens the definitions of employees, where SE’d can be accommodated: (1) in general definition, employee includes: (a) a person employed in any industry, whether on salary or wages or piece-work rates, or (b) any person taken to be an employee by subsection. (2) A person is not prevented from being an employee only because—(a) the person is working under a contract for labour only, or substantially for labour only, or (b) the person works part-time or on a casual basis, or (c) the person is the lessee of any tools or other implements of production, or(d) the person is an outworker, or (e) the person is paid wholly or partly by commission (such as a person working in the capacity of salesperson, commercial traveler or insurance agent). (3) Deemed employees: the persons described in Schedule 1 are taken to be employees for the purposes of this Act. Any person described in that Schedule as the employer of such an employee is taken to be the employer. (4) Exclusion: a person employed or engaged by his or her spouse, de facto partner or parent is not an employee for the purposes of this Act. ijerph-19-05310-t004_Table 4 Table 4 Different terms for self-employment. Independent operator ‘Gig’ worker ‘Gig’ employment Entrepreneur Self-employment without employee Self-employment with employee Independent contractor Dependent contractor Disguised worker Bogus worker False Worker Sham worker Own account self-employment Solo self-employment Stable own account self-employment Own boss employment Own boss worker Unincorporated self-employment Incorporated self-employment Dependent self-employment Economically dependent self-employment ijerph-19-05310-t005_Table 5 Table 5 Government and Non-Government Supports for SE’d Workers following illness or injury. Ontario, Canada NSW, Australia Supports That Cover/Required for all SE’d Workers Ontario Disability Support Program Ontario Works Ontario Health Insurance Plan (OHIP) Workplace Safety and Insurance (for construction workers only) Canada Pension Plan (Federal) Old Age Pension Disability support pension (DSP) Survivor’s pension Sickness and maternity benefits Unemployment Family allowances Motor Accident Insurance (Compulsory Third Party) National Disability Insurance Scheme (NDSI) Supports That Are Available to SE’d Workers only if They opt in and pay a premium Employment Insurance Special Benefits (federal) WSIB (for all occupations except construction) Work injury Personal injury/accident insurance ijerph-19-05310-t006_Table 6 Table 6 Key Supportive Policies. Ontario, Canada NSW, Australia Ontario Disability Support Program Ontario Works Ontario Health Insurance Plan (OHIP) Workplace Safety and Insurance (for construction workers only) Canada Pension Plan (Federal) Employment Insurance Special Benefits (federal) WSIB (for all occupations except construction) Old Age Pension Disability Support Pension (DSP) Survivor’s Pension Sickness and Maternity Benefits Unemployment Benefits Family Allowances Motor Accident Insurance National Disability Insurance Scheme (NDSI) Work Injury Personal Injury/Accident Insurance Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Wall S. Dimensions of precariousness in an emerging sector of self-employment: A study of self-employed nurses Gend. Work Organ. 2015 22 221 236 10.1111/gwao.12071 2. Law Commission of Ontario Vulnerable Workers and Precarious Work: Final Report Law Commission of Ontario Toronto, ON, Canada 2012 3. Khan T.H. MacEachen E. Hopwood P. Goyal J. Self-employment, work and health: A critical narrative review Work 2021 70 945 957 10.3233/WOR-213614 34744041 4. Quinlan M. The Effects of Non-Standard Forms of Employment on Worker Health and Safety ILO Geneva, Switzerland 2015 5. Taylor M. Marsh G. Nicol D. Broadbent P. Good Work: The Taylor Review of Modern Working Practices Department for Business, Energy & Industrial Strategy London, UK 2017 6. ILO World Employment Social Outlook ILO Geneva, Switzerland 2015 7. Khan T.H. MacEachen E. Dunstan D. Self-employment and Social Supports in Canada and Australia: A Comparative Policy Analysis Proceedings of the Canadian Association for Work & Labour Studies Conference Alberta, AB, Canada 1–3 June 2021 8. Lewchuk W. De Wolff A. King A. Polanyi M. From job strain to employment strain: Health effects of precarious employment Just Labour 2003 3 10.25071/1705-1436.165 9. Facey M.E. Eakin J.M. Contingent work and ill-health: Conceptualizing the links Soc. Theory Health 2010 8 326 349 10.1057/sth.2010.3 10. OECD OECD Employment Outlook 2019: The Future of Work Available online: https://www.oecd-ilibrary.org/employment/oecd-employment-outlook-2019_9ee00155-en (accessed on 20 May 2020) 11. Apouey, Benedicte and Apouey, Benedicte and Stabile, Mark, The Effects of Self and Temporary Employment on Mental Health: The Role of the Gig Economy in the UK Available online: https://ssrn.com/abstract=3395144 (accessed on 24 May 2019) 12. Sharp L. Torp S. Van Hoof E. de Boer A. Cancer and its impact on work among the self-employed: A need to bridge the knowledge gap Eur. J. Cancer Care 2017 26 e12746 10.1111/ecc.12746 13. Clare R. Craston A. Super and the Self-Employed The Association of Superannuation Funds of Australia Limited (ASFA) Sydney, Australia 2016 14. Yssad L.F. Ferrao V. Labour Statistics at a glance, Self-employed Canadians: Who and Why? Statistics Canada Ottawa, ON, Canada 2019 15. Quinlan M. Workers’ compensation and the challenges posed by changing patterns of work: Evidence from Australia Policy Pract. Health Saf. 2004 2 25 52 10.1080/14774003.2004.11667642 16. Yoon J. Bernell S.L. The effect of self-employment on health, access to care, and health behavior Health 2013 5 2116 10.4236/health.2013.512289 17. Rietveld C.A. Van Kippersluis H. Thurik A.R. Self-employment and health: Barriers or benefits? Health Econ. 2015 24 1302 1313 10.1002/hec.3087 25048640 18. Bambra C. Going beyond the three worlds of welfare capitalism: Regime theory and public health research J. Epidemiol. Community Health 2007 61 1098 1102 10.1136/jech.2007.064295 18000134 19. International Labour Organization (ILO) Ensuring Better Social Protection for Self-Employed Workers International Labour Organization (ILO) Geneva, Switzerland Organisation for Economic Co-Operation and Development (OECD) Riyadh, Saudia Arabia 2020 20. Geva-May I. Pal L.A. Good fences make good neighbours: Policy evaluation and policy analysis–exploring the differences Evaluation 1999 5 259 277 10.1177/13563899922208986 21. Yanow D. Conducting Interpretive Policy Analysis Sage Thousand Oaks, CA, USA 2000 Volume 47 22. Yanow D. Interpretation in policy analysis: On methods and practice Crit. Policy Anal. 2007 1 110 122 10.1080/19460171.2007.9518511 23. Kautonen T. Kibler E. Minniti M. Late-career entrepreneurship, income and quality of life J. Bus. Ventur. 2017 32 318 333 10.1016/j.jbusvent.2017.02.005 24. Quinlan M. The implications of labour market restructuring in industrialized societies for occupational health and safety Econ. Ind. Democr. 1999 20 427 460 10.1177/0143831X99203005 25. Blank V.L. Andersson R. Lindén A. Nilsson B.-C. Hidden accident rates and patterns in the Swedish mining industry due to involvement of contractor workers Saf. Sci. 1995 21 23 35 10.1016/0925-7535(95)00004-6 26. Rousseau D.M. Libuser C. Contingent workers in high risk environments Calif. Manag. Rev. 1997 39 103 123 10.2307/41165889 27. Saksvik P.Ø. Attendance pressure during organizational change Int. J. Stress Manag. 1996 3 47 59 10.1007/BF01857888 28. Nichols T. The Sociology of Industrial Injury Mansell New York, NY, USA 1997 29. Aya K.A. Social exclusion and earlier disadvantages: An empirical study of poverty and social exclusion in Japan Soc. Sci. Jpn. J. 2010 13 5 30 10.1093/ssjj/jyp042 30. Hilbrecht M. Self-employment and experiences of support in a work–family context J. Small Bus. Entrep. 2016 28 75 96 10.1080/08276331.2015.1117878 31. Gevaert J. De Moortel D. Wilkens M. Vanroelen C. What’s up with the self-employed? A cross-national perspective on the self-employed’s work-related mental well-being SSM-Popul. Health 2018 4 317 326 10.1016/j.ssmph.2018.04.001 29854916 32. Lewchuk W. Clarke M. De Wolff A. Working without commitments: Precarious employment and health Work Employ. Soc. 2008 22 387 406 10.1177/0950017008093477 33. Dahl M.S. Nielsen J. Mojtabai R. The effects of becoming an entrepreneur on the use of psychotropics among entrepreneurs and their spouses Scand. J. Public Health 2010 38 857 863 10.1177/1403494810375490 20601437 34. Zissimopoulos J.M. Karoly L.A. Transitions to self-employment at older ages: The role of wealth, health, health insurance and other factors Labour Econ. 2007 14 269 295 10.1016/j.labeco.2005.08.002 35. Salonen J. Koskinen L. Nummi T. The risk of under-insurance in the Finnish statutory pension scheme for self-employed workers: A trajectory analysis Int. Soc. Secur. Rev. 2020 73 25 48 10.1111/issr.12249 36. Corden A. Self-Employed People in the United Kingdom: Included or Excluded? Int. Soc. Secur. Rev. 1999 52 31 47 10.1111/1468-246X.00032 37. Spasova S. Bouget D. Ghailani D. Vanhercke B. Self-employment and social protection: Understanding variations between welfare regimes J. Poverty Soc. Justice 2019 27 157 175 10.1332/175982719X15538492348045 38. Conen W. Schulze Buschoff K. Precariousness among solo self-employed workers: A German-Dutch comparison J. Poverty Soc. Justice 2019 27 177 197 10.1332/175982719X15478021367809 39. MacEachen E. Work Disability Policy: Current Challenges and New Questions The Science and Politics of Work Disability Prevention Routledge New York, NY, USA 2018 3 17 40. Wassink J.T. Hagan J.M. A dynamic model of self-employment and socioeconomic mobility among return migrants: The case of urban Mexico Soc. Forces 2018 96 1069 1096 10.1093/sf/sox095 31186591 41. Driscoll T.R. Healey S. Mitchell R.J. Mandryk J.A. Hendrie A.L. Hull B.P. Are the self-employed at higher risk of fatal work-related injury? Saf. Sci. 2003 41 503 515 10.1016/S0925-7535(01)00081-9 42. Clark K. Drinkwater S. Pushed out or pulled in? Self-employment among ethnic minorities in England and Wales Labour Econ. 2000 7 603 628 10.1016/S0927-5371(00)00015-4 43. Sohns F. Revilla Diez J. Self-Employment and Its Influence on the Vulnerability to Poverty of Households in Rural Vietnam—A Panel Data Analysis Geogr. Rev. 2017 107 336 359 10.1111/j.1931-0846.2016.12206.x 44. Vermeylen G. Wilkens M. Biletta I. Fromm A. Exploring self-employment in the European Union Publications Office of the European Union Luxembourg 2017 45. Williams D. The Self-Employed: Providing for the Self-Providers Int. Soc. Secur. Rev. 1999 52 7 30 10.1111/1468-246X.00031 46. Duncan P. Bertolozzi M.R. Cowley S. Egry E.Y. Chiesa A.M. de Siqueira França F.O. “Health for all” in England and Brazil? Int. J. Health Serv. 2015 45 545 563 10.1177/0020731415584558 26077860 47. Prasad A. The contest over meaning: Hermeneutics as an interpretive methodology for understanding texts Organ. Res. Methods 2002 5 12 33 10.1177/1094428102051003 48. Behling F. Harvey M. The evolution of false self-employment in the British construction industry: A neo-Polanyian account of labour market formation Work Employ. Soc. 2015 29 969 988 10.1177/0950017014559960 49. Bögenhold D. From Hybrid Entrepreneurs to Entrepreneurial Billionaires: Observations on the Socioeconomic Heterogeneity of Self-employment Am. Behav. Sci. 2019 63 129 146 10.1177/0002764218794231 50. Weil D. Understanding the Present and Future of Work in the Fissured Workplace Context RSF Russell Sage Found. J. Soc. Sci. 2019 5 147 165 10.7758/rsf.2019.5.5.08 51. Nordenmark M. Vinberg S. Strandh M. Job control and demands, work-life balance and wellbeing among self-employed men and women in Europe Vulnerable Groups Incl. 2012 3 18896 10.3402/vgi.v3i0.18896 52. Nordenmark M. Hagqvist E. Vinberg S. Sickness Presenteeism among the Self-employed and Employed in Northwestern EuropedThe Importance of Time Demands Framework 2019 8 19 53. Bujacz A. Eib C. Toivanen S. Not all are equal: A latent profile analysis of well-being among the self-employed J. Happiness Stud. 2020 21 1661 1680 10.1007/s10902-019-00147-1 54. Fudge J. Labour protection for self-employed workers Just Labour 2003 3 10.25071/1705-1436.166 55. Stephan U. Roesler U. Comparison of entrepreneurs’ and employee’s health in a national representative sample J. Occup. Organ. Psychol. 2010 83 717 738 10.1348/096317909X472067 56. Bennaars H. Social protection for the self-employed: An EU legal perspective Self-Employment as Precarious Work Edward Elgar Publishing Cheltenham, UK 2019 57. Boeri T. Giupponi G. Krueger A.B. Machin S. Solo self-employment and alternative work arrangements: A cross-country perspective on the changing composition of jobs J. Econ. Perspect. 2020 34 170 195 10.1257/jep.34.1.170 58. Dixon-Woods M. Cavers D. Agarwal S. Annandale E. Arthur A. Harvey J. Hsu R. Katbamna S. Olsen R. Smith L. Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups BMC Med. Res. Methodol. 2006 6 35 10.1186/1471-2288-6-35 16872487 59. Hudon A. Lippel K. MacEachen E. Mapping first-line health care providers’ roles, practices, and impacts on care for workers with compensable musculoskeletal disorders in four jurisdictions: A critical interpretive synthesis Am. J. Ind. Med. 2019 62 545 558 10.1002/ajim.22972 31074020 60. Cassidy A. Home alone? Dealing with the solitude of self-employment The Guardian 10 May 2017 p. 27 61. MacEachen E. Reid-Musson E. Saunders R. Meyer S. Bigelow PKosny A. Bartel E. Varatharajan S. Driving For Uber: A Developmental Evaluation of Occupational Health and Safety Conditions of Ride-Share Work University of Waterloo Waterloo, ON, Canada 2019 62. Thörnquist A. False self-employment and other precarious forms of employment in the ‘grey area’ of the labour market Int. J. Comp. Labour Law Ind. Relat. 2015 31 411 429 63. Bartel E. MacEachen E. Reid-Musson E. Meyer S.B. Saunders R. Bigelow P. Kosny A. Varatharajan S. Stressful by design: Exploring health risks of ride-share work J. Transp. Health 2019 14 100571 10.1016/j.jth.2019.100571 64. Tran M. Sokas R.K. The gig economy and contingent work: An occupational health assessment J. Occup. Environ. Med. 2017 59 e63 10.1097/JOM.0000000000000977 28244887 65. Bajwa U. Gastaldo D. Di Ruggiero E. Knorr L. The health of workers in the global gig economy Glob. Health 2018 14 124 10.1186/s12992-018-0444-8 66. Browne B. Restoring Security and Respect:-Rebuilding NSW’s Workers Compensation System The Australia Institute Canberra, Australia 2018 67. Lippel K. Precarious employment and occupational health and safety regulation in Quebec Precarious employment: Understanding labour market insecurity in Canada McGill–Queen’s University Press Montreal, QC, Canada 2006 241 255 68. Purse K. The evolution of workers’ compensation policy in Australia Health Sociol. Rev. 2005 14 8 20 10.5172/hesr.14.1.8 69. Spasova S. Bouget D. Ghailani D. Vanhercke B. Access to social protection for people working on non-standard contracts and as self-employed in Europe A Study of National Policies, European Social Policy Network (ESPN) European Commission Brussels, Belgium 2017 70. Rainone S. Countouris N. Collective bargaining and self-employed workers: The need for a paradigm shift ETUI Research Paper-Policy Brief European Economic, Employment and Social Policy Brussels, Belgium 2021 71. Pasma C. Regehr S. Basic Income: Some Policy Options for Canada Rapport Établi Pour le Réseau Canadien Pour le Revenu Garanti Basic Income Canada Network Toronto, ON, Canada 2019 72. Busby C. Muthukumaran R. Precarious positions: Policy options to mitigate risks in non-standard employment CD Howe Inst. Comment. 2016 462 1 24 10.2139/ssrn.2888937 73. Laflamme A.-M. Changing Work Relationships and the Protection of Workers under Quebec and Australian Occupational Health and Safety Law Can. Lab. Emp. LJ 2015 19 223 74. May B. Precarious Work: Understanding the Changing Nature of Work in Canada House of Commons London, UK 2019 75. Lippel K. Lötters F. Public insurance systems: A comparison of cause-based and disability-based income support systems Handbook of Work Disability Springer Berlin/Heidelberg, Germany 2013 183 202 76. Whiteford P. Heron A. Australia: Providing Social Protection to Non-Standard Workers with Tax Financing OECD Paris, France 2018 77. Esterberg K.G. Qualitative Methods in Social Research McGrawn Hill Company Boston, TX, USA 2002 78. McNaughton D. Symons G. Light J. Parsons A. “My dream was to pay taxes”: The self-employment experiences of individuals who use augmentative and alternative communication J. Vocat. Rehabil. 2006 25 181 196 79. Arnold N.L. Ipsen C. Self-employment policies: Changes through the decade J. Disabil. Policy Stud. 2005 16 115 122 10.1177/10442073050160020201 80. Larson S.L. Hill S.C. Rural-urban differences in employment-related health insurance J. Rural Health 2005 21 21 30 10.1111/j.1748-0361.2005.tb00058.x 15667006 81. Hartman E. Oude Vrielink H. Huirne R. Metz J. Sick leave analysis among self-employed Dutch farmers Occup. Med. 2003 53 461 468 10.1093/occmed/kqg089 14581644 82. Rizzo D.C. With a little help from my friends: Supported self-employment for people with severe disabilities J. Vocat. Rehabil. 2002 17 97 105 83. Fossen F.M. König J. Public health insurance, individual health, and entry into self-employment Small Bus. Econ. 2017 49 647 669 10.1007/s11187-017-9843-0 84. Barber D. III Moffett M. State health insurance subsidies and the self-employed Small Bus. Inst. J. 2015 11 26209 85. Grégoris M. Deschamps F. Salles J. Sanchez S. Health assessment of self-employed in the food service industry Int. J. Occup. Environ. Health 2017 23 234 242 10.1080/10773525.2018.1470788 29722638 86. Wijnvoord L.E. Brouwer S. Buitenhuis J. van der Klink J.J. de Boer M.R. Indications of a scarring effect of sickness absence periods in a cohort of higher educated self-employed PLoS ONE 2016 11 e0156025 10.1371/journal.pone.0156025 27213963 87. Ashley D. Graf N.M. The process and experiences of self-employment among people with disabilities: A qualitative study Rehabil. Couns. Bull. 2018 61 90 100 10.1177/0034355216687712 88. Ostrow L. Smith C. Penney D. Shumway M. “It suits my needs”: Self-employed individuals with psychiatric disabilities and small businesses Psychiatr. Rehabil. J. 2019 42 121 131 10.1037/prj0000341 30570270 89. Beattie J. McLeod C. Murray M. Pedler D. Brumby S. Gabbe B. What Happens to the Farm? Australian Farmers’ Experiences after a Serious Farm Injury J. Agromed. 2018 23 134 143 10.1080/1059924X.2017.1422836 90. Fleming P. Self-employment used to be the dream. Now it’sa nightmare The Guardian 19 October 2016 p. 1 91. Jurik N.C. Getting away and getting by: The experiences of self-employed homeworkers Work Occup. 1998 25 7 35 10.1177/0730888498025001002 92. Cohen R.L. Hardy K. Valdez Z. Introduction to the Special Issue: Everyday Self-Employment Am. Behav. Sci. 2019 63 119 128 10.1177/0002764218794786 93. Innangard Worker Misclassification: An Innangard Report on Employee Status and Consequences of Worker Misclassification in Key Jurisdictions International Employment Law Alliance Geneva, Switzerland 2019 94. Pedersini R. Coletto D. Self-Employed Workers: Industrial Relations and Working Conditions Eurofound Dublin, Ireland 2009 95. Kaine S. Rawling M. ‘Comprehensive campaigning’ in the NSW transport industry: Bridging the divide between regulation and union organizing J. Ind. Relat. 2010 52 183 200 10.1177/0022185609359444 96. Quinlan M. Mayhew C. Precarious employment and workers’ compensation Int. J. Law Psychiatry 1999 22 491 520 10.1016/S0160-2527(99)00023-0 10637755 97. Smeaton D. Self-employed workers: Calling the shots or hesitant independents? A consideration of the trends Work Employ. Soc. 2003 17 379 391 10.1177/0950017003017002008 98. Behrendt C. Nguyen Q.A. Ensuring universal social protection for the future of work Transf. Eur. Rev. Labour Res. 2019 25 205 219 10.1177/1024258919857031 99. Lewin-Epstein N. Yuchtman-Yaar E. Health risks of self-employment Work Occup. 1991 18 291 312 10.1177/0730888491018003003 100. Khan T.H. MacEachen E. A furnished house without walls: Examining the work and health support systems of self-employed workers in Ontario, Canada Saf. Health Work 2022 13 S201 10.1016/j.shaw.2021.12.1380 101. Collie A. Di Donato M. Iles R. Work disability in Australia: An overview of prevalence, expenditure, support systems and services J. Occup. Rehabil. 2019 29 526 539 10.1007/s10926-018-9816-4 30374851 102. van den Groenendaal S.M.E. Akkermans J. Fleisher C. Kooij D.T. Poelle R.F. Freese C. A qualitative exploration of solo self-employed workers’ career sustainability J. Vocat. Behav. 2022 134 103692 10.1016/j.jvb.2022.103692 103. Kim I.-H. Muntaner C. Shahidi F.V. Vives A. Vanroelen C. Benach J. Welfare states, flexible employment, and health: A critical review Health Policy 2012 104 99 127 10.1016/j.healthpol.2011.11.002 22137444 104. Guo Y. Gasparrini A. Armstrong B.G. Tawatsupa B. Tobias A. Lavigne E. Coelho M.d.S.Z.S. Pan X. Kim H. Hashizume M. Temperature variability and mortality: A multi-country study Environ. Health Perspect. 2016 124 1554 1559 10.1289/EHP149 27258598 105. Gevaert J. Van Aerden K. De Moortel D. Vanroelen C. Employment quality as a health determinant: Empirical evidence for the waged and self-employed Work Occup. 2021 48 146 183 10.1177/0730888420946436 106. Rivero F.M. Padrosa E. Utzet M. Benach J. Julià M. Precarious employment, psychosocial risk factors and poor mental health: A cross-sectional mediation analysis Saf. Sci. 2021 143 105439 10.1016/j.ssci.2021.105439 107. Corujo B.S. The ‘gig’economy and its impact on social security: The Spanish example Eur. J. Soc. Secur. 2017 19 293 312 10.1177/1388262717745751 108. Foster J. Tracking Precarity: Employment Pathways of Precarious Status Migrant Workers in Canada Can. J. Sociol. 2021 46 257 278 109. Payne S. Ontario WSIB Shakedown: Self-Employed Contractors Mad as Hell Contractor 9 February 2013 Available online: https://www.canadiancontractor.ca/canadian-contractor/mandatory-wsib-in-ontario-self-employed-contractors-mad-as-hell/5475/ (accessed on 12 February 2019) 110. Alfers L. Lund F. Moussié R. Approaches to social protection for informal workers: Aligning productivist and human rights-based approaches Int. Soc. Secur. Rev. 2017 70 67 85 10.1111/issr.12153 111. Hossian M.A. Khan T.H. Poverty and public services: Social exclusion of urban poor Decelerated Decline, State of Poverty in Bangladesh Titumir R.A. Unnayen Onneshan, Shrabon Prokashani Dhaka, Bangladesh 2012 113 134 112. Ståhl C. MacEachen E. Universal Basic income as a policy response to COVID-19 and precarious employment: Potential impacts on rehabilitation and return-to-work J. Occup. Rehabil. 2021 31 3 6 10.1007/s10926-020-09923-w 32816204

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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092291 cancers-14-02291 Review Hypoxia as a Modulator of Inflammation and Immune Response in Cancer https://orcid.org/0000-0003-4117-6689 Castillo-Rodríguez Rosa A. 12* Trejo-Solís Cristina 3 https://orcid.org/0000-0001-5835-9866 Cabrera-Cano Alfredo 14 https://orcid.org/0000-0003-2095-9182 Gómez-Manzo Saúl 5 Dávila-Borja Víctor Manuel 6 Corbet Cyril Academic Editor Kurelac Ivana Academic Editor 1 Laboratorio de Oncología Experimental, Instituto Nacional de Pediatría, Mexico City 04530, Mexico; alfredocc@xanum.uam.mx 2 Programa Investigadoras e Investigadores por México, Consejo Nacional de Ciencia y Tecnología (CONACYT), Mexico City 03940, Mexico 3 Laboratorio Experimental de Enfermedades Neurodegenerativas, Instituto Nacional de Neurología y Neurocirugía, Mexico City 14269, Mexico; cristina.trejo@innn.edu.mx 4 Posgrado en Biología Experimental, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana-Iztapalapa, Mexico City 09340, Mexico 5 Laboratorio de Bioquímica Genética, Instituto Nacional de Pediatría, Mexico City 04530, Mexico; saulmanzo@ciencias.unam.mx 6 Independent Researcher, Dallas, TX 75149, USA; victorm.davila.borja@gmail.com * Correspondence: racastilloro@conacyt.mx; Tel.: +52-55-1084-0900 04 5 2022 5 2022 14 9 229122 3 2022 25 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary The tumoral microenvironment comprises cancer cells and surrounding components, including immune and endothelial cells, along with the extracellular matrix. As the tumoral cells proliferate, a gradient of oxygen and nutrients is established while the tumor becomes a solid mass. Tumoral cells have developed strategies to adapt themselves to the hypoxic microenvironment and to modify the tumoral microenvironment, including the inflammatory cells, in order to maintain their proliferation and ulterior metastasis, representing a crucial factor in the malignity of the disease. Therefore, we analyze the signaling and cellular components that interconnect inflammation and hypoxia, emphasizing the most recent findings and contributing to their understanding, as a reference for new therapeutic strategies. Abstract A clear association between hypoxia and cancer has heretofore been established; however, it has not been completely developed. In this sense, the understanding of the tumoral microenvironment is critical to dissect the complexity of cancer, including the reduction in oxygen distribution inside the tumoral mass, defined as tumoral hypoxia. Moreover, hypoxia not only influences the tumoral cells but also the surrounding cells, including those related to the inflammatory processes. In this review, we analyze the participation of HIF, NF-κB, and STAT signaling pathways as the main components that interconnect hypoxia and immune response and how they modulate tumoral growth. In addition, we closely examine the participation of the immune cells and how they are affected by hypoxia, the effects of the progression of cancer, and some innovative applications that take advantage of this knowledge, to suggest potential therapies. Therefore, we contribute to the understanding of the complexity of cancer to propose innovative therapeutic strategies in the future. hypoxia inflammation cancer tumoral microenvironment HIF-1α NF-κB STAT Consejo Nacional de Ciencia y Tecnología (CONACYT)SALUD-2014-1-233868 Catedras-CONACYT No. 1059 Instituto Nacional de Pediatría016/2019 037/2015 This research was funded by Consejo Nacional de Ciencia y Tecnología (CONACYT), grant number SALUD-2014-1-233868, Catedras-CONACYT No. 1059 and by federal funds of the Instituto Nacional de Pediatría, Grant Numbers 016/2019 and 037/2015. ==== Body pmc1. Introduction: Hypoxia and Inflammation as a Cancer Hallmark Chronic inflammation and viral infections often precede the development of cancer. In fact, the association between cancer and inflammation has been reported frequently; as examples, we can mention ulcerative colitis and colorectal cancer; hepatitis B or C and hepatocellular carcinoma (HCC); tobacco consumption and lung cancer; and human papillomavirus infection and cervical cancer, among many other cases [1,2,3,4]. Therefore, a clear connection has been established, implicating that inflammation as immune response promotes oncogenic transformation or supports tumoral progression. Moreover, the cells that coordinate the inflammatory response are responsible for the recognition and elimination of tumoral cells, which develop mechanisms to avoid these processes. In this complex context, tumoral hypoxia plays an important role in the regulation of the metabolism and the elements that integrate the tumoral microenvironment (TME). The cellular components of the TME include cancer cells as well as immune cells like lymphocytes T and B, tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs), natural killer (NK) cells, Myeloid-Derived Suppressor Cells (MDSCs), tumor-associated neutrophils (TANs), dendritic cells, mast cells, granulocytes as well as adipocytes, endothelial cells and pericytes [5,6]. An intricate communication is established between cancer and its surrounding cells, releasing several cytokines and molecules to modulate the environment and allow tumoral growth and metastasis. Furthermore, tumoral progression requires extra support of oxygen and energy. In these circumstances, the tumor develops hypoxia, a stressful factor that modifies the phenotype of the cancerous and surrounding cells in order to allow their adaptation and survival. The interconnection between hypoxia and inflammation has been recognized and plays different roles at several levels of the progression of cancer. Here, we analyze the effect of tumoral hypoxia over the inflammatory response, including the signaling pathways that link the hypoxic and inflammatory process, and then analyze their particularities in the immune cellular components. Finally, we analyze some future therapeutic approaches that have been developed as a result of the knowledge in this field. 2. Regulation of Inflammatory Pathways by Hypoxia Hypoxia is a factor that awakens a series of signaling responses in cells in order to adapt their cellular processes to the lack of oxygen, like metabolism. However, hypoxic mediators interact with other important pathways that influence the immune response or vice versa. We consider the participation of HIF, nuclear factor kappa B (NF-κB), and Signal transducer and activator of transcription (STAT) pathways as the main mediators of the inflammatory response and hypoxia, and therefore we analyze them hereafter. 2.1. HIF Pathway The understanding of how cells adapt to low levels of oxygen is considered crucial. In fact, the 2019 Nobel Prize in Physiology or Medicine was awarded to William Kaelin, Peter Ratcliffe, and Gregg Semenza for their studies in cellular oxygen sensing and adaptability [7]; furthermore, the hypoxia inducible factors (HIFs) are the key point in this phenomenon. The HIFs belong to a transcription factor family characterized by a basic helix-loop-helix (bHLH)/PAS domains, which regulate the cell adaptation to the hypoxic microenvironment [8,9,10]. This family contains three α isoforms, known as HIF-1α, HIF-2α, also called endothelial PAS domain-containing protein 1 (EPAS1), and HIF-3α. Another member of the HIF family is the β isoform (HIF-1β), also called aryl hydrocarbon receptor nuclear translocator (ARNT) [8,10,11,12]. HIF-1α and HIF-2α have 48% identity in their amino acid sequence; in fact, the maximal conservation regions are in the bHLH (85%), PAS-A (68%), and PAS-B (73%) domains. Both isoforms also share sequence identity in the C-terminal domain, which possesses a hypoxia response domain [12]. HIF-3α shares high similarity to HIF-1α and HIF-2α in the bHLH and PAS domains; however, HIF-3α does not have a transactivation domain, like HIF-1α and HIF-2α [13]. The α subunits bind with the β subunits to form active heterodimers that bind to DNA. The most studied heterodimer is HIF-1α/HIF-1β [8,10,12,13]. Under normoxic conditions, the HIF-α subunits are regulated by post-translational modifications that allow their degradation. These modifications are mainly hydroxylations in proline residues, which are carried out by the activity of enzymes called prolyl hydroxylases, which use oxygen as a substrate (Figure 1) [14]. In mammals, three isoforms of prolyl hydroxylases (PHD) have been identified: PHD1, PHD2, and PHD3 [14]. However, it has been reported that PHD2 is the most important in the hydroxylation and degradation of HIF-1α and HIF-2α, since the inhibition of the expression of PHD2 supports angiogenesis and promotes the stability and transcriptional activity of HIF-1α [15]. For instance, Hsu and colleagues demonstrated that lung cancer cells secrete an exosomal microRNA called mir23-a, which binds to the 3 ‘UTR region of PHD2, thus inhibiting its expression and promoting the transcriptional activity of HIF-1α, angiogenesis, and tumoral progression [16]. The hydroxylation in proline 564 is recognized by the tumor suppressing protein von Hippel-Lindau (pVHL), which acts as an E3 ubiquitin ligase by adding ubiquitin residues to the HIF-α subunits, thus promoting their degradation (Figure 1) [17,18,19,20]. Loss of function or inhibition of pVHL expression prevents HIF-1α degradation, which supports tumor progression. For instance, Chakraborty and colleagues demonstrated that epigenetic regulation, specifically methylations in the VHL promoter, decreases its expression and thus increases the levels of HIF-1α and vascular endothelial growth factor (VEGF) [21]. Besides PHD, other hydroxylations are carried out on asparagine residues by another enzyme known as factor inhibiting HIF (FIH) [22,23]. Hydroxylations at asparagine residues prevent HIF from binding to transcriptional cofactors such as p300, thus inhibiting its activity [22,23,24]. Under hypoxia, the activity of PHD enzymes is compromised, and HIF-α subunits are not degraded; this allows cellular adaptation to hypoxic stress (Figure 1) [25,26]. HIF-1α and HIF-2α differently regulate the cellular response to hypoxia. Holmquist-Mengelbier and colleagues suggested that HIF-1α is the main regulator of the response to acute hypoxia, while HIF-2α is the main regulator of the response to chronic hypoxia, using an in vitro model of neuroblastoma [26]. After the stabilization of HIF-α subunits, they are translocated to the nucleus and form a heterodimer with the HIF-1β subunit, which binds to DNA sequences called hypoxia response elements (HREs) [8,11]. This union activates the transcription of different genes related to mesenchymal-epithelial transition, metastasis, and angiogenesis, such as erythropoietin, VEGF, among others, but also genes related to metabolism and biotransformation as glucose transporter (GLUT) 1, hexokinase 2 (HK2), lactate dehydrogenase A (LDHA), carbonic anhydrase IX (CAIX), enolase 1 (ENO1), solute carrier family 2 member 2 (SLC2A1), and even cytochromes P450 [11,27,28,29,30,31,32,33,34,35]. In this sense, Valencia and colleagues, using medulloblastoma cells, demonstrated that hypoxia and HIF-1α promote resistance to cyclophosphamide and ifosfamide by decreasing the expression of cytochromes P450 CYP2B6, CYP3A4, and CYP3A5 [36]. Recently, in our laboratory, we demonstrated that hypoxia increased the expression of the isoforms CYP24A1 and CYP2S1 related to the activity of HIF-1α in a liver cancer cell model [32]. Interestingly, other alternative signaling pathways can promote the degradation and inhibition or the stabilization and activation of HIF-α subunits. For instance, Bao and colleagues demonstrated that G9a and G9a-like protein (GLP) are methyltransferases that methylate HIF-1α in its transactivation domain, specifically in lysine 674, thus inhibiting its transcriptional activity. They also demonstrated that these enzymes only methylate HIF-1α and not HIF-2α [30]. Moreover, the heat shock protein 90 (Hsp90) binds to HIF-1α, thus supporting its stabilization [35]. Another signaling pathway that positively participates in the transcription and translation of HIF-α is the pathway regulated by PI3K/AKT/mTOR proteins [33]. In this sense, the genetic and pharmacological inhibition of PI3K/mTOR signaling induces a reduction of tumor hypoxia [37]. Phosphorylation is another mechanism that increases HIF activity. For example, the phosphorylation of HIF-1α at serine residues 641 and 643 by nuclear protein kinases such as p42/p44 MAPK improves its transcriptional activity and its accumulation in the nucleus [38]. Likewise, the phosphorylation of HIF-2α at the serine residue 672 by ERK1/2 results in its transcriptional activity and nuclear accumulation [39]. In recent years, several studies have shown the role of long non-coding RNAs in cancer progression [40,41]. Wen and colleagues demonstrated that the long non-coding RNA DANCR promotes the stability of HIF-1α mRNA, supporting cancer cell invasion and migration [40]. Barth and colleagues reported the role of other long non-coding RNAs in the regulation of HIF-α [41]. The interrelation between the HIF pathway, inflammation, and cancer has been extensively described, finding examples in several cancer types (Figure 2). Clear cell renal cell carcinoma (ccRCC) is particularly HIF-dependent; it is characterized by an accumulation of HIF-1α and HIF-2α due to a mutational inactivation of VHL, independently of the oxygen levels. Using human ccRCC cell lines, it has been reported that HIF-1α is essential for tumor formation and induces a glycolytic profile, while HIF-2α regulates lipoprotein metabolism, biogenesis of ribosome, and induction of MYC and E2F. More importantly, the proteomic analysis showed that HIF-2α-deficient tumors presented a better anti-tumoral response, demonstrated by an increment in the antigen presentation, interferon (IFN) signaling, and CD8+ T cell infiltration and activation. This would suggest that HIF-2α is also a repressor of the anti-tumoral immune response, even independently of hypoxia or HIF-1α [42] (Figure 2a). Interestingly, HIF-2α induces the expression of the Programmed death-ligand 1 (PD-L1), as observed in ccRCC [43]. PD-L1 binds to its transmembrane receptor, the programmed cell death protein 1 (PD-1), which is usually expressed in cytotoxic T lymphocytes, suppressing their activation and thus the immune response. Thus, immunotherapy with HIF-2α inhibitors should consider that PD-L1 expression could also be reduced and might reduce the effectivity of the immunotherapy [44]. Moreover, VHL disease can lead to the development of highly vascularized tumors in addition to ccRCC, such as hemangioblastomas in the brain or retina, and pheochromocytoma. The constant activation of the HIF pathway leads to the expression of proangiogenic proteins such as VEGF and other HIF targets related to the progression of the tumor and inflammation [45]. However, VHL mutations could be related to alterations in other pathways independent of HIF, including those related to inflammation. In this respect, the downregulation of Endoglin (ENG) and tumor necrosis factor (TNF) α, which is an activator of the NF-κB pathway, has been reported. As expected, a decrease in the expression of targets of NF-κB as matrix metalloproteinases (MMPs), cyclooxygenase 2 (COX2), and nitric oxide synthase (NOS)3 were revealed by RNAseq of blood outgrowth endothelial cells from VHL disease patients, as a model to assess the systemic effects in other organs predisposed to develop malignant tumors [46]. Smoking is the principal inductor of an inflammatory process known as chronic obstructive pulmonary disease (COPD), which is considered a risk factor to develop lung cancer; moreover, the inflammation derived from COPD and the overexpression of HIF-1α potentiate the activation of KRAS signaling, which in turn induce tumorigenesis. In fact, the deficiency of HIF-1α decreases epithelial inflammation and avoids the induction of lung cancer, even in the presence or absence of COPD, in a murine model [47] (Figure 2b). The oxygen levels and expression of HIF-1α could be also regulated by microbiota linked to chronic inflammation [1]. In the intestinal microenvironment, some microorganisms release peptides that induce an inflammatory response, which has been related to chronic inflammation and cancer [48,49]. But in other cases, the microbiota could exert a protective effect in cancer and also be synergistic to cancer treatment as an immunomodulator [50]. Reciprocally, hypoxia could also modulate the presence of specific microbiota, which is associated with chronic inflammation and the presence of colorectal or liver cancer [51]. In HCC, the most frequent form of liver cancer, a correlation has been established between inflammation, hypoxia, and cancer; however, the participation of hepatitis B virus (HBV) as an inductor of the HIF pathway has been questioned. In this sense, an in vivo model using mice infected with HBV to produce chronic hepatitis B as a precursor of HCC was used to evaluate their association with hypoxia. The authors found an increase in the hypoxic profile genes of chronic hepatitis B groups without cirrhosis or HCC but no evidence that regulatory hepatitis B X protein (HBx) could modulate the HIF expression, contrary to previous reports. However, independently of the HBx participation, a clear connection between inflammation and hypoxia activation pathways was confirmed as a potent precursor of HCC (Figure 2c) [52]. In a study of pancreatic cancer samples, the expression of toll-like receptors (TLRs), a characteristic type of single-pass membrane-spanning receptor expressed in immune cells, was associated with HIF-1α and CAIX. Particularly, TLR2 and TLR9 showed a correlation with nuclear HIF-1α only in early pancreatic lesions as pancreatic intraepithelial neoplasia type I and II, but not in type III or pancreatic carcinoma, which implies that innate inflammation and hypoxia are coexistent factors that could be involved in early carcinogenesis (Figure 2d) [53]. Furthermore, TLR expression has been abnormally found in several types of tumoral cells, such as endometrial, oral, glioma, prostate, liver, endometrial, gastric, and pancreas [53,54,55,56,57,58,59]. It has been reported that TLR3 could induce the expression of the I.3 isoform of HIF-1α, which accumulates in the nucleus even in normoxia, promoting the secretion of VEGF and tumor progression in prostate cancer [56]. In glioma biopsies, TLR4 was overexpressed. Moreover, TNF-α induced the activation of the TLR4-AKT-HIF-1α axis [55]. A feedback mechanism was found in oral squamous cell carcinoma (OSCC), where the activation of TL3 and TLR4 induced the expression of HIF-1α; in addition, HIF-1α bound to the promoter of TLR3 and TLR4, increasing their expression [54]. Furthermore, it has been documented that hypoxia induces the overexpression of TLR9 in HCC. Hypoxia promotes the translocation from the nucleus to the cytoplasm of damage-associated molecular pattern (DAMP) proteins, such as high mobility group box 1 (HMGB1) and mitochondrial DNA (mtDNA). Then, HMGB1 and mtDNA can activate endosomal TLR9, leading to tumor progression in a feedback mechanism [57]. In endothelial cells, Biglycan (BGN), a protein from the extracellular matrix, interacts with TLR2 and TLR4, leading to an increase in the HIF-1α activity, including VEGF overexpression, which in turn promotes gastric cancer progression and metastasis [59]. The correlation between HIF and several cytokines, such as interleukin (IL)-1β, IL-6, and IFN, has also been reported. For example, IL-6 is a pleiotropic cytokine synthesized by immune cells, endothelial cells, fibroblasts, myocytes, and adipocytes; moreover, IL-6 modulates inflammation and enhances the transcription and nuclear translocation of HIF-1α through the STAT3 pathway [60]. The expression of HIF-1α is also induced by IFN-α, a cytokine released by lymphocytes in response to viral infections, apparently through the Janus Kinases (JAK)/PI3K/mTORC2 signaling pathway [61]. Piasecka and colleagues demonstrated that some cytokines such as IL-1β, TNF-α, IFN, and monocyte chemoattractant protein 1 (MCP1) stimulate the NF-κB/COX2 signaling pathway, which induces the overexpression of HIF-1α and HIF-3α in tumoral cells and mesenchymal stem cells [62,63]. HIF-1α also leads to the expression of COX2, an enzyme that metabolizes the synthesis of prostaglandins [64,65] (Figure 2e). On the contrary, HIF-1α could induce the secretion of other cytokines, such as IL-1β by TAMs and cancer cells stimulated by hypoxia [65,66]. For instance, breast cancer cells that were stimulated by hypoxia released IL-1β, which in turn induced the activation of invasive CAFs (Figure 2f) [65]. A clear association between hypoxia and the induction and secretion of the transforming growth factor (TGF)-β has been established in several types of cancer, such as pancreatic, colorectal, kidney, lung, melanoma, oral, and breast [67,68,69,70,71,72,73,74,75,76,77]. TGF-β is a pleiotropic cytokine linked to the regulation of the epithelial-mesenchymal transition (EMT) related to metastasis, suppression of the immune response, and regulation of TME cellular components such as cancer stem cells (CSCs), CAFs, and TAMs [69,71,73,75,78,79]. In particular, TGF-β inhibits glycolysis in normoxia; however, this is reverted in hypoxia. Using a lung cancer model, it has been reported that the TGF–β/Smad signaling pathway leads to the phosphorylation of Smad2 and Smad3; in hypoxia, HIF-1α binds to Smad3 phosphorylated, inducing the expression of c-Myc, which induces the expression of protein machinery to alternative splicing targeting PKM2, which in turn activates glycolysis [74]. Interestingly, a decrease in the activation of the TGF-β pathway through the downregulation of the TGF-β receptor type 2 (TGFBR2) has been associated with hypoxia. Apparently, hypoxia induced the expression of the enhancer of zeste homolog 2 (EZH2), a histone methyltransferase, which in turn regulates the hypermethylation of the TGFBR2 promoter in a model of prostate cancer [80]. In another approach, when TGFBR2 is depleted in CD4+ T cells, a remodeling of the vasculature in the tumor leads to the death of tumoral avascular regions and suppresses the tumor progression [79]. A mechanism of resistance of immunotherapy has been related to the influence of HIF-1α over the extracellular adenosine (eADO) axis. ATP/ADP in the extracellular space is converted to adenosine monophosphate (AMP) by the ectonucleotidase CD39; then, AMP is metabolized by CD73 to produce eADO, which has multiple immunosuppressive functions through its interaction with adenosine receptors (ARs) such as A1, A2A, A2B, and A3. Interestingly, HIF-1α induces and regulates the expression of ectonucleotidases CD39 and CD73, along with A2A and A2B receptors, in tumors (Figure 2g) [81,82,83,84,85]. Tumoral cells release exosomes that contain diverse elements, allowing their communication with near or distant cells distributed through the body. Interestingly, a hypoxic environment increases the number of extracellular vesicles in some types of cancer, such as breast or lung. In addition, it has been found that pancreatic cancer cells release exosomes enriched with miR-301a-3p after a hypoxic stimulus, targeting surrounding macrophages and inducing their transition to an M2 pro-tumoral phenotype, which facilitates the progression of cancer [86]. Likewise, another group described that hypoxic tumoral cells release exosomes enriched with chemokines/chemoattractants, macrophage colony-stimulating factor (M-CSF), monocyte chemoattractant protein-1(MCP1), C–C motif chemokine (CCL) 2, endothelial monocyte-activating polypeptide II (EMAP II), leukotriene A-4 hydrolase (LTA4H), TGF-β1, TGF-β2, TGF-β3, macrophage migration inhibitory factor (MIF), and ferritin heavy/light chain (FTH, FTL). These chemokines promote recruitment and M2 macrophage polarization (Figure 2h) [87]. The role of cancer stem cells (CSCs) as initiators of a cancerous population has also been discussed, and the hypoxic environment seems a key factor in CSC activation. For example, it has been reported that CCAAT-enhancer-binding proteins (C/EBP) δ induce a CSC phenotype and interestingly, hypoxia and IL-6 enhanced their expression. Moreover, there is a feedback loop that allows C/EBPδ to amplify IL-6 and HIF-1α expression, as was observed in a breast cancer model [88]. As mentioned above, in our laboratory, we report that hypoxia promotes the overexpression of cytochrome P450 CYP2S1 [32]. This enzyme is important, since it participates in the regulation of inflammatory molecules such as arachidonic acid, linoleic acid, prostaglandins, and thromboxane [89]. However, the role of CYP2S1 in inflammation, carcinogenic processes, and tumor hypoxia remains unclear [90]. We will describe with more detail the interrelation between hypoxia and some of the most important inflammatory pathways, such as NF-κB and STAT3, in the next sections. 2.2. NF-κB Pathway It has been documented that the correlation between the activation of the NF-κB pathway and hypoxic conditions, particularly linked to HIF, is the principal mediator in the hypoxic response facilitating the progression of cancer [91,92]. Usually, the NF-κB pathway is related to the response to inflammation mediated by the immune system. However, it is also implicated in other important physiological functions, such as apoptosis evasion, proliferation, as well as cell adhesion and tissue remodeling. Consequently, NF-κB deregulation has been involved in many human diseases, including cancer [93,94]. The NF-κB complex is a family of nuclear transcription factors that recognize a consensus DNA sequence (GGGRNYYYCC, where R is a purine, Y is a pyrimidine, and N is any nucleotide) and mediate the induction or inhibition of the transcription of their target genes [95,96]. This family includes RelA (p65), RelB, c-Rel, p50/p105 (NF-κB1), and p52/p100 (NF-κB2), and they are capable of forming homo- and heterodimers. They are also characterized by an N-terminal REL homology domain [97], which allows their binding to DNA and their dimerization. When this pathway is inactive, the NF-κBs are sequestered in the cytosol by the inhibitory proteins of κB (IκBs) (Figure 3). But when the pathway is active, the IκBs are phosphorylated by the IκB kinase (IKK) complex. This complex is integrated by the catalytic subunits IKKα and IKKβ and several copies of the regulatory subunit NF-κB essential modifier or NEMO, also known as IKKγ. The phosphorylation of the κBs leads to their ubiquitination and degradation, releasing the NF-κBs to be translocated to the nucleus [94]. Regularly, the activation of the pathway is derived due to the kinase activation in response to extracellular signals, including cytokines such as TNF-α, IL-1, IL-6, reactive oxygen species (ROS), or prostaglandins [98]. Alternatively, the non-canonical pathway relays in p100, which inhibits RelB. The activation of the pathway through the TNF receptor family members triggers NF-κB-Inducing Kinase (NIK), which activates IKKα to phosphorylate p100 and send it to ubiquitination. Thus, RelB is released and interacts with p52, to form a dimer that translocates to the nucleus and activates the gene transcription [99] (Figure 3). The interaction between hypoxia and the NF-κB pathway seems to be synergistic and is highly related to HIF. In this context, abundant evidence has been reported about the crosstalk between the transcription factors NF-κB and HIF. For example, the stimulation of the NF-κB pathway by their respective ligands as TNF-α increased the HIF-1α levels, even in normoxic conditions, and activates target genes linked to hypoxic conditions. Moreover, the HIF-1α promoter has NF-κB binding sites [100]. In addition, it has been documented that hypoxia itself stimulates the NF-κB pathway through different mechanisms, which are regulated in a feedback sense. In an in vitro model with an exposition of 0.02% of O2, the phosphorylation and degradation of the inhibitory subunit IκBα allowed the translocation of NF-κB factors and thus the activation of the pathway [101]. In addition, it has been reported that the promoter of IKKβ has a binding site for HIF-1α; thus, IKKβ expression was induced, leading to an increase of IκBα phosphorylation and p65 activation [102]. It has been suggested that HIF regulates the TLR/NF-κB signaling pathway under hypoxic stress through the positive regulation of TLR4 transcription [54,103]. These observations confirm the correlation between HIF-1α and NF-κB pathways but also show the reliance on the activators of these pathways. Recently, the regulation of hypoxia over NF-κB through TGF-β–activated kinase 1 (TAK) was reported [104]. This kinase mediates NF-κB activation after stimulation with the IL-1 receptor or TNF receptor. After TAK activation, it is recruited to TNF receptor–associated factor (TRAF) 6 or TRAF2. TRAF6 catalyzes the poly-ubiquitination in the lysine 63, which activates the TAK kinase complex (including TAB1, TAB2, and TAB3) and phosphorylates serine residues of IKKβ, therefore activating the NF-κB pathway [105]. Hypoxia induces the IKK activity through calcium/calmodulin-dependent kinase 2 (CaMK2). This mechanism implies Ca2+ release and requires the activation of TAK1. Interestingly, the inhibition of IκBα results from the SUMOylation in critical lysines and the release of RelA to activate NF-κB [106]. Furthermore, hypoxia can directly stimulate the NF-κB pathway through the inhibition of prolyl-hydroxylases, which can interact with these transcription factors. The PHDs and FIH can sense oxygen levels and catalyze the hydroxylation of the proline residues within consensus LxxLAP motifs (PHD1, PHD2, PHD3) and asparagine residues (FIH) in the target protein, as discussed earlier [107]. It has been documented that hypoxia activates IKKβ through phosphorylation dependence and consequent phosphorylation and degradation of IκBα. This interaction is regulated by the recognition of a LxxLAP consensus motif contained in IKKα/β by PHD1; as hypoxia inactivates the PHD1 hydroxylation over IKKβ, then leads to the activation of NF-κB [108], which could benefit the progression of cancer. The downregulation of PHD2 also has been correlated with NF-κB activation and inflammation. It has been reported that the estrogen receptor β (ERβ) induces the expression of PHD2, leading to a degradation of HIF-1α [109]. In contrast, chronic inflammation of the prostate is related to loss of Erβ, and the authors proposed a model in which the loss of ERβ and PHD2 downregulation, as well as hypoxia, stabilizes HIF-1α and activates inflammation through NF-κB [102]. However, other groups proposed that the pro- or anti-inflammatory effects of PHD1 and PHD2 as well as PHD expression were linked to NF-κB activation. Li and colleagues showed that, independently of HIF-1α, PHD2 controls the NF-κB/p65 transactivation in a model of nucleus pulposus in vitro with a pro-inflammatory effect; in addition, PHD2 expression seems to be regulated by NF-κB [110]. Importantly, this study suggests that NF-κB and PHD2 constitute a functional circuit, each regulating the activity of the other. Likewise, Ullah and colleagues reported that PHD1 inhibition reduced the inflammatory response in vivo but increased p53 activity [111]. PHD3 interacts with IKKβ, blocking the interaction of IKKβ and Hsp90, avoiding IKKβ phosphorylation independently of PHD3 hydroxylase activity. The low expression of PHD3 in colon cancer is related to a malignant course of the disease together with an increase of NF-κB activity [112]. In other reports, PHD3 binds to IKKγ and inhibits its ubiquitination, decreasing the NF-κB activity [113], which could be protective in the case of cancer. In fact, several reports have demonstrated that IKKγ polyubiquitination is necessary in the activation of IKKγ/NF-κB signaling [114,115,116]. On the other hand, FIH could hydroxylate proteins with an ankyrin repeat domain, including IκBα, IκBε, and p105 [117]; however, a functional effect has not yet been detected [118]. 2.3. STAT Pathway Another important group of proteins related to inflammation and cancer is a protein family known as signal transducer and activator of transcription proteins (STATs). STATs are cytoplasmic proteins that, after their activation, form dimers and translocate to the nucleus to induce the transcription of several genes related to proliferation or immune response [119]. STATs can be activated after the binding of certain cytokines, such as IL-6, INF-γ, or growth factors such as epidermal growth factor (EGF), to their respective receptors. After the binding of IFN-γ and other cytokines to their respective receptors, some associated-receptor tyrosine kinases, such as the JAK family, are activated [120]. In the case of JAK, the dimerization or oligomerization of the receptor allows its activation and subsequent transphosphorylation in the tyrosine residues, and in consequence activates the phosphorylation of the cytoplasmic tails of the receptors [119,121]. This allows the recruitment of STAT proteins through their Src-homology 2 domain (SH2). A third phosphorylation occurs in the tyrosine residues of STATs, which now can form homodimers (STAT1, STAT3, STAT4, STAT5aA, STAT5B) or heterodimers (STAT1 and STAT2, or STAT1 and STAT3) and are allowed to enter the nucleus to work with other co-activators of transcription factors and thus increase the transcription of several genes related to proliferation or immune response (Figure 4) [122]. Alternatively, STATs could be activated by receptors with intrinsic tyrosine kinase activity (RTKs), which bind to growth factors such as EGF or platelet-derived growth factor (PDGF). The RTKs could then activate STATs directly or indirectly through non-receptor tyrosine kinases (NRTKs), such as SRC family kinases, which are recruited to phosphorylate and activate STAT proteins. NRTK could also activate STATs even without the activation of a receptor [119,123]. In cancer, several alterations of this pathway have been reported, including mutations in JAK or STAT, overactivation by an excess of ILs, or the reduction of the negative regulators of the pathway [124]. In these circumstances, the activation of the pathway occurs in both tumoral and immune cells of the surrounding microenvironment and affects processes such as proliferation, escape of apoptosis, and metabolic adaptation. In this sense, STAT3 and STAT5 increase the expression of cyclin D2 and D1, respectively, while STAT3 downregulates p21, both increasing the cell cycle [125]. STAT3 and STAT5 also induce transcription of BCL-xL to avoid apoptosis [125,126,127]. In fact, STAT3 activation promotes the escape of immunosurveillance [128,129], contrary to STAT1, which exerts an antitumoral effect. In particular, STAT3 has been identified as a regulator of inflammation and cancer [130]. In relation with metabolism and hypoxia, STAT3 decreases the mitochondria activity, increases glycolysis, and upregulates HIF-1α and VEGF [131,132,133,134]. Mechanistically, it has been reported that STAT3 seems to stabilize HIF-1α and prevents its degradation, but also accelerates its synthesis de novo [134]. In this sense, in has been reported that STAT3 competes against VHL in the binding of HIF-1α, inhibiting VHL activity and thus increasing HIF-1α stabilization [135]. STAT3 also interacts with HIF-1α to recruit coactivators such as CREB binding protein (CBP), p300, and RNA polymerase II (Pol II) to target gene promoters usually induced by HIF-1α activity [136]. Interestingly, hypoxia induces the activation of Src/PI3K proteins, stabilizing HIF-1α expression levels while it phosphorylates and activates STAT3 [137]. HIF-1α and STAT3 bind to VEGF promoter, forming a complex with CBP/p300 and Ref-1/APE, thus having a synergic effect on the overexpression of VEGF, which is essential to tumoral cell survival in hypoxia and inflammation [132,137]. Additionally, downstream, the expression of Akt as a consequence of STAT3 activation leads to upregulation of HIF when the pathway is stimulated by growth signals such as IL-6, contributing to the upregulation of VEGF [133]. Furthermore, hypoxia seems to induce the activation of other members of the STAT family, such as STAT5 [138,139]. Hypoxia induces the phosphorylation of STAT5, leading to an increment in its binding to DNA, more specifically, in the gene promoter; in this manner, hypoxia would induce the expression of proliferation genes such as cyclin D1 [140]. The intercommunication between STAT and NF-κB pathways with hypoxia reflects the complexity of the hypoxic effects in cancer (Figure 5). It has been proposed that both STAT3 and NF-κB promote tumoral initiation, promotion, and progression through overexpression of pro-tumorigenic genes such as TNF-α, fibroblast growth factor (FGF) 2, VEGF, IL-1β,-8,-11,-12,-17,-22,-23, IFN-δ, vascular cell adhesion-1 (VCAM-1), ICAM-1, C-X-C Motif Chemokine Receptor (CXCR) 4, M-CSF, MCP-1, metalloproteases (MMP) 9,-2, Cyclin D, and c-FLIP [141,142,143,144]. Some target genes of NF-κB, like IL-6, are activators of STAT3, which acetylates RelA, retains NF-κB in the nucleus, and thus prolongs its activity in cancer cells [145]. Ivanova and Perkins have reported that hypoxia induced the translocation of RelA and IκBα from the cytoplasm to the mitochondria. Interestingly, the ROS produced during hypoxia is linked to the recruitment of RelA and IκBα to mitochondria and the authors suggested that STAT3 could facilitate this process [146]. In fact, mitochondrial RelA would regulate mitochondrial energy production and oxygen consumption [147]. The biological processes involved in the intercommunication of hypoxia and STATs are complex. Recently, hypoxia has been related to the induction of pyroptosis through the participation of STAT3 [148]. Pyroptosis is another type of programmed cell death characterized by the participation of gasdermins, a group of proteins that induce the formation of pores in the membrane and the release of pro-inflammatory molecules. Gasdermin D (GSDMD) is activated after it is cleaved by caspases 1, 4, 5, and 11, a group of caspases that do not participate in apoptosis [149]. Interestingly, PD-L1, usually known as a suppressor of anti-tumoral immunity, translocates into the nucleus in hypoxic conditions; however, this is not dependent on HIF-1α. Moreover, this effect was mediated by the phosphorylation in Y705 of STAT3, which interacted with PD-L1. Both nuclear PD-L1 and Y705-STAT3 induce the expression of gasdermin C (GSDMC), which will be cleaved by caspase-8. The stimulation with TNF-α would then induce pyroptosis instead of apoptosis in hypoxia, explaining the mechanism of how TNF-α induces tumor necrosis in hypoxia (Supplementary Figure S1) [148]. Another mechanism underlying the communication between hypoxia and inflammation could be mediated by microRNAs (miRNAs). miRNAs are non-coding RNAs that are 21–23 nt long and that regulate the gene expression at a post-transcriptional level and play an important role in the regulation of inflammation in cancer [150]. In fact, it has been reported that miRNAs regulate the expression of STAT3 through transcription factors such as NF-κB or HIF-1α, with the latter closely related to hypoxia in cancers such as leukemia or colon cancer [151,152]. Interestingly, it has been documented that the induction of hypoxia in acute myeloid leukemia (AML) and the subsequent expression of HIF-1α leads to cell differentiation [153]. In this sense, it has been reported that HIF-1α, through the downregulation of c-Myc, represses miR17 and miR20a, which in turn decreases the expression of STAT3 and p21 in a model of AML [151]. In these cells, the hypoxic microenvironment represents, in the case of HIF-1α activation, a protective system that could be a potential treatment strategy. In the case of colon cancer, the knockout of miR-139-5p activates STAT3, facilitating a pro-tumoral state [150,152]. 3. Cellular Mediators of Inflammation Modulated by the Hypoxic Response as Inductors of Cancer Progression Hypoxia is not restricted to only tumoral cells; it is part of all TMEs, including the cellular mediators of inflammation. We explore in detail the effects of hypoxia in each inflammatory cellular component and how it participates in cancer development (Table 1, Figure 6). 3.1. Macrophages Immune cells as macrophages and neutrophils are attracted to zones with low levels of oxygen, such as wounds, but also to hypoxic tumoral regions. The presence of macrophages is a well-characterized phenomenon that is associated with cancer, and there has been much study of the presence of the macrophages and the correlation with a bad prognosis [211]. Monocytes are recruited to the tumor by chemokines such as CCL2, CCL5, CCL7, CCL8, CXCL12, VEGF, and M-CSF, and become TAMs [154,212]. TAMs release cytokines such as IL-8 or TGF-β and pro-angiogenic factors such as VEGF and FGF2, which induce revascularization to bring nutrients to the zones without irrigation, allowing tumoral progression. In addition, the intercommunication between tumoral cells promotes the release of endothelin-1 and endothelin-2 and induces the secretion of MMP2, MMP7, or MMP9, increasing the metastasis. In addition, TAMs generate an immuno-protective environment, inhibiting the activation of T cells [158]. In addition to the presence of macrophages in the tumor, the subtype of the macrophage is also crucial. Macrophages have a specific subtype, named M1 or M2. The M1 phenotype is activated in the presence of microorganisms or IFN-γ and is characterized by high secretion of IL12/IL-23 but low IL-10. M1 cells have an inflammatory profile and eliminate pathogens and debris and therefore are considered as a tumor suppressor phenotype. In this sense, the M1 phenotype releases IL-12, IFN-γ, TNF-α, IL-1β, ROS, and nitric acid, hence promoting the recruitment and activity of NK cells and CD8 + T cells in the tumor microenvironment to induce an anti-tumor immune function and inflammation. Furthermore, IL-1β, TNF-α, and IL-1 activate NF-κB through binding to their corresponding receptors [213]. On the contrary, the M2 phenotype is related to an anti-inflammatory function, linked to the release of proliferative signals and the revascularization of the tumor. Importantly, the tumoral cells release cytokines that induce the polarization of the TAMs to the M2 phenotype [154,214]. In this sense, the M2 phenotype is induced by signals such as IL4, IL10, IL-13, TGF, M-CSF, and glucocorticoids, among other cytokines. Activated M2 macrophages produce high levels of IL-10, IL-6, and EGF, which activate the JAK/STAT3 signaling. Moreover, M2 macrophages release CCL22, but in contrast to the M1 phenotype, produce low levels of IL-12 [213,215]. CCL22 promotes the infiltration of Treg cells to the tumor, releasing IL-10, which suppresses the antigen presentation function of dendritic cells and the anti-cancer response of CD8+ T cells [213]. On the other hand, studies have reported the overexpression of PD-L1 in M2 macrophages, which binds to CD8+ T cells through the programmed death-1 (PD-1) receptor, thereby achieving the tumor immune escape [213]. However, it is worth noting that there is a combinatorial spectrum of macrophage populations, other particular populations, such as CD169+ macrophages and TCR+ macrophages, have been recognized. Moreover, some groups reassign tumor-associated macrophages as a particular population with a potential switch from the M1 to M2 profile and vice versa, which can be used as a therapeutic approach [216]. In this context, the hypoxic microenvironment induces the M2 phenotype, promoting the survival of tumoral cells. In addition, the low concentration of oxygen modulates the expression of hypoxia-sensitive genes in M2 TAMs, particularly those related to angiogenesis [159]. For example, M2 TAMs secrete IL-6 with the corresponding expression of the IL-6 receptor in the tumoral cells, activating the STAT3 pathway to promote survival in the tumoral cells located in the hypoxic region [162]. Moreover, in a hepatocarcinoma model, hypoxia, as well as the necrotic debris of tumoral cells, induced IL-1β release from M2 TAMs, which up-regulated the expression of HIF-1α through the NF-κB/COX-2 pathway. Interestingly, this profile induces a mesenchymal phenotype in the tumoral cells, characterized by an increment of vimentin and a reduction of E-cadherin [66]. However, even the induction of M2 TAM phenotype by hypoxia is clear; in some cases a pro-inflammatory profile has also been reported [66,163,217]. Importantly, HIF is a key regulator in the bidirectional response between the macrophages and the tumoral cell; therefore, the presence of macrophages in hypoxic conditions has been linked to a bad prognosis. The hypoxic microenvironment, through HIF as the principal mediator, induces the secretion of chemokines, which recruit macrophages and restrain them in the tumor. For example, HIF induces the expression of CCL2 in pancreatic ductal adenocarcinoma cells, which induces the recruitment of macrophages to the tumor [155]. Other chemokines related to monocyte recruitment in hypoxia are CCL5, VEGF, EMAP II, and endothelin-1 and 2 [156]. It has been reported that hypoxia, through HIF-1α, induces the up-regulation of CXCR4 in TAMs but also in endothelial and cancer cells; this axis regulates the migration of the different cells that integrate the TME [157]. In addition, hypoxic macrophages show elevated secretion of CCL4 and promote MMP9 expression in glioblastoma cells, while the hypoxia up-regulates the CCR5 expression [161]. Even more, there is also a clear effect between the recruitment and activation of the tumoral macrophages and the presence of HIF. It seems that HIF benefits the recruitment and the M2 phenotype polarization. For example, the induction of HIF-1α leads to IL-10 expression and, as a consequence, the polarization of M2 macrophages in an inflammatory environment due to obesity [164]. Furthermore, it seems that hypoxia through HIF is a major regulator of the M2 polarization in macrophages, although in some cases it seems that HIF could support the M1 phenotype and also be protective [167]. Recently, it has been reported that hypoxia can contribute to immune evasion avoiding macrophage phagocytosis through the regulation of CD47 expression in cancer cells. CD47 is a cell-surface protein that binds to the signal regulatory protein α (SIRPα) expressed in macrophages, preventing phagocytosis. Moreover, HIF-1α activates the transcription of CD47 in breast cancer cells in hypoxia [218]. As a consequence, anti-CD47 antibodies have been proposed as therapeutic alternatives, with favorable results [219]. Macrophages can also recognize and eliminate tumoral targeted cells marked with antibodies, in a mechanism known as antibody-dependent cellular phagocytosis (ADCP). Fcγ receptors expressed in macrophages recognize and bind to the Fc regions of antibodies, activating a signaling cascade, resulting in phagocytosis being proposed as a possible strategy for immunotherapies [220]. However, ADCP is impaired by the inhibitory receptor FcγRIIb. Interestingly, HIF-1α induced the transcription of FcγRIIb, contributing to the resistance to immunotherapy in hypoxic tumors [221]. Delprat and colleagues make a distinction and propose that intermittent hypoxia, also known as cycling hypoxia (cyH), exacerbates the inflammatory response in the TME. In particular, cyH induces a pro-inflammatory phenotype in unpolarized M0 and amplifies this profile in M1 macrophages through the activation of the c-jun/p65 signaling pathway [222]. Even though the principal and best-characterized mediator of hypoxia is HIF-1α, some evidence suggests that HIF-2α also has an important role in the modulation of the macrophage function. Mice with myeloid cells lacking HIF-2α expression show a diminution in the infiltration of TAMs, apparently through the modulation of the expression of M-CSF receptor and CXCR4, hence reducing the tumoral progression [223]. It seems that the different isoforms of HIF could be induced from a different stimulus. For example, Th1 cytokines benefit the M1 phenotype through HIF-1α, whereas Th2 induces the M2 phenotype through HIF-2α and regulates the NO production [224]. Moreover, the activating transcription factor (ATF4) is stimulated by stress signals, including hypoxia [225]. In this sense, macrophages in hypoxic conditions express not only HIF-1α and HIF-2α, but also ATF4 [226,227]; more importantly, ATF4 is capable of inducing the recruitment of M2 macrophages to the tumor in a hemangioma model [228]. Tumoral hypoxia produces metabolic modifications, including the activation of the glycolytic pathway, the inhibition of oxidative phosphorylation (OXPHOS) in mitochondria, and the accumulation of lactate. HIF-1α is a major inductor of glycolysis, which allows M1 macrophage differentiation. Furthermore, OXPHOS and glycolysis are required for M2 macrophage differentiation. The regulation of this switch would participate in the anti-tumoral protection [165]. On the other hand, lactosis in solid tumors is related to the differentiation of monocytes to macrophages. Moreover, TAMs exhibit an inflammatory profile, such as CXCL1, CCL18, and CCL24, which favor the accumulation of immunosuppressive myeloid cells, T cells, and monocytes, as well as M-CSF, which induces monocyte recruitment and M2 TAM differentiation, conferring a protumor and inflammatory M2 phenotype [163]. The effects of angiogenesis induced by the TAMs go beyond the release of angiogenic factors. Recently, it has been reported that macrophages themselves could form non-endothelial vascularity around the tumor, derived from the hypoxic stimulus [160]. This flexibility is evidence of the multiplicity of the tumoral environment to facilitate tumoral progression. The regulation of the TME is related also to different levels, including miRNAs. These non-coding RNAs regulate different functions in the cell, and it seems that they are involved in the regulation of the immune cells that surround the TME; miRNAs have been extensively reviewed elsewhere [150]. A recent example is miR-155 and miR-21, which regulate the TAM function and reduce tumoral growth [229]. Interestingly, miR-17 and miR-20a regulate the expression of HIF2-α, even in normoxic conditions, and induce a pro-angiogenic response in TAMs [230]. In another example, hypoxia induces the expression and secretion of miR-940 in exosomes of epithelial ovarian cancer, which are delivered in macrophages and lead to M2 polarization and thus cancer progression [166]. 3.2. Fibroblasts The fibroblasts are the most abundant cell type in the stroma and usually secrete extracellular matrix in wounds to achieve reparation, following the evolution in the inflammation process. However, in the complexity of the TME, the CAFs acquire a pro-tumoral function, including the induction of metastasis through the remodeling of the extracellular matrix (ECM) and the secretion of angiogenic and proliferative factors [231]. In this sense, tumor cells induce the transformation of stromal fibroblasts into pro-tumorigenic CAFs through the release of IL-6, TGFβ, PDGF, exosomes, and specific TME stimulus, including hypoxia, acidification, and oxidative stress, which promote the recruitment and activation of fibroblasts [168,169,232]. It has been demonstrated that tumoral cells induce the transformation of fibroblasts isolated from an initial hyperplastic state into CAFs with pro-inflammatory properties. CAFs, through the IL-1β/NF-κB signaling axis, induce the transcription of COX-2, IL-1β, IL-6, CCL3, CXCL1, CXCL2, CXCL5, MMP3, and MMP12, leading to macrophage recruitment, angiogenesis, tumoral growth, and metastasis [233]. In addition, the treatment of fibroblasts with pro-inflammatory leukemia inhibitory factor (LIF) induces an epigenetic switch, through p300 histone acetyltransferases that acetylate STAT3. Then, STAT3 induces the transcription and activation of DNMT3b methyltransferase, which inhibits the tyrosine phosphatase (SHP-1) expression, resulting in constitutive activation of the JAK1/STAT3 pathway and leading to extracellular matrix remodeling and collective migration and invasion of neoplastic cells [234]. Moreover, CAFs impair tumor immunity due to the induction of massive infiltration of myeloid cells into the tumor stroma. CAFs also decrease the proliferation and activation of T cell cytotoxicity [235,236]. However, as previously mentioned, hypoxia and oxidative stress induce the differentiation of CAFs and lead to metastasis. In this regard, ROS induces the conversion of stromal fibroblasts into migrating myofibroblasts, due to the accumulation of HIF-1α, which promotes the activation of the CXCL12/CXCR4/Rho A signaling pathway. These characteristics were found in HER2-human breast carcinomas, which present high rates of cell proliferation, neovascularization, and metastasis [170]. Another approach showed that breast cancer cells lead to the transformation of fibroblasts to CAFs through an autophagic mechanism. Tumoral hypoxia activates HIF-1α and NF-κB transcription factors, which drive the autophagic degradation and loss of Cav-1 with the consequent stabilization of CAFs, thus exerting pro-tumoral actions that will benefit the metastasis of the cancerous cells [171]. In this regard, CAFs play an important role in the regulation of cancer metabolism, primarily through the secretion of metabolites and the generation of a stiffer and fibrotic ECM, which in turn affects cancer cell metabolism. In this sense, it has been proposed that the activation of catabolic and autophagic pathways in CAFs increase the production of metabolites such as pyruvate, lactate, glutamate, and ketone bodies that are available to the surrounding cancer cells; moreover, this correlates with a higher invasive and resistance capacity of these cells through a reciprocal metabolic reprogramming [235,237]. However, the effects of hypoxia on CAFs could seem contradictory. For example, the hypoxic conditions seem to reverse the pro-tumoral phenotype of the CAFs, observed with the impairment of the ECM remodeling and CAF-induced cell invasion, through a mechanism dependent on the inhibition of PHD2 through low oxygen levels and the consequent stabilization of HIF-1α in a breast cancer model, making PHD2 in CAFs a probable therapeutic target [172,173]. 3.3. Natural Killer Cells NK cells are lymphocytes from the innate response associated to antitumor protection [238,239,240]. In this sense, activated NK cells recognize and eliminate tumoral cells without the requirement of previous recognition. For instance, NK cells recruit type 1 dendritic cells to the tumor and promote T1 cell polarization through the release of CCL2, CCL3, CCL4, CCL5, XCL1, and CXCL8, thus inducing anti-tumoral protection [241,242]. NK cells also release granules with cytotoxic content, such as IFN, TRAIL, and FasL. NK cell-through killing is executed by FASL and TRAIL on the NK cell surface, which leads to apoptotic cell death in target cells. Furthermore, the NK cells contain lytic granules with perforin, a protein that causes membrane pores, and granzymes, a family of serine proteases, which are exocytosed to lysed target cells [243]. These properties seem very beneficial to developing new cancer immunotherapies [239]. Cellular acidity derived from anaerobic metabolism due to hypoxia has detrimental effects on NK and T cells [174]. In this sense, the TME facilitates the tumor evasion of the immune system. As the tumor grows and hypoxia is established, cancer cells change their metabolism to a glycolytic profile; in this context, cells metabolize pyruvate to lactate through LDH, inducing an acidic environment. The high levels of lactate and pyruvate induce the accumulation of HIF-1α, even in the presence of oxygen, and as a consequence induce the expression of genes from the HIF-1α pathway, including those that lead to a glycolytic environment [244]. Moreover, LDHA, a target of HIF-1α [245], leads to lactate accumulation, which in turn impairs the function of NK cells and T lymphocytes [175]. High levels of lactate inhibit the production of IFN-γ, apparently through the inactivation of the nuclear factor of activated T cells (NFAT). A diminution in the viability of both NK cells and T lymphocytes was detected in this lactic environment [176]. Moreover, evidence shows that the accumulation of lactate and this acidic environment impairs the cytotoxicity action of NK cells, which is favorable to tumoral cell proliferation and protection from the immune system [175,177]. As previously discussed, hypoxia has a crosslink with the STAT pathway. It has been reported that hypoxia induces impairment of the NK cell cytotoxicity against tumor cells, and this effect is associated with the reduction in the phosphorylation of ERK and STAT3. The ERK and STA3 phosphorylation depend on the activation of the tyrosine phosphatase Src homology region 2 domain-containing phosphatase-1 (SHP-1) by hypoxia; in fact, the pharmacological inhibition of SHP-1 by TPI-1 allows a partial recuperation of NK cytototoxicity [246]. NK cells express the NKG2D transmembrane receptor that binds to their ligand (NKG2DL), present in the tumor cells; thus, NK cells can recognize and kill the tumoral cells [247]. However, the microenvironment may modify the expression of NKG2D receptor or ligand, avoiding tumoral immunosurveillance. For example, in a model of resistant prostate cancer, hypoxia decreased the expression of UL16 binding protein, which is a member of the NKG2D family, and MHC class I chain-related proteins A and B (MICA/MICB). Apparently, hypoxia also induced the expression of PD-L1, which could be blocked with inhibitors of the JAK/STAT3 axis to re-activate the cytotoxic action of NK cells [178]. In accordance with this, another group reported a decrease in MICA expression in osteosarcoma cells, inhibiting the NK cell antitumoral cytotoxicity [181]. In a model of pancreatic cancer, Ou and colleagues found that hypoxia leads to a significant presence of soluble major histocompatibility complex class I, chain-related (sMICA), related to the shedding of membrane MIC (mMICA) from the tumor cell membrane to a soluble form. In addition, the expression of NKG2D was downregulated, avoiding the NK cytotoxicity over tumoral cells [179,180]. Alternatively, the shedding of sMICA could be inhibited by nitric oxide signaling, counteracting the hypoxic effect [248]. Moreover, the participation of dysregulated circRNAs and miRNAs such as circ_0000977/miR-153 was linked to the regulation of HIF-1α. In hypoxia, an increase in the presence of circ_0000977 was detected and correlated with an upregulation of HIF-1α, while miR-153 had the opposite action. More interesting, miR-153 was able to bind to circ_0000977 and HIF-1α, establishing a possible mechanism of regulation. The authors proposed that hypoxia leads to an increase of circ_0000977, which inhibits miR153 and releases its repression over HIF-1α and A Disintegrin and Metalloproteinase Domain 10 (ADAM10). Then, a transition from membranal MICA to soluble MICA occurs; sMICA then bounds to NKG2D over NK cells, decreasing their stimulation and leading to the immune escape of the tumoral cells [180]. In contrast, Sarkar and colleagues suggested that the detrimental action of hypoxia over NK cells could be counteracted with a pre-activation of NK cells by IL-2 using a model of melanoma. Apparently, in this model, they did not find alterations in the levels of MICA/B, HLA-ABC, and ULP1-2 under hypoxia [249]. Hypoxia decreases the levels of other NK cell membrane receptors, such as NKp46, NKp30, and NKG2D, as previously mentioned. Then, NK cell ability to eliminate tumor cells would be reduced [250]. Interestingly, CD16+ NK cells recognize the Fc of immunoglobulins attached to target cells, establishing a mechanism known as antibody-dependent cellular cytotoxicity (ADCC) to eliminate them. Moreover, hypoxia seems not to particularly affect the ADCC mechanism. Solocinski and colleagues used a model with NK cells that overexpress CD16 receptor and showed that these cells maintain their cytotoxic capacities in hypoxic conditions, being a potential strategy for immunotherapy in cancer [251]. It has been observed that hypoxia did not decrease the expression of CD16 receptor in NK cells, contrary to other activating receptors [250]. Metabolic stress such as in the hypoxic microenvironment is also related to the release of eADO. Hypoxia induces dephosphorylation of adenosine triphosphate (ATP) through nucleoside triphosphate dephosphorylases (NTPD) and upregulates the activity of ectonucleotidases such as CD39 and CD73, increasing the adenosine levels. Then, adenosine modulates immune cells through the activation of adenosine receptors such as A1, A2A, A2B, and A3, located in the immune cells [252]. Particularly in NK cells, adenosine seems to inhibit granule exocytosis and the lytic activity of NK cells. An extended review of this topic has been published recently [84]. The TME depends on the intercommunication between the tumoral cells and surrounding cells, and hypoxic signals model this communication in both directions. In a revealing work, Krzywinska and colleagues demonstrated that the deletion of HIF-1α in NK cells impairs their cytotoxicity but decreases tumoral growth [182]. Moreover, the NK cells with HIF-1α deletion were associated with a deficient vasculature in the tumors and consequently with metastasis. The absence of HIF-1α in NK cells was associated with a decreased expression of the soluble form of VEGF receptor 1 (sVEGFR1) in the tumors from mice with NK cells with HIF-1α deletion. Interestingly, sVEGFR1 sequestrates VEGF and modulates its bioavailability. In this case, the secretion of HIF-1α from NK cells leads to the expression of sVEGFR1 and avoids aberrant angiogenesis in tumors through the regulation of bioavailability of VEGF [182]. 3.4. Myeloid-Derived Suppressor Cells The MDSCs are immature myeloid cells that originated in bone marrow from immature myeloid cells (IMCs) and differentiate in dendritic cells, macrophages, and granulocytes. MDSCs are characterized by their suppressive activity over T cells; moreover, MDSCs have been associated with the inhibition of antitumoral immunity and the promotion of tumor progression [190,253,254]. This response is related to the release of pro-angiogenic molecules, including VEGF-A, Bv8, bFGF, elastase, and MMP9 [255,256]. The MDSC are classified according to their lineage into two groups: monocytic MDSCs (M-MDSCs) and polymorphonuclear MDSCs (PMN-MDSCs). MDSCs are activated by several stimuli, such as tissular damage, pathogens, chronic infections, autoimmune diseases, and inflammatory signals in the context of cancer [254]. MDSCs are present in the majority of cancer types, promoting the progression of the tumor and inhibiting the antitumoral immunity mediated by T cells; in fact, this represents an obstacle to the immunotherapies against cancer [190,257]. MDSCs produce high levels of ROS and nitric oxide, which hinder the infiltration, activation, and apoptosis of T cells [255,258,259]. MDSCs also produce ROS and peroxynitrite, which induce the nitration of CTR/CD8 receptors, reducing their interaction to cognate antigen-MHC complexes and thus inhibiting CD8+ T cells [258]. Tumors release prostaglandin E2 (PGE2), inducing the nuclear accumulation of p50 NF-κB in M-MDSCs. Furthermore, p50 facilitates the binding of STAT1 to DNA to activate the transcription of nitric oxide synthase (NOS2) and other genes dependent on IFNγ activation, promoting an immunosuppressive phenotype of MDSCs [260]. Furthermore, MDSCs induce the expression of immunosuppressive cytokines and mediators, such as COX2, arginase (Arg) 2, inducible nitric oxide synthase 2 (iNOS2), PD-L1, TGFβ, IL-10, and CCR5, leading to activation and infiltration of Tregs as well as NK cell inhibition [255,259]. In this context, intratumoral hypoxia induces the expression of immunosuppressor molecules such as CD47 and PD-L, cytokines such as CCL26, and proteins such as ectonucleoside triphosphate diphosphohydrolase 2 (ENTP2/CD39L1), which depend on HIF activity. These molecules act as chemoattractants to recruit and increase the MDSCs in the tumor and to inhibit indirectly the cytotoxicity produced by the NK cells, prevent immune surveillance, and increase tumoral growth and progression [183,184,185]. Moreover, the overexpression of ENTPD2 leads to an increase of AMP, which prevents the differentiation of MDSC and facilitates its accumulation in the tumor [185]. In this sense, some growth factors such as VEGF also act as a chemoattractant of MDSC. MDSC secretes VEGF, inducing angiogenesis [184,190,191,192]. The overexpression of CD45 protein tyrosine phosphatase (PTP) in MDSCs exposed to hypoxia in the tumor site promotes the inactivation of STAT3, resulting in the M-MDSC differentiation to TAM [188]. Moreover, hypoxia induces a shift from the dimeric to the monomeric form of CD45 phosphatase, the more active form of this protein. Apparently, when M-MDSCs migrate to the tumor, the hypoxia induces the overexpression of sialin, a sialic acid transporter, facilitating the transport of sialic acid to the membrane, allowing its binding to CD45 phosphatase and preventing its dimerization. The activation of CD45 phosphatase then leads to inactivation of STAT3, thus facilitating MDSC differentiation into TAM [188]. Likewise, it has been described that HIF-1α mediates the differentiation of MDSCs to TAMs through the upregulation of iNOS and Arg1. Consequently, the expression of nicotinamide adenine dinucleotide phosphate oxidase (NOX) 2 and ROS in MDSCs decreases, leading to the suppression of antigen-specific and nonspecific T cell activity [189]. In addition, hypoxia can increase the MDSC activities through HIF1α/miR-210 signaling. miR-210 enhances the Arg1 activity and NO levels, without alteration of ROS, IL6, IL10, and PD-L1 levels [261]. It has been observed that lactate localized in hypoxic areas induces the recruitment of MDSCs and inactivates NK cells in the tumor site, resulting in a suppression of the anti-tumoral response [175]. In fact, it has been demonstrated that lactate derived from tumor cells upregulates the expression of PD-L1 [262]. In this sense, an essential mechanism of immunosuppression is mediated by HIF-1α/PD-L1 signaling in TAM, MDSCs, and dendritic cells by hypoxia [186,187]. In addition, it has been reported that the upregulation of PD-L1 transcript in hypoxia is mediated by the cooperative interaction of PKM2/HIF-1/p300 on the PD-L1 promoter [187]. Furthermore, PD-L1 on cancer cells induces the glycolytic process through Akt/mTOR signaling, inducing an immunosuppressive tumor microenvironment [263]. The blockade of PD-L1 with a monoclonal antibody in hypoxia reverts the immunosuppressive response, increasing the proliferation and activity of T cells accompanied by the downregulation of IL-6 and IL-10 in MDSCs. Thus, the inhibition of PD-L1 in tumoral hypoxia is proposed as a potential treatment [186]. 3.5. T Cells T cells are also important for adaptative immunity and usually mature in the thymus. Naïve T cells are activated after the interaction of the antigen-T cell receptor to differentiate in CD4+ or CD8+. In the case of CD4+ T cells, they can be divided into helper (Th) and regulatory T cells (Treg). Th cells, in turn, are subdivided into distinct subtypes and activate different cellular types: Th1 releases IFN-γ and IL-2 to activate macrophages and cytotoxic T cells; Th2 secretes IL-4 and IL-13 and activates B cells, while Th17 releases IL-17A to recruit neutrophils and macrophages. Treg suppresses the immune response. CD8+ T cells or cytotoxic T cells release pro-inflammatory cytokines such as INF-γ and TNF-α as well as cytotoxic molecules such as perforin and granzymes and can eliminate cells that are infected. After antigen stimulus, T cells proliferate using aerobic glycolysis, as c-Myc and HIF are important regulators to control glycolysis and glutaminolysis [264]. In particular, hypoxia can also affect the functions of T cells, apparently supporting the antitumoral response. Palazon and colleagues demonstrated that HIF-1α induces a glycolytic profile and increases the migration of CD8+ T cells. Moreover, an increase in the cytotoxic activity of CD8+ T cells was observed, linked to the increase of costimulatory molecules such as CD137, OX40, GITR, PD-1, TIM3, and LAG3 and the production of granzyme B. VEGF-A expression, a target gene of the HIF pathway, is also correlated with tumoral vascularization [193]. Other groups have reported that hypoxia enhanced the lytic activity and function of cytotoxic T lymphocytes (CTLs), related to the increase of granzyme-B [194,195,196]. On the contrary, another group reported that HIF2α and not HIF1α induces cytotoxic differentiation and cytolytic activity over CD8+T using retroviral vectors for ectopic expression of HIF1α and HIF2α in CD8+ T cells [197]. However, there is controversy around hypoxia and its adverse effects in cancer. For example, hypoxia has been linked to radiotherapy resistance. In this sense, hypoxia downregulates the MHC I expression of tumor cells, avoiding their recognition by CD8+ T cells. In addition, hypoxia seems to reduce the levels of CXCL9, CXCL10, and IDO, whose expression is stimulated by IFN-γ, as a potent cytokine with antiproliferative actions [198]. Thus, hypoxia reduces the proliferation and antitumor functions of CD8+ T cells, preventing the antitumoral immune response [199]. Interestingly, the chronic response of T cells to a prolonged stimulus such as cancer has been defined as T cell exhaustion [265]; moreover, the density of exhausted T and B cells, as well as T-cell exhaustion–related genes like PDL1, B7H3, FOXO1, and PRDM1, correlates with a high expression of HIF-1α in glioblastoma [200]. HIF-1α and VEGFA promote the differentiation of the CD8+T cells to exhausted T cells, highlighting their proangiogenic profile [201]. Recently, a subset of T cells that do not recirculate, known as tissue-resident memory T cells (TRM), was identified. TRM cells express CD69 and CD103 in some tissues and secrete different cytokines according to their residency as TGF-β, IL-15, Type I IFN, and IL-12, contributing antitumoral activity and better prognosis. In this sense, the presence of hypoxia and TGF-β1 induce the differentiation of CD8+ T cells to TRM [202]. Moreover, hypoxia promotes the antitumor effect of TRM cells, as was evaluated using a VHL-deficient CD8+ T cell tumoral model [266]. It has been reported that a synergism exists between the expression of TGF-β and hypoxia to induce the differentiation of CD8+ T cells in the TRM, which contributes to antitumoral response [267]. Moreover, another subset of T cells known as gamma delta (γδ) T cells, found in peripheral blood, has been described as expressing characteristics of innate and adaptive immune responses and has been postulated as a candidate for immunotherapy in cancer [268]. Interestingly, hypoxia drives a reduction in γδ T cell cytotoxicity against oral tumoral cells, due to a decrease in the degranulation of the cytotoxic contents and inducing their differentiation to γδT17, which releases IL-17, a pro-tumorigenic cytokine [203]. A precondition of anti-angiogenesis therapy in cancer using anti-VEGF antibodies demonstrated improvement of the function of CD8+ T cells, apparently linked to an increase in hypoxia due to the inhibition of VEGFR2 signaling [269]. In another immunotherapy model, CTLs were preincubated in 1% oxygen and showed that the package of granzyme-B per granule was more efficient and thus their cytotoxic effect improved. This correlates with a better regression of the tumor in vivo in a model of melanoma [270]. Besides the HIF-1α pathway, other signaling pathways can participate and modulate T cell function. For instance, delta-like 1 (DLL1), is a ligand of the Notch pathway that is expressed in endothelial cells and has been linked to aberrant vascularization in cancer, acting as a compensator of tumoral hypoxia. When DLL1 is overexpressed in breast and lung cancer lines, it induces a normal vascularization around the tumor and the activation of CD8+ T cells, which could be useful in cancer immunotherapy, ameliorating the distribution of the antitumoral drugs [271]. Moreover, it has been demonstrated that HIF-1α binds to the FoxP3 promoter and induces its expression. FoxP3 is a crucial regulator of T cell differentiation into Treg, which deploys anti-inflammatory mechanisms associated with a bad prognosis in cancer [204,205]. Recently, the role of HIF-2α in the stabilization of Treg has been characterized. In fact, the knockout of HIF-2α in Treg results in an inability to suppress inflammation; moreover, the implantation of Tregs with the knockout of HIF-2α resulted in a restriction of the tumoral growth in an in vivo model of colon carcinoma [272]. 3.6. B Cells B cells are responsible for the humoral immune response. Briefly, B cells mature in bone marrow, and then they exit to the bloodstream and ganglia, where are exposed and recognize antigens; later, they differentiate into plasmatic or memory cells, both with the capacity to produce antibodies. Normally, B cell development occurs in the bone marrow and implies their maturation and selection through the B cell receptor (BCR). Interestingly, the regulation of HIF-1α is essential for the normal maturation of B cells. A sustained expression of HIF-1α leads to developmental arrest and BCR defects due to suppression of the proapoptotic BCL-2-interacting mediator of cell death (BIM) [273]. Additionally, HIF-1α induces a glycolytic profile in immature B cells [274,275]. Several studies have reported the capacity of B cells to promote an antitumoral function [276,277]. For instance, B cells enhance T cell antitumoral response by acting as antigen presentation cell (APC), or they release effect cytokines as IFN-γ to polarize T cells towards a Th1 or Th2 phenotype [278]. It has been reported that both CD20+ B cells and CD8+ T cells cooperate to induce antitumor immunity in ovarian cancer, increasing patient survival significantly [276]. In another example of anti-tumoral response, margin infiltrating B cells mediated direct cytotoxicity through the secretion of IFN-γ, TRAIL, and granzyme B on hepatoma cells [279]. Furthermore, human B cells stimulated with CpG-oligodeoxynucleotides showed a tumor-killing effect through TRAIL/Apo-2L signaling [280]. The role of hypoxia in B cells in a tumoral context is still under discussion. Lee and colleagues showed that the deletion of HIF-1α induced B cell infiltration and accelerated the progression of pancreatic cancer [206]. On the contrary, B regulatory cells are particularly important in cancer, as they exert an immunosuppressive role. B regulatory cells secrete TGFβ and IL-10; in fact, IL-10 suppresses innate immune responses, which results in tumoral protection [281]. However, in cancer, hypoxia seems to enhance the IL-10 production by B cells. For instance, hypoxia induces the expression of the high-mobility group B1 (HMGB1) in the tumor cell-released autophagosomes (TRAPs), which in turn induce IL-10 production in B cells, with a consequent suppression of T cell function and thus protection for tumors against immune response [207]. 3.7. Endothelial Cells Diverse stimuli such as proinflammatory cytokines and TNF-α in the circulation activate endothelial cells, increasing their permeability and inducing leukocyte adhesion. Endothelial cells under proinflammatory conditions induce the expression of E-selectin [282] and P-selectin overexpression [283] to promote the “tethering” and “rolling” of leukocytes through interaction between selectins and their PSGL-1 ligands [284]. Endothelial cells also release cytokines such as IL-8, which binds to CXCR1 and CXCR2 on neutrophils [285,286], and chemokines including CCL2 or MCP-1, which act through CCR4 and CCR2 on T lymphocytes and monocytes [287,288]. Leukocyte rolling is controlled by the expression of specific adhesion molecules on leukocytes and endothelial cell surfaces. The endothelial cells express the surface integrins ICAM-1 and VCAM-1, leading to the expression, spreading, and clustering of receptors such as VLA-4 and LFA-1 in the leukocytes, mediating the adhesion and transmigration of the leukocytes into the subendothelial spaces of the vessel wall [288,289,290,291,292]. The mechanisms of adhesion of cancer cells to endothelial cells and the transmigration through the endothelium are still under discussion. Tremblay and colleagues demonstrated that E-selectin induced by IL-1 is necessary for the adhesion and rolling of circulating colon neoplastic cells on endothelial cells and also is required by subsequent diapedesis [293]. The authors suggested that colon cancer cells bind at endothelial cells and induce an endothelial cell retraction and blebbing; thus, cancer cells can be engulfed in large vacuoles and transported within and through the endothelial cells [293]. In this sense, it has been demonstrated that breast adenocarcinoma MCF-7 cells were able to adhere to endothelial cells and promote their retraction as well as promote the apoptosis of HUVEC, inducing transendothelial migration [294,295]. In addition, Laferrière and colleagues reported that TNF-α mediated the adhesion between HT-29 colon cancer cells and HUVEC cells via E-selectin upregulation [296]. This process promotes the activation of SAPK2/p38/HSP27signaling in HT-29, enhancing mobility and transendothelial migration [282]. Furthermore, it has been suggested that tumor cells promote the apoptotic death of endothelial cells and migrate through a cavity formed in an endothelial cell monolayer [297]. In addition, it has been proposed that the tumor cell transmigrates through the endothelial cell–cell contacts [297]. In this sense, vascular tissues showed that VE-cadherin–containing adherent junctions were relocated and not opened or disrupted, whereas PECAM-1–containing junctions were opened during PMN transendothelial migration [298]. The permeability of endothelial cells to circulating tumor cells (CTCs) has a key role in the induction of metastasis, and this characteristic could be affected by hypoxia. Using a model of lung cancer, acute hypoxia leads to the stabilization of HIF-1α, increasing microvascular permeability and allowing the retention of myeloid cells, thus establishing a pro-metastatic environment characterized by a decrease in endothelial cells (CD31+CD45−). The expression of HIF-2α predominates in chronic hypoxia, decreasing the capacity of endothelial cells to permeate to CTC. In hypoxic conditions, the intercellular adhesion molecule 1 (ICAM1), involved in endothelium-macrophage adhesion, and the levels of CCL2, a cytokine that allows the interaction of endothelial cells and macrophages, were elevated, contributing to macrophage recruitment and metastasis. Moreover, myeloid cell infiltration was notably higher [208]. On the other hand, Schmedtje and colleagues reported that hypoxia induces the transcription of COX-2 through p65 NF-κB activation in HUVEC cells [299]. It has been suggested that prostaglandin and PAF synthesis in endothelial cells by COX-2 and PLA2 induces the adherence of neutrophils to the endothelium after hypoxia [209,300]. It has also been demonstrated that hypoxia promotes the endothelial ICAM-1 upregulation as well as monocyte–endothelium interaction by HIF1/Arg2/mitochondrial ROS [210]. 4. Targeting Tumor Hypoxia and Inflammation The hypoxic phenomenon around the tumoral cells involves an intricate flux of immune cells, which ultimately facilitates tumoral growth. In addition, this characteristic is related to resistance to radio and chemotherapy. However, with the increasing knowledge of these interactions, new options are available for different therapeutic approaches. The perspectives are encouraging, and new alternatives to regulate the actions of NF-κB and HIF have been tested in a model of colitis, a factor related to the early onset of colon cancer [301,302]. For example, two natural-origin compounds, caffeic acid phenethyl ester (CAPE) and piceatannol (PIC), were nano-encapsulated in an albumin matrix and reduced the inflammation and also the levels of HIF-1α and p65 in an in vivo model with mice [301], though the mechanism for this effect was not clear. In the near future, there will likely be more alternatives to manage inflammation and cancer. Another option is to target HIF in the tumoral cells. There are several inhibitors at different levels of the HIF pathway, including the dimerization of HIF-1α/HIF-1β, the binding of HIF-1α to DNA, or the interactions of HIF-1α with other proteins. In addition, other inhibitors act indirectly, avoiding the HIF-1α translation and stabilization or, on the contrary, benefitting the degradation of HIF-1α [303]. Recently, a HIF-2α inhibitor called Belzutifan was approved by the FDA and used to treat tumors derived from VHL diseases such as renal cell carcinoma [304,305]. Patients with VHL disease will develop several tumors in their lifetime that require surgery; however, systemic therapy such as HIF-2α inhibitor administration in patients with lesions less than 3 cm in diameter would reduce their surgical interventions and the rate of metastasis. Nearly 50% of the patients with ccRCC showed an objective response, even though the expected secondary effects such as anemia or fatigue were observed. Moreover, an improvement in pancreatic lesions and hemangioblastoma was also documented. Therefore, the downregulation of hypoxic mediators such as HIF-2α results in a reduction of the proliferation rate of tumoral cells with VHL defects [306]. HCC is characterized by extensive vascularization. The overexpression of VHL protein as a therapeutic approach attempts to decrease the pro-tumorigenic effects of the HIF pathway. For instance, the overexpression of VHL with the coadministration of doxorubicin leads to a decrease in cell proliferation and angiogenesis, in addition to the downregulation of NF-κB, using a murine model [307]. Moreover, Iwamoto and colleagues analyzed the effect of a synthetic sulfoglycolipid known as sulfoquinovosyl-acylpropanediol (SQAP) to upregulate the expression of VHL protein using samples of HCC xenotransplanted to mice. SQAP decreased the expression of HIF-1α, HIF-2α, and NF-κB, leading to a downregulation of the tumoral angiogenesis and thus making VHL a possible therapeutic target in vascularized tumors [308]. Several strategies point to inhibiting the TGF-β effects, which are upregulated in hypoxia. For instance, the administration of an inhibitor of the TGFBR1, known as LY2109761, together with transarterial embolization (TAE) in a model of liver cancer resulted in suppression of tumor growth and metastasis [309]. Another approach attempted to inhibit TGF-β through a TGFBR2 blockade in CD4+ T cells to increase an antitumoral response in tumors resistant to antiangiogenic immunotherapies. To do this, the authors designed a CD4 TGF-β Trap (4T-Trap), which consisted of the TGF-β-neutralizing TGFBR2 extracellular domain attached to a non-immunosuppressive CD 4 antibody; 4T-Trap inhibited the TGF-β signaling cascade in TH cells, leading to remodeling of vasculature and cancer cell death [310]. A different approach that has gained interest is centered on TAMs. One method could be the inhibition of the recruitment of the macrophages to the tumor through the CCL2/CCR2 axis. This includes inhibitors such as trabectedin, monoclonal antibodies such as carlumab directed to CCL2, or inhibitors of CCR2 such as PF-04136309 [311]. The complementary therapy of TAMs as a target could help in synergy with other approaches. For example, an inhibitor of CXCL-12 known as Olaptesed pegol (NOX-A12) prevented the recruitment of the macrophages in a hypoxic environment and helped to prevent the resistance of an anti-angiogenic approach in a glioma model in vivo [312]. The M-CSF/M-CSFR axis is also a target in the regulation of the macrophage pro-tumoral activity, as it activates the M2 macrophage activity, using synthetic inhibitors as PLX6134 or PLX3397 [313]. It is feasible to think about the reprogramming of the macrophages to the M1 phenotype through TLR agonists or anti-CD40 antibodies [311,313]. In an in silico study, bioactive compounds derived from Annona muricata, a tropical plant with anti-inflammatory effects, potentially disrupted the interaction between TLR4 and its ligand and thus the activation of HIF-1α [314]. In an interesting approach, a targeted therapy was proposed using macrophages as vectors to the tumoral cells carrying genes that are activated by hypoxia-responsive promoters, resulting in a more specific treatment focus in the hypoxic tumoral and resistant cells [154]. It has also been postulated to use macrophages as carriers of nanoparticles that can be directed to the tumor, exploiting the capability of recruitment around the tumor and providing more specific delivery of the antineoplastic drug in a glioma model [315]. In a similar approach, macrophages could engulf and transport nanoshells of gold, be attracted to the hypoxic tumoral areas, and then be eliminated by photothermal ablation [316]. In parallel, Hayasi and colleagues evaluated the pharmacological activation of p53 using DS-5272, an inhibitor of the interaction between MDM2 and non-mutated p53. This effect is related to the fact that MDM2 is a ubiquitin ligase that sends p53 to proteasomal degradation. They found that DS-5272 is capable of inducing an inflammatory response in leukemia cells, including the up-regulation of PDL-L1, which suppresses the activity of NK and T cells. In accordance, the expression of PDL-L1 depended on HIF-1α. Thus, hypoxia and the induction of the HIF-1α/PD-L1 axis lead to evasion of the immune system and induce a resistant phenotype in cells treated with DS-5272 [317]. Hypoxia is also a factor that challenges the success of immunotherapy. Immune checkpoint blockade (ICB) using PD-1 inhibitors was proposed to treat cancer; however, some patients failed to respond. Interestingly, the hypoxic microenvironment contributes to the resistance to immunotherapy. In this sense, Kumagi and colleagues reported that high levels of lactate induced the expression of PD-1 in Treg cells. Glycolytic activity is associated with high lactate levels, and hypoxia could promote glycolysis; furthermore, Treg cells metabolize free fatty acids and can proliferate in hypoxic conditions. When lactate is introduced to the cell through the monocarboxylate transporter 1 (MCT1), NFAT1 is translocated to the nucleus to induce the expression of PD-1, which is linked to an immunosuppressive function and thus contributes to the tumoral evasion of the immune surveillance and the resistance to the therapy with ICB [318]. As the relation between the cells that integrate the TME is understood more deeply, new approaches can be proposed using different techniques, such as gene therapy. For example, a vector could be designed with a promoter constructed with hypoxic and cytokine-inducible enhancers targeting tumoral endothelial cells [319]. 5. Conclusions The intricate and complex TME is influenced by low levels of oxygen in solid tumors. An adaptation occurs to perpetuate the viability of tumoral cells and also affects the immune cellular components that enrich the TME. As we show in this review, inflammation and hypoxia are closely linked and support the progression of cancer. Particularly, hypoxia influences the cellular components of the inflammation response and becomes a factor in tumoral resistance. Hopefully, having a more comprehensive panorama of the TME opens a new perspective to strategies that are directed not only to the tumoral but also surrounding immune cells to restrain the progression of cancer in a more integrative and effective manner. Acknowledgments We appreciate the assistance and the valuable comments provided by Israel Pérez-López and José Luis Hernández-Islas. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14092291/s1, Figure S1: Connection between hypoxia and pyroptosis. Click here for additional data file. Author Contributions Conceptualization, R.A.C.-R. and V.M.D.-B.; methodology, R.A.C.-R., A.C.-C., C.T.-S., S.G.-M. and V.M.D.-B.; software, R.A.C.-R., A.C.-C., C.T.-S., S.G.-M. and V.M.D.-B.; validation, R.A.C.-R., A.C.-C., C.T.-S., S.G.-M. and V.M.D.-B.; formal analysis, R.A.C.-R., A.C.-C., C.T.-S., S.G.-M. and V.M.D.-B.; investigation, R.A.C.-R., A.C.-C., C.T.-S. and S.G.-M.; resources, R.A.C.-R. and V.M.D.-B.; data curation, R.A.C.-R., A.C.-C., C.T.-S. and S.G.-M.; writing—original draft preparation, R.A.C.-R., A.C.-C., C.T.-S. and S.G.-M.; writing—review and editing, R.A.C.-R., A.C.-C., C.T.-S., S.G.-M. and V.M.D.-B.; visualization, R.A.C.-R., A.C.-C. and C.T.-S.; supervision, R.A.C.-R.; project administration, R.A.C.-R.; funding acquisition, R.A.C.-R. and V.M.D.-B. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 HIF-1α pathway. In normoxia (left), HIF-1α is hydroxylated by PHDs to be recognized by VHL, which adds ubiquitin units to send HIF-1α to the proteosome to be degraded. In hypoxia (right), PHDs are inactivated and HIF-1α is translocated to the nucleus, forming a dimmer with HIF-1β to induce the transcription of several target genes. VEGF, Vascular Endothelial Growth Factor; EPO, erythropoietin; LDH, Lactate Dehydrogenase; TGF-β, Transforming Growth Factor β; CAIX, Carbonic Anhydrase 9; MMP2, Matrix Metallopeptidase 2; GLUT1, Glucose transporter 1. Figure 2 Interrelation between the HIF pathway, inflammation, and cancer. (a) In ccRCC, VHL is inactive, leading to HIF-1α and HIF-2α accumulation. As a consequence, there is a decrease in antitumoral response due to low levels of HIF-1α, IFN, and CD8+ inactivated cells. (b) Inflammation- induced by COPD with the overexpression of HIF-1α leads to overactivation of KRAS signaling and cancer. (c) Viruses such as HBV also induce inflammation that synergizes with hypoxia as factors to induce cancer. (d) Correlation between the expression of TLR and nuclear HIF-1α was observed in early carcinogenesis of the pancreas. (e) IL-6, NF-κB, and IFN-α induce the overexpression of HIF-1α; indirectly, TNF-α and MCP1 also induce HIF-1α through the NF-κB/COX2 axis. HIF-1α also induces the expression of COX2. (f) HIF-1α stimulates TAMs and tumoral cells to release IL-1β, which stimulates CAFs. Tumoral cells also secrete TGF-β. (g) HIF-1α induces and regulates the expression of CD39 and CD73 to obtain eADO. (h) Hypoxic tumoral cells release exosomes enriched with molecules, such as TGFβ-inducing M2 TAMs recruitment. Abbreviations: clear cell renal cell carcinoma, ccRCC; chronic obstructive pulmonary disease, COPD; hepatitis B virus, HBV; toll-like receptors, TLR; interleukin 1-beta, IL-1β; tumor necrosis factor-α, TNF-α; interferons, IFN; monocyte chemoattractant protein 1, MCP1; extracellular adenosine, eADO. See more details in the main text. Lung icon of Figure 2b is from Servier Medical Art. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/, accessed on 2 January 2022). Figure 3 Canonical and non-canonical pathway of NF-κB. On the (left), p50/p65 subunits are inhibited by IκBs; however, when the pathway is activated, IκBs are phosphorylated by the IKK complex integrated by IKKα, IKKβ, and IKKγ and sent to degradation. Then, the p50/p65 are released and translocated in the nucleus to activate the transcription of the target genes. On the (right), in the non-canonical pathway, RelB is sequestered by p100. When the pathway is activated, IKKα phosphorylates and sends p100 to degradation. Then, RelB is released and forms a dimer with p52, which is translocated to the nucleus. Abbreviations: IκB kinase complex (IKK); Transforming growth factor-β–activated kinase 1 (TAK); NF-κB-Inducing Kinase (NIK). Figure 4 STAT pathway. After the interaction of the ligands with their corresponding receptors, associated tyrosine kinases, such as JAKs, are transphosphorylated to then phosphorylate the cytoplasmic tail receptors. Then, STATs are recruited, and both are phosphorylated to form dimers that are translocated into the nucleus to activate gene transcription (see details in the text). Figure 5 Intercommunication between HIF, NF-κB, and STAT pathways during hypoxia. Hypoxia induces NF-κB activity through CaMK2 and the presence of TAK and IKK, leading to the sumoylation of IκBα. TNF-α also increases HIF-1α levels through the NF-κB pathway. Hypoxia through HIF-1α also induces phosphorylation of the inhibitory IκBα for its degradation and thus activation of NF-κB. Moreover, hypoxia inactivates the PHD hydroxylation over IKKβ, which conducts IKKβ to degradation; instead, IKKβ phosphorylates IκBα to finally activate NF-κB. STAT3 induces HIF-1α expression and avoids its degradation, even independently of hypoxia, inducing gene transcription. STAT3 and HIF-1α interact and recruit coactivators to induce gene transcription, including VEGF. Hypoxia induces the expression of Src, which leads to STAT3 activation and, in consequence, HIF-1α stabilization. Akt is also activated by STAT3, and as feedback, induces HIF-1α expression. miR17 and miR20a inhibit differentiation and STAT3 activation. However, HIF-1α inhibits these miRNAs and avoids their effects (see more details in the main text). Figure 6 Intercommunication between tumoral and immune cells in hypoxia. Hypoxia triggers the activation of HIF-1α, NFκB, and STAT pathways, boosting the transcription and releasing of chemotactic factors (CXCL12, VEGF, and CCL-2, -5, -7, -8, -12 and -26), pro-inflammatory cytokines (TNF-α, TNFβ, and IL-1,-6) as well as the secretion of exosomes, PD-L1, lactate, PGE2, ROS, and NO, among other molecules that targets immune cells. Red arrows represent the stimulation of immune cells, whereas red truncated arrows represent inhibition. These signal molecules activate several mechanisms that result in the infiltration of pro-tumor immune cells, such as TAMs, MDSCs, CAFs, Ns, and Treg cells, to the tumor, which suppress the anti-tumor response of CD8+ cells, B cells, NK cells, and dentric cells (DCs). Immune cells, in response, release IL-1β, -4, -6, -8, -10, -12, -13, -17, CCL-1, -2, -3, -5, -22, TNFα, TNF-β, IFN-γ,M- CSF, VEGF, bFGFβ, PDGF, PDL1, MMP-2,-9, Arg-1, NOX2, and COX-2 as well as the release of glutamate, pyruvate, and lactate among other molecules, resulting in the promotion of inflammation, metabolic adaptations, growth of tumors, epithelial to mesenchymal transition, angiogenesis, migration, invasion, metastasis, and resistance to chemo, radio, and immune therapy. Black arrows represent the stimulation of tumoral cells, whereas black truncated arrows represent inhibition. See main text for more details. cancers-14-02291-t001_Table 1 Table 1 Effects of hypoxia over cellular components of immune response. Cell Type Effects of Hypoxia References TAMs Recruitment to hypoxic regions Release of pro-angiogenic factors and revascularization Promotion of secretion of MMPs in tumoral cells Switching to M2 phenotype [154,155,156,157] [156,158,159,160] [161] [162,163,164,165,166] CAFs Induction and stabilization of pro-tumorigenic CAFs Reversal of pro-tumoral phenotype [167,168,169,170,171] [172,173] NK cells Impairment of NK cells function [174,175,176,177,178,179,180,181,182] MDSC Recruitment to tumor and inhibition of immune response Differentiation to TAMs Release of VEGF [175,183,184,185,186,187] [188,189] [184,190,191,192] T cells Enhanced recruitment and lytic activity (CD8+) Decreased anti-tumoral functions of CD8+ Differentiation in TRM or exhausted T cells Reduction of antitumoral γδ T cells Differentiation of anti-inflammatory Tregs [193,194,195,196,197] [198,199] [200,201,202] [203] [204,205] B cells Decrease of B cell infiltration Suppression of T cell antitumoral response [206] [207] Endothelial cells Increase of microvascular permeability Increase of cell adhesion [208] [209,210] TAMs: Tumoral associated-macrophages; CAFs: cancer-associated fibroblasts; NKs, Natural Killers, MDSCs: Myeloid-Derived Suppressor Cells. See more details in the main text. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Singhal R. Shah Y.M. Oxygen battle in the gut: Hypoxia and hypoxia-inducible factors in metabolic and inflammatory responses in the intestine J. Biol. Chem. 2020 295 10493 10505 10.1074/jbc.REV120.011188 32503843 2. Takahashi H. Ogata H. Nishigaki R. Broide D.H. Karin M. Tobacco smoke promotes lung tumorigenesis by triggering IKKbeta- and JNK1-dependent inflammation Cancer Cell 2010 17 89 97 10.1016/j.ccr.2009.12.008 20129250 3. Russo F.P. Zanetto A. Pinto E. Battistella S. Penzo B. Burra P. Farinati F. Hepatocellular Carcinoma in Chronic Viral Hepatitis: Where Do We Stand? Int. J. Mol. Sci. 2022 2 500 10.3390/ijms23010500 4. Chan C.K. Aimagambetova G. Ukybassova T. Kongrtay K. Azizan A. Human Papillomavirus Infection and Cervical Cancer: Epidemiology, Screening, and Vaccination-Review of Current Perspectives J. Oncol. 2019 2019 3257939 10.1155/2019/3257939 31687023 5. Jin M.Z. Jin W.L. The updated landscape of tumor microenvironment and drug repurposing Signal Transduct. Target. Ther. 2020 5 166 10.1038/s41392-020-00280-x 32843638 6. Giraldo N.A. Sanchez-Salas R. Peske J.D. Vano Y. Becht E. Petitprez F. Validire P. Ingels A. Cathelineau X. Fridman W.H. The clinical role of the TME in solid cancer Br. J. Cancer 2019 120 45 53 10.1038/s41416-018-0327-z 30413828 7. Zhang Q. Yan Q. Yang H. Wei W. Oxygen sensing and adaptability won the 2019 Nobel Prize in Physiology or medicine Genes Dis. 2019 6 328 332 10.1016/j.gendis.2019.10.006 31832511 8. Wang G.L. Jiang B.H. Rue E.A. Semenza G.L. Hypoxia-inducible factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated by cellular O2 tension Proc. Natl. Acad. Sci. USA 1995 92 5510 5514 10.1073/pnas.92.12.5510 7539918 9. Zhu C. Yu J. Pan Q. Yang J. Hao G. Wang Y. Li L. Cao H. Hypoxia-inducible factor-2 alpha promotes the proliferation of human placenta-derived mesenchymal stem cells through the MAPK/ERK signaling pathway Sci. Rep. 2016 6 35489 10.1038/srep35489 27765951 10. Gu Y.Z. Moran S.M. Hogenesch J.B. Wartman L. Bradfield C.A. Molecular characterization and chromosomal localization of a third alpha-class hypoxia inducible factor subunit, HIF3alpha Gene Expr. 1998 7 205 213 9840812 11. Wang G.L. Semenza G.L. Purification and characterization of hypoxia-inducible factor 1 J. Biol. Chem. 1995 270 1230 1237 10.1074/jbc.270.3.1230 7836384 12. Tian H. McKnight S.L. Russell D.W. Endothelial PAS domain protein 1 (EPAS1), a transcription factor selectively expressed in endothelial cells Genes Dev. 1997 11 72 82 10.1101/gad.11.1.72 9000051 13. Hara S. Hamada J. Kobayashi C. Kondo Y. Imura N. Expression and characterization of hypoxia-inducible factor (HIF)-3alpha in human kidney: Suppression of HIF-mediated gene expression by HIF-3alpha Biochem. Biophys. Res. Commun. 2001 287 808 813 10.1006/bbrc.2001.5659 11573933 14. Epstein A.C. Gleadle J.M. McNeill L.A. Hewitson K.S. O’Rourke J. Mole D.R. Mukherji M. Metzen E. Wilson M.I. Dhanda A. C. elegans EGL-9 and mammalian homologs define a family of dioxygenases that regulate HIF by prolyl hydroxylation Cell 2001 107 43 54 10.1016/S0092-8674(01)00507-4 11595184 15. Berra E. Benizri E. Ginouves A. Volmat V. Roux D. Pouyssegur J. HIF prolyl-hydroxylase 2 is the key oxygen sensor setting low steady-state levels of HIF-1alpha in normoxia EMBO J. 2003 22 4082 4090 10.1093/emboj/cdg392 12912907 16. Hsu Y.L. Hung J.Y. Chang W.A. Lin Y.S. Pan Y.C. Tsai P.H. Wu C.Y. Kuo P.L. Hypoxic lung cancer-secreted exosomal miR-23a increased angiogenesis and vascular permeability by targeting prolyl hydroxylase and tight junction protein ZO-1 Oncogene 2017 36 4929 4942 10.1038/onc.2017.105 28436951 17. Jaakkola P. Mole D.R. Tian Y.M. Wilson M.I. Gielbert J. Gaskell S.J. von Kriegsheim A. Hebestreit H.F. Mukherji M. Schofield C.J. Targeting of HIF-alpha to the von Hippel-Lindau ubiquitylation complex by O2-regulated prolyl hydroxylation Science 2001 292 468 472 10.1126/science.1059796 11292861 18. Yu F. White S.B. Zhao Q. Lee F.S. HIF-1alpha binding to VHL is regulated by stimulus-sensitive proline hydroxylation Proc. Natl. Acad. Sci. USA 2001 98 9630 9635 10.1073/pnas.181341498 11504942 19. Groulx I. Lee S. Oxygen-dependent ubiquitination and degradation of hypoxia-inducible factor requires nuclear-cytoplasmic trafficking of the von Hippel-Lindau tumor suppressor protein Mol. Cell Biol. 2002 22 5319 5336 10.1128/MCB.22.15.5319-5336.2002 12101228 20. Lisztwan J. Imbert G. Wirbelauer C. Gstaiger M. Krek W. The von Hippel-Lindau tumor suppressor protein is a component of an E3 ubiquitin-protein ligase activity Genes Dev. 1999 13 1822 1833 10.1101/gad.13.14.1822 10421634 21. Chakraborty C. Mitra S. Roychowdhury A. Samadder S. Dutta S. Roy A. Das P. Mandal R.K. Sharp T.V. Roychoudhury S. Deregulation of LIMD1-VHL-HIF-1alpha-VEGF pathway is associated with different stages of cervical cancer Biochem. J. 2018 475 1793 1806 10.1042/BCJ20170649 29654110 22. Lando D. Peet D.J. Gorman J.J. Whelan D.A. Whitelaw M.L. Bruick R.K. FIH-1 is an asparaginyl hydroxylase enzyme that regulates the transcriptional activity of hypoxia-inducible factor Genes Dev. 2002 16 1466 1471 10.1101/gad.991402 12080085 23. Lando D. Peet D.J. Whelan D.A. Gorman J.J. Whitelaw M.L. Asparagine hydroxylation of the HIF transactivation domain a hypoxic switch Science 2002 295 858 861 10.1126/science.1068592 11823643 24. Mahon P.C. Hirota K. Semenza G.L. FIH-1: A novel protein that interacts with HIF-1alpha and VHL to mediate repression of HIF-1 transcriptional activity Genes Dev. 2001 15 2675 2686 10.1101/gad.924501 11641274 25. Semenza G.L. Roth P.H. Fang H.M. Wang G.L. Transcriptional regulation of genes encoding glycolytic enzymes by hypoxia-inducible factor 1 J. Biol. Chem. 1994 269 23757 23763 10.1016/S0021-9258(17)31580-6 8089148 26. Holmquist-Mengelbier L. Fredlund E. Lofstedt T. Noguera R. Navarro S. Nilsson H. Pietras A. Vallon-Christersson J. Borg A. Gradin K. Recruitment of HIF-1alpha and HIF-2alpha to common target genes is differentially regulated in neuroblastoma: HIF-2alpha promotes an aggressive phenotype Cancer Cell 2006 10 413 423 10.1016/j.ccr.2006.08.026 17097563 27. Buffa F.M. Harris A.L. West C.M. Miller C.J. Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene Br. J. Cancer 2010 102 428 435 10.1038/sj.bjc.6605450 20087356 28. Tolonen J.P. Heikkila M. Malinen M. Lee H.M. Palvimo J.J. Wei G.H. Myllyharju J. A long hypoxia-inducible factor 3 isoform 2 is a transcription activator that regulates erythropoietin Cell Mol. Life Sci. 2020 77 3627 3642 10.1007/s00018-019-03387-9 31768607 29. Yang Y.J. Na H.J. Suh M.J. Ban M.J. Byeon H.K. Kim W.S. Kim J.W. Choi E.C. Kwon H.J. Chang J.W. Hypoxia Induces Epithelial-Mesenchymal Transition in Follicular Thyroid Cancer: Involvement of Regulation of Twist by Hypoxia Inducible Factor-1alpha Yonsei Med. J. 2015 56 1503 1514 10.3349/ymj.2015.56.6.1503 26446630 30. Bao L. Chen Y. Lai H.T. Wu S.Y. Wang J.E. Hatanpaa K.J. Raisanen J.M. Fontenot M. Lega B. Chiang C.M. Methylation of hypoxia-inducible factor (HIF)-1alpha by G9a/GLP inhibits HIF-1 transcriptional activity and cell migration Nucleic Acids Res. 2018 46 6576 6591 10.1093/nar/gky449 29860315 31. Kim D.H. Hossain M.A. Kim M.Y. Kim J.A. Yoon J.H. Suh H.S. Kim G.Y. Choi Y.H. Chung H.Y. Kim N.D. A novel resveratrol analogue, HS-1793, inhibits hypoxia-induced HIF-1alpha and VEGF expression, and migration in human prostate cancer cells Int. J. Oncol. 2013 43 1915 1924 10.3892/ijo.2013.2116 24100602 32. Cabrera-Cano A. Davila-Borja V.M. Juarez-Mendez S. Marcial-Quino J. Gomez-Manzo S. Castillo-Rodriguez R.A. Hypoxia as a modulator of cytochromes P450: Overexpression of the cytochromes CYP2S1 and CYP24A1 in human liver cancer cells in hypoxia Cell Biochem. Funct. 2021 39 478 487 10.1002/cbf.3612 33377261 33. Gkotinakou I.M. Kechagia E. Pazaitou-Panayiotou K. Mylonis I. Liakos P. Tsakalof A. Calcitriol Suppresses HIF-1 and HIF-2 Transcriptional Activity by Reducing HIF-1/2alpha Protein Levels via a VDR-Independent Mechanism Cells 2020 9 2440 10.3390/cells9112440 34. Melstrom L.G. Salabat M.R. Ding X.Z. Strouch M.J. Grippo P.J. Mirzoeva S. Pelling J.C. Bentrem D.J. Apigenin down-regulates the hypoxia response genes: HIF-1alpha, GLUT-1, and VEGF in human pancreatic cancer cells J. Surg. Res. 2011 167 173 181 10.1016/j.jss.2010.10.041 21227456 35. Kataria N. Martinez C.A. Kerr B. Zaiter S.S. Morgan M. McAlpine S.R. Cook K.M. C-Terminal HSP90 Inhibitors Block the HIF-1 Hypoxic Response by Degrading HIF-1alpha through the Oxygen-Dependent Degradation Pathway Cell Physiol. Biochem. 2019 53 480 495 10.33594/000000152 31486323 36. Valencia-Cervantes J. Huerta-Yepez S. Aquino-Jarquin G. Rodriguez-Enriquez S. Martinez-Fong D. Arias-Montano J.A. Davila-Borja V.M. Hypoxia increases chemoresistance in human medulloblastoma DAOY cells via hypoxiainducible factor 1alphamediated downregulation of the CYP2B6, CYP3A4 and CYP3A5 enzymes and inhibition of cell proliferation Oncol. Rep. 2019 41 178 190 10.3892/or.2018.6790 30320358 37. Kelly C.J. Hussien K. Fokas E. Kannan P. Shipley R.J. Ashton T.M. Stratford M. Pearson N. Muschel R.J. Regulation of O2 consumption by the PI3K and mTOR pathways contributes to tumor hypoxia Radiother. Oncol. 2014 111 72 80 10.1016/j.radonc.2014.02.007 24631147 38. Mylonis I. Chachami G. Samiotaki M. Panayotou G. Paraskeva E. Kalousi A. Georgatsou E. Bonanou S. Simos G. Identification of MAPK phosphorylation sites and their role in the localization and activity of hypoxia-inducible factor-1alpha J. Biol. Chem. 2006 281 33095 33106 10.1074/jbc.M605058200 16954218 39. Gkotinakou I.M. Befani C. Simos G. Liakos P. ERK1/2 phosphorylates HIF-2alpha and regulates its activity by controlling its CRM1-dependent nuclear shuttling J. Cell Sci. 2019 132 jcs225698 10.1242/jcs.225698 30962349 40. Wen X. Liu X. Mao Y.P. Yang X.J. Wang Y.Q. Zhang P.P. Lei Y. Hong X.H. He Q.M. Ma J. Long non-coding RNA DANCR stabilizes HIF-1alpha and promotes metastasis by interacting with NF90/NF45 complex in nasopharyngeal carcinoma Theranostics 2018 8 5676 5689 10.7150/thno.28538 30555573 41. Barth D.A. Prinz F. Teppan J. Jonas K. Klec C. Pichler M. Long-Noncoding RNA (lncRNA) in the Regulation of Hypoxia-Inducible Factor (HIF) in Cancer Noncoding RNA 2020 6 27 10.3390/ncrna6030027 42. Hoefflin R. Harlander S. Schafer S. Metzger P. Kuo F. Schonenberger D. Adlesic M. Peighambari A. Seidel P. Chen C.Y. HIF-1alpha and HIF-2alpha differently regulate tumour development and inflammation of clear cell renal cell carcinoma in mice Nat. Commun. 2020 11 4111 10.1038/s41467-020-17873-3 32807776 43. Messai Y. Gad S. Noman M.Z. Le Teuff G. Couve S. Janji B. Kammerer S.F. Rioux-Leclerc N. Hasmim M. Ferlicot S. Renal Cell Carcinoma Programmed Death-ligand 1, a New Direct Target of Hypoxia-inducible Factor-2 Alpha, is Regulated by von Hippel-Lindau Gene Mutation Status Eur. Urol. 2016 70 623 632 10.1016/j.eururo.2015.11.029 26707870 44. Kong S.K. Kim B.S. Lim H. Kim H.J. Kim Y.S. Dissection of PD-L1 promoter reveals differential transcriptional regulation of PD-L1 in VHL mutant clear cell renal cell carcinoma Lab. Investig. 2022 102 352 362 10.1038/s41374-021-00703-5 34789838 45. Bader H.L. Hsu T. Systemic VHL gene functions and the VHL disease FEBS Lett. 2012 586 1562 1569 10.1016/j.febslet.2012.04.032 22673568 46. de Rojas P.I. Albinana V. Taranets L. Recio-Poveda L. Cuesta A.M. Popov N. Kronenberger T. Botella L.M. The Endothelial Landscape and Its Role in Von Hippel-Lindau Disease Cells 2021 10 2313 10.3390/cells10092313 34571962 47. De la Garza M.M. Cumpian A.M. Daliri S. Castro-Pando S. Umer M. Gong L. Khosravi N. Caetano M.S. Ramos-Castaneda M. Flores A.G. COPD-Type lung inflammation promotes K-ras mutant lung cancer through epithelial HIF-1alpha mediated tumor angiogenesis and proliferation Oncotarget 2018 9 32972 32983 10.18632/oncotarget.26030 30250643 48. Zhang H. Sun L. When human cells meet bacteria: Precision medicine for cancers using the microbiota Am. J. Cancer Res. 2018 8 1157 1175 30094091 49. Allen J. Sears C.L. Impact of the gut microbiome on the genome and epigenome of colon epithelial cells: Contributions to colorectal cancer development Genome Med. 2019 11 11 10.1186/s13073-019-0621-2 30803449 50. Fessler J. Matson V. Gajewski T.F. Exploring the emerging role of the microbiome in cancer immunotherapy J. Immunother. Cancer 2019 7 108 10.1186/s40425-019-0574-4 30995949 51. Han N. Pan Z. Liu G. Yang R. Yujing B. Hypoxia: The “Invisible Pusher” of Gut Microbiota Front. Microbiol. 2021 12 690600 10.3389/fmicb.2021.690600 34367091 52. Liu P.J. Harris J.M. Marchi E. D’Arienzo V. Michler T. Wing P.A.C. Magri A. Ortega-Prieto A.M. van de Klundert M. Wettengel J. Hypoxic gene expression in chronic hepatitis B virus infected patients is not observed in state-of-the-art in vitro and mouse infection models Sci. Rep. 2020 10 14101 10.1038/s41598-020-70865-7 32839523 53. Leppanen J. Helminen O. Huhta H. Kauppila J.H. Isohookana J. Haapasaari K.M. Karihtala P. Parkkila S. Saarnio J. Lehenkari P.P. Toll-like receptors 2, 4 and 9 and hypoxia markers HIF-1alpha and CAIX in pancreatic intraepithelial neoplasia APMIS 2018 126 852 863 10.1111/apm.12894 30357962 54. Han S. Xu W. Wang Z. Qi X. Wang Y. Ni Y. Shen H. Hu Q. Han W. Crosstalk between the HIF-1 and Toll-like receptor/nuclear factor-kappaB pathways in the oral squamous cell carcinoma microenvironment Oncotarget 2016 7 37773 37789 10.18632/oncotarget.9329 27191981 55. Tewari R. Choudhury S.R. Ghosh S. Mehta V.S. Sen E. Involvement of TNFalpha-induced TLR4-NF-kappaB and TLR4-HIF-1alpha feed-forward loops in the regulation of inflammatory responses in glioma J. Mol. Med. 2012 90 67 80 10.1007/s00109-011-0807-6 21887505 56. Paone A. Galli R. Gabellini C. Lukashev D. Starace D. Gorlach A. De Cesaris P. Ziparo E. Del Bufalo D. Sitkovsky M.V. Toll-like receptor 3 regulates angiogenesis and apoptosis in prostate cancer cell lines through hypoxia-inducible factor 1 alpha Neoplasia 2010 12 539 549 10.1593/neo.92106 20651983 57. Liu Y. Yan W. Tohme S. Chen M. Fu Y. Tian D. Lotze M. Tang D. Tsung A. Hypoxia induced HMGB1 and mitochondrial DNA interactions mediate tumor growth in hepatocellular carcinoma through Toll-like receptor 9 J. Hepatol. 2015 63 114 121 10.1016/j.jhep.2015.02.009 25681553 58. Wojcik-Krowiranda K.M. Forma E. Bienkiewicz A. Cwonda L. Wronska-Stefaniak J. Brys M. TLR family gene expression in relation to the HIF1alpha and the VEGFR pathway activation in endometrial cancer Ginekol. Pol. 2020 91 439 446 10.5603/GP.2020.0073 32902840 59. Hu L. Zang M.D. Wang H.X. Li J.F. Su L.P. Yan M. Li C. Yang Q.M. Liu B.Y. Zhu Z.G. Biglycan stimulates VEGF expression in endothelial cells by activating the TLR signaling pathway Mol. Oncol. 2016 10 1473 1484 10.1016/j.molonc.2016.08.002 27590684 60. Xu S. Yu C. Ma X. Li Y. Shen Y. Chen Y. Huang S. Zhang T. Deng W. Wang Y. IL-6 promotes nuclear translocation of HIF-1alpha to aggravate chemoresistance of ovarian cancer cells Eur. J. Pharmacol. 2021 894 173817 10.1016/j.ejphar.2020.173817 33345849 61. Yeh Y.H. Hsiao H.F. Yeh Y.C. Chen T.W. Li T.K. Inflammatory interferon activates HIF-1alpha-mediated epithelial-to-mesenchymal transition via PI3K/AKT/mTOR pathway J. Exp. Clin. Cancer Res. 2018 37 70 10.1186/s13046-018-0730-6 29587825 62. Cuomo F. Coppola A. Botti C. Maione C. Forte A. Scisciola L. Liguori G. Caiafa I. Ursini M.V. Galderisi U. Pro-inflammatory cytokines activate hypoxia-inducible factor 3alpha via epigenetic changes in mesenchymal stromal/stem cells Sci. Rep. 2018 8 5842 10.1038/s41598-018-24221-5 29643458 63. Piasecka D. Braun M. Mieszkowska M. Kowalczyk L. Kopczynski J. Kordek R. Sadej R. Romanska H.M. Upregulation of HIF1-alpha via an NF-kappaB/COX2 pathway confers proliferative dominance of HER2-negative ductal carcinoma in situ cells in response to inflammatory stimuli Neoplasia 2020 22 576 589 10.1016/j.neo.2020.09.003 32980776 64. Ding Y. Zhuang S. Li Y. Yu X. Lu M. Ding N. Hypoxia-induced HIF1alpha dependent COX2 promotes ovarian cancer progress J. Bioenerg. Biomembr. 2021 53 441 448 10.1007/s10863-021-09900-9 33973103 65. Lappano R. Talia M. Cirillo F. Rigiracciolo D.C. Scordamaglia D. Guzzi R. Miglietta A.M. De Francesco E.M. Belfiore A. Sims A.H. The IL1beta-IL1R signaling is involved in the stimulatory effects triggered by hypoxia in breast cancer cells and cancer-associated fibroblasts (CAFs) J. Exp. Clin. Cancer Res. 2020 39 153 10.1186/s13046-020-01667-y 32778144 66. Zhang J. Zhang Q. Lou Y. Fu Q. Chen Q. Wei T. Yang J. Tang J. Wang J. Chen Y. Hypoxia-inducible factor-1alpha/interleukin-1beta signaling enhances hepatoma epithelial-mesenchymal transition through macrophages in a hypoxic-inflammatory microenvironment Hepatology 2018 67 1872 1889 10.1002/hep.29681 29171040 67. Yang L. Cui R. Li Y. Liang K. Ni M. Gu Y. Hypoxia-Induced TGFBI as a Serum Biomarker for Laboratory Diagnosis and Prognosis in Patients with Pancreatic Ductal Adenocarcinoma Lab. Med. 2020 51 352 361 10.1093/labmed/lmz063 31626700 68. Costanza B. Rademaker G. Tiamiou A. De Tullio P. Leenders J. Blomme A. Bellier J. Bianchi E. Turtoi A. Delvenne P. Transforming growth factor beta-induced, an extracellular matrix interacting protein, enhances glycolysis and promotes pancreatic cancer cell migration Int. J. Cancer 2019 145 1570 1584 10.1002/ijc.32247 30834519 69. Tang Y.A. Chen Y.F. Bao Y. Mahara S. Yatim S. Oguz G. Lee P.L. Feng M. Cai Y. Tan E.Y. Hypoxic tumor microenvironment activates GLI2 via HIF-1alpha and TGF-beta2 to promote chemoresistance in colorectal cancer Proc. Natl. Acad. Sci. USA 2018 115 E5990 E5999 10.1073/pnas.1801348115 29891662 70. Huang K. Zhang X. Hao Y. Feng R. Wang H. Shu Z. Li A. Du M. Hypoxia Tumor Microenvironment Activates GLI2 through HIF-1alpha and TGF-beta2 to Promote Chemotherapy Resistance of Colorectal Cancer Comput. Math. Methods Med. 2022 2022 2032895 10.1155/2022/2032895 35186110 71. Liu C. Zhang W. Wang J. Si T. Xing W. Tumor-associated macrophage-derived transforming growth factor-beta promotes colorectal cancer progression through HIF1-TRIB3 signaling Cancer Sci. 2021 112 4198 4207 10.1111/cas.15101 34375482 72. Mallikarjuna P. Raviprakash T.S. Aripaka K. Ljungberg B. Landstrom M. Interactions between TGF-beta type I receptor and hypoxia-inducible factor-alpha mediates a synergistic crosstalk leading to poor prognosis for patients with clear cell renal cell carcinoma Cell Cycle 2019 18 2141 2156 10.1080/15384101.2019.1642069 31339433 73. Ando A. Hashimoto N. Sakamoto K. Omote N. Miyazaki S. Nakahara Y. Imaizumi K. Kawabe T. Hasegawa Y. Repressive role of stabilized hypoxia inducible factor 1alpha expression on transforming growth factor beta-induced extracellular matrix production in lung cancer cells Cancer Sci. 2019 110 1959 1973 10.1111/cas.14027 31004547 74. Huang Y. Chen Z. Lu T. Bi G. Li M. Liang J. Hu Z. Zheng Y. Yin J. Xi J. HIF-1alpha switches the functionality of TGF-beta signaling via changing the partners of smads to drive glucose metabolic reprogramming in non-small cell lung cancer J. Exp. Clin. Cancer Res. 2021 40 398 10.1186/s13046-021-02188-y 34930376 75. Ziani L. Buart S. Chouaib S. Thiery J. Hypoxia increases melanoma-associated fibroblasts immunosuppressive potential and inhibitory effect on T cell-mediated cytotoxicity Oncoimmunology 2021 10 1950953 10.1080/2162402X.2021.1950953 34367731 76. Yoshimoto S. Tanaka F. Morita H. Hiraki A. Hashimoto S. Hypoxia-induced HIF-1alpha and ZEB1 are critical for the malignant transformation of ameloblastoma via TGF-beta-dependent EMT Cancer Med. 2019 8 7822 7832 10.1002/cam4.2667 31674718 77. Fico F. Santamaria-Martinez A. TGFBI modulates tumour hypoxia and promotes breast cancer metastasis Mol. Oncol. 2020 14 3198 3210 10.1002/1878-0261.12828 33080107 78. Wang H.Y. Zhang X.P. Wang W. Regulation of epithelial-to-mesenchymal transition in hypoxia by the HIF-1alpha network FEBS Lett. 2022 596 338 349 10.1002/1873-3468.14258 34905218 79. Liu M. Kuo F. Capistrano K.J. Kang D. Nixon B.G. Shi W. Chou C. Do M.H. Stamatiades E.G. Gao S. TGF-beta suppresses type 2 immunity to cancer Nature 2020 587 115 120 10.1038/s41586-020-2836-1 33087928 80. Zhou H. Wu G. Ma X. Xiao J. Yu G. Yang C. Xu N. Zhang B. Zhou J. Ye Z. Attenuation of TGFBR2 expression and tumour progression in prostate cancer involve diverse hypoxia-regulated pathways J. Exp. Clin. Cancer Res. 2018 37 89 10.1186/s13046-018-0764-9 29699590 81. Eltzschig H.K. Kohler D. Eckle T. Kong T. Robson S.C. Colgan S.P. Central role of Sp1-regulated CD39 in hypoxia/ischemia protection Blood 2009 113 224 232 10.1182/blood-2008-06-165746 18812468 82. Synnestvedt K. Furuta G.T. Comerford K.M. Louis N. Karhausen J. Eltzschig H.K. Hansen K.R. Thompson L.F. Colgan S.P. Ecto-5’-nucleotidase (CD73) regulation by hypoxia-inducible factor-1 mediates permeability changes in intestinal epithelia J. Clin. Investig. 2002 110 993 1002 10.1172/JCI0215337 12370277 83. Kong T. Westerman K.A. Faigle M. Eltzschig H.K. Colgan S.P. HIF-dependent induction of adenosine A2B receptor in hypoxia FASEB J. 2006 20 2242 2250 10.1096/fj.06-6419com 17077301 84. Allard B. Allard D. Buisseret L. Stagg J. The adenosine pathway in immuno-oncology Nat. Rev. Clin. Oncol. 2020 17 611 629 10.1038/s41571-020-0382-2 32514148 85. Vijayan D. Young A. Teng M.W.L. Smyth M.J. Targeting immunosuppressive adenosine in cancer Nat. Rev. Cancer 2017 17 709 724 10.1038/nrc.2017.86 29059149 86. Wang X. Luo G. Zhang K. Cao J. Huang C. Jiang T. Liu B. Su L. Qiu Z. Hypoxic Tumor-Derived Exosomal miR-301a Mediates M2 Macrophage Polarization via PTEN/PI3Kgamma to Promote Pancreatic Cancer Metastasis Cancer Res. 2018 78 4586 4598 10.1158/0008-5472.CAN-17-3841 29880482 87. Park J.E. Dutta B. Tse S.W. Gupta N. Tan C.F. Low J.K. Yeoh K.W. Kon O.L. Tam J.P. Sze S.K. Hypoxia-induced tumor exosomes promote M2-like macrophage polarization of infiltrating myeloid cells and microRNA-mediated metabolic shift Oncogene 2019 38 5158 5173 10.1038/s41388-019-0782-x 30872795 88. Balamurugan K. Mendoza-Villanueva D. Sharan S. Summers G.H. Dobrolecki L.E. Lewis M.T. Sterneck E. C/EBPdelta links IL-6 and HIF-1 signaling to promote breast cancer stem cell-associated phenotypes Oncogene 2019 38 3765 3780 10.1038/s41388-018-0516-5 30262865 89. Bui P. Imaizumi S. Beedanagari S.R. Reddy S.T. Hankinson O. Human CYP2S1 metabolizes cyclooxygenase- and lipoxygenase-derived eicosanoids Drug Metab. Dispos. 2011 39 180 190 10.1124/dmd.110.035121 21068195 90. Yang C. Li C. Li M. Tong X. Hu X. Yang X. Yan X. He L. Wan C. CYP2S1 depletion enhances colorectal cell proliferation is associated with PGE2-mediated activation of beta-catenin signaling Exp. Cell Res. 2015 331 377 386 10.1016/j.yexcr.2014.12.008 25557876 91. Royds J.A. Dower S.K. Qwarnstrom E.E. Lewis C.E. Response of tumour cells to hypoxia: Role of p53 and NFkB Mol. Pathol. 1998 51 55 61 10.1136/mp.51.2.55 9713587 92. Rius J. Guma M. Schachtrup C. Akassoglou K. Zinkernagel A.S. Nizet V. Johnson R.S. Haddad G.G. Karin M. NF-kappaB links innate immunity to the hypoxic response through transcriptional regulation of HIF-1alpha Nature 2008 453 807 811 10.1038/nature06905 18432192 93. Karin M. Greten F.R. NF-kappaB: Linking inflammation and immunity to cancer development and progression Nat. Rev. Immunol. 2005 5 749 759 10.1038/nri1703 16175180 94. Perkins N.D. The diverse and complex roles of NF-kappaB subunits in cancer Nat. Rev. Cancer 2012 12 121 132 10.1038/nrc3204 22257950 95. Zabel U. Schreck R. Baeuerle P.A. DNA binding of purified transcription factor NF-kappa B. Affinity, specificity, Zn2+ dependence, and differential half-site recognition J. Biol. Chem. 1991 266 252 260 1985897 96. Chen F.E. Huang D.B. Chen Y.Q. Ghosh G. Crystal structure of p50/p65 heterodimer of transcription factor NF-kappaB bound to DNA Nature 1998 391 410 413 10.1038/34956 9450761 97. Muller C.W. Harrison S.C. The structure of the NF-kappa B p50:DNA-complex: A starting point for analyzing the Rel family FEBS Lett. 1995 369 113 117 10.1016/0014-5793(95)00541-G 7641872 98. Perkins N.D. Integrating cell-signalling pathways with NF-kappaB and IKK function Nat. Rev. Mol. Cell Biol. 2007 8 49 62 10.1038/nrm2083 17183360 99. Sun S.C. Non-canonical NF-kappaB signaling pathway Cell Res. 2011 21 71 85 10.1038/cr.2010.177 21173796 100. van Uden P. Kenneth N.S. Rocha S. Regulation of hypoxia-inducible factor-1alpha by NF-kappaB Biochem. J. 2008 412 477 484 10.1042/BJ20080476 18393939 101. Koong A.C. Chen E.Y. Giaccia A.J. Hypoxia causes the activation of nuclear factor kappa B through the phosphorylation of I kappa B alpha on tyrosine residues Cancer Res. 1994 54 1425 1430 8137243 102. Mak P. Li J. Samanta S. Mercurio A.M. ERbeta regulation of NF-kB activation in prostate cancer is mediated by HIF-1 Oncotarget 2015 6 40247 40254 10.18632/oncotarget.5377 26450901 103. Fan P. Zhang J.J. Wang B. Wu H.Q. Zhou S.X. Wang C.Y. Zhang J.H. Tian Y. Wu H.S. Hypoxia-inducible factor-1 up-regulates the expression of Toll-like receptor 4 in pancreatic cancer cells under hypoxic conditions Pancreatology 2012 12 170 178 10.1016/j.pan.2012.02.015 22487528 104. D’Ignazio L. Bandarra D. Rocha S. NF-kappaB and HIF crosstalk in immune responses FEBS J. 2016 283 413 424 10.1111/febs.13578 26513405 105. Sato S. Sanjo H. Takeda K. Ninomiya-Tsuji J. Yamamoto M. Kawai T. Matsumoto K. Takeuchi O. Akira S. Essential function for the kinase TAK1 in innate and adaptive immune responses Nat. Immunol. 2005 6 1087 1095 10.1038/ni1255 16186825 106. Culver C. Sundqvist A. Mudie S. Melvin A. Xirodimas D. Rocha S. Mechanism of hypoxia-induced NF-kappaB Mol. Cell Biol. 2010 30 4901 4921 10.1128/MCB.00409-10 20696840 107. Scholz C.C. Taylor C.T. Hydroxylase-dependent regulation of the NF-kappaB pathway Biol. Chem. 2013 394 479 493 10.1515/hsz-2012-0338 23362195 108. Cummins E.P. Berra E. Comerford K.M. Ginouves A. Fitzgerald K.T. Seeballuck F. Godson C. Nielsen J.E. Moynagh P. Pouyssegur J. Prolyl hydroxylase-1 negatively regulates IkappaB kinase-beta, giving insight into hypoxia-induced NFkappaB activity Proc. Natl. Acad. Sci. USA 2006 103 18154 18159 10.1073/pnas.0602235103 17114296 109. Mak P. Chang C. Pursell B. Mercurio A.M. Estrogen receptor beta sustains epithelial differentiation by regulating prolyl hydroxylase 2 transcription Proc. Natl. Acad. Sci. USA 2013 110 4708 4713 10.1073/pnas.1221654110 23487784 110. Li J. Yuan W. Jiang S. Ye W. Yang H. Shapiro I.M. Risbud M.V. Prolyl-4-hydroxylase domain protein 2 controls NF-kappaB/p65 transactivation and enhances the catabolic effects of inflammatory cytokines on cells of the nucleus pulposus J. Biol. Chem. 2015 290 7195 7207 10.1074/jbc.M114.611483 25635047 111. Ullah K. Rosendahl A.H. Izzi V. Bergmann U. Pihlajaniemi T. Maki J.M. Myllyharju J. Hypoxia-inducible factor prolyl-4-hydroxylase-1 is a convergent point in the reciprocal negative regulation of NF-kappaB and p53 signaling pathways Sci. Rep. 2017 7 17220 10.1038/s41598-017-17376-0 29222481 112. Xue J. Li X. Jiao S. Wei Y. Wu G. Fang J. Prolyl hydroxylase-3 is down-regulated in colorectal cancer cells and inhibits IKKbeta independent of hydroxylase activity Gastroenterology 2010 138 606 615 10.1053/j.gastro.2009.09.049 19786027 113. Fu J. Taubman M.B. EGLN3 inhibition of NF-kappaB is mediated by prolyl hydroxylase-independent inhibition of IkappaB kinase gamma ubiquitination Mol. Cell Biol. 2013 33 3050 3061 10.1128/MCB.00273-13 23732909 114. Tang E.D. Wang C.Y. Xiong Y. Guan K.L. A role for NF-kappaB essential modifier/IkappaB kinase-gamma (NEMO/IKKgamma) ubiquitination in the activation of the IkappaB kinase complex by tumor necrosis factor-alpha J. Biol. Chem. 2003 278 37297 37305 10.1074/jbc.M303389200 12867425 115. Tokunaga F. Sakata S. Saeki Y. Satomi Y. Kirisako T. Kamei K. Nakagawa T. Kato M. Murata S. Yamaoka S. Involvement of linear polyubiquitylation of NEMO in NF-kappaB activation Nat. Cell Biol. 2009 11 123 132 10.1038/ncb1821 19136968 116. Rahighi S. Ikeda F. Kawasaki M. Akutsu M. Suzuki N. Kato R. Kensche T. Uejima T. Bloor S. Komander D. Specific recognition of linear ubiquitin chains by NEMO is important for NF-kappaB activation Cell 2009 136 1098 1109 10.1016/j.cell.2009.03.007 19303852 117. Cockman M.E. Lancaster D.E. Stolze I.P. Hewitson K.S. McDonough M.A. Coleman M.L. Coles C.H. Yu X. Hay R.T. Ley S.C. Posttranslational hydroxylation of ankyrin repeats in IkappaB proteins by the hypoxia-inducible factor (HIF) asparaginyl hydroxylase, factor inhibiting HIF (FIH) Proc. Natl. Acad. Sci. USA 2006 103 14767 14772 10.1073/pnas.0606877103 17003112 118. Shin D.H. Li S.H. Yang S.W. Lee B.L. Lee M.K. Park J.W. Inhibitor of nuclear factor-kappaB alpha derepresses hypoxia-inducible factor-1 during moderate hypoxia by sequestering factor inhibiting hypoxia-inducible factor from hypoxia-inducible factor 1alpha FEBS J. 2009 276 3470 3480 10.1111/j.1742-4658.2009.07069.x 19456861 119. Levy D.E. Darnell J.E. Jr. Stats: Transcriptional control and biological impact Nat. Rev. Mol. Cell Biol. 2002 3 651 662 10.1038/nrm909 12209125 120. Darnell J.E. Jr. Kerr I.M. Stark G.R. Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins Science 1994 264 1415 1421 10.1126/science.8197455 8197455 121. Shuai K. Liu B. Regulation of JAK-STAT signalling in the immune system Nat. Rev. Immunol. 2003 3 900 911 10.1038/nri1226 14668806 122. Bowman T. Garcia R. Turkson J. Jove R. STATs in oncogenesis Oncogene 2000 19 2474 2488 10.1038/sj.onc.1203527 10851046 123. Azevedo A. Silva S. Rueff J. Non-Receptor Tyrosine Kinases Role and Significance in Hematological Malignancies, Tyrosine Kinases as Druggable Targets in Cancer IntechOpen London, UK 2019 10.5772/intechopen.84873 124. Thomas S.J. Snowden J.A. Zeidler M.P. Danson S.J. The role of JAK/STAT signalling in the pathogenesis, prognosis and treatment of solid tumours Br. J. Cancer 2015 113 365 371 10.1038/bjc.2015.233 26151455 125. de Groot R.P. Raaijmakers J.A. Lammers J.W. Koenderman L. STAT5-Dependent CyclinD1 and Bcl-xL expression in Bcr-Abl-transformed cells Mol. Cell Biol. Res. Commun. 2000 3 299 305 10.1006/mcbr.2000.0231 10964754 126. Catlett-Falcone R. Landowski T.H. Oshiro M.M. Turkson J. Levitzki A. Savino R. Ciliberto G. Moscinski L. Fernandez-Luna J.L. Nunez G. Constitutive activation of Stat3 signaling confers resistance to apoptosis in human U266 myeloma cells Immunity 1999 10 105 115 10.1016/S1074-7613(00)80011-4 10023775 127. Al Zaid Siddiquee K. Turkson J. STAT3 as a target for inducing apoptosis in solid and hematological tumors Cell Res. 2008 18 254 267 10.1038/cr.2008.18 18227858 128. Yu H. Kortylewski M. Pardoll D. Crosstalk between cancer and immune cells: Role of STAT3 in the tumour microenvironment Nat. Rev. Immunol. 2007 7 41 51 10.1038/nri1995 17186030 129. Wang T. Niu G. Kortylewski M. Burdelya L. Shain K. Zhang S. Bhattacharya R. Gabrilovich D. Heller R. Coppola D. Regulation of the innate and adaptive immune responses by Stat-3 signaling in tumor cells Nat. Med. 2004 10 48 54 10.1038/nm976 14702634 130. Yu H. Pardoll D. Jove R. STATs in cancer inflammation and immunity: A leading role for STAT3 Nat. Rev. Cancer 2009 9 798 809 10.1038/nrc2734 19851315 131. Demaria M. Giorgi C. Lebiedzinska M. Esposito G. D’Angeli L. Bartoli A. Gough D.J. Turkson J. Levy D.E. Watson C.J. A STAT3-mediated metabolic switch is involved in tumour transformation and STAT3 addiction Aging 2010 2 823 842 10.18632/aging.100232 21084727 132. Wei D. Le X. Zheng L. Wang L. Frey J.A. Gao A.C. Peng Z. Huang S. Xiong H.Q. Abbruzzese J.L. Stat3 activation regulates the expression of vascular endothelial growth factor and human pancreatic cancer angiogenesis and metastasis Oncogene 2003 22 319 329 10.1038/sj.onc.1206122 12545153 133. Xu Q. Briggs J. Park S. Niu G. Kortylewski M. Zhang S. Gritsko T. Turkson J. Kay H. Semenza G.L. Targeting Stat3 blocks both HIF-1 and VEGF expression induced by multiple oncogenic growth signaling pathways Oncogene 2005 24 5552 5560 10.1038/sj.onc.1208719 16007214 134. Jung J.E. Lee H.G. Cho I.H. Chung D.H. Yoon S.H. Yang Y.M. Lee J.W. Choi S. Park J.W. Ye S.K. STAT3 is a potential modulator of HIF-1-mediated VEGF expression in human renal carcinoma cells FASEB J. 2005 19 1296 1298 10.1096/fj.04-3099fje 15919761 135. Jung J.E. Kim H.S. Lee C.S. Shin Y.J. Kim Y.N. Kang G.H. Kim T.Y. Juhnn Y.S. Kim S.J. Park J.W. STAT3 inhibits the degradation of HIF-1alpha by pVHL-mediated ubiquitination Exp. Mol. Med. 2008 40 479 485 10.3858/emm.2008.40.5.479 18985005 136. Pawlus M.R. Wang L. Hu C.J. STAT3 and HIF1alpha cooperatively activate HIF1 target genes in MDA-MB-231 and RCC4 cells Oncogene 2014 33 1670 1679 10.1038/onc.2013.115 23604114 137. Gray M.J. Zhang J. Ellis L.M. Semenza G.L. Evans D.B. Watowich S.S. Gallick G.E. HIF-1alpha, STAT3, CBP/p300 and Ref-1/APE are components of a transcriptional complex that regulates Src-dependent hypoxia-induced expression of VEGF in pancreatic and prostate carcinomas Oncogene 2005 24 3110 3120 10.1038/sj.onc.1208513 15735682 138. Joung Y.H. Park J.H. Park T. Lee C.S. Kim O.H. Ye S.K. Yang U.M. Lee K.J. Yang Y.M. Hypoxia activates signal transducers and activators of transcription 5 (STAT5) and increases its binding activity to the GAS element in mammary epithelial cells Exp. Mol. Med. 2003 35 350 357 10.1038/emm.2003.46 14646587 139. Lee M.Y. Joung Y.H. Lim E.J. Park J.H. Ye S.K. Park T. Zhang Z. Park D.K. Lee K.J. Yang Y.M. Phosphorylation and activation of STAT proteins by hypoxia in breast cancer cells Breast 2006 15 187 195 10.1016/j.breast.2005.05.005 16084091 140. Joung Y.H. Lim E.J. Lee M.Y. Park J.H. Ye S.K. Park E.U. Kim S.Y. Zhang Z. Lee K.J. Park D.K. Hypoxia activates the cyclin D1 promoter via the Jak2/STAT5b pathway in breast cancer cells Exp. Mol. Med. 2005 37 353 364 10.1038/emm.2005.45 16155412 141. Atkinson G.P. Nozell S.E. Benveniste E.T. NF-kappaB and STAT3 signaling in glioma: Targets for future therapies Expert Rev. Neurother. 2010 10 575 586 10.1586/ern.10.21 20367209 142. Fan Y. Mao R. Yang J. NF-kappaB and STAT3 signaling pathways collaboratively link inflammation to cancer Protein Cell 2013 4 176 185 10.1007/s13238-013-2084-3 23483479 143. Bollrath J. Greten F.R. IKK/NF-kappaB and STAT3 pathways: Central signalling hubs in inflammation-mediated tumour promotion and metastasis EMBO Rep. 2009 10 1314 1319 10.1038/embor.2009.243 19893576 144. He G. Karin M. NF-kappaB and STAT3—Key players in liver inflammation and cancer Cell Res. 2011 21 159 168 10.1038/cr.2010.183 21187858 145. Lee H. Herrmann A. Deng J.H. Kujawski M. Niu G. Li Z. Forman S. Jove R. Pardoll D.M. Yu H. Persistently activated Stat3 maintains constitutive NF-kappaB activity in tumors Cancer Cell 2009 15 283 293 10.1016/j.ccr.2009.02.015 19345327 146. Ivanova I.G. Perkins N.D. Hypoxia induces rapid, STAT3 and ROS dependent, mitochondrial translocation of RelA(p65) and IkappaBalpha Biosci. Rep. 2019 39 BSR20192101 10.1042/BSR20192101 31484794 147. Johnson R.F. Witzel I.I. Perkins N.D. p53-dependent regulation of mitochondrial energy production by the RelA subunit of NF-kappaB Cancer Res. 2011 71 5588 5597 10.1158/0008-5472.CAN-10-4252 21742773 148. Hou J. Zhao R. Xia W. Chang C.W. You Y. Hsu J.M. Nie L. Chen Y. Wang Y.C. Liu C. PD-L1-mediated gasdermin C expression switches apoptosis to pyroptosis in cancer cells and facilitates tumour necrosis Nat. Cell Biol. 2020 22 1264 1275 10.1038/s41556-020-0575-z 32929201 149. Shi J. Zhao Y. Wang K. Shi X. Wang Y. Huang H. Zhuang Y. Cai T. Wang F. Shao F. Cleavage of GSDMD by inflammatory caspases determines pyroptotic cell death Nature 2015 526 660 665 10.1038/nature15514 26375003 150. Chakraborty C. Sharma A.R. Sharma G. Lee S.S. The Interplay among miRNAs, Major Cytokines, and Cancer-Related Inflammation Mol. Ther. Nucleic Acids 2020 20 606 620 10.1016/j.omtn.2020.04.002 32348938 151. He M. Wang Q.Y. Yin Q.Q. Tang J. Lu Y. Zhou C.X. Duan C.W. Hong D.L. Tanaka T. Chen G.Q. HIF-1alpha downregulates miR-17/20a directly targeting p21 and STAT3: A role in myeloid leukemic cell differentiation Cell Death Differ. 2013 20 408 418 10.1038/cdd.2012.130 23059786 152. Zou F. Mao R. Yang L. Lin S. Lei K. Zheng Y. Ding Y. Zhang P. Cai G. Liang X. Targeted deletion of miR-139-5p activates MAPK, NF-kappaB and STAT3 signaling and promotes intestinal inflammation and colorectal cancer FEBS J. 2016 283 1438 1452 10.1111/febs.13678 26859226 153. Huang Y. Du K.M. Xue Z.H. Yan H. Li D. Liu W. Chen Z. Zhao Q. Tong J.H. Zhu Y.S. Cobalt chloride and low oxygen tension trigger differentiation of acute myeloid leukemic cells: Possible mediation of hypoxia-inducible factor-1alpha Leukemia 2003 17 2065 2073 10.1038/sj.leu.2403141 14523474 154. Murdoch C. Lewis C.E. Macrophage migration and gene expression in response to tumor hypoxia Int. J. Cancer 2005 117 701 708 10.1002/ijc.21422 16106399 155. Li N. Li Y. Li Z. Huang C. Yang Y. Lang M. Cao J. Jiang W. Xu Y. Dong J. Hypoxia Inducible Factor 1 (HIF-1) Recruits Macrophage to Activate Pancreatic Stellate Cells in Pancreatic Ductal Adenocarcinoma Int. J. Mol. Sci. 2016 17 799 10.3390/ijms17060799 156. Murdoch C. Giannoudis A. Lewis C.E. Mechanisms regulating the recruitment of macrophages into hypoxic areas of tumors and other ischemic tissues Blood 2004 104 2224 2234 10.1182/blood-2004-03-1109 15231578 157. Schioppa T. Uranchimeg B. Saccani A. Biswas S.K. Doni A. Rapisarda A. Bernasconi S. Saccani S. Nebuloni M. Vago L. Regulation of the chemokine receptor CXCR4 by hypoxia J. Exp. Med. 2003 198 1391 1402 10.1084/jem.20030267 14597738 158. Mukaida N. Sasakki S. Popivanova B.K. Tumor Necrosis Factor (TNF) and Chemokines in Colitis-Associated Cancer Cancers 2011 3 2811 2826 10.3390/cancers3032811 24212934 159. Laoui D. Van Overmeire E. Di Conza G. Aldeni C. Keirsse J. Morias Y. Movahedi K. Houbracken I. Schouppe E. Elkrim Y. Tumor hypoxia does not drive differentiation of tumor-associated macrophages but rather fine-tunes the M2-like macrophage population Cancer Res. 2014 74 24 30 10.1158/0008-5472.CAN-13-1196 24220244 160. Barnett F.H. Rosenfeld M. Wood M. Kiosses W.B. Usui Y. Marchetti V. Aguilar E. Friedlander M. Macrophages form functional vascular mimicry channels in vivo Sci. Rep. 2016 6 36659 10.1038/srep36659 27834402 161. Wang Y. Liu T. Yang N. Xu S. Li X. Wang D. Hypoxia and macrophages promote glioblastoma invasion by the CCL4-CCR5 axis Oncol. Rep. 2016 36 3522 3528 10.3892/or.2016.5171 27748906 162. Jeong S.K. Kim J.S. Lee C.G. Park Y.S. Kim S.D. Yoon S.O. Han D.H. Lee K.Y. Jeong M.H. Jo W.S. Tumor associated macrophages provide the survival resistance of tumor cells to hypoxic microenvironmental condition through IL-6 receptor-mediated signals Immunobiology 2017 222 55 65 10.1016/j.imbio.2015.11.010 26705936 163. Paolini L. Adam C. Beauvillain C. Preisser L. Blanchard S. Pignon P. Seegers V. Chevalier L.M. Campone M. Wernert R. Lactic Acidosis Together with GM-CSF and M-CSF Induces Human Macrophages toward an Inflammatory Protumor Phenotype Cancer Immunol. Res. 2020 8 383 395 10.1158/2326-6066.CIR-18-0749 31924656 164. Ambade A. Satishchandran A. Saha B. Gyongyosi B. Lowe P. Kodys K. Catalano D. Szabo G. Hepatocellular carcinoma is accelerated by NASH involving M2 macrophage polarization mediated by hif-1alphainduced IL-10 Oncoimmunology 2016 5 e1221557 10.1080/2162402X.2016.1221557 27853646 165. Yu Q. Wang Y. Dong L. He Y. Liu R. Yang Q. Cao Y. Wang Y. Jia A. Bi Y. Regulations of Glycolytic Activities on Macrophages Functions in Tumor and Infectious Inflammation Front. Cell. Infect. Microbiol. 2020 10 287 10.3389/fcimb.2020.00287 32596169 166. Chen X. Ying X. Wang X. Wu X. Zhu Q. Wang X. Exosomes derived from hypoxic epithelial ovarian cancer deliver microRNA-940 to induce macrophage M2 polarization Oncol. Rep. 2017 38 522 528 10.3892/or.2017.5697 28586039 167. Werno C. Menrad H. Weigert A. Dehne N. Goerdt S. Schledzewski K. Kzhyshkowska J. Brune B. Knockout of HIF-1alpha in tumor-associated macrophages enhances M2 polarization and attenuates their pro-angiogenic responses Carcinogenesis 2010 31 1863 1872 10.1093/carcin/bgq088 20427344 168. Quante M. Tu S.P. Tomita H. Gonda T. Wang S.S. Takashi S. Baik G.H. Shibata W. Diprete B. Betz K.S. Bone marrow-derived myofibroblasts contribute to the mesenchymal stem cell niche and promote tumor growth Cancer Cell 2011 19 257 272 10.1016/j.ccr.2011.01.020 21316604 169. Pietras K. Pahler J. Bergers G. Hanahan D. Functions of paracrine PDGF signaling in the proangiogenic tumor stroma revealed by pharmacological targeting PLoS Med. 2008 5 e19 10.1371/journal.pmed.0050019 18232728 170. Toullec A. Gerald D. Despouy G. Bourachot B. Cardon M. Lefort S. Richardson M. Rigaill G. Parrini M.C. Lucchesi C. Oxidative stress promotes myofibroblast differentiation and tumour spreading EMBO Mol. Med. 2010 2 211 230 10.1002/emmm.201000073 20535745 171. Martinez-Outschoorn U.E. Trimmer C. Lin Z. Whitaker-Menezes D. Chiavarina B. Zhou J. Wang C. Pavlides S. Martinez-Cantarin M.P. Capozza F. Autophagy in cancer associated fibroblasts promotes tumor cell survival: Role of hypoxia, HIF1 induction and NFkappaB activation in the tumor stromal microenvironment Cell Cycle 2010 9 3515 3533 10.4161/cc.9.17.12928 20855962 172. Madsen C.D. Pedersen J.T. Venning F.A. Singh L.B. Moeendarbary E. Charras G. Cox T.R. Sahai E. Erler J.T. Hypoxia and loss of PHD2 inactivate stromal fibroblasts to decrease tumour stiffness and metastasis EMBO Rep. 2015 16 1394 1408 10.15252/embr.201540107 26323721 173. Kuchnio A. Moens S. Bruning U. Kuchnio K. Cruys B. Thienpont B. Broux M. Ungureanu A.A. Leite de Oliveira R. Bruyere F. The Cancer Cell Oxygen Sensor PHD2 Promotes Metastasis via Activation of Cancer-Associated Fibroblasts Cell Rep. 2015 12 992 1005 10.1016/j.celrep.2015.07.010 26235614 174. Huber V. Camisaschi C. Berzi A. Ferro S. Lugini L. Triulzi T. Tuccitto A. Tagliabue E. Castelli C. Rivoltini L. Cancer acidity: An ultimate frontier of tumor immune escape and a novel target of immunomodulation Semin. Cancer Biol. 2017 43 74 89 10.1016/j.semcancer.2017.03.001 28267587 175. Husain Z. Huang Y. Seth P. Sukhatme V.P. Tumor-derived lactate modifies antitumor immune response: Effect on myeloid-derived suppressor cells and NK cells J. Immunol. 2013 191 1486 1495 10.4049/jimmunol.1202702 23817426 176. Brand A. Singer K. Koehl G.E. Kolitzus M. Schoenhammer G. Thiel A. Matos C. Bruss C. Klobuch S. Peter K. LDHA-Associated Lactic Acid Production Blunts Tumor Immunosurveillance by T and NK Cells Cell Metab. 2016 24 657 671 10.1016/j.cmet.2016.08.011 27641098 177. Terren I. Orrantia A. Vitalle J. Zenarruzabeitia O. Borrego F. NK Cell Metabolism and Tumor Microenvironment Front. Immunol. 2019 10 2278 10.3389/fimmu.2019.02278 31616440 178. Xu L.J. Ma Q. Zhu J. Li J. Xue B.X. Gao J. Sun C.Y. Zang Y.C. Zhou Y.B. Yang D.R. Combined inhibition of JAK1,2/Stat3PDL1 signaling pathway suppresses the immune escape of castrationresistant prostate cancer to NK cells in hypoxia Mol. Med. Rep. 2018 17 8111 8120 10.3892/mmr.2018.8905 29693186 179. Lu Y. Hu J. Sun W. Duan X. Chen X. Hypoxia-mediated immune evasion of pancreatic carcinoma cells Mol. Med. Rep. 2015 11 3666 3672 10.3892/mmr.2015.3144 25573413 180. Ou Z.L. Luo Z. Wei W. Liang S. Gao T.L. Lu Y.B. Hypoxia-induced shedding of MICA and HIF1A-mediated immune escape of pancreatic cancer cells from NK cells: Role of circ_0000977/miR-153 axis RNA Biol. 2019 16 1592 1603 10.1080/15476286.2019.1649585 31402756 181. Yamada N. Yamanegi K. Ohyama H. Hata M. Nakasho K. Futani H. Okamura H. Terada N. Hypoxia downregulates the expression of cell surface MICA without increasing soluble MICA in osteosarcoma cells in a HIF-1alpha-dependent manner Int. J. Oncol. 2012 41 2005 2012 10.3892/ijo.2012.1630 22992985 182. Krzywinska E. Kantari-Mimoun C. Kerdiles Y. Sobecki M. Isagawa T. Gotthardt D. Castells M. Haubold J. Millien C. Viel T. Loss of HIF-1alpha in natural killer cells inhibits tumour growth by stimulating non-productive angiogenesis Nat. Commun. 2017 8 1597 10.1038/s41467-017-01599-w 29150606 183. Li Y. Patel S.P. Roszik J. Qin Y. Hypoxia-Driven Immunosuppressive Metabolites in the Tumor Microenvironment: New Approaches for Combinational Immunotherapy Front. Immunol. 2018 9 1591 10.3389/fimmu.2018.01591 30061885 184. Chiu D.K. Xu I.M. Lai R.K. Tse A.P. Wei L.L. Koh H.Y. Li L.L. Lee D. Lo R.C. Wong C.M. Hypoxia induces myeloid-derived suppressor cell recruitment to hepatocellular carcinoma through chemokine (C-C motif) ligand 26 Hepatology 2016 64 797 813 10.1002/hep.28655 27228567 185. Chiu D.K. Tse A.P. Xu I.M. Di Cui J. Lai R.K. Li L.L. Koh H.Y. Tsang F.H. Wei L.L. Wong C.M. Hypoxia inducible factor HIF-1 promotes myeloid-derived suppressor cells accumulation through ENTPD2/CD39L1 in hepatocellular carcinoma Nat. Commun. 2017 8 517 10.1038/s41467-017-00530-7 28894087 186. Noman M.Z. Desantis G. Janji B. Hasmim M. Karray S. Dessen P. Bronte V. Chouaib S. PD-L1 is a novel direct target of HIF-1alpha, and its blockade under hypoxia enhanced MDSC-mediated T cell activation J. Exp. Med. 2014 211 781 790 10.1084/jem.20131916 24778419 187. Palsson-McDermott E.M. Dyck L. Zaslona Z. Menon D. McGettrick A.F. Mills K.H.G. O’Neill L.A. Pyruvate Kinase M2 Is Required for the Expression of the Immune Checkpoint PD-L1 in Immune Cells and Tumors Front. Immunol. 2017 8 1300 10.3389/fimmu.2017.01300 29081778 188. Kumar V. Cheng P. Condamine T. Mony S. Languino L.R. McCaffrey J.C. Hockstein N. Guarino M. Masters G. Penman E. CD45 Phosphatase Inhibits STAT3 Transcription Factor Activity in Myeloid Cells and Promotes Tumor-Associated Macrophage Differentiation Immunity 2016 44 303 315 10.1016/j.immuni.2016.01.014 26885857 189. Corzo C.A. Condamine T. Lu L. Cotter M.J. Youn J.I. Cheng P. Cho H.I. Celis E. Quiceno D.G. Padhya T. HIF-1alpha regulates function and differentiation of myeloid-derived suppressor cells in the tumor microenvironment J. Exp. Med. 2010 207 2439 2453 10.1084/jem.20100587 20876310 190. Ostrand-Rosenberg S. Fenselau C. Myeloid-Derived Suppressor Cells: Immune-Suppressive Cells That Impair Antitumor Immunity and Are Sculpted by Their Environment J. Immunol. 2018 200 422 431 10.4049/jimmunol.1701019 29311384 191. Kusmartsev S. Eruslanov E. Kubler H. Tseng T. Sakai Y. Su Z. Kaliberov S. Heiser A. Rosser C. Dahm P. Oxidative stress regulates expression of VEGFR1 in myeloid cells: Link to tumor-induced immune suppression in renal cell carcinoma J. Immunol. 2008 181 346 353 10.4049/jimmunol.181.1.346 18566400 192. Yang L. DeBusk L.M. Fukuda K. Fingleton B. Green-Jarvis B. Shyr Y. Matrisian L.M. Carbone D.P. Lin P.C. Expansion of myeloid immune suppressor Gr+CD11b+ cells in tumor-bearing host directly promotes tumor angiogenesis Cancer Cell 2004 6 409 421 10.1016/j.ccr.2004.08.031 15488763 193. Palazon A. Tyrakis P.A. Macias D. Velica P. Rundqvist H. Fitzpatrick S. Vojnovic N. Phan A.T. Loman N. Hedenfalk I. An HIF-1alpha/VEGF-A Axis in Cytotoxic T Cells Regulates Tumor Progression Cancer Cell 2017 32 669 683.e5 10.1016/j.ccell.2017.10.003 29136509 194. Caldwell C.C. Kojima H. Lukashev D. Armstrong J. Farber M. Apasov S.G. Sitkovsky M.V. Differential effects of physiologically relevant hypoxic conditions on T lymphocyte development and effector functions J. Immunol. 2001 167 6140 6149 10.4049/jimmunol.167.11.6140 11714773 195. Nakagawa Y. Negishi Y. Shimizu M. Takahashi M. Ichikawa M. Takahashi H. Effects of extracellular pH and hypoxia on the function and development of antigen-specific cytotoxic T lymphocytes Immunol. Lett. 2015 167 72 86 10.1016/j.imlet.2015.07.003 26209187 196. Doedens A.L. Phan A.T. Stradner M.H. Fujimoto J.K. Nguyen J.V. Yang E. Johnson R.S. Goldrath A.W. Hypoxia-inducible factors enhance the effector responses of CD8(+) T cells to persistent antigen Nat. Immunol. 2013 14 1173 1182 10.1038/ni.2714 24076634 197. Velica P. Cunha P.P. Vojnovic N. Foskolou I.P. Bargiela D. Gojkovic M. Rundqvist H. Johnson R.S. Modified Hypoxia-Inducible Factor Expression in CD8(+) T Cells Increases Antitumor Efficacy Cancer Immunol. Res. 2021 9 401 414 10.1158/2326-6066.CIR-20-0561 33602720 198. Jorgovanovic D. Song M. Wang L. Zhang Y. Roles of IFN-gamma in tumor progression and regression: A review Biomark Res. 2020 8 49 10.1186/s40364-020-00228-x 33005420 199. Murthy A. Gerber S.A. Koch C.J. Lord E.M. Intratumoral Hypoxia Reduces IFN-gamma-Mediated Immunity and MHC Class I Induction in a Preclinical Tumor Model Immunohorizons 2019 3 149 160 10.4049/immunohorizons.1900017 31356176 200. Liu S. Liu X. Zhang C. Shan W. Qiu X. T-Cell Exhaustion Status Under High and Low Levels of Hypoxia-Inducible Factor 1alpha Expression in Glioma Front. Pharmacol. 2021 12 711772 10.3389/fphar.2021.711772 34305618 201. Bannoud N. Dalotto-Moreno T. Kindgard L. Garcia P.A. Blidner A.G. Marino K.V. Rabinovich G.A. Croci D.O. Hypoxia Supports Differentiation of Terminally Exhausted CD8 T Cells Front. Immunol. 2021 12 660944 10.3389/fimmu.2021.660944 34025660 202. Mami-Chouaib F. Tartour E. Editorial: Tissue Resident Memory T Cells Front. Immunol. 2019 10 1018 10.3389/fimmu.2019.01018 31191515 203. Sureshbabu S.K. Chaukar D. Chiplunkar S.V. Hypoxia regulates the differentiation and anti-tumor effector functions of gammadeltaT cells in oral cancer Clin. Exp. Immunol. 2020 201 40 57 10.1111/cei.13436 32255193 204. Clambey E.T. McNamee E.N. Westrich J.A. Glover L.E. Campbell E.L. Jedlicka P. de Zoeten E.F. Cambier J.C. Stenmark K.R. Colgan S.P. Hypoxia-inducible factor-1 alpha-dependent induction of FoxP3 drives regulatory T-cell abundance and function during inflammatory hypoxia of the mucosa Proc. Natl. Acad. Sci. USA 2012 109 E2784 E2793 10.1073/pnas.1202366109 22988108 205. Ohue Y. Nishikawa H. Regulatory T (Treg) cells in cancer: Can Treg cells be a new therapeutic target? Cancer Sci. 2019 110 2080 2089 10.1111/cas.14069 31102428 206. Lee K.E. Spata M. Bayne L.J. Buza E.L. Durham A.C. Allman D. Vonderheide R.H. Simon M.C. Hif1a Deletion Reveals Pro-Neoplastic Function of B Cells in Pancreatic Neoplasia Cancer Discov. 2016 6 256 269 10.1158/2159-8290.CD-15-0822 26715642 207. Zhang Y. Pan N. Sheng Y. Zhou M. Wen Z. Chen Y. Huang F. Wang L.X. Hypoxia enhances IL-10-producing B cell generation through upregulating high-mobility group B1 on tumor cell-released autophagosomes Immunol. Lett. 2019 216 36 42 10.1016/j.imlet.2019.09.005 31568811 208. Reiterer M. Colaco R. Emrouznejad P. Jensen A. Rundqvist H. Johnson R.S. Branco C. Acute and chronic hypoxia differentially predispose lungs for metastases Sci. Rep. 2019 9 10246 10.1038/s41598-019-46763-y 31308473 209. Kubes P. Ibbotson G. Russell J. Wallace J.L. Granger D.N. Role of platelet-activating factor in ischemia/reperfusion-induced leukocyte adherence Am. J. Physiol. 1990 259 G300 G305 10.1152/ajpgi.1990.259.2.G300 2166441 210. Liang X. Arullampalam P. Yang Z. Ming X.F. Hypoxia Enhances Endothelial Intercellular Adhesion Molecule 1 Protein Level Through Upregulation of Arginase Type II and Mitochondrial Oxidative Stress Front. Physiol. 2019 10 1003 10.3389/fphys.2019.01003 31474872 211. Hanahan D. Weinberg R.A. Hallmarks of cancer: The next generation Cell 2011 144 646 674 10.1016/j.cell.2011.02.013 21376230 212. Allavena P. Germano G. Marchesi F. Mantovani A. Chemokines in cancer related inflammation Exp. Cell Res. 2011 317 664 673 10.1016/j.yexcr.2010.11.013 21134366 213. Li L. Yu R. Cai T. Chen Z. Lan M. Zou T. Wang B. Wang Q. Zhao Y. Cai Y. Effects of immune cells and cytokines on inflammation and immunosuppression in the tumor microenvironment Int. Immunopharmacol. 2020 88 106939 10.1016/j.intimp.2020.106939 33182039 214. Mantovani A. Sica A. Sozzani S. Allavena P. Vecchi A. Locati M. The chemokine system in diverse forms of macrophage activation and polarization Trends Immunol. 2004 25 677 686 10.1016/j.it.2004.09.015 15530839 215. Mantovani A. Allavena P. Sica A. Tumour-associated macrophages as a prototypic type II polarised phagocyte population: Role in tumour progression Eur. J. Cancer 2004 40 1660 1667 10.1016/j.ejca.2004.03.016 15251154 216. Chavez-Galan L. Olleros M.L. Vesin D. Garcia I. Much More than M1 and M2 Macrophages, There are also CD169(+) and TCR(+) Macrophages Front. Immunol. 2015 6 263 10.3389/fimmu.2015.00263 26074923 217. Saha J. Sarkar D. Pramanik A. Mahanti K. Adhikary A. Bhattacharyya S. PGE2-HIF1alpha reciprocal induction regulates migration, phenotypic alteration and immunosuppressive capacity of macrophages in tumor microenvironment Life Sci. 2020 253 117731 10.1016/j.lfs.2020.117731 32353431 218. Zhang H. Lu H. Xiang L. Bullen J.W. Zhang C. Samanta D. Gilkes D.M. He J. Semenza G.L. HIF-1 regulates CD47 expression in breast cancer cells to promote evasion of phagocytosis and maintenance of cancer stem cells Proc. Natl. Acad. Sci. USA 2015 112 E6215 E6223 10.1073/pnas.1520032112 26512116 219. Tseng D. Volkmer J.P. Willingham S.B. Contreras-Trujillo H. Fathman J.W. Fernhoff N.B. Seita J. Inlay M.A. Weiskopf K. Miyanishi M. Anti-CD47 antibody-mediated phagocytosis of cancer by macrophages primes an effective antitumor T-cell response Proc. Natl. Acad. Sci. USA 2013 110 11103 11108 10.1073/pnas.1305569110 23690610 220. Cao X. Chen J. Li B. Dang J. Zhang W. Zhong X. Wang C. Raoof M. Sun Z. Yu J. Promoting antibody-dependent cellular phagocytosis for effective macrophage-based cancer immunotherapy Sci. Adv. 2022 8 eabl9171 10.1126/sciadv.abl9171 35302839 221. Hussain K. Liu R. Smith R.C.G. Muller K.T.J. Ghorbani M. Macari S. Cleary K.L.S. Oldham R.J. Foxall R.B. James S. HIF activation enhances FcgammaRIIb expression on mononuclear phagocytes impeding tumor targeting antibody immunotherapy J. Exp. Clin. Cancer Res. 2022 41 131 10.1186/s13046-022-02294-5 35392965 222. Delprat V. Tellier C. Demazy C. Raes M. Feron O. Michiels C. Cycling hypoxia promotes a pro-inflammatory phenotype in macrophages via JNK/p65 signaling pathway Sci. Rep. 2020 10 882 10.1038/s41598-020-57677-5 31964911 223. Imtiyaz H.Z. Williams E.P. Hickey M.M. Patel S.A. Durham A.C. Yuan L.J. Hammond R. Gimotty P.A. Keith B. Simon M.C. Hypoxia-inducible factor 2alpha regulates macrophage function in mouse models of acute and tumor inflammation J. Clin. Investig. 2010 120 2699 2714 10.1172/JCI39506 20644254 224. Takeda N. O’Dea E.L. Doedens A. Kim J.W. Weidemann A. Stockmann C. Asagiri M. Simon M.C. Hoffmann A. Johnson R.S. Differential activation and antagonistic function of HIF-{alpha} isoforms in macrophages are essential for NO homeostasis Genes Dev. 2010 24 491 501 10.1101/gad.1881410 20194441 225. Ye J. Koumenis C. ATF4, an ER stress and hypoxia-inducible transcription factor and its potential role in hypoxia tolerance and tumorigenesis Curr. Mol. Med. 2009 9 411 416 10.2174/156652409788167096 19519398 226. Elbarghati L. Murdoch C. Lewis C.E. Effects of hypoxia on transcription factor expression in human monocytes and macrophages Immunobiology 2008 213 899 908 10.1016/j.imbio.2008.07.016 18926304 227. Mukherjee D. Bercz L.S. Torok M.A. Mace T.A. Regulation of cellular immunity by activating transcription factor 4 Immunol. Lett. 2020 228 24 34 10.1016/j.imlet.2020.09.006 33002512 228. Xia H.F. Zhu J.Y. Wang J.N. Ren J.G. Cai Y. Wang F.Q. Zhang W. Chen G. Zhao Y.F. Zhao J.H. Association of ATF4 Expression With Tissue Hypoxia and M2 Macrophage Infiltration in Infantile Hemangioma J. Histochem. Cytochem. 2017 65 285 294 10.1369/0022155417694872 28438094 229. Xi J. Huang Q. Wang L. Ma X. Deng Q. Kumar M. Zhou Z. Li L. Zeng Z. Young K.H. miR-21 depletion in macrophages promotes tumoricidal polarization and enhances PD-1 immunotherapy Oncogene 2018 37 3151 3165 10.1038/s41388-018-0178-3 29540832 230. Xu Z. Zhao L. Zhu L.Y. He M. Zheng L. Wu Y. MicroRNA-17, 20a regulates the proangiogenic function of tumor-associated macrophages via targeting hypoxia-inducible factor 2alpha PLoS ONE 2013 8 e77890 10.1371/journal.pone.0077890 24194900 231. Casazza A. Di Conza G. Wenes M. Finisguerra V. Deschoemaeker S. Mazzone M. Tumor stroma: A complexity dictated by the hypoxic tumor microenvironment Oncogene 2014 33 1743 1754 10.1038/onc.2013.121 23604130 232. Giannoni E. Bianchini F. Masieri L. Serni S. Torre E. Calorini L. Chiarugi P. Reciprocal activation of prostate cancer cells and cancer-associated fibroblasts stimulates epithelial-mesenchymal transition and cancer stemness Cancer Res. 2010 70 6945 6956 10.1158/0008-5472.CAN-10-0785 20699369 233. Erez N. Truitt M. Olson P. Arron S.T. Hanahan D. Cancer-Associated Fibroblasts Are Activated in Incipient Neoplasia to Orchestrate Tumor-Promoting Inflammation in an NF-kappaB-Dependent Manner Cancer Cell 2010 17 135 147 10.1016/j.ccr.2009.12.041 20138012 234. Albrengues J. Bertero T. Grasset E. Bonan S. Maiel M. Bourget I. Philippe C. Herraiz Serrano C. Benamar S. Croce O. Epigenetic switch drives the conversion of fibroblasts into proinvasive cancer-associated fibroblasts Nat. Commun. 2015 6 10204 10.1038/ncomms10204 26667266 235. Kalluri R. The biology and function of fibroblasts in cancer Nat. Rev. Cancer 2016 16 582 598 10.1038/nrc.2016.73 27550820 236. Monteran L. Erez N. The Dark Side of Fibroblasts: Cancer-Associated Fibroblasts as Mediators of Immunosuppression in the Tumor Microenvironment Front. Immunol. 2019 10 1835 10.3389/fimmu.2019.01835 31428105 237. Nazemi M. Rainero E. Cross-Talk Between the Tumor Microenvironment, Extracellular Matrix, and Cell Metabolism in Cancer Front. Oncol. 2020 10 239 10.3389/fonc.2020.00239 32175281 238. Stojanovic A. Cerwenka A. Natural killer cells and solid tumors J. Innate Immun. 2011 3 355 364 10.1159/000325465 21502747 239. Huntington N.D. Cursons J. Rautela J. The cancer-natural killer cell immunity cycle Nat. Rev. Cancer 2020 20 437 454 10.1038/s41568-020-0272-z 32581320 240. Smyth M.J. Thia K.Y. Street S.E. Cretney E. Trapani J.A. Taniguchi M. Kawano T. Pelikan S.B. Crowe N.Y. Godfrey D.I. Differential tumor surveillance by natural killer (NK) and NKT cells J. Exp. Med. 2000 191 661 668 10.1084/jem.191.4.661 10684858 241. Bottcher J.P. Bonavita E. Chakravarty P. Blees H. Cabeza-Cabrerizo M. Sammicheli S. Rogers N.C. Sahai E. Zelenay S. e Sousa C.R. NK Cells Stimulate Recruitment of cDC1 into the Tumor Microenvironment Promoting Cancer Immune Control Cell 2018 172 1022 1037.e14 10.1016/j.cell.2018.01.004 29429633 242. Vivier E. Raulet D.H. Moretta A. Caligiuri M.A. Zitvogel L. Lanier L.L. Yokoyama W.M. Ugolini S. Innate or adaptive immunity? The example of natural killer cells Science 2011 331 44 49 10.1126/science.1198687 21212348 243. Voskoboinik I. Whisstock J.C. Trapani J.A. Perforin and granzymes: Function, dysfunction and human pathology Nat. Rev. Immunol. 2015 15 388 400 10.1038/nri3839 25998963 244. Lu H. Forbes R.A. Verma A. Hypoxia-inducible factor 1 activation by aerobic glycolysis implicates the Warburg effect in carcinogenesis J. Biol. Chem. 2002 277 23111 23115 10.1074/jbc.M202487200 11943784 245. Semenza G.L. Jiang B.H. Leung S.W. Passantino R. Concordet J.P. Maire P. Giallongo A. Hypoxia response elements in the aldolase A, enolase 1, and lactate dehydrogenase A gene promoters contain essential binding sites for hypoxia-inducible factor 1 J. Biol. Chem. 1996 271 32529 32537 10.1074/jbc.271.51.32529 8955077 246. Teng R. Wang Y. Lv N. Zhang D. Williamson R.A. Lei L. Chen P. Lei L. Wang B. Fu J. Hypoxia Impairs NK Cell Cytotoxicity through SHP-1-Mediated Attenuation of STAT3 and ERK Signaling Pathways J. Immunol. Res. 2020 2020 4598476 10.1155/2020/4598476 33123602 247. Duan S. Guo W. Xu Z. He Y. Liang C. Mo Y. Wang Y. Xiong F. Guo C. Li Y. Natural killer group 2D receptor and its ligands in cancer immune escape Mol. Cancer 2019 18 29 10.1186/s12943-019-0956-8 30813924 248. Siemens D.R. Hu N. Sheikhi A.K. Chung E. Frederiksen L.J. Pross H. Graham C.H. Hypoxia increases tumor cell shedding of MHC class I chain-related molecule: Role of nitric oxide Cancer Res. 2008 68 4746 4753 10.1158/0008-5472.CAN-08-0054 18559521 249. Sarkar S. Germeraad W.T. Rouschop K.M. Steeghs E.M. van Gelder M. Bos G.M. Wieten L. Hypoxia induced impairment of NK cell cytotoxicity against multiple myeloma can be overcome by IL-2 activation of the NK cells PLoS ONE 2013 8 e64835 10.1371/journal.pone.0064835 23724099 250. Balsamo M. Manzini C. Pietra G. Raggi F. Blengio F. Mingari M.C. Varesio L. Moretta L. Bosco M.C. Vitale M. Hypoxia downregulates the expression of activating receptors involved in NK-cell-mediated target cell killing without affecting ADCC Eur. J. Immunol. 2013 43 2756 2764 10.1002/eji.201343448 23913266 251. Solocinski K. Padget M.R. Fabian K.P. Wolfson B. Cecchi F. Hembrough T. Benz S.C. Rabizadeh S. Soon-Shiong P. Schlom J. Overcoming hypoxia-induced functional suppression of NK cells J. Immunother. Cancer 2020 8 e000246 10.1136/jitc-2019-000246 32345623 252. Kumar V. Adenosine as an endogenous immunoregulator in cancer pathogenesis: Where to go? Purinergic Signal. 2013 9 145 165 10.1007/s11302-012-9349-9 23271562 253. Groth C. Hu X. Weber R. Fleming V. Altevogt P. Utikal J. Umansky V. Immunosuppression mediated by myeloid-derived suppressor cells (MDSCs) during tumour progression Br. J. Cancer 2019 120 16 25 10.1038/s41416-018-0333-1 30413826 254. Veglia F. Sanseviero E. Gabrilovich D.I. Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity Nat. Rev. Immunol. 2021 21 485 498 10.1038/s41577-020-00490-y 33526920 255. Tartour E. Pere H. Maillere B. Terme M. Merillon N. Taieb J. Sandoval F. Quintin-Colonna F. Lacerda K. Karadimou A. Angiogenesis and immunity: A bidirectional link potentially relevant for the monitoring of antiangiogenic therapy and the development of novel therapeutic combination with immunotherapy Cancer Metastasis Rev. 2011 30 83 95 10.1007/s10555-011-9281-4 21249423 256. Shojaei F. Wu X. Qu X. Kowanetz M. Yu L. Tan M. Meng Y.G. Ferrara N. G-CSF-initiated myeloid cell mobilization and angiogenesis mediate tumor refractoriness to anti-VEGF therapy in mouse models Proc. Natl. Acad. Sci. USA 2009 106 6742 6747 10.1073/pnas.0902280106 19346489 257. Ostrand-Rosenberg S. Beury D.W. Parker K.H. Horn L.A. Survival of the fittest: How myeloid-derived suppressor cells survive in the inhospitable tumor microenvironment Cancer Immunol. Immunother. 2020 69 215 221 10.1007/s00262-019-02388-8 31501954 258. Nagaraj S. Gupta K. Pisarev V. Kinarsky L. Sherman S. Kang L. Herber D.L. Schneck J. Gabrilovich D.I. Altered recognition of antigen is a mechanism of CD8+ T cell tolerance in cancer Nat. Med. 2007 13 828 835 10.1038/nm1609 17603493 259. Gabrilovich D.I. Ostrand-Rosenberg S. Bronte V. Coordinated regulation of myeloid cells by tumours Nat. Rev. Immunol. 2012 12 253 268 10.1038/nri3175 22437938 260. Porta C. Consonni F.M. Morlacchi S. Sangaletti S. Bleve A. Totaro M.G. Larghi P. Rimoldi M. Tripodo C. Strauss L. Tumor-Derived Prostaglandin E2 Promotes p50 NF-kappaB-Dependent Differentiation of Monocytic MDSCs Cancer Res. 2020 80 2874 2888 10.1158/0008-5472.CAN-19-2843 32265223 261. Noman M.Z. Janji B. Hu S. Wu J.C. Martelli F. Bronte V. Chouaib S. Tumor-Promoting Effects of Myeloid-Derived Suppressor Cells Are Potentiated by Hypoxia-Induced Expression of miR-210 Cancer Res. 2015 75 3771 3787 10.1158/0008-5472.CAN-15-0405 26206559 262. Feng J. Yang H. Zhang Y. Wei H. Zhu Z. Zhu B. Yang M. Cao W. Wang L. Wu Z. Tumor cell-derived lactate induces TAZ-dependent upregulation of PD-L1 through GPR81 in human lung cancer cells Oncogene 2017 36 5829 5839 10.1038/onc.2017.188 28604752 263. Chang C.H. Qiu J. O’Sullivan D. Buck M.D. Noguchi T. Curtis J.D. Chen Q. Gindin M. Gubin M.M. van der Windt G.J. Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression Cell 2015 162 1229 1241 10.1016/j.cell.2015.08.016 26321679 264. Magalhaes I. Yogev O. Mattsson J. Schurich A. The Metabolic Profile of Tumor and Virally Infected Cells Shapes Their Microenvironment Counteracting T Cell Immunity Front. Immunol. 2019 10 2309 10.3389/fimmu.2019.02309 31636636 265. Blank C.U. Haining W.N. Held W. Hogan P.G. Kallies A. Lugli E. Lynn R.C. Philip M. Rao A. Restifo N.P. Defining ‘T cell exhaustion’ Nat. Rev. Immunol. 2019 19 665 674 10.1038/s41577-019-0221-9 31570879 266. Liikanen I. Lauhan C. Quon S. Omilusik K. Phan A.T. Bartroli L.B. Ferry A. Goulding J. Chen J. Scott-Browne J.P. Hypoxia-inducible factor activity promotes antitumor effector function and tissue residency by CD8+ T cells J. Clin. Investig. 2021 131 e143729 10.1172/JCI143729 33792560 267. Hasan F. Chiu Y. Shaw R.M. Wang J. Yee C. Hypoxia acts as an environmental cue for the human tissue-resident memory T cell differentiation program JCI Insight 2021 6 e138970 10.1172/jci.insight.138970 34027895 268. Fisher J.P. Heuijerjans J. Yan M. Gustafsson K. Anderson J. gammadelta T cells for cancer immunotherapy: A systematic review of clinical trials Oncoimmunology 2014 3 e27572 10.4161/onci.27572 24734216 269. de Almeida P.E. Mak J. Hernandez G. Jesudason R. Herault A. Javinal V. Borneo J. Kim J.M. Walsh K.B. Anti-VEGF Treatment Enhances CD8(+) T-cell Antitumor Activity by Amplifying Hypoxia Cancer Immunol. Res. 2020 8 806 818 10.1158/2326-6066.CIR-19-0360 32238381 270. Gropper Y. Feferman T. Shalit T. Salame T.M. Porat Z. Shakhar G. Culturing CTLs under Hypoxic Conditions Enhances Their Cytolysis and Improves Their Anti-tumor Function Cell Rep. 2017 20 2547 2555 10.1016/j.celrep.2017.08.071 28903036 271. Zhang N. Yin R. Zhou P. Liu X. Fan P. Qian L. Dong L. Zhang C. Zheng X. Deng S. DLL1 orchestrates CD8(+) T cells to induce long-term vascular normalization and tumor regression Proc. Natl. Acad. Sci. USA 2021 118 e2020057118 10.1073/pnas.2020057118 34035167 272. Hsu T.S. Lin Y.L. Wang Y.A. Mo S.T. Chi P.Y. Lai A.C. Pan H.Y. Chang Y.J. Lai M.Z. HIF-2alpha is indispensable for regulatory T cell function Nat. Commun. 2020 11 5005 10.1038/s41467-020-18731-y 33024109 273. Burrows N. Bashford-Rogers R.J.M. Bhute V.J. Penalver A. Ferdinand J.R. Stewart B.J. Smith J.E.G. Deobagkar-Lele M. Giudice G. Connor T.M. Dynamic regulation of hypoxia-inducible factor-1alpha activity is essential for normal B cell development Nat. Immunol. 2020 21 1408 1420 10.1038/s41590-020-0772-8 32868930 274. Kojima H. Kobayashi A. Sakurai D. Kanno Y. Hase H. Takahashi R. Totsuka Y. Semenza G.L. Sitkovsky M.V. Kobata T. Differentiation stage-specific requirement in hypoxia-inducible factor-1alpha-regulated glycolytic pathway during murine B cell development in bone marrow J. Immunol. 2010 184 154 163 10.4049/jimmunol.0800167 19949104 275. Cho S.H. Raybuck A.L. Stengel K. Wei M. Beck T.C. Volanakis E. Thomas J.W. Hiebert S. Haase V.H. Boothby M.R. Germinal centre hypoxia and regulation of antibody qualities by a hypoxia response system Nature 2016 537 234 238 10.1038/nature19334 27501247 276. Nielsen J.S. Sahota R.A. Milne K. Kost S.E. Nesslinger N.J. Watson P.H. Nelson B.H. CD20+ tumor-infiltrating lymphocytes have an atypical CD27-memory phenotype and together with CD8+ T cells promote favorable prognosis in ovarian cancer Clin. Cancer Res. 2012 18 3281 3292 10.1158/1078-0432.CCR-12-0234 22553348 277. Rodriguez-Pinto D. B cells as antigen presenting cells Cell Immunol. 2005 238 67 75 10.1016/j.cellimm.2006.02.005 16574086 278. Nelson B.H. CD20+ B cells: The other tumor-infiltrating lymphocytes J. Immunol. 2010 185 4977 4982 10.4049/jimmunol.1001323 20962266 279. Shi J.Y. Gao Q. Wang Z.C. Zhou J. Wang X.Y. Min Z.H. Shi Y.H. Shi G.M. Ding Z.B. Ke A.W. Margin-infiltrating CD20(+) B cells display an atypical memory phenotype and correlate with favorable prognosis in hepatocellular carcinoma Clin. Cancer Res. 2013 19 5994 6005 10.1158/1078-0432.CCR-12-3497 24056784 280. Kemp T.J. Moore J.M. Griffith T.S. Human B cells express functional TRAIL/Apo-2 ligand after CpG-containing oligodeoxynucleotide stimulation J. Immunol. 2004 173 892 899 10.4049/jimmunol.173.2.892 15240676 281. Nothelfer K. Sansonetti P.J. Phalipon A. Pathogen manipulation of B cells: The best defence is a good offence Nat. Rev. Microbiol. 2015 13 173 184 10.1038/nrmicro3415 25659322 282. Laferriere J. Houle F. Taher M.M. Valerie K. Huot J. Transendothelial migration of colon carcinoma cells requires expression of E-selectin by endothelial cells and activation of stress-activated protein kinase-2 (SAPK2/p38) in the tumor cells J. Biol. Chem. 2001 276 33762 33772 10.1074/jbc.M008564200 11448946 283. Pober J.S. Cotran R.S. Cytokines and endothelial cell biology Physiol. Rev. 1990 70 427 451 10.1152/physrev.1990.70.2.427 1690903 284. Springer T.A. Traffic signals for lymphocyte recirculation and leukocyte emigration: The multistep paradigm Cell 1994 76 301 314 10.1016/0092-8674(94)90337-9 7507411 285. Wolff B. Burns A.R. Middleton J. Rot A. Endothelial cell “memory” of inflammatory stimulation: Human venular endothelial cells store interleukin 8 in Weibel-Palade bodies J. Exp. Med. 1998 188 1757 1762 10.1084/jem.188.9.1757 9802987 286. Schraufstatter I.U. Chung J. Burger M. IL-8 activates endothelial cell CXCR1 and CXCR2 through Rho and Rac signaling pathways Am. J. Physiol. Lung Cell. Mol. Physiol. 2001 280 L1094 L1103 10.1152/ajplung.2001.280.6.L1094 11350788 287. Carman C.V. Martinelli R. T Lymphocyte-Endothelial Interactions: Emerging Understanding of Trafficking and Antigen-Specific Immunity Front. Immunol. 2015 6 603 10.3389/fimmu.2015.00603 26635815 288. Luscinskas F.W. Kansas G.S. Ding H. Pizcueta P. Schleiffenbaum B.E. Tedder T.F. Gimbrone M.A. Jr. Monocyte rolling, arrest and spreading on IL-4-activated vascular endothelium under flow is mediated via sequential action of L-selectin, beta 1-integrins, and beta 2-integrins J. Cell Biol. 1994 125 1417 1427 10.1083/jcb.125.6.1417 7515891 289. Diamond M.S. Springer T.A. The dynamic regulation of integrin adhesiveness Curr. Biol. 1994 4 506 517 10.1016/S0960-9822(00)00111-1 7922371 290. Luo B.H. Carman C.V. Springer T.A. Structural basis of integrin regulation and signaling Annu. Rev. Immunol. 2007 25 619 647 10.1146/annurev.immunol.25.022106.141618 17201681 291. Ley K. Laudanna C. Cybulsky M.I. Nourshargh S. Getting to the site of inflammation: The leukocyte adhesion cascade updated Nat. Rev. Immunol. 2007 7 678 689 10.1038/nri2156 17717539 292. Sakai Y. Kobayashi M. Lymphocyte ‘homing’ and chronic inflammation Pathol. Int. 2015 65 344 354 10.1111/pin.12294 25831975 293. Tremblay P.L. Huot J. Auger F.A. Mechanisms by which E-selectin regulates diapedesis of colon cancer cells under flow conditions Cancer Res. 2008 68 5167 5176 10.1158/0008-5472.CAN-08-1229 18593916 294. Lewalle J.M. Bajou K. Desreux J. Mareel M. Dejana E. Noel A. Foidart J.M. Alteration of interendothelial adherens junctions following tumor cell-endothelial cell interaction in vitro Exp. Cell Res. 1997 237 347 356 10.1006/excr.1997.3799 9434630 295. Kebers F. Lewalle J.M. Desreux J. Munaut C. Devy L. Foidart J.M. Noel A. Induction of endothelial cell apoptosis by solid tumor cells Exp. Cell Res. 1998 240 197 205 10.1006/excr.1998.3935 9596992 296. Laferriere J. Houle F. Huot J. Adhesion of HT-29 colon carcinoma cells to endothelial cells requires sequential events involving E-selectin and integrin beta4 Clin. Exp. Metastasis 2004 21 257 264 10.1023/B:CLIN.0000037708.09420.9a 15387376 297. Mierke C.T. Role of the endothelium during tumor cell metastasis: Is the endothelium a barrier or a promoter for cell invasion and metastasis? J. Biophys. 2008 2008 183516 10.1155/2008/183516 20107573 298. Su W.H. Chen H.I. Jen C.J. Differential movements of VE-cadherin and PECAM-1 during transmigration of polymorphonuclear leukocytes through human umbilical vein endothelium Blood 2002 100 3597 3603 10.1182/blood-2002-01-0303 12393634 299. Schmedtje J.F. Jr. Ji Y.S. Liu W.L. DuBois R.N. Runge M.S. Hypoxia induces cyclooxygenase-2 via the NF-kappaB p65 transcription factor in human vascular endothelial cells J. Biol. Chem. 1997 272 601 608 10.1074/jbc.272.1.601 8995303 300. Michiels C. Arnould T. Remacle J. Endothelial cell responses to hypoxia: Initiation of a cascade of cellular interactions Biochim. Biophys. Acta 2000 1497 1 10 10.1016/S0167-4889(00)00041-0 10838154 301. Tambuwala M.M. Khan M.N. Thompson P. McCarron P.A. Albumin nano-encapsulation of caffeic acid phenethyl ester and piceatannol potentiated its ability to modulate HIF and NF-kB pathways and improves therapeutic outcome in experimental colitis Drug Deliv. Transl. Res. 2019 9 14 24 10.1007/s13346-018-00597-9 30430451 302. Syed A.R. Thakkar P. Horne Z.D. Abdul-Baki H. Kochhar G. Farah K. Thakkar S. Old vs new: Risk factors predicting early onset colorectal cancer World J. Gastrointest. Oncol. 2019 11 1011 1020 10.4251/wjgo.v11.i11.1011 31798781 303. Bhattarai D. Xu X. Lee K. Hypoxia-inducible factor-1 (HIF-1) inhibitors from the last decade (2007 to 2016): A “structure-activity relationship” perspective Med. Res. Rev. 2018 38 1404 1442 10.1002/med.21477 29278273 304. Visweswaran V. Pavithran K. Belzutifan: A Narrative Drug Review Curr. Drug Res. Rev. 2022 10.2174/2589977514666220401094724 35366789 305. Choueiri T.K. Kaelin W.G. Jr. Targeting the HIF2-VEGF axis in renal cell carcinoma Nat. Med. 2020 26 1519 1530 10.1038/s41591-020-1093-z 33020645 306. Jonasch E. Donskov F. Iliopoulos O. Rathmell W.K. Narayan V.K. Maughan B.L. Oudard S. Else T. Maranchie J.K. Welsh S.J. Belzutifan for Renal Cell Carcinoma in von Hippel-Lindau Disease N. Engl. J. Med. 2021 385 2036 2046 10.1056/NEJMoa2103425 34818478 307. Wang J. Ma Y. Jiang H. Zhu H. Liu L. Sun B. Pan S. Krissansen G.W. Sun X. Overexpression of von Hippel-Lindau protein synergizes with doxorubicin to suppress hepatocellular carcinoma in mice J. Hepatol. 2011 55 359 368 10.1016/j.jhep.2010.10.043 21168458 308. Iwamoto H. Nakamura T. Koga H. Izaguirre-Carbonell J. Kamisuki S. Sugawara F. Abe M. Iwabata K. Ikezono Y. Sakaue T. Inhibition of hypoxia-inducible factor via upregulation of von Hippel-Lindau protein induces “angiogenic switch off” in a hepatoma mouse model Mol. Ther. Oncolytics 2015 2 15020 10.1038/mto.2015.20 27119112 309. Song S. He X. Zeng Z. Zhang H. Yao Q. Yang F. Zheng C. Guo X. Blocking transforming growth factor-beta reduces the migration and invasion of the residual tumour after TAE Am. J. Transl. Res. 2019 11 2155 2167 31105825 310. Li S. Liu M. Do M.H. Chou C. Stamatiades E.G. Nixon B.G. Shi W. Zhang X. Li P. Gao S. Cancer immunotherapy via targeted TGF-beta signalling blockade in TH cells Nature 2020 587 121 125 10.1038/s41586-020-2850-3 33087933 311. Cui R. Yue W. Lattime E.C. Stein M.N. Xu Q. Tan X.L. Targeting tumor-associated macrophages to combat pancreatic cancer Oncotarget 2016 7 50735 50754 10.18632/oncotarget.9383 27191744 312. Deng L. Stafford J.H. Liu S.C. Chernikova S.B. Merchant M. Recht L. Martin Brown J. SDF-1 Blockade Enhances Anti-VEGF Therapy of Glioblastoma and Can Be Monitored by MRI Neoplasia 2017 19 1 7 10.1016/j.neo.2016.11.010 27940247 313. Poh A.R. Ernst M. Targeting Macrophages in Cancer: From Bench to Bedside Front. Oncol. 2018 8 49 10.3389/fonc.2018.00049 29594035 314. Dewi F.R.P. Ahmar R.F. Alifiyah N.I. Shoukat N. Wahyuningsih S.P.A. The potential of A. Muricata Bioactive Compounds to Inhibit HIF1alpha Expression Via Disruption of Tyrosine Kinase Receptor Activity: An In Silico Study Acta Inform. Med. 2021 29 176 181 10.5455/aim.2021.29.176-181 34759456 315. Pang L. Qin J. Han L. Zhao W. Liang J. Xie Z. Yang P. Wang J. Exploiting macrophages as targeted carrier to guide nanoparticles into glioma Oncotarget 2016 7 37081 37091 10.18632/oncotarget.9464 27213597 316. Choi M.R. Stanton-Maxey K.J. Stanley J.K. Levin C.S. Bardhan R. Akin D. Badve S. Sturgis J. Robinson J.P. Bashir R. A cellular Trojan Horse for delivery of therapeutic nanoparticles into tumors Nano Lett. 2007 7 3759 3765 10.1021/nl072209h 17979310 317. Hayashi Y. Goyama S. Liu X. Tamura M. Asada S. Tanaka Y. Fukuyama T. Wunderlich M. O’Brien E. Mizukawa B. Antitumor immunity augments the therapeutic effects of p53 activation on acute myeloid leukemia Nat. Commun. 2019 10 4869 10.1038/s41467-019-12555-1 31653912 318. Kumagai S. Koyama S. Itahashi K. Tanegashima T. Lin Y.T. Togashi Y. Kamada T. Irie T. Okumura G. Kono H. Lactic acid promotes PD-1 expression in regulatory T cells in highly glycolytic tumor microenvironments Cancer Cell 2022 40 201 218. e9 10.1016/j.ccell.2022.01.001 35090594 319. Modlich U. Pugh C.W. Bicknell R. Increasing endothelial cell specific expression by the use of heterologous hypoxic and cytokine-inducible enhancers Gene Ther. 2000 7 896 902 10.1038/sj.gt.3301177 10845728

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091769 nutrients-14-01769 Systematic Review Effect of Caffeine Ingestion on Indirect Markers of Exercise-Induced Muscle Damage: A Systematic Review of Human Trials Caldas Leonardo Carvalho 1 Salgueiro Rafael Barreira 2 https://orcid.org/0000-0002-1909-329X Clarke Neil David 3 https://orcid.org/0000-0001-8904-2693 Tallis Jason 3* https://orcid.org/0000-0003-2832-0922 Barauna Valerio Garrone 145 https://orcid.org/0000-0002-2970-7355 Guimaraes-Ferreira Lucas 136 Tauler Pedro Academic Editor 1 Postgraduate Program in Physical Education, Center of Physical Education and Sports, Federal University of Espirito Santo, Vitória 29075-910, ES, Brazil; leocaldas03@gmail.com (L.C.C.); barauna2@gmail.com (V.G.B.); ad6463@coventry.ac.uk (L.G.-F.) 2 Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo 05508-000, SP, Brazil; rafaeleefe@yahoo.com.br 3 Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry CV1 5FB, UK; neil.clarke@coventry.ac.uk 4 Postgraduate Program in Physiological Sciences, Centre of Health Sciences, Federal University of Espirito Santo, Vitória 29075-910, ES, Brazil 5 Postgraduate Program in Medical Sciences, Santa Cruz State University, Ilhéus 45662-900, BA, Brazil 6 School of Life Sciences, Coventry University, Coventry CV1 5FB, UK * Correspondence: jason.tallis@coventry.ac.uk; Tel.: +44-02477-658562 23 4 2022 5 2022 14 9 176928 2 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The effect of caffeine on mitigating exercise-induced muscle damage (EIMD) is still poorly understood, but it was hypothesized that caffeine could contribute to decreasing delayed onset muscle soreness, attenuating temporary loss of strength, and reducing circulating levels of blood markers of muscle damage. However, evidence is not conclusive and beneficial effects of caffeine ingestion on EIMD are not always observed. Factors, such as the type of exercise that induces muscle damage, supplementation protocol, and type of marker analyzed contribute to the differences between the studies. To expand knowledge on the role of caffeine supplementation in EIMD, this systematic review aimed to investigate the effect of caffeine supplementation on different markers of muscle damage. Fourteen studies were included, evaluating the effect of caffeine on indirect muscle damage markers, including blood markers (nine studies), pain perception (six studies), and MVC maximal voluntary contraction force (four studies). It was observed in four studies that repeated administration of caffeine between 24 and 72 h after muscle damage can attenuate the perception of pain in magnitudes ranging from 3.9% to 26%. The use of a single dose of caffeine pre-exercise (five studies) or post-exercise (one study) did not alter the circulating blood levels of creatine kinase (CK). Caffeine supplementation appears to attenuate pain perception, but this does not appear to be related to an attenuation of EIMD, per se. Furthermore, the effect of caffeine supplementation after muscle damage on strength recovery remains inconclusive due to the low number of studies found (four studies) and controversial results for both dynamic and isometric strength tests. ergogenic aids recovery lengthening contractions muscle damage delayed onset muscle soreness ==== Body pmc1. Introduction Caffeine consumption has been used as an ergogenic aid to improve exercise performance, as small but significant improvements were reported for long-duration aerobic exercise [1,2] and improving strength, muscle endurance, and power [3,4,5]. The low cost, easy acquisition, rapid absorption [6,7,8], and wealth of evidence supporting performance-enhancing effects, have contributed to the popularity of caffeine use in sports [9], with evidence estimating three out of four elite athletes (74%) use caffeine as an ergogenic aid before or during a sporting event [10]. In sports, even well-trained athletes could suffer from adverse effects caused by training sessions or competition, leading to muscle pain, temporary loss in muscle strength production capability, and reduced range of motion, which might impair recovery and sports performance [11,12,13]. In addition to improving sports performance, evidence also points out that caffeine could also contribute to attenuating exercise-induced muscle damage (EIMD) [14]. EIMD is characterized by physical damage to muscle fibers at the macro and micro structural levels, involving the sarcomeres, cell membrane, and connective tissue [15]. Eccentric muscle contractions are known to induce EIMD [16,17] but other factors also seem to influence EIMD occurrence, such as exercise intensity [18], skeletal muscle fiber type recruited during exercise [19], muscle contraction velocity [20], and joint range of motion during exercise [21,22]. EIMD is manifested by temporary impairments in muscle functioning, such as decreases in force production capacity, reductions in range of motion, swelling of the affected limb, increased stiffness, and muscle pain [23,24]. It was demonstrated that caffeine ingestion results in attenuation of delayed-onset muscle damage (DOMS) [25,26], attenuation of temporary loss of muscle [27] and reduction in blood markers of muscle damage [28]. However, evidence is not conclusive and beneficial effects of caffeine ingestion on EIMD are not always observed [29,30]. The differences between studies may be related to several possible factors, such as timing of supplementation (pre or post the event causing muscle damage), duration of supplementation protocol (e.g., acute versus chronic), and methods used for assessing muscle damage (e.g., pain perception, loss of strength, and blood markers of injury). Several studies have investigated the effect of caffeine using only one indirect marker of muscle damage, although it is not clear whether caffeine has a direct effect on each of these markers or if there is an interaction between them. For example, would decreases in pain perception with caffeine supplementation also be related to lower strength losses and lower circulating levels of creatine kinase after EIMD? Or do these effects happen independently? Therefore, the objective of this literature systematic review is to expand the understanding of the role of caffeine in mitigating the damage related to muscle damage, investigating the mechanisms of action involved and how the different supplementation protocols can interfere with its effects on EIMD attenuation or recovery. In our understanding, there are two possibilities for caffeine’s actions on EIMD: (1) caffeine used before a muscle damage-inducing protocol could result in less muscle damage; and/or (2) caffeine consumption after induction of muscle damage could act to relieve symptoms, especially recovery in contractile function after EIMD. 2. Materials and Methods 2.1. Experimental Approach to the Problem A systematic review was conducted following the procedures outlined by the Cochrane Handbook [31]. To guide the search, the following question was elaborated: Can caffeine supplementation attenuate exercise-induced muscle damage? The electronic searches included four recognized databases: PubMed, Scopus, Cochrane, and Bireme. 2.2. Procedure The systematic literature search was performed using the following terms and Boolean operators: “caffeine” AND “muscle damage” OR “exercise induced muscle damage” OR “soreness” OR “delayed onset muscle soreness” OR “pain”. No restrictions on any language or year of publication were applied, but only articles with abstracts in English were included. The search was performed in January 2022. Inclusion criteria were studies with human participants that investigated the effects of any form of caffeine ingestion on direct muscle damage markers (e.g., using muscle biopsy or magnetic resonance imaging) and/or indirect markers (changes in maximum isometric strength, muscle pain, changes in joint range of motion, changes in muscle circumference indicating swelling and blood markers of muscle damage). Studies were excluded if they did not include a placebo condition for comparison or combined caffeine with other nutritional supplements. Additionally, studies using animal models were also excluded. Following initial screening of the abstracts, two researchers independently screened the study’s full texts against the inclusion criteria. Any disagreements were discussed and resolved by consensus between both researchers. The literature search was performed in the following sequence: (A) the studies were electronically saved for later reading and evaluation; (B) initial screening was performed, abstracts were read, and those that did not meet the inclusion criteria were excluded; (C) the abstracts containing sufficient information described in the inclusion criteria and presented no reason for exclusion were archived for later reading of the full text; (D) after reading the full text, the studies were included or excluded according to the previous selection criteria; (E) after reading the full text from each study, the reference lists were also searched for any additional articles that were not found by our search strategy (Figure 1). 2.3. Coding and Classifying Variables The main coded categories of each included study were: (a) identification of the studies (authors and year of publication); (b) characteristics of the sample (age, sex, level of training); (c) caffeine consumption habits of the participants; (d) characteristics of the methodological quality of the studies (randomization and blinding strategy, study design, allocation concealment, intervention monitoring, loss to follow-up); (e) muscle damage protocol; (f) caffeine supplementation protocol (dose administered and duration of supplementation). The characteristics of the studies are shown in Table 1. Study quality was assessed according to the PEDro scale (https://pedro.org.au/english/resources/pedro-scale/ (20 April 2022)). The PEDro scale has strong reliability and validity [41,42,43] and has been widely used in other systematic reviews related to caffeine supplementation [2,5,44,45,46,47]. The scale consists of a list of 11 items; for each individual criterion of scientific methodology, studies receive a score of 1 when the criterion is clearly met or 0 when that criterion is not adequately met. The first item (eligibility criteria) does not receive a score because it is related to external validity and, therefore, does not reflect the quality dimensions assessed by the PEDro scale. Thus, the total scores range from 0 to 10. The criteria included in the Scale are criteria of: (1) eligibility criteria were specified (no score); (2) subjects were randomly allocated to groups; (3) allocation was concealed; (4) the groups were similar at baseline regarding the most important prognostic indicators; (5) there was blinding of all subjects; (6) there was blinding of all therapists who administered the therapy; (7) there was blinding of all assessors who measured at least one key outcome; (8) measures of at least one key outcome were obtained from more than 85% of the subjects initially allocated to groups; (9) all subjects for whom outcome measures were available received the treatment or control condition as allocated or, where this was not the case, data for at least one key outcome were analyzed by “intention to treat”; (10) the results of between-group statistical comparisons are reported for at least one key outcome; and (11) the study provides both point measures and measures of variability for at least one key outcome. The PEDro score for each study is shown in Table 2. 3. Results 3.1. Studies Search and Selection Process The initial search (PubMed, Scopus, Cochrane, and Bireme) resulted in 976 articles; 961 of them were excluded after reading the title and abstract for not meeting the inclusion criteria. The remaining 15 articles were included for full-text screening; 1 study was excluded [48], as it was identified that another study [36] already included in this review, presented analogous participants and results. Therefore, at the end of the search, 14 studies [25,27,28,29,30,32,33,34,35,36,37,38,39,40] were included in this systematic review (Figure 1). 3.2. Studies and Participant Characteristics All data characteristics of the studies could be found in Table 1. The sample size of each study ranged from 6 to 35 participants resulting in a total sample of 248 participants, 174 men (70%) and 74 women (30%); 127 participants (51%) were athletes from various sports (soccer, handball, basketball, cycling, skiers), 51 participants (21%) were physically active, 12 participants (5%) had experience with resistance training, 10 participants (4%) had no exercise experience, and 48 participants (19%) had no described training status. There is no consensus on the classification of habitual caffeine consumption, but Filip et al. [49] proposed a classification based on daily caffeine intake relative to body weight (mg·kg−1.day−1). According to these authors, mild consumers ingest less than 3 mg·kg−1·day−1 of caffeine. Most of the studies included in the present review used absolute doses when accessing caffeine daily consumption, so we established the daily dose of 200 mg·day−1 as the limit between low/mild and moderate/high consumers, which is close to the values proposed by Filip et al. [49] if we consider a 70 kg adult. Eight studies [27,28,30,34,36,37,38,39] included participants with a history of low/mild caffeine consumption (<200 mg/day) representing 117 participants (47%); however, in the study by Hurley et al. [34], the participants’ mean caffeine consumption was not described. Three studies [25,29,33] included moderate to high caffeine users (>200 mg/day) representing 59 participants (24%) and three studies [32,35,40] did not assess mean caffeine consumption of participants, representing 72 participants (29%). Eleven studies (78.5%) used a double-blind cross-over design. In nine of those studies, the washout period between the caffeine/placebo condition was greater than 6 days and in two studies this period was less than 48 h. The other three studies (21.5%) opted for a double-blind design with parallel groups. The protocol for inducing muscle damage was varied, ranging from exercises in isolated muscle groups (e.g., quadriceps and elbow flexors) to multi-articular exercises involving the whole body. Resistance exercise with eccentric muscle contraction for inducing muscle damage was used by six studies [29,30,33,34,38,48], and eight other studies [25,27,28,32,35,37,39,40] used a variety of test protocols including exercise on cyclergometer, treadmill running, stair climbing, and sport-specific movements for soccer and skiing. Caffeine dosage varied from 3 mg·kg−1 to 7 mg·kg−1. Eight studies [28,32,35,37,38,39,40,48] used a single dose 55 to 70 min prior to an EIMD protocol. One study [27] used a single dose 24 h after the EIMD protocol and in five studies [25,29,30,33,34] caffeine was ingested two or more times between 48 and 72 h after EIMD. 3.3. Methodological Quality of Studies The PEDro scale was used to assess the methodological quality of the studies (Table 2) and 12 studies (86%) received the maximum score (10 points). Work by Bassini-Cameron et al. [32] study received 8 of 10 total points, not fulfilling the seventh criterion, since three of the participants had been reassigned to the control group after protocol intervention for not completing the task; and it also affects the eighth criterion, in which the reallocation represented a loss of more than 85% allowed by this criterion. Maridakis et al. [30] scored nine points for not meeting the third criterion of the PEDro scale. The reason is that, even before caffeine treatment, the supposed caffeine treatment group already had a difference in pain perception vs. placebo group. 3.4. Effect of Caffeine Supplementation on Indirect Markers of Muscle Damage Six studies (43%) evaluated the effect of caffeine supplementation on delayed onset muscle soreness (DOMS). Of these, four studies found that caffeine ingestion was able to reduce pain perception between 24 and 48 h following the muscle damage protocol [25,27,30,34], one study [33] found no significant difference between groups and one study [39] observed higher DOMS in the caffeine group when compared to the placebo group. In total, nine studies (64%) evaluated blood markers of muscle damage, two studies found higher circulating levels of creatine kinase (CK) in the caffeine-supplemented groups [32,39], and one study found the opposite result [28] with a higher circulating level of CK in the placebo group. Most studies (six studies) found no significant difference between groups (caffeine vs. placebo) for blood markers of muscle damage including CK, lactate dehydrogenase (LDH), aspartate aminotransferase, alanine aminotransferase, and oxidative stress markers, such as: malondialdehyde and total antioxidant capacity [34,35,36,37,38,40]. Four studies evaluated the effects of caffeine supplementation on maximum voluntary isometric contraction (MVIC) loss after EIMD. Chen et al. [27] observed that caffeine ingestion resulted in an attenuation of MVIC loss 48 h after the EIMD protocol. However, three other studies did not observe any difference between caffeine and placebo conditions on MVIC recovery after EIMD [29,30,33]. 4. Discussion The current systematic review aimed to summarize the effects of acute caffeine ingestion on attenuation of muscle damage or improving recovery after EIMD. Studies supplemented caffeine pre and/or post exercise-induced muscle damage protocol and evaluated at least one muscle damage marker. Due to the complexity of measuring muscle damage, studies have used a wide variety of direct and indirect markers [50,51]. Indirect markers used in the included studies were force production capacity loss, reduced joint range of motion, muscle swelling (increased limb circumference), DOMS, and blood markers (i.e., muscle damage, inflammation, and oxidative stress markers) [23,50,52]. Direct methods for assessing muscle damage included muscle biopsy and magnetic resonance imaging [51]. However, no studies included in the current review evaluated direct markers of muscle damage. All fourteen studies included in the systematic review evaluated the effects of caffeine on indirect markers of muscle damage. Nine studies included blood markers, six studies used pain perception, and four studies evaluated muscle strength loss after an EIMD protocol. 4.1. Muscle Soreness The most common symptom of muscle damage induced by eccentric contractions is DOMS and it is also the most widely used injury marker in human studies [50,53,54]. It is postulated that caffeine has an analgesic effect on DOMS due to its action on the central nervous system [30,34,55]. Of six studies evaluating the effects of caffeine supplementation on DOMS, four observed a lower pain perception in caffeine condition when compared to placebo between 24 and 72 h after exercise. The magnitude of pain attenuation varied according to the scale used. Caldwell et al. [25], for example, observed reductions of 1.3 points in the caffeine group 24 h after exercise using a 1–6 point pain perception scale, which represents a reduction of 26%. In another study [34], pain in the caffeine group was reduced by 0.9 points 48 h after exercise, using a 0–10 point scale (9%), and Chen et al. [27] used a scale of 0–100 points and observed reductions of 11.2 points (11.2%) in the perception of pain in the caffeine group 48 h after exercise. Maridakis et al. [30], using the same scale, observed reductions of 3.9 points in the caffeine group 24 h after muscle damage induction exercise. It is important to highlight that in the Maridakis et al. study, pain perception analysis was performed while the participants were performing submaximal and maximum isometric eccentric muscle actions, in contrast to other studies where pain perception was accessed at rest or after exercise using muscle palpation. Only two studies showed an absence or negative effect of caffeine on pain perception. Stadheim et al. [39] investigated the effects of a single dose of caffeine followed by a 10-min cross-country skiing exercise protocol on an ergometer. These authors observed that the caffeine groups showed elevated pain perception after 24 h of the test simultaneously with greater workload performed (longer distance covered) on the ergometer when compared to the placebo group. Therefore, the higher pain perception may be related to the injury caused by the greater effort during the ergometer test. Green et al. [33] evaluated pain perception 24 h after eccentric contractions of the knee extensor muscles and the effects of caffeine ingestion. The authors observed no significant differences in pain perception after the exercise protocol between caffeine and placebo groups. In this study, participants were regular caffeine consumers (although the exact daily caffeine intake was not reported), which differ from the four other studies that observed a decrease in pain perception after caffeine ingestion compared to placebo, using low caffeine consumers (daily caffeine consumption lower than 230 mg·kg−1 of body weight). Caffeine effect on habitual and non-habitual consumers remains under debate due to a limited number of studies and controversial results [9]. Taken together, four out of five studies using caffeine supplementation after the induction of EIMD showed decreases in pain perception after 24 to 72 h with magnitudes ranging from 3.9% to 26% when compared to the placebo group. It is also important to note that the peak in DOMS also occurred 48 to 72 h after EIMD [23,54,56]. Differences observed in the magnitude of DOMS attenuation after caffeine supplementation may be related to different exercise protocols, which could lead to different levels of muscle damage and due to the complexity of cellular events associated with muscle damage and the interaction of several chemical mediators after eccentric exercise capable of stimulating nociceptors. It is proposed that DOMS is mainly caused by eccentric muscle contractions, which might lead to tissue microdamage and stimulate the release of chemokines from damaged myofibrils [15]. Chemokines enter the circulation and recruit inflammatory cells, which infiltrate skeletal muscle and release chemical mediators, such as bradykinins and prostaglandins. Bradykinins and prostaglandins act as signaling mechanisms by stimulating muscle fibers to synthesize neural growth factor (NGF) and glial derived neutrophil factor (GDNF), which are capable of stimulating nociceptors III and IV [54,57,58]. The bradykinins release can even occur in the absence of muscle cell damage and inflammation [58]. Alternatively, eccentric muscle contractions can cause high compressive forces within the muscle spindle, generating microdamage in type II afferent neurons that are also related to DOMS [59,60]. Another mechanism related to pain stimuli involves adenosine receptors. Those receptors are mainly regulated by ATP metabolism [61]. Adenosine levels increase in muscle and plasma during muscle contraction [62]. After eccentric exercise, the adenosine receptor 1 (A1) gene expression also increases, reaching approximately six-fold in skeletal muscle [63]. A1 receptors are involved nociception and pain processing located in several neural tissues, including the peripheral afferent nerves at the spinal dorsal horn level, as well as central areas, such as the brain cortex, cerebellum, and hippocampus [64]. The analgesic effect of caffeine may be related to its action as a non-selective adenosine antagonist blocking the pain perception, which is propagated from peripheral nerves to the central nervous system [30,34,55]. 4.2. Muscle Strength Assessment Measurements of maximum voluntary contraction are considered the best method to identify muscle damage, as it is directly related to the magnitude and change in the temporal course that occurs after the injury [50]. Despite this, our review identified only four studies (28%) that investigated the effects of caffeine on changes in MVIC after muscle injury. Chen et al. [27] performed a downhill running protocol on a motorized treadmill at 70% of VO2 max for 30 min with 10 male and 10 female athletes. Participants received a 6 mg·kg−1 bodyweight of caffeine or placebo 24 or 48 h after the EIMD protocol. Knee extensor MVIC, pain perception and blood CK levels were used as muscle injury markers. As hypothesized, there were reductions in knee extensor MVIC 24 and 48 h after the exercise protocol. Furthermore, caffeine-supplemented group also presented 10.2% of attenuation in MVIC loss 48 h after EIMD when compared to placebo ingestion. Green et al. [33] evaluated the effect of caffeine supplementation (6 mg·kg−1) under two conditions: (a) muscle uninjured; (b) muscle injured. The sample consisted of eight men and eight women. Muscle damage was assessed using the pain perception scale (1–100 points) and two maximum strength tests using an isokinetic dynamometer: MVIC and maximum voluntary dynamic contraction (MVDC). In the muscle injured condition, muscle damage was induced by 100 eccentric quadriceps contractions and reassessed 24 h after exercise. As expected, in the muscle injured condition, reductions in strength performance were observed in both tests. The caffeine group had a smaller reduction in MVDC (−9.4%) when compared to the placebo group, but no difference was observed in the MVIC test. Similarly, in the muscle uninjured condition, caffeine ingestion did not improve MVIC test, but MVDC was improved by 6.8%. These results suggest that caffeine supplementation after an EIMD protocol results in the attenuation of dynamic strength loss after EIMD and increases dynamic strength performance in no injured muscle. However, isometric strength was not affected by caffeine supplementation in neither condition. Another study [29] investigated the effect of caffeine supplementation (6 mg·kg−1) under two conditions, muscle uninjured and muscle injured. Participants performed 50 eccentric quadriceps contractions to induce muscle damage and MVIC was assessed 24 and 48 h after this protocol. MVIC performance was decreased during this period, but no differences were observed between caffeine and placebo conditions. When no EIMD was induced, caffeine resulted in a 10.4% improvement in MIVC performance and a 6.2% increase in muscle activation compared to placebo. In contrast to Green et al. [33], this study suggested that the positive effect of caffeine supplementation on MVIC only occurs in muscle without EIMD. Maridakis et al. [30] investigated the effect of pre- and post-exercise caffeine supplementation (5 mg·kg−1), with a muscle damage induction protocol of 64 eccentric quadriceps contractions, performed by 10 women with no experience in resistance training. Muscle damage was assessed by pain perception (0–100 point scale) and quadriceps MVIC test performed 24 and 48 h after exercise. A decrease in MVIC after EIMD was observed but with no differences in strength and pain perception between caffeine and placebo conditions. Taken together, the studies on the effect of caffeine on strength recovery after muscle injury have conflicting results. Two studies observed positive effects of caffeine supplementation after muscle damage but used different strength assessment methods (MVIC [27] or MVDC [33]). When analyzing the effect of caffeine ingestion after the EIMD protocol (supplementation post-EIMD) using isometric strength testing, three studies indicate that caffeine does not attenuate strength loss caused by muscle damage [29,30,33]. In the condition of uninjured muscle (supplementation without EIMD), a larger set of studies has observed that supplementation with caffeine enhances strength performance in different types of dynamic tests (e.g., maximal or submaximal isokinetic, 1 RM, vertical jump) [65,66]. The mechanisms involved in the decrease of strength performance after muscle damage seem to be related to impaired excitation–contraction coupling caused by disruptions that occur in the sarcoplasmic reticulum, transverse tubules, and sarcolemma [67]. On the other hand, caffeine could have positive effects on strength and power activities due to increased recruitment of motor units and improved excitation–contraction coupling [33,62]. Studies using high doses of caffeine in skeletal muscle cells isolated from an animal model observed direct effects, such as (1) increased calcium mobilization from the sarcoplasmic reticulum; (2) greater direct sensitivity to calcium in skeletal muscle; (3) modifications in Na+/K+ ATPase activity [68,69]. Caffeine concentrations used in cell culture studies are considered toxic when extrapolated to human studies [27,62,70]. However, it was demonstrated that micromolar concentrations of caffeine can result in a small but significant enhancement in power output (3–6%) in isolated mouse skeletal muscles [68]. In humans, blood caffeine concentrations reaches 10 to 70 uM after the ingestion of 3–9 mg·kg−1 [71]. Based on the available data, the possibility of a direct effect of caffeine on skeletal muscle (damaged or intact) with doses commonly used in studies employing human participants cannot be discarded. Therefore, a possible mechanism for the effects of caffeine on the recovery of muscle function following EIMD is the attenuation of the impaired excitation–contraction coupling after the muscle damage by its direct action on skeletal muscle increasing calcium sensitivity, and also attenuating extracellular K+ accumulation due to increased Na+/K+ ATPase activity in skeletal muscle. Another suggested mechanism is the effect of caffeine on the CNS reducing pain perception (see topic Section 4.1). It is well accepted that nociceptive stimuli reduces motor cortical excitability [27,72]. Chen et al. [27], for example, observed an inverse correlation between muscle pain intensity and strength production capacity. In addition, caffeine supplementation contributed to pain relief and strength recovery after muscle injury. However, this evidence was not confirmed by other studies, such as Maridakis et al. [30]. After muscle damage, authors observed a reduction in pain perception in individuals treated with caffeine; however, it was not enough to attenuate MVIC strength losses. Green et al. [33] observed greater recovery of MVDC in the caffeine group, although the pain perception was not different between the caffeine and placebo groups. Therefore, it remains only speculative that pain may interfere with the ability to produce force and some evidence suggests that damaged muscles could be fully active regardless of the muscle pain existence [51,73]. 4.3. Blood Markers of Muscle Damage The presence of muscle proteins and enzyme fragments in the bloodstream is indicative of muscle damage [51]. Muscle injury is characterized by damage to the extracellular matrix resulting in loss of sarcoplasmic membrane integrity, allowing muscle proteins to leak from the cell into the circulation, such as CK, hemoglobin, LDH, and several others [24,51,74]. Although several muscle proteins can be used as indirect injury markers, CK has received more attention, once the magnitude of its increment is larger relative to other proteins and the cost of the assay is comparatively lower [51]. For example, in this review, nine studies that used blood markers, used at least CK as one of the markers of muscle damage. However, despite being widely used in studies, the use of blood CK as an indirect marker of muscle damage is controversial and is not necessarily related to the magnitude of structural damage in skeletal muscle cells. For example, Fielding et al. [75] observed no relationship between blood CK levels and Z-Band ultrastructural damage after eccentric contractions of the quadriceps muscle. Additionally, the authors observed a greater increase in CK in the group that received fluid and electrolytes replacement during exercise, demonstrating that the hydration level can influence the CK response to the same exercise protocol. In addition, other factors such as gender and age can also influence plasma CK concentrations, as discussed by Baird et al. [76]. Therefore, the results of studies that used blood markers of muscle damage, such as CK, should be interpreted with caution. The effect of caffeine on markers of muscular damage in the bloodstream is still poorly understood, and some studies suggest that it could increase the inflammatory response due to its antagonistic action on adenosine receptors. By binding to A2A and A2B receptors on immune system cells, adenosine inhibits their activity, reducing the inflammatory cells infiltration and the pro-inflammatory cytokines expression [77]. Caffeine ingestion could abrogate adenosine receptor signaling and increase the acute inflammatory response contributing to increased muscle damage [32,77]. Nine studies investigated the effect of caffeine supplementation on muscle damage, with eight studies using a single dose before the EIMD protocol, and only one study providing caffeine on several moments after muscle damage induction [34]. In six studies, no differences in circulating levels of CK or LDH were observed between caffeine and placebo conditions (five with pre-EIMD supplementation and one post-EIMD). Only three studies observed differences between conditions, all providing a single caffeine dose prior to EIMD. Bassini-Cameron et al. [32] and Stadheim et al. [39] observed a higher CK level in the caffeine group, while Ferreira et al. [28] observed the opposite. To induce muscle damage, these last three studies used maximum effort exercise protocols (all-out type), which do not allow equalizing the work volume between groups. Therefore, the circulating CK level may be related to the greater work performance during the test and not to the direct effect of supplementation in inducing muscle damage. For example, in the study of Stadheim et al. [39], the highest CK levels in the caffeine groups were accompanied by the greater volume of work performed by the caffeine group. The other two studies, Bassini-Cameron et al. [32] and Ferreira et al. [28], did not report whether there was a difference between groups for workload in the Yo-Yo test or in the repeated sprints test on the cycle ergometer, respectively. Taken together, the research does not appear to demonstrate that caffeine supplementation results in increased muscle damage after an exercise bout, but due to a limited number of studies, future research is needed to better clarify this issue. However, caffeine may modulate the anti-inflammatory response. It was demonstrated that acute supplementation of 6 mg·kg−1 of caffeine before completing a 15 km race improves the anti-inflammatory response indicated by increases in plasma levels of IL-6 and IL-10 [78]. This finding is particularly interesting and could explain a possible protective effect on injured skeletal muscle. The EIMD is divided into two phases, the first characterized by the result of eccentric muscle actions causing damage to the muscle fiber and cellular matrix. The second phase is characterized by activation of proteolytic pathways mediated by Ca2+, migration of inflammatory cells to the injured site, and production of reactive oxygen species that contribute to further increase muscle damage [24,56]. In a study with an animal model, it was observed that attenuating the inflammatory process related to the second phase of muscle damage with the use of non-steroidal anti-inflammatory drugs improves recovery from EIMD, with an attenuation of strength deficit following an eccentric contraction protocol [79]. Therefore, future studies should investigate whether caffeine could have similar anti-inflammatory effects and could contribute to reducing secondary muscle damage. 4.4. Methodological Considerations Based on the PEDro scale, 12 studies (86%) received the maximum score (10 points) and only 2 studies (14%) received a score between 8 and 9 points; therefore, all included studies, according to the scale, are classified as good or excellent [5,44]. Other important methodological issues affecting study results are highlighted in Table 2, including participants’ average caffeine consumption history, type of study design, muscle damage induction protocol, and supplementation protocol. Regarding the methodological design, 3 studies opted for a design with parallel groups (independent samples) while the majority (11 studies) used a cross-over design (dependent samples). The parallel-type design has some disadvantages, for example, it has been observed that subjects undergoing the same muscle damage protocol respond differently. Lower responders reduce MVC test by 18.5%, while higher responders lose muscle MVC strength by 57.8% [23]. Individual variability has also been observed for the effect of caffeine supplementation on performance [80]. Cross-over designs may be more useful to reduce individual variability observed both related to muscle damage and caffeine. For specific studies that used the cross-over design, the wash-out period between the two conditions tested could also affect the results. Two of them used relatively short intervals between conditions (caffeine or placebo) (between 24 and 48 h). Although the caffeine effect had a short half-life (4 to 6 h), the duration of muscle damage effects could last for several days [15,23,81]. The investigation of these two factors in a short period of time could generate misleading results. For example, if the investigation of pain perception in the caffeine condition was carried out 48 h after exercise and the followed placebo experimental condition, without correct washout, it is possible that an increased pain perception will not be directly related to the supplementation condition, but rather to the pain perception evolution peak, which usually occurs between 48 and 72 h after muscle damage. To avoid this, it would be necessary to ensure complete recovery of muscle injury markers before subjecting them to a second condition. Regarding the supplementation protocol, the dose used ranged from 3 to 7.5 mg/kg of body weight, which corresponds to the dosage widely used in the literature with positive effects on sports performance [9]. The majority, nine studies (64%) investigated the effect of supplementation for a short period of time (<24 h after muscle injury), while only five studies (36%) investigated the effect for a longer period than 48 h after muscle injury. Considering that, the effects of muscle injury could last for longer periods (7 days), longer-term studies in the monitoring of muscle injury markers should be recommended to investigate the effect of caffeine on muscle recovery. To avoid bias factors, the muscle damage induction protocol must also ensure the volume and intensity equalization for both groups evaluated. Some studies used exercise protocols that did not guarantee this equalization. Caldwell et al. [25] used a time trial as test; Bassini-Cameron et al. [32] tested the volunteers until fatigue, and some studies performed a maximal effort test [28,37,38,39]. In all of these uncontrolled studies, there exist the possibility of one of the groups exerting greater effort during the test than the other group, leading to a further higher muscle injury level, masking the effect of supplementation on muscle recovery. In addition, five of those studies performed supplementation with caffeine in the pre-exercise moment, which could contribute to higher performance of the caffeine groups during the test and higher levels of muscle damage. 4.5. Limitations and Future Perspectives In this systematic review, 14 studies were found that evaluated the effect of caffeine on indirect muscle damage markers. It is worth mentioning that indirect muscle damage markers present limitations and significant differences on magnitude and time course responses among them [50,51]. Other limitations when using indirect markers include: (1) although DOMS is often used as a marker of muscle damage, it can occur independently of the EIMD, and may even manifest in the absence of muscle damage [58]. (2) The use of blood activity of muscle enzymes to assess muscle damage is controversial. For example, it has been observed that serum CK concentrations after muscle damage are not correlated with other injury markers, such as muscle strength and DOMS [82] and, therefore, CK could be more useful as a qualitative marker of skeletal muscle trauma rather than a quantitative indicator of the extent of muscle damage [83]. (3) Maximum voluntary contraction peak torque is considered the best method to assess EIMD [50], but was used in only four studies. In addition, these studies presented controversial results possibly due to different strength assessment methods used. Furthermore, it is unclear whether the effect of caffeine on muscle strength recovery observed in some studies [27,33] was due to a protective effect against muscle damage, involving as yet unknown mechanisms of action. Most likely, caffeine ingestion results in strength loss attenuation following EIMD due to its ergogenic effects as discussed herein. Therefore, future studies using direct and indirect markers and different types of strength tests (isometric/dynamic) may contribute to understanding the role of caffeine in the prevention of damage and in the recovery of symptoms related to muscle damage. Another important consideration is related to the timing of caffeine ingestion. It is possible to consider two hypotheses for caffeine supplementation (which may even occur simultaneously). The first is that caffeine ingestion before an EIMD protocol could attenuate the occurrence of muscle damage. Another hypothesis is that the use of caffeine after a muscle damaging protocol could contribute to a better recovery from muscle damage, improving contractile function. Further studies should specifically address these issues to better understand the application of caffeine supplementation in EIMD. Few studies investigated the effect of prolonged caffeine supplementation during the muscle recovery phase. Ideally, a well-designed study would constantly follow-up the groups throughout at least 7 days after the muscle injured, since the pain and blood CK levels might peak between 48 and 72 h after the EIMD protocol. Furthermore, the experiments might also need to account for the volume and intensity of the muscle damage protocol and for this, the trial must be extremely well applied, ideally equalizing total work performed during the muscle damage inducing exercise protocol. The effects of chronic caffeine supplementation and its effects on EIMD and recovery may also be an important area of focus for future. A study with rats demonstrated that chronic caffeine supplementation (1 mg·mL−1 diluted in tap water) for 30 days resulted in lower blood CK activity, fewer damaged muscle cells, and a lower amount of inflammatory cells in both sedentary and trained animals after the last exercise session [84]. Furthermore, 4 weeks of coffee consumption in mice prior to injury induced by cardiotoxin has been shown to increase muscle regenerative capacity, which has been attributed to cell proliferation marker Ki67 and an increased quantity of embryonic myosin heavy chain, a marker of immature myotubes [85]. Whilst the results of previous work are promising, they should be interpreted with caution given that these findings have only been demonstrated in animal models. In addition, coffee contains several other substances in addition to caffeine, such as chlorogenic acids, which may contribute the effects independent of caffeine. Moreover, muscle damage was induced by cardiotoxin injection, which differs in magnitude of muscle damage when compared to EIMD. Whether caffeine is able to acutely stimulate satellite cells proliferation and assist in the regeneration process after EIMD is still a matter of speculation and should be further investigated. This review also highlights some methodological issues that should be considered in future studies, such as better methodological control of the study quality by PEDro scale, standardizing the caffeine treatment dose and, when possible, optimizing and opting for the cross-over experimental design with a longer wash-out period, allowing a complete reestablishment of the total body homeostasis between test conditions. 5. Conclusions The present systematic review found 14 studies that evaluated the effect of caffeine on indirect muscle damage markers, including blood markers, pain perception, and strength performance. Of the nine studies using blood markers, six indicated that caffeine administered pre (five studies) or post (one study) an EIMD protocol does not cause more muscle damage, considering CK circulating levels, but this should be interpreted with caution due to the limitations of using CK as a marker of muscle damage, as discussed herein. Caffeine ingestion may result in lower pain perception (as shown in four of six studies included in this systematic review). The effects of caffeine on muscle strength following EIMD is still inconclusive, due to the limited number of studies and conflicting results. The limited and controversial evidence prevents accurate conclusions regarding the effects of acute caffeine consumption on the attenuation of muscle damage when used prior to an EIMD protocol. Caffeine consumed following EIMD however may acutely relieve some symptoms, attenuating pain perception and potentially increasing strength. Based on the current review and on its well described ergogenic effects, caffeine supplementation may be a valid strategy for athletes who need to recover between strenuous training sessions or competitions. Author Contributions Conceptualization, All authors; literature search, L.C.C. and R.B.S.; data analysis, L.C.C. and L.G.-F.; writing—original draft preparation, All authors; writing—review and editing, All authors. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available upon request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Procedure for selection of the studies and decision-marking inclusion and exclusion. nutrients-14-01769-t001_Table 1 Table 1 Characteristics of the studies and main results. Study Training Status Sample Age Caffeine Consumption Study Design Muscle Damage Protocol Supplementation Protocol Findings (Caf × Pla) Caldwell et al. [25] Recreational cyclists n = 30; 46 ± 11 ~230 mg/day 2 parallel groups 164 km of cycling 2 daily doses for 4 days after (8 doses of 3 mg/kg) ↓DOMS in Caffeine group 24 h after EIMD. (25M; 5F) (Caf; Pla) Cameron et al. [32] Soccer athletes n = 22M 26–31 Non described 3 parallel groups VDR + Yo-Yo IRT pre-exercise ↑∆CK in Caffeine group; No difference between groups for CKMB and LDH. (Caf; Pla; Con) (1 dose of 5 mg/kg) Chen et al. [27] College athletes n = 20; M = 21.1 ± 1.1; F = 20.4 ± 1.2 <200 mg/wk Crossover Downhill running 24 h or 48 h post-exercise ↑recovery of MVIC and ↓ DOMS in Caffeine group 48 h after EIMD. (10M; 10F) (After 24 h) (30-min) (1 dose of 6 mg/kg) Ferreira et al. [28] Physically active n = 20M 25.2–26.2 ±72 mg/day 2 parallel groups 13 × 30 s sprint standard bicycle Pre-exercise ↑CK 24 and 48 h after EIMD in Placebo group. (Caf; Pla) (1 dose of 5 mg/kg) Green et al. [33] Physically active n = 16 24.3 ± 4.3 Usual consumers Crossover Eccentric contraction Pre, 24 h post-exercise ↑MVDC in Caffeine group; No difference between groups for DOMS and MVIC. (8M; 8F) (After 1 week) (Quadriceps) (2 doses of 6 mg/kg) Hurley et al. [34] Resistance-trained n = 12M 20 ± 1 Low consumers Crossover Eccentric contraction Pre, 24–120 h post-exercise ↓DOMS on the 2–3 day in Caffeine group; No difference between groups for CK. (After 1 week) (Elbow flexors) (6 doses of 5 mg/kg) Kazman et al. [35] Non described n = 35 27,2 ± 8 Non described Crossover 60-min walking and Pre-exercise No difference between groups for CK. (29M; 6F) (After 1 week) 5-min step/squat (1 dose of 7.5 mg/kg) Machado et al. [36] Soccer athletes n = 15M 18.4 ± 0.8 <100 mg/day Crossover Full body strength session Pre-exercise No difference between groups for CK and LDH. (After 1 week) (1 dose of 4.5 mg/kg) Mahdavi et al. [37] Basketball athletes n = 26F 24.22 ± 2.65 116.88 mg/day Crossover Wingate test Pre-exercise No difference between groups for CK, MDA, and TAC (After 1 week) (30-sec) (1 dose of 5 mg/kg) Maridakis et al. [30] No experience Strength training n = 10F 21.3 ± 1.6 55.1 ± 30.9 mg/day Cross-over Eccentric contraction (Quadriceps) Pre, 24 h or 48 h post-exercise ↓DOMS in Caffeine group; No difference between groups for MVIC. (After 24 h or 48 h) (2 doses of 5 mg/kg) Ribeiro et al. [38] Handball athletes n = 6M 21.6 ± 2.9 ~60 mg/day Cross-over Vertical jumps Pre-exercise ↑vertical jump in Caffeine group; no difference between groups for CK and LDH. (After 1 week) (4 sets of 30-sec) (1 dose of 6 mg/kg) Stadheim et al. [39] Elite cross-country skiers n = 8M 20,0 ± 1,0 <150 mg/day Cross-over Double poling ergometer (10-min) 1 dose pre-exercise ↑test performance, ↑CK, ↑DOMS in Caffeine groups (3 mg/kg–4.5 mg/kg) (After 6 days) (3 mg/kg or 4.5 mg/kg) Park et al. [29] Non described n = 13 25.5 ± 3.3 213 ± 151 mg/day Cross-over Eccentric contraction (Quadriceps) 24–48 h post-exercise No difference between groups for MVIC. (4M; 9F) (After 2 week) (2 doses of 6 mg/kg) Vimercatt et al. [40] Physically active n = 15M 19 ± 1 Non described Cross-over Treadmill running 1 dose pre-exercise No difference between groups for CK, LDH, ALT, and AST. (After 2 week) (60-min) (4.4 mg/kg or 5.5 mg/kg) ALT = alanine aminotransferase; AST = aspartate aminotransferase; Caf = caffeine Group; CK = creatine kinase; CKMB = creatine kinase MB isoform; DOMS = delayed onset muscle soreness; EIMD = exercise-induced muscle damage; F = female; LDH = lactate dehydrogenase; M = male; MDA = malondialdehyde; MVDC = maximum voluntary dynamic contraction; MVIC = maximum voluntary isometric contraction; n = sample size; Pla = placebo group; TAC = total antioxidant capacity; VDR = variable distance run protocol; YoYo IRT = Yo-Yo intermittent recovery test; ↓ = statistically significant decrease; ↑ = statistically significant increase. nutrients-14-01769-t002_Table 2 Table 2 Assessment of the methodological quality of studies using the PEDro scale. Study Criteria PEDro Score 1* 2 3 4 5 6 7 8 9 10 11 Caldwell et al. [25] 1 1 1 1 1 1 1 1 1 1 1 10 Cameron et al. [32] 0 1 1 1 1 1 1 0 0 1 1 8 Chen et al. [27] 1 1 1 1 1 1 1 1 1 1 1 10 Ferreira et al. [28] 0 1 1 1 1 1 1 1 1 1 1 10 Green et al. [33] 1 1 1 1 1 1 1 1 1 1 1 10 Hurley et al. [34] 0 1 1 1 1 1 1 1 1 1 1 10 Kazman et al. [35] 1 1 1 1 1 1 1 1 1 1 1 10 Machado et al. [36] 0 1 1 1 1 1 1 1 1 1 1 10 Mahdavi et al. [37] 0 1 1 1 1 1 1 1 1 1 1 10 Maridakis et al. [30] 1 1 1 0 1 1 1 1 1 1 1 9 Ribeiro et al. [38] 0 1 1 1 1 1 1 1 1 1 1 10 Stadheim et al. [39] 0 1 1 1 1 1 1 1 1 1 1 10 Park et al. [29] 1 1 1 1 1 1 1 1 1 1 1 10 Vimercatt et al. [40] 0 1 1 1 1 1 1 1 1 1 1 10 Criteria 1* = the eligibility criterion is not scored for being related to external validity and, therefore, does not reflect the quality dimensions assessed by the PEDro Scale. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Doherty M. Smith P.M. Effects of Caffeine Ingestion on Exercise Testing: A Meta-Analysis Int. J. Sport Nutr. Exerc. Metab. 2004 14 626 646 10.1123/ijsnem.14.6.626 15657469 2. Southward K. Rutherfurd-Markwick K.J. Ali A. The Effect of Acute Caffeine Ingestion on Endurance Performance: A Systematic Review and Meta–Analysis Sports Med. 2018 48 1913 1928 10.1007/s40279-018-0939-8 29876876 3. Grgic J. Trexler E.T. Lazinica B. Pedisic Z. Effects of caffeine intake on muscle strength and power: A systematic review and meta-analysis J. Int. Soc. Sports Nutr. 2018 15 11 10.1186/s12970-018-0216-0 29527137 4. Warren G.L. Park N.D. Maresca R.D. McKibans K.I. Millard-Stafford M.L. Effect of caffeine ingestion on muscular strength and endurance: A meta-analysis Med. Sci. Sports Exerc. 2010 42 1375 1387 10.1249/MSS.0b013e3181cabbd8 20019636 5. Grgic J. Caffeine ingestion enhances Wingate performance: A meta-analysis Eur. J. Sport Sci. 2018 18 219 225 10.1080/17461391.2017.1394371 29087785 6. Chvasta T.E. Cooke A.R. Emptying and absorption of caffeine from the human stomach Gastroenterology 1971 61 838 843 10.1016/S0016-5085(19)33396-7 5125686 7. Graham T.E. Spriet L.L. Metabolic, catecholamine, and exercise performance responses to various doses of caffeine J. Appl. Physiol. 1995 78 867 874 10.1152/jappl.1995.78.3.867 7775331 8. Mumford G.K. Benowitz N.L. Evans S.M. Kaminski B.J. Preston K.L. Sannerud C.A. Silverman K. Griffiths R.R. Absorption rate of methylxanthines following capsules, cola and chocolate Eur. J. Clin. Pharmacol. 1996 51 319 325 10.1007/s002280050205 9010706 9. Guest N.S. VanDusseldorp T.A. Nelson M.T. Grgic J. Schoenfeld B.J. Jenkins N.D.M. Arent S.M. Antonio J. Stout J.R. Trexler E.T. International society of sports nutrition position stand: Caffeine and exercise performance J. Int. Soc. Sports Nutr. 2021 18 1 10.1186/s12970-020-00383-4 33388079 10. Del Coso J. Muñoz G. Muñoz-Guerra J. Prevalence of caffeine use in elite athletes following its removal from the World Anti-Doping Agency list of banned substances Appl. Physiol. Nutr. Metab. 2011 36 555 561 10.1139/h11-052 21854160 11. Keane K.M. Salicki R. Goodall S. Thomas K. Howatson G. Muscle Damage Response in Female Collegiate Athletes After Repeated Sprint Activity J. Strength Cond. Res. 2015 29 2802 2807 10.1519/JSC.0000000000000961 25853920 12. Leeder J.D.C. van Someren K.A. Gaze D. Jewell A. Deshmukh N.I.K. Shah I. Barker J. Howatson G. Recovery and adaptation from repeated intermittent-sprint exercise Int. J. Sports Physiol. Perform. 2014 9 489 496 10.1123/ijspp.2012-0316 23479406 13. Twist C. Eston R.G. The effect of exercise-induced muscle damage on perceived exertion and cycling endurance performance Eur. J. Appl. Physiol. 2009 105 559 567 10.1007/s00421-008-0935-z 19023588 14. Harty P.S. Cottet M.L. Malloy J.K. Kerksick C.M. Nutritional and Supplementation Strategies to Prevent and Attenuate Exercise-Induced Muscle Damage: A Brief Review Sport. Med.-Open 2019 5 1 10.1186/s40798-018-0176-6 30617517 15. Hyldahl R.D. Hubal M.J. Lengthening our perspective: Morphological, cellular, and molecular responses to eccentric exercise Muscle Nerve 2014 49 155 170 10.1002/mus.24077 24030935 16. Faulkner J.A. Brooks S.V. Opiteck J.A. Injury to Skeletal Muscle Fibers during Contractions: Conditions of Occurrence and Prevention Phys. Ther. 1993 73 911 921 10.1093/ptj/73.12.911 8248299 17. Pokora I. Kempa K. Chrapusta S. Langfort J. Effects of downhill and uphill exercises of equivalent submaximal intensities on selected blood cytokine levels and blood creatine kinase activity Biol. Sport 2014 31 173 178 10.5604/20831862.1111434 25177094 18. Nosaka K. Newton M. Sacco P. Muscle damage and soreness after endurance exercise of the elbow flexors Med. Sci. Sports Exerc. 2002 34 920 927 10.1097/00005768-200206000-00003 12048316 19. Vijayan K. Thompson J.L. Norenberg K.M. Fitts R.H. Riley D.A. Fiber-type susceptibility to eccentric contraction-induced damage of hindlimb-unloaded rat AL muscles J. Appl. Physiol. 2001 90 770 776 10.1152/jappl.2001.90.3.770 11181582 20. Chapman D. Newton M. Sacco P. Nosaka K. Greater muscle damage induced by fast versus slow velocity eccentric exercise Int. J. Sports Med. 2006 27 591 598 10.1055/s-2005-865920 16874584 21. Child R.B. Saxton J.M. Donnelly A.E. Comparison of eccentric knee extensor muscle actions at two muscle lengths on indices of damage and angle-specific force production in humans J. Sports Sci. 1998 16 301 308 10.1080/02640419808559358 9663954 22. Nosaka K. Sakamoto K. Effect of elbow joint angle on the magnitude of muscle damage to the elbow flexors Med. Sci. Sports Exerc. 2001 33 22 29 10.1097/00005768-200101000-00005 11194107 23. Damas F. Nosaka K. Libardi C. Chen T. Ugrinowitsch C. Susceptibility to Exercise-Induced Muscle Damage: A Cluster Analysis with a Large Sample Int. J. Sports Med. 2016 37 633 640 10.1055/s-0042-100281 27116346 24. Howatson G. van Someren K.A. The Prevention and Treatment of Exercise-Induced Muscle Damage Sports Med. 2008 38 483 503 10.2165/00007256-200838060-00004 18489195 25. Caldwell A.R. Tucker M.A. Butts C.L. McDermott B.P. Vingren J.L. Kunces L.J. Lee E.C. Munoz C.X. Williamson K.H. Armstrong L.E. Effect of Caffeine on Perceived Soreness and Functionality Following an Endurance Cycling Event J. Strength Cond. Res. 2017 31 638 643 10.1519/JSC.0000000000001608 27552210 26. Kim J. Lee J. A review of nutritional intervention on delayed onset muscle soreness. Part I J. Exerc. Rehabil. 2014 10 349 356 10.12965/jer.140179 25610818 27. Chen H.-Y. Chen Y.-C. Tung K. Chao H.-H. Wang H.-S. Effects of caffeine and sex on muscle performance and delayed-onset muscle soreness after exercise-induced muscle damage: A double-blind randomized trial J. Appl. Physiol. 2019 127 798 805 10.1152/japplphysiol.01108.2018 31219772 28. Ferreira G.A. Felippe L.C. Bertuzzi R. Bishop D.J. Barreto E. De-Oliveira F.R. Lima-Silva A.E. The Effects of Acute and Chronic Sprint-Interval Training on Cytokine Responses Are Independent of Prior Caffeine Intake Front. Physiol. 2018 9 671 10.3389/fphys.2018.00671 29922173 29. Park N.D. Maresca R.D. McKibans K.I. Morgan D.R. Allen T.S. Warren G.L. Caffeine’s beneficial effect on maximal voluntary strength and activation in uninjured but not injured muscle Int. J. Sport Nutr. Exerc. Metab. 2008 18 639 652 10.1123/ijsnem.18.6.639 19164833 30. Maridakis V. O’Connor P.J. Dudley G.A. McCully K.K. Caffeine Attenuates Delayed-Onset Muscle Pain and Force Loss Following Eccentric Exercise J. Pain 2007 8 237 243 10.1016/j.jpain.2006.08.006 17161977 31. Higgins J.P.T. Green S. Cochrane Handbook for Systematic Reviews of Interventions 4.2.6 Higgins J.P.T. Green S. The Cochrane Library Hoboken, NJ, USA 2006 32. Bassini-Cameron A. Sweet E. Bottino A. Bittar C. Veiga C. Cameron L.-C. Effect of caffeine supplementation on haematological and biochemical variables in elite soccer players under physical stress conditions Br. J. Sports Med. 2007 41 523–530; discussion 530 10.1136/bjsm.2007.035147 17473001 33. Green M.S. Martin T.D. Corona B.T. Effect of Caffeine Supplementation on Quadriceps Performance after Eccentric Exercise J. Strength Cond. Res. 2018 32 2863 2871 10.1519/JSC.0000000000002530 29481452 34. Hurley C.F. Hatfield D.L. Riebe D.A. The effect of caffeine ingestion on delayed onset muscle soreness J. Strength Cond. Res. 2013 27 3101 3109 10.1519/JSC.0b013e3182a99477 24164961 35. Kazman J.B. Attipoe S. Kupchak B.R. Deuster P.A. Caffeine and heat have additive but not interactive effects on physiologic strain: A factorial experiment J. Therm. Biol. 2020 89 102563 10.1016/j.jtherbio.2020.102563 32364995 36. Machado M. Koch A.J. Willardson J.M. dos Santos F.C. Curty V.M. Pereira L.N. Caffeine Does Not Augment Markers of Muscle Damage or Leukocytosis Following Resistance Exercise Int. J. Sports Physiol. Perform. 2010 5 18 26 10.1123/ijspp.5.1.18 20308693 37. Mahdavi R. Daneghian S. Homayouni A. Jafari A. Effects of caffeine supplementation on oxidative stress, exercise-induced muscle damage and leukocytosis Pharm. Sci. 2012 18 177 182 38. Ribeiro B.G. Morales A.P. Sampaio-Jorge F. Barth T. De Oliveira M.B.C. Coelho G.M.D.O. Leite T.C. Caffeine Attenuates Decreases in Leg Power Without Increased Muscle Damage J. Strength Cond. Res. 2016 30 2354 2360 10.1519/JSC.0000000000001332 26808856 39. Stadheim H.K. Spencer M. Olsen R. Jensen J. Caffeine and performance over consecutive days of simulated competition Med. Sci. Sports Exerc. 2014 46 1787 1796 10.1249/MSS.0000000000000288 25134002 40. Vimercatti N.S. Zovico P.V.C. Carvalho A.S. Barreto J.G. Machado M. Two doses of caffeine do not increase the risk of exercise-induced muscle damage or leukocytosis Phys. Educ. Sport 2008 52 96 99 10.2478/v10030-008-0022-6 41. de Morton N.A. The PEDro scale is a valid measure of the methodological quality of clinical trials: A demographic study Aust. J. Physiother. 2009 55 129 133 10.1016/S0004-9514(09)70043-1 19463084 42. Maher C.G. Sherrington C. Herbert R.D. Moseley A.M. Elkins M. Reliability of the PEDro scale for rating quality of randomized controlled trials Phys. Ther. 2003 83 713 721 10.1093/ptj/83.8.713 12882612 43. Tooth L. McCluskey A. Hoffmann T. McKenna K. Lovarini M. Appraising the quality of randomized controlled trials: Inter-rater reliability for the OTseeker evidence database J. Eval. Clin. Pract. 2005 11 547 555 10.1111/j.1365-2753.2005.00574.x 16364108 44. Mielgo-Ayuso J. Calleja-Gonzalez J. Del Coso J. Urdampilleta A. León-Guereño P. Fernández-Lázaro D. Caffeine supplementation and physical performance, muscle damage and perception of fatigue in soccer players: A systematic review Nutrients 2019 11 440 10.3390/nu11020440 30791576 45. Chia J.S. Barrett L.A. Chow J.Y. Burns S.F. Effects of Caffeine Supplementation on Performance in Ball Games Sports Med. 2017 47 2453 2471 10.1007/s40279-017-0763-6 28741186 46. Astorino T.A. Roberson D.W. Efficacy of Acute Caffeine Ingestion for Short-term High-Intensity Exercise Performance: A Systematic Review J. Strength Cond. Res. 2010 24 257 265 10.1519/JSC.0b013e3181c1f88a 19924012 47. Ganio M.S. Klau J.F. Casa D.J. Armstrong L.E. Maresh C.M. Effect of Caffeine on Sport-Specific Endurance Performance: A Systematic Review J. Strength Cond. Res. 2009 23 315 324 10.1519/JSC.0b013e31818b979a 19077738 48. Machado M. Zovico P.V.C. Paulúcio D. Pereira L.N. Barreto J.G. Pereira R. Caffeine does not increase resistance exercise-induced microdamage J. Exerc. Sci. Fit. 2008 6 115 120 49. Filip A. Wilk M. Krzysztofik M. Del Coso J. Inconsistency in the Ergogenic Effect of Caffeine in Athletes Who Regularly Consume Caffeine: Is It Due to the Disparity in the Criteria That Defines Habitual Caffeine Intake? Nutrients 2020 12 1087 10.3390/nu12041087 50. Warren G.L. Lowe D.A. Armstrong R.B. Measurement tools used in the study of eccentric contraction-induced injury Sports Med. 1999 27 43 59 10.2165/00007256-199927010-00004 10028132 51. Clarkson P.M. Hubal M.J. Exercise-induced muscle damage in humans Am. J. Phys. Med. Rehabil. 2002 81 S52 S69 10.1097/00002060-200211001-00007 12409811 52. Nosaka K. Newton M. Sacco P. Delayed-onset muscle soreness does not reflect the magnitude of eccentric exercise-induced muscle damage Scand. J. Med. Sci. Sports 2002 12 337 346 10.1034/j.1600-0838.2002.10178.x 12453160 53. Paulsen G. Mikkelsen U.R. Raastad T. Peake J.M. Leucocytes, cytokines and satellite cells: What role do they play in muscle damage and regeneration following eccentric exercise? Exerc. Immunol. Rev. 2012 18 42 97 22876722 54. Hody S. Croisier J.-L. Bury T. Rogister B. Leprince P. Eccentric Muscle Contractions: Risks and Benefits Front. Physiol. 2019 10 536 10.3389/fphys.2019.00536 31130877 55. Sawynok J. Adenosine receptor targets for pain Neuroscience 2016 338 1 18 10.1016/j.neuroscience.2015.10.031 26500181 56. Bongiovanni T. Genovesi F. Nemmer M. Carling C. Alberti G. Howatson G. Nutritional interventions for reducing the signs and symptoms of exercise-induced muscle damage and accelerate recovery in athletes: Current knowledge, practical application and future perspectives Eur. J. Appl. Physiol. 2020 120 1965 1996 10.1007/s00421-020-04432-3 32661771 57. Cheung K. Hume P. Maxwell L. Delayed onset muscle soreness: Treatment strategies and performance factors Sports Med. 2003 33 145 164 10.2165/00007256-200333020-00005 12617692 58. Mizumura K. Taguchi T. Delayed onset muscle soreness: Involvement of neurotrophic factors J. Physiol. Sci. 2016 66 43 52 10.1007/s12576-015-0397-0 26467448 59. Sonkodi B. Delayed Onset Muscle Soreness (DOMS): The Repeated Bout Effect and Chemotherapy-Induced Axonopathy May Help Explain the Dying-Back Mechanism in Amyotrophic Lateral Sclerosis and Other Neurodegenerative Diseases Brain Sci. 2021 11 108 10.3390/brainsci11010108 33467407 60. Sonkodi B. Berkes I. Koltai E. Have we looked in the wrong direction for more than 100 years? Delayed onset muscle soreness is, in fact, neural microdamage rather than muscle damage Antioxidants 2020 9 212 10.3390/antiox9030212 61. Latini S. Pedata F. Adenosine in the central nervous system: Release mechanisms and extracellular concentrations J. Neurochem. 2001 79 463 484 10.1046/j.1471-4159.2001.00607.x 11701750 62. Davis J.M. Zhao Z. Stock H.S. Mehl K.A. Buggy J. Hand G.A. Central nervous system effects of caffeine and adenosine on fatigue Am. J. Physiol. Regul. Integr. Comp. Physiol. 2003 284 R399 R404 10.1152/ajpregu.00386.2002 12399249 63. Chen Y.-W. Hubal M.J. Hoffman E.P. Thompson P.D. Clarkson P.M. Molecular responses of human muscle to eccentric exercise J. Appl. Physiol. 2003 95 2485 2494 10.1152/japplphysiol.01161.2002 12937035 64. Ribeiro J.A. Sebastião A.M. de Mendonça A. Adenosine receptors in the nervous system: Pathophysiological implications Prog. Neurobiol. 2002 68 377 392 10.1016/S0301-0082(02)00155-7 12576292 65. Grgic J. Grgic I. Pickering C. Schoenfeld B.J. Bishop D.J. Pedisic Z. Wake up and smell the coffee: Caffeine supplementation and exercise performance-an umbrella review of 21 published meta-analyses Br. J. Sports Med. 2020 54 681 688 10.1136/bjsports-2018-100278 30926628 66. Grgic J. Mikulic P. Schoenfeld B.J. Bishop D.J. Pedisic Z. The Influence of Caffeine Supplementation on Resistance Exercise: A Review Sport. Med. 2019 49 17 30 10.1007/s40279-018-0997-y 67. Morgan D.L. Allen D.G. Early events in stretch-induced muscle damage J. Appl. Physiol. 1999 87 2007 2015 10.1152/jappl.1999.87.6.2007 10601142 68. Tallis J. Duncan M.J. James R.S. What can isolated skeletal muscle experiments tell us about the effects of caffeine on exercise performance? Br. J. Pharmacol. 2015 172 3703 3713 10.1111/bph.13187 25988508 69. Lamb G.D. Cellini M.A. Stephenson D.G. Different Ca2+ releasing action of caffeine and depolarisation in skeletal muscle fibres of the rat J. Physiol. 2001 531 715 728 10.1111/j.1469-7793.2001.0715h.x 11251053 70. Davis J.K. Green J.M. Ergogenic Value and Mechanisms of Action Sport. Med. 2009 39 813 832 10.2165/11317770-000000000-00000 71. Graham T.E. Caffeine and exercise: Metabolism, endurance and performance Sports Med. 2001 31 785 807 10.2165/00007256-200131110-00002 11583104 72. Proske U. Weerakkody N. Percival P. Morgan D. Gregory J. Canny B. Force-matching errors after eccentric exercise attributed to muscle soreness Clin. Exp. Pharmacol. Physiol. 2003 30 576 579 10.1046/j.1440-1681.2003.03880.x 12890182 73. Newham D.J. Jones D.A. Clarkson P.M. Repeated high-force eccentric exercise: Effects on muscle pain and damage J. Appl. Physiol. 1987 63 1381 1386 10.1152/jappl.1987.63.4.1381 3693172 74. Clarkson P.M. Sayers S.P. Etiology of Exercise-Induced Muscle Damage Can. J. Appl. Physiol. 1999 24 234 248 10.1139/h99-020 10364418 75. Fielding R.A. Violan M.A. Svetkey L. Abad L.W. MManfredi T.J. Cosmas A. Bean J. Effects of prior exercise on eccentric exercise-induced neutrophilia and enzyme release Med. Sci. Sports Exerc. 2000 32 359 364 10.1097/00005768-200002000-00015 10694117 76. Baird M.F. Creatine-Kinase-and Exercise-Related Muscle Damage Implications for Muscle Performance and Recovery J. Nutr. Metab. 2012 2012 960363 10.1155/2012/960363 22288008 77. Hatfield S. Belikoff B. Lukashev D. Sitkovsky M. Ohta A. The antihypoxia-adenosinergic pathogenesis as a result of collateral damage by overactive immune cells J. Leukoc. Biol. 2009 86 545 548 10.1189/jlb.0908577 19564571 78. Tauler P. Martínez S. Moreno C. Monjo M. Martínez P. Aguiló A. Effects of caffeine on the inflammatory response induced by a 15-km run competition Med. Sci. Sports Exerc. 2013 45 1269 1276 10.1249/MSS.0b013e3182857c8a 23299767 79. Lapointe B.M. Frenette J. Côté C.H. Lengthening contraction-induced inflammation is linked to secondary damage but devoid of neutrophil invasion J. Appl. Physiol. 2002 92 1995 2004 10.1152/japplphysiol.00803.2001 11960950 80. Guest N. Corey P. Vescovi J. El-Sohemy A. Caffeine, CYP1A2 Genotype, and Endurance Performance in Athletes Med. Sci. Sports Exerc. 2018 50 1570 1578 10.1249/MSS.0000000000001596 29509641 81. Laumonier T. Menetrey J. Muscle injuries and strategies for improving their repair J. Exp. Orthop. 2016 3 15 10.1186/s40634-016-0051-7 27447481 82. Margaritis I. Tessier F. Verdera F. Bermon S. Marconnet P. Muscle enzyme release does not predict muscle function impairment after triathlon J. Sports Med. Phys. Fit. 1999 39 133 139 83. Koch A.J. Pereira R. Machado M. The creatine kinase response to resistance exercise J. Musculoskelet. Neuronal Interact. 2014 14 68 77 24583542 84. Santos V.B.C. Ruiz R.J. Vettorato E.D. Nakamura F.Y. Juliani L.C. Polito M.D. Siqueira C.C.M. Ramos S.P. Effects of chronic caffeine intake and low-intensityexercise on skeletal muscle of Wistar rats Exp. Physiol. 2011 96 1228 1238 10.1113/expphysiol.2011.060483 21890517 85. Guo Y. Niu K. Okazaki T. Wu H. Yoshikawa T. Ohrui T. Furukawa K. Ichinose M. Yanai K. Arai H. Coffee treatment prevents the progression of sarcopenia in aged mice in vivo and in vitro Exp. Gerontol. 2014 50 1 8 10.1016/j.exger.2013.11.005 24269808

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095740 ijerph-19-05740 Article Female Sex and Living in a Large City Moderate the Relationships between Nursing Students’ Stress Level, Perception of Their Studies, and Intention to Practice Professionally: A Cross-Sectional Study https://orcid.org/0000-0002-6223-1504 Pawlak Natalia Dominika 12* https://orcid.org/0000-0003-1364-5767 Serafin Lena 1 https://orcid.org/0000-0002-1023-3057 Czarkowska-Pączek Bożena 1 Cañadas-De la Fuente Guillermo A. Academic Editor 1 Department of Clinical Nursing, Health Sciences Faculty, Medical University of Warsaw, Erazma Ciolka Street 27, 01-445 Warsaw, Poland; lena.serafin@wum.edu.pl (L.S.); bozena.czarkowska-paczek@wum.edu.pl (B.C.-P.) 2 Doctoral School, Medical University of Warsaw, Zwirki i Wigury Street 61, 02-091 Warsaw, Poland * Correspondence: natalia.pawlak@wum.edu.pl 09 5 2022 5 2022 19 9 574019 3 2022 06 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). One way to increase nursing retention is to expand the number of nursing education programs; however, a more cost-effective initial step would be to ensure that each graduate will start a professional career. Nursing studies expose students to prolonged and uncontrolled stress that negatively affects their professional identity and health. Two hundred and fifty-four nursing students participated in this study. The data were obtained using the Perceived Stress Scale (PSS-10), a proprietary questionnaire on the students’ perception of their study, intention to practice in the future, and other metrics. Among our sample, a dozen students were unsure that they would enter the nursing profession. Stress levels in women were higher than in men. Respondents indicated that they were afraid of the return of the pandemic. This analysis was significant among people living in large cities. Based on our findings, five themes should be prioritised: favourable study environment and adequate competencies (including implementation of stress management techniques, especially among women and students living and studying in large cities), appropriate working hours, quality of practical classes, and quality of personal protective equipment. nursing student stress professional practice This research received no external funding. ==== Body pmc1. Introduction The shortage of nurses that results from low nurse retention, defined as “keeping nurses in their jobs”, and instability in the nursing workforce are major global concerns [1,2]. The number of nurses per 1000 inhabitants varies widely among countries. Of those countries reporting to OECD, besides the Slovak Republic, this number decreased in 2020 compared to 2019. The mean number of nurses per 1000 inhabitants in OECD countries in 2019 was 8.83, while, in 2020, this decreased to 6.98 [3,4]. Moreover, there is evidence that more nurses retire than enter the profession every year, contributing to the nurses’ constantly increasing mean age and lowering nurse retention [5]. The World Health Organization estimates that the global needs-based shortage of nurses and midwives will be greater than 9 million by 2030 [6]. There are several ways to counteract the nursing shortage, such as pull and push factors, including appropriate and supporting working conditions, limiting working pressures, appropriate wages, career development and opportunities, and improving the social image of the profession [7]. Then, these factors are also crucial to maintaining healthcare workers’ mental health and their ability to deliver effective patient care [8,9]. Another way to increase nursing retention is to expand the number of nursing education programs and ensure that each graduate will start a professional career. This also counteracts the ageing of the nursing population. One way to increase the number of nursing students and graduates is to ensure a supportive learning environment and appropriate acquisition of knowledge and practical skills resulting in the readiness to professionally practice. According to the Directive 2005/36/EC, and later 2013/55/EU [10], basic nursing education comprises 4600 h of training, half of which is practical and at least one-third is theoretical. The nursing educational program obliges the nursing student to plan, organise, evaluate, and communicate the nursing care given directly with a healthy or sick individual [10]. In many countries, including Poland, nursing education programs lead to the obtaining of a practice license that is valid for 3 years, which means about 1500 education hours per year, making the program especially challenging. Thus, nursing studies expose students to prolonged and uncontrolled stress that negatively affects their professional identity and health [11]. Therefore, this study was conducted to determine the impact of stress levels on those intending to pursue professional practice among last-year nursing students and to determine the impact of sex, place of residence, and type of university on the relationship between their stress level, perception of the study, and intention to professionally practice in the future. 2. Materials and Methods 2.1. Design and Sample This was a correlational cross-sectional study of the bachelor’s degree nursing students in their final year. The study was performed from January to April 2021. The inclusion criteria were being in the last year of undergraduate studies in the field of nursing and not practicing nursing or other medical professions. Convenience sampling was used in this study and included 254 participants. The minimum required sample size was calculated a priori using G*Power software, assuming a confidence interval of 95%, a statistical power of 80%, and an α of 0.05. The minimum sample size was 186, and 260 students completed the questionnaire. After data analysis, six participants were excluded because they did not meet the inclusion criteria. 2.2. Instrument This work used an online survey using Google Forms. The invitation to participate was shared via social media groups focused on nursing students. Data were obtained using two questionaries. The first was the Polish adaptation of Perceived Stress Scale (PSS-10). The second was developed in house and included 5 questions regarding their attitude to nursing studies and plans for future professional life. Because the COVID-19 pandemic increased the awareness of difficulties and threads connecting with nursing practice, we also asked the responders how the pandemic has impacted their professional choices. An additional part of the questionnaire was a metric that allowed us to characterize the study group. The PSS-10 was developed by Cohen et al. [12], and its Polish validity and reliability study was conducted by Juczyński and Ogińska-Bulik [13]. It uses a five-point Likert-type scoring system. Each item on the scale is scored with options such as “never = 0 points”, “almost never = 1 point”, “sometimes = 2 points”, “fairly often = 3 points”, and “very often = 4 points”. The overall score of the scale is the sum of all points with a theoretical distribution from 0 to 40. A higher score implies a greater level of perceived stress. The internal reliability coefficient of the items regarding perceived stress on the Polish version of scale is 0.86 [13]. In our study, the Cronbach’s α coefficient for the PSS-10 scale was 0.714. The second part of the questionnaire consisted of 5 questions about the perception of the nursing studies and intent to pursue professional practice after completing the study program. The 5-point Likert scale from 0 “never” to 4 “very often” was again used to answer the statements. These questions have been developed by authors based on a literature review [11,14,15,16]. Sociodemographic data collection was performed at the end of the questionnaire. The questions concern age, sex, type of university, year of study, and place of residence. 2.3. Ethical Consideration This study was approved by the Medical University of Warsaw Review Board (AKBE/2/2021). Before answering, the students were informed about the aim of the study, inclusion criteria, the voluntary and anonymous nature of participation, and the right to withdraw from the study with no specific explanation needed. On the first page of the online link, students were asked to check the statement agreeing to participate with an understanding of the research assumptions. The survey would not open until the box was checked. Participants received no compensation for completing the survey. 2.4. Data Analysis Statistical analyses used IBM SPSS Statistics 25.0 (Predictive Solutions, Cracow, Poland). Spearman correlation was performed to establish the relationship between the variables. A moderation analysis was performed using A. Hayes’ macro-PROCESS to establish the moderating role of sociodemographic variables for the relationship between answers to inhouse questions and stress (2017). A linear regression analysis was performed using the stepwise method to determine whether the sociodemographic variables were predictors of the stress level. The level of significance was α = 0.05. 3. Results 3.1. Students’ Characteristics The study included 254 nursing students in their final year. Table 1 presents the socio-demographic characteristics of the study group (sex, age, universities, place of residence). Place of residence has been presented based on the stratification of cities according to the Central Statistical Office in Poland (small cities, medium-sized cities, large cities, and the largest cities in Poland) [17]. The mean age of the participants was 22.8 years. The youngest person was 20 and the oldest was 47 years old. 3.2. Students’ Stress Level The mean PSS-10 score was 24.95 (SD = 5.64). The minimum value in this scale was 0 points, and the maximum was 40 points. The analysis showed that the distribution of results is left-skewed, which indicates that most of the respondents obtained results above the group mean, suggesting a higher level of stress. Linear regression analysis was performed using the stepwise method to determine whether sex, place of residence, and type of university were significant predictors of the stress level. This step only used those predictors that met the probability criteria F < 0.05. The model was well suited to the data: F (1.252) = 7.60; p = 0.006. The analysis showed that sex was the only significant predictor of the perceived stress level (B = −3.07; SE = 1.11; p = 0.006). Stress levels in women were on average 3.07 points higher than in men. Sex accounted for 2.9% of the stress level variance. 3.3. Students’ Perception of Their Study and Future Practice Many of respondents (37.8%; n = 97) presented, at least sometimes, a feeling of regret in choosing nursing as a field of study. Moreover, many students had not finally decided to work in the profession after graduation (78%; n = 198). Most respondents frequently thought that distance learning and the limitations of practical classes had a negative impact on their practical skills (73.1%; n = 185). As many as 80.8% (n = 204) of respondents indicated that they very often or fairly often were aware that the pandemic could repeat itself. Detailed results regarding the students’ perception of the study and their intention to professional practice are presented in Table 2. 3.4. The Relationship between Stress Levels and Students’ Perception of Their Study and Intention to Professional Practice There was no correlation between stress and the willingness to work in the profession (r = 0.10, p = 0.110). There was also no correlation between the level of stress and limited practical activities at the bedside on practical skills (r = 0.11, p = 0.069). However, the analysis showed the relationship between stress level and concern about the lack of personal protective equipment in the facility (r = 0.28, p < 0.001) and awareness that the current pandemic situation related to COVID-19 may repeat itself (r = 0.20. p = 0.001). 3.5. Moderators for the Relationship between Stress Levels and Students’ Perception of Their Study and Intention to Professional Practice A moderation analysis was performed using A. Hayes’ PROCESS to determine whether sex, type of university, and place of residence is a moderator of the relationship between responses to questions related to the students’ perception of their study and intention to professionally practice. In relation to sex, of the five analyzed models, only one showed a significant moderation effect—sex moderated the relationship between regretting the choice of studying nursing and stress. The model fit the data well; F (3.250) = 6.50; p < 0.001, which explains the 7.2% of the dependent variable variance. Table 3 presents the regression coefficients of the analyzed model. A detailed analysis of simple effects showed that there was no significant relationship between regret choosing a field of study and stress among women (B = 0.50; SE = 0.31; p = 0.106); this was significant in men (B = 2.32; SE = 0.77; p = 0.003; 95%CI [0.79; 3.84]). Stress was higher when they regretted choosing a field of study. These results are illustrated in Supplementary Figure S1. The analysis of the moderation of five models in which the type of university was included as the moderator did not show a significant moderating role of the type of university. Therefore, these models will not be described. An analysis of the moderation of five models in which the place of residence was included as a moderator showed a moderating role of two models; these are discussed below. The first model considered the moderating role of the place of residence for the relationship between the answer to the question “Do you think to starting working in the profession after graduation?” as well as perceived stress. The model turned out to be a good fit for the data (F (9.244) = 2.21; p = 0.022) and explained 7.5% of the dependent variable’s variance. The overall (higher order) interaction effect was statistically significant (F (4.244) = 3.12; p = 0.016), and its inclusion increased the percentage of explained variance by 4.7%. The regression coefficients for the discussed model are presented in Table 4. The analysis of simple effects showed that a significant relationship between the decision to work in the profession after graduating from nursing studies and stress was significant only in the case of people living in cities with more than 500,000 residents. A higher willingness to work in the profession after graduation implied a higher stress level. The effects were insignificant in the remaining groups (Table 5; Supplementary Figure S2). The second model considered the moderating role of the place of residence for the relationship between perceived stress and the answer to the following question: “Are you aware that the current COVID-19 pandemic may repeat itself?” The model turned out to be a good fit for the data (F (9.244) = 3.82; p < 0.001) and explained 12.4% of the dependent variable’s variance. The regression coefficients for the model in question are shown in Table 6. The overall (higher order) interaction effect was statistically significant (F (4.244) = 3.62; p = 0.007), and its inclusion increased the percentage of explained variance by 5.2%. The regression coefficients for the discussed model are presented in Table 6. The analysis of simple effects showed that a significant relationship between the answer to the question regarding awareness of the possibility of repeating the current situation with COVID-19 and stress was significant among people living in cities from 151,000 to 500,000 inhabitants as well as in cities with more than 500,000 residents. More awareness correlated with a higher stress level. The effect was insignificant in smaller towns and among people living in the countryside (Supplementary Figure S3; Table 7). 4. Discussion Taking care of adequate nursing resources begins with ensuring the appropriate and adequate number of nursing students. Another problem is to ensure that every graduate will start their professional career. Among our sample, more than a dozen students were unsure that they would enter the nursing profession. Therefore, it is important to make nursing studies friendly for students and to provide them with the appropriate knowledge, skills, and social competencies that will allow them to start their jobs with the feeling that they are properly prepared. Supporting future healthcare professionals, both pre- and post-graduation, seems crucial in solving the global nursing shortage [16]. Additionally, the COVID-19 pandemic has seriously impacted the learning conditions and has demonstrated that the profession of a nurse is particularly difficult, dangerous, possibly health- and life-threatening, and has revealed in the majority of health care facilities a lack of preparation in terms of ensuring epidemiologically safe conditions for medical personnel, including nurses, which results in high levels of stress and anxiety [18]. Thus, this possibly deepened the students’ fear regarding the future professional environment in terms of physical and psychological threats and therefore impacted the decision to start a nursing career after studies were completed. Yang et al. showed in general that students who experienced or witnessed stressful events related to COVID-19 reported negative psychological symptoms [19]. These symptoms could be manifested by a sense of tension, fear of infection, insomnia, and depressed mood [15,19]. In general, nursing students experience greater stress levels than other college students [20], and this could affect patients’ outcomes, patient safety, and quality of care [21]. Undergraduate nursing students are exposed to stressful situations, especially those in the more clinically-oriented years of training [22]. Our study revealed that nursing students perceived a moderate stress level (24.91 ± 5.65), though most respondents reported higher than all group mean stress levels. In Aslan and Pekince [14], the stress level of Turkish nursing students measured by using the same tool during the pandemic was 31.69 ± 6.91. This level was considered moderate. Nursing students normally presented moderate stress levels [23,24,25,26]. Previous research has shown that stress levels decreased with higher knowledge about the pandemic [27,28]. Nursing students are a very specific group of students and are directly integrated into the pandemic given their health training and area of knowledge [18]; thus, their stress level is not higher than before the pandemic [14]. Erisn [11] showed that health awareness was high [11]. This may be because students receive reliable knowledge in medicine and thus try to translate this information into future professional practice. However, education regarding infection prevention and protection measures should be incorporated into the study program to a greater extent. Especially here, respondents frequently realise a pandemic may reoccur, and specialists are alarmed that future pandemics are inevitable [29]. We did not confirm the correlation between stress level and willingness to work in nursing. Despite the fact that a large percentage of the respondents considered that the limitation of practical classes influences the development of their skills, we did not confirm the relationship between stress level and limited practical classes in real contact with the healthy or sick individual, which is essential for providing appropriate professional skills among graduates. Organising such classes for nursing students is associated with several difficulties, such as accelerated patient processing, in which patients are discharged from hospitals earlier, reductions in the number of hospital beds on the wards where students mainly have their clinical practice, or limited space in highly specialised wards that can only accommodate a limited number of students. Therefore, additional solutions should be implemented to provide an appropriate number of hours of practical training, for instance, partial training in simulation centres. This takes additional significance in the context of a potential reoccurrence of pandemic and the necessity to implement e-learning and distance learning [30] to limit the spread of SARS-CoV-2 or another microorganism [31]. The effectiveness of simulation learning has been shown in different nursing areas to be as good as or even better than traditional learning; however, the EU requirements describe clinical learning as being ‘in direct contact with a healthy or sick individual’ [32]. Thus, the revision of these requirements should be alternatively considered. Interestingly, the students’ sociodemographic characteristics are related to their stress level [14,33]. Here, only sex was a significant predictor of perceived stress. Even though men in our study accounted for only 11.4% of respondents, this is still a lot compared to the percentage of men in nursing in Poland, which is 2.7% [34]. Female students showed higher rates of perceived stress than men. This result agrees with previous studies [14,35,36,37]. Long-term analysis revealed that women themselves attach more importance to their inner experiences: they are more vulnerable to depression, anxiety, and loneliness [38]. We found that only men who said they regretted choosing a field of study had higher stress. This means that stress in men causes an active attitude towards a potential stressor that may make it easier to cope, which is worth considering in future research. Therefore, supporting nursing students, most of whom are female, in managing stress is an important aspect of preparing them for professional nursing practice. It is important to support nursing students in coping with stress, thus reducing, for instance, the risk of premature termination of professional education. Often, instructors do not realise the causes or extent of students’ stress; however, a deliberate engagement with students about their stress and offering interventions can be beneficial [39]. Therefore, it is critical for the faculty to monitor students’ stress and provide opportunities for frequent debriefing sessions, particularly during times of crisis such as a pandemic [15]. There was a correlation between nursing students’ residence and their perceived stress level. Nursing students who declared that they lived in larger cities during their study or stayed at the place of study far from their relatives might have had more stress. Üstün found that the anxiety levels of participants who were away from their families and social life and those who felt lonely were significantly higher than other participants [40]. A pandemic could impact this correlation. Living in larger cities with restrictions around social distancing can be more stressful. Bai et al. found that nursing students living in rural areas during the pandemic were more likely to choose nursing as their future career than their counterparts living in urban areas [41]. We found that the strongest relationship was between stress and concern about the facility’s lack of personal protective equipment. Studies had shown that students had increased fear and anxiety in clinical settings when personal protective equipment was deficient [23,42]. According to Savitsky et al., 50% of students working in healthcare settings lacked personal protective equipment at work; moreover, among these, the level of anxiety was higher. This anxiety continued into the current academic year and increased [23]. Preventive measures provide better comfort at work, reduce anxiety levels, and negate disease risk. 5. Limitations This study has some limitations. First, the cross-sectional design cannot establish a causal link between the investigated variables and does not allow us to formulate conclusions regarding the long-term effects of stress. Therefore, a longitudinal design is recommended for future studies. Second, convenience sampling does not generalise the results among nursing students. A randomised sample from different nursing schools is suggested to further study this issue. 6. Conclusions Adequate nursing retention relies on many factors, including the number of nursing students. The development and monitoring of the intention to work in the nursing profession should be constantly implemented by the education environment. Monitoring stress levels among nursing students and supporting career decisions should be performed in centres of nursing education considering the nursing shortage. An appropriate and favourable study environment and adequate competences should be provided to nursing students. These include the implementation of stress management techniques, especially among women and students living and studying in large cities, an appropriate number of hours and quality of practical classes providing adequate competences and skills, and personal protective equipment in the healthcare facility. Due to the common awareness that a reoccurrence of the COVID-19 pandemic is possible, knowledge regarding the pandemic and alternative ways of conducting practical classes should be considered. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095740/s1, Figure S1: Relationship between regretting choice of major and stress level with considering sex.; Figure S2: The relationship between the decision to pursue a career after graduation and stress levels by place of residence.; Figure S3: The relationship between awareness of the possibility of a repeat of the current pandemic situation and stress levels by place of residence. Click here for additional data file. Author Contributions N.D.P., L.S. and B.C.-P. contributed to the study design. N.D.P. conducted data collection. N.D.P., L.S. and B.C.-P. provided data analysis. N.D.P. and L.S. wrote the main manuscript text. B.C.-P. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Medical University of Warsaw (AKBE/2/2021). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare that they have no competing interests. ijerph-19-05740-t001_Table 1 Table 1 Students’ characteristics (N = 254). Characteristics of Respondents N % Sex Women 225 88.6 Men 29 11.4 Age ≤20–25 231 90.9 26–30 10 3.9 31–25 6 2.4 >36 7 2.8 University Medical 241 94.9 Vocational 13 5.1 Place of residence Village 84 33.1 City up to 50,000 residents 26 10.2 City from 50,001 to 150,000 residents 30 11.8 City from 150,001 to 500,000 residents 20 7.9 City > 500,000 residents 94 37 ijerph-19-05740-t002_Table 2 Table 2 Students’ perception of their study and intention to professional practice (N = 254). Never Hardly Ever Sometimes Quite Often Very Often N % N % N % N % N % Do you regret choosing a field of study (nursing)? 115 45.3 41 16.1 67 26.0 19 7.5 12 4.7 Do you think that limiting practical work at the bedside may adversely affect the development of your practical skills? 15 5.9 16 6.3 38 15.0 41 16.1 144 57.0 Do you think to starting working in the profession after graduation? 7 2.8 8 3.1 41 16.0 56 22.0 142 56.0 Are you worried about the lack of personal protective equipment at the facility where you decide to work? 37 15.0 24 9.4 64 25.0 51 20.1 78 31.0 Are you aware that the current COVID-19 pandemic may repeat itself? 5 2.0 4 1.6 41 16.0 53 20.8 151 60.0 ijerph-19-05740-t003_Table 3 Table 3 Regression coefficients for the model considering the moderating role of sex for the relationship between regret choosing a field of study and stress. 95% CI B SE t p LL UL Constant 24.91 0.34 72.60 <0.001 24.24 25.59 Do you regret choosing a field of study (Nursing)? 0.70 0.29 2.44 0.015 0.14 1.26 Sex −3.51 1.10 −3.18 0.002 −5.68 −1.34 Interaction 1.82 0.83 2.18 0.030 0.17 3.46 B—unstandardized regression coefficient; SE—standard error; t—t-statistic; p—p-value; CI—confidence interval; LL—lower level; UL—upper level. ijerph-19-05740-t004_Table 4 Table 4 Regression coefficients for the model considering the moderating role of the place of residence for the relationship between the decision to go to work after graduation from nursing and stress. 95% CI B SE t p LL UL Constant 25.32 0.60 42.05 <0.001 24.14 26.51 Do you think to starting working in the profession after graduation? −0.67 0.66 −1.02 0.310 −1.98 0.63 W1 −1.04 1.24 −0.84 0.402 −3.49 1.40 W2 −0.58 1.21 −0.48 0.632 −2.97 1.81 W3 −1.17 1.38 −0.85 0.397 −3.90 1.55 W4 −0.11 0.83 −0.13 0.897 −1.75 1.53 Interaction 1 −0.93 1.46 −0.64 0.525 −3.80 1.94 Interaction 2 1.81 1.25 1.45 0.148 −0.65 4.27 Interaction 3 2.19 1.12 1.96 0.051 −0.01 4.39 Interaction 4 2.42 0.84 2.88 0.004 0.77 4.07 Annotation. Interaction 1: question × W1; Interaction 2: question × W2; Interaction 3: question × W3; Interaction 4: question × W4. B—unstandardized regression coefficient; SE—standard error; t—t-statistic; p—p-value; CI—confidence interval; LL—lower level; UL—upper level. ijerph-19-05740-t005_Table 5 Table 5 Simple effects coefficients for the place of residence in the context of the relationship between the decision to work after graduation in nursing and stress. B SE p 95% CI Village −0.67 0.66 0.310 −1.98; 0.63 City up to 50,000 residents −1.60 1.39 0.219 −4.16; 0.96 City from 50,001 to 150,000 residents 1.14 1.06 0.283 −0.95; 3.22 City from 150,001 to 500,000 residents 1.51 0.90 0.093 −0.25; 3.28 City > 500,000 residents 1.75 0.52 0.001 0.73; 2.76 B—unstandardized regression coefficient; SE—standard error; p—p-value, CI—confidence interval. ijerph-19-05740-t006_Table 6 Table 6 Regression coefficients for the model considering the moderating role of the place of residence for the relationship between awareness of the possibility of a repetition of the current pandemic situation and stress. 95% CI B SE t p LL UL Constant 25.25 0.58 43.24 <0.001 24.10 26.40 Are you aware that the current COVID-19 pandemic may repeat itself? 0.25 0.65 0.38 0.706 −1.04 1.53 W1 −0.80 1.21 −0.66 0.511 −3.19 1.59 W2 −0.16 1.16 −0.14 0.889 −2.45 2.12 W3 −0.61 1.34 −0.45 0.651 −3.26 2.04 W4 −0.19 0.81 −0.23 0.818 −1.78 1.40 Interaction 1 −0.72 1.23 −0.59 0.557 −3.15 1.70 Interaction 2 0.74 1.25 0.59 0.554 −1.71 3.21 Interaction 3 2.87 1.13 2.54 0.012 0.65 5.10 Interaction 4 2.45 0.89 2.75 0.006 0.69 4.20 Annotation. Interaction 1: question × W1; Interaction 2: question × W2; Interaction 3: question × W3; Interaction 4: question × W4. B—unstandardized regression coefficient; SE—standard error; t—t-statistic; p—p-value; CI—confidence interval; LL—lower level; UL—upper level. ijerph-19-05740-t007_Table 7 Table 7 Simple effects coefficients for the place of residence in the context of the relationship between awareness of the possibility of a repetition of a pandemic situation and stress. B SE p 95% CI Village 0.24 0.65 0.706 −1.04; 1.53 city up to 50,000 residents −0.48 1.04 0.649 −2.53; 1.58 city from 50,001 to 150,000 residents 0.99 1.07 0.356 −1.12; 3.09 city from 150,001 to 500,000 residents 3.12 0.92 0.001 1.30; 4.93 city > 500,000 residents 2.69 0.60 <0.001 1.50; 3.88 B—unstandardized regression coefficient; SE—standard error; p—p-value, CI—confidence interval. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Søbstad J.H. Pallesen S. Bjorvatn B. Costa G. Hystad S.W. Predictors of turnover intention among Norwegian nurses: A cohort study Health Care Manag. Rev. 2021 46 367 374 10.1097/HMR.0000000000000277 32109924 2. Dotson M.J. Dave D.S. Cazier J.A. Spaulding T.J. An empirical analysis of nurse retention: What keeps RNs in nursing? J. Nurs. Adm. 2014 2 111 116 10.1097/NNA.0000000000000034 24451449 3. Health at Glance Available online: https://www.oecd-ilibrary.org/social-issues-migration-health/health-at-a-glance-2021_ae3016b9-en (accessed on 24 February 2022) 4. Czarkowska-Paczek B. Dawidowska M. Serafin L. The number of nurses and midwives per 1000 inhabitants influences life expectancy: A retrospective analysis based on data from 46 countries Int. J. Occup. Med. Environ. Health 2021 34 505 512 10.13075/ijomeh.1896.01699 33559650 5. Marc M. Bartosiewicz A. Chmiel Z. Januszewicz Z. A nursing shortage—A prospect of global and local policies Int. Nurs. Rev. 2018 66 9 16 10.1111/inr.12473 30039849 6. World Health Organization Available online: http://www.who.int/hrh/resources/16059_Global_strategyWorkforce2030.pdf?ua=1&ua=1 (accessed on 24 February 2022) 7. Roth C. Wensing M. Breckner A. Mahler C. Krug K. Berger S. Keeping nurses in nursing: A qualitative study of German nurses’ perceptions of push and pull factors to leave or stay in the profession BMC Nurs. 2022 21 48 10.1186/s12912-022-00822-4 35193561 8. Feola A. Cassandro P. Carfora A. Petrella R. Giordano C. Stefanizzi I.M. Borriello R. Suicides in physicians: Two cases of poisoning involving fentanyl and Phenobarbital Minerva Psichiatr. 2017 58 103 109 10.23736/S0391-1772.17.01931-8 9. Havaei F. Ma A. Staempfli S. MacPhee M. Nurses’ Workplace Conditions Impacting Their Mental Health during COVID-19: A Cross-Sectional Survey Study Healthcare 2021 9 84 10.3390/healthcare9010084 33467080 10. Directive 2005/36/EC Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02005L0036-20140117 (accessed on 24 February 2022) 11. Ersin F. Kartal M. The determination of the perceived stress levels and health-protective behaviors of nursing students during the COVID-19 pandemic Perspect. Psychiatr. Care 2020 8 10.1111/ppc.12636 12. Cohen S. Kamarck T. Mermelstein R. The PSS Scale is reprinted with permission of the American Sociological Association. A global measure of perceived stress J. Health Soc. Behav. 1983 24 386 396 13. Juczynski Z. Oginska-Bulik N. Tools for Measuring Stress and Coping with Stress, Psychological Test Laboratory Psychological Test Laboratory of the Polish Psychological Association Warsaw, Poland 2009 978-83-60733-47-9 14. Aslan H. Pekince H. Nursing students’ views on the COVID-19 pandemic and their percieved stress levels Perspect Psychiatr. Care 2021 57 695 701 10.1111/ppc.12597 32808314 15. Fitzgerald A. Konrad S. Transition in learning during COVID-19: Student nurse anxiety, stress, and resource support Nurs. Forum. 2021 56 298 304 10.1111/nuf.12547 33484171 16. Lin Y. Hu Z. Danaee M. Alias H. Wong L.P. The Impact of the COVID-19 Pandemic on Future Nursing Career Turnover Intention Among Nursing Students Risk Manag. Healthc. Policy 2021 14 3605 3615 10.2147/RMHP.S322764 34475792 17. Central Statistical Office Poland Available online: https://stat.gov.pl/obszary-tematyczne/ludnosc/ludnosc/powierzchnia-i-ludnosc-w-przekroju-terytorialnym-w-2020-roku,7,17.html (accessed on 3 May 2022) 18. Gallego-Gómez J.I. Campillo-Cano M. Carrión-Martínez A. Balanza S. Rodríguez-González-Moro M.T. Simonelli-Muñoz A.J. Rivera-Caravaca J.M. The COVID-19 Pandemic and Its Impact on Homebound Nursing Students Int. J. Environ. Res. Public Health 2020 17 7383 10.3390/ijerph17207383 33050435 19. Yang D. Tu C.C. Dai X. The effect of the 2019 novel coronavirus pandemic on college students in Wuhan Psychol. Trauma Theory Res. Pract. Policy 2020 12 (Suppl. S1) S6 S14 10.1037/tra0000930 20. Wolf L. Warner Stridham A. Ross R. Predictor of stress and coping strategies of US accelerated vs. generic baccalaureate nursing students: An embedded mixed methods study Nurse Educ. Today 2015 35 201 205 10.1016/j.nedt.2014.07.005 25127928 21. Jennings B.M. Work Stress and Burnout among Nurses: Role of the Work Environment and Working Conditions Patient Safety and Quality: An Evidence-Based Handbook for Nurses Hughes R.G. Agency for Healthcare Research and Quality (US) Rockville, MD, USA 2008 Chapter 26. 22. Mathias C.T. Wentzel D.L. Descriptive study of burnout, compassion fatigue and compassion satisfaction in undergraduate nursing students at a tertiary education institution in KwaZulu-Natal Curationis 2017 40 e1 e6 10.4102/curationis.v40i1.1784 23. Savitsky B. Findling Y. Ereli A. Hendel T. Anxiety and coping strategies among nursing students during the COVID-19 pandemic Nurse Educ. Pract. 2020 46 102809 10.1016/j.nepr.2020.102809 32679465 24. Wang C. Pan R. Wan X. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China Int J. Environ. Res. Public Health 2020 17 1729 10.3390/ijerph17051729 25. Kalkan Uğurlu Y. Mataracı Değirmenci D. Durgun H. Gök Uğur H. The examination of the relationship between nursing students’ depression, anxiety and stress levels and restrictive, emotional, and extfernal eating behaviors in COVID-19 social isolation process Perspect. Psychiatr. Care 2021 57 507 516 10.1111/ppc.12703 33270226 26. Sümen A. Adıbelli D. Nursing students’ readiness and coping strategies for the COVID-19 pandemic in Turkey J. Prof. Nurs. 2021 37 553 561 10.1016/j.profnurs.2021.03.005 34016314 27. Maarefvand M. Hosseinzadeh S. Farmani O. Farahani A.S. Khubchandani J. Coronavirus outbreak and stress in iranians Int. J. Environ. Res. Public. Health 2020 17 4441 10.3390/ijerph17124441 32575763 28. Zhi X. Lu L. Pu Y. Meng A. Zhao Y. Cheng F. Investigation and analysis of psychological stress and professional identity of nursing students during COVID-19 pandemic. Indian J. Exp. Biol. 2020 58 426 432 29. Horizon The EU Research & Innovation Magazine Available online: https://ec.europa.eu/research-and-innovation/en/horizon-magazine/qa-future-pandemics-are-inevitable-we-can-reduce-risk (accessed on 24 February 2022) 30. Marinoni G. Land H. Jensen T. The Impact of COVID-19 on Higher Education around the World International Association of Universities Global Survey Report Paris, France 2020 978-92-9002-212-1 31. Elsalem L. Al-Azzam N. Jum’ah A.A. Obeidat N. Sindiani A.M. Kheirallah K.A. Stress and behavioral changes with remote E-exams during the COVID-19 pandemic: A cross-sectional study among undergraduates of medical sciences Ann. Med. Surg. 2020 60 271 279 10.1016/j.amsu.2020.10.058 33163179 32. Henriksen J. Lofmark A. Wallinvirta E. Gunnarsdottir B.J. Slettebo A. European Union directives and clinical practice in nursing education in the Nordic countries Nord. J. Nurs. Res. 2020 40 3 5 10.1177/2057158519857045 33. Masha’al D. Rababa M. Shahrour G. Distance Learning-Related Stress Among Undergraduate Nursing Students During the COVID-19 Pandemic J. Nurs. Educ. 2020 59 666 674 10.3928/01484834-20201118-03 33253395 34. Supreme Council of Nurses and Midwives Poland Available online: https://nipip.pl/liczba-pielegniarek-poloznych-zarejestrowanych-zatrudnionych/ (accessed on 2 May 2022) 35. Anbumalar C. Agines D. Jaswanti V.P. Priya D. Reniangelin D. Gender differences in perceived stress levels and coping strategies among college students Int. J. Indian Psychol. 2017 4 22 33 10.25215/0404.103 36. Torres-Montiel S. Pelaez-Hernandez V. Robles-Uribe B. Gender differences in perceived stress, psychological well-being and therapeutic compliance Eur. Respir. J. 2017 50 PA3897 37. Turan N. Durgun H. Kaya H. Ertaş G. Kuvan D. The relationship between stress status and cognitive flexibility levels of nursing students J. Acad. Res. Nurs. (JAREN) 2019 5 59 66 10.5222/jaren.2019.43265 38. Gao W.B. Chen Z.Y. Wang Y.N. Analysis on the influence and change trend of public mentality during Sars epidemic Chin. Ment. Health J. 2003 17 594 596 39. Snyder B.L. Practicing what we preach: Teaching psychiatric–mental health student nurses to care for themselves J. Psychosoc. Nurs. Ment. Health Serv. 2020 58 40 45 10.3928/02793695-20200406-02 40. Üstün G. Determining depression and related factors in a society affected by COVID-19 pandemic Int. J. Soc. Psychiatry 2020 57 54 63 41. Bai W. Xi H.T. Zhu Q. Wang Z. Han L. Chen P. Cai H. Zhao Y.J. Chen L. Ge Z.M. Changes in Nursing Students’ Career Choices Following the COVID-19 Pandemic in China Front. Psychiatry 2021 12 657021 10.3389/fpsyt.2021.657021 33927657 42. Tang X. Wu C. Li X. Song Y. Yao X. Wu X. Duan Y. Zhang H. Wang Y. Qian Z. On the origin and continuing evolution of SARS-CoV-2 Natl. Sci. Rev. 2020 7 1012 1023 10.1093/nsr/nwaa036 34676127

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094958 ijms-23-04958 Communication An In Silico Methodology That Facilitates Decision Making in the Engineering of Nanoscale Protein Materials Parladé Eloi 12* https://orcid.org/0000-0003-0017-8274 Voltà-Durán Eric 123 Cano-Garrido Olivia 4 Sánchez Julieta M. 12356 https://orcid.org/0000-0001-5119-2266 Unzueta Ugutz 137 López-Laguna Hèctor 123 Serna Naroa 4 Cano Montserrat 4 Rodríguez-Mariscal Manuel 4 https://orcid.org/0000-0003-1052-0424 Vazquez Esther 123 https://orcid.org/0000-0002-2615-4521 Villaverde Antonio 123* Putz Mihai V. Academic Editor Cao Yi Academic Editor 1 CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), C/Monforte de Lemos 3-5, 28029 Madrid, Spain; eric.volta@uab.cat (E.V.-D.); jsanchezqa@gmail.com (J.M.S.); uunzueta@santpau.cat (U.U.); hector.lopez@uab.cat (H.L.-L.); esther.vazquez@uab.es (E.V.) 2 Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain 3 Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain 4 Nanoligent S.L., Eureka Building, Av. de Can Doménech s/n, Campus de la UAB, 08193 Bellaterra, Spain; olivia.cano.garrido@gmail.com (O.C.-G.); naroas@nanoligent.com (N.S.); mcano@nanoligent.com (M.C.); mrm@nanoligent.com (M.R.-M.) 5 Departamento de Química, Cátedra de Química Biológica, Facultad de Ciencias Exactas, Físicas y Naturales, ICTA, Universidad Nacional de Córdoba, Av. Vélez Sársfield 1611, Córdoba 5016, Argentina 6 Instituto de Investigaciones Biológicas y Tecnológicas (IIByT), CONICET-Universidad Nacional de Córdoba, Córdoba 5016, Argentina 7 Biomedical Research Institute Sant Pau (IIB Sant Pau), Sant Antoni Ma Claret 167, 08025 Barcelona, Spain * Correspondence: eloi.parlade@uab.cat (E.P.); antonio.villaverde@uab.cat (A.V.) 29 4 2022 5 2022 23 9 495801 4 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Under the need for new functional and biocompatible materials for biomedical applications, protein engineering allows the design of assemblable polypeptides, which, as convenient building blocks of supramolecular complexes, can be produced in recombinant cells by simple and scalable methodologies. However, the stability of such materials is often overlooked or disregarded, becoming a potential bottleneck in the development and viability of novel products. In this context, we propose a design strategy based on in silico tools to detect instability areas in protein materials and to facilitate the decision making in the rational mutagenesis aimed to increase their stability and solubility. As a case study, we demonstrate the potential of this methodology to improve the stability of a humanized scaffold protein (a domain of the human nidogen), with the ability to oligomerize into regular nanoparticles usable to deliver payload drugs to tumor cells. Several nidogen mutants suggested by the method showed important and measurable improvements in their structural stability while retaining the functionalities and production yields of the original protein. Then, we propose the procedure developed here as a cost-effective routine tool in the design and optimization of multimeric protein materials prior to any experimental testing. nanomaterials protein stability nanomedicine mutagenesis Retos Colaboración of the Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la SociedadRTC-2017-6125-1 VI National R&D&I Plan 2008–2011, Iniciativa Ingenio 2010, Consolider Program, CIBER ActionsInstituto de Salud Carlos IIIEuropean Regional Development FundAGAUR2019FI_B00352 Ministerio de Ciencia e InnovaciónPU18/04615 ISCIII co-funded by European Social FundCP19/00028 Nanoligent S.L. participates in the project «NANOTRAC. Desarrollo de un nuevo medicamento selectivo con potente actividad antimetastática» funded in the call Retos Colaboración of the Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, under the Plan Estatal de Investigación Científica y Técnica y de Innovación 2017–2020 (RTC-2017-6125-1). The authors are also indebted to the CERCA programme from la Generalitat de Catalunya, Spain, and to the Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain, which is an initiative funded by the VI National R&D&I Plan 2008–2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions and financed by the Instituto de Salud Carlos III, with assistance from the European Regional Development Fund. H.L.L. was supported by a predoctoral fellowship from AGAUR (2019FI_B00352), and E.V.D. was supported by a predoctoral fellowship from Ministerio de Ciencia e Innovación, Spain (FPU18/04615). U.U. was supported by a Miguel Servet contract (CP19/00028) from ISCIII co-funded by European Social Fund (ESF investing in your future). A.V. received an ICREA ACADEMIA award. ==== Body pmc1. Introduction The acquisition and grouping of desired biological activities, which can be combined in a single polypeptide chain through multidomain recruitment, allows producing modular proteins with specific functionalities that are not occurring in nature [1,2,3,4,5,6]. Designing multidomain proteins is a strategy especially appealing in the generation of protein materials at micro- and nanoscales, in which the building blocks must gain assembling abilities for regulatable oligomerization [7,8]. Under urgent demands from biomedical fields such as drug delivery [9,10,11] and regenerative medicine [12,13], emerging protein materials offer the possibility to assemble as supramolecular structures of defined geometries and mechanical properties, combined with desired biological functionalities [14]. For instance, protein scaffolds in tissue engineering provide mechanically stable substrates for cell growth but also display integrin-binding peptides [15] or release growth factors [16] to enhance either substrate colonization or/and proliferation. In drug delivery, protein nanoparticles offer a nanoscale size that is convenient for the prolonged circulation of payload drugs in blood and for optimal tissue and cell penetrability [17], plus specific cell targeting through solvent-display of homing peptides (i.e., specific binders of cell surface tumoral markers [18]). However, while functional recruitment through domain fusion can be organized on the simple basis of requested bio-physical properties [4,19], the whole functionality, stability, and productivity of the target proteins in cell factories are often neglected in the first design schemes. A poor or limited yield or conformational quality of recombinant proteins (being both common events [20,21]) might result in failing materials, which despite showing potential in the clinical field, are not robust enough to be brought to the industry. In this context, rational site-directed protein engineering allows functional and structural refinement of protein functionalities that had already been achieved by domain recruitment through gene fusion. Such fine-tuning process should consider all functional and structural aspects that could be associated with the final product, with particular emphasis on the biofabrication step. The generation of structured, hierarchical tuning processes beyond the initial modular design would ensure the robust applicability of clinically relevant products, which upon a first straightforward design, could not reach optimal performance. Driven by the need to improve current protein scaffolds available for targeted drug delivery, we set out to develop a rational refining procedure described herein with transversal applicability for any kind of protein material. Specifically, we illustrate this process with the generation of a series of humanized protein nanoparticles for their application in selective drug delivery for oncology. Protein assembling, stability, and the precise cell targeting of the whole functional nanoparticles have been polished through site-directed mutagenesis of a modular polypeptide based on the human nidogen [22] empowered with T22, a peptidic ligand of the tumoral marker CXCR4 [23,24]. The architecture of the nanoparticles formed by this protein [25] and related fusion proteins [26,27,28,29,30,31,32,33] is supported by the coordination of divalent cations such as Zn2+ with histidine-rich domains [34], which overhang from the building blocks [35]. The rational selection of mutational targets and the sequential assay-and-error application of semi-rational protein design has rendered a fully tailored polypeptide that, in contrast to the parental protein, fulfills all the requirements for clinical development, including a smooth biofabrication process. 2. Materials and Methods 2.1. Rational Refining Procedure The refining methodology consisted of the application of successive prediction algorithms to the structural data of the desired protein material. This was implemented in two stages. In the first one, the protein structure was subjected to a stability analysis to pinpoint areas contributing negatively to the overall robustness of the product, either by promoting precipitation or displaying excessive thermal mobility. Both issues were tackled in parallel by comparing precipitation and B-factor score predicted by Aggrescan3D 2.0 [36] and ResQ (via I-TASSER) [37,38] algorithms, respectively. High positive values in Aggrescan3D were the main indicator of instability, and residues harboring such scores were preselected for refinement, especially if they were consistent with a peak in B-factor. In the second stage, the impact of each preselected mutation was estimated while taking into account all possible residue substitutions. The implementation of this step was performed by combining the output of DeepDDG [39], a neural network-based algorithm used to predict stability changes of protein point mutations, and STRUM [40], a machine learning algorithm trained on evolutionary information. In both stages, comparison of the scores between any of the used algorithms required a Z-score normalization of the data to cope with differences in scale of the outputs. High positive values of each index were favorable for choosing a given mutation. In the final decision regarding which residues would serve as a replacement, hydrophobic amino acids were not considered as suitable for surface-exposed sites to avoid protein insolubility and aggregation. Reciprocally, the introduction of polar amino acids should be avoided in buried residue positions. 2.2. Protein Production and Characterization Proteins were designed in-house, and the encoding genes were provided by GeneArt (Thermo Fisher, Waltham, MA, USA) subcloned into pET26b plasmids (Novagen-Merck, Darmstadt, Germany). The parental protein was T22-HSNBT1-H6, and all its derivatives were named T22-HSNBT2-H6 through T22-HSNBT8-H6. Protein-encoding plasmids were transformed into Escherichia coli BL21 DE3 (Novagen-Merck, Darmstadt, Germany), and the encoded protein was produced overnight (O/N) at 20 °C in Lysogeny Broth (LB) medium upon induction with 0.1 mM isopropyl-β-D-1-tiogalactopyranoside (IPTG). Cells were then harvested by centrifugation (15 min at 5000× g) and resuspended in wash buffer (20 mM Tris, 500 mM NaCl, 10 mM Imidazole, pH 8) in the presence of protease inhibitors (cOmplete™ EDTA-Free, Roche, Basel, Switzerland). Cells were then disrupted in an EmulsiFlex-C5 system (Avestin, Ottawa, ON, Canada) by 3 rounds at 8000 psi. The soluble fraction of the cell lysate containing the proteins was separated by centrifugation (45 min at 15,000× g) and then charged into a HisTrap HP column (GE Healthcare, Chicago, IL, USA) for purification by immobilized metal affinity chromatography (IMAC) in an ÄKTA pure system (GE Healthcare). Protein elution was achieved by applying a linear gradient of elution buffer (20 mM Tris, 500 mM NaCl, 500 mM Imidazole, pH 8). Purified protein fractions were then dialyzed against sodium carbonate (166 mM NaCO3H, pH 8). Protein purity was determined by SDS-PAGE gel electrophoresis and subsequent Western blot immunodetection using an anti-His monoclonal antibody (Santa Cruz Biotechnology, Dallas, TX, USA). Protein integrity was also determined by MALDI-TOF mass spectrometry. The final protein concentration was determined by Bradford assay and Nanodrop. 2.3. Morphometric Characterization and Zeta Potential Protein nanoparticle sizes were measured by Dynamic Light Scattering (DLS) at 633 nm prior to and after Zn-mediated oligomerization. Volume size distribution (expressed in nm) and zeta potential (expressed in mV) of protein materials were determined in a Zetasizer Pro (Malvern Instruments, Malvern, United Kingdom). All samples were measured in triplicates, and protein concentration was set at 1.5 mg/mL in carbonate buffer (166 mM NaCO3H, pH 8, refractive index 1.33, viscosity 0.887 mPa·s). 2.4. Determination of Intrinsic Fluorescence and Unfolding Temperature Fluorescence spectra were recorded in a Cary Eclipse spectrofluorometer (Agilent Technologies, Santa Clara, CA, USA). A quartz cell with a 10 mm path length and a thermostatted holder was used. The excitation and emission slits were set at 5 nm. The excitation wavelength was set at 295 nm, and the emission spectra were acquired within the 310–450 nm range. The protein concentration was 0.2 mg/mL in carbonate buffer (166 mM NaHCO3, pH 8). In order to evaluate the conformation stability against heating, we obtained the fluorescence spectra at 5 °C temperature steps, and we calculated the center of spectral mass (CSM) for each spectrum. CSM is a weighted average of the fluorescence spectrum peak. It is also related to the relative exposure of the tryptophan (Trp) in the protein to the environment [41]. The maximum red-shift in the CSM of the Trp is compatible with large solvent accessibility and the protein unfolding. The CSM was calculated for each of the fluorescence emissions according to the following equation, where Ii is the fluorescence intensity measure at the wavelength λi. λ=∑λi·Ii∑Ii Midpoint unfolding temperature (Tm) was determined in GraphPad Prism 8.0.2 as the temperature value that corresponds to the inflexion point of the CSM vs. temperature curve. 2.5. Monomethyl Auristatin E Conjugation T22-HSNBT1-H6, T22-HSNBT2-H6, and T22-HSNBT5-H6 through T22-HSNBT8-H6 were covalently linked to maleimide-functionalized Monomethyl auristatin E (MC-MMAE, 911 g/mol, Levena Biopharma, San Diego, CA, USA) through solvent-exposed cysteine-tiol and lysine-amine groups at a 1:10 protein:MMAE molar ratio upon incubation for 4 h at RT in a one-pot reaction [29]. The concentration of each protein was set to 1.5–2 mg. Afterward, all protein conjugates were dialyzed (4 rounds of 90 min) against sodium carbonate buffer in 12–14 kDa MWCO membranes (Spectra/Por™ 2) to remove unlinked MMAE and centrifuged at 15,000× g for 15 min to remove precipitated protein. Reaction efficacy was finally checked by MALDI-TOF mass spectrometry. 2.6. Protein Modeling and Statistical Analyses Visualization and modeling of the three-dimensional structure of T22-HSNBT-H6 were conducted in ChimeraX software (version 1.2), and molecular lipophilicity potential was calculated using pyMLP [42,43]. Gaussian distribution of values was not assumed for any of the compared datasets. Hence, the nonparametric Mann–Whitney U test was used to compare means and extract significance values. All statistical analyses were performed using the built-in analysis tool in GraphPad Prism version 8.0.2. 3. Results and Discussion 3.1. In Silico Procedure The presented rational refining procedure is herein demonstrated in oligomeric protein nanoparticles envisaged for nanomedical applications, namely the cell-targeted delivery of antitumor payload drugs. These nanoparticles result from the organization of the modular protein T22-HSNBT1-H6 with the assistance of Zn cations present in the media (Figure 1A, Patent WO2021130390). This protein is derived from the humanized version of the CXCR4-directed T22-GFP-H6 [25,44] that was re-designed, substituting GFP by the G2 domain of nidogen (Uniprot identifier: P14543) [25]. Implementation of the first step of the refining process yielded an aggregation/flexibility profile (Figure 1B) that was used to pre-select nine sites of interest to be mutated (V45, V121, F157, V176, I200, Y201, V215, V236, and L237). The first 25 residues of the protein were not eligible for mutation as they contain the ligand peptide T22 and a flexible spacer required for proper CXCR4 targeting. Four of the preselected residues were finally selected after comparison of the predicted aggregation propensity, flexibility (ResQ, B-factor), and ΔΔG (STRUM) scores, all stacked together in Figure 1C. Then, in the second step of the process, all possible amino acid substitutions with the potential to improve stability and solubility of the protein material were evaluated by combining ΔΔG scores of both STRUM and DeepDDG methods in a normalized data plot (Figure 1D). All four chosen mutations (V45T, V121Q, F157E, and V215T) involved residues exposed on the surface of the assembled protein material. Due to the hydrophilic nature of the new residues, the predicted lipophilicity was expected to decrease in comparison to the original material (Figure 1E,F). Single mutants were designed to encompass each of the best-scoring substitutions individually, and two additional mutants were designed to harbor three and all four of the selected mutations. The rationale behind the mutant with three out of the four possible mutations (T22-HSNBT6-H6) was to include as many mutations as possible without compromising the targeting properties given by T22. Then, the mutation Val215, which is the closest to T22, was not included in this construct. A modular view of the proteins and their incorporated mutations is presented in Figure 2. An additional clone (T22-HSNBT8-H6) was also designed to incorporate all the selected mutations plus an additional substitution at C214 to remove the capacity to bind MMAE at that particular site, which was suspected of inducing protein precipitation. As this residue was already identified, only the second step of the procedure was applied to choose a substitute residue (serine). Obtaining this additional mutant was highly interesting to reduce the potential oligomeric states of the protein, envisaging highly soluble monomers still capable of forming nanoparticles upon coordination with cationic Zn [45]. In this context, we selected the I-TASSER server as the starting point of the process because, aside from integrating the ResQ algorithm, it outputs a PDB file with the predicted protein structure of the query sequence, which can be used directly as input for Aggrescan3D. Interestingly, the feasibility of using low-resolution structure models for high-accuracy stability change prediction upon point mutations has already been demonstrated [46], and a reliable tridimensional model is not required. In fact, some sequence-based methods exploiting evolutionary information show performances comparable to structure-based tools [46]. Nevertheless, new algorithms for the determination of protein stability after point mutations are constantly under development and could theoretically be used indistinctively to reproduce the current strategy. Several methods propose diverse approaches to the same end, allowing sequence or structure-based inputs [47], the incorporation of biochemical properties data [48], or the stability prediction of multiple point mutations [49]. Needless to say, protein materials with expected enzymatic or binding capacities are susceptible to compromises in activity to favor solubility whenever a mutation tackles a catalytic residue or binding site. In such cases, users should consider the implications of proceeding with the given mutation. 3.2. Protein Expression and Purification As stated above, the modular design of T22-HSNBT1-H6 [25] is similar to T22-GFP-H6. The GFP-based version forms multimeric nanoparticles of 12 nm efficiently targeted to CXCR4+ cancer cells [44]. Several mutated versions of the parental protein (from T22-HSNBT1-H6 to T22-HSNBT8-H6) were designed and produced in E. coli according to the defined purposes described above. For simplification purposes, the terms T22-HSNBT-H6 and HSNBT will be used indistinctively from now on (as synonyms) in text and figures. An initial expression test was carried out as a first approach to evaluate the feasibility of recombinant production and the quality of each new mutant protein. All mutant proteins were successfully detected by Western blot in the cell lysates, after cell disruption (Figure S1A), with molecular weights within the expected range (~30.3 kDa). Proteins containing the mutation F157E (namely HSNBT4, HSNBT6, and HSNBT7) exhibited a slightly higher migrating band. The analysis of HSNBT3 and HSNBT4 was halted at this point because an important fraction of these proteins occurred in the insoluble cell fraction (data not shown). HSNBT8, harboring the most mutations, was designed individually after verifying that its closest construct, HSNBT7, was properly produced. At this point, protein production was scaled up to 500 mL cultures maintaining the same conditions. All the proteins were successfully purified by metal affinity chromatography with suitable yields (Figure S1B), and their integrity was assessed by both SDS-PAGE/Western blot (Figure S1C) and MALDI-TOF (Figure S2A), being in 166 mM NaCO3H buffer at pH 8. Mass spectrometry profiles confirmed that the mobility shift in SDS-PAGE of proteins harboring the mutation F157E (HSNBT6, HSNBT7, and HSNBT8) was not caused by any unexpected insertion (molar mass did not vary) and was rather due to conformational changes and/or changes in SDS binding induced by the newly accommodated glutamic acid. 3.3. Stability Study, Size Distribution, and Nanoparticle Formation Several indicators of stability were relied upon to evaluate the properties of the new protein materials [50,51]. First, zeta potential (Figure 3A) was measured to evaluate the degree of repulsion between proteins in the dispersion and have a grasp of their stability. Generally, it is considered that high (either positive or negative) values of zeta potential are indicative of suitable stability of the system [52]. In this case, negative zeta potentials were obtained for all proteins, and while no significant differences were seen, a trend was evident in which all the mutated candidates exhibited more negative averages compared to the original protein HSNBT1. Regardless, a significant change in zeta potential was not expected as surface charges were mostly unaltered, and only one negative charge was introduced (F157E). Second, the intrinsic fluorescence of the proteins was used to assess unfolding parameters linked to temperature [53,54]. We found that the Tm of the mutant proteins (Figure 3B) was in the same range as the original material yet slightly higher, indicative of increased tolerance and stability against increasing temperature. Since, among other uses, protein materials are particularly useful as drug carriers, this ability was explored by chemical conjugation with MMAE, a potent antitumor drug. Due to the hydrophobic nature of MMAE, it is essential to ensure the solubility of the conjugate, which was evaluated by assessing protein precipitation in the post-conjugation dialysis with the storage buffer (166 mM NaCO3H, pH 8), presenting the data as a percentage soluble protein remaining relative to the original concentration (Figure 3C). Significant improvements were reported for all mutants (above 85% solubility), except for HSNBT6, which showed high variability in replicate measurements, still remaining far more soluble on average than the original material. Additionally, the cysteine removal in HSNBT8 greatly contributed to the stabilization of the protein during conjugation, as no precipitation was detected in the assays involving this candidate. The maleimide functional group in MMAE preferably reacts with thiol groups in cysteines. Then, the only accessible cysteine not forming disulfide bonds was Cys214 (HSNBT1-HSNBT7), so conjugation at this position was deemed destabilizing. Instead, HSNBT8 had Cys214 replaced with Ser214, meaning that MMAE was distributed throughout the many amine groups from exposed lysines, keeping the protein material soluble. Supporting this claim, up to one linked MMAE was detected via MALDI-TOF in the soluble fractions of HSNBT1-HSNBT7, while up to three linked MMAE could be identified in HSNBT8, which did not precipitate (Figure S1D). At this point, HSNBT6 and HSNBT8 were selected to proceed further with the characterization because of their high production yields (namely 26 and up to 28 mg/L, respectively). Volume size distribution was studied via DLS using HSNBT1 as a reference. As depicted in Figure 3D, the same size was maintained in all protein materials, confirming that the chosen mutations did not affect the quaternary structure of the protein in its native state. Finally, the capacity of the new protein materials to assemble into nanoparticles was explored by adding ZnCl2 at a final concentration of 0.04–0.08 mM. In all cases, an increase in size was achieved (Figure 3D), reflecting nanoscale oligomerization. Specifically, HSNBT6 and HSNBT8 formed nanoparticles of around 17.5 and 11.5 nm, respectively, while the reference HSNBT1 yielded 31 nm-nanoparticles. Smaller nanoparticles in HSNBT8 were expected, as the lone cysteine at position 214 that was removed could promote the dimerization of the building blocks before assembly with Zn2+, leading to bigger nanoparticles. Nevertheless, these size ranges were within those considered optimal in medical applications, namely between 10 and 100 nm, that favor recirculation in the bloodstream and prevent renal clearance [55]. Most importantly, the results also confirm that mutations that originated from the refining protocol did not interfere with the Zn-driven assembling capacity of the building block. Hence, both candidates HSNBT6 and HSNBT8 represent successful improvements over the starting material, suitable for clinically oriented applications. 4. Conclusions In this study, we have presented a sequential in silico screening procedure to be routinely applied to improve the stability of nanoscale protein materials envisaged for biomedical applications. This platform provides an array of favorable mutations prone to stabilize the final product, either in the monomeric form or as nano-sized oligomers. While of a non-automated nature, the method offers flexibility and possibilities for further modulation since the users may follow the basic steps using their preferred algorithms, fitting specific needs or improving the whole process with updated algorithms. Thus, the inclusion of brief in vitro optimization methods, such as the one described herein, into protein design processes should improve the success chance of the resulting materials at virtually no cost. Moreover, adapting such methodologies will enhance project viability prior to reaching the experimental phase, where having unsuccessful candidates translates into large expenditures of time, personnel, and laboratory consumables. 5. Patents Protein scaffolds described herein are protected under patent WO2021130390A1, licensed to Nanoligent S.L. Acknowledgments Molecular graphics and analyses were performed with UCSF ChimeraX, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from the National Institutes of Health R01-GM129325 and the Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094958/s1. Click here for additional data file. Author Contributions Conceptualization, E.P., O.C.-G. and A.V.; methodology, E.P., E.V.-D., J.M.S. and H.L.-L.; software, E.P.; formal analysis, E.P.; investigation, E.P., O.C.-G. and N.S.; resources, U.U., E.V. and A.V.; writing—original draft preparation, E.P. and A.V.; writing—review and editing, E.P., E.V.-D., O.C.-G., J.M.S., U.U., H.L.-L., N.S., M.C., M.R.-M., E.V. and A.V.; project administration, M.C., M.R.-M., E.V. and A.V.; funding acquisition, M.C., M.R.-M., E.V. and A.V. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are openly available at: https://www.dropbox.com/s/p5h0ogt5cf5t0rv/DATA.xlsx?dl=0 (accessed on 1 April 2022). Conflicts of Interest M.R.-M., E.V. and A.V. are co-founders of Nanoligent S.L.; O.C.-G., N.S., M.C. and M.R.-M. are or were employed by Nanoligent S.L. during this study. The other authors declare no conflict of interest. Figure 1 (A) Amino acid sequence of the construct T22−HSNBT1−H6. Residues mutated at some point are highlighted in bold and blue; numeration starts at Met0. (B) Visualization of B-factor (dotted line) and aggregation (continuous line) predictors for each residue in T22-HSNBT1-H6. Positive aggregation values indicate tendency to aggregate and are highlighted in red. Preselected residues are marked with blue dots. (C) Stacked aggregation (Aggrescan3D), B-factor (ResQ), and mutation probability (STRUM) prediction scores of the preselected residues. (D) Scores of STRUM (light gray) and DeepDDG (dark gray) predictors for each possible substitution in the four selected residues. Hydrophobic residues are filled in a diagonal hatch pattern, and arrows indicate the chosen substitution for each amino acid. (E) Three-dimensional representation of T22-HSNBT1-H6, with the atoms of the selected residues for mutation displayed in blue. (F) Surface lipophilicity potential map. Insets on the right side highlight the predicted lipophilicity of the selected residues before and after substitution. Coloring ranges from dark cyan (most hydrophilic) to white to dark gold (most lipophilic). Figure 2 Modular design of the proteins derived from T22-HSNBT1-H6. Inverted black triangles indicate the approximate location of each chosen mutation in the core module of the scaffold protein. The precise position and nature of each mutation are indicated next to the modular construct, providing the original residue, its position in the sequence, and the new residue. Figure 3 (A). Distribution of the zeta potential values measured for the studied proteins. (B) Tm of the studied proteins obtained from CSM curves. (C) Precipitated portion of each of the protein mutants after the conjugation with the drug MMAE. (D) Size-volume profile (left) and size data (right) of selected candidates measured by DLS before and after nanoparticle formation induced with ZnCl2. Significance indicated as: * p ≤ 0.05, *** p ≤ 0.001. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Dimarco R.L. Heilshorn S.C. Multifunctional Materials through Modular Protein Engineering Adv. Mater. 2012 24 3923 3940 10.1002/adma.201200051 22730248 2. Siciliano V. Diandreth B. Monel B. Beal J. Huh J. Clayton K.L. Wroblewska L. McKeon A. Walker B.D. Weiss R. Engineering Modular Intracellular Protein Sensor-Actuator Devices Nat. Commun. 2018 9 10.1038/s41467-018-03984-5 29760420 3. Arís A. Villaverde A. Modular Protein Engineering for Non-Viral Gene Therapy Trends Biotechnol. 2004 22 371 377 10.1016/j.tibtech.2004.05.004 15245910 4. Vazquez E. Ferrer-Miralles N. Mangues R. Corchero J. Schwartz S. Jr. Villaverde A. Modular Protein Engineering in Emerging Cancer Therapies Curr. Pharm. Des. 2009 15 893 916 10.2174/138161209787582084 19275653 5. Glasgow A.A. Huang Y.M. Mandell D.J. Thompson M. Ritterson R. Loshbaugh A.L. Pellegrino J. Krivacic C. Pache R.A. Barlow K.A. Computational Design of a Modular Protein Sense-Response System Science 2019 366 1024 1028 10.1126/science.aax8780 31754004 6. Matico R. Szewczuk L.M. Pietrak B. Chen S. Dul E. Bonnette W.G. Meinhold D.W. Quinque G. Totoritis R. Lewis T. Modular Protein Ligation: A New Paradigm as a Reagent Platform for Pre-Clinical Drug Discovery Sci. Rep. 2019 9 13078 10.1038/s41598-019-49149-2 31511536 7. Main E.R.G. Phillips J.J. Millership C. Repeat Protein Engineering: Creating Functional Nanostructures/Biomaterials from Modular Building Blocks Biochem. Soc. Trans. 2013 41 1152 1158 10.1042/BST20130102 24059501 8. Vazquez E. Mangues R. Villaverde A. Functional Recruitment for Drug Delivery through Protein-Based Nanotechnologies Nanomedicine 2016 11 1333 1336 10.2217/nnm-2016-0090 27221076 9. Korpi A. Anaya-Plaza E. Välimäki S. Kostiainen M. Highly Ordered Protein Cage Assemblies: A Toolkit for New Materials Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2020 12 e1578 10.1002/wnan.1578 31414574 10. Jao D. Xue Y. Medina J. Hu X. Protein-Based Drug-Delivery Materials Materials 2017 10 517 10.3390/ma10050517 11. Berckman E.A. Hartzell E.J. Mitkas A.A. Sun Q. Chen W. Biological Assembly of Modular Protein Building Blocks as Sensing, Delivery, and Therapeutic Agents Annu. Rev. Chem. Biomol. Eng. 2020 11 35 62 10.1146/annurev-chembioeng-101519-121526 32155350 12. Hussey G.S. Dziki J.L. Badylak S.F. Extracellular Matrix-Based Materials for Regenerative Medicine Nat. Rev. Mater. 2018 3 159 173 10.1038/s41578-018-0023-x 13. DeFrates K.G. Moore R. Borgesi J. Lin G. Mulderig T. Beachley V. Hu X. Protein-Based Fiber Materials in Medicine: A Review Nanomaterials 2018 8 457 10.3390/nano8070457 14. Hamley I.W. Protein Assemblies: Nature-Inspired and Designed Nanostructures Biomacromolecules 2019 20 1829 1848 10.1021/acs.biomac.9b00228 30912925 15. Dhavalikar P. Robinson A. Lan Z. Jenkins D. Chwatko M. Salhadar K. Jose A. Kar R. Shoga E. Kannapiran A. Review of Integrin-Targeting Biomaterials in Tissue Engineering Adv. Healthc. Mater. 2020 9 2000795 10.1002/adhm.202000795 32940020 16. Subbiah R. Guldberg R.E. Materials Science and Design Principles of Growth Factor Delivery Systems in Tissue Engineering and Regenerative Medicine Adv. Healthc. Mater. 2019 8 1801000 10.1002/adhm.201801000 17. Jain A. Singh S.K. Arya S.K. Kundu S.C. Kapoor S. Protein Nanoparticles: Promising Platforms for Drug Delivery Applications ACS Biomater. Sci. Eng. 2018 4 3939 3961 10.1021/acsbiomaterials.8b01098 33418796 18. Hamley I.W. Small Bioactive Peptides for Biomaterials Design and Therapeutics Chem. Rev. 2017 117 14015 14041 10.1021/acs.chemrev.7b00522 29227635 19. Serna N. Sánchez-García L. Unzueta U. Díaz R. Vázquez E. Mangues R. Villaverde A. Protein-Based Therapeutic Killing for Cancer Therapies Trends Biotechnol. 2018 36 318 335 10.1016/j.tibtech.2017.11.007 29246477 20. Rosano G.L. Ceccarelli E.A. Recombinant Protein Expression in Escherichia Coli: Advances and Challenges Front. Microbiol. 2014 5 172 10.3389/fmicb.2014.00172 24860555 21. Corchero J.L. Gasser B. Resina D. Smith W. Parrilli E. Vázquez F. Abasolo I. Giuliani M. Jäntti J. Ferrer P. Unconventional Microbial Systems for the Cost-Efficient Production of High-Quality Protein Therapeutics Biotechnol. Adv. 2013 31 140 153 10.1016/j.biotechadv.2012.09.001 22985698 22. Nagayoshi T. Sanborn D. Hickok N.J. Olsen D.R. Fazio M.J. Chu M.L. Knowlton R. Mann K. Deutzmann R. Timpl R. Human Nidogen: Complete Amino Acid Sequence and Structural Domains Deduced from CDNAs, and Evidence for Polymorphism of the Gene DNA 1989 8 581 594 10.1089/dna.1989.8.581 2574658 23. Tamamura H. Kuroda M. Masuda M. Otaka A. Funakoshi S. Nakashima H. Yamamoto N. Waki M. Matsumoto A. Lancelin J.M. A Comparative Study of the Solution Structures of Tachyplesin I and a Novel Anti-HIV Synthetic Peptide, T22 ([Tyr5,12, Lys7]-Polyphemusin II), Determined by Nuclear Magnetic Resonance Biochim. Biophys. Acta (BBA) Protein Struct. Mol. 1993 1163 209 216 10.1016/0167-4838(93)90183-R 24. Tamamura H. Imai M. Ishihara T. Masuda M. Funakoshi H. Oyake H. Murakami T. Arakaki R. Nakashima H. Otaka A. Pharmacophore Identification of a Chemokine Receptor (CXCR4) Antagonist, T22 ([Tyr5,12, Lys7]-Polyphemusin II), Which Specifically Blocks T Cell-Line-Tropic HIV-1 Infection Bioorganic Med. Chem. 1998 6 1033 1041 10.1016/S0968-0896(98)00061-3 25. Álamo P. Cedano J. Conchillo-Sole O. Cano-Garrido O. Alba-Castellon L. Serna N. Aviñó A. Carrasco-Diaz L.M. Sánchez-Chardi A. Martinez-Torró C. Rational Engineering of a Human GFP-like Protein Scaffold for Humanized Targeted Nanomedicines Acta Biomater. 2021 130 211 222 10.1016/j.actbio.2021.06.001 34116228 26. López-Laguna H. Sánchez-García L. Serna N. Voltà-Durán E. Sánchez J.M. Sánchez-Chardi A. Unzueta U. Łoś M. Villaverde A. Vázquez E. Engineering Protein Nanoparticles Out from Components of the Human Microbiome Small 2020 16 2001885 10.1002/smll.202001885 27. Serna N. Álamo P. Ramesh P. Vinokurova D. Sánchez-García L. Unzueta U. Gallardo A. Céspedes M.V. Vázquez E. Villaverde A. Nanostructured Toxins for the Selective Destruction of Drug-Resistant Human CXCR4+ Colorectal Cancer Stem Cells J. Control. Release 2020 320 96 104 10.1016/j.jconrel.2020.01.019 31931052 28. López-Laguna H. Cubarsi R. Unzueta U. Mangues R. Vázquez E. Villaverde A. Endosomal Escape of Protein Nanoparticles Engineered through Humanized Histidine-Rich Peptides Sci. China Mater. 2020 63 644 653 10.1007/s40843-019-1231-y 29. Pallarès V. Unzueta U. Falgàs A. Sánchez-Garciá L. Serna N. Gallardo A. Morris G.A. Alba-Castellón L. Álamo P. Sierra J. An Auristatin Nanoconjugate Targeting CXCR4+ Leukemic Cells Blocks Acute Myeloid Leukemia Dissemination J. Hematol. Oncol. 2020 13 10.1186/s13045-020-00863-9 30. Unzueta U. Roldán M. Pesarrodona M. Benitez R. Sánchez-Chardi A. Conchillo-Solé O. Mangues R. Villaverde A. Vázquez E. Self-Assembling as Regular Nanoparticles Dramatically Minimizes Photobleaching of Tumour-Targeted GFP Acta Biomater. 2020 103 272 280 10.1016/j.actbio.2019.12.003 31812843 31. Falgàs A. Pallarès V. Unzueta U. Céspedes M.V. Arroyo-Solera I. Moreno M.J. Gallardo A. Mangues M.A. Sierra J. Villaverde A. A CXCR4-Targeted Nanocarrier Achieves Highly Selective Tumor Uptake in Diffuse Large B-Cell Lymphoma Mouse Models Haematologica 2020 105 741 753 10.3324/haematol.2018.211490 31248974 32. Sánchez-García L. Sala R. Serna N. Álamo P. Parladé E. Alba-Castellón L. Voltà-Durán E. Sánchez-Chardi A. Unzueta U. Vázquez E. A Refined Cocktailing of Pro-Apoptotic Nanoparticles Boosts Anti-Tumor Activity Acta Biomater. 2020 113 584 596 10.1016/j.actbio.2020.06.033 32603867 33. Serna N. Cano-Garrido O. Sánchez-García L. Pesarrodona M. Unzueta U. Sánchez-Chardi A. Mangues R. Vázquez E. Villaverde A. Engineering Protein Venoms as Self-Assembling CXCR4-Targeted Cytotoxic Nanoparticles Part. Part. Syst. Charact. 2020 37 2000040 10.1002/ppsc.202000040 34. López-Laguna H. Sánchez J. Unzueta U. Mangues R. Vázquez E. Villaverde A. Divalent Cations: A Molecular Glue for Protein Materials Trends Biochem. Sci. 2020 45 992 1003 10.1016/j.tibs.2020.08.003 32891514 35. López-Laguna H. Unzueta U. Conchillo-Solé O. Sánchez-Chardi A. Pesarrodona M. Cano-Garrido O. Voltà E. Sánchez-García L. Serna N. Saccardo P. Assembly of Histidine-Rich Protein Materials Controlled through Divalent Cations Acta Biomater. 2019 83 257 264 10.1016/j.actbio.2018.10.030 30366134 36. Kuriata A. Iglesias V. Pujols J. Kurcinski M. Kmiecik S. Ventura S. Aggrescan3D (A3D) 2.0: Prediction and Engineering of Protein Solubility Nucleic Acids Res. 2019 47 W300 W307 10.1093/nar/gkz321 31049593 37. Yang J. Wang Y. Zhang Y. ResQ: An Approach to Unified Estimation of B-Factor and Residue-Specific Error in Protein Structure Prediction J. Mol. Biol. 2016 428 693 701 10.1016/j.jmb.2015.09.024 26437129 38. Roy A. Kucukural A. Zhang Y. I-TASSER: A Unified Platform for Automated Protein Structure and Function Prediction Nat. Protoc. 2010 5 725 738 10.1038/nprot.2010.5 20360767 39. Cao H. Wang J. He L. Qi Y. Zhang J.Z. DeepDDG: Predicting the Stability Change of Protein Point Mutations Using Neural Networks J. Chem. Inf. Modeling 2019 59 1508 1514 10.1021/acs.jcim.8b00697 40. Quan L. Lv Q. Zhang Y. STRUM: Structure-Based Prediction of Protein Stability Changes upon Single-Point Mutation Bioinformatics 2016 32 2936 2946 10.1093/bioinformatics/btw361 27318206 41. Ahmad P. ul Islam B. Allarakha S. Dixit K. Ali A. Rabbani G. Khan R.H. Siddiqui S.A. Preferential Recognition of Peroxynitrite-Modified Human Serum Albumin by Circulating Autoantibodies in Cancer Int. J. Biol. Macromol. 2015 72 875 882 10.1016/j.ijbiomac.2014.10.001 25307128 42. Broto P. Moreau G. Vandycke C. Molecular Structures: Perception, Autocorrelation Descriptor and Sar Studies: System of Atomic Contributions for the Calculation of the n-Octanol/Water Partition Coefficients Eur. J. Med. Chem. 1984 19 71 78 43. Laguerre M. Saux M. Dubost J.P. Carpy A. MLPP: A Program for the Calculation of Molecular Lipophilicity Potential in Proteins Pharm. Pharmacol. Commun. 1997 3 217 222 44. Céspedes M.V. Unzueta U. Aviñó A. Gallardo A. Álamo P. Sala R. Sánchez-Chardi A. Casanova I. Mangues M.A. Lopez-Pousa A. Selective Depletion of Metastatic Stem Cells as Therapy for Human Colorectal Cancer EMBO Mol. Med. 2018 10 e8772 10.15252/emmm.201708772 30190334 45. López-Laguna H. Sánchez J.M. Carratalá J.V. Rojas-Peña M. Sánchez-García L. Parladé E. Sánchez-Chardi A. Voltà-Durán E. Serna N. Cano-Garrido O. Biofabrication of Functional Protein Nanoparticles through Simple His-Tag Engineering ACS Sustain. Chem. Eng. 2021 9 12341 12354 10.1021/acssuschemeng.1c04256 34603855 46. Fariselli P. Martelli P.L. Savojardo C. Casadio R. INPS: Predicting the Impact of Non-Synonymous Variations on Protein Stability from Sequence Bioinformatics 2015 31 2816 2821 10.1093/bioinformatics/btv291 25957347 47. Li B. Yang Y.T. Capra J.A. Gerstein M.B. Predicting Changes in Protein Thermodynamic Stability upon Point Mutation with Deep 3D Convolutional Neural Networks PLoS Comput. Biol. 2020 16 e1008291 10.1371/journal.pcbi.1008291 33253214 48. Chen C.W. Lin M.H. Liao C.C. Chang H.P. Chu Y.W. IStable 2.0: Predicting Protein Thermal Stability Changes by Integrating Various Characteristic Modules Comput. Struct. Biotechnol. J. 2020 18 622 630 10.1016/j.csbj.2020.02.021 32226595 49. Montanucci L. Capriotti E. Frank Y. Ben-Tal N. Fariselli P. DDGun: An Untrained Method for the Prediction of Protein Stability Changes upon Single and Multiple Point Variations BMC Bioinform. 2019 20 335 10.1186/s12859-019-2923-1 50. Rabbani G. Ahmad E. Zaidi N. Fatima S. Khan R.H. PH-Induced Molten Globule State of Rhizopus Niveus Lipase Is More Resistant Against Thermal and Chemical Denaturation Than Its Native State Cell Biochem. Biophys. 2012 62 487 499 10.1007/s12013-011-9335-9 22215307 51. Rabbani G. Kaur J. Ahmad E. Khan R.H. Jain S.K. Structural Characteristics of Thermostable Immunogenic Outer Membrane Protein from Salmonella Enterica Serovar Typhi Appl. Microbiol. Biotechnol. 2014 98 2533 2543 10.1007/s00253-013-5123-3 23949993 52. Lu G.W. Gao P. Emulsions and Microemulsions for Topical and Transdermal Drug Delivery Handbook of Non-Invasive Drug Delivery Systems Elsevier Amsterdam, The Netherlands 2010 59 94 53. Rabbani G. Ahmad E. Zaidi N. Khan R.H. PH-Dependent Conformational Transitions in Conalbumin (Ovotransferrin), a Metalloproteinase from Hen Egg White Cell Biochem. Biophys. 2011 61 551 560 10.1007/s12013-011-9237-x 21833676 54. Rabbani G. Ahmad E. Khan M.V. Ashraf M.T. Bhat R. Khan R.H. Impact of Structural Stability of Cold Adapted Candida Antarctica Lipase B (CaLB): In Relation to PH, Chemical and Thermal Denaturation RSC Adv. 2015 5 20115 20131 10.1039/C4RA17093H 55. Longmire M. Choyke P.L. Kobayashi H. Clearance Properties of Nano-Sized Particles and Molecules as Imaging Agents: Considerations and Caveats Nanomedicine 2008 3 703 717 10.2217/17435889.3.5.703 18817471

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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092842 molecules-27-02842 Article Mutual Influence of Some Flavonoids and Classical Nonionic Surfactants on Their Adsorption and Volumetric Properties at Different Temperatures Taraba Anna https://orcid.org/0000-0003-1791-2893 Szymczyk Katarzyna * Zdziennicka Anna https://orcid.org/0000-0002-8852-4495 Jańczuk Bronisław Silva Bruno Academic Editor Department of Interfacial Phenomena, Institute of Chemical Sciences, Faculty of Chemistry, Maria Curie-Skłodowska University in Lublin, Maria Curie-Skłodowska Sq. 3, 20-031 Lublin, Poland; anna.taraba@poczta.umcs.lublin.pl (A.T.); anna.zdziennicka@mail.umcs.pl (A.Z.); bronislaw.janczuk@poczta.umcs.lublin.pl (B.J.) * Correspondence: katarzyna.szymczyk@mail.umcs.pl; Tel.: +48-81-537-55-38 29 4 2022 5 2022 27 9 284212 4 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Due to the increasing practical use of mixtures of flavonoids with nonionic surfactants the presented studies were based on the measurements of surface tension and conductivity of aqueous solution of the quercetin (Q) and rutin (Ru) in the mixtures with Triton X-114 (TX114) and Tween 80 (T80) as well as the contact angle of model liquids on the PTFE surface covered by the quercetin and rutin layers. Based on the obtained results components and parameters of the quercetin and rutin surface tension were determined and the mutual influence of Q and Ru in the mixtures with TX114 and T80 on their adsorption and volumetric properties were considered. It was found, among others, that based on the surface tension isotherms of the aqueous solution of the single flavonoid and nonionic surfactant, the surface tension isotherms of the aqueous solution of their mixture, the composition of the mixed monolayer at the water-air interface as well as the CMC of flavonoid + nonionic surfactant mixture can be predicted. The standard Gibbs energy, enthalpy and entropy of the adsorption and aggregation of the studied mixtures were also found, showing the mechanism of the adsorption and aggregation processes of the flavonoid + nonionic surfactant mixture. flavonoids nonionic surfactants adsorption micellization surface tension contact angle This research received no external funding. ==== Body pmc1. Introduction Flavonoids which can be found mainly in blue and red fruits as well as vegetables have many very important properties for the functioning of the human population [1,2,3,4,5,6]. Among the flavonoids, the quercetin (Q) and rutin (Ru) play the important role in their practical applications [7,8,9,10,11,12]. However, these applications are limited due, among others, to the poor solubility of the flavonoids in water. The other difficulties are associated with the lack of the flavonoids stability under the influence of temperature, pH, light and enzymes [13,14]. The literature data indicate that the flavonoids stability can be improved by the addition of the nonionic surfactants [15,16]. Of these surfactants polysorbates (Tweens) and Tritons seem to be the most proper for this purpose [17,18,19,20,21]. These nonionic surfactants are biodegradable and characterized by great physicochemical stability and large water solubility. For this reason, they are widely used in the pharmaceutical, cosmetic and even food industries. Tweens, for example are widely applied as dough conditioners, enhancers of the softness retention properties of mono- and diglycerides in the yeast-leavened bakery goods (such as bread and doughnuts) and as surfactants maintaining the emulsion stability in such products as butter, chocolate, and precooked foods [22]. These applications are connected, among others, with their adsorption and aggregation properties [23,24,25]. Flavonoids, which are poorly soluble in water, can be accumulated in surfactant micelles, particularly nonionic, as well as in the mixed interface layers. As a matter of fact, the formation of mixed layers at the interfaces results from the interface tension changes. The micellization process of nonionic surfactants in the presence of flavonoids should be also changed. The adsorption of the surfactants and other compounds at the water-air interface and micelle formation in the bulk phase depend on the surface tension of the surfactants, additives and water. It is impossible to find the components and parameters of the Q and Ru surface tension in the literature. These components and parameters of flavonoids as well as tail and head of nonionic surfactants influence on the reduction of the water surface tension by the mixed monolayer formed at the water-air interface as well as the micelle formation in the bulk phase. The adsorption and aggregation properties of the mixture of different compounds depend on the interactions between their molecules. The intermolecular interactions of the mixture compounds can be deduced, among others, based on the surface tension isotherms. It is possible that we can describe and/or predict these isotherms. The literature reports many systems for which the surface tension isotherms of the surfactant mixtures were mathematically described or thermodynamically predicted [26,27]. However, it is difficult to find such studies dealing with the mixtures of surfactants like Tween 80, which in the opinion of some authors has antioxidant properties [28], as well as flavonoids. Therefore, the aim of our studies was to determine the surface tension isotherms of the aqueous solution of Triton X-114 (TX114) and Tween 80 (T80) with the addition of quercetin and rutin at temperature equal to 293, 303 and 313 K. These nonionic surfactants have in their molecules, among others, the aromatic ring, oxyethylene, -CH3 and -OH groups. There are the big differences in the sizes of TX114 and T80 molecules and it is possible to find in the literature these sizes and contactable area, which is important for understanding the intermolecular interactions [29,30]. To explain the tendency of the flavonoid + nonionic surfactant mixtures to adsorb at the water-air interface and to form the micelles in the bulk phase the knowledge of the thermodynamic parameters is useful. For determination of these parameters the measurements of the surface tension of the aqueous solution of the flavonoid + nonionic surfactant mixtures at minimum three different temperatures is needed. For more detailed explanation of the changes of the surface tension of aqueous solution of nonionic surfactants with the addition of flavonoids as a function of surfactants concentration at the constant concentration of added flavonoids, their surface tension components and parameters were determined. Thus the contact angles of water, formamide and diiodomethane on the flavonoids layer formed on the model solid were measured. The obtained isotherms of the surface tension were considered due to their description and prediction. Based on these isotherms the critical micelle concentration (CMC) values as well as thermodynamic parameters of the adsorption and micellization were established. 2. Results 2.1. Some Physicochemical Properties of Quercetin, Rutin, TX114 and T80 The adsorption and aggregation properties of different kinds of the compounds in the aqueous media depend on the volume of their molecules, the presence of the hydrophobic and hydrophilic groups in the molecules and their arrangement as well as the contactable area of molecules dependent on their configuration and orientation. The volume of the quercetin, rutin, TX114 and T80 in the aqueous environment can be established taking into account the length of the chemical bonds, the angle between the bonds and the average distance between them and water molecules [31]. This average distance can be in the range from 1.56 to 2 Å at 293 K [32,33]. In our calculations, this distance was assumed to be 2 Å but in the case of hydrogen bonds creation as equal to 1.93 Å [31]. The earlier calculations showed that the volume of a given compound molecule can be determined based on the volume of the cube in which the molecule is inscribed or the sum of the volumes of cubes in which individual parts of more complex molecules are described [31,33]. The volume of one molecule of the studied compounds determined in such a way is the smallest for quercetin and largest for T80 (Table 1). The volumes of rutin and TX114 are comparable. To examine the reliability of the calculated volume of quercetin, rutin, TX114 and T80 molecules, their molar volume and then their density was determined (Table 1). For Ru, TX114 and T80, the density determined in a such way is close to the literature data [34,35] and in the case of Q the determined value of its density is close to that determined by us (Table 1). This fact suggests that the volumes of quercetin, rutin, TX114 and T80 molecules calculated by us are reliable. If so, it is possible to establish the contactable area of these molecules in the monolayer at the water-air interface. In fact, this area depends on the orientation of the molecules of a given compound in the monolayer. In the case of TX114 and T80 their contactable area depends also on their molecules configuration [25,31,36,37]. Table 1 presents the values of the range of the contactable area of quercetin, rutin, TX114 and T80 molecules depending on their orientation and configuration in the monolayer at the water-air interface. The comparison of the contactable area of the molecules with that occupied by the molecules of the studied compounds in the saturated monolayer at the water-air interface can be useful for the explanation of the orientation and packing of these molecules in this monolayer. The minimal area (Amin) occupied by the molecules of quercetin, rutin, TX114 and T80 can be calculated from their maximal concentration (Γmax) in the surface monolayer at the water-air interface using the expression [38]:(1) Amin=1Nmax, where N is the Avogadro number. As it was difficult to find the Γmax values for quercetin and rutin in the literature, the surface tension (γLV) of the aqueous solution of the flavonoids was measured (Figure 1). It appeared that the obtained surface tension isotherms of the aqueous solution of quercetin and rutin can be successfully described by the numerically solved Szyszkowski equation against γLV. This equation has the form [38]:(2) γ0−γLV=RTnΓmaxln(Ca+1), where γ0 is the solvent surface tension, n is the parameter used in the Gibbs isotherm equation for determination of the surface excess concentration of the given surfactant and the mixture of surfactants, C is the surfactant concentration and a is the constant. Taking into account the values of Γmax for quercetin and rutin calculated from Equation (2) and the literature values for TX114 and T80 [23,25], the values of Amin were determined from Equation (1) (Table 1). From the comparison of the Amin values to those of contactable area it results that with exception for TX114 the Amin values are close to those of the contactable area at the perpendicular orientation of their molecules towards the water-air interface (Table 1). However, in the case of TX114 it is possible that the tail of its molecules is oriented parallel towards the water-air interface. It should be mentioned that the Amin value of TX114 is close to the contactable area of head of its molecule at the parallel orientation toward the interface (Table 1: 115.73 Å2 − 51.12 Å2 = 64.61 Å2). The maximal packing of quercetin, rutin, TX114 and T80 in the saturated monolayer can be deduced based on the ratio of Γmax to Γ∞, where Γ∞ is the limiting concentration of a given compound in the saturated monolayer, which is directly associated with the size of the molecule and its orientation toward the interface. The Γ∞ values can be determined not only based on the molecule size but also using the Joos concept [39]. The ratio of Γmax to Γ∞ (Table 1) indicates that the smallest packing of TX114 in the saturated monolayer at the water-air interface, among the studied compounds, takes place. This probably results, among others, from the fact that the hydrogen ions can be joined with the oxyethylene groups in the TX114 molecules and the repulsive electrostatic interactions took place [38]. The Γmax is the reflection of the surface tension of the aqueous solution of a given surfactant. The surface tension of the solution depends on that of all its components. In the case of the compounds whose molecules have the hydrophobic and hydrophilic parts, commonly known as surfactants, their surface tension depends on the orientation of hydrophobic and hydrophilic parts toward the air phase. If the surfactant molecules are oriented by the hydrophobic part toward the air, the surface tension of surfactant is called the tail surface tension (γT) and at the orientation by the hydrophilic phase toward the air phase the head surface tension (γH) [32]. In the literature it is difficult to find the surface tension of the quercetin and rutin. Indeed, in the case of the flavonoid molecules it is impossible to distinguish the tail and head. Therefore, the components and parameters of their surface tension can be treated as an average effect of the hydrophobic and polar interactions related to the different chemical functional groups in their molecules. The Lifshitz-van der Waals component (γLW), electron-acceptor (γ+) and electron-donor (γ−) parameters of the studied flavonoids surface tension were determined based on the contact angle (θ) for such model liquids as water, formamide and diiodomethane on the polytetrafluoroethylene (PTFE) surface covered by the flavonoid layer (Table S1 in SM) using the van Oss et al. equation [40,41,42]:(3) γ2(cosθ+1)=2(γ1LWγ2LW+γ1+γ2−+γ1−γ2+), where 1 and 2 refer to the flavonoids and the nonionic surfactants, respectively. From the calculations based on Equation (3) it appeared that the surface tension of flavonoids is almost the same as the surface tension of TX114 head and smaller than that of T80 head (Table 1). There are the big differences between the values of γ− parameter. Probably this difference has an effect on the solubility of flavonoids which is smaller than that of nonionic surfactants. The determined components and parameters of flavonoids surface tension are of significant importance in the interactions between the flavonoids and the surfactant molecules in the mixed monolayer at the water-air interface and in the micelles. It should be noted that the water-surfactant head interfacial tension has the negative values. These negative values influence on the solubility of the surfactants in water. On other hand, the positive values of the water-surfactant tail interfacial tension decide about the adsorption and aggregation properties of surfactants [38]. 2.2. Surface Tension of the Aqueous Solution of Flavonoids with Nonionic Surfactant Mixtures According to van Oss et al. the surface tension of solids, liquids and solutions depends on the Lifshitz-van der Waals (LW), acid-base (AB) and electrostatic (EL) intermolecular interactions in the interface region [40,41,42]. The LW interactions are present in each substance but the presence of AB and EL depend on the type of the substance. In the case of the aqueous solutions of the organic substances, whose concentration at the interface is higher than that in the bulk phase their surface tension depends on the LW, AB and/or EL intermolecular interactions between all molecules being in the interface region. As the calculated LW component of the flavonoids surface tension is higher than that of water [43], the flavonoids presence in the interface region does not reduce the water surface tension due to the LW interactions (Table 1). In the case of TX114 and T80 they can decrease of the LW component of water by the orientation of their molecules toward the air phase but to a small extent. This conclusion results from the fact that the LW component of the water surface tension is smaller than that of flavonoids and insignificantly larger than the tail surface tension of TX114 and T80 which results from only the LW interactions (Table 1). Theoretically, the minimal surface tension of the aqueous solution of a given surfactant at its saturated monolayer at the water-air interface should be close to the surface tension of this surfactant tail. On the other hand, the largest reduction of water surface tension by the surfactant adsorption at the water-air interface takes place in the surfactant concentration range in the bulk phase corresponding to its saturated monolayer. This decrease of water surface tension results mainly from the decrease of AB component of this tension. Probably the surfactant molecules in the saturated monolayer with the increase of their concentration in the bulk phase change orientation and the part of the tail in their molecules are in the air phase as a result of the changes in the gradient of surfactants concentration in the surface region. The shape of surface tension isotherm of the aqueous solution of flavonoids and nonionic surfactant mixtures proved that their concentration corresponds to the saturated mixed monolayer, particularly at the constant concentration of flavonoids equal to 1 × 10−4 M (Figure 2 and Figure 3). The mutual effect of the flavonoids and nonionic surfactants on the reduction of water surface tension can be clearly seen if the minimal values of γLV of the aqueous solution of flavonoid and nonionic surfactant mixture are compared with the solution of single nonionic surfactant (Figure 2 and Figure 3) [23,25]. For almost all systems there is a linear dependence between γLV and the temperature (Figure S1 in SM as an example) and the flavonoids cause the increase of γLV minimal values of solution in the presence of TX114 or T80 in comparison to the solutions of single nonionic surfactants. This increase depends on the kind of flavonoid. The minimal values of γLV for the studied flavonoid and TX114 mixture at 293 K are smaller than that of flavonoid (Table 1) and larger than the surface tension of TX114 tail (Table 1) [31]. The same relation takes place in the case of the flavonoid + T80 mixtures. All  γLV isotherms obtained for the aqueous solution of flavonoids and nonionic surfactant mixtures can be successfully described by the exponential function of the second order (Figures S2–S9 in SM). This function has the form:(4) γLV=y0+A1exp(−Ct1)+A2exp(−Ct2), where y0, A1, A2, t1 and t2 are the constants. The y0 values change linearly as a function of temperature for all studied aqueous solutions of flavonoid and nonionic surfactant mixtures (Figures S10 and S11 in SM). Moreover, it seems that the y0 values are related to the LW interactions between the water, flavonoids and nonionic surfactant molecules in the surface region. These values are close to the minimal surface tension of the solutions (Figure 2 and Figure 3). It is more difficult to find the relationship between the constants A1, A2, t1 and t2 in Equation (4) and the physicochemical properties of flavonoids and nonionic surfactants (Figures S10 and S11 in SM). Taking into account the conclusion drawn from our earlier studies [44], we can suppose that A1 and A2 can be joined with the polar interactions between the flavonoids and the nonionic surfactant molecules and t1 and t2 with the activity coefficient of the flavonoids and the nonionic surfactants in the mixed monolayer. Unfortunately, more detailed explanation of the constants in the equation of the exponential function of the second order for the studied mixtures based on the surface tension components and parameters of the water, flavonoids and nonionic surfactants is impossible. The attempt to describe the surface tension isotherms of the aqueous solutions of a mixture of flavonoids with the nonionic surfactants by the Szyszkowski equation (Equation (2)) [38] was only partially successful (Figures S2–S9 in SM). It should be mentioned that probably only compound molecules in the monomeric form adsorbing at the water-air interface reduce the water surface tension [27]. For the studied system with T80 it was difficult to establish the surfactants concentration at which they were present in the monomeric form which was related to the flavonoids + nonionic surfactant mixtures in which the constant flavonoid concentration was equal to 1 × 10−4 M. The deviation of the γLV values calculated from Equation (2) from the measured ones is greater for the aqueous solution of the mixtures of rutin with TX114 and quercetin with T80 than for the solution of the quercetin with TX114 and rutin with T80 mixtures. This is in accordance with the forces of interactions between these compounds in the bulk phase [31]. It is known that the surface tension of the aqueous solution of the binary and ternary mixtures of the surfactants can be predicted using proper methods. For this purpose the method proposed by Fainerman and Miller [45,46] is very often applied. However, this method was successfully used for prediction of the aqueous solution of surfactant mixtures surface tension in which the interactions between the mixture components were not very strong [31]. The main problem to use the Fainerman and Miller equation [45,46] for calculation of γLV is to establish the proper area occupied by one mole of the mixture components and the mixture itself at the water-air interface (ϖ=πRTΓ∞) particularly when the concentration of one component of the mixture is constant and the other variable. The limiting area occupied by one mole of the binary surfactant mixtures depends on the limiting surface concentration which should satisfy the following simple expression:(5) Γ∞=Γ1∞x1s+Γ2∞x2s, where Γ1∞ and Γ2∞ are the limiting surface concentrations of components 1 and 2 and x1s and x2s are the mole fractions of surfactants 1 and 2 in the mixed monolayer at the water-air interface. If the reduction of water surface tension by a given component of the mixed monolayer is proportional to its individual reduction at the same concentration in the aqueous solution, then x1s=π1π1+π2 and x2s=π2π1+π2 (π1 and π2 are the surface pressure of components 1 and 2, respectively) [44]. In such case it is possible to apply the Fainerman and Miller equation for prediction of the surface tension of the aqueous solution of binary surfactant mixtures. This equation has the form [45,46]:(6) expΠ=expΠ1+expΠ2−1, where Π=πϖ/RT, Π1=π1ϖ1/RT and Π2=π2ϖ2/RT (R is the gas constant and T is the temperature). The γLV values calculated from Equation (6) for the aqueous solution of quercetin + TX114 and rutin + TX114 mixtures at the constant concentration of flavonoids equal to 1 × 10−5 M are very close to the measured ones (Figures S2 and S6 in SM). However, at the constant concentration of flavonoids equal to 1 × 10−4 M (Figures S3, S5, S7 and S9 in SM) only for the aqueous solution of quercetin with TX114 mixture the γLV values calculated from Equation (6) are close to the measured ones but the differences between the calculated and measured γLV values are greater than at the quercetin concentration equal to 1 × 10−5 M. In the case of the aqueous solution of flavonoids with T80 mixtures at the constant concentrations of flavonoids equal to 1 × 10−5 M (Figures S4 and S8 in SM) and to 1 × 10−4 M (Figures S5 and S9 in SM) there are significantly greater differences between the calculated and measured γLV values than for the mixtures of flavonoids with TX114. The reason for these differences can be changes of the limiting concentration of flavonoids and T80. This concentration depends on the orientation of flavonoid molecules as well as the configuration of T80 ones. As mentioned above the minimal contactable area of flavonoids can be changed significantly depending on their orientation toward the water-air interface (Table 1). On the other hand, the contactable area of T80 depends largely on the configuration of its molecules in the monolayer at the water-air interface [37]. To explain the contribution of flavonoids and nonionic surfactants to reduction of water surface tension, the γLV values for the studied systems were calculated from the following expressions:(7) γLV=γW−π1=π2, and (8) γLV=γLV,1x1s+γLV,2x2s, where γLV,1 and γLV,2 are the surface tension of the aqueous solution of flavonoid and nonionic surfactants, respectively at their concentration in the aqueous solution of the mixture the same as in the individual solution. Equation (7) gives reliable results only in the case when the independent adsorption takes place. It is possible at the concentration of the mixtures corresponding to the unsaturated mixed monolayer at the water-air interface. It appeared that the shape of γLV isotherms calculated from Equations (7) and (8) for the aqueous solution of the studied flavonoids with the TX114 mixtures is different from those for the mixtures of flavonoids with T80 (Figures S2–S9 in SM). At the constant concentration of flavonoids in the mixtures equal 1 × 10−5 M the independent adsorption takes place in the range of small T80 concentrations (Figures S4 and S8 in SM). For all studied systems the γLV values calculated from Equation (8) are higher than the measured ones. This indicates that in the range of the concentrations of the flavonoids with the nonionic surfactants mixture in which independent adsorption takes place Equation (8) does not give the real results and in the concentration range of these mixtures corresponding to the saturated mixed monolayer the γLV,1 and γLV,2 values are smaller than those corresponding to mixture components surface tension values at the same concentration in their individual solutions. 2.3. Composition and Concentration of the Mixed Monolayer at the Water-Air Interface The composition of the surfactants binary mixtures very often is determined using the Rosen and Hua concept [47]. Unfortunately, it is impossible to use this concept for determination of the composition of the mixed monolayers at the water-air interface containing the flavonoids and nonionic surfactants due to the difficulties to establish the range of concentration of the aqueous solution of flavonoids, nonionic surfactants and mixtures of flavonoids with nonionic surfactants at which there is the linear dependence between the surface tension of solutions and the logarithm from their concentration. The earlier presented considerations dealing with the composition of the mixed monolayers showed that the values of the relative mole fractions of surfactants in the mixed monolayers are close to those of the fraction of the surface area occupied by a given surfactant in this monolayer [27,44]. Thus, it is possible to assume approximately that x1s and x2s determined in the above mentioned way can be treated as the mole fraction of flavonoid and nonionic surfactant, respectively (Figures S12 and S13 in SM). From the comparison of the x2s with x2b (x2b=C2C1+C2 is the molar fraction of the nonionic surfactant in the mixture in the bulk phase) it results that for all studied systems the curve of x2b lies below that of x2s in the concentration range of the nonionic surfactant from zero to the value at which the cross point of x2b curve with x2s is observed. It is possible that this point corresponds to CMC. As a matter of fact, the composition of the mixed surface layer at the water-air interface depends on the concentration of particular components of the mixture at this interface. The concentration of the surfactants at the water-air interface is very often determined using the Gibbs isotherm equation [38]. However, for the aqueous solution of the flavonoids with the nonionic surfactant mixtures it is impossible to determine the Gibbs excess concentration for the flavonoids and in many cases for the nonionic surfactants in the whole range of their concentration in the bulk phase. The measurements of natural pH of the aqueous solution of flavonoid + nonionic surfactant mixtures indicate that its values decrease as a function of nonionic surfactants concentration (Figures S14 and S15 in SM). This suggests that the flavonoid and/or the nonionic surfactant can assume the ionic form. In the case of nonionic surfactants as mentioned above, the hydrogen ions can be joined with the oxyethylene groups and their behaviour can be similar to that of the cationic surfactants. It should be remembered that according to the Gibbs isotherm equation [38] the excess concentration of surfactants depends on their activity in the bulk phase and on the differences of the surface tension of the solution in relation to the surfactant activity. To determine the excess Gibbs surface active ions concentration in the Gibbs equation instead of RT the nRT is used where n assumes different values depending on the kind of surfactant and mixtures of surfactants. However, the best description of the surface tension isotherms of many surfactants can be obtained from the Szyszkowski equation using the maximal Gibbs surface excess concentration determined by the use of RT in the Gibbs equation [38]. In such case the Gibbs free energy of adsorption calculated based on the constant a in the Szyszkowski equation is close to that obtained by the other methods [38]. Thus, it can be assumed that also in the Frumkin equation the same maximal values of surfactants concentration in the monolayer as in the Szyszkowski equation should be used. However, in the case of the mixture to determine the surface concentration of a given mixture component its maximal concentration which depends on the composition of the mixed monolayer as well as the contribution of this component in the reduction of water surface tension should be used. The maximum concentration of a given mixture component in the mixed monolayer at the water-air interface should be equal to the product of its molar fraction in this layer and the maximum concentration for an individual solution (xsΓmax). On the other hand, the contribution of a given mixture component to the reduction of the water surface tension is equal to the product of the surface pressure of the mixed monolayer (π) and the mole fraction of this component in the layer (πi=xisπ). Taking this fact into account the Frumkin equation for i component of the surfactants mixture can assume the form:(9) πi=−RTxisΓimaxln(1−ΓixisΓimax), From the calculations made using Equation (9) it results that at the constant quercetin and rutin concentrations and variable concentration of TX114 in the bulk phase, the flavonoids concentration decreases and that of TX114 increases in the mixed monolayer at the water-air interface as a function of TX114 concentration in the bulk phase and depend on the temperature (Figures S16 and S17 in SM). In the whole range of TX114 concentration in the bulk phase at the constant flavonoids concentration equal to 1 × 10−4 M the saturated mixed monolayer of flavonoid and TX114 mixture is formed. The sum of flavonoid and TX114 concentrations decreases insignificantly as a function of TX114 concentration in the bulk phase, however, it is greater than for individual TX114 (Figures S16 and S17 in SM, Table 1). When the constant concentration of the flavonoid is equal to 1 × 10−5 M, the increase of TX114 concentration causes the increase of the sum of the flavonoid + TX114 concentrations in the mixed monolayer. For this case the sum of TX114 and flavonoid concentrations is higher than that for individual TX114. This fact proves that there are strong interactions of flavonoid molecules with TX114 ones and the area occupied by the flavonoid molecules is close to the minimal possible value (Table 1). The behaviour of the flavonoid + T80 mixtures is somewhat different from that of flavonoid + TX114 (Figures S16 and S17 in SM). In fact, in the case of the flavonoid + T80 mixture the concentration of its components in the mixed monolayer at the water-air interface depends on the temperature and T80 variable concentration in the bulk phase. However, the sum of the flavonoid + T80 concentrations in the mixed monolayer at the constant flavonoid concentration equal to 1 × 10−4 M does not depend practically on the T80 concentration in the bulk phase and is higher than the maximal T80 concentration in its single monolayer [22] (Table 1, Figures S16 and S18 in SM). At the constant concentration of flavonoid equal to 1 × 10−5 M in the bulk phase some changes of the flavonoid + T80 concentrations sum in the mixed monolayers take place in the T80 small concentration range. For the flavonoid + TX114 and flavonoid + T80 mixtures the higher sum of concentrations in the mixed monolayer is observed at the constant flavonoid concentration in the bulk phase equal to 1 × 10−4 M than at 1 × 10−5 M. This fact confirms the conclusion that there are strong interactions between the flavonoids and nonionic surfactants in the mixed monolayer at the water-air interface and that the molecules of flavonoids occupy the minimal possible area (Table 1). 2.4. CMC The aggregation of the nonionic surfactants in the presence of flavonoids is very important because of possible dissolution of flavonoids in the micelles. The determination of the critical micelle concentration (CMC) can be useful to understand the solubilization behaviour of flavonoids. The literature reports numerous methods for determination of CMC and among them these based on the surface tension and conductivity isotherms are often used [38]. It should be mentioned that different methods used for the CMC determination can give different values. This can be due to the fact that CMC is not related to a single concentration value of surfactants and their mixtures, but to a certain concentration range [24]. The sensitivity of a given method in determination of CMC can depend on the size and shape of the micelles or the density of the electric charge [38]. This is confirmed by the CMC values determined for the aqueous solutions of a mixture of flavonoids with the nonionic surfactants from the surface tension and conductivity isotherms (Figure 4). The CMC values determined from the conductivity isotherms of all binary mixtures of flavonoids and nonionic surfactants are higher than determined based on the surface tension isotherms (Table S2 in SM). It can be suggested that between the concentration of the aqueous solution of flavonoid + nonionic surfactant mixture at which the aggregation process was detected from the surface tension isotherm and the concentration detected from the conductivity isotherm the micelle size and/or the electric charge density may be changed. The CMC values of the aqueous solutions of the flavonoid + TX114 mixtures determined from the surface tension isotherms are insignificantly higher than those for the aqueous solution of TX114 determined also from the surface tension isotherm (Table S2 in SM) [24]. No significant effect of the constant flavonoid concentration in the bulk phase on CMC is observed. In the case of the aqueous solution of flavonoid + T80 there can be drawn the same conclusion as for the flavonoid + TX114 mixtures (Table S2 in SM). The temperature in the range from 293 to 313 K affects only insignificantly on the CMC of the studied systems. This may be due to the fact that in this temperature range the increase in the kinetic energy of the surfactant molecules can be compensated by a decrease in their hydration degree. It is very interesting that the crossing point on the curves of the mole fraction of the TX114 and/or T80 composition in the mixed monolayer at the water-air interface with the curves of the mole fraction of these compounds in the mixture of flavonoid + nonionic surfactant in the bulk phase is close to the CMC determined from the isotherms of the surface tension (Figures S12 and S13, Table S2 in SM). This probably means that the tendency of the flavonoids to solubilize in the nonionic surfactants micelles is greater than to adsorb at the water-air interface. 2.5. Thermodynamic Parameters of the Adsorption and Micellization The thermodynamic parameters of the adsorption and micellization process show the mechanism of these processes. The standard Gibbs free energy of adsorption (ΔGads0) and micellization (ΔGmic0) indicate the tendency to adsorb and aggregate a given surface active agent. The standard enthalpy of adsorption (ΔHads0) and micellization (ΔHmic0) provides the information about the reactions during the adsorption and micellization, respectively. Whereas the standard entropy of adsorption (ΔSads0) and micellization (ΔSmic0), which is a driving force of these processes is the result of all structural changes of the bulk phase of the solution and in the interface region. The relationship between the thermodynamic function of the adsorption and micellization processes can be expressed in the forms [38,48]:(10) ΔGads0=ΔHads0−TΔSads0, and (11) ΔGmic0=ΔHmic0−TΔSmic0, The literature reports numerous methods for determination of the thermodynamic functions [38,48]. However, in the case of the systems studied by us the most proper method for determination of ΔGads0 for the nonionic surfactants was based on the constant a in the Szyszkowski equation [38]. The a constant can be expressed in the form:(12) a=ϖexpΔGads0RT, From the calculations of ΔGads0 from Equation (12) it results that the tendency of the nonionic surfactants to adsorb at the water-air interface from the bulk phase of the flavonoid + nonionic surfactant mixture is greater than in the absence of flavonoid (Table S3 in SM). This is particularly visible in the case of T80. This confirm the above mentioned suggestion that there are the strong interactions between the molecules of flavonoids and nonionic surfactants increasing its hydrophobic properties. It is not excluded that in the adsorption of nonionic surfactants at the water-air interface together with flavonoids dimmers can be formed [49]. The tendency to adsorb of flavonoid + nonionic surfactant mixture at the water-air interface can be deduced based on the ΔGads0 values calculated from the following equation [50]:(13) ΔGads0=RTlnCMCω−γW−γLVminΓmax, The values of ΔGads0 calculated from Equation (13) suggest that the adsorption activity of the flavonoid + nonionic surfactant mixture is higher than ΔGads0 of the flavonoid in the absence of the nonionic surfactant and that without flavonoid (Table S3 in SM). As follows from Table S3 for the given system there are some differences between the ΔGads0 values calculated from Equation (13) if the CMC values taken for calculation were determined from the surface tension isotherms, from the cross point of curves of mole fraction of nonionic surfactant in the bulk phase and in the mixed monolayers as well as those determined from the conductivity isotherms. It can be expected that the difference between the ΔGads0 values calculated from Equation (13) for the studied mixtures and ΔGads0 for the individual components of the mixture [23,25] results from the small negative values of the free energy of mixing of flavonoids and nonionic surfactants in the mixed monolayer because of strong interactions between their molecules. Considering the influence of the interactions between the flavonoid and nonionic surfactant molecules on the tendency of the mixture of flavonoid with the surfactant to adsorb at the water-air interface, one would expect a similar tendency to form micelles whose a measure is the standard free energy of micellization. This energy can be determined from the equation which has the form [38]:(14) ΔGmic0=RTlnCMCω, The values of ΔGmic0 calculated from Equation (14) for the flavonoids + nonionic surfactants mixture are practically close to that of the nonionic surfactants in the absence of flavonoids and depend on the temperature but not on the concentration of flavonoids and their type (Table S4 in SM) [24,25]. It probable means that the flavonoids do not form with nonionic surfactants typical mixed micelles but only are present in the insert of the nonionic surfactants micelles. Due to the adsorption and micellization processes more information can be provided by the standard entropy and the standard enthalpy of adsorption and micellization. The standard entropy of adsorption and micellization can be established based on the following equations [38]:(15) d(ΔGads0)dT=−ΔSads0, and (16) d(ΔGmic0)dT=−ΔSmic0. From the calculations it results that the ΔHads0 values for the flavonoid + TX114 mixtures are negative independently of the constant flavonoid concentration and its type. The ΔHads0 values for this mixture calculated from Equation (10) are close to the ΔHads0 values for quercetin and rutin, respectively (Table S5 in SM). This indicates that for these systems the small changes in dehydration of mixture components takes place. On contrary to the flavonoid + TX114 mixtures, the ΔHads0 values of the flavonoid + T80 mixtures at the constant flavonoid concentration equal to 1 × 10−4 M indicate the strong dehydration takes place as a result of the strong interactions between the flavonoid and the nonionic surfactant in the mixed monolayer at the water-air interface. In the case of the micellization, in contrast to adsorption, the standard enthalpy and entropy of micellization of the flavonoids + nonionic surfactant mixtures depend on the constant flavonoids concentration and their type (Tables S6 and S7 in SM). These thermodynamic functions differ significantly from than those for TX114 and T80 in the absence of flavonoids (Table S8 in SM). At the constant concentration of flavonoids equal to 1 × 10−4 M independently of the kind of nonionic surfactants, the values of ΔHmic0 are positive. This may result from the fact that during the penetration of flavonoids molecules into the micelles significant dehydration proceeds. At the constant flavonoid concentration equal to 1 × 10−5 M ΔHmic0 assumes the positive and negative values depending on the type of the systems. This fact suggests that in the micellization process the greater number of bonds is disrupted than is formed for the quercetin molecules with TX114 than with rutin. In fact, the TΔSads0 and TΔSmic0 (Equations (10), (11), (15) and (16)) assume larger or smaller values than ΔGads0 and ΔGmic0 depending on the values of standard entropy of adsorption and micellization, respectively (Tables S3 and S4 in SM). 3. Materials and Methods Quercetin (Q, ≥95%, CAS Number 117-39-5), rutin (Ru, ≥95%, CAS Number 207671-50-9), Triton X-114 (TX114, laboratory grade, CAS Number 9036-19-5) and Tween 80 (T80, CAS Number 9005-65-6) were purchased from Sigma-Aldrich and used for the solution preparation. Analytically pure ethanol (EtOH) came from POCH Gliwice. The water used for the solution preparation was doubly distilled and deionized (Destamat Bi18E). Its resistance was equal to 18.2 × 106 Ω⋅m and the conductivity at T = 293 K was equal to 1.2 μS. The Q/Ru stock solution in EtOH was prepared dissolving the Q/Ru quantity to obtain the concentration in solution equal to 2 × 10−3 M (CQ or CRu). There was also prepared the aqueous stock solution of TX114/T80, where the surfactant concentration, C, was equal to 1 × 10−2 M. Then there were made the following mixtures: Q (CQ = 1 × 10−5 and 1 × 10−4 M) + TX114 (CTX114 = 1 × 10−6–1 × 10−2 M) Ru (CRu = 1 × 10−5 and 1 × 10−4 M) + TX114 (CTX114 = 1 × 10−6–1 × 10−2 M) Q (CQ = 1 × 10−5 and 1 × 10−4 M) + T80 (CT80 = 1 × 10−6–1 × 10−2 M) Ru (CRu = 1 × 10−5 and 1 × 10−4 M) + T80 (CT80 = 1 × 10−6–1 × 10−2 M) All the mixtures solution were prepared in the 100 mL glass flask wrapped with the aluminum foil, protecting flavonoids against the light. In addition, the quercetin and rutin solutions in water in the range of their concentration from 1 × 10−5 M to 1 × 10−4 M were prepared. The stock Q and Ru solutions were also used for preparation of quercetin and rutin layers on the polytetrafluoroethylene (PTFE) surface. First, the PTFE plates were washed with a nonionic detergent and next with methanol. Next there were placed twice in an ultrasonic bath in the Milli-Q water for 15 min. Then the plates were dried with warm air for 10 min. Purity of the plates was controlled by the measurement of the water contact angle. The flavonoid layers were prepared by immersing the PTFE in the Q/Ru stock solution for 24 h. For the advancing contact angle (θ) measurements on the obtained layers water, formamide and diiodomethane were used. Water was doubly distilled and deionized (Destamat Bi18E, Inkom Instruments, Warsaw, Poland). Its resistance was equal to 18.2 × 106 Ω⋅m and the conductivity at T = 293 K was equal to 1.2 μS. Formamide (>99.5%) and diiodomethane (>99%) were bought from Sigma-Aldrich. Measurements of the advancing contact angle were made using the sessile drop method, DSA30 measuring system (Krüss, Germany) in a thermostated chamber. The contact angle was measured for at least 20 drops and good reproducibility was found. In most cases the standard deviation for each set of values was less than 1.2°. The surface tension (γLV) measurements of the studied mixtures were made using the Krüss K100 tensiometer calibrated before the measurements. The calibration was made only at 293 K using water and methanol whose surface tension at this temperature was equal to 72.8 and 22.5 mN/m, respectively. The surface tension measurements for each concentration and composition of the mixtures were repeated at least ten times. The standard deviation of the results obtained from the measurements was ±0.1 mN/m and the uncertainty was in the range from 0.3% to 0.9%. The conductivity and pH measurements were performed using Mettler Toledo™ Seven Multi with the accuracy ±0.5%. All measurements were made at the temperature equal to 293, 303 and 313 K. 4. Conclusions The results obtained from the measurements and their thermodynamic analysis allow to draw many conclusions. The surface tension of quercetin and rutin are almost the same. There is an insignificant difference between their components and parameters. The contribution of the acid-base interactions to the flavonoids surface tension is insignificant, which explains their weak solubility in water. The surface tension of the flavonoids is comparable to that of the nonionic surfactants head. However, there are the great differences between the components and parameters of this tension. The surface tension isotherms of the aqueous solution of quercetin and rutin can be described by the Szyszkowski equation. The Szyszkowski equation can be also applied for the isotherms of the surface tension of the aqueous solution of mixtures of flavonoid + nonionic surfactant in which the concentration of flavonoid is constant but that of the nonionic surfactant variable. This fact suggests that the application of the Szyszkowski equation is broader than one would expect. However, for the Szyszkowski equation application the concentration of surface active agents only in the monomeric form in aqueous solution should be taken into account.The isotherms of this solution can be also described by the exponential function of the second order. The constants in this function depend on the components and parameters of the surface active agents surface tension, however, as so far it is difficult to express them by proper mathematical relationships. The surface tension isotherms of the aqueous solution of the flavonoid + nonionic surfactant mixture can be predicted by the Fainerman and Miller equation but not for all studied systems due to strong intermolecular interactions of the flavonoid and nonionic surfactant molecules in the mixed monolayer at the water-air interface. The maximal concentration of the sum of flavonoid and nonionic surfactants in the mixed monolayer is higher than in the monolayer of the nonionic surfactant in the absence of flavonoid, which suggests that the attractive interactions between the flavonoids and the nonionic surfactant molecules is greater than between the nonionic surfactant molecules. The mole fraction of flavonoid and nonionic surfactant in the mixed monolayer at the water-air interface can be determined based on the monolayer pressure of flavonoid in the absence of nonionic surfactant and the pressure of nonionic surfactant without flavonoid. The mole fraction of the nonionic surfactants in the mixed monolayer is smaller than in the bulk phase in the range of their concentrations in the bulk phase higher than CMC. The point of the intersection of the mole fraction isotherm of nonionic surfactant in the mixed monolayer with the mole fraction isotherm in the bulk phase occurs at the concentration in the bulk phase close to the CMC value determined from the surface tension isotherm of the aqueous solution of flavonoid + nonionic surfactant mixture. The CMC of the flavonoid and nonionic surfactant mixtures determined from the surface tension isotherm is insignificantly smaller than CMC of the nonionic surfactants in the absence of flavonoids. The CMC of the flavonoid + nonionic surfactant mixture depends only slightly on the temperature in the range from 293 to 313 K. The standard Gibbs free energy of the adsorption and micellization of the flavonoid + nonionic surfactant mixtures indicates that the tendency to adsorb flavonoids and nonionic surfactants mixture at the water-air interface is greater than that of the surfactants in the absence of flavonoids but the tendency to form micelles is comparable. The standard enthalpy of adsorption and micellization of the flavonoid + nonionic surfactant mixtures indicates that during the adsorption of the flavonoid + nonionic surfactant mixture the dehydration of its components in the micellization process is greater than in the adsorption except for the flavonoid + T80 mixture at the constant concentration of flavonoid equal to 1 × 10−4 M. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules27092842/s1, Table S1: The values of the contact angle (o) measured on the quercetin and rutin layer formed on PTFE surface for water, formamide and diiodomethane; Table S2: The values of the critical micelle concentration, CMC (M), for the flavonoid + TX114 and flavonoid + T80 mixtures at the temperature equal to 293, 303 and 313 K; Table S3:The values of the standard Gibbs free energy of adsorption (ΔGads0) for the flavonoid + TX114 and flavonoid + T80 mixtures at the water-air interface at the temperature equal to 293, 303 and 313 K; Table S4: The values of the standard Gibbs free energy of micellization (ΔGmic0) for the flavonoid + TX114 and flavonoid + T80 mixtures at the water-air interface at the temperature equal to 293, 303 and 313 K. Table S5: The values of the standard Gibbs free energy of adsorption (ΔGads0), the standard enthalpy of adsorption (ΔHads0) and the standard entropy of adsorption (ΔSads0) for quercetin, rutin, TX114 and T80 at the temperature equal to 293, 303 and 313 K; Table S6: The values of the standard enthalpy of adsorption (ΔHads0) (kJ/mol) and micellization (ΔHmic0) (kJ/mol) for the flavonoid + TX114 and flavonoid + T80 mixtures at the water-air interface at the temperature equal to 293, 303 and 313 K; Table S7: The values of the standard entropy of adsorption (ΔSads0) (kJ/molK) and micellization (ΔSmic0) (kJ/molK) for the flavonoid + TX114 and flavonoid + T80 mixtures at the water-air interface at the temperature equal to 293, 303 and 313 K; Table S8: The literature values of the CMC, ΔGmic0 (kJ/mol), ΔHmic0 (kJ/mol) and ΔSmic0 (kJ/molK) for TX114 and T80; Figure S1: A plot of the surface tension (γLV) of aqueous solutions of quercetin (a) and rutin (b) with TX114 and T80 (C = 10−5 M) vs. temperature (T). Curves 1 and 3 correspond to CQ/Ru = 10−5 M and curves 2 and 4 correspond to CQ/Ru = 10−4 M, respectively; Figure S2: A plot of the surface tension (γLV) of aqueous solutions of Q + TX114 at the constant Q concentration equal to 1 × 10−5 M vs. the logarithm of TX114 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S3: A plot of the surface tension (γLV) of aqueous solutions of Q + TX114 at the constant Q concentration equal to 1 × 10−4 M vs. the logarithm of TX114 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S4: A plot of the surface tension (γLV) of aqueous solutions of Q + T80 at the constant Q concentration equal to 1 × 10−5 M vs. the logarithm of T80 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S5: A plot of the surface tension (γLV) of aqueous solutions of Q + T80 at the constant Q concentration equal to 1 × 10−4 M vs. the logarithm of T80 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S6: A plot of the surface tension (γLV) of aqueous solutions of Ru + TX114 at the constant Ru concentration equal to 1 × 10−5 M vs. the logarithm of TX114 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S7: A plot of the surface tension (γLV) of aqueous solutions of Ru + TX114 at the constant Ru concentration equal to 1 × 10−4 M vs. the logarithm of TX114 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S8: A plot of the surface tension (γLV) of aqueous solutions of Ru + T80 at the constant Ru concentration equal to 1 × 10−5 M vs. the logarithm of T80 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S9: A plot of the surface tension (γLV) of aqueous solutions of Ru + T80 at the constant Ru concentration equal to 1 × 10−4 M vs. the logarithm of T80 concentration (C) at T = 293 K (a), 303 K (b) and 313 K (c). Points 1 correspond to the measured values. Curves 2, 3, 4, 5 and 6 correspond to the values calculated from Equations (2), (4), (6), (7) and independent adsorption, respectively; Figure S10: A plot of the constant y0 (a), A1 (b), t1 (c), A2 (d) and t2 (e) in Equation (4) for the Q + TX114 (curves 1 and 1′) and Q + T80 (curves 2 and 2′), T80 (curve 3) and TX114 (curve 4) vs. the temperature (T). Curves 1 and 2 correspond to the constant flavonoid concentration equal to 1 × 10−5 M, curves 1′ and 2′ to the concentration equal to 1 × 10−4 M; Figure S11: A plot of the constant y0 (a), A1 (b), t1 (c), A2 (d) and t2 (e) in Equation (4) for the Ru + TX114 (curves 1 and 1′) and Ru +T 80 (curves 2 and 2′), T80 (curve 3) and TX114 (curve 4) vs. the temperature (T). Curves 1 and 2 correspond to the constant flavonoid concentration equal to 1 × 10−5 M, curves 1′ and 2′ to the concentration equal to 1 × 10−4 M; Figure S12: A plot of the values of x2b (curve 1) and x2s at temperature equal to 293 K (curve 2), 303 K (curve 3) and 313 K (curve 4) for aqueous solutions of Q + TX114 at the constant Q concentration equal to 1 × 10−5 M (a) and 1 × 10−4 M (b) as well as Q + T80 at the constant Q concentration equal to 1 × 10−5 M (c) and 1 × 10−4 M (d) vs. the logarithm of surfactant concentration (C); Figure S13: A plot of the values of x2b (curve 1) and x2s at temperature equal to 293 K (curve 2), 303 K (curve 3) and 313 K (curve 4) for aqueous solutions of Ru + TX114 at the constant Ru concentration equal to 1 × 10−5 M (a) and 1 × 10−4 M (b) as well as Ru + T80 at the constant Ru concentration equal to 1 ×10−5 M (c) and 1 × 10−4 M (d) vs. the logarithm of surfactant concentration (C); Figure S14: A plot of the values of pH of the aqueous solutions of TX114 with quercetin (curves 1 and 2) and rutin (curves 3 and 4) at temperature equal to 293 K vs. the logarithm of surfactant concentration (C); Figure S15: A plot of the values of pH of the aqueous solutions of T80 with quercetin (curves 1 and 2) and rutin (curves 3 and 4) at temperature equal to 293 K vs. the logarithm of surfactant concentration (C); Figure S16: A plot of the surface concentration (Γ) of Q (curves 1′ and 1″), TX114/T80 (curves 2, 2′ and 2″) and the sum values for Q and TX114/T80 (curves 3, 3′ and 3″) calculated from Equation (9) vs. the logarithm of TX114/T80 concentration (C) at the constant Q concentration equal to 1 × 10−5 M ((a) and c)) and 1 × 10−4 M ((b) and (d)). Curves 1, 2 and 3 correspond to temperature equal to 293 K. curves 1′, 2′ and 3′ to 303 K and curves 1″, 2″ and 3″ to 313 K, respectively; Figure S17: A plot of the surface concentration (Γ) of Ru (curves 1′ and 1″), TX114/T80 (curves 2, 2′ and 2″) and the sum values for Ru and TX114/T80 (curves 3, 3′ and 3″) calculated from Equation (9) vs. the logarithm of TX114/T80 concentration (C) at the constant Ru concentration equal to 1 × 10−5 M ((a) and c)) and 1 × 10−4 M ((b) and (d)). Curves 1, 2 and 3 correspond to temperature equal to 293 K. curves 1′, 2′ and 3′ to 303 K and curves 1″, 2″ and 3″ to 313 K, respectively. Click here for additional data file. Author Contributions Conceptualization, A.T., K.S., A.Z. and B.J.; methodology, A.T. and K.S.; software, K.S.; validation, K.S., A.Z. and B.J.; formal analysis, K.S., A.Z. and B.J.; investigation, A.T. and K.S.; resources, A.T. and K.S.; data curation, A.T., K.S., A.Z. and B.J.; writing—original draft preparation, K.S., A.Z. and B.J.; Writing—Review & Editing A.T., K.S., A.Z. and B.J.; visualization, K.S., A.Z. and B.J.; supervision, B.J.; project administration, K.S., A.Z. and B.J.; funding acquisition, B.J. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A plot of the surface tension (γLV) of the aqueous solutions of quercetin (curves 1–3) and rutin (curves 1′–3′) vs. the logarithm of their concentration (log CQ and log CRu) at the temperatures equal to 293 (curves 1 and 1′), 303 (curves 2 and 2′) and 313 K (curves 3 and 3′), respectively. Figure 2 A plot of the surface tension (γLV) of the aqueous solutions of (a) Q + TX114 (CQ = 10−5 M), (b) Q + TX114 (CQ = 10−4 M), (c) Q + T80 (CQ = 10−5 M) and (d) Q + T80 (CQ = 10−4 M) vs. the logarithm of surfactant concentration (log C) at different temperatures equal to 293 (curve 1), 303 (curve 2), and 313 K (curve 3), respectively. Figure 3 A plot of the surface tension (γLV) of the aqueous solutions of (a) Ru + TX114 (CRu = 10−5 M), (b) Ru + TX114 (CRu = 10−4 M), (c) Ru + T80 (CRu = 10−5 M) and (d) Ru + T80 (CRu = 10−4 M) vs. the logarithm of surfactant concentration (log C) at different temperatures equal to 293 (curve 1), 303 (curve 2), and 313 K (curve 3), respectively. Figure 4 A plot of the specific conductivity (κ) of the aqueous solutions of (a) Q + TX114 (CQ = 10−5 M and 10−4 M), (b) Q + T80 (CQ = 10−5 M and 10−4 M), (c) Ru + TX114 (CRu = 10−5 M and 10−4 M) and (d) Ru + T80 (CRu = 10−5 M and 10−4 M) (d) vs. the logarithm of surfactant concentration (log C) at different temperatures equal to 293 (curve 1), 303 (curve 2), and 313 K (curve 3), respectively. molecules-27-02842-t001_Table 1 Table 1 The thermodynamic parameters for quercetin, rutin, TX114 and T80. Quercetin Rutin TX114 T80 Γmax (×10−6 mol/m2) T = 293 K 4.40 4.30 2.52 3.94 T = 303 K 4.30 4.15 2.45 3.81 T = 313 K 4.10 3.90 2.39 3.68 Amin (Å2) T = 293 K 37.73 38.61 65.89 42.14 T = 303 K 38.61 40.01 67.77 43.58 T = 313 K 40.50 42.57 69.47 45.12 Γ∞ (×10−6 mol/m2) 4.77 4.70 4.65 4.04 A0 (Å2) 34.81 35.33 35.71 41.10 Γmax/∞ 0.9224 0.9149 0.5419 0.9752 Occupied area (Å2) 24.42–131.65 35.33–240.4 35.70–115.73 35.70–51.12 41.10–475.10 41.10–96.05 Volume of one molecule (Å3) 456.15 832.99 856.10 1978.98 Molar volume (cm3/mole) 274.74 501.70 515.63 1192.54 Density (g/cm3) 1.1000 1.1100 1.2169 1.3881 1.0953 1.0580 1.0985 1.0600 Components and parameters of surface tension (mN/m) γLVLW 36.53 38.02 22.00 21.00 26.90 42.49 γLV+ 0.186 0.132 1.51 0.03 γLV− 10.57 13.26 48.75 55.71 γLVAB 2.80 22.65 17.16 2.59 γLV 39.33 40.67 39.16 45.08 Water-surfactant interfacial tension (mN/m) Water-tail - - 51.00 51.00 Water-head 18.50 15.45 −13.75 −20.12 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Panche A.N. Diwan A.D. Chandra S.R. Flavonoids: An overview J. Nutr. Sci. 2016 5 e47 10.1017/jns.2016.41 28620474 2. George V.C. Dellaire G. Rupasinghe H.P.V. Plant flavonoids in cancer chemoprevention: Role in genome stability J. Nutr. Biochem. 2017 45 1 14 10.1016/j.jnutbio.2016.11.007 27951449 3. Ginwala R. Bhavsar R. Chigbu D.I. Jain P. Khan Z.K. Potential role of flavonoids in treating chronic inflammatory diseases with a special focus on the anti-inflammatory activity of apigenin Antioxidants 2019 8 35 10.3390/antiox8020035 30764536 4. Ravishankar D. Rajora A.K. Greco F. Osborn H.M.I. Flavonoids as prospective compounds for anti-cancer therapy Int. J. Biochem. Cell. Biol. 2013 12 2821 2831 10.1016/j.biocel.2013.10.004 5. Kawai M. Hirano T. Higa S. Arimitsu J. Maruta M. Kuwahara Y. Ohkawara T. Hagihara K. Yamadori T. Shima Y. Flavonoids and related compounds as anti-allergic substances Allergol. Int. 2017 56 113 123 10.2332/allergolint.R-06-135 6. Manzoor M.F. Hussain A. Sameen A. Sahar A. Khan S. Siddique R. Aadil R.M. Xu B. Novel extraction, rapid assessment and bioavailability improvement of quercetin: A review Ultrason. Sonochem. 2021 78 105686 105701 10.1016/j.ultsonch.2021.105686 34358980 7. da Silva A.B. Coelho P.L.C. das Neves Oliveira M. Oliveira J.L. Amparo J.A.O. da Silva K.C. Soares J.R.P. Pitanga B.P.S. Dos Santos Souza C. de Faria Lopes G.P. The flavonoid rutin and its aglycone quercetin modulate the microglia inflammatory profile improving antiglioma activity Brain Behav. Immun. 2020 85 170 185 10.1016/j.bbi.2019.05.003 31059805 8. Salehi B. Machin L. Monzote L. Sharifi-Rad J. Ezzat S.M. Salem M.A. Merghany R.M. El Mahdy N.M. Kılıç C.S. Sytar O. Therapeutic Potential of Quercetin: New Insights and Perspectives for Human Health ACS Omega 2020 5 11849 11872 10.1021/acsomega.0c01818 32478277 9. Yang H. Yang T. Heng C. Zhou Y. Jiang Z. Qian X. Du L. Mao S. Yin X. Lu Q. Quercetin improves nonalcoholic fatty liver by ameliorating inflammation, oxidative stress, and lipid metabolism in db/db mice Phytother. Res. PTR 2019 33 3140 3152 10.1002/ptr.6486 31452288 10. Di Petrillo A. Orrù G. Fais A. Fantini M.C. Quercetin and its derivates as antiviral potentials: A comprehensive review Phytother. Res. PTR 2022 36 266 278 10.1002/ptr.7309 34709675 11. Ben Sghaier M. Pagano A. Mousslim M. Ammari Y. Kovacic H. Luis J. Rutin inhibits proliferation, attenuates superoxide production and decreases adhesion and migration of human cancerous cells Biomed. Pharmacother. 2016 84 1972 1978 10.1016/j.biopha.2016.11.001 27829548 12. Imani A. Maleki N. Bohlouli S. Kouhsoltani M. Sharifi S. Dizaj S.M. Molecular mechanisms of anticancer effect of rutin Phytother. Res. 2021 35 2500 2513 10.1002/ptr.6977 33295678 13. Luthria D.L. Optimization of extraction of phenolic acids from a vegetable waste product using a pressurized liquid extractor J. Funct. Foods 2012 4 842 850 10.1016/j.jff.2012.06.001 14. Samaram S. Mirhosseini H. Tan C.P. Ghazali H.M. Bordbar S. Serjouie A. Optimisation of ultrasound-assisted extraction of oil from papaya seed by response surface methodology: Oil recovery, radical scavenging antioxidant activity and oxidation stability Food Chem. 2015 172 7 17 10.1016/j.foodchem.2014.08.068 25442517 15. Neto A.O.W. da Silva D.C. Arruda G.M. da Hora L.F. Rodrigues M.A.F. Chemical study of the application of nonionic surfactants nonylphenol in delaying the acidizing reaction of carbonate matrices J. Dispers. Sci. Technol. 2021 1 1 8 10.1080/01932691.2021.1880932 16. Ravichandran V. Lee M. Nguyen Cao T.G. Shim M.S. Polysorbate-based drug formulations for brain-targeted drug delivery and anticancer therapy Appl. Sci. 2021 11 9336 10.3390/app11199336 17. Abbot V. Sharma P. Investigation of interactions between quercetin and Tween 80 through electrolyte induced thermodynamic approach Mat. Today: Proc. 2020 28 61 64 10.1016/j.matpr.2020.01.274 18. Dwivedi M. Blech M. Presser I. Garidel P. Polysorbate degradation in biotherapeutic formulations: Identification and discussion of current root causes Int. J. Pharm. 2018 552 422 436 10.1016/j.ijpharm.2018.10.008 30300706 19. Kerwin B.A. Polysorbates 20 and 80 used in the formulation of protein biotherapeutics: Structure and degradation pathways J. Pharm. Sci. 2008 97 2924 2935 10.1002/jps.21190 17973307 20. Thoduvayil S. Dhandapani G. Brahma R. Balaya R.D.A. Mangalaparthi K.K. Patel K. Kumar M. Tennyson J. Satheeshkumar P.K. Kulkarni M.J. Triton X-114 fractionated subcellular proteome of leptospira interrogans shows selective enrichment of pathogenic and outer membrane proteins in the detergent fraction Proteomics 2020 20 2000170 10.1002/pmic.202000170 21. Alibrahim M. Removal of toxic Eosin Y dye from water samples by cloud point extraction using Triton X-114 as nonionic surfactant Tensid. Surf. Deterg. 2020 57 326 331 22. Katsoyannos E. Gortzi O. Chatzilazarou A. Athanasiadis V. Tsaknis J. Lalas S. Evaluation of the suitability of low hazard surfactants for the separation of phenols and carotenoids from red-flesh orange juice and olive mill wastewater using cloud point extraction J. Sep. Sci. 2012 35 2665 2670 10.1002/jssc.201200356 22887931 23. Zdziennicka A. Szymczyk K. Krawczyk J. Jańczuk B. Activity and thermodynamic parameters of some surfactants adsorption at the water–air interface Fluid Phase Equilib. 2012 318 25 33 10.1016/j.fluid.2012.01.014 24. Zdziennicka A. Szymczyk K. Krawczyk J. Jańczuk B. Critical micelle concentration of some surfactants and thermodynamic parameters of their micellization Fluid Phase Equilib. 2012 322–323 126 134 10.1016/j.fluid.2012.03.018 25. Szymczyk K. Zdziennicka A. Jańczuk B. Adsorption and aggregation properties of some Polysorbates at different temperatures J. Sol. Chem. 2018 47 1824 1840 10.1007/s10953-018-0823-z 26. Jańczuk B. Szymczyk K. Zdziennicka A. Adsorption properties of hydrocarbon and fluorocarbon surfactants ternary mixture at the water-air interface Molecules 2021 26 4313 10.3390/molecules26144313 34299588 27. Jańczuk B. Zdziennicka A. Szymczyk K. González-Martin M.L. Prediction of aqueous solution surface tension of some surfactant mixtures and composition of their monolayers at the solution-air interface Coll. Interfaces 2022 5 53 10.3390/colloids5040053 28. Pérez-Rosés A. Risco E. Vila R. Peñalver P. Cañigueral S. Antioxidant activity of Tween-20 and Tween-80 evaluatedthrough different in-vitro tests J. Pharm. Pharmacol. 2014 67 666 672 10.1111/jphp.12369 25556861 29. Taraba A. Szymczyk K. Aggregation behavior of Triton X-114 and Tween 80 at various temperatures and concentrations studied by density and viscosity measurements J. Therm. Anal. Calorim. 2016 126 315 326 30. Taraba A. Szymczyk K. Properties of aqueous solutions of nonionic surfactants, Triton X-114 and Tween 80, at temperatures from 293 to 318K: Spectroscopic and ultrasonic studies Chem. Phys. 2017 483–484 96 102 31. Zdziennicka A. Krawczyk J. Szymczyk K. Jańczuk B. Macroscopic and microscopic properties of some surfactants and biosurfactants Int. J. Mol. Sci. 2018 19 1934 10.3390/ijms19071934 32. van Oss C.J. Constanzo P.M. Adhesion of anionic surfactants to polymer surfaces and low-energy materials J. Adhes. Sci. Technol. 1992 4 477 487 10.1163/156856192X00809 33. Jańczuk B. MéndezSierra A.M. González-Martín M.L. Bruque J.M. Wójcik W. Properties of Decylammonium Chloride and Cesium Perfluorooctanoate at interfaces and standard free energy of their adsorption J. Coll. Interface Sci. 1997 192 408 414 10.1006/jcis.1997.5054 9367563 34. Available online: https://www.chemicalbook.com/ChemicalProductProperty_US_CB8153566.aspx (accessed on 5 April 2022) 35. Available online: https://pubchem.ncbi.nlm.nih.gov/compound/5280343 (accessed on 5 April 2022) 36. Aizawa H. Morphology of polysorbate 80 (Tween 80) micelles in aqueous 1,4-dioxane solutions J. Appl. Cryst. 2009 42 592 596 10.1107/S002188980902295X 37. Amani A. York P. de Waard H. Anwar J. Molecular dynamics simulation of a polysorbate 80 micelle in water Soft Matter 2011 7 2900 2908 10.1039/c0sm00965b 38. Rosen M.J. Surfactants and Interfacial Phenomena 3rd ed. Wiley-Interscience New York, NY, USA 2004 34 178 39. Joos P. Thermodynamics of mixed monolayers Bull. Soc. Chim. Belg. 1967 76 591 600 10.1002/bscb.19670761105 40. van Oss C.J. Interfacial Forces in Aqueous Media Marcel Dekker New York, NY, USA 1994 41. van Oss C.J. Good R.J. Surface tension and the solubility of polymers and biopolymers: The role of polar and apolar interfacial free energies J. Macromol. Sci. Chem. 1989 26 1183 1203 10.1080/00222338908052041 42. van Oss C.J. Chaudhury M.K. Good R.J. Monopolar surfaces Adv. Coll. Interface Sci. 1987 28 35 64 10.1016/0001-8686(87)80008-8 43. Zdziennicka A. Szymczyk K. Krawczyk J. Jańczuk B. Some remarks on the solid surface tension determination from contact angle measurements Appl. Surf. Sci. 2017 405 88 101 10.1016/j.apsusc.2017.01.068 44. Szaniawska M. Szymczyk K. Zdziennicka A. Jańczuk B. Adsorption properties and composition of binary Kolliphor mixtures at the water–air interface at different temperatures Molecules 2022 27 877 10.3390/molecules27030877 35164143 45. Fainerman V.B. Miller R. Aksenenko E.V. Simple model for prediction of surface tension of mixed surfactant solutions Adv. Colloid Interface Sci. 2002 96 339 359 10.1016/S0001-8686(01)00088-4 11908794 46. Fainerman V.B. Miller R. Simple method to estimate surface tension of mixed surfactant solutions J. Phys. Chem. B 2001 105 11432 11438 10.1021/jp004179b 47. Rosen J.M. Hua X.Y. Surface concentrations and molecular interactions in binary mixtures of surfactants J. Colloid Interface Sci. 1982 86 164 172 10.1016/0021-9797(82)90052-2 48. Adamson W. Gast A.P. Physical Chemistry of Surfaces 6th ed. Wiley Interscience New York, NY, USA 1997 49. Djeradi H. Rahmouni A. Cheriti A. Antioxidant activity of flavonoids: A QSAR modeling using Fukui indices descriptors J. Mol. Model. 2014 20 2476 10.1007/s00894-014-2476-1 25311723 50. Zdziennicka A. Jańczuk B. Modification of adsorption, aggregation and wetting properties of surfactants by short chain alcohols Adv. Colloid Interface Sci. 2020 284 102249 10.1016/j.cis.2020.102249 32987295

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094648 ijms-23-04648 Article PAPPA Expression in Indeterminate Thyroid Nodules as Screening Test to Select Patients for Molecular Testing https://orcid.org/0000-0002-8573-4913 Marzocchi Carlotta 1† https://orcid.org/0000-0002-5741-295X Cantara Silvia 12*† Sagnella Alfonso 1 Castagna Maria Grazia 1 Wasniewska Malgorzata Gabriela Academic Editor Bossowski Artur Academic Editor 1 Department of Medical, Surgical and Neurological Sciences, University of Siena, Viale Bracci 1, 53100 Siena, Italy; carlottamarzocchi@libero.it (C.M.); alfonso.sagnella@student.unisi.it (A.S.); mariagrazia.castagna@unisi.it (M.G.C.) 2 Laboratory of Clinical and Traslational Research, AOU Siena, Viale Bracci 1, 53100 Siena, Italy * Correspondence: cantara@unisi.it; Tel.: +39-0577-585243 † These authors contributed equally to the work. 22 4 2022 5 2022 23 9 464808 4 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Pregnancy-associated plasma protein A (PAPPA) acts as an oncogene, and its expression is increased in multiple malignancies, including thyroid cancer. Molecular tests represent a useful tool in the management of indeterminate thyroid nodules; however, they are not conducted in all centers, and they contribute to increase the per-patient cost of nodule evaluation. In this study, we examined whether PAPPA expression could represent a promising new screening test in the management of indeterminate thyroid nodules. Toward this aim, PAPPA expression was evaluated in 107 fine needle aspiration cytologies (FNAC) belonging to Bethesda III–IV categories that had been sent to molecular biology to discriminate the nature of the nodules. We found that the PAPPA expression increased and showed an elevated sensitivity (97.14%) and negative predictive value (98%) in indeterminate cytological samples positive for mutations. The enhanced expression was not linked to a specific oncogene. Our findings demonstrated that assessing the PAPPA expression in indeterminate thyroid cytologies could represent a useful screening tool to select all patients that effectively need to be sent to molecular testing, thereby, leading to a potential cost reduction in the management of patients. PAPPA FNAC indeterminate thyroid nodules thyroid cancer molecular test ==== Body pmc1. Introduction Pregnancy-associated plasma protein A (PAPPA) is a metalloproteinase that interacts with insulin-like growth binding proteins (IGFBPs), especially IGFBP4, regulating proteolysis and bioavailability of insulin-like growth factor ligand 1 (IGF1) [1]. Circulating PAPPA represents a consolidated biomarker in combined first-trimester screening tests, allowing an early prenatal diagnosis of chromosomal abnormalities [2,3], preeclampsia [4] and intrauterine growth restriction risk [5]. In addition to pregnancy, PAPPA was found to be increased in several tumors, including thyroid cancer [6,7]. Studies have demonstrated that PAPPA acts as an oncogene by promoting cancer cells proliferation, migration and invasion [8]. In light of these data, PAPPA may be considered as an interesting potential target for the treatment of tumor progression [8]. We first demonstrated that PAPPA behaves as a promising diagnostic marker for differentiated thyroid cancer contributing to the pre-surgical classification of thyroid nodules according to the final histology [7]. Early diagnosis of thyroid cancer represents a priority as thyroid nodules are increasing in the general population in all countries [9]. The majority of thyroid nodules are benign hyperplastic nodules, and thyroid cancer is found in less than 10% [10]. Fine needle aspiration cytology (FNAC) represents the gold standard to discriminate benign from malignant nodules despite limitations due to inadequate or indeterminate samples [11]. Only about 10% to 30% and 25% to 40% of Bethesda categories III and IV (indeterminate cytologies), respectively are malignant at the final histology [12]. This means that a high proportion of patients with indeterminate FNAC will undergo unnecessary thyroid surgery. The discovery of genetic alterations in differentiated thyroid cancer prompted the search of somatic mutations in material obtained by FNAC, aimed to increase the diagnostic accuracy of traditional cytology and to help clinicians in the appropriate clinical decision [13]. To further increase the sensitivity and specificity over the years, other markers (i.e., microRNAs, immunocytochemistry and proteomics markers) have been proposed together with molecular test; however, none of these have provided adequate results or been introduced in clinical practice [14]. Molecular testing has actually evolved from single mutation evaluation to more broad genetic panels conducted using advanced technologies, such as next generation sequencing [15]. As a result, molecular testing must be performed in specialized laboratories and by qualified professionals; however, most centers lack facilities and the appropriate expertise. In our study, we aimed to evaluate whether the expression of PAPPA in indeterminate FNAC could be used as a screening tool to select patients to be sent for advanced molecular diagnostic testing. 2. Results 2.1. Molecular Characterization of FNAC A seven-gene panel of mutations was investigated as 107 FNAC samples. From the analysis, 35 out of 107 (32.7%) samples were found positive for one mutation, and 72 out of 107 (67.3%) were negative. RAS oncogenes were more frequently mutated (17/35, 48.6%) with 9/17 (52.9%) NRAS, 7/17 (41.2%) HRAS and 1/17 (5.9%) KRAS. BRAF mutation(s) was found in 13/35 cases (37.1%) with 12/13 (92.3%) BRAF V600E and 1/13 (7.7%) BRAF K601E. Four/35 (11.4%) cases harbored RET/PTC1 rearrangements, and only 1/35 cases (2.9%) showed PAX8/PPARγ rearrangement. No RET/PTC2 or RET/PTC3 rearrangements were found. The results of the molecular biology tests are summarized in Table 1. 2.2. PAPPA Expression Increased in Positive Mutations Cytological Samples PAPPA mRNA expression was analyzed by qPCR in 107 cytological samples characterized for mutations. PAPPA was significantly higher (p < 0.0001) in cytological specimens positive for mutations (n = 35) compared to negative cases (n = 72) (Figure 1a). The group of positive mutations consists of 27/35 (77.1%) samples belonging to Bethesda categories III–IV and 8/35 (22.9%) to Bethesda categories V–VI. These latest categories were included for the comparison of all samples regarding suspicion for/malignancy. Cytological specimens negative for mutations were all Bethesda categories III–IV (Figure 1a). To verify if the Bethesda V–VI samples with positive mutations could influence statistical significance, the same analysis was conducted excluding them. Again, considering only samples belonging to Bethesda categories III–IV positive for mutations (n = 27), PAPPA levels were significantly increased (p < 0.0001) compared to Bethesda categories III–IV negative for mutations (Figure 1b). The extent of PAPPA expression was similar between Bethesda III–IV positive for mutations and Bethesda V–VI (n = 8) (p = 0.49) (Figure 1c). Finally, no correlations were found between PAPPA levels and specific gene alterations (p = 0.44) (Figure 1d). 2.3. PAPPA Expression Showed a High Sensitivity and Negative Predictive Value to Identify Nodules with Genetic Alterations We evaluated whether PAPPA expression could be used as a potential biomarker to screen nodules with oncogene mutations respect to those with negative mutations. As shown in Figure 2a by the receiver operating characteristic (ROC) curve area of 90.1% (95% confidence interval: 84.5–95.6%; p < 0.0001), PAPPA mRNA levels displayed a high degree of diagnostic accuracy to distinguish cytologies that were positive for mutations from those negative for mutations. Our criterion for evaluating the optimal threshold of the test was to maximize the sensitivity and minimize false negative results in order to correctly select patients to be sent to molecular testing. The calculated Youden cut-off of 0.02732 showed a sensitivity of 97.14% and a specificity of 69.44% with an overall accuracy of 78.5%, a negative predictive value (NPV) of 98% and a positive predictive value of PPV of 60.7% (Figure 2b). 3. Discussion The majority of thyroid nodules are benign, and approximately 10% of them are cancerous [10]. In this view, it is very important for the pre-surgical diagnosis to distinguish benign from malignant thyroid nodules in order to limit surgical treatment only to the malignant/suspicious ones. Currently, FNAC represents the “gold standard” for the differential diagnosis of thyroid nodules. In general, in expert hands, it is associated with good specificity and sensitivity [11]. However, this procedure has some limitations related to inadequate sampling (2–16%) or to the difficulty to discriminate follicular lesions (5–20%). Among the indeterminate samples, only a proportion are malignant at the final histology [12]. The discovery of genetic alterations specific for differentiated thyroid cancer may provide molecular markers to be searched for in the material obtained by FNAC, thus, increasing the diagnostic accuracy of traditional cytology. Several molecular tests have been introduced in the clinical routine, such as the Gene Expression Classifier (GEC), which recognizes benign lesions on the basis of an expression pattern of mRNA [16], a seven-gene mutational panel [17,18] and targeted next-generation sequencing (tNGS) [19,20,21]. Mutation panels aimed to identified malignancies must include at least BRAF, RAS point mutations and RET/PTC and PAX8/PPARγ rearrangements. “Homemade” methods, including PCR with final sequencing or commercial kits based on real time PCR (qPCR), are available. The use of tNGS with larger panels of genes is an alternative method capable to attain a NPV of 95% or more and a high PPV and sensitivity [13]. Although molecular tests represent a useful tool in the management of indeterminate nodules [13], they are not conducted in all centers and contribute to increasing the cost per-patient for nodule evaluation. In this optic, to optimize personalized medical care and management algorithms, PAPPA expression on FNAC could represent a promising, new, quick, cheap and easy screening tool for correctly selecting patients with indeterminate cytology in which molecular investigations are helpful (Figure 3). PAPPA mRNA levels are increased in positive for mutation cytologies, and, with a calculated Youden cut-off of 0.02732, PAPPA reached a sensitivity of 97.14% with a negative predictive value of 98%, thereby, strengthening the results of our previous work [7]. The study has a few limitations since histological confirmation was available only in a small subgroup of thyroid nodules. Indeed, histology was available in 8/27 Bethesda III–IV samples positive for mutations. We have to consider that we are a reference center for the management of indeterminate lesions, and we received samples for the genetic analysis from several endocrinology units widespread for Italy. Not all patients are submitted to surgery in our clinic. However, the correlation between histology and PAPPA expression was coherent as we already published in our previous work [7]. Furthermore, all patients followed in our center with indeterminate nodule(s) negative for mutations (n = 72) preferred a conservative approach, and, due to the lack of clinical evidence, these patients were not submitted to surgery. In the follow up period, nodules did not increase in diameter, and the ultrasound characteristics, in terms of the echogenicity, presence/absence of microcalcifications and margins, remained the same (data not shown). However, the study has several strengths, such as a standardized management in the same institution with detailed information regarding the long term follow-up of thyroid nodules not submitted to surgery. Finally, to our knowledge, this is the first study that evaluated the usefulness of a screening test in selecting indeterminate thyroid nodules worthy of molecular analysis. Our preliminary results seem to suggest that PAPPA expression can be performed on indeterminate FNAC before the molecular tests in order to identify patients at risk of having cancer and that will benefit from genetic analysis. The introduction of this test in the practice could reduce the costs for the management of indeterminate lesions. Nevertheless, our results need to be confirmed in a larger series of indeterminate thyroid nodules characterized for mutations. 4. Materials and Methods 4.1. Patients This study retrospectively analyzed 107 consecutive thyroid nodules belonging to 104 patients who underwent to FNAC from 2015 to 2021 and of which the cytological material was still available in our bank. Our cohort of patients consist of 84 females (80.8%) and 20 males (19.2%). Thyroid cytopathologies were reported using the Bethesda System. We found that 79/107 (73.8%) were Bethesda III, 20/107 (18.7%) were Bethesda IV, and 8/107 (7.5%) were Bethesda V–VI. Only 15 patients underwent thyroid surgery. At the final histology, one nodule Bethesda III was found with adenoma, seven Bethesda IV were found to be malignant (one hurtle, one follicular thyroid cancer (FTC) and three papillary thyroid cancers (PTC), two were PTC follicular variant (PTCFV)), and all Bethesda V–VI were confirmed thyroid cancers (seven PTC and one PTCFV). Informed consent was signed by each patient enrolled in the study, and the study was approved from our local Ethical Committee (Ethics Committee of Regione Toscana, Area Vasta Sud Est, AOUS. Protocol ID: 10167). 4.2. RNA and DNA Isolation from Cytological Material Cytological material, achieved after the fine-needle aspiration biopsy procedure, was preserved in two aliquots of 150 µL/each of RNAprotect Cell Reagent (Qiagen, Hilden, Germany) before RNA and DNA extraction. RNA and DNA were isolated using an RNeasy mini kit (Qiagen, Hilden, Germany) and QIAamp DNA blood mini kit (Qiagen, Hilden, Germany), respectively, following the manufacturer’s instructions. The nucleic acid quantity and quality were assessed using NanoDrop One (Thermo Scientific, Waltham, MA, USA). 4.3. Oncogene Mutations Analysis All samples were genotyped using a qPCR procedure. Specifically, RET/PTC1, RET/PTC2, RET/PTC3 and PAX8/PPARG rearrangements were evaluated using RNA with a EasyPGX® ready THYROID Fusion kit (Diatech Pharmacogenetics, Jesi, Italy). Point mutations were searched on DNA at codons 12,13 (exon 2) and 61 (exon 3) of KRAS, NRAS and HRAS genes, and at codons 600/601 of BRAF gene using a EasyPGX® ready THYROID kit (Diatech Pharmacogenetics, Jesi, Italy). Samples were run on the thermal cycler EasyPGX qPCR instrument 96 (Diatech Pharmacogenetics, Jesi, Italy), and the data were analyzed with the “EasyPGX Analysis Software” (Diatech Pharmacogenetics, Jesi, Italy). 4.4. PAPPA Evaluation by Quantitative Real Time PCR Two-hundred nanograms of RNA for each sample were retrotranscribed with M-MuLV-RH First Stand cDNA Synthesis Kit (Experteam, Venice, Italy). The expression levels of PAPPA were evaluated with qPCR using FastStart Essential DNA Green Master Mix (Roche, Basilea, Switzerland) on the Rotor-Gene Q real time PCR (Qiagen, Hilden, Germany). Each sample was run in triplicate and normalized against actin (ACTB, Eurofins, Luxemburg, Luxemburg). The quantification of the PAPPA expression levels was determined using the 2-ΔCT method. The specific primers were PAPPA PF: 5′-TGAATCTGAGCAGCACATTG-3′ and PR: 5′-CATCGTCTTCCAAGCACTTC-3′; and ACTB PF: 5′-CACCAACTGGGACGACAT-3′ and PR: 5′-ACAGCCTGGATAGCAACG-3′. 4.5. Statistical Analysis All statistical analyses were conducted using the software GraphPad Prism version 5. A value of p < 0.05 was considered to be statistically significant. For the qPCR analysis, the normality of the data was assessed using the Shapiro–Wilk test. Statistical differences in the PAPPA mRNA levels were verified using the two tailed Mann–Whitney U test to compare two groups and by the Kruskal–Wallis H test, followed by Dunn’s test, to compare two or more independent groups. The accuracy of the PAPPA mRNA expression as a diagnostic test was evaluated by the ROC curve and the AUC. Author Contributions Conceptualization, C.M. and S.C.; methodology, C.M. and S.C.; formal analysis, C.M. and S.C.; data curation, C.M. and A.S.; writing—original draft preparation, C.M. and S.C.; writing—review and editing, M.G.C.; funding acquisition, M.G.C. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Regione Toscana, Area Vasta Sud Est, Azienda Ospedaliera universitaria Senense (protocol code 10167l). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Pregnancy-associated plasma protein A (PAPPA) expression mRNA levels in cytological samples. (a) PAPPA expression in Bethesda III–IV with negative mutations (n = 72) compared to Bethesda III–IV-V–VI with positive mutations (n = 35) samples. p < 0.0001 by the Mann–Whitney U test; (b) PAPPA expression in Bethesda III–IV with negative mutations (n = 72) compared to Bethesda III–IV with positive mutations (n = 27) samples. p < 0.0001 by the Mann–Whitney U test; (c) Comparison of PAPPA expression in positive for mutations samples belonging to Bethesda categories III–IV (n = 27) and V–VI (n = 8). p = 0.49 by the Mann–Whitney U test; (d) PAPPA mRNA expression stratified according with the specific gene mutations in BRAF (n = 13), RAS (n = 17), RET (n = 4) and PAX8 (n = 1). p = 0.44 by the Kruskal–Wallis test. Figure 2 Diagnostic performance of the PAPPA mRNA expression levels in 107 cytological samples. (a) Receiver operating characteristic (ROC) curve and related area under the curve (AUC) of PAPPA expression to discriminate cytological samples positive for seven-gene panel. (b) The sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) of PAPPA expression with the cut off set at 0.02732. Abbreviations: TP, True positive; TN, true negative; FN, false negative; and FP, false positive. Figure 3 Classic management algorithm for indeterminate FNAC and the one proposed with the use of PAPPA mRNA expression as screening test. (a) Management algorithm for indeterminate thyroid nodules advocated by major societal guidelines. (b) Proposed management algorithm for indeterminate thyroid nodules introducing a PAPPA expression cut-off as new screening tool to select patients to be sent to molecular testing. ijms-23-04648-t001_Table 1 Table 1 Point mutations and rearrangements found in 35 cytological samples. Gene Cases (%) Oncogenic Alteration Cases (%) BRAF 13/35 (37.1%) BRAF V600E BRAF K601E 12/13 (92.3%) 1/13 (7.7%) RAS NRAS 9/17 (52.9%) 17/35 (48.6%) HRAS 7/17 (41.2%) KRAS 1/17 (5.9%) RET 4/35 (11.4%) RET/PTC1 4/4 (100%) PAX8 1/35 (2.9%) PAX8/PPARγ 1/1 (100%) Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hjortebjerg R. IGFBP-4 and PAPP-A in normal physiology and disease Growth Horm. IGF Res. 2018 41 7 22 10.1016/j.ghir.2018.05.002 29864720 2. Spencer K. Ong C.Y. Liao A.W. Nicolaides K.H. The influence of parity and gravidity on first trimester markers of chromosomal abnormality Prenat. Diagn. 2000 20 792 794 10.1002/1097-0223(200010)20:10<792::AID-PD914>3.0.CO;2-5 11038455 3. Shiefa S. Amargandhi M. Bhupendra J. Moulali S. Kristine T. First Trimester Maternal Serum Screening Using Biochemical Markers PAPP-A and Free β-hCG for Down Syndrome, Patau Syndrome and Edward Syndrome Indian J. Clin. Biochem. 2013 28 3 12 10.1007/s12291-012-0269-9 24381414 4. Luewan S. Teja-Intr M. Sirichotiyakul S. Tongsong T. Low maternal serum pregnancy-associated plasma protein-A as a risk factor of preeclampsia Singap. Med. J. 2018 59 55 59 10.11622/smedj.2017034 5. Antsaklis P. Fasoulakis Z. Theodora M. Diakosavvas M. Kontomanolis E.N. Association of Low Maternal Pregnancy-associated Plasma Protein A with Adverse Perinatal Outcome Cureus 2019 11 e4912 10.7759/cureus.4912 31423389 6. Guo Y. Bao Y. Guo D. Yang W. Pregnancy-associated plasma protein a in cancer: Expression, oncogenic functions and regulation Am. J. Cancer Res. 2018 8 955 963 30034934 7. Marzocchi C. Capezzone M. Sagnella A. Cartocci A. Costantini M.C. Brindisi L. Mancini V. Cantara S. Castagna M.G. Pregnancy-associated plasma protein A mRNA expression as a marker for differentiated thyroid cancer: Results from a “surgical” and a “cytological” series J. Endocrinol. Investig. 2022 45 369 378 10.1007/s40618-021-01655-9 34350538 8. Conover C.A. Oxvig C. PAPP-A and cancer J. Mol. Endocrinol. 2018 61 T1 T10 10.1530/JME-17-0236 29844094 9. Guth S. Theune U. Aberle J. Galach A. Bamberger C.M. Very high prevalence of thyroid nodules detected by high frequency (13 MHz) ultrasound examination Eur. J. Clin. Investig. 2009 39 699 706 10.1111/j.1365-2362.2009.02162.x 19601965 10. Wong R. Farrell S.G. Grossmann M. Thyroid nodules: Diagnosis and management Med. J. Aust. 2018 209 92 98 10.5694/mja17.01204 29996756 11. Haugen B.R. Alexander E.K. Bible K.C. Doherty G.M. Mandel S.J. Nikiforov Y.E. Pacini F. Randolph G.W. Sawka A.M. Schlumberger M. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer Thyroid 2016 26 1 133 10.1089/thy.2015.0020 26462967 12. Durante C. Grani G. Lamartina L. Filetti S. Mandel S.J. Cooper D.S. The Diagnosis and Management of Thyroid Nodules: A Review JAMA 2018 319 914 924 10.1001/jama.2018.0898 29509871 13. Paschke R. Cantara S. Crescenzi A. Jarzab B. Musholt T.J. Sobrinho Simoes M. European Thyroid Association Guidelines regarding Thyroid Nodule Molecular Fine-Needle Aspiration Cytology Diagnostics Eur. Thyroid J. 2017 6 115 129 10.1159/000468519 28785538 14. Cantara S. Marzocchi C. Pilli T. Cardinale S. Forleo R. Castagna M.G. Pacini F. Molecular Signature of Indeterminate Thyroid Lesions: Current Methods to Improve Fine Needle Aspiration Cytology (FNAC) Diagnosis Int. J. Mol. Sci. 2017 18 775 10.3390/ijms18040775 15. Khan T.M. Zeiger M.A. Thyroid Nodule Molecular Testing: Is It Ready for Prime Time? Front. Endocrinol. 2020 11 590128 10.3389/fendo.2020.590128 16. Alexander E.K. Schorr M. Klopper J. Kim C. Sipos J. Nabhan F. Parker C. Steward D.L. Mandel S.J. Haugen B.R. Multicenter clinical experience with the Afirma gene expression classifier J. Clin. Endocrinol. Metab. 2014 99 119 125 10.1210/jc.2013-2482 24152684 17. Cantara S. Capezzone M. Marchisotta S. Capuano S. Busonero G. Toti P. Di Santo A. Caruso G. Carli A.F. Brilli L. Impact of proto-oncogene mutation detection in cytological specimens from thyroid nodules improves the diagnostic accuracy of cytology J. Clin. Endocrinol. Metab. 2010 95 1365 1369 10.1210/jc.2009-2103 20130073 18. Bardet S. Goardon N. Lequesne J. Vaur D. Ciappuccini R. Leconte A. Monpeyssen H. Saguet-Rysanek V. Clarisse B. Lasne-Cardon A. Diagnostic and prognostic value of a 7-panel mutation testing in thyroid nodules with indeterminate cytology: The SWEETMAC study Endocrine 2021 71 407 417 10.1007/s12020-020-02411-4 32638211 19. Nikiforov Y.E. Carty S.E. Chiosea S.I. Coyne C. Duvvuri U. Ferris R.L. Gooding W.E. Hodak S.P. LeBeau S.O. Ohori N.P. Highly accurate diagnosis of cancer in thyroid nodules with follicular neoplasm/suspicious for a follicular neoplasm cytology by ThyroSeq v2 next-generation sequencing assay Cancer 2014 120 3627 3634 10.1002/cncr.29038 25209362 20. Nikiforova M.N. Mercurio S. Wald A.I. Barbi de Moura M. Callenberg K. Santana-Santos L. Gooding W.E. Yip L. Ferris R.L. Nikiforov Y.E. Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules Cancer 2018 124 1682 1690 10.1002/cncr.31245 29345728 21. Nikiforov Y.E. Baloch Z.W. Clinical validation of the ThyroSeq v3 genomic classifier in thyroid nodules with indeterminate FNA cytology Cancer Cytopathol. 2019 127 225 230 10.1002/cncy.22112 30811896

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091077 animals-12-01077 Article Social Box: Influence of a New Housing System on the Social Interactions of Stallions When Driven in Pairs https://orcid.org/0000-0002-6259-2377 Gmel Annik Imogen Zollinger Anja Wyss Christa Bachmann Iris https://orcid.org/0000-0002-7988-6929 Briefer Freymond Sabrina * Wickens Carissa Academic Editor Hartmann Elke Academic Editor Agroscope, Swiss National Stud Farm, Les Longs Prés, CH-1580 Avenches, Switzerland; annik.gmel@agroscope.admin.ch (A.I.G.); anja.zollinger@agroscope.admin.ch (A.Z.); christa.wyss@agroscope.admin.ch (C.W.); iris.bachmann@agroscope.admin.ch (I.B.) * Correspondence: sabrina.briefer@agroscope.admin.ch; Tel.: +41-(0)58-482-61-01 21 4 2022 5 2022 12 9 107728 2 2022 16 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary In order to improve the housing conditions of stallions in individual boxes, we tested a so-called “social box” allowing increased physical contact between neighbouring horses. This study aimed at investigating whether housing stallions in social boxes potentially changes their behaviour during carriage driving. We hypothesised that the stay in social boxes would decrease the number of unwanted social interactions when driven in pairs. Eight Franches-Montagnes breeding stallions were observed when driven in pairs with a “neutral” stallion housed in a so-called “conventional box”, strongly limiting physical contact. They were driven on a standardised route over the course of four days before, during, and after being housed in a social box. The behaviours of the pairs and the interventions of the groom and the driver during the test drives were assessed live and using video recordings. The results showed that the stallions performed more social interactions during the driving test before being housed in social boxes and that these interactions decreased over the four days. This suggests that being housed in social boxes decreased the social behaviour of stallions while driven in pairs. Another important factor in reducing unwanted social interactions of stallions during carriage driving appears to be the consistency of the driver and the groom in their demands to teach the stallions that social interactions are unwanted while being driven in pairs. Other effects, such as habituation to the test conditions and the pairing, could not be assessed here and represent a limitation of our study. Abstract In order to improve the housing conditions of stallions in individual boxes, we tested a so-called “social box” allowing increased physical contact between neighbouring horses. This study investigated whether housing stallions in social boxes changes the number of social interactions during carriage driving. We hypothesised that the stay in social boxes would decrease the number of unwanted social interactions between stallions when driven in pairs. Eight Franches-Montagnes breeding stallions were observed when driven in pairs with a “neutral” stallion housed in a so-called “conventional box”, strongly limiting physical contact. They were driven on a standardised route over the course of four days before, during, and after being housed in social boxes. The type and frequency of behaviours of the pairs and the interventions of the groom and the driver during the test drives were assessed live and using video recordings. Results from linear mixed-effect models show that unwanted social interactions decreased during and after the stallions were housed in the social box (p < 0.001). Stallions’ interactions also decreased over the four days (p < 0.01), suggesting a habituation to the test conditions by learning not to interact, or by subtly settling dominance. The social box tended to decrease unwanted social behaviours of stallions driven in pairs and could therefore be used as an environmental enrichment for horses. stallions driving individual housing social interactions welfare ==== Body pmc1. Introduction Most wild or feral living equids are gregarious, foraging animals living in harem or bachelor bands [1,2], and the domestic horse, Equus caballus, has the same ethological need for social contacts with conspecifics [3,4]. However, current housing systems that keep horses in individual stabling tend to strongly limit natural behaviour patterns, such as foraging, locomotor behaviour, and social interactions [5], leading to an increase of stereotypic behaviour in horses housed in sub-optimal conditions [6]. While there are some indications that group housing would potentially improve animal welfare, and despite it being more cost effective [7], a large proportion of horses, and stallions especially, are still mainly kept in individual housing systems. This is partly because many owners perceiving group housing as a potential risk for injuries due to negative interactions between horses, and between stallions in particular [4,8,9]. However, under natural conditions, young wild and feral stallions live together in a bachelor band before establishing their own harem band [8]. Negative social behaviours, such as fights, threats, and agonistic behaviours (avoidance and submissive behaviour), as well as positive social behaviours, such as play fighting and allogrooming, were all observed in stallion bands [9,10,11,12]. Under natural conditions, real fights and injuries due to social interactions are rare, and mostly avoided through ritualised behaviours, settling dominance between horses [9,11,13]. Social contacts are actually essential and play a great role in reducing conflicts and help building a stable hierarchy among the group [14]. Consequently, keeping stallions together has been shown to be possible at least on pasture: the stallions showed mainly ritual and agonistic interactions during the period of integration into the group, and affiliative behaviours increased over time whilst the amount of agonistic interactions decreased [9]. Nonetheless, it is not always possible to keep horses in a group on pasture, for various other practical reasons, such as a lack of space in countries with limited agrarian surfaces, or conversely, a considerable risk of obesity and laminitis due to high-energy grassland pastures. Therefore, adaptations of individual housing systems appear to represent a reasonable compromise between practical constraints and an increase of the possibility for social tactile interactions. Allowing horses to have more social interactions in their stables may also have positive consequences on their behaviour during training. Previous studies reported increased aggressiveness between horses after social deprivation, especially during ridden training sessions [13,15,16], which could be explained by social frustration and an impairment in social skills induced by limited social contacts between horses [4,17,18]. One can assume that negative social interactions are of particular concern to equestrian disciplines using several horses simultaneously, such as carriage driving. However, to our knowledge, no studies have looked at the potential interactions between horses during carriage driving so far. This equestrian discipline requires a driver (holding the reins), one or more grooms holding the horses while the driver gets on or off the carriage, and standing on the carriage behind the driver during the drive, as well as one, two, or four horses [19]. In practice, for driving, pairs are often chosen according to affinity. However, interactions between horses while driving can be dangerous for both horses and drivers, which is why horses are especially trained not to interact while they are hitched to a carriage in pairs. This is to ensure that the horses are attentive to the driver’s and the groom’s indications, and not to the other horse. Indeed, the forcibly shared personal space (<1 m) could provoke the horses to seek interactions, in order to settle inter-equine conflicts or to play, and ignore human instructions, which might lead to accidents. One essential aim of the driver and grooms is therefore to decrease the number of interactions between horses. This factor is the responsibility of the driver and groom to remain consistent in their demands, by punishing interactions right after they occur, and/or rewarding the absence of interactions, according to learning theory [20]. However, despite their training, interactions between horses may still happen. Another solution could be to decrease the desire for interactions between driven horses by allowing more social interactions in the stables. With the aim to test a new type of individual housing system, Agroscope evaluated the effect on the behaviour and injury prevalence of a so called “social box” for horses, which allows increased physical contact between the neighbouring stallions by passing their head, neck and/or limbs through vertical bars spaced at 30 cm [21]. The aim of the present study was to investigate whether social interactions in stallions driven in pairs depended on the housing conditions they were living in, i.e., whether the social box potentially might change the social behaviour of Franches-Montagnes stallions when driven in pairs. For the purpose of this study, we built a strong behavioural methodology specifically to measure social interactions during driving sessions. We hypothesise that interactions during the driving exercises would decrease between stallions kept in a social box, due to the possibility for more social interactions in the stables and therefore less frustration-related aggressive behaviours during forced proximity with another stallion at work. 2. Materials and Methods This study was carried out from October 2014 to February 2015 at the Swiss National Stud Farm (“SNSF”) in Avenches, Switzerland, in full compliance with national rules and regulations; under the permit number VD 2810.a. 2.1. Animals For this study, 10 Franches-Montagnes breeding stallions owned by the SNSF were used (mean age ± SD = 8.60 ± 3.17; range 4–14 years). The horses were housed in individual boxes on straw litter and were fed hay and concentrate three times per day (7:00 a.m., 11:00 a.m., 16:00 p.m.). Water was available ad libitum. Horses were exercised 5–6 times a week. During their initial training at 3 years old, all the stallions were ridden and driven to pass the Franches-Montagnes stallion-licensing test. However, after initial training, not all horses participating in this study were still driven regularly. Following legal requirements in Switzerland, all stallions had been socialised in groups after weaning until they arrived as three-year-olds at the SNSF, but extensive tactile contact was limited thereafter due to current housing conditions in individual boxes. 2.2. Experimental Housing Facility All the stables at the SNSF consisted of two rows of four (9.3 m2) boxes facing each other and separated by a corridor of 3 m in width. In the so called “conventional box”, the partition between two boxes consisted of a lower solid wooden part (1.40 m high) and an upper part (another 1.15 m high) with vertical metal bars spaced at 5 cm, allowing visual and olfactory contact but strongly limiting tactile contact. In the so called “social box”, the partition between two boxes consisted of one part with vertical metal bars (from the ground to a height of 2.55 m) spaced at 30 cm allowing the horses to pass their head, neck, and legs to the adjacent box. The second part of the partition was solid, allowing the horses to visually isolate themselves from the neighbouring horse if they wanted to [21]. Each stallion had direct contact with only one neighbour. Each set of two consecutive social boxes was then separated from the next set of social boxes by an opaque partition. 2.3. Experimental Design This investigation was part of a large study investigating physical and behavioural welfare parameters in breeding stallions when housed in individual boxes allowing physical contact [21]. The tested stallions remained for 4 weeks in a conventional box next to their newly assigned neighbour, then spent 4 weeks in the social box, and another 8 weeks in a conventional box with the same neighbour. To assess whether the stay in a social box was influencing the social behaviour of the stallions during training, eight test stallions were observed driven in pairs with alternatively one of two stallions “neutral” to the treatment. The neutral stallions had never lived in a social box and were housed in conventional boxes in an adjacent barn, with visual, olfactory, and strongly limited tactile contact with other horses (not included in the study). The driven pairs were observed on four days in a row (during four distinct test drives) the week before the test stallions were integrated into a social box (before), the fourth week of housing in the social box (during), and the eighth week after returning from the stay in the social box to a conventional box (after), (Figure 1). Each driven pair acted as its own control. There were only four social boxes in total, so that the eight horses were randomly divided into two groups of four (group A and B), but the exact same timeline was followed in both groups. 2.4. Test Drive Procedure The test drive was composed of three distinct parts: the hitching (putting the stallions in front of the carriage and getting ready for the drive), the actual driving sequence, and the unhitching (releasing the stallions from the carriage) (Figure 1). The route was established beforehand and remained standardised for all drives during the study: the total route included one stop of 10 s, five stops of 30 s, two stops of two minutes and one stop of five minutes. The pace was mostly walk and some trot (no canter). Mean time ± SD per test drive was 38.90 ± 3.03 min. Each test stallion was driven twice with each neutral stallion, except under specific circumstances such as an unexpected lameness or colic (horse 2, horse 3, and horse 7, see Table 1). As the neutral horses performed two test drives, the order of the test horse was defined so that each test horse was hitched once on the first, and once the second drive of each neutral horse. The stallions were hitched with an English collar to a marathon cart. The bridle was equipped with a straight bar elbow bit and half-cup blinkers. Both driver and groom were equine professionals. The driver was not a collaborator of the SNSF, did not know the stallions beforehand, and was blind to the treatment. The driver was instructed to act consistently over the course of the study, i.e., the interventions (use of rein, whip, or voice) were supposed to be adequate to the intensity of the interactions between the stallions. However, he was instructed not to specifically anticipate and hinder interactions before they occurred. During hitching, the groom had to remain in front of the pair until the start of the driving sequence. The groom was also instructed not to hinder interactions beforehand, i.e., not holding the stallions’ reins during hitching unless the stallions were moving the carriage before the beginning of the driving session. From the driver’s perspective, the test stallion was always hitched on the left and the neutral stallion on the right-hand side. The driver and the observer were the same for all test drives, while the groom was the same for all test weeks except for Group B “during”. The observer was unfamiliar to the stallions. 2.5. Behavioural Observations The behaviour of the pair, the groom, and the driver was filmed with a GoPro Hero 3 during the entire test drive (except two videos, which were incomplete). The camera was placed on the head of the observer. The hitching and unhitching sequences were filmed standing in front of the carriage, while the driving sequence was filmed by the observer on the carriage, sitting next to the driver. In total, 88 test drives were completed, of which 86 were analysed from video recordings (Table 1). All the behavioural observations were recorded by the same observer using The Observer XT software v.11.5, Noldus Information Technology [22]. Behaviours were recorded as occurrences (“Point Events”). Events longer than one second were counted as multiple events, i.e., one “new” occurrence for each additional second. 2.5.1. Human Interventions The behaviour of the groom and the driver (human interventions) was first assessed live during the test drive with a portable recording device (Workabout Pro3 handheld computer) using the Pocket Observer software [22]. All videos of the test drives were reassessed over the computer in the week following the test drive. Two types of interventions were counted for the groom, and three for the driver (Table 2). Voice presence was considered a vocal signal directed at both stallions simultaneously. All other driver interventions could be attributed towards a specific stallion. The behaviour of the humans was only assessed if directly related to a social interaction between the stallions, i.e., directly following a stallion interaction. Actions directly relevant for hitching and driving (such as pulling on the reins to turn or stop) and interventions of the groom and driver to stop unwanted behaviour irrelevant to social interactions were thus not assessed. 2.5.2. Interactions between Stallions The behaviour of the stallions (stallion interactions) was assessed in the weeks following the video analysis of the human interventions using video recordings only. For the video analysis, the order of visualisation was semi-randomised, so as not to watch the same test stallion twice consecutively. The behaviour of the stallions was classified into six occurrences (Table 3). The observer only assessed the behaviour of the stallions directly related to a social interaction, defined as one stallion establishing at least visual contact with the other. Visual contact was the least intensive interaction that could be recognised by the observer. Actions with no obvious social purpose, such as gnawing the driving material, were not assessed. The number of stallion’s interactions was then compared to the number of human interventions. 2.6. Statistical Analysis 2.6.1. Descriptive Statistics Statistical analysis was performed with R software v.4.4.1 [23]. Simple descriptive statistics were computed with the psych package [24]. In a first step, descriptive statistics of the human interventions, i.e., groom and driver, and of the behaviour of the horses were presented. Considering the fact that certain human interventions and horse behaviours were very rare (<5% of all interventions or interactions), the interventions and behaviours were regrouped as follows:- Human interventions were regrouped by person: groom total (“GT”) consisted of the sum of the interventions groom signal (“GS”) and groom presence (“GP”), while driver total (“DT”) consisted of the sum of interventions driver reins (“DR”), driver whip (“DW”), and driver voice (“DV”). - The horse behaviours were regrouped by situation (hitching, standing, moving). Backing up while hitching (“BH”) was regrouped with approach while hitching (“AH”) as hitching total (“HT”). Standing total (“ST”) encompassed approaches while standing (“AS”) and rears while standing (“RS”). Movement total (“MT”) consisted of approaches while moving (“AM”) and rears while moving (“RM”). All the horse interactions were then regrouped into one category named total interaction (“TI”) and used as the explanatory variable in the analyses. Furthermore, the total human interventions and stallion interactions were compared using Pearson’s correlations. 2.6.2. Statistical Modelling In order to assess the effect of the housing system (social or conventional boxes), we investigated the effect of the housing system (“Treatment”) on the total number of interactions (“TI”) during the test drive using linear mixed-effect models (LMM; lmer function, lme4 library, [25] in the R software v.4.4.1 [23]). With the assumption that one stallion initiating an interaction should have an influence on the reaction of the other stallion, the sum of interactions of the different pairs (N = 16) during the test drive (TI) was included in the model as response variable. The type of housing system (Treatment, “before”, “during”, or “after” being housed in social box), the four different days during which the pairs were observed (four distinct test drives, in each treatment) (“Day”), and whether the neutral stallion was on his first or second test drive (“Drive”) were included as fixed factors. In order to control for repeated measurements of the same pair of stallions, this factor was included as random factor. For all models, the residuals were checked graphically for normal distribution and homoscedasticity (simulate Residuals function, package DHARMa, [26]. For the LMMs, p-values (PBmodcomp function, package pbkrtest [27] were calculated using parametric bootstrap methods (1000 bootstrap samples)). Models were fitted with maximum likelihood. The p-values calculated with parametric bootstrap tests give the fraction of simulated likelihood ratio test statistic values (LRT) that are larger than or equal to the observed LRT value. This test is more adequate than the raw LRT test because it does not rely on a large-sample asymptotic analysis and correctly takes the random-effects structure into account [27]. p-values were extracted by comparing the two models with and without each term, both fitted with the maximum likelihood method (ML), using a likelihood ratio test. The results are presented after model simplification. When a significant interaction effect was found, further two-by-two comparisons were performed using either LMMs or applying a Tukey correction (function glht, package multcomp in R, Multiple comparisons of means). The significance level was set at alpha = 0.05. Moreover, because of the small sample size, we carried out a power analysis for the effect of Day and for the effect of Treatment on Total interactions in order to calculate if the power of our analyses was large enough (pwr.f2 function, pwr library; in R v4.4.1). 2.6.3. Observer Reliability (Intra-Reliability of the Observer) Intra-observer reliability was calculated for human interventions (live observations vs. first video assessment, first vs. second video assessment) and horse interactions (first vs. second video assessment). For the human interventions, the concordance between live and video observations was evaluated with Cohen’s kappa of the number of interventions on the 86 available test drives to ensure that the video perspective gave the same information as observing the equivalent situation directly. In addition, the intra-rater reliability of video observations was calculated by comparing 32 videos assessed twice. Two videos per tested horse-pair were selected, i.e., 4 videos per tested horse, 16 per control horse, with each horse-pair being observed twice and covering the three treatment situations (at least one test drive for each treatment). After an initial analysis of the horse behaviours on all videos, 32 videos were also reassessed (four videos per tested horse, 16 per control horse, with each horse-pair being observed twice and at least one test drive for each treatment) to evaluate the intra-rater reliability, similarly to the human interventions. For the video analyses, the order of visualisation was semi-randomised, so as not to watch the same test stallion or treatment twice consecutively. Cohen’s Kappa (κ) [28] was calculated by the Observer XT software [22] for the counted observations of horse and human behaviour for each separate behaviour. 3. Results 3.1. Behavioural Observations 3.1.1. Descriptive Statistics Stallion Interactions A mean of 54.87 ± 1.68 interactions in total (TI) were observed per drive, representing approximately 1.5 interactions per minute (Table 4). Across situations, 78.25% of TI were initiated when the horses were not moving (i.e., while standing (AS), 52.51% or hitching (TH), 25.74%), and approaches were the most common behaviour between stallions (25.70% while hitching (AH), 52.12% while standing (AS) and 21.47% during movement (AM)) (Table 4). Some behaviours were specific to an individual, e.g., backs while hitching (BH) was only exhibited by stallion #4. Other types of specific behaviours were seen in several, but not all individuals (rears while standing (RS) in stallion #1, #8, and #9; rears in movement (RM) in stallion #1, #3, #8, #9, and #10, see Supplementary Table S1 for details). All the behaviours of the stallions are summarised in Supplementary Table S1. Human Interventions Regarding human interventions, 37% could be attributed to the groom and 63% to the driver (Table 5). GP and DV were artificially inflated, as they count twice (for both horses of the pair) while the intervention actually occurs once for the pair. The driver used the reins as the main intervention aid (91% of DT), followed by voice (7% of DT) and whip (1% of DT). Groom presence hardly ever occurred (0.6% of GT) and so groom signals (GS) explained most of the groom interventions. All the human interventions are summarised in Table 5. 3.2. Model Results There was an effect of the statistical interaction between Treatment (before, during or after being housed in social boxes) and Day (Day1 to Day4) on total interactions (TI) (LMM: interaction effect between Treatment and Day on TI, p = 0.003, see Supplementary Materials for more details). Power analysis conducted on the results of this model revealed that this model had a power of 100%. Post-hoc comparisons showed that TI differed between Treatment for Day1 (LMM: effect of Treatment on TI, p = 0002; Figure 2). Power analysis conducted on the results of this model revealed that this model had a power of p > 0.99. During Day1, there was significantly more TI before being housed in social boxes than during and after (Treatment before–during, Multiple comparisons of means Tukey: Z = −4.78, p < 0.001; Treatment before–after, Multiple comparisons of means Tukey: Z = 3.65, p = 0.0007; Figure 2). However, there was no difference in TI during and after being housed in social boxes (Treatment during and after, Multiple comparisons of means Tukey: Z = −1.37, p = 0.36; Figure 2). There was no other effect of Treatment on TI during the other days (LMMs: p > 0.77). Moreover, before being housed in social boxes, Day had an effect on TI (LMM: effect of Day on TI, p = 0.001, Figure 3). Before being housed in social boxes, there was significantly more TI during Day1 than during Day2, Day3 and Day4 (Day1–Day2, Multiple comparisons of means Tukey: Z = −3.707, p < 0.01; Day1–Day3, Multiple comparisons of means Tukey: Z = −3.819, p < 0.001, Day1–Day4, Multiple comparisons of means Tukey: Z = −5.467, p < 0.01; Figure 3). Power analysis conducted on the results of this model revealed that this model had a power of 100%. However, there was no difference in TI during Day2 and Day3, Day3 and Day4 and Day2 and Day4 (Day2–Day3, Day3–Day4, Day2–Day4, Multiple comparisons of means Tukey: p > 0.51; Figure 3). There was also no effect of Day on TI during and after being housed in the social box (LMM: p > 0.07). Finally, whether the neutral horse was on its first or second test drive (“Drive”) did not have any effect on TI (LMM: effect of Drive on TI, p = 0.12). 3.3. Reliability Statistics In the comparison of driver observations live vs. video (N = 86 comparisons), there was substantial intra-observer reliability, but with a very large range (κ = 0.72, −0.14 < κ < 0.94). A subsampling of 32 videos (two per pair) showed a larger mean κ = 0.75 (0.58 < κ < 0.91) between live and first video analysis, a mean κ = 0.80 for comparisons of videos only (0.59 < κ < 0.96), and a mean κ = 0.73 for comparisons between the live results and the second video analysis (0.57 < κ < 0.90). For the reliability of the observations of horse interactions, two videos per pair (32 videos in total) were assessed twice. The intra-observer reliability between the first and second video analysis was substantial (κ = 0.75, 0.47 < κ < 0.92). 4. Discussion The results of this study showed that the social box offering opportunities for more physical contact between stallions did not increase their interactions while driven in pairs. This result is consistent with studies testing the influence of the housing system providing social contact between horses on their working ability [13,15,16]. However, our results showed that the horses performed more social interactions during the driving test before being housed in the social box and that these interactions were decreasing over the first few days. Moreover, our aim was also to establish a methodology to measure social interactions during driving sessions. The substantial intra-observer reliability of the human interventions between live observations and observations through video recordings suggests that the GoPro video camera fixed on the head of the observer gave her the same point of view as during live observations. The intra-observer reliability of the horse interactions confirms that they could easily be recorded. Single stable housing has been demonstrated multiple times to be detrimental to the welfare of horses [6]. This restrictive housing system offers poor opportunities for the horses to fulfil species-specific behaviours, i.e., social interactions and locomotor behaviour, and results in animals staying in a frustration related stress state. This housing-related welfare impairment can lead to abnormal stereotypical behaviour, excessive aggressiveness towards humans [29], unresponsiveness towards their environment and an increase in alert posture [6]. Moreover, it might also negatively affect the training of horses. Previously performed studies on young horses showed that the social environment to which horses are exposed affects learning abilities: young horses stabled in groups were easier to train, less stressed, and demonstrated less aggressive interactions towards humans than single stabled horses [3,15,16]. Concurrently, horses kept in single housing systems performed more aggressive social interactions such as biting in compensation [16]. The need for social interactions might be fulfilled for stallions staying in the social box, replacing the conventional box, and therefore we expected to have a positive effect of the social box by finding less unwanted social interactions when driven in pairs. Our results showed clearly that the horses performed more social interactions during the first day of the test drives, before being housed in social boxes. Furthermore, the first day generally showed more interactions, and these interactions were decreasing over the four days, especially before being housed in the social box, at the start of the study. As an explanation, we suggest that the decrease in interactions between the first and the following days may indicate a trained response of the stallions, following the consistent demands from the groom and the driver to stop interacting. In terms of learning theory, the driver and the groom added aversive stimuli using the rein, whip, voice, and hand signals in order to decrease the frequency of undesired behaviours, such as social interactions during work in pairs [30]. All stimuli were used in a fairly consistent manner: hand signals and pulling on the reins were most frequent, and of low intensity, while the whip was only used when the horse did not react to the reins or the voice. Such interventions are called positive punishment, and to be effective in learning, the punishing stimulus needs to be applied simultaneously with the undesired behaviour [30]. However, there may be several additional effects concurrent to the effect of the housing system, which could not be addressed in this study and are therefore to be considered as limitation of the study. The decrease between the first and the following days may indicate a certain habituation to the driving partner in the pair by a settling of dominance between the pairs too subtle to be recognised by the observer. We currently cannot disentangle these potential effects from the positive effect attributed to the housing system. As to our knowledge, so far, no studies have looked at the interactions between horses driven in pairs, and one of our aims was also to validate our methodology for measuring social interactions during driving sessions. We limited the ethogram to behaviours that were obvious to the observer, with the lowest intensity of interaction consisting in one horse turning his head towards the other (“approach”). It is possible that more subtle clues between the two stallions might have been missed and were not recorded for the analysis. However, the substantial intra-observer reliability shows that the behaviours we recorded could be reliably assessed from videos and indicate that the methodology is sound for further research. Furthermore, the intra-observer reliability for the human interventions between live and video observations suggests that either direct observations or assessing on video recordings would be sufficient to record the total interactions between horses driven in pairs. Future studies could use our ethogram as a basis to study the social interactions during driving sessions. For example, some factors, e.g., the friendliness between horses harnessed or individual horses’personality, could influence the number of interactions during the drive, warranting further investigations. Moreover, this ethogram could be used to assess in what kind of situations interactions are most likely to occur, and when they might escalate, resulting in an increased risk of accidents. In our study, most interactions (78.25% of TI) were initiated when the horses were not moving. Therefore, it would be important to train the horses to not interact in these situations. In practice, this would mean planning more stops in the training sessions, where the horses have to stand still, in order to correctly punish the horses to learn not to interact and of course reward them for desired behaviour. The most visibly impressive and potentially dangerous interactions occurred when a stallion reared, either while standing (RS) or even in movement (RM). However, these behaviours were extremely rare. Only one horse backed into the cart while he was being hitched next to the other stallion (BH). This behaviour is dangerous, as the horse may injure himself against the cart, and is also disturbing to the neighbouring horse, but seemed specific to this one individual. Overall, extreme behaviours were rare, and no injuries or accidents occurred. This article is but a first approach to the complex interactions of horses driven in pairs in response to different housing conditions. It shows several limitations, especially the small number of horses and the limited, though reliable, ethogram, which might have missed more subtle social clues between stallions. No information on the dominance between pairs was established beforehand, which could potentially be a relevant indicator for the subsequent number of interactions between horses. Furthermore, due to the use of neutral stallions in the pair, it is currently unknown whether the stay in the social box between horses driven together would decrease or increase the unwanted interactions during drives even further. 5. Conclusions Our results indicate that being housed in social boxes seems to decrease the number of social interactions between Franches-Montagnes stallions when driven in pairs. Further studies should investigate if factors, such as the affinity between harnessed horses, could influence the number of interactions and whether horses staying together in social boxes would show even fewer interactions when driven together. Acknowledgments We would like to thank the highly competent “neutral driver” Fritz Schmid from the Nationales Pferdezentrum Bern, as well as Christophe Guerry and Christa Graf, the grooms of the Swiss National Stud Farm. Special thanks go to Sara Hintze and Anne-Laure Maigrot for advice in statistical analysis. Supplementary Materials The following supporting information can be downloaded at: www.mdpi.com/article/10.3390/ani12091077/s1, Table S1: Descriptive statistics for all observed stallion interactions per stallions. Total number of instances; mean ± SE; min-max; over the course of the study. Click here for additional data file. Author Contributions A.I.G. and S.B.F. wrote the manuscript. C.W. and A.Z. planned the experiment. A.I.G., C.W. and A.Z. conducted the experiment. A.I.G. produced the raw data from the video analyses. A.I.G. and S.B.F. analysed the data. A.Z., C.W., I.B. and S.B.F. controlled the research work. All authors have read and agreed to the published version of the manuscript. Funding This project would not have been possible without the financial aid of the foundation: Christa Tag Zwilling-Stiftung, Wiesenstrasse 10, CH-8008 Zürich, CHE-355.024.419. Institutional Review Board Statement The study was approved by the Cantonal department of the Federal Food Safety and Veterinary Office: approval number VD 2810.a; Switzerland. Informed Consent Statement Not applicable. Data Availability Statement Data are available upon reasonable request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Experimental procedure. The black dotted line indicate the housing system of the stallions at the time during which they were observed (before, during and after being housed in social box). The black arrows indicate the different days during which the drive tests were performed. “CB” is the abbreviation for conventional box, “SB” for social box. Figure 2 “Total interactions during Day1”. Boxplot of the total interactions recorded in the different treatments (before, during and after being housed in social box) during the first day. The horizontal line shows the median, the box extends from the lower to the upper quartile, and the whiskers to 1.5 × the interquartile range above the upper quartile or below the lower quartile. The black dots indicate the means. Significant differences between treatment are indicated as ** p ≤ 0.001. The lines show the model estimates (middle line) and 95% confidence intervals (upper and lower line). Figure 3 “Total interactions before being housed in social box”. Boxplot of the total interactions recorded during the different days, before being housed in the social box. The horizontal line shows the median, the box extends from the lower to the upper quartile, and the whiskers to 1.5 × the interquartile range above the upper quartile or below the lower quartile. The black dots indicate the mean. Significant differences between treatments are indicated as * p ≤ 0.05, ** p ≤ 0.001. animals-12-01077-t001_Table 1 Table 1 Effective pairing of the test (H1–H8) and neutral (N1–N2) horses before, during and after the stay in the social box. Both neutral horses were driven twice per day, so that the first and second drive of the day were also recorded (“drive”). The numbers in bold indicate the days of data collection. Endash (“-“) alone, indicate that the test stallion was driven only once because of specific circumstances such as colic or lameness. Day Drive Before During After Group A Group B Group A Group B Group A Group B 1 1 H2-N1/H8-N2 H4-N1/H5-N2 H2-N1/H8-N2 H1-N1/H4-N1 H2-N1/H8-N2 H4-N1/H5-N2 2 H6-N1/H3-N2 H7-N1/H1-N2 H6-N1/H3-N2 H7-N2/H5-N2 H6-N2/H3-N2 –/H1-N2 2 1 H3-N1/H6-N2 H7-N1/H1-N2 –/H6-N2 H4-N1/H5-N2 H3-N1/H6-N2 –/H1-N2 2 –/H8-N2 H5-N1/H4-N2 H2-N1/H8-N2 H7-N1/H1-N2 H2-N1/H8-N2 H5-N1/H4-N2 3 1 H8-N1/H2-N2 H5-N1/H4-N2 H8-N1/H2-N2 H7-N1/H1-N2 H8-N1/H2-N2 H5-N1/H4-N2 2 H3-N1/H6-N2 H1-N1/H7-N2 –/H6-N2 H5-N1/H4-N2 H3-N1/H6-N2 H1-N1/– 4 1 H6-N1/H3-N2 H1-N1/H7-N2 H6-N1/– H5-N1/H4-N2 H6-N1/H3-N2 H1-N1/– 2 H8-N1/H2-N2 H4-N1/H5-N2 H8-N1/H2-N2 H1-N1/H7-N2 H2-N1/H8-N2 H4-N1/H5-N2 animals-12-01077-t002_Table 2 Table 2 Human interventions respective of the groom and driver reacting to social interactions between stallions, highlighted in bold, assessed during the drive test. Behaviour of the Humans Description of the Behaviour groom signal (GS) The groom moves towards the horse and/or touches the horse (or the bridle) to disrupt an interaction between the horses groom presence (GP) The groom is present at the head of the horses during the drive to deescalate a dangerous situation as perceived by the groom and driver driver reins (DR) Driver pulls rein on the horse in reaction to a social interaction driver whip (DW) Driver uses the whip on the horse in reaction to a social interaction driver voice (DV) Driver uses his voice to hinder a mutual social interaction animals-12-01077-t003_Table 3 Table 3 Descriptions of stallion interactions highlighted in bold assessed during the test drive. Behaviour of the Horse Description of the Behaviour Approach while hitching (AH) The horse aims his head at the other horse (turns his head approximately 30° towards the other horse), with or without tactile contact, during hitching procedures Backs while hitching (BH) The horse backs into the cart to avoid hitching after eye contact with other horse Approach while standing (AS) The horse aims his head at the other horse (turns his head approximately 30° towards the other horse), with or without tactile contact, while standing Rear while standing (RS) The horse rears in the direction of the other horse while standing Approach in movement (AM) The horse aims his head at the other horse (turns his head approximately 30° towards the other horse), with or without tactile contact, while in movement Rear in movement (RM) The horse rears in the direction of the other horse while in movement animals-12-01077-t004_Table 4 Table 4 Descriptive statistics of the number of observed horse interactions between stallions driven in pairs highlighted in bold over the course of the study (Total number of occurrences; mean ± SE; min-max; percentage of total recorded behaviours). The behaviours in italics indicate the behaviours regrouped by type of behaviour. The number of occurrences in italics indicates the number of occurrences for the behaviours regrouped by type of behaviours. The number of occurrences in italics and bold indicates the number of occurrences for the total driving. The number of occurrences in bold indicates the number of occurrences for the total interactions. See Table 3 for the detailed ethogram. Behaviour of the Horses Total Number (Over All Drives) Mean ± SE Minimum-Maximum Percentage of Total Recorded Behaviours Approach while hitching (AH) 2426 14.1 ± 0.6 0–39 25.70% Backs while hitching (BH) 3 0.02 ± 0.01 0–2 0.03% Total hitching (TH = AH + BH) 2429 14.12 ± 0.6 0–39 25.74% Approach while Standing (AS) 4919 28.60 ± 1.20 0–89 52.12% Rear while standing (RS) 37 0.22 ± 0.09 0–10 0.39% Total standing (TS = AS + RS) 4956 28.81 ± 1.2 0–89 52.51% Approach in movement (AM) 2026 11.78 ± 0.72 0–69 21.47% Rear in movement (RM) 27 0.16 ± 0.05 0–6 0.29% Total movement (TM = AM + RM) 2053 11.94 ± 0.72 0–69 21.75% Total driving (TD = TS + TM) 7009 40.75 ± 1.52 3–134 74.26% Total interactions (TI = TH + TS + TM ) 9438 54.87 ± 1.68 8–151 100.00% animals-12-01077-t005_Table 5 Table 5 Descriptive statistics of the number of observed human interventions to stop stallions driven in pairs from interacting over the course of the study (Total number of occurrences mean ± SE; min-max; percentage of total recorded interventions). The number of occurrences in italics indicates the number of occurrences for the total groom, resp. total driver interventions. The number of occurrences in italics and bold indicates the number of occurrences for the total groom and driver interventions. See Table 2 for the detailed ethogram. Human Interventions Total Number (Over All Drives) Mean ± SE Minimum-Maximum Percentage of Total Recorded Behaviours Groom Signal (GS) 2399 13.95 ± 0.61 0–34 37.23% Groom Presence (GP) 14 0.08 ± 0.04 0–4 0.22% Total groom (TG = GS + GP) 2413 14.03 ± 0.61 0–34 37.45% Driver Reins (DR) 3678 21.38 ± 1.31 0–108 57.08% Driver Whip (DW) 63 0.37 ± 0.08 0–6 0.98% Driver Voice (DV) 290 1.69 ± 0.19 0–13 4.50% Total driver (TD = DR + DW + DV) 4031 23.44 ± 1.41 0–110 62.55% Total human interventions ( TG + TD ) 6444 37.47 ± 1.67 0–135 100.00% Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Salter R. Hudson R. Social organization of feral horses in western Canada Appl. Anim. Ethol. 1982 8 207 223 10.1016/0304-3762(82)90205-X 2. Linklater W.L. Cameron E.Z. Tests for cooperative behaviour between stallions Anim. Behav. 2000 60 731 743 10.1006/anbe.2000.1525 11124871 3. Yarnell K. Hall C. Royle C. Walker S.L. Domesticated horses differ in their behavioural and physiological responses to isolated and group housing Physiol. Behav. 2015 143 51 57 10.1016/j.physbeh.2015.02.040 25725117 4. Christensen J.W. Ladewig J. Sondergaard E. Malmkvist J. Effects of individual versus group stabling on social behaviour in domestic stallions Appl. Anim. Behav. Sci. 2002 75 233 248 10.1016/S0168-1591(01)00196-4 5. Werhahn H. Hessel E.F. Van den Weghe H.F.A. Competition Horses Housed in Single Stalls (II): Effects of Free Exercise on the Behavior in the Stable, the Behavior during Training, and the Degree of Stress J. Equine Vet. Sci. 2012 32 22 31 10.1016/j.jevs.2011.06.009 6. Ruet A. Lemarchand J. Parias C. Mach N. Moisan M.-P. Foury A. Briant C. Lansade L. Housing horses in individual boxes is a challenge with regard to welfare Animals 2019 9 621 10.3390/ani9090621 7. Schwarz A. Gazzarin C. How Economical Is the Pension House for Horses? An Analysis of Three Types of Farms on the Basis of Case Studies ART-Berichte Ettenhausen, Switzerland 2013 8. Ladewig J. Søndergaard E. Christensen J. Ontogeny: Preparing the young horse for its adult life The Domestic Horse, the Evolution, Development and Management of Its Behaviour Cambridge University Press Cambridge, UK 2005 139 149 9. Briefer Freymond S. Briefer F.E. Von Niederhäusern R. Bachmann I. Pattern of Social Interactions after Group Integration: A Possibility to Keep Stallions in Group PLoS ONE 2013 8 e54688 10.1371/journal.pone.0054688 23382940 10. Tilson R.L. Sweeny K.A. Binczik G.A. Reindl N.J. Buddies and bullies: Social structure of a bachelor group of Przewalski horses Appl. Anim. Behav. Sci. 1988 21 169 185 10.1016/0168-1591(88)90106-2 11. McDonnell S.M. Haviland J.C.S. Agonistic ethogram of the equid bachelor band Appl. Anim. Behav. Sci. 1995 43 147 188 10.1016/0168-1591(94)00550-X 12. McDonnell S.M. Poulin A. Equid play ethogram Appl. Anim. Behav. Sci. Equine Behav. 2002 78 263 290 10.1016/S0168-1591(02)00112-0 13. Søndergaard E. Halekoh U. Young horses’ reactions to humans in relation to handling and social environment Appl. Anim. Behav. Sci. 2003 84 265 280 10.1016/j.applanim.2003.08.011 14. Goodwin D. Horse Behaviour: Evolution, Domestication and Feralisation The Welfare of Horses Waran N. Kluwer Alphen aan den Rijn, The Netherlands 2002 1 18 15. Rivera E. Benjamin S. Nielsen B. Shelle J. Zanella A. Behavioral and physiological responses of horses to initial training: The comparison between pastured versus stalled horses Appl. Anim. Behav. Sci. 2002 78 235 252 10.1016/S0168-1591(02)00091-6 16. Søndergaard E. Ladewig J. Group housing exerts a positive effect on the behaviour of young horses during training Appl. Anim. Behav. Sci. 2004 87 105 118 10.1016/j.applanim.2003.12.010 17. Fureix C. Bourjade M. Henry S. Sankey C. Hausberger M. Exploring aggression regulation in managed groups of horses Equus caballus Appl. Anim. Behav. Sci. 2012 138 216 228 10.1016/j.applanim.2012.02.009 18. Hartmann E. Sondergaard E. Keeling L.J. Keeping horses in groups: A review Appl. Anim. Behav. Sci. 2012 136 77 87 10.1016/j.applanim.2011.10.004 19. Fédération Equestre Internationale Rules for International Combined Driving Events 10th ed. Fédération Equestre Internationale Lausanne, Switzerland 2009 20. McLean A.N. McGreevy P.D. Horse-training techniques that may defy the principles of learning theory and compromise welfare J. Vet. Behav. 2010 5 187 195 10.1016/j.jveb.2010.04.002 21. Zollinger A. Wyss C. Bardou D. Bachmann I. Social box: A new housing system increases social interactions between stallions Animals 2022 in preparation 22. Van Cann R. Jansen S. Brinkkemper S. Noldus Information Technology Palgrave Macmillan Book: Software Business Start-Up Memories Springer London, UK 2013 57 65 23. R Development Core Team R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing Vienna, Austria 2013 24. Revelle W. Installing R and the Psych Package Department of Psychology, Northwestern University Evanston, IL, USA 2013 25. Pinheiro J.C. Bates D.M. Mixed-Effects Models in S and S-PLUS Springer New York, NY, USA 2000 26. Hartig F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level/Mixed) Regression Models R package v0.2.0 University of Regensburg Regensburg, Germany 2018 27. Halekoh U. Højsgaard S. A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models the R package pbkrtest J. Stat. Softw. 2014 59 1 32 10.18637/jss.v059.i09 26917999 28. Cohen J. A coefficient of agreement for nominal scales Educ. Psychol. Meas. 1960 20 37 46 10.1177/001316446002000104 29. Christensen J.W. Zharkikh T. Ladewig J. Yasinetskaya N. Social behaviour in stallion groups (Equus przewalskii and Equus caballus) kept under natural and domestic conditions Appl. Anim. Behav. Sci. 2002 76 11 20 10.1016/S0168-1591(01)00208-8 30. McLean A.N. Christensen J.W. The application of learning theory in horse training Appl. Anim. Behav. Sci. 2017 190 18 27 10.1016/j.applanim.2017.02.020

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093344 sensors-22-03344 Article S-Scheme BiOCl/MoSe2 Heterostructure with Enhanced Photocatalytic Activity for Dyes and Antibiotics Degradation under Sunlight Irradiation Huang Yan 12 Chen Fan 1 Guan Zhipeng 1 Luo Yusheng 1 Zhou Liang 3 Lu Yufeng 1 https://orcid.org/0000-0001-9771-0444 Tian Baozhu 14* Zhang Jinlong 1* Blackman Chris Academic Editor 1 Key Laboratory for Advanced Materials and Feringa Nobel Prize Scientist Joint Research Center, Institute of Fine Chemicals, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China; huangyan_135@126.com (Y.H.); avazaza0131@icloud.com (F.C.); guan10130725@126.com (Z.G.); lyslouis217@126.com (Y.L.); luyufenghd@163.com (Y.L.) 2 Research Institute of Physical and Chemical Engineering of Nuclear Industry, 168 Jintang Road, Tianjin 300180, China 3 State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes, School of Resources & Environmental Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China; zhouliang@ecust.edu.cn 4 Key Laboratory of Specially Functional Polymeric Materials and Related Technology (Ministry of Education), East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China * Correspondence: baozhutian@ecust.edu.cn (B.T.); jlzhang@ecust.edu.cn (J.Z.); Tel.: +86-21-64252062 (B.T. & J.Z.) 27 4 2022 5 2022 22 9 334431 3 2022 25 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Semiconductor photocatalysis is considered to be a promising technique to completely eliminate the organic pollutants in wastewater. Recently, S-scheme heterojunction photocatalysts have received much attention due to their high solar efficiency, superior transfer efficiency of charge carriers, and strong redox ability. Herein, we fabricated an S-scheme heterostructure BiOCl/MoSe2 by loading MoSe2 nanosheets on the surface of BiOCl microcrystals, using a solvothermal method. The microstructures, light absorption, and photoelectrochemical performances of the samples were characterized by the means of SEM, TEM, XRD, transient photocurrents, electrochemical impedance, and photoluminescence (PL) spectra. The photocatalytic activities of BiOCl, MoSe2, and the BiOCl/MoSe2 samples with different MoSe2 contents were evaluated by the degradation of methyl orange (MO) and antibiotic sulfadiazine (SD) under simulated sunlight irradiation. It was found that BiOCl/MoSe2 displayed an evidently enhanced photocatalytic activity compared to single BiOCl and MoSe2, and 30 wt.% was an optimal loading amount for obtaining the highest photocatalytic activity. On the basis of radical trapping experiments and energy level analyses, it was deduced that BiOCl/MoSe2 follows an S-scheme charge transfer pathway and •O2−, •OH, and h+ all take part in the degradation of organic pollutants. photocatalysis dye antibiotics S-scheme heterojunction photocatalytic activity reactive species organic pollutant National Natural Science Foundation of ChinaU1862112 21573069 Shanghai Municipal Science and Technology Major Project2018SHZDZX03 Program of Introducing Talents of Discipline to UniversitiesB16017 Fundamental Research Funds for the Central Universities50321041917001 50321042017001 Fundamental Research Funds for the Central UniversitiesJKD01211701 This research was funded by the National Natural Science Foundation of China (U1862112 and 21573069), Shanghai Municipal Science and Technology Major Project (2018SHZDZX03), Program of Introducing Talents of Discipline to Universities (B16017), Fundamental Research Funds for the Central Universities (50321041917001 and 50321042017001), and Fundamental Research Funds for the Central Universities (JKD01211701). ==== Body pmc1. Introduction With the rapid development of urbanization and industrialization, water pollution has become more and more serious and imparted huge adverse effects on aquatic ecosystems, human health, and the development of economy and society [1,2,3]. In recent decades, the removal of noxious organic pollutants in wastewater, such as drugs [4,5], dyes [6,7], and antibiotics [8], has become a big challenge that must be managed. For instance, the antibiotics always bring about side effects on ecosystems and human health by inducing the proliferation of bacterial drug resistance [6]. The carcinogenic and teratogenic dyes can enter the human body along with the polluted water, leading to the appearance of cancers and other serious illnesses. To eliminate these organic pollutants, a series of techniques, such as physical adsorption, micro-biological degradation, and chemical oxidation, have been applied in the remediation of organic pollutants [1,9]. However, these strategies are still insufficient to completely remove the water-borne organic pollutants because of their low efficiency, as well as the formation of secondary waste products [10,11,12]. Alternatively, semiconductor photocatalysis has received much attention as a promising solution to completely eliminate the organic contaminants in wastewater [1,2,3,4,5,6,7,13,14,15,16,17,18,19]. As a semiconductor with wide bandgap, BiOCl is considered to be an ideal photocatalyst for the decomposition of organic pollutants in wastewater under UV light [20,21]. The main weakness of BiOCl is that it cannot respond to visible light, severely blocking its application in the whole solar spectrum. To solve this problem, the researchers have developed many strategies, such as fabricating oxygen vacancies, depositing with metals, constructing heterojunctions, and so on [22,23,24,25,26,27,28,29,30]. Although these approaches can extend the light response of BiOCl to the visible region, they inevitably decrease the redox ability of the photogenerated electrons and holes. In this regard, the researchers further exploited a series of all-solid-state and direct Z-scheme composite semiconductors to avoid decreasing the redox ability of photogenerated charge carriers [13,14,31,32,33,34,35,36,37,38]. Recently, Yu et al. proposed a novel S-scheme heterojunction theory and reasonably explained the transfer pathway of photogenerated charge carriers in the two semiconductors [39]. From then on, a series of S-scheme photocatalytic materials have been reported and successfully applied in the fields of environment and energy [40,41,42,43,44,45,46,47]. Layer-structured molybdenum selenide (MoSe2) has a narrow band gap (about 1.3–1.9 eV) [48,49], which means it can respond to the whole UV-visible-near-infrared (UV-Vis-NIR) light. However, its multilayer structure and narrow bandgap usually lead to the high recombination rate of photogenerated charge carriers [50]. In this regard, coupling MoSe2 with other semiconductors with wide bandgaps is an ideal strategy to take its advantages and simultaneously avoid its flaws. So far, several composite MoSe2-based photocatalysts have been exploited [51,52,53,54]. However, to the best our knowledge, the S-scheme heterojunction photocatalyst based on MoSe2 and BiOCl has never been studied. Herein, we first constructed the S-scheme heterojunction BiOCl/MoSe2 photocatalyst by loading MoSe2 nanosheets on the surface of BiOCl microcrystals, using a solvothermal method. The morphology and crystalline structures of the as-prepared samples were characterized by the means of scanning electron microscopy (SEM), transmission electron microscopy (TEM), and high-resolution transmission electron microscopy (HR-TEM). The light absorption properties of the samples were analyzed by UV-Vis diffuse reflectance spectroscope (DRS). The photoelectric properties and the separation rate of charge carriers were investigated using transient photocurrents, electrochemical impedance, and photoluminescent (PL) spectra. The photocatalytic activities of BiOCl and the different BiOCl/MoSe2 samples were evaluated by the degradation of azo dye methyl orange (MO) and antibiotic sulfadiazine (SD) under simulated sunlight irradiation. On the basis of the radical trapping experiments and potential analyses of BiOCl and MoSe2 conduction bands (CB) and valence bands (VB), the possible photocatalytic mechanism of S-scheme BiOCl/MoSe2 was proposed. 2. Materials and Methods 2.1. Materials Bismuth nitrate pentahydrate (Bi(NO3)3·5H2O) and absolute ethanol (C2H5OH) were provided by Sinopharm Chemical Reagent Co., Ltd., Shanghai, China. Selenium powder, sodium molybdate dihydrate (Na2MoO4·2H2O), and sodium borohydride (NaBH4) were purchased from Shanghai Adamas Reagent Co., Ltd., Shanghai, China. Potassium chloride (KCl) was obtained from Shanghai Lingfeng Chemical Reagent Co., Ltd., Shanghai, China. All the reagents were analytically pure grade and used as received without further purification. Milli-Q water was homemade and the resistivity was 18.2 MΩ cm. 2.2. Synthesis of BiOCl/MoSe2 BiOCl nanosheets were prepared using a hydrothermal method, similar to the previous report [55]. The detailed procedures were as follows: Firstly, 1 mmol Bi(NO3)3·5H2O and 1 mmol KCl were successively dispersed in 15 mL deionized water and stirred at room temperature for 1 h. Then, the mixture was transferred into a 50 mL Teflon-lined stainless-steel autoclave and placed in an oven to react at 160 °C for 24 h. Subsequently, the suspension was cooled to room temperature and the precipitation was washed, respectively, with deionized water and ethanol three times. Finally, the product was dried in a vacuum drying oven at 70 °C for 8 h, denoted as BiOCl. BiOCl/MoSe2 was synthesized via a modified solvothermal method [56]: Firstly, 200.5 mg BiOCl, 0.079 mmol Na2MoO4·2H2O, 0.158 mmol selenium powder, and 0.079 mmol NaBH4 were added into a 25 mL mixture solution of ethanol and water with a volume ratio of 1:1. After the mixture was stirred at room temperature for 1 h, the obtained homogeneous mixture was transferred into a 50 mL Teflon-lined stainless-steel autoclave and kept at 180 °C for 12 h. Then, the autoclave was cooled to room temperature and the obtained precipitate was washed with deionized water and ethanol three times, respectively. Finally, the obtained product was dried in a vacuum drying oven at 70 °C for 8 h. The theoretical loading amount of the MoSe2 sample was 10 wt.%, denoted as BiOCl/MoSe2-10. By changing the dosages of Na2MoO4·2H2O, selenium powder, and NaBH4, the BiOCl/MoSe2 samples with 30 wt.% and 50 wt.% MoSe2 contents were also synthesized, denoted as BiOCl/MoSe2-30 and BiOCl/MoSe2-50, respectively. Pure MoSe2 was further prepared by the same method, except that BiOCl was not added. 2.3. Characterization The morphologies of the obtained samples were observed via scanning electron microscope (SEM, TESCAN VEGA 3 SBH), transmission electron microscope (TEM, JEM2000EX), and high-resolution transmission electron microscope (HR-TEM, JEOJ JEM2100). The crystalline structures of the samples were analyzed using a Riguku D/Max 2550 VB/PC X-ray diffractometer with Cu Kα (λ = 1.5406 A) radiation, operated at a voltage of 40 kV and a current of 40 mA. The UV-Vis diffuse reflectance spectra of the samples were recorded on a SHIMADZU UV-2450 spectrophotometer and a Lambda 950 spectrophotometer, equipped with an integrating sphere assembly, using BaSO4 as the reference material. The photoluminescence (PL) spectra were tested on a Shimadzu RF5301PC fluorescence spectrophotometer and the 320 nm line of Xe lamp was used as the excitation source. The transient photocurrents, electrochemical impedance, and Mott–Schottky spectra were measured by a Zahner electrochemical workstation equipped with a three-electrode system, in which the platinum electrode and saturated calomel electrode were used as the counter electrode and reference electrode, respectively, and 0.2 mg photocatalyst sample was coated on 1.5 cm2 FTO glass as the working electrode. The transient photocurrent and Mott–Schottky tests were performed in a 0.5 M Na2SO4 aqueous solution and a 300 W Xe lamp with AM 1.5 filter as the light source. A mixed aqueous solution of 2.0 mM K3[Fe(CN)6], 2.0 mM K4[Fe(CN)6], and 0.5 M KCl was used as the electrolyte for the electrochemical impedance tests. 2.4. Photocatalytic Activity Measurement The photocatalytic activities of the prepared samples were evaluated by the degradation of methyl orange (MO) and sulfadiazine (SD) under simulated sunlight irradiation, using a 300 W Xe lamp with AM1.5 as the light source. For each measurement, a 50 mg photocatalyst was dispersed in a 50 mL MO/or SD (20 mg/L) solution in a quartz tube and stirred in the dark for 30 min to achieve the adsorption–desorption of MO/or SD on the surface of the photocatalyst. At a given time interval, 5 mL of the mixture solution was withdrawn, centrifuged, and filtered to remove the remaining particles. The residual concentrations of MO and SD were determined using a UV-Vis spectrophotometer and a high-performance liquid chromatograph, respectively. 3. Results and Discussion 3.1. Morphological and Crystalline Structures The morphological structures of the samples were observed by SEM, TEM, and HR-TEM images. As shown in Figure 1A,B, the surface of BiOCl sheets seems to be smooth and the width and thickness of BiOCl sheets are in the range of 1−4.5 μm and 300−400 nm, respectively. From the TEM images of BiOCl and BiOCl/MoSe2-30, it can be seen that the block-structured MoSe2 consists of many thin nanosheets (Figure 1C), which are uniformly wrapped on the surface of BiOCl sheets to form a shell structure (Figure 1D). The lattice structure of BiOCl/MoSe2-30 was further analyzed using HR-TEM images. In Figure 1E, the lattice spacing was measured to be 0.65 nm, attributed to the (0 0 2) crystal planes of 2H phase MoSe2 [57]. In Figure 1F, the lattice spacing of 0.275 nm corresponds to BiOCl (1 1 0) crystal planes, while that of 0.28 nm is attributed to MoSe2 (1 0 0) crystal planes. These results demonstrate the formation of a BiOCl/MoSe2 heterojunction structure [58]. The crystalline structures of the synthesized samples were analyzed by X-ray diffraction patterns (XRD). As shown in Figure 2, BiOCl presents the diffraction peaks at 2θ = 24.1°, 25.9°, 33.4°, 36.5°, 40.9°, 49.7°, 54.1°, 63.1°, and 68.1°, attributed to BiOCl (0 0 2), (1 0 1), (1 0 2), (0 0 3), (1 1 2), (1 1 3), (2 1 1), (2 0 3), and (2 2 0) crystal planes, respectively (JCPDS No. 06-0249) [54]. In contrast, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50 exhibit an obvious diffraction peak at 24.1°, while the other characteristic peaks become very weak, due to the resistance of the thick MoSe2 shell layer to X-ray. Even enlarged 10 times in intensity, the diffraction peaks of MoSe2 (1 0 2) and (1 1 0) are still very weak and broad, which is probably ascribable to both its low crystallinity as well as the very thin sheet structure. 3.2. Light Absorption and PL Properties The optical properties of MoSe2, BiOCl, and BiOCl/MoSe2 were investigated by UV-Vis DRS and PL spectra. As shown in Figure 3A,B, pure BiOCl only can absorb UV light, while MoSe2 displays strong light absorption in the whole UV-Vis-NIR region. After coupling with MoSe2, all the BiOCl/MoSe2 samples exhibit a significantly enhanced absorption in the visible and NIR region, and the absorption intensity gradually increases with the increase of MoSe2 content. PL spectrum is a useful technique to investigate the trapping, migration, and transfer efficiency of the photogenerated charge carriers in semiconductor photocatalysts [31,59,60]. Herein, we tested the PL spectra of BiOCl and the different BiOCl/MoSe2 samples at room temperature with an excitation wavelength of 320 nm. As displayed in Figure 3C, BiOCl exhibits a strong PL emission band in the range of 350–550 nm, while all the BiOCl/MoSe2 samples only have a very weak PL emission peak at 470 nm. After increasing the luminous flux of excitation light, the three BiOCl/MoSe2 samples also exhibit the PL emission bands in the range of 350–550 nm, similar to that of BiOCl (Figure 3D). The PL intensity of BiOCl/MoSe2-30 is near to that of BiOCl/MoSe2-50 and obviously weaker than that of BiOCl/MoSe2-10. These results indicate that the coupling of BiOCl and MoSe2 can effectively restrain the recombination of photogenerated charge carriers and that 30 wt.% is the optimal MoSe2 loading amount for effectively separating the photogenerated electrons and holes. 3.3. Photoelectric Characteristics The photoelectric characteristics of BiOCl and the different BiOCl/MoSe2 samples were investigated by transient photocurrent measurements, which can further disclose the production, separation, and transfer efficiency of photogenerated charge carriers in these samples. As shown in Figure 4A, both BiOCl and MoSe2 exhibit very weak photocurrent intensity due to the low sunlight response ability and the high recombination rate of photo-generated electrons and holes, respectively. In contrast, all the BiOCl/MoSe2 composite photocatalysts display obviously enhanced current photocurrent intensity, indicating that the formation of a heterojunction structure can effectively promote the separation and transfer of photogenerated charge carriers. Amongst these samples, BiOCl/MoSe2-30 shows the highest photocurrent intensity, which is about four times that of pure BiOCl. For BiOCl/MoSe2-50, its photocurrent intensity is evidently weaker than that of BiOCl/MoSe2-30, resulting from the shielding of excess MoSe2 to light [61]. The electrochemical impedance spectra (EIS) can be used to disclose the dynamics of the mobile and bound charges in the interfacial or bulk regions of semiconductors, and the smaller curvature radius usually implies the weaker resistance to charge transfer [14,62,63]. In the EIS Nyquist spectra of Figure 4B, all the BiOCl/MoSe2 samples exhibit much smaller semicircle diameters than BiOCl, implying that coupling MoSe2 can effectively decrease the transfer resistance of the carriers in BiOCl. As the loading amount of MoSe2 increases from 10 wt.% to 30 wt.%, the semicircle diameter of the EIS curve obviously becomes smaller and it almost has no change when the loading amount of MoSe2 is further increased to 30 wt.%. Combining the results of the transient photocurrents and EIS spectra, it can be concluded that 30 wt.% is the optimal MoSe2 loading amount for effectively facilitating the production, separation, and transfer of photogenerated change carriers. 3.4. Photocatalytic Activity and Mechanism Figure 5A,B presents the degradation curves of MO and SD over the different photocatalysts under simulated sunlight irradiation, respectively. In the absence of photocatalyst, the concentrations of MO and SD almost have no change under simulated sunlight irradiation, indicating that they have high photostability. Both pure BiOCl and MoSe2 exhibit low photocatalytic activity for MO and SD degradation, which is because BiOCl cannot respond to visible light while MoSe2 has the high recombination rate of photogenerated electrons and holes. Compared to pure MoSe2 and BiOCl, all the BiOCl/MoSe2 samples show evidently enhanced photocatalytic activity for MO and SD degradation, because the heterojunction structure between MoSe2 and BiOCl can effectively restrain the recombination of photogenerated electrons and holes. To more accurately compare the photocatalytic activities of BiOCl and the different BiOCl/MoSe2 samples, we further fitted the kinetic curves of MO and SD degradations over these samples. From Figure 5C,D, it can be seen that the degradations of MO and SD over these photocatalysts follow the pseudo first-order kinetic reaction. By comparing the reaction kinetic constants in Table 1, we know that BiOCl/MoSe2-30 possesses the highest photocatalytic activity among all the samples. Given that photostability is very important to a photocatalyst for its practical applications, we further tested the photostability of BiOCl/MoSe2-30 using the cyclic degradation experiments of MO and SD under simulated sunlight irradiation. As shown in Figure 5E, the degradation rates of MO and SD only display a slight decrease after four cycles, probably due to the inevitable loss of photocatalysts during the recycle runs. This result indicates that BiOCl/MoSe2-30 is a stable photocatalyst under simulated sunlight irradiation. In the photocatalytic degradation process, the reactive species that take part in the organic pollutant decomposition mainly include hydroxyl radical (•OH), superoxide radical (•O2−), and hole (h+). Herein, we identified the produced reactive species over BiOCl/MoSe2-30 in the organic decomposition process by addition of radical trapping agents. It is known that •OH, h+, and •O2− can be quenched by tert-butanol (TBA), EDTA-2Na, and p-benzoquinone (PBQ), respectively. As shown in Figure 5F, the degradation rate of MO was evidently inhibited after addition of EDTA-2Na, PBQ, and TBA, implying that all h+, •O2−, and •OH take part in the degradation of MO. The effect of these species for MO degradation deceases in the order of h+ > •O2− > •OH. To clarify the migration pathways of photogenerated charge carriers in BiOCl/MoSe2, it is necessary to identify the conduction band (CB) and valence band (VB) potentials of MoSe2 and BiOCl. In our previous studies [14,62], we have calculated the potentials of BiOCl CB and VB, which are +0.14 eV and +3.51 eV, respectively. Herein, we estimated the potentials of MoSe2 CB and VB by analyzing its UV-Vis absorption spectrum and Mott–Schottky curve. Firstly, the bandgap energy of MoSe2 nanosheets was calculated using Tauc plot via the following Kubelka–Munk equation [64]:(αhν)2 = A(hν − Eg)(1) where h, α, ν, A, and Eg are the Planck constant, absorption coefficient, light frequency, constant value, and bandgap energy, respectively. As shown in Figure 6A, the bandgap energy of MoSe2 was estimated to be 1.9 eV, similar to the value of the previous reports [52,65,66]. Then, the potential of MoSe2 CB edge was determined by Mott–Schottky analysis [67]. As shown in Figure 6B, the potential of MoSe2 CB (ECB) was estimated using the extrapolation of the Mott–Schottky plots at different frequencies (1 kHz, 2 kHz, and 3 kHz) to be −0.59 V (vs. NHE). According to the equation of EVB = ECB + Eg (EVB is the potential of VB), the potential of MoSe2 VB was further calculated to be 1.31 eV. On the basis of the CB and VB potentials of BiOCl and MoSe2, BiOCl/MoSe2 should be ascribed to one of the three types of heterojunction, i.e., Type-II, direct Z-scheme, and S-scheme. Firstly, assuming that BiOCl/MoSe2 is a Type-II semiconductor, the electrons on MoSe2 CB would migrate to BiOCl CB. Given that the potential of BiOCl CB (0.14 eV vs. NHE) is more positive than E0(O2/•O2−) (−0.33 eV vs. MHE) [68,69,70], the adsorbed O2 cannot be reduced by the electrons on BiOCl CB to form •O2−. Similarly, since the potential of MoSe2 VB (1.31 eV vs. NHE) is more negative than E0(•OH/OH−) (1.99 eV vs. NHE) [68,69,70], the holes on MoSe2 VB cannot oxidize OH– into •OH. However, the presence of •O2− and •OH has been proved by the radical trapping experiments (Figure 5F), implying that BiOCl/MoSe2 is not a traditional Type-II semiconductor and the electrons for •O2− production and the holes for •OH production come from the MoSe2 CB and BiOCl VB, respectively. Moreover, Z-scheme heterojunction also has a theoretical problem in explaining the transfer pathway of photogenerated electrons and holes in BiOCl/MoSe2: from the perspective of charge transfer, the electrons on MoSe2 CB will preferentially recombine with the holes on BiOCl VB, rather than the electrons on BiOCl CB recombine with the holes on MoSe2 VB. The S-scheme heterojunction is more reasonable to illustrate the transfer pathway of photogenerated electrons and holes in BiOCl/MoSe2 [39,41,71,72]—in this composite photocatalytic system, BiOCl is the oxidation photocatalyst (OP) and MoSe2 is the reduction photocatalyst (RP), both of which form an S-scheme heterojunction [39,41,71,72]. After the two components are in close contact, the electrons in MoSe2 spontaneously transfer to BiOCl, producing an electron depletion layer and electron accumulation layer near the interface of MoSe2 and BiOCl, respectively. Thus, MoSe2 would be positively charged and BiOCl would be positively charged, forming an internal electric field directing from MoSe2 to BiOCl. Meanwhile, after BiOCl and MoSe2 contact together, their Fermi energy should be aligned to the same level. Thus, the Fermi levels of BiOCl and should upward shift and upward shift, respectively, together with the band bending at their interfaces. Both the coulomb force of electric field and the band bending urge the photogenerated electrons from BiOCl to recombine with the holes from MoSe2 VB. Due to the band bending, the electrons on MoSe2 CB and holes on BiOCl will be reserved. Based on the above experimental results and analyses, the degradation mechanism of organic pollutants over S-scheme BiOCl/MoSe2 was proposed: As illustrated in Figure 7, under simulated sunlight irradiation, both BiOCl and MoSe2 can produce holes on their VB and electrons on their CB. Using the acceleration of internal electric field, the photogenerated electrons on BiOCl CB and the holes on MoSe2 would be recombined. As a result, the powerful electrons on MoSe2 CB and the powerful holes on BiOCl VB would be reserved. Subsequently, the electrons on MoSe2 CB would react with adsorbed O2 to form •O2−. Meanwhile, some holes on the BiOCl VB would oxidize OH− to produce •OH. All of •O2−, •OH, and h+ take part in the degradation of organic pollutants. 4. Conclusions In summary, S-scheme BiOCl/MoSe2 heterojunction was fabricated via a modified solvothermal method. It was found that the thin MoSe2 nanosheets are uniformly wrapped on the surface of BiOCl microcrystals to form a shell structure. The MoSe2 diffraction peaks of MoSe2 and the different BiOCl/MoSe2 samples are very weak due to its low crystallinity and thin layer structure. The UV-Vis diffuse reflectance spectra show that all the BiOCl/MoSe2 samples exhibit a significantly enhanced absorption in the visible and near-infrared light region when compared with BiOCl, and the absorption intensity gradually increases with the increase of MoSe2 content. From the photoluminescence spectra, transient photocurrents, and electrochemical impedance spectra, it can be concluded that the BiOCl/MoSe2 heterojunction can effectively promote the transfer of photogenerated charge carriers. The results of MO and SD degradations indicate that all the BiOCl/MoSe2 samples display an evidently enhanced photocatalytic activity compared to single BiOCl and MoSe2, and the optimal MoSe2 loading amount for obtaining the highest photocatalytic activity is 30 wt.%. The radical trapping experiments disclosed that all h+, •O2−, and •OH take part in the degradation of organic pollutants and h+ plays a more important role than •O2− and •OH. By further analyzing the potentials of BiOCl and MoSe2 CB and VB, it can be deduced that the BiOCl/MoSe2 follows an S-scheme photocatalytic mechanism. We think that this study provides a reference for fabricating the S-scheme photocatalytic materials to eliminate the organic pollutants in wastewater under sunlight irradiation. Acknowledgments All authors gratefully acknowledge the support of Science and Technology on Particle Transport and Separation Laboratory. Author Contributions Conceptualization, B.T., J.Z. and Z.G.; methodology, Y.H., F.C. and Z.G.; formal analysis, Y.H. and Z.G.; Investigation, Y.L. (Yusheng Luo); data curation, F.C.; writing—original draft preparation, Y.H.; writing—review and editing, B.T.; visualization, L.Z. and Y.L. (Yufeng Lu); supervision, B.T. and J.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A) SEM image of BiOCl. (B–D) TEM images of (B) BiOCl, (C) MoSe2, and (D) BiOCl/MoSe2-30. (E,F) HR-TEM images of BiOCl/MoSe2-30. Figure 2 XRD patterns of MoSe2, BiOCl, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50. Figure 3 (A) UV−Vis DRS spectra of MoSe2, BiOCl, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50 in the UV and visible light region. (B) DRS spectra of MoSe2 in the UV, visible light, and NIR region. (C) PL spectra of BiOCl, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50. (D) Enhanced PL spectra of BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50. Figure 4 (A) Transient photocurrents of MoSe2, BiOCl, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50 under simulated sunlight irradiation; (B) Nyquist plots of the electrochemical impedance spectra of BiOCl, BiOCl/MoSe2-10, BiOCl/MoSe2-30, and BiOCl/MoSe2-50. Figure 5 (A,B) Photocatalytic degradation curves of (A) MO and (B) SD over the different photocatalysts under simulated sunlight irradiation. Corresponding fitted degradation kinetic curves of (C) MO and (D) SD. (E) Cyclic photocatalytic degradations of MO and SD over BiOCl/MoSe2-30. The reaction time of each cycle experiment for MO is 120 min and that for SD is 4 h. (F) Photocatalytic degradation rates of MO over BiOCl/MoSe2-30 in the presence of different radical scavengers. Figure 6 (A) Plots of (αhν)1/2 (MoSe2) versus photon energy (hν); (B) Mott–Schottky plots of MoSe2. Figure 7 Proposed photocatalytic mechanism of S-scheme BiOCl/MoSe2. sensors-22-03344-t001_Table 1 Table 1 The kinetic constants of photocatalytic degradation of MO and SD over the different samples. Sample MoSe2 BiOCl BiOCl/MoSe2-10 BiOCl/MoSe2-30 BiOCl/MoSe2-50 MO (min−1) 0.0020 0.0027 0.0063 0.0307 0.0082 SD (h−1) 0.1246 0.3258 0.5829 0.9323 0.4004 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Som I. Roy M. Saha R. Advances in nanomaterial-based water treatment approaches for photocatalytic degradation of water pollutants ChemCatChem 2020 12 3409 3433 10.1002/cctc.201902081 2. Ren G.M. Han H.T. Wang Y.X. Liu S.T. Zhao J.Y. Meng X.C. Li Z.Z. Recent advances of photocatalytic application in watertreatment: A review Nanomaterials 2021 11 1804 10.3390/nano11071804 34361190 3. Natarajan S. Bajaj H.C. Tayade R.J. Recent advances based on the synergetic effect of adsorption for removal of dyes from waste water using photocatalytic process J. Environ. Sci. 2018 65 201 222 10.1016/j.jes.2017.03.011 29548392 4. Molinari R. Pirillo F. Loddo V. Palmisano L. Heterogeneous photocatalytic degradation of pharmaceuticals in water by using polycrystalline TiO2 and a nanofiltration membrane reactor Catal. Today 2006 118 205 213 10.1016/j.cattod.2005.11.091 5. Mendez-Arriaga F. Esplugas S. Giménez J. Photocatalytic degradation of non−steroidal anti−inflammatory drugs with TiO2 and simulated solar irradiation Water Res. 2008 42 585 594 10.1016/j.watres.2007.08.002 17761209 6. Hu J.L. Yang Q.H. Lin H. Ye Y.P. He Q. Zhang J.N. Qian H.S. Mesoporous silica nanospheres decorated with CdS nanocrystals for enhanced photocatalytic and excellent antibacterial activities Nanoscale 2013 5 6327 6332 10.1039/c3nr01329d 23760602 7. Dong R.F. Tian B.Z. Zhang J.L. Wang T.T. Tao Q.S. Bao S.Y. Yang F. Zeng C.Y. AgBr@Ag/TiO2 core−shell composite with excellent visible light photocatalytic activity and hydrothermal stability Catal. Commun. 2013 38 16 20 10.1016/j.catcom.2013.04.006 8. Elmolla E.S. Chaudhuri M. Photocatalytic degradation of amoxicillin, ampicillin and cloxacillin antibiotics in aqueous solution using UV/TiO2 and UV/H2O2/TiO2 photocatalysis Desalination 2010 252 46 52 10.1016/j.desal.2009.11.003 9. Sarayu K. Sandhya S. Current technologies for biological treatment of textile wastewater—A review Appl. Biochem. Biotechnol. 2012 167 645 661 10.1007/s12010-012-9716-6 22585363 10. Palominos R.A. Mondaca M.A. Giraldo A. Peñuela G. Perez-Moya M. Mansilla H.D. Photocatalytic oxidation of the antibiotic tetracycline on TiO2 and ZnO suspensions Catal. Today 2009 144 100 105 10.1016/j.cattod.2008.12.031 11. Wang P.H. Yap P.S. Lim T.T. C−N−S tridoped TiO2 for photocatalytic degradation of tetracycline under visible−light irradiation Appl. Catal. A 2011 399 252 261 10.1016/j.apcata.2011.04.008 12. Crini G. Lichtfouse E. Advantages and disadvantages of techniques used for wastewater treatment Environ. Chem. Lett. 2019 17 145 155 10.1007/s10311-018-0785-9 13. Bao S.Y. Wu Q.F. Chang S.Z. Tian B.Z. Zhang J.L. Z-scheme CdS−Au−BiVO4 with enhanced photocatalytic activity for organic contaminant decomposition Catal. Sci. Technol. 2017 7 124 132 10.1039/C6CY01980C 14. Li Q.Y. Guan Z.P. Wu D. Zhao X.G. Bao S.Y. Tian B.Z. Zhang J.L. Z-scheme BiOCl-Au-CdS heterostructure with enhanced sunlight-driven photocatalytic activity in degrading water dyes and antibiotics ACS Sustain. Chem. Eng. 2017 5 6958 6968 10.1021/acssuschemeng.7b01157 15. Kong W.H. Wang S.L. Wu D. Chen C.R. Luo Y.S. Pei Y.T. Tian B.Z. Zhang J.L. Fabrication of 3D sponge@AgBr-AgCl/Ag and tubular photoreactor for continuous wastewater purification under sunlight irradiation ACS Sustain. Chem. Eng. 2019 7 14051 14063 10.1021/acssuschemeng.9b02575 16. Cheng T.T. Gao H.J. Liu G.R. Pu Z.S. Wang S.F. Yi Z. Wu X.W. Yang H. Preparation of core-shell heterojunction photocatalysts by coating CdS nanoparticles onto Bi4Ti3O12 hierarchical microspheres and their photocatalytic removal of organic pollutants and Cr(VI) ions Colloid Surf. A 2022 633 127918 10.1016/j.colsurfa.2021.127918 17. Li L.X. Gao H.J. Yi Z. Wang S.F. Wu X.W. Li R.S. Yang H. Comparative investigation on synthesis, morphological tailoring and photocatalytic activities of Bi2O2CO3 nanostructures Colloid Surf. A 2022 644 128758 10.1016/j.colsurfa.2022.128758 18. Chen H. Chen Z.H. Yang H. Wen L.H. Yi Z. Zhou Z.G. Dai B. Zhang J.G. Wu X.W. Wu P.H. Multi-mode surface plasmon resonance absorber based on dart-type single-layer graphene RSC Adv. 2022 12 7821 7829 10.1039/D2RA00611A 35424732 19. Li L.X. Sun X.F. Xian T. Gao H.J. Wang S.F. Yi Z. Wu X.W. Yang H. Template-free synthesis of Bi2O2CO3 hierarchical nanotubes self-assembled from ordered nanoplates for promising photocatalytic application Phys. Chem. Chem. Phys. 2022 24 8279 8295 10.1039/D1CP05952A 35319037 20. Lei Y.Q. Wang G.H. Song S.Y. Fan W.Q. Zhang H.J. Synthesis, characterization and assembly of BiOCl nanostructure and their photocatalytic properties CrystEngComm 2009 11 1857 1862 10.1039/b909013b 21. Zhang X. Ai Z.H. Jia F.L. Zhang L.Z. Generalized one-pot synthesis, characterization, and photocatalytic activity of hierarchical BiOX (X = Cl, Br, I) nanoplate microspheres J. Phys. Chem. C 2008 112 747 753 10.1021/jp077471t 22. Guan M.L. Xiao C. Zhang J. Fan S.J. An R. Cheng Q.M. Xie J.F. Zhou M. Ye B.J. Xie Y. Vacancy associates promoting solar–driven photocatalytic activity of ultrathin bismuth oxychloride nanosheets J. Am. Chem. Soc. 2013 135 10411 10417 10.1021/ja402956f 23782301 23. Zhao K. Zhang L.Z. Wang J.J. Li Q.X. He W.W. Yin J.J. Surface structure–dependent molecular oxygen activation of BiOCl single–crystalline nanosheets J. Am. Chem. Soc. 2013 135 15750 15753 10.1021/ja4092903 24116848 24. Ye L.Q. Deng K.J. Xu F. Tian L.H. Peng T.Y. Zan L. Increasing visible–light absorption for photocatalysis with black BiOCl Phys. Chem. Chem. Phys. 2012 14 82 85 10.1039/C1CP22876E 22080233 25. Weng S.X. Chen B.B. Xie L.Y. Zheng Z.Y. Liu P. Facile in situ synthesis of a Bi/BiOCl nanocomposite with high photocatalytic activity J. Mater. Chem. A 2013 1 3068 3075 10.1039/c2ta01004f 26. Dong F. Xiong T. Yan S. Wang H.Q. Sun Y.J. Zhang Y.X. Huang H.W. Wu Z.B. Facets and defects cooperatively promote visible light plasmonic photocatalysis with Bi nanowires@BiOCl nanosheets J. Catal. 2016 344 401 410 10.1016/j.jcat.2016.10.005 27. Jiang J. Zhang L.Z. Li H. He W.W. Yin J.J. Self–doping and surface plasmon modification induced visible light photocatalysis of BiOCl Nanoscale 2013 5 10573 10581 10.1039/c3nr03597b 24056871 28. Tan C.W. Zhu G.Q. Hojamberdiev M. Okada K. Liang J.C. Luo X. Liu P. Liu Y. Co3O4 nanoparticles–loaded BiOCl nanoplates with the dominant {001} facets: Efficient photodegradation of organic dyes under visible light Appl. Catal. B 2014 152–153 425 436 10.1016/j.apcatb.2014.01.044 29. Li T.B. Chen G. Zhou C. Shen Z.Y. Jin R.C. Sun J.X. New photocatalyst BiOCl/BiOI composites with highly enhanced visible light photocatalytic performances Dalton Trans. 2011 40 6751 6758 10.1039/c1dt10471c 21617792 30. Yu L.H. Zhang X.Y. Li G.W. Cao Y.T. Shao Y. Li D.Z. Highly efficient Bi2O2CO3/BiOCl photocatalyst based on heterojunction with enhanced dye–sensitization Appl. Catal. B 2016 187 301 309 10.1016/j.apcatb.2016.01.045 31. Bao S.Y. Wang Z. Zhang J.L. Tian B.Z. Facet-heterojunction-based Z-Scheme BiVO4{010} microplates decorated with AgBr-Ag nanoparticles for the photocatalytic inactivation of bacteria and the decomposition of organic contaminants ACS Appl. Nano Mater. 2020 3 8604 8617 10.1021/acsanm.0c00703 32. Yuan Z. Huang H. Li N. Chen D. Xu Q. Li H. He J. Lu J. All-solid-state WO3/TQDs/In2S3 Z-scheme heterojunctions bridged by Ti3C2 quantum dots for efficient removal of hexavalent chromium and bisphenol A J. Hazard. Mater. 2021 409 125027 10.1016/j.jhazmat.2020.125027 33421880 33. Wen X.J. Niu C.G. Zhang L. Liang C. Guo H. Zeng G.M. Photocatalytic degradation of ciprofloxacin by a novel Z-scheme CeO2–Ag/AgBr photocatalyst: Influencing factors, possible degradation pathways, and mechanism insight J. Catal. 2018 358 141 154 10.1016/j.jcat.2017.11.029 34. Jo W.K. Natarajan T.S. Influence of TiO2 morphology on the photocatalytic efficiency of direct Z-scheme g-C3N4/TiO2 photocatalysts for isoniazid degradation Chem. Eng. J. 2015 281 549 565 10.1016/j.cej.2015.06.120 35. Jin Z. Hu R. Wang H. Hu J. Ren T. One-step impregnation method to prepare direct Z-scheme LaCoO3/g-C3N4 heterojunction photocatalysts for phenol degradation under visible light Appl. Surf. Sci. 2019 491 432 442 10.1016/j.apsusc.2019.06.143 36. Huang S. Zhang J. Qin Y. Song F. Du C. Su Y. Direct Z-scheme SnO2/Bi2Sn2O7 photocatalyst for antibiotics removal: Insight on the enhanced photocatalytic performance and promoted charge separation mechanism J. Photochem. Photobiol. A 2021 404 112947 10.1016/j.jphotochem.2020.112947 37. Shangguan X.Y. Fang B.L. Xu C.X. Tan Y. Chen Y.G. Xia Z.J. Chen W. Fabrication of direct Z-scheme FeIn2S4/Bi2WO6 hierarchical heterostructures with enhanced photocatalytic activity for tetracycline hydrochloride photodagradation Ceram. Int. 2021 47 6318 6328 10.1016/j.ceramint.2020.10.210 38. Li G. Wang B. Zhang J. Wang R. Liu H. Rational construction of a direct Z-scheme g-C3N4/CdS photocatalyst with enhanced visible light photocatalytic activity and degradation of erythromycin and tetracycline Appl. Surf. Sci. 2019 478 1056 1064 10.1016/j.apsusc.2019.02.035 39. Xu Q.L. Zhang L.Y. Cheng B. Fan J.J. Yu J.G. S-Scheme heterojunction photocatalyst Chem 2020 6 1543 1559 10.1016/j.chempr.2020.06.010 40. Bao Y.J. Song S.Q. Yao G.J. Jiang S.J. S-Scheme photocatalytic systems Sol. RRL 2021 5 2100118 10.1002/solr.202100118 41. Luo Y.S. Chi Z.L. Zhang J.L. Tian B.Z. Photothermocatalytic system designed by facet-heterojunction to enhance the synergistic effect of toluene oxidation ChemCatChem 2022 14 e202101958 10.1002/cctc.202101958 42. Wang J. Zhang Q. Deng F. Luo X.B. Dionysiou D.D. Rapid toxicity elimination of organic pollutants by the photocatalysis of environment-friendly and magnetically recoverable step-scheme SnFe2O4/ZnFe2O4 nano-heterojunctions Chem. Eng. J. 2020 379 122264 10.1016/j.cej.2019.122264 43. He R.A. Liu H.J. Liu H.M. Xu D.F. Zhang L.Y. S-scheme photocatalyst Bi2O3/TiO2 nanofiber with improved photocatalytic performance J. Mater. Sci. Technol. 2020 52 145 151 44. Gogoi D. Makkar P. Ghosh N.N. Solar light-irradiated photocatalytic degradation of model dyes and industrial dyes by a magnetic CoFe2O4–gC3N4 S-scheme heterojunction photocatalyst ACS Omega 2021 6 4831 4841 10.1021/acsomega.0c05809 33644591 45. Jia X.M. Han Q.F. Liu H.Z. Li S.Z. Bi H.P. A dual strategy to construct flowerlike S-scheme BiOBr/BiOAc1−xBrx heterojunction with enhanced visible-light photocatalytic activity Chem. Eng. J. 2020 399 125701 10.1016/j.cej.2020.125701 46. Dou L. Jin X.Y. Chen J.F. Zhong J.B. Li J.Z. Zeng Y. Duan R. One-pot solvothermal fabrication of S-scheme OVs-Bi2O3/Bi2SiO5 microsphere heterojunctions with enhanced photocatalytic performance toward decontamination of organic pollutants Appl. Surf. Sci. 2020 527 146775 10.1016/j.apsusc.2020.146775 47. Lian X. Xue W.H. Dong S. Liu E.Z. Li H. Xu K.Z. Construction of S-scheme Bi2WO6/g-C3N4 heterostructure nanosheets with enhanced visible-light photocatalytic degradation for ammonium dinitramide J. Hazard. Mater. 2021 412 125217 10.1016/j.jhazmat.2021.125217 33517062 48. Huang K.J. Zhang J.Z. Fan Y. Preparation of layered MoSe2 nanosheets on Ni-foam substrate with enhanced supercapacitor performance Mater. Lett. 2015 152 244 247 10.1016/j.matlet.2015.03.130 49. Eftekhari A. Molybdenum diselenide (MoSe2) for energy storage, catalysis, and optoelectronics Appl. Mater. Today 2017 8 1 7 10.1016/j.apmt.2017.01.006 50. Liu Z. Li N. Zhao H. Du Y. Colloidally synthesized MoSe2/graphene hybrid nanostructures as efficient electrocatalysts for hydrogen evolution J. Mater. Chem. A 2015 3 19706 19710 10.1039/C5TA05223H 51. Zhang H. Tang G.G. Wan X. Xu J. Tang H. High-efficiency all-solid-state Z-scheme Ag3PO4/g-C3N4/MoSe2 photocatalyst with boosted visible-light photocatalytic performance for antibiotic elimination Appl. Surf. Sci. 2020 530 147234 10.1016/j.apsusc.2020.147234 52. Zheng X.T. Yang L.M. Li Y.B. Yang L.X. Luo S.L. Direct Z-scheme MoSe2 decorating TiO2 nanotube arrays photocatalyst for water decontamination Electrochim. Acta 2019 298 663 669 10.1016/j.electacta.2018.12.130 53. Tahir M.B. Asiri A.M. Nabi G. Rafique M. Sagir M. Fabrication of heterogeneous photocatalysts for insight role of carbon nanofibre in hierarchical WO3/MoSe2 composite for enhanced photocatalytic hydrogen generation Ceram. Int. 2019 45 5547 5552 10.1016/j.ceramint.2018.12.012 54. Zhang S.M. Chen L. Shen J. Li Z.F. Wu Z.H. Feng W.H. Xu K.Q. Xu D.F. Chen X.H. Zhang S.Y. TiO2@MoSe2 line-to-face heterostructure: An advanced photocatalyst for highly efficient reduction of Cr (VI) Ceram. Int. 2019 45 18065 18072 10.1016/j.ceramint.2019.06.027 55. Jiang J. Zhao K. Xiao X.Y. Zhang L.Z. Synthesis and facet-dependent phoyoreactivity of BiOCl single-crystalline nanosheets J. Am. Chem. Soc. 2012 134 4473 4476 10.1021/ja210484t 22379954 56. Yang S. Shao C.L. Zhou X.J. Li X.H. Tao R. Li X.W. Liu S. Liu Y.C. MoSe2/TiO2 nanofibers for cycling photocatalytic removing water pollutants under UV-Vis-NIR light ACS Appl. Nano Mater. 2020 3 2278 2287 10.1021/acsanm.9b02357 57. Fan C. Wei Z. Yang S. Li J. Synthesis of MoSe2 flower-like nanostructures and their photo-responsive properties RSC Adv. 2014 4 775 778 10.1039/C3RA42564A 58. Xiao P. Lou J. Zhang H. Song W. Wu X.L. Lin H. Chen J. Liu S. Wang X. Enhanced visible-light-driven photocatalysis from WS2 quantum dots coupled to BiOCl nanosheets: Synergistic effect and mechanism insight Catal. Sci. Technol. 2018 8 201 209 10.1039/C7CY01784G 59. Liu Y. Zhang P. Tian B.Z. Zhang J.L. Core-shell structural CdS@SnO2 nanorods with excellent visible-light photocatalytic activity for the selective oxidation of benzyl alcohol to benzaldehyde ACS Appl. Mater. Interfaces 2015 7 13849 13858 10.1021/acsami.5b04128 26057028 60. Wang S. Han Y. Luo Y. Ma Y. Zhang J. Tian B. Au thorn-decorated TiO2 hierarchical microspheres with superior photocatalytic bactericidal activity under red and NIR light irradiation J. Alloys Compd. 2022 910 164485 10.1016/j.jallcom.2022.164485 61. Li H. Yang C. Wang X. Zhang J. Xi J. Du G. Ji Z. Mixed 3D/2D dimensional TiO2 nanoflowers/MoSe2 nanosheets for enhanced photoelectrochemical hydrogen generation J. Am. Chem. Soc. 2019 103 1187 1196 62. Han Y.Q. Li Q.Y. Bao S.Y. Lu Y.F. Guan Z.P. Zhang J.L. Tian B.Z. Z-scheme heterostructure BiOCl-Ag-AgBr with enhanced sunlight-driven photocatalytic activity in simultaneous removal of Cr6+ and phenol contaminants Catal. Today 2021 376 151 161 63. Guan Z.P. Li Q.Y. Shen B. Bao S.Y. Zhang J.L. Tian B.Z. Fabrication of Co3O4 and Au co-modified BiOBr flower-like microspheres with high photocatalytic efficiency for sulfadiazine degradation Sep. Purif. Technol. 2020 234 116100 10.1016/j.seppur.2019.116100 64. Dion M.C.L. Fauzia V. Imawan C. The Effect of deposition of MoSe2 nanosheets on the performance of a ZnO-based UV detector J. Phys. Conf. Ser. 2021 1951 012006 10.1088/1742-6596/1951/1/012006 65. Kwon I.S. Kwak I.H. Debela T.T. Abbas H.G. Park Y.C. Ahn J. Park J. Kang H.S. Se-rich MoSe2 nanosheets and their superior electrocatalytic performance for hydrogen evolution reaction ACS Nano 2020 14 6295 6304 10.1021/acsnano.0c02593 32356967 66. Wang G.Y. Zhang Y.Z. You C.Y. Liu B.Y. Yang Y.H. Li H.J.W. Cui A.J. Liu D.M. Yan H. Two dimensional materials based photodetectors Infrared Phys. Technol. 2018 88 149 173 10.1016/j.infrared.2017.11.009 67. Bao S.Y. Wang Z.Q. Gong X.Q. Zeng C.Y. Wu Q.F. Tian B.Z. Zhang J.L. AgBr tetradecahedrons with co-exposed {100} and {111} facets: Simple fabrication and enhancing spatial charge separation using facet heterojunctions J. Mater. Chem. A 2016 4 18570 18577 10.1039/C6TA06594E 68. Hong X.D. Li Y. Wang X. Long J.P. Liang B. Carbon nanosheet/MnO2/BiOCl ternary composite for degradation of organic pollutants J. Alloys Compd. 2022 891 162090 10.1016/j.jallcom.2021.162090 69. Acharya L. Nayak S. Pattnaik S.P. Acharya R. Parida K. Resurrection of boron nitride in p-n type-II boron nitride/B-doped-g-C3N4 nanocomposite during solid-state Z-scheme charge transfer path for the degradation of tetracycline hydrochloride J. Colloid Interface Sci. 2020 566 211 223 10.1016/j.jcis.2020.01.074 32006817 70. Tang M.L. Ao Y.H. Wang P.F. Wang C. All-solid-state Z-scheme WO3 nanorod/ZnIn2S4 composite photocatalysts for the effective degradation of nitenpyram under visible light irradiation J. Hazard. Mater. 2020 387 121713 10.1016/j.jhazmat.2019.121713 31767501 71. Cheng C. He B.W. Fan J.J. Cheng B. Cao S.W. Yu J.G. An Inorganic/Organic S-scheme heterojunction H2-production photocatalyst and its charge transfer mechanism Adv. Mater. 2021 33 2100317 10.1002/adma.202100317 33904199 72. Deng H.Z. Fei X.G. Yang Y. Fan J.J. Yu J.G. Cheng B. Zhang L.Y. S-scheme heterojunction based on p-type ZnMn2O4 and n-type ZnO with improved photocatalytic CO2 reduction activity Chem. Eng. J. 2021 409 127377 10.1016/j.cej.2020.127377

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092413 jcm-11-02413 Article To Optimize Radiotherapeutic Plans for Superior Tumor Coverage Predicts Malignant Glioma Prognosis and Normal Tissue Complication Probability Kuo Chun-Yuan 12 Liu Wei-Hsiu 34 https://orcid.org/0000-0003-4823-6541 Chou Yu-Ching 5 Li Ming-Hsien 1 Tsai Jo-Ting 16 Huang David YC 7 https://orcid.org/0000-0003-2784-5604 Lin Jang-Chun 16* Verma Vivek Academic Editor 1 Department of Radiation Oncology, Shuang Ho Hospital, Taipei Medical University, Taipei 11031, Taiwan; 10637@s.tmu.edu.tw (C.-Y.K.); 09112@s.tmu.edu.tw (M.-H.L.); 10576@s.tmu.edu.tw (J.-T.T.) 2 School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 11031, Taiwan 3 Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical Center, No.325, Sec. 2, Cheng-Kung Road, Taipei 11490, Taiwan; doc20444@mail.ndmctsgh.edu.tw 4 Department of Surgery, School of Medicine, National Defense Medical Center, Taipei 11490, Taiwan 5 School of Public Health, National Defense Medical Center, Taipei 11490, Taiwan; trishow@mail.ndmctsgh.edu.tw 6 Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan 7 Department of Medical Physics, Duke University, Durham, NC 27708, USA; yh126@duke.edu * Correspondence: 13451@s.tmu.edu.tw; Tel.: +886-2-22490088; Fax: +886-2-22484822 25 4 2022 5 2022 11 9 241305 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Background: Radiotherapy (RT) provides a modern treatment to enhance the malignant glioma control rate. The purpose of our study was to determine the effect of tumor coverage on disease prognosis and to predict optimal RT plans to achieve a lower normal tissue complication probability (NTCP). Methods: Ten malignant-glioma patients with tumors adjacent to organs at risk (OARs) were collected. The patients were divided into two groups according to adequate coverage or not, and prognosis was analyzed. Then, using intensity-modulated radiation therapy (IMRT), volume-modulated arc therapy (VMAT), and helical tomotherapy (TOMO) to simulate new treatment plans for 10 patients, the advantages of these planning systems were revealed for subsequent prediction of NTCP. Results: The results of clinical analysis indicated that overall survival (p = 0.078) between the adequate and inadequate groups showed no differences, while the adequate group had better recurrence-free survival (p = 0.018) and progression-free survival (p = 0.009). TOMO had better CI (p < 0.001) and also predicted a lower total-irradiated dose to the normal brain (p = 0.001) and a lower NTCP (p = 0.027). Conclusions: The TOMO system provided optimal therapeutic planning, reducing NTCP and achieving better coverage. Combined with the clinical results, our findings suggest that TOMO can make malignant glioma patients close to OARs achieve better disease control. malignant glioma IMRT VMAT TOMO NTCP ==== Body pmc1. Introduction Malignant glioma is the most common and most aggressive type of brain cancer [1]. In addition, malignant glioma is characterized by a poor prognosis and high local recurrence rate. Recent studies have shown that the median time to local recurrence and progression of glioblastoma multiforme (GBM) is 7–9 months [2,3,4,5]. Currently, the standard treatment for GBM in clinical practice is to remove as much of the tumor as possible, followed by concurrent chemoradiotherapy (CCRT) after operation [6,7]. If radiotherapy (RT) is not started within 6 weeks after complete tumor resection, the survival rate of GBM patients is significantly reduced [8]. RT, as part of the main treatment course for patients with malignant gliomas, is an efficient and targeted treatment that can destroy possible malignant cells around brain tissues after surgical resection. From clinical observation, the high-quality RT plan requires that the tumor coverage by the 100% prescribed dose is no less than 95% of the planning target volume (PTV). However, the tumor coverage must sometimes be limited to avoid damaging adjacent organs at risk (OARs), such as the brain stem, optic nerve, optic chiasm, lens, and cochlea/inner ear, reducing the quality of RT [9,10]. The closer the tumor is to the OARs, the more difficult it can be to determine the appropriate tumor coverage; insufficient tumor coverage can affect the patients’ prognosis, while tumor coverage that meets the requirement for adequate high-quality RT could result in the delivery of a high radiation dose to the OARs and subsequently could cause related complications and side effects. Moreover, because the life expectancy of GBM patients is significantly shortened, retaining neurological function and maintaining the ability to perform daily activities are important treatment goals [11,12,13]. Along with the evolution of RT technology, intensity-modulated radiation therapy (IMRT) has also been developed. Compared with three-dimensional conformal radiation therapy (3D-CRT), IMRT has better dose conformity, lower doses to OARs, and more rapid dose attenuation outside the target area while reaching similar or better tumor coverage, thereby better protecting the surrounding OARs and normal tissues [14,15,16,17,18]. Compared with IMRT, the greatest advantage of volume-modulated arc therapy (VMAT) is that the performance of VMAT is similar to that of IMRT but with a shorter dose delivery time, thereby improving treatment efficacy [19,20]. During VMAT, the rotational speed of the gantry, the output dose rate, and the shape of the treatment field, which can be adjusted by moving the leaves of the multileaf collimator (MLC), can be simultaneously changed [19,21]. Unlike IMRT and VMAT, which both use a linear accelerator (Linac) to deliver treatment, tomotherapy (TOMO) has a different mechanical configuration. TOMO applies helical radiation therapy by scanning with a fan beam emitted by a 6 MV single-photon energy Linac loaded on the circular gantry of a computed tomography (CT) scanner in a mode similar to CT scans, in combination with a treatment bed that can continuously move during treatment [22]. This study aimed to evaluate the effect of tumor coverage on malignant glioma response rate and the dosimetric differences among IMRT, VMAT, and TOMO for the treatment of malignant gliomas adjacent to OARs by comparing the tumor coverage and normal tissue complication probability (NTCP) of adjacent OARs. 2. Materials and Methods 2.1. The Patient Data and Simulation A retrospective design was used to collect data from 10 patients with malignant glioma treated between December 2011 and November 2016, including 1 with oligoastrocytoma (OA), 3 with anaplastic astrocytoma (AA), and 6 with GBM. The clinical target volume (CTV) in the original computerized treatment plans of these 10 patients was close to at least 1 OAR, and in 9 patients, the tumors even caused different degrees of brain stem compression. The RT techniques were selected for these 10 patients based on the professional considerations of the attending physicians and the preferences of the patients. Five, two, and three cases were treated with IMRT, VMAT, and TOMO. The clinical condition of the 10 patients is listed in Table 1. All 10 patients underwent CT simulation using the Philips Brilliance CT Big Bore at our hospital while in the supine position. The head was fixed with a thermoplastic head mask. The scanning range was from approximately 3 cm above the top of the head to approximately 5 cm below the foramen magnum at a slice thickness of 3 mm. CT images and diagnostic magnetic resonance imaging (MRI) images were input into the Pinnacle3 treatment planning system (Philips HealthCare, Fitchburg, MA, USA) of our hospital for image registration so that the attending physicians could delineate the target area of the tumor and the adjacent OARs. High-risk CTV (CTV_H60) was defined as the resection cavity and MRI T1-weighted enhancement zone after tumor resection. Low-risk CTV (CTV_L46) was defined as CTV_H60 plus the isometric margin resulting from the expansion of the CTV_H60 by 2 cm in each direction and included the peritumor edema zone. Then, the high-risk PTV (PTV_H60) and low-risk PTV (PTV_L46) were obtained by extending a 3-mm isometric margin from the CTV_H60 and CTV_L46, respectively. The adjacent OARs included the brain stem, optic nerve, optic chiasm, lens, cochlea/inner ear, normal brain, etc. The volume of the normal brain was defined as the remaining brain tissue after excluding the CTV_H60, brain stem, and optic chiasm from the whole brain. 2.2. Planning Target and Organ Constraints Regardless of the original choices of RT techniques for these 10 cases, to compare the differences in the dosimetric performance of IMRT, VMAT, and TOMO, the same qualified medical physicist recreated the computerized treatment plans with the three RT techniques for the 10 cases in this study. Sequential boost, a commonly used clinical treatment method in our hospital, was used in all three computerized treatment plans. In phase I, a prescribed dose of 46 Gy was used to treat the PTV_L46 in 23 fractions. In phase II, a prescribed dose of 14 Gy was used to treat the PTV_H60 7 times for local dose enhancement. The clinical dose limits of adjacent OARs had to meet the requirements of the QUANTEC summary guideline [23]. In addition, the dose limit to each OAR in any stage of the computerized treatment plan had to be less than a certain proportion of the dose limit (depending on the ratio of the prescribed dose to the total dose at that stage). This conservative approach was applied to minimize the risk of complications in OARs so that the patients could have good quality of life after treatment. The PTV dose coverage requirements and the adjacent OAR clinical dose limit requirements in the three computerized treatment plans are listed in Table 2. 2.3. Radiotherapy Planning Technique In the computerized treatment plans for all three treatment techniques, 6 MV photon beams were used. At least six coplanar treatment beams were used in all of the step-and-shoot IMRT treatment plans, and one noncoplanar treatment beam was selectively used in combination as needed. The incidence angle of the treatment beam was selected based on the principle that the treatment beam should be incidental from the affected (ipsilateral) side whenever possible, and the incidence from the far (contralateral) side should be avoided as much as possible to reduce the dose to normal brain tissue. Three or four partial coplanar arcs were used in all of the VMAT treatment plans. The incidence angle of the arc beam was selected based on the same principle used to select the incidence angle of the treatment beam in the IMRT treatment plans. The inverse treatment planning of IMRT and VMAT was optimized using the Pinnacle3 treatment planning system (Philips HealthCare, Fitchburg, MA, USA) of our hospital, and the dose calculation grid size all had a resolution of 3 mm. The Linac used for IMRT and VMAT in our hospital is an Elekta Synergy Linear accelerator (Elekta, Stockholm, Sweden). The MLC is equipped with 40 pairs of 1 cm wide leaves. The built-in computerized treatment plan system TomoTherapy Hi-Art software (version 5.1.6) (Accuray, Madison, WI, USA) was used for inverse treatment planning for helical TOMO. The three major setting parameters were the field width, pitch, and modulation factor of the fan beam. Based on comprehensive consideration of the requirements and the treatment times for the clinical treatment plans, the medical physicist set the field width to 1.05 cm, the pitch to 0.430, and the initial range of the modulation factor to 2.0–4.0 for all TOMO computerized treatment plans, and the actual range of the modulation factor was 1.714–3.788 after completion of the treatment plans. In addition, due to the different sizes of the fields of view of the CT images of the 10 cases, the resolutions of the dose calculation grid size of the TOMO treatment plans were also slightly different, ranging from 1.73 mm to 2.63 mm. In this study, the dosimetric performances of IMRT, VMAT, and TOMO were compared by evaluating the quality of the computerized treatment plans for the three treatment techniques with several dosimetric parameters. In addition to the coverage of the PTV and the dose to adjacent OARs, the conformity index (CI), the gradient index (GI), the heterogeneity index (HI), and the NTCP of normal brain tissue were compared. CI is defined as follows, according to the Paddick conformity index [24]:CI=TVPIV2TV×PIV where TV is the volume of the planned target, PIV is the volume covered by the prescribed dose, and TVPIV is the volume of the part of the planned target covered by the prescribed dose. The closer the CI is to 1, the higher the dose conformity. GI is defined as follows, according to the Paddick gradient index [25]:GI=PIV50%PDPIV where PIV50%PD is the volume covered by 50% of the prescribed dose. GI represents the dose fall-off outside the TV, and the lower the GI, the better the protection of normal tissues. The HI is defined as follows in this study [26]:HI=(Dmax−Dmin)Dmean where Dmax is the maximum dose to the TV, Dmin is the minimum dose to the TV, and Dmean is the average dose to the TV. The lower the HI, the more uniform the dose to the TV. Because the tumors were adjacent to the OARs in the patients enrolled in this study, a conflict between the PTV coverage requirements and the adjacent OAR dose limit requirements could be expected. Subsequently, there must be a trade-off between the two, which is also a challenge of this study. Therefore, three scenarios were assumed to compare the advantages and disadvantages of IMRT, VMAT, and TOMO to identify planning benefits on tumor coverage, dose limitation of OARs, and NTCP: (1) When the three treatment techniques (IMRT_C, VMAT_C, and TOMO_C) all reached the adequate PTV coverage requirements, the doses to the adjacent OARs and the dosimetric parameters were compared. (2) When the three treatment techniques (IMRT_N, VMAT_N, and TOMO_N) all met the OAR dose limit requirements, the PTV coverage, no matter whether adequate or not, and the dosimetric parameters were compared. (3) For the same treatment technique, the effects of the adequate PTV coverage requirement and meeting the OAR dose limit requirement on the NTCP and prognosis were compared. 2.4. Statistical Analysis All data were expressed as frequency, percentage, and mean ± SD. Continuous and categorical variables were compared between different PTV coverage groups (adequate or inadequate group) with the Mann–Whitney U test or the chi-square test (or Fisher’s exact test), as appropriate. In addition, we used the Kaplan-Meier method to estimate the recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS) for patients. The log-rank test was used to evaluate differences in RFS, PFS, and OS between the different PTV coverage groups. Furthermore, we performed the Kruskal–Wallis test among different treatment types (IMRT, VMAT, and TOMO) on cancer tissue or normal tissue and the Mann–Whitney U Test between cancer tissue and normal tissue in the same treatment types for treatment parameters in phase I, phase II, and phase I + phase II. All statistical tests were two-sided, and a level of 0.05 was considered statistically significant. All data analyses were performed using SPSS version 23 (IBM SPSS Statistics 23). 3. Results 3.1. Patient Characteristics and Clinical Prognosis We separated the 10 patients into two groups according to the PTV coverage. The adequate group included patients who had PTV coverage of more than 95% prescribed dose in the 95% targeted volume. There were four patients in the adequate group, including two men and two women with three frontal lobe tumors and one parietal lesion. In contrast, six patients were in the inadequate group, including two men and four women with four frontal brain lesions and two temporal tumors. Table 1 shows that there was no significant difference between the two groups in terms of age, gender, ECOG, tumor location, tumor side of brain, operation type, WHO grade, or chemotherapy administration. Comparing the disease prognosis of malignant glioma between the two groups, there was no significant difference in overall survival (OS) (p = 0.078) between the adequate and inadequate groups, as shown in Figure 1. In contrast, better recurrence-free survival (RFS) (Figure 2a) and progression-free survival (PFS) (Figure 2b) were observed in the adequate coverage group, with statistically significant differences (p = 0.018 in RFS; p = 0.009 in PFS) compared to the inadequate group. These results suggest that optimal coverage of RT planning could have benefits in tumor local control. Therefore, we further arranged the dosimetric comparison of IMRT, VMAT, and TOMO to point out which planning can provide superior tumor coverage. It might be a hint that optimizing radiotherapeutic plans could make adequate tumor coverage to result in better RFS and PFS. 3.2. RT Simulated Planning Furthermore, we arranged the three different planning systems, including IMRT, VMAT, and TOMO, to re-plan the therapeutic programs under two optimal conditions. First, regarding consistency, to optimize PTV coverage and achieve adequate conditions, IMRT_C, VMAT_C, and TOMO _C were set to V95% ≥ 95% PTV. However, in the first situation, OARs might receive an excessive dose, inducing more complications after RT. Thus, in the second situation, the possible PTV coverage was as large as possible with optimal dose limitations to OARs. IMRT_N, VMAT_N, and TOMO _N could achieve these conditions as Figure 3. Thus, we attempted to cross-compare the three planning systems with different optimal targets or the same planning system under different situations. Those results are shown in Table 3. There was more optimal coverage with PTV and V100% in TOMO_C than with other RT planning (IMRT and VMAT) regardless of whether it was phase I or phase II planning (p = 0.002; p = 0.006). In phase I, TOMO_C planning had a lower PTV Dmax (p = 0.01) and Dmin (p = 0.001) and better CI (p < 0.001) and HI (p = 0.001) for the therapeutic programs. At the same time, TOMO_C could predict a lower total-irradiated dose to the normal brain (p = 0.001) and lower NTCP (p = 0.027), with significant differences observed compared to the first situation. However, VMAT_C had the lowest right lens dose, with significant differences observed when compared with TOMO_C and IMRT_C. Although TOMO_C could not achieve a better OAR dose than the other RT techniques under optimal coverage, the other OARs, except for right lens Dmax, were not significantly different among TOMO_C, VMAT_C, and IMRT_C. In TOMO_N, we found a lower PTV Dmin (p = 0.002) and PTV Dmax (p = 0.009) and better CI (p = 0.001) and HI (p = 0.004) in phase I planning. There was also a better brain stem dose (p = 0.005) in phase I and a lower total normal brain dose (p = 0.004) under phase I + phase II for malignant glioma patients. There were no differences among the three RT planning systems in NTCP after optimal dosimetry to OARs. In Table 4, we further analyze adequate planning with the three RT planning systems with optimal OARs or with the same planning system under different optimal situations. PTV_L46 was planned 46 Gy in 23 fractions in phase I planning, and following that, a prescribed dose of 14 Gy in 7 fractions was used to treat the PTV_H60 for local dose enhancement in phase II planning. Regardless of phase I or phase II planning under optimal dose limitations to OARs, there were no significant differences among the three RT planning systems, including IMRT_N, VMAT_N, and TOMO_N. In particular, the TOMO planning system could provide similar adequate PTV plans to both optimal targets, including V95% ≥ 95% PTV and OARs. However, when using the IMRT planning system to achieve optimal dose limitations to OARs, there was less adequate PTV coverage in IMRT_N than IMRT_C, showing a statistically significant difference (p = 0.003). VMAT_C also had more adequate planning for PTV coverage than VMAT_N (p = 0.033). 4. Discussion RT is a critical modality of treatment for patients with malignant gliomas, including WHO grade III and grade IV gliomas. In our previous study, optimal tumor coverage could not always be attained with the RT technique because of the dose limitation to OARs. At the same time, we also demonstrated that, regardless of the higher or lower tumor coverage rates of the RT program, it had similar effects on the overall survival of GBM patients [27]. Following advances in delivery and precision, RT should continue to play an important role in realizing optimal disease outcomes for patients with malignant glioma [28]. Therefore, we attempted to classify subgroups of patients from our previous research [27]. We found that, due to inadequate planning, the recurrence-free survival and progression-free survival of malignant glioma patients with irradiated areas adjacent to vital organs were significantly different from those of patients with optimal PTV coverage. Although overall survival was not affected by the tumor coverage rates of RT in our study, RT could be affected by treatments such as surgical interventions, chemotherapy and subsequent intensive care. According to Buckner et al., study in 2016 [29], the therapeutic benefit of CCRT seems to be better in IDH1-mutated oligoastrocytoma patients than RT alone. Therefore, multimodal treatments could improve overall survival in malignant glioma. A recent review article [30] has allowed an innovative tool, next-generation sequencing (NGS), to use liquid biopsy of glioma in the prediction of disease prognosis determining neural stem-like cells combined with different molecular markers to develop malignant glioma. These complicated modalities might induce differences in the disease survival rate and local tumor control. If there is a shorter time to tumor progression, patients should receive more medical interventions after the disease worsens. A series of RT planning studies showed that TOMO often has greater benefit in terms of organ preservation for patients with glioma [31], breast cancer [32], gastric cancer [33], and rectal cancer [34]. Contouring of high-grade glioma for RT planning has shown that TOMO could provide superior OAR sparing compared with VMAT and IMRT techniques. Although HI and CI seem optimal with the TOMO system, PTV coverage consistently presented no significant differences among TOMO, VMAT, and IMRT. Compared with Liu et al.’s publication [31], we found not only superior CI but also better PTV coverage and PTV Dmax with TOMO_C. Increasing evidence has shown that RT side effects can be reduced by planning RT in advance with high precision. A retrospective study [35] of prostate cancer patients analyzed rectal toxicity and proved that VMAT was more effective in decreasing proctitis than IMRT adding topical medications. The pulmonary and cardiac radiation dose of left breast cancer can be reduced significantly via the deep-inspiration-breath-hold technique RT [36] and skin toxicity can be decreased through image-guided RT planning for breast cancer [32]. Modern RT technology advances effectively through VMAT to achieve nodule regression of Merkel cell carcinoma and prevent those patients’ skin toxicity [37]. Proton therapy can provide glioma patients with better sparing of healthy brain tissue from the irradiated field and preserve neurocognition [38]. We also identified the probability of normal brain complications with three RT planning systems. The Pinnacle3 treatment planning system (Philips HealthCare, Fitchburg, MA, USA) could provide the NTCP to determine the toxicity of TOMO, VMAT and IMRT. Compared with VMAT and IMRT, TOMO_C can significantly decrease the likelihood of complications in normal brain tissues. In other words, TOMO_C predicts similar NTCP results as TOMO_N, suggesting that the TOMO system can further optimize tumor coverage and spare OARs to prevent neuropathy. To the best of our knowledge, this study is the first to confirm the correlation between neurotoxicity and RT techniques. 5. Conclusions Considered together, for patients with malignant glioma adjacent to OARs or that compresses the brain stem, the TOMO system could provide the optimal therapeutic plan to lessen the NTCP and obtain better coverage. In conclusion, our clinical results indicate that TOMO planning could allow malignant glioma patients requiring irradiation in areas adjacent to OARs (brain stem, optic chiasma, and inner ear). From clinical results, better coverage could make patients with malignant glioma have better RFS and PFS. Taken together, TOMO planning might have the trend to improve disease local control, and this conclusion should be proved after a randomized phase III study in the future. Author Contributions Conceptualization, J.-C.L. and C.-Y.K.; methodology, C.-Y.K.; software, Y.-C.C.; validation, J.-C.L., W.-H.L. and J.-T.T.; formal analysis, J.-T.T.; investigation, C.-Y.K. and D.Y.C.H.; resources, J.-C.L., M.-H.L. and J.-T.T.; data curation, J.-T.T.; writing—original draft preparation, J.-C.L. and W.-H.L.; writing—review and editing, J.-C.L., W.-H.L. and C.-Y.K.; funding acquisition, J.-C.L., C.-Y.K. and W.-H.L. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Shuang Ho Hospital, Taipei Medical University (109HCP-08 to C.-Y.K.), and the Ministry of Science and Technology (MOST 110-2314-B-038-149 to J.-C.L.). Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by TMU-Joint Institutional Review Board (TMU-JIRB No.: N201805021; date of approval: 2019/11/09). Informed Consent Statement Patient consent was waived due to nearly all patients died from disease and only document evaluation. Data Availability Statement Not applicable due to partial ongoing study of data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Kaplan–Meier overall survival by adequate group compared with inadequate (p = 0.078). Figure 2 (a) Recurrence-free survival for comparing adequate with inadequate group (p = 0.018); (b) progression-free survival for comparing adequate with inadequate group (p = 0.009). Figure 3 The 4th patient’s dose distributions on IMRT, VMAT, and TOMO. Color-wash areas: 46.00 Gy (pink), 41.40 Gy (yellow). IMRT: intensity-modulated radiation therapy; VMAT: volumetric-modulated arc therapy; TOMO: helical tomotherapy. jcm-11-02413-t001_Table 1 Table 1 Patients and tumor characteristics (n = 10). PTV Coverage Variables Adequate (n = 4) Inadequate (n = 6) p Value Age 56.5 ± 22.31 54.5 ± 9.07 0.874 Gender 1.000   Female 2 (50.0) 4 (66.7)   Male 2 (50.0) 2 (33.3) ECOG 1 1.000   0 1 (25.0) 1 (16.7)   1 2 (50.0) 4 (66.7)   2 1 (25.0) 1 (16.7) Tumor location 0.467   Frontal lobe 3 (75.0) 4 (66.7)   Parietal lobe 1 (25.0) 0 (0)   Occipital lobe 0 (0) 0 (0)   Temporal lobe 0 (0) 2 (33.3) Tumor side of brain 1.000   Right side 2 (50.0) 4 (66.7)   Left side 2 (50.0) 2 (33.3)   Bilateral 0 (0) 0 (0) Operation 0.667   Total resection 2 (50.0) 5 (83.3)   Subtotal resection 1 (25.0) 0 (0)   Biopsy only 1 (25.0) 1 (16.7) WHO Grade 2 0.432   OA 0 (0) 1 (16.7)   AA 1 (25) 2 (33.3)   GBM 3 (75) 3 (50) Chemotherapy 1.000   No 0 (0) 1 (16.7)   Yes (Temozolomide) 4 (100) 5 (83.3) 1 ECOG: Eastern Cooperative Oncology Group. 2 OA: oligoastrocytoma; AA: anaplastic astrocytoma; GBM: glioblastoma multiforme. jcm-11-02413-t002_Table 2 Table 2 Target coverage goal and dose constraints for the critical organ. Structure PTV 1 Coverage Goal/OARs Dose Constraints Targets   PTV Coverage V100% ≥ 95% PTV, Ideally V95% ≥ 95% PTV, Adequate   PTV maximum dose <110% prescribed dose OARs 2   Brain stem Dmax ≤ 54 Gy   Lens Dmax ≤ 5 Gy   Optic nerve/chiasm Dmax ≤ 55 Gy   Cochlea/Inner ear Dmean ≤ 45 Gy 1 PTV: planning target volume. 2 OARs: organs at risk. jcm-11-02413-t003_Table 3 Table 3 Dosimetric results for planning target volume and organs at risk in glioblastoma. Variable IMRT VMAT TOMO C v N C v N C v N IMRT v VMAT v TOMO Mean + SD Quick Reference Guide (p-Value) * C N C N C N IMRT VMAT TOMO C N Tumor volume (cm3) Phase I 482.13 ± 156.79 482.13 ± 156.79 482.13 ± 156.79 482.13 ± 156.79 482.13 ± 156.79 482.13 ± 156.79 Phase II 203.32 ± 139.56 203.32 ± 139.56 203.32 ± 139.56 203.32 ± 139.56 203.32 ± 139.56 203.32 ± 139.56 PTV Coverage V100% (%) Phase I 95.07 ± 0.08 89.68 ± 5.51 95.04 ± 0.08 91.75 ± 4.09 95.30 ± 0.25 93.93 ± 2.56 0.013 * 0.031 * 0.126 0.002 * 0.099 Phase II 95.17 ± 0.17 93.59 ± 4.36 95.08 ± 0.08 93.32 ± 3.72 95.38 ± 0.29 94.77 ± 1.98 0.280 0.170 0.341 0.006 * 0.624 PTV Coverage V95% (%) Phase I 98.87 ± 0.76 95.66 ± 3.31 98.75 ± 1.01 96.45 ± 2.85 98.89 ± 0.94 97.92 ± 2.23 0.014 * 0.027 * 0.216 0.931 0.214 Phase II 99.45 ± 0.54 98.42 ± 2.94 99.47 ± 0.50 98.51 ± 2.47 99.72 ± 0.23 99.23 ± 1.62 0.289 0.241 0.351 0.335 0.716 PTV Dmax (Gy) Phase I 50.21 ± 0.54 50.28 ± 0.38 49.38 ± 0.69 49.65 ± 0.40 49.37 ± 0.72 49.48 ± 0.80 0.751 0.301 0.750 0.010 * 0.009 * Phase II 15.02 ± 0.30 15.00 ± 0.29 14.90 ± 0.24 14.93 ± 0.28 14.69 ± 0.24 14.75 ± 0.29 0.875 0.777 0.631 0.029 * 0.158 PTV Dmin (Gy) Phase I 37.02 ± 2.21 34.05 ± 2.80 36.82 ± 2.90 34.98 ± 3.58 31.25 ± 4.30 29.19 ± 3.98 0.017 * 0.223 0.280 0.001 * 0.002 * Phase II 11.92 ± 1.46 11.63 ± 1.59 11.79 ± 1.65 11.17 ± 1.79 12.14 ± 0.93 11.64 ± 1.85 0.684 0.433 0.456 0.849 0.790 Planning CI Phase I 0.83 ± 0.04 0.80 ± 0.06 0.87 ± 0.03 0.84 ± 0.05 0.92 ± 0.03 0.90 ± 0.04 0.270 0.162 0.349 <0.001 * 0.001 * Phase II 0.81 ± 0.05 0.80 ± 0.08 0.82 ± 0.08 0.81 ± 0.09 0.93 ± 0.02 0.93 ± 0.03 0.631 0.798 0.905 <0.001 * <0.001 * Planning GI Phase I 2.60 ± 0.43 2.72 ± 0.53 2.59 ± 0.48 2.66 ± 0.48 2.60 ± 0.37 2.62 ± 0.40 0.569 0.746 0.929 0.999 0.879 Phase II 3.82 ± 1.26 3.88 ± 1.29 4.00 ± 1.69 4.22 ± 2.24 3.54 ± 0.76 3.62 ± 0.90 0.915 0.812 0.852 0.729 0.698 Planning HI Phase I 0.28 ± 0.05 0.34 ± 0.06 0.26 ± 0.06 0.31 ± 0.08 0.39 ± 0.09 0.44 ± 0.09 0.016 * 0.163 0.266 0.001 * 0.004 * Phase II 0.22 ± 0.12 0.23 ± 0.12 0.20 ± 0.08 0.24 ± 0.10 0.18 ± 0.08 0.22 ± 0.15 0.717 0.276 0.468 0.710 0.927 Brain stem Dmax (Gy) Phase I 44.38 ± 2.69 41.32 ± 0.10 43.83 ± 2.96 41.20 ± 0.38 42.82 ± 3.16 40.80 ± 0.44 0.006 * 0.020 * 0.075 0.492 0.005 * Phase II 10.07 ± 4.87 9.78 ± 4.65 9.88 ± 4.61 9.47 ± 4.29 9.15 ± 4.90 8.99 ± 4.74 0.893 0.837 0.942 0.903 0.927 Phase I + II 54.17 ± 5.41 51.00 ± 4.62 53.50 ± 5.47 50.59 ± 4.09 51.58 ± 5.39 49.23 ± 4.24 0.175 0.195 0.294 0.548 0.639 Optic chiasm Dmax (Gy) Phase I 40.95 ± 7.87 38.65 ± 6.79 39.34 ± 10.08 37.71 ± 9.08 37.90 ± 11.20 36.42 ± 10.15 0.493 0.709 0.761 0.787 0.851 Phase II 8.64 ± 5.79 8.36 ± 5.54 8.24 ± 6.14 7.97 ± 5.89 7.95 ± 5.59 7.82 ± 5.45 0.914 0.919 0.959 0.966 0.976 Phase I + II 49.46 ± 12.07 46.83 ± 10.90 47.47 ± 14.62 45.48 ± 13.49 45.55 ± 14.35 44.02 ± 13.69 0.615 0.756 0.810 0.817 0.886 Left optic nerve Dmax(Gy) Phase I 29.38 ± 15.39 28.42 ± 15.32 28.51 ± 15.83 28.16 ± 15.73 27.09 ± 15.08 26.10 ± 14.79 0.890 0.962 0.883 0.945 0.933 Phase II 6.44 ± 5.19 6.33 ± 5.32 6.63 ± 5.51 6.61 ± 5.49 5.45 ± 4.56 5.34 ± 4.57 0.962 0.994 0.955 0.858 0.845 Phase I + II 35.72 ± 19.92 34.68 ± 20.05 34.97 ± 20.43 34.68 ± 20.49 32.01 ± 18.38 30.88 ± 18.10 0.909 0.975 0.891 0.905 0.882 Right optic nerve Dmax (Gy) Phase I 31.05 ± 14.89 30.08 ± 14.11 27.96 ± 15.11 26.92 ± 14.12 26.39 ± 14.20 25.84 ± 13.88 0.882 0.875 0.932 0.773 0.784 Phase II 5.59 ± 4.37 5.57 ± 4.36 5.24 ± 4.56 5.00 ± 4.19 4.36 ± 3.42 4.52 ± 3.67 0.993 0.903 0.920 0.794 0.848 Phase I + II 36.54 ± 17.97 35.60 ± 17.06 33.17 ± 18.39 31.89 ± 17.02 30.56 ± 16.41 30.17 ± 16.32 0.906 0.873 0.959 0.750 0.763 Left lens Dmax (Gy) Phase I 3.93 ± 1.34 3.37 ± 0.84 2.88 ± 0.98 2.87 ± 0.82 2.95 ± 1.00 2.81 ± 0.92 0.276 0.988 0.752 0.082 0.301 Phase II 0.77 ± 0.41 0.76 ± 0.41 0.62 ± 0.34 0.63 ± 0.34 0.62 ± 0.37 0.62 ± 0.37 0.953 0.995 0.976 0.631 0.663 Phase I + II 4.68 ± 1.63 4.11 ± 1.12 3.49 ± 1.14 3.48 ± 1.03 3.55 ± 1.31 3.41 ± 1.22 0.377 0.985 0.802 0.114 0.326 Right lens Dmax (Gy) Phase I 3.77 ± 0.86 3.45 ± 0.69 2.86 ± 0.74 2.82 ± 0.73 3.05 ± 0.80 3.11 ± 0.83 0.367 0.895 0.869 0.041 * 0.192 Phase II 0.78 ± 0.41 0.78 ± 0.41 0.64 ± 0.34 0.65 ± 0.34 0.65 ± 0.38 0.64 ± 0.37 0.996 0.964 0.981 0.656 0.672 Phase I + II 4.53 ± 1.16 4.21 ± 0.97 3.49 ± 0.95 3.46 ± 0.94 3.65 ± 1.04 3.72 ± 1.06 0.519 0.931 0.890 0.079 0.240 Left inner ear Dmean (Gy) Phase I 20.16 ± 14.18 17.11 ± 12.72 16.26 ± 11.69 16.43 ± 11.71 14.66 ± 11.20 14.23 ± 11.17 0.619 0.974 0.932 0.602 0.852 Phase II 2.43 ± 2.86 2.58 ± 2.89 2.45 ± 2.40 2.30 ± 2.36 1.58 ± 1.74 1.57 ± 1.75 0.907 0.890 0.991 0.655 0.627 Phase I + II 22.58 ± 16.07 19.69 ± 14.65 18.71 ± 13.51 18.73 ± 13.56 16.17 ± 12.31 15.73 ± 12.32 0.679 0.997 0.938 0.596 0.794 Right inner ear Dmean (Gy) Phase I 19.11 ± 15.01 17.80 ± 12.73 17.78 ± 13.87 16.37 ± 12.61 14.49 ± 14.68 13.40 ± 12.72 0.836 0.815 0.862 0.767 0.734 Phase II 2.34 ± 2.84 2.60 ± 3.26 2.86 ± 3.50 2.70 ± 3.27 1.75 ± 2.27 1.69 ± 2.25 0.851 0.919 0.956 0.699 0.706 Phase I + II 21.45 ± 16.57 20.41 ± 14.97 20.64 ± 16.09 19.07 ± 14.76 16.21 ± 15.70 15.07 ± 13.75 0.884 0.823 0.865 0.740 0.697 Normal brain (WB-CTV_H) Phase I + II Dmax (Gy) 64.44 ± 0.80 64.29 ± 0.74 63.34 ± 0.82 63.52 ± 0.61 62.60 ± 1.15 62.83 ± 1.17 0.669 0.574 0.656 0.001 * 0.004 * Phase I + II Dmean (Gy) 34.80 ± 4.12 34.35 ± 3.89 33.67 ± 3.59 33.01 ± 3.33 31.85 ± 3.24 31.67 ± 3.20 0.804 0.674 0.900 0.213 0.247 Phase I + II NTCP (%) 5.20 ± 2.57 4.50 ± 2.37 4.20 ± 1.75 4.00 ± 1.70 2.70 ± 1.34 2.70 ± 1.34 0.535 0.798 1.000 0.027 * 0.697 IMRT, intensity-modulated radiation therapy; VMAT, volumetric-modulated radiation therapy; TOMO, tomotherapy; SD, standard deviation; VX, the percentage of organ receiving more or equal to x Gy; Dmax, maximum dose of certain OAR; Dmean, mean dose of certain OAR. * Quick reference guide is based on the significant p-value (p < 0.05). jcm-11-02413-t004_Table 4 Table 4 Comparison of PTV coverage through different planning technique compassion. PTV Coverage Variables Adequate Inadequate p-Value Phase I 0.202 IMRT_N 3 7 VMAT_N 5 5 TOMO_N 7 3 Phase II 1.000 IMRT_N 8 2 VMAT_N 8 2 TOMO_N 9 1 Phase I 0.003 * IMRT_C 10 0 IMRT_N 3 7 Phase II 0.474 IMRT_C 10 0 IMRT_N 8 2 Phase I 0.033 * VMAT_C 10 0 VMAT_N 5 5 Phase II 0.474 VMAT_C 10 0 VMAT_N 8 2 Phase I 0.211 TOMO_C 10 0 TOMO_N 7 3 Phase II 1.000 TOMO_C 10 0 TOMO_N 9 1 * Quick reference guide is based on the significant p-value (p < 0.05). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ostrom Q.T. Gittleman H. Liao P. Rouse C. Chen Y. Dowling J. Wolinsky Y. Kruchko C. Barnholtz-Sloan J. Cbtrus statistical report: Primary brain and central nervous system tumors diagnosed in the united states in 2007–2011 Neuro-Oncology 2014 16 (Suppl. 4) iv1 iv63 10.1093/neuonc/nou223 25304271 2. Brandes A.A. Tosoni A. Franceschi E. Sotti G. Frezza G. Amistà P. Morandi L. Spagnolli F. Ermani M. Recurrence pattern after temozolomide concomitant with and adjuvant to radiotherapy in newly diagnosed patients with glioblastoma: Correlation with mgmt promoter methylation status J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2009 27 1275 1279 10.1200/JCO.2008.19.4969 3. Milano M.T. Okunieff P. Donatello R.S. Mohile N.A. Sul J. Walter K.A. Korones D.N. Patterns and timing of recurrence after temozolomide-based chemoradiation for glioblastoma Int. J. Radiat. Oncol. Biol. Phys. 2010 78 1147 1155 10.1016/j.ijrobp.2009.09.018 20207495 4. McDonald M.W. Shu H.K. Curran W.J. Jr. Crocker I.R. Pattern of failure after limited margin radiotherapy and temozolomide for glioblastoma Int. J. Radiat. Oncol. Biol. Phys. 2011 79 130 136 10.1016/j.ijrobp.2009.10.048 20399036 5. Pan H. Alksne J. Mundt A.J. Murphy K.T. Cornell M. Kesari S. Lawson J.D. Patterns of imaging failures in glioblastoma patients treated with chemoradiation: A retrospective study Med. Oncol. 2012 29 2040 2045 10.1007/s12032-011-0116-5 22108847 6. Bleeker F.E. Molenaar R.J. Leenstra S. Recent advances in the molecular understanding of glioblastoma J. Neuro-Oncol. 2012 108 11 27 10.1007/s11060-011-0793-0 22270850 7. Cabrera A.R. Kirkpatrick J.P. Fiveash J.B. Shih H.A. Koay E.J. Lutz S. Petit J. Chao S.T. Brown P.D. Vogelbaum M. Radiation therapy for glioblastoma: Executive summary of an american society for radiation oncology evidence-based clinical practice guideline Pract. Radiat. Oncol. 2016 6 217 225 10.1016/j.prro.2016.03.007 27211230 8. Valduvieco I. Verger E. Bruna J. Caral L. Pujol T. Ribalta T. Boget T. Oleaga L. Pineda E. Graus F. Impact of radiotherapy delay on survival in glioblastoma Clin. Transl. Oncol. Off. Publ. Fed. Span. Oncol. Soc. Natl. Cancer Inst. Mex. 2013 15 278 282 10.1007/s12094-012-0916-x 9. El-Hossiny H.A. Diab N.A. El-Taher M.M. A comparative dosimetric study of adjuvant 3d conformal radiotherapy for operable stomach cancer versus ap-pa conventional radiotherapy in nci-cairo J. Egypt. Natl. Cancer Inst. 2009 21 197 202 10.1007/s10330-010-0615-4 10. Gursel B. Meydan D. Ozbek N. Ofluoglu T. Dosimetric comparison of three different external beam whole breast irradiation techniques Adv. Ther. 2011 28 1114 1125 10.1007/s12325-011-0078-1 22076811 11. Bosma I. Vos M.J. Heimans J.J. Taphoorn M.J. Aaronson N.K. Postma T.J. van der Ploeg H.M. Muller M. Vandertop W.P. Slotman B.J. The course of neurocognitive functioning in high-grade glioma patients Neuro-Oncology 2007 9 53 62 10.1215/15228517-2006-012 17018697 12. MacDonald S.M. Ahmad S. Kachris S. Vogds B.J. DeRouen M. Gittleman A.E. DeWyngaert K. Vlachaki M.T. Intensity modulated radiation therapy versus three-dimensional conformal radiation therapy for the treatment of high grade glioma: A dosimetric comparison J. Appl. Clin. Med. Phys. 2007 8 47 60 10.1120/jacmp.v8i2.2423 17592465 13. Saad S. Wang T.J. Neurocognitive deficits after radiation therapy for brain malignancies Am. J. Clin. Oncol. 2015 38 634 640 10.1097/COC.0000000000000158 25503433 14. Hermanto U. Frija E.K. Lii M.J. Chang E.L. Mahajan A. Woo S.Y. Intensity-modulated radiotherapy (imrt) and conventional three-dimensional conformal radiotherapy for high-grade gliomas: Does imrt increase the integral dose to normal brain? Int. J. Radiat. Oncol. Biol. Phys. 2007 67 1135 1144 10.1016/j.ijrobp.2006.10.032 17208388 15. Wagner D. Christiansen H. Wolff H. Vorwerk H. Radiotherapy of malignant gliomas: Comparison of volumetric single arc technique (rapidarc), dynamic intensity-modulated technique and 3d conformal technique Radiother. Oncol. J. Eur. Soc. Ther. Radiol. Oncol. 2009 93 593 596 10.1016/j.radonc.2009.10.002 16. Zach L. Stall B. Ning H. Ondos J. Arora B. Uma S. Miller R.W. Citrin D. Camphausen K. A dosimetric comparison of four treatment planning methods for high grade glioma Radiat. Oncol. 2009 4 45 10.1186/1748-717X-4-45 19845946 17. Amelio D. Lorentini S. Schwarz M. Amichetti M. Intensity-modulated radiation therapy in newly diagnosed glioblastoma: A systematic review on clinical and technical issues Radiother. Oncol. J. Eur. Soc. Ther. Radiol. Oncol. 2010 97 361 369 10.1016/j.radonc.2010.08.018 20926149 18. Briere T.M. McAleer M.F. Levy L.B. Yang J.N. Sparing of normal tissues with volumetric arc radiation therapy for glioblastoma: Single institution clinical experience Radiat. Oncol. 2017 12 79 10.1186/s13014-017-0810-3 28464840 19. Otto K. Volumetric modulated arc therapy: Imrt in a single gantry arc Med. Phys. 2008 35 310 317 10.1118/1.2818738 18293586 20. Rao M. Yang W. Chen F. Sheng K. Ye J. Mehta V. Shepard D. Cao D. Comparison of elekta vmat with helical tomotherapy and fixed field imrt: Plan quality, delivery efficiency and accuracy Med. Phys. 2010 37 1350 1359 10.1118/1.3326965 20384272 21. Teoh M. Clark C.H. Wood K. Whitaker S. Nisbet A. Volumetric modulated arc therapy: A review of current literature and clinical use in practice Br. J. Radiol. 2011 84 967 996 10.1259/bjr/22373346 22011829 22. Mackie T.R. Holmes T. Swerdloff S. Reckwerdt P. Deasy J.O. Yang J. Paliwal B. Kinsella T. Tomotherapy: A new concept for the delivery of dynamic conformal radiotherapy Med. Phys. 1993 20 1709 1719 10.1118/1.596958 8309444 23. Marks L.B. Yorke E.D. Jackson A. Ten Haken R.K. Constine L.S. Eisbruch A. Bentzen S.M. Nam J. Deasy J.O. Use of normal tissue complication probability models in the clinic Int. J. Radiat. Oncol. Biol. Phys. 2010 76 S10 S19 10.1016/j.ijrobp.2009.07.1754 20171502 24. Paddick I. A simple scoring ratio to index the conformity of radiosurgical treatment plans Technical note. J. Neurosurg. 2000 93 (Suppl. 3) 219 222 10.3171/jns.2000.93.supplement_3.0219 11143252 25. Paddick I. Lippitz B. A simple dose gradient measurement tool to complement the conformity index J. Neurosurg. 2006 105 194 201 10.3171/sup.2006.105.7.194 26. Gevaert T. Levivier M. Lacornerie T. Verellen D. Engels B. Reynaert N. Tournel K. Duchateau M. Reynders T. Depuydt T. Dosimetric comparison of different treatment modalities for stereotactic radiosurgery of arteriovenous malformations and acoustic neuromas Radiother. Oncol. J. Eur. Soc. Ther. Radiol. Oncol. 2013 106 192 197 10.1016/j.radonc.2012.07.002 27. Liu W.H. Lin J.C. Chou Y.C. Li M.H. Tsai J.T. Cd44-associated radioresistance of glioblastoma in irradiated brain areas with optimal tumor coverage Cancer Med. 2020 9 350 360 10.1002/cam4.2714 31746135 28. Rahman R. Sulman E. Haas-Kogan D. Cagney D.N. Update on radiation therapy for central nervous system tumors Hematol. Oncol. Clin. N. Am. 2022 36 77 93 10.1016/j.hoc.2021.08.006 34711456 29. Buckner J.C. Shaw E.G. Pugh S.L. Chakravarti A. Gilbert M.R. Barger G.R. Coons S. Ricci P. Bullard D. Brown P.D. Radiation plus procarbazine, ccnu, and vincristine in low-grade glioma N. Engl. J. Med. 2016 374 1344 1355 10.1056/NEJMoa1500925 27050206 30. Bonosi L. Ferini G. Giammalva G.R. Benigno U.E. Porzio M. Giovannini E.A. Musso S. Gerardi R.M. Brunasso L. Costanzo R. Liquid biopsy in diagnosis and prognosis of high-grade gliomas; state-of-the-art and literature review Life 2022 12 407 10.3390/life12030407 35330158 31. Liu P. Liu G. Wang G. Zhou W. Sun Y. Chen W. Zeng Q. Hong J. Xie Q. Ou L. Comparison of dosimetric gains provided by intensity-modulated radiotherapy, volume-modulated arc therapy, and helical tomotherapy for high-grade glioma BioMed Res. Int. 2020 2020 4258989 10.1155/2020/4258989 32258121 32. Lin J.C. Tsai J.T. Chou Y.C. Li M.H. Liu W.H. Compared with intensity-modulated radiotherapy, image-guided radiotherapy reduces severity of acute radiation-induced skin toxicity during radiotherapy in patients with breast cancer Cancer Med. 2018 7 3622 3629 10.1002/cam4.1630 29968974 33. Huang S.F. Lin J.C. Shiau A.C. Chen Y.C. Li M.H. Tsai J.T. Liu W.H. Optimal tumor coverage with different beam energies by imrt, vmat and tomo: Effects on patients with proximal gastric cancer Medicine 2020 99 e23328 10.1097/MD.0000000000023328 33217871 34. Lin J.C. Tsai J.T. Chen L.J. Li M.H. Liu W.H. Compared planning dosimetry of tomo, vmat and imrt in rectal cancer with different simulated positions Oncotarget 2017 8 42020 42029 10.18632/oncotarget.14923 28159930 35. Ferini G. Tripoli A. Molino L. Cacciola A. Lillo S. Parisi S. Umina V. Illari S.I. Marchese V.A. Cravagno I.R. How much daily image-guided volumetric modulated arc therapy is useful for proctitis prevention with respect to static intensity modulated radiotherapy supported by topical medications among localized prostate cancer patients? Anticancer Res. 2021 41 2101 2110 10.21873/anticanres.14981 33813420 36. Ferini G. Molino L. Tripoli A. Valenti V. Illari S.I. Marchese V.A. Cravagno I.R. Borzi G.R. Anatomical predictors of dosimetric advantages for deep-inspiration-breath-hold 3d-conformal radiotherapy among women with left breast cancer Anticancer Res. 2021 41 1529 1538 10.21873/anticanres.14912 33788746 37. Ferini G. Valenti V. Puliafito I. Illari S.I. Marchese V.A. Borzì G.R. Volumetric modulated arc therapy capabilities for treating lower-extremity skin affected by several merkel cell carcinoma nodules: When technological advances effectively achieve the palliative therapeutic goal while minimising the risk of potential toxicities Medicina 2021 57 1379 34946324 38. Shih H.A. Sherman J.C. Nachtigall L.B. Colvin M.K. Fullerton B.C. Daartz J. Winrich B.K. Batchelor T.T. Thornton L.T. Mancuso S.M. Proton therapy for low-grade gliomas: Results from a prospective trial Cancer 2015 121 1712 1719 10.1002/cncr.29237 25585890

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095122 ijerph-19-05122 Article Implementation of Interventions and Policies on Opioids and Awareness of Opioid-Related Harms in Canada: A Multistage Mixed Methods Descriptive Study Goyer Camille 12 https://orcid.org/0000-0003-1261-2218 Castillon Genaro 2 Moride Yola 23* Tchounwou Paul B. Academic Editor 1 Faculty of Pharmacy, Université de Montréal, Montreal, QC H3C 3J7, Canada; camille.goyer@umontreal.ca 2 YolaRX Consultants, Montreal, QC H3W 1Y7, Canada; genaro.castillon@yolarx.com 3 Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy, and Aging Research, Rutgers, The State University of New Jersey, New Brunswick, NJ 08854, USA * Correspondence: morideyo@ifh.rutgers.edu 22 4 2022 5 2022 19 9 512214 2 2022 06 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In Canada, interventions and policies have been implemented to minimize the risk of opioid-related harms. This mixed methods study aimed at describing trends over time in implementation, as well as in awareness and health outcomes. For implementation, we conducted a scoping review to identify opioids interventions and policies implemented in Canada between 1 January 2016 and 15 November 2019. Awareness was measured through a descriptive analysis of opioid-related harm cases reported by consumers and health care professionals (HCPs) to the national spontaneous reporting system and of social media coverage, while health outcome consisted of opioid-related deaths recorded in the coroner’s reports database of the province of Quebec, Canada. Trends over time in implementation of interventions were compared to trends in awareness and opioid-related deaths, without implying causality. There were 413 national or provincial interventions on opioids implemented over the study period, with a four-fold increase in 2016. The most common (31.5%) was harm reduction strategies, such as naloxone distribution. The reporting rate of opioid-related harms ranged between 0.1 and 0.2 per 100,000 persons with no observed time trend. Compared to 2015, the number of social media posts increased in 2016 by 35.4% (Reddit), 329.0% (Facebook), and 381.5% (Twitter). Between 2016 and 2019, there was a slight decrease in the number of opioid-related deaths recorded in the coroner’s database. Overall, the increase in the number of policies did not see a parallel increase in spontaneous reports of opioid-related harms as an indicator of consumer or HCP awareness. Conversely, the dramatic increase in social media coverage was consistent with heightened public awareness. Although no inferences of causality were made in this study, the decrease in opioid-related deaths observed in the recent years may indicate a potential effectiveness of interventions and policies. risk minimization measures policies evaluation framework opioid-related harms opioid use disorders opioids spontaneous reporting social media ==== Body pmc1. Introduction Canada is in the midst of an expanding opioid epidemic. Between January 2016 and March 2019, there were 12,800 apparent opioid-related deaths, with approximately 85% occurring in the provinces of British Columbia, Alberta, and Ontario, and 20,700 emergency medical services in response to a suspected opioid overdose [1]. In 2016, approximately 20 million opioid prescriptions were dispensed, which is equivalent to nearly 1 prescription for every adult, making Canada the second-largest consumer of prescription opioids in the world, after the United States (US) [2]. According to the Canadian Public Health Association, opioid-related deaths between 2009 and 2014 increased 7-fold in British Columbia and 20-fold in Alberta, demonstrating that the opioid epidemic in Canada has been expanding as early as 2009 [3]. As an attempt to curb the opioid epidemic, officially declared in 2016, policies on opioids have been implemented in Canada, such as drug scheduling to increase accessibility to naloxone [4], communication to health care professionals (HCPs) [5] and/or patients, as well as interventions at the point of care (e.g., opioid stickers in pharmacies, triplicate prescriptions, prescription monitoring programs) in order to increase the awareness of opioid-related harm [6]. In parallel, targeted risk management plans and follow-up commitments by the pharmaceutical industry specifically for opioids have been integrated into the Canadian drug regulations in 2018 [7]. At the same time, opioids working groups have also been created at Health Canada and the Canadian Institute for Health Information. Several models and theoretical frameworks have been published in the literature for the evaluation of health interventions, including the ones proposed for therapeutic risk minimization [8]. Within these frameworks, components of effectiveness evaluation consist of coverage, process indicators (i.e., awareness, knowledge, and understanding of key safety messages) as well as health outcomes [9,10]. For opioids, the number of evaluation studies reported in the peer-reviewed literature has lagged far behind the number of interventions and policies that have been implemented thus far [11]. A lack of harmonized guidance on methodological frameworks for studies of effectiveness of therapeutic risk minimization interventions has recently been observed [12], which may have contributed to the fragmented evidence on the impact of opioid interventions. A common shortcoming of these evaluation studies is the lack of data sources for the measurement of effectiveness outcomes. To our knowledge, a comprehensive and concurrent description of all components of the therapeutic risk minimization framework (i.e., intervention coverage, process indicators, health outcomes) using a multistage mixed methods design has not yet been conducted, which was the rationale for this study. Each component was evaluated individually with no attempt of inferring any causal associations between the observed trends. 2. Materials and Methods 2.1. Overview The principle of integration of this mixed methods research occurs at two levels [13]. The first is at the study design level, by integrating an exploratory multistage mixed methods framework design. This design was sought to focus on a qualitative description of interventions and policies that aimed at decreasing opioid-related harms over time, and to assess, in parallel, process outcomes (HCP and consumer awareness of opioid-related harms through social media and spontaneous reporting data) as well as health outcomes (opioid-related deaths in the province of Quebec, representing approximately 22.3% of the Canadian population). The second principle is the contiguous approach to integration, which involves interpreting and reporting the findings independently for each component of the evaluation framework, as described below. The following components of an evaluation framework were addressed in our study: (a) Implementation of risk minimization interventions and policies on opioids in Canada; (b) Process measures consisting of awareness measured by the reporting of opioid-related harms by HCPs and consumers to the national spontaneous reporting system (Canada Vigilance) as well as social media monitoring; and (c) Health outcome, measured by opioid-related deaths recorded in a provincial Coroner’s report database (Quebec only). These measures were selected on the basis of their availability at the national or, alternatively, the provincial levels. Trends over time in the implementation of interventions were compared to trends in awareness and in opioid-related deaths. These outcomes could not be used for hypothesis-testing purposes regarding the effectiveness of interventions, since they could not be linked to one another at the patient or HCP level. Hence, for this project, each component has been individually analyzed using a multistage mixed methods approach with an ecological perspective, without implying causality. 2.2. Implementation: Scoping Review of Interventions and Policies A scoping review was conducted, involving a literature search of Canadian interventions (i.e., risk mitigation strategies, education and/or continuing education, public opioid awareness programs, policies, update or creation of guidelines/standard of practice, knowledge exchange, pharmacovigilance, control, and monitoring, community interventions, prevention measures) aiming to minimize or mitigate opioid-related harms, or increase awareness of the opioid crisis. The search was conducted using MEDLINE and Embase over the period from 1 January 2016 through 15 November 2019 (date last searched). The year 2016 was selected as it corresponded to the year when the opioid crisis was officially declared by the government of Canada [14]. The search strategy is presented in Supplementary Materials. There was no restriction on the geographical scope for the search strategy, as relevant sources may not be indexed using the country as a keyword. National interventions were those implemented at a federal level (e.g., by Health Canada, the national regulatory agency) whereas provincial interventions were those implemented by provincial governments (according to the Canada Health Act, the provision of health care services is under the responsibility of provinces) [15]. For additional sources, pragmatic searches of relevant websites of governmental and non-governmental organizations were also conducted in English and French using Google (Accessed on 13 November 2019: www.google.com/) and Google Scholar (Accessed on 13 November 2019: www.google.com/scholar/) search engines. We included publications (i.e., original studies, literature reviews, conference proceedings, opinions, editorials) that described interventions and policies aiming to minimize or mitigate opioid-related harm in Canada, implemented between 1 January 2016 and 31 December 2019, and excluded those that did not explicitly mention implementation in Canada or in one of its provinces. For each source retained in the review, the following data were extracted: Type of intervention (i.e., policy change, educational material, awareness material, update of treatment guideline or creation of a treatment guideline, pharmacovigilance, control, and monitoring), name, date of first implementation in Canada and/or date the intervention was announced on the website (expressed in quarter and year) during the study period, and whether it had provincial or national coverage. If only the year was reported, the date of implementation was assigned as the first quarter (Q1) of the year. Publications describing interventions aiming to minimize opioid-related harms were retained while those that did not mention interventions or mentioned interventions outside of Canada were excluded. A qualitative description of interventions was conducted and using the date of implementation, a graphical representation of the number of interventions over time was derived along with a visual assessment of trends. 2.3. Awareness Outcome: Spontaneous Reports of Opioid-Related Harms Canada Vigilance is the national post-market surveillance program that collects spontaneous reports of suspected adverse effects of prescription and non-prescription health products made by HCPs or consumers in Canada [16]. It does not cover the cases associated with illicit opioid usage. Although a useful tool for drug safety signal detection at the country level, spontaneous reporting data are associated with well-known limitations for the estimation of incidence of adverse events, since reporting is greatly influenced by external factors such as media coverage, regulatory communications, time since product market launch, etc. [17,18]. However, being highly influenced by those external factors, increases in reporting are known to be the result of increased awareness of identified or suspected risks [17,18]. Hence, we considered trends in spontaneous reporting as an indicator of awareness of opioid-related harms. We included all case reports of overdose, opioid-related death, abuse, misuse, dependence, and diversion with an opioid as the suspected drug between 1 January 2009 and 31 August 2019 (last date available). The year 2009 was selected as a starting point based on the literature, reporting that the opioid epidemic in Canada has been expanding as early as 2009. Opioid-related harms were first identified using predefined Preferred Terms (PTs) in the Medical Dictionary for Regulatory Activities (MedDRA, Version 22.1). We excluded case reports that mentioned opioids as a concomitant drug (not the suspected drug), those that were intentional adverse drug reactions (ADRs) (e.g., suicide), cases with missing data on the product information (not clear if a harmful event was suspected to have been caused by an opioid), and invalid case reports (i.e., lack of an identifiable patient, reporter, adverse reaction term or health product) [9]. Descriptive analyses were conducted on the following patient characteristics: Age group (Neonate: 0–<25 days, Infant: >25 days–<1 year, Child: ≥1–<13, Adolescent: ≥13–<18, Adult: ≥18–65, Elderly: >65), sex, type of opioid-related harms including seriousness (based on the regulatory criteria) [19], suspected opioid(s) (i.e., opioid name, route of administration, dosage form (short acting, long-acting, extended release)), reporter type (HCPs or non-HCPs/consumers), and number of reports by quarter. In the absence of data on the total number of prescription opioids users in Canada, the reporting rate was estimated by using the absolute number of spontaneous reports per quarter as the numerator and the quarterly Canadian population estimate, derived from Statistic Canada [20], as the denominator. 2.4. Awareness Outcome: Social Media Posts Information on the public level of awareness of the opioid crisis and of the implementation of interventions and policies, was sought through digital surveillance of Reddit, Twitter, and Facebook over the period 2009–2019. These generic social media networks were used given their free public access. Hence, specialized health care social networks or forums (e.g., Drugs-Forum.com, accessed on 20 November 2019) that did not allow public access were excluded. Posts on recreational opioid use were also excluded. For Reddit, a program was developed using the website’s application programming interface (API) to extract relevant posts. Duplicate posts were removed by cross-checking the post ID provided in the extracted file. For Twitter, Twitter-scraper [21], known as a web scraper program, was used to extract posts with the topic and geographical scope of interest. This program extracts structured data from Twitter posts within a time frame and by using specific keywords. For Reddit and Twitter, the program extracted structured data by selecting posts with the following keywords: ‘Canada’ and ‘Opioid(s), including their specific names’ or ‘Opioid-related harm, including other keywords associated with opioid use’. Duplicates were removed by the ‘tweet Id’ and the list of posts was then manually screened to identify unwanted posts (e.g., drug advertising). For Facebook, Canadian public groups referring to substance use, drug use, and the Canadian opioid crisis (e.g., Save Our Young Adults from Prescription Drug Abuse) were identified before initiating data extraction. These groups were identified using the keywords: Drugs, Canada drugs, substance use, and opioid. Each group was then analyzed to determine whether they were Canadian public groups referencing the opioid crisis. For feasibility reasons, a manual screening of public posts in each group was conducted since Facebook no longer allows for programs to scrape groups or profiles. For each post retained, the following general information was extracted: Website (i.e., Reddit, Twitter, Facebook) and the post date (quarter and year). Frequencies and percentages were obtained for categorical variables (website name, group names (Facebook groups, subreddits), source publication) while the number of posts, minimum, and maximum were calculated for each time point. 2.5. Health Outcome: Opioid-Related Death (Province of Quebec Only) All deaths that are accidental, intentional, homicidal, or unknown cause of opioid overdoses are brought to the coroner’s office for analysis. Coroner’s databases are maintained individually for each province, and, for this project, public access was only available for the province of Quebec covering the period from 1 January 2009 through 31 December 2017 (last date available). The opioid-related death cases were identified using the International Classification of Disease, 10th Revision (ICD-10) codes: T40.X (Poisoning by, adverse effect of and underdosing of narcotics and psychodysleptics [hallucinogens]) referring to an opioid-overdose leading to death (T40.2 (other opioids), T40.4 (other synthetic narcotics), T40.1 (heroin), T40.3 (methadone), T40.6 (narcotics), T40.0 (opium)). The type of opioid(s) suspected of causing the death was identified through an examination of the report narratives. Frequency distribution was obtained for age group at the time of death (Neonate: 0–<25 days, Infant: >25 days–<1 year, Child: ≥1–<13, Adolescent: ≥13–<18, Adult: ≥18–65, Elderly: >65), sex, and the suspected opioid(s). Acquisition channel (prescription or illicit) was not available. A graphical representation of the number and characteristics of opioid-related deaths by year was derived, and a visual analysis of trends was undertaken. 3. Results 3.1. Implementation: Scoping Review of Interventions and Policies A total of 413 interventions and policies aiming to reduce opioid-related harms or increase awareness of the opioid crisis were identified in Canada between 2016 and 2019: 129 (31.2%) were national (i.e., implemented in all provinces, including Quebec) while 284 (68.8%) were provincial (implemented in one province only) (Supplementary Materials, Table S1). The number of province-specific interventions varied greatly, with British Columbia having the most (n = 102; 24.7%), followed by Ontario (n = 80; 19.4%), Alberta (n = 37; 9.0%), and Quebec (n = 20; 4.8%). National interventions, implemented in all provinces, also increased over time. Trends over time in the number of interventions by province is shown in Figure 1. Overall, there was an increase in the number of interventions over time, with a plateau starting 2019 Q1. From 2016 (reference period, n = 99 newly implemented interventions and policies) to 2019 (n = 413 interventions and policies, cumulative at the national or provincial level), there was a 4.2-fold increase in the number of interventions and policies across all provinces. As shown in Table 1, the most common types of interventions were harm reduction or risk mitigation strategies (n = 130; 31.5%), followed by education and/or continuing education (n = 101; 24.5%), public opioid awareness programs (n = 65, 15.7%), and policies (n = 51, 12.3%). Examples of harm-reduction strategies include Take-Home Naloxone programs across the country [22], drug checking services for fentanyl for drug users [23], and centers for substance use [24]. Of the 101 education strategies identified, 71 (70.3%) targeted HCPs, 24 (23.8%) were community-based (patients and non-patients), and 6 (5.9%) targeted patients. Examples of education and/or continuing education for HCPs are: training courses specific to opioids, improving prescription practices, and treating opioid-related harms. Other material consisted of webinars and workshops on how to detect an opioid overdose [25] and on how to use a naloxone kit [26]. Examples of opioid awareness resources for the community are: Video (End Stigma Campaign) [27], web series on patients living with opioid use disorder [28], and fact sheets on opioids and pain management [29]. Of the 65 awareness strategies, 57 (87.7%) targeted the community (i.e., non-patients and patients) and 8 (12.3%) targeted patients only. An example of policy change was the removal of naloxone from the prescription list (Schedule I to Schedule II) in Canada, effective as of March 2016 [4]. Establishing take-home naloxone programs across Canada may increase access to naloxone for opioid users and for their friends and family before the arrival of first responders. 3.2. Awareness Outcome: Spontaneous Reports of Opioid-Related Harms In Canada Vigilance, there were 6727 reports of opioid-related harms, corresponding to 4970 patients between 1 January 2009 and 31 August 2019. Patient characteristics are further described in Table 2. There was a predominance of males (n = 2730; 54.9%). The mean ± standard deviation (SD) patient age was 38.1 ± 17.0 years and, after excluding unknown age groups, adults age ≥18–<65 years accounted for the majority of opioid-related harm cases (67.5% overall and 90.0% when excluding reports of unknown age). The vast majority of reported opioid-related harms were categorized as serious (n = 4881; 98.2%). The types of opioid-related harms consisted of abuse, misuse and/or dependence (n = 3986; 59.3%), followed by opioid-related death (n = 1344; 20.0%). Oxycodone was the most frequently suspected opioid (n = 2047; 30.3%), followed by hydromorphone (n = 1402; 20.8%) (Supplementary Materials, Table S2). Between 2009 Q1 and 2018 Q3, the reporting rate varied between 0.1 and 0.2 spontaneous reports per 100,000 persons/quarter (Supplementary Materials, Figure S1). However, there were two reporting quarters that experienced peaks in reporting. The first occurred in 2012 Q1, with a reporting rate 0.5 per 100,000 persons, and the second was in 2018 Q4, when the reporting rate rose to 1.8 reported cases per 100,000 persons. The latter period corresponds to a simultaneous transmission of cumulated reports originating from marketing authorization holders (MAHs) following the implementation of the new regulation on opioids (87.4% of the total number of cases reported during that quarter) [30]. As part of Health Canada’s Opioid Action Plan, MAHs were required to develop and implement Canadian-specific risk management plans for opioid products in order to monitor, prevent, and mitigate the risks associated with the use of opioids. 3.3. Awareness Outcome: Social Media Posts Over the study period, the number of posts related to the Canadian opioid crisis, or an adverse event suspected to have been caused by an opioid in Canada, was 1619 for Facebook, 1132 for Reddit, and 43,058 for Twitter. Graphical representation of trends over time in each social media can be found in Figure 2. Overall, regardless of the type of social media, the number of posts increased as of 2016 Q1. Between 2015 and 2016, there was a 35.4%, 329.0%, and 381.5% increase of posts for Reddit, Facebook, and Twitter, respectively. Trends after the year 2016 were comparable between Reddit and Twitter: the frequency of posts slightly decreased after 2016 Q4 and plateaued as of 2017 Q1 through 2019 Q3. However, on Facebook, trends continued to increase after the year 2016. There was a sharp increase of posts in 2019 Q1, which corresponds mainly to the high activity from one public group on Facebook that shared content on the number of overdoses related to an opioid. 3.4. Health Outcome: Opioid-Related Death (Province of Quebec Only) In the Quebec coroner’s reports database, there were 1582 confirmed opioid-related deaths between 1 January 2009 and 31 December 2019. The distribution of death cases by age group and sex is reported in Table 3. Mean age ± SD was 44.8 ± 13.3 years and most cases involved males (n = 1074; 67.9%). Hydromorphone was the leading opioid causing death (n = 557; 22.9%), followed by morphine (n = 425; 17.5%), and fentanyl and its derivatives (acetyl-fentanyl, butyryl fentanyl, carfentanyl, fluorobutyryl fentanyl, furanyl-fentanyl, norfentanyl, and par-fluorobutyryl fentanyl) (n = 323; 13.3%) (Supplementary Materials, Table S5). As shown in Figure 3, the annual number of opioid-related deaths in Quebec increased from a total of 108 cases in 2009 to 147 in 2019, although a reversal in trend was observed starting in 2017. The number of opioid-related deaths associated with fentanyl and its derivatives increased by 6.8-fold between 2009 Q1 and 2017 Q4 (Supplementary Materials, Figure S3) and decreased from 75 deaths in 2017 to 25 deaths in 2019. The relative distribution of fentanyl- and oxycodone-related deaths to the total number of deaths between 2016 and 2019 slightly decreased over time (respectively, 18.9% and 18.0% of deaths in 2016, and 12.7% and 10.2% of deaths in 2019). Methadone-related deaths increased between 2009 and 2019 (respectively, 5.3% and 13.7% of deaths). Graphical representations of the relative distribution of fentanyl-, oxycodone-, and methadone-related deaths may be found in Supplementary Materials (Figure S4). 4. Discussion This mixed methods study provided a description of trends over time in the number and type of opioid interventions and policies implemented in Canada since the start of the opioid epidemic in 2016, as well as in the reporting of opioid-related harms and social media coverage (awareness), and in the number of deaths due to opioid overdose in Quebec (health outcome). Collectively, measures that have been used cover all indicators of the framework for the evaluation of effectiveness of therapeutic risk minimization interventions [10]. Findings from this study may be relevant elsewhere, as opioid-related harm has become a public health crisis in many countries globally. From the scoping review, we observed that the geographical distribution of the interventions implemented reflected areas in Canada most affected by the opioid crisis, namely British Columbia, Alberta, and Ontario [31]. Moreover, social media coverage on the level of opioid awareness also increased over time since 2016. The relatively stable spontaneous reporting rate over time of opioid-related harms associated with prescription opioids was not suggestive of an awareness effect between 2016 and 2019 (Figures S1 and S2 of Supplementary Materials). Instead, a large number of simultaneous transmissions of cumulated reports originating from MAHs occurred at the end of the year 2018, due to the new regulation implemented by Health Canada, which requires pharmaceutical companies to report any opioid-related harm [32]. Our findings reinforce the fact that social media is a recognized source of data when assessing awareness of opioid-related harms in the community, as previously reported by other studies [33,34,35,36]. According to a recent review, social media is also sensitive to measure the effect of risk communication interventions, such as black box warnings and label changes [36]. A unique strategy was used in our study to measure the level of awareness of the opioid crisis by using two complementary types of data sources, i.e., spontaneous reports and social media, which has not yet been documented in the literature. Spontaneous reporting systems, such as Canada Vigilance, traditionally used for signal detection purposes, may also be a useful tool to assess the awareness in the community, especially in Canada, where there is a paucity of nationwide data sources [17,19]. Absence of time trends in AE reporting may be due to the social and sensitive nature of opioid-related harm. While AE reporting has been previously used as a proxy of awareness of the risks associated with statin usage [17], reporting practices for opioid-related harm may differ from that of other drugs. Further research would be needed to understand the determinants of reporting practices for opioid-related harm. Many opioid-related deaths were due to strong opioids such as hydromorphone, fentanyl, methadone, and oxycodone. Between 2009 and 2017, we observed an increase in fentanyl-related deaths along with a decrease in oxycodone-related deaths, which may reflect changes in prescription practices due to the introduction of potent opioids like fentanyl, which was highlighted in a recent study [37]. Starting in 2017, there was a reversal in the trend toward a decrease in opioid-related deaths in Quebec. However, it is unclear as to why methadone-related deaths constantly increased over time. These findings suggest that the evaluation of interventions and policies on opioids should also address individual products as opposed to opioids in general. This study does have some limitations. Interventions that were not published on the web or in the literature may have led to an underestimation of the true efforts made to reduce opioid-related harms in Canada. The total number of users of individual prescription opioid products in Canada was not available, which did not allow for the estimation of a reporting rate [38]. Spontaneous reports of opioid-related harms are only provided at a national level and thus, disaggregation of spontaneous reporting of opioid-related harms by province is not possible. The number of posts made on public social media sites without adjusting for confounding variables may not accurately represent awareness. The type of posts and what it was referring to (e.g., opioid awareness, adverse drug reaction) was not analyzed, and only the volume of posts on the opioid crisis in Canada was measured. In addition, the inclusion of posts from specific groups aiming to raise awareness on opioids/drugs may overestimate the general public’s awareness on the matter [38]. Opioid-related deaths were assessed using the coroner’s reports database, which is a robust and objective measure but available only at the provincial level, which limits the generalizability of the findings on the health outcomes. Furthermore, it was not possible to distinguish between prescribed and illicit opioid usage. Finally, study data cannot be used for hypothesis-testing purposes regarding the effectiveness of risk minimization interventions and policies, since they cannot be linked to one another at the patient or HCP level. Hence, for this project, these have been individually analyzed using a mixed methods approach under an ecological perspective, without implying causality. 5. Conclusions To our knowledge, a comprehensive and concurrent description of all components of the risk minimization framework (i.e., intervention coverage, process indicators, health outcomes) using a multistage mixed methods design has not yet been conducted, which was the rationale for this study. Although no inferences of causality were made in this study, the slight decrease in opioid-related deaths in the recent years may reflect a potential effectiveness of interventions and policies. However, it is not possible to determine which interventions and policies are the most effective. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/ijerph19095122/s1, Table S1. Number of RMIs and policies implemented at national and provincial level between 2016 and 2019. Table S2. Suspected-health products characteristics causing opioid-related harm in Canada Vigilance between 2009 and 2019. Table S3. Suspected-health product characteristics causing opioid-related harms in Canada Vigilance between 2009 and 2019. Table S4. Suspected opioids causing deaths in Quebec (Coroner’s reports) between 2009 and 2019. Figure S1. Reporting rate of opioid-related harm case reports (n = 4970) initially received in Canada Vigilance between 2009 and 2019. Figure S2. Number of opioid-related harm case reports according to the type of reporter between 2009 and 2019 in Canada Vigilance. Figure S3. Number of opioid-related deaths in Quebec caused by fentanyl and its derivatives (n = 271) and hydromorphone (n = 448) between 2009 and 2017. Figure S4. Relative distribution of fentanyl-, hydromorphone-, and oxycodone-related deaths in Quebec between 2009 and 2017. Click here for additional data file. Author Contributions All authors (C.G., G.C. and Y.M.) contributed to the conceptualization, methodology, validation and formal analysis, investigation, resources, data curation, writing of the original draft, review and editing, and the visualization, of the manuscript. G.C. and Y.M. contributed to the supervision and project administration. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Camille Goyer received a studentship from MITACS through the Accelerates program. Institutional Review Board Statement Ethical review and approval were not required since all data used originated from the public domain. Informed Consent Statement Not available. Data Availability Statement The data used are not available from the investigators. Conflicts of Interest The authors declare no conflict of interest for this study. Unrelated to this project, Camille Goyer, Genaro Castillon, and Yola Moride provide consultancy services to pharmaceutical companies, some of which are opioids manufacturers. The views expressed in this research are those of the authors and do not necessarily reflect those of MITACS. Figure 1 Distribution of opioid interventions and policies in Canada between 2016 and 2019 by year of implementation and province. Figure 2 (A) Number of Facebook and Reddit posts mentioning the opioid crisis and/or opioid-related harms on Facebook (n = 1619) and Reddit (n = 1132) between 2009 and 2019; (B) Number of posts mentioning the opioid crisis and/or opioid-related harms on Twitter (n = 43,058) between 2009 and 2019. Figure 3 Number of opioid-related deaths in Quebec between 2009 and 2019. The arrows and corresponding dashed lines represent the number of interventions and policies implemented at that moment in time. The linear blue lines represent the trend in the number of opioid-related deaths in time before and after the declaration of the Canadian opioid epidemic. ijerph-19-05122-t001_Table 1 Table 1 Types of opioid risk minimization interventions and policies implemented in Canada (national or provincial) between 2016 and 2019. Type of Interventions * n (%) Total = 413 Harm reduction strategies 130 (31.5) Education/continuing education 101 (24.5)   For HCPs only 71 (70.3)   For the community 26 (25.7)   For patients only 4 (4.0) Opioid awareness 65 (15.7)   For the community 57 (87.7)   For patients or family only 8 (12.3)   Policy changes 51 (12.3) Update/creation of guidelines/standard of practice 28 (6.8) Knowledge exchange 16 (3.9) Pharmacovigilance, control, and monitoring 11 (2.7) Community interventions 9 (2.2) Prevention measures 2 (0.5) HCP: Health care professional. * Categories are mutually exclusive. Note: Interventions targeting patients apply to opioid users or their families (e.g., the Neighbourhood Pharmacy Association of Canada Created a handout named “Opioid Pain Medicines Information for Patients and Families”). Interventions targeting the community involve those directed towards a broader population (e.g., the University of Waterloo created a video on Naloxone administration). Interventions that target the community are also likely to reach HCPs and patients. ijerph-19-05122-t002_Table 2 Table 2 Characteristics of patients and reporters of opioid-related harm cases reported to Canada Vigilance between 2009 and 2019. Patient Characteristics n (%) Total = 4970 Sex   Male 2730 (54.9)   Female 1969 (39.6)   Unknown 271 (5.5) Age   Mean ± SD, in years 38.1 ± 17.0   Neonate (0–<25 days) 8 (0.2)   Infant (>25 days–<1 year) 16 (0.3)   Child (≥1–<13 years) 44 (0.9)   Adolescent (≥13–<18 years) 76 (1.5)   Adult (≥18–<65 years) 3356 (67.5)   Elderly (≥65 years) 228 (4.6)   Unknown 1242 (25.0) Seriousness of opioid-related harm   Serious 4881 (98.2)   Non-serious 89 (1.8) Type of reporter   Non-HCP 3174 (63.9)   HCP 1501 (30.2)   Unknown 295 (6.0) Opioid-related harm a Total = 6727   Abuse/Misuse/Dependence 3986 (59.3)   Opioid-related death 1344 (20.0)   Overdose 1159 (17.2)   Diversion 38 (3.5) SD: Standard deviation, HCP: Health care professional, Non-HCP: Non-health care professional. a Some case reports reported more than one opioid-related harm. ijerph-19-05122-t003_Table 3 Table 3 Characteristics of patients for opioid-related deaths in Quebec (Coroner’s reports) (2009–2019). Patient Characteristics n (% Total = 1582 Sex   Male 1074 (67.9)   Female 508 (32.1) Age   Mean ± SD, in years 44.8 ± 13.3   Pediatric (0–<13 years) -   Adolescent (≥13–<18) 3 (0.2)   Adult (18–<65 years) 1498 (94.7)   Elderly (>65 years) 80 (5.1)   Unknown 1 (0.1) SD: Standard deviation. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Government of Canada Opioid- and Stimulant-Related Harms in Canada Government of Canada 2021 Available online: https://health-infobase.canada.ca/substance-related-harms/opioids-stimulants (accessed on 5 April 2022) 2. Belzak L. Halvesron J. Evidence synthesis—The opioid crisis in Canada: A national perspective Health Promot. Chronic Dis. Prev. Can. 2018 38 224 233 10.24095/hpcdp.38.6.02 29911818 3. Canadian Public Health Association The Opioid Crisis in Canada Canadian Public Health Association 2016 Available online: https://www.cpha.ca/sites/default/files/uploads/policy/positionstatements/opioid-positionstatement-e.pdf (accessed on 5 April 2022) 4. CCSA The Availability of Take-Home Naloxone in Canada. Canadian Centre on Substance Abuse 2016 Available online: https://www.ccsa.ca/sites/default/files/2019–05/CCSA-CCENDU-Take-Home-Naloxone-Canada-2016-en.pdf (accessed on 5 April 2022) 5. Government of Canada Federal actions on opioids to date Government of Canada 2022 Available online: https://www.canada.ca/en/health-canada/services/opioids/federal-actions/overview.html#a1 (accessed on 5 April 2022) 6. Health Canada Opioid Warning Sticker and Patient Information Handout, and Risk Management Plans Government of Canada 2019 Available online: https://www.canada.ca/en/health-canada/services/drugs-health-products/drug-products/applications-submissions/policies/warning-sticker-opioid-patient-information-handout.html (accessed on 5 April 2022) 7. Health Canada Submission of Targeted Risk Management Plans and Follow-Up Commitments for Prescription Opioid-Containing Products—Guidance for Industry Government of Canada Ottawa, ON, Canada 2018 8. CIOMS Working Group IX Practical Approaches to Risk Minimisation for Medicinal Products: Report of CIOMS Working Group IX CIOMS Working Group IX Geneva, Switzerland 2014 184 978-92-9036-084-4 9. Smith M.Y. Russell A. Bahri P. Mol P. Frise S. Freeman E. Morrato E.H. The RIMES Statement: A Checklist to Assess the Quality of Studies Evaluating Risk Minimization Programs for Medicinal Products Drug Saf. 2018 41 389 401 10.1007/s40264-017-0619-x 29218682 10. EMA Guideline on Good Pharmacovigilance Practices (GVP)—Module XVI—Risk Minimisation Measures: Selection of Tools and 5 Effectiveness Indicators (Rev 3) EMA Amsterdam, The Netherlands 2021 11. Moride Y. Lemieux-Uresandi D. Castillon G. Moura C.S. Pilote L. Faure M. Bernartsky S. A Systematic Review of Interventions and Programs Targeting Appropriate Prescribing of Opioids Pain Physician 2019 22 229 240 10.36076/ppj/2019.22.229 31151331 12. Mouchantaf R. Auth D. Moride Y. Raine J. Han S.Y. Smith M.Y. Risk Management for the 21st Century: Current Status and Future Drug Saf. 2021 44 409 419 10.1007/s40264-020-01033-z 33565024 13. Fetters M.D. Curry L.A. Creswell J.W. Achieving Integration in Mixed Methods Designs—Principles and Practices Health Serv. Res. 2013 48 2134 2156 10.1111/1475-6773.12117 24279835 14. Health Canada Actions on Opioids 2016 and 2017 Government of Canada Ottawa, ON, Canada 2017 978-0-660-23819-7 15. Canada Health Act, RSC 1985, c C-6 2022 Available online: https://canlii.ca/t/532qv (accessed on 5 April 2022) 16. Health Canada Canada Vigilance Program. Government of Canada 2018 Available online: https://www.canada.ca/en/health-canada/services/drugs-health-products/medeffect-canada/canada-vigilance-program.html (accessed on 5 April 2022) 17. Van Hunsel F. van Puijenbroek E. de Jong-van den Berg L. van Grootheest K. Media attention and the influence on the reporting odds ratio in disproportionality analysis: An example of patient reporting of statins Pharmacoepidemiol. Drug Saf. 2010 19 26 32 10.1002/pds.1865 19953500 18. Schroeder D.R. Statistics: Detecting a Rare Adverse Drug Reaction Using Spontaneous Reports Reg. Anesth. Pain Med. 1998 23 (Suppl. S2) 183 189 10.1097/00115550-199823062-00009 9845392 19. Health Canada Good Pharmacovigilance Practices (GVP) Guidelines (GUI-0102) Health Canada Ottawa, ON, Canada 2013 20. Statistics Canada Table 17-10-0009-01 Population Estimates, Quarterly Available online: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1710000901 (accessed on 5 April 2022) 21. İşgüzar B. Twitter-Scraper GitHub 2019 Available online: https://github.com/bisguzar/twitter-scraper (accessed on 5 April 2022) 22. Towards the Heart Take Home Naloxone Towards the Heart 2012 Available online: https://towardtheheart.com/naloxone (accessed on 5 April 2022) 23. Tupper K.W. McCrae K. Garber I. Lysyshyn M. Wood E. Initial results of a drug checking pilot program to detect fentanyl adulteration in a Canadian setting Drug Alcohol Depend. 2018 190 242 245 10.1016/j.drugalcdep.2018.06.020 30064061 24. College of Physicians and Surgeons of British Columbia Annual Report 2016/17 College of Physicians and Surgeons of British Columbia Vancouver, BC, Canada 2017 25. CIHI Webinar: Opioid Overdose Canadian Institute for Health Information 2018 Available online: https://www.cihi.ca/en/bulletin/webinar-opioid-overdose (accessed on 5 April 2022) 26. School of Pharmacy Naloxone and Opioid Resources, University of Waterloo Available online: https://uwaterloo.ca/pharmacy/resources-services-and-initiatives/health-resources/naloxone-and-opioid-resources (accessed on 5 April 2022) 27. Healthy Canadians End Stigma Campaign YouTube 2019 Available online: https://www.youtube.com/watch?v=Lj-lnShfDu0 (accessed on 5 April 2022) 28. Health Canada Opioid Lived Experiences Health Canada 2017 Available online: https://www.canada.ca/en/health-canada/services/opioids/awareness-resources.html#t2 (accessed on 5 April 2022) 29. Canadian Pain Society Opioids and Pain Management Canadian Pain Society Markham, ON, Canada 2018 30. Health Canada Drug and Medical Device Highlights 2018: Helping you Maintain and Improve Your Health Health Canada 2019 Available online: https://www.canada.ca/en/health-canada/services/publications/drugs-health-products/drug-medical-device-highlights-2018.html (accessed on 5 April 2022) 31. Government of Canada National Report: Apparent Opioid-Related Deaths in Canada, Health Info-Base Canada 2019 Available online: https://health-infobase.canada.ca/datalab/national-surveillance-opioid-mortality.html (accessed on 5 April 2022) 32. Mowatt G.D. Goodman N. Medicinal product regulation and product liability in Canada: Overview, Life Sciences Global Guide 2016/2017, Practical Law Available online: https://content.next.westlaw.com/2-616-7870?__lrTS=20220201130028830&transitionType=Default&contextData=(sc.Default)&firstPage=true (accessed on 5 April 2022) 33. Ahmed Y.A. Ahmad M.N. Ahmad N. Zakaria N.H. Social media for knowledge-sharing: A systematic literature review Telemat. Inform. 2019 37 72 112 10.1016/j.tele.2018.01.015 34. Pierce C.E. Bouri K. Pamer C. Proestel S. Rodriguez H.W. Van Le H. Freifeld C.C. Brownstein J.S. Walderhaug M. Edwards I.R. Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts Drug Saf. 2017 40 317 331 10.1007/s40264-016-0491-0 28044249 35. Pappa D. Stergioulas L.K. Harnessing social media data for pharmacovigilance: A review of current state of the art, challenges and future directions Int. J. Data Sci. Anal. 2019 8 113 135 10.1007/s41060-019-00175-3 36. Lee J.-Y. Lee Y.-S. Kim D.H. Lee H.S. Yang B.R. Kim M.G. The Use of Social Media in Detecting Drug Safety–Related New Black Box Warnings, Labeling Changes, or Withdrawals: Scoping Review JMIR Public Health Surveill. 2021 7 e30137 10.2196/30137 34185021 37. Fischer B. Rehm J. Tyndall M. Effective Canadian policy to reduce harms from prescription opioids: Learning from past failures Can. Med. Assoc. J. 2016 188 1240 1244 10.1503/cmaj.160356 27821465 38. Food and Drug Administration Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment Food and Drug Administration 2005 Available online: https://www.fda.gov/files/drugs/published/Good-Pharmacovigilance-Practices-and-Pharmacoepidemiologic-Assessment-March-2005.pdf (accessed on 5 April 2022)

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093297 sensors-22-03297 Communication Magnetic Nanoparticles as Effective Heavy Ion Adsorbers in Natural Samples https://orcid.org/0000-0002-1594-5889 Klekotka Urszula 1 Wińska Ewelina 1 https://orcid.org/0000-0002-1164-4747 Zambrzycka-Szelewa Elżbieta 1 Satuła Dariusz 2 Kalska-Szostko Beata 1* Marrazza Giovanna Academic Editor 1 Faculty of Chemistry, University of Bialystok, Ciolkowskiego 1K, 15-245 Bialystok, Poland; u.klekotka@uwb.edu.pl (U.K.); ewelinawinska@wp.pl (E.W.); elazamb@uwb.edu.pl (E.Z.-S.) 2 Faculty of Physics, University of Bialystok, Ciolkowskiego 1L, 15-245 Bialystok, Poland; d.satula@uwb.edu.pl * Correspondence: kalska@uwb.edu.pl 25 4 2022 5 2022 22 9 329721 1 2022 08 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This paper refers to research based on tests completed on the adsorption of heavy metal ions (Pb2+, Cu2+, Cd2+) from selected natural liquid samples such as apple, tomato, and potato juices using surface-functionalized Mn ferrite nanoparticles (Mn0.2Fe2.8O4). To determine the most efficient adsorption conditions of these heavy metals, the nanoparticles’ surfaces were modified with five different ligands (phthalic anhydride, succinic anhydride, acetic anhydride, 3-phosphonopropionic acid, and 16-phosphonohexadecanoic acid). To evaluate the success of the adsorption process, the resultant liquid samples were examined for the amount of residuals using the flame atomic absorption spectroscopy method. The Mn ferrite particles selected for these tests were first characterized physicochemically by the following methods: transmission electron microscopy, scanning electron microscopy, X-ray diffraction, IR spectroscopy, Mössbauer spectroscopy. ferrite nanoparticles heavy metal detection food pollution particles functionalization ==== Body pmc1. Introduction At present, environmental contamination from heavy metals is a highly urgent subject for scientists. Heavy metals are toxic to plants, animals, and humans [1]. Ubiquitous heavy metals cause a threat to human health and life. For this reason, it is important to effectively detect them and prevent poisoning [2]. Properly modified nanoparticles can capture many substances (ions or compounds) from various types of solutions (natural or artificial) and be successfully used as detectors or removal centers for these substances [3]. Especially effective in such instances are surface-functionalized magnetic nanoparticles which can be easily manipulated by external magnetic field [4]. Therefore, it is crucial to remove dangerous impurities from the human diet and environment [5,6] or, at minimum, have information about their contribution values. Heavy metals occur as contaminants in food because of their prevalence in the environment, resulting from human activities. People can be exposed to these metals, for example, through the consumption of contaminated food or water. Their accumulation in the body leads to harmful effects over time [7]. The major heavy metals present in food are lead, cadmium, and copper [8,9]. Both the International Agency for Research on Cancer and the National Toxicology Program have recognized cadmium as a classified Group 1 carcinogen [10]. Cd accumulates in the circulatory system, heart, kidneys, and lungs. Additionally, it is very toxic to bones [8]. In contrast, lead (Pb) damages the respiratory and immune systems. This metal is very toxic, especially for children, because it damages their nervous system. In children’s bodies, no organ system is immune to the effects of lead poisoning [8]. Poisoning with copper can cause nausea and central nervous system injury, as well as renal insufficiency [11]. The threat of heavy metals is a direct result of their movement through the trophic chain from soil–plant–animal–human, potentially resulting in their accumulation in the human body [12,13]. The largest sources of heavy metals in soil comes from bedrock, industrial emissions, communications, and agriculture (Figure 1). The mining, metallurgy, and chemical industries are among the largest anthropogenic sources of soil pollution [12,13]. Magnetic nanoparticles can potentially be used to cleanse food of heavy metals due to their easy manipulation based on an external magnetic field. Moreover, a short contact time can ensure optimal conditions. In aqueous solutions, one of the important parameters is the pH of the contaminated mixture because of the formation of a thin layer of Fe-OH bonds on the surface of magnetite nanoparticles. This, in turn, can be protonated or deprotonated regardless of the pH. For easier removal of heavy metal ions, the surface of nanoparticles should be slightly negative, which can be obtained (most often reported) in solutions with a pH higher than six [14,15]. Nowadays, magnetic nanoparticles are used to treat water contaminated with heavy metals [14,16,17,18]. Suitable modification of the nanoparticles may result in a higher adsorption efficiency of heavy metals or an increase in the effects of the selected ion adsorption [19]. This can be achieved using magnesium–zinc ferrite, which successfully improves the removal of Cr(VI) and Ni(II) from solution [20], or calcium-doped ferrite which is most effective in the adsorption of Pd in comparison to other substances [21]. Summarizing the scattered data presented in the literature regarding the metal detectors based on nanoparticles, the most important are: the pH of the solution (its optimal value depends on the adsorbed ion) [22], the particles’ core composition (which is related to the size, shape, and surface morphology of the singular objects) [22,23], and the surfactant [24]. In this case, surfactants play roles not only as surface stabilizers, which prevent the aggregation of especially magnetic nanoparticles, but also in changing the surface characteristics to allow physical or chemical interactions. Additionally, surfactants separate the magnetic cores to a sufficient distance to prevent unfavorable magnetic attraction which reduces the effective surface area [25,26]. In this paper, we present research on the removal of selected heavy metal ions (Cd, Cu, Pb) from contaminated natural liquid samples (fruit and vegetables juices) by surface-modified (acetic anhydride, phthalic anhydride, succinic anhydride, 3-phosphonopropionic acid, and 16-phosphonohexadecanoic acid) Mn ferrite nanoparticles (Mn0.2Fe2.8O4). This study is a continuation of our previously obtained results and conclusions [27]. Therefore, similar experimental protocols were employed. 2. Materials and Methods 2.1. Reagents and Solutions All chemicals used in this work were analytical grade and were used without any purification. FeCl2·4H2O, FeCl3·6H2O, tetrabutylammonium hydroxide (TBAOH) (40% in water), NH3 (25%), MnCl2 (anhydrous), CuSO4 (anhydrous), PbCl2 (anhydrous), Cd(NO3)2·4H2O, and acetic anhydride (AA C4H6O3) were purchased from Polish Chemical Reagents. Phthalic anhydride (PA C8H4O3), succinic anhydride (SA C4H4O3), 3-phosphonopropionic acid (3-PPA C3H7O5P), 16-phosphonohexadecanoic acid (16-PHDA C16H33O5P), and PBS (phosphate buffer sulfate) were received from Sigma–Aldrich. All chemicals were of ACS purity. 2.2. Apparatus Nanoparticles used in the experiments were analyzed structurally, in terms of chemical composition, and magnetically by:(i) X-ray diffractometry (XRD) (Agilent Technologies SuperNova diffractometer with a Mo micro-focused source (Kα2 = 0.713067 Å))—placing a small amount of powder on a nylon loop using a high viscosity oil—to determine the crystal structure; (ii) Transmission electron microscopy (TEM) (FEI Tecnai G2 X-TWIN 200 kV microscope—prefixing a drop of nanoparticle solution, on a carbon-covered 400 mesh Cu grid—to control particle morphology, shape, and size; (iii) Infrared spectroscopy (IR) in the spectral range between 500 and 4000 cm−1 (using a Nicolet 6700 spectrometer working in transmission mode)—positioning a small amount of particle powder on a diamond window and squeezing via a stamp—to confirm surface functionalization; (iv) Scanning electron microscope (INSPEC 60)—placing a small amount of particle powder on the microscopic table via conducting carbon tape—to examine the morphology of the obtained particle film; (v) Mössbauer spectroscopy with a spectrometer working in constant acceleration mode with a 57Co in Rh matrix radioactive source—mixing the particle powder with BN and forming a disc—to establish the magnetic state of particles. The spectra were calibrated using α-Fe as a reference foil at room temperature (RT). The amounts of Pb, Cu, and Cd elements in the tested solutions were measured using flame atomic absorption spectrometry (FAAS). Experiments were performed in a high-resolution continuum source atomic absorption spectrometer ContrAA 700 (Analytik Jena AG, Jena, Germany) equipped with a continuum light source—xenon short-arc lamp XBO 301 (GLE, Berlin, Germany) with the arc in a hot spot mode suitable for all elements’ determination. A double monochromator consisting of a prism pre-monochromator and a high-resolution echelle grating monochromator, along with a charge-coupled device (CCD) array detector with 588 pixels equipped with an air-acetylene flame was used for the determination of Pb, Cd, and Cu under optimized conditions of (a) Pb: burner height 7 mm, burner length 100 mm, air–C2H2 flow rate 75 L h−1; (b) Cu: burner height 4 mm, burner length 100 mm, air–C2H2 flow rate 65 L h−1; and (c) Cd: burner height 5 mm, burner length 100 mm, air–C2H2 flow rate 55 L h−1. 2.3. Synthesis of Mn2+ Doped Ferrite Nanoparticles Magnetite nanoparticles doped with manganese were synthesized by co-precipitation of Fe(II), Mn(II), and Fe(III) chlorides in a 0.5% ammonia solution. As a surfactant, a water solution of TBAOH was used. In this case, about 20% of the iron (II) was replaced by Mn(II) [28,29]. The exact synthesis has been described in our previous papers [27]. The final sample was dried by rotary evaporation until a powder was obtained. 2.4. Modification of Nanoparticles PA, SA, AA, 3-PPA, and 16-PHDA After synthesis, nanoparticles were modified with selected anhydrides (PA, SA, AA), and organophosphorus acids (3-PPA, 16-PHDA). Every step of the modification was conducted at room temperature. The attachment of anhydrides was conducted as follows: the respective anhydrous solutions were prepared in ethanol with a concentration of 0.14 M. Then, a solution of the corresponding anhydride was mixed with about 80 mg of nanoparticles (in powder form) and stirred for 4 h [24]. After this time, the solution was removed (with the assistance of an external magnetic field), and the powder was washed 3 times with ethanol and dried at RT (room temperature). The modification with organophosphorus acids involved a different procedure. First, the nanoparticles were washed with acetone and ethanol. Then, 10 mg of nanoparticles (in powder form) was mixed with a 1mM solution of 3-PPA or 16-PHDA for 18 h. In the next step, a mixture of nanoparticles and organophosphorus acid solution was placed in an ultrasonic bath for 1 min, and then the solution was removed with the assistance of an external magnetic field. In the end, nanoparticles were washed 3 times with PBS solution and dried [30]. Modified nanoparticles were characterized using IR spectroscopy. 2.5. Preparation of Food Samples Solution for FAAS In these studies, three types of vegetable/fruit juices were tested: tomato, apple, and potato, respectively. Squeezed juices from fresh fruits/vegetables were initially separated from the parenchyma with the use of a centrifuge, and the precipitate was separated from the solutions. The pH values of the respective solutions were: apple juice (2.07), tomato juice (4.98), potato juice (6.20). Then, the respective solutions were contaminated with each heavy metal ion at a concentration of 100 ppm. Then, the prepared juice samples were added to 2 mg of modified Mn-doped ferrite nanoparticles. The whole mixture of nanoparticles was stirred for 10 min. Afterward, the liquid was separated from the solid phase via the assistance of an external magnetic field. In the obtained solutions, the concentrations of Pb, Cu, and Cd ions were measured using the FAAS method. 3. Results 3.1. Physicochemical Characterization of Pristine and Modified Ferrite Nanoparticles The morphology of the fabricated pristine nanoparticles was characterized using TEM. As shown in Figure 2A, the obtained nanoparticles have round shapes and well-defined sizes with a narrow size distribution. The calculated nanoparticles’ diameter is about 15 ± 2 nm. Moreover, surfactant (TBAOH) shells can be also seen in the TEM image. Therefore, primary surface modification is confirmed [27]. The IR spectrum (Figure 2B) of Mn0.2Fe2.8O4 nanoparticles show only bands typical for the procedure used. The intensive signals present below 600 cm−1 originate from the Fe-O bonds in magnetite [31]. Bands around 1400–1600 cm−1 and below 3000 cm−1 are characteristic of O–H [32]. Depicted in Figure 2C, the X-ray diffractograms show a set of patterns that are typical for magnetite (or maghemite) structure without the reflections typical for other Mn or Fe oxide phases. These signals can be assigned Miller indexes of (220), (311), (400), (422), (511), and (440) [33]. The lattice constant calculated from the diffractograms (8.38 ± 0.02 Å) is consistent with the literature value of magnetite (8.39 ± 0.01 Å) [34]. The EDX measurements also showed that the percentage of Mn was 15%. This proves the substitution of Fe atoms by Mn2+ in the magnetite. Such a result confirms the successful incorporation of Mn into the primary structure [28]. The Mössbauer spectrum depicted in Figure 2D shows that Mn0.2Fe2.8O4 nanoparticles are in a different magnetic state than typical Fe3O4 at RT (room temperature) [27,35]. Such changes can be expected from dipole–dipole interactions between Mn2+ and Fe2+, Fe3+, when Mn2+ is incorporated into the structure [28]. At RT, Mn-doped particles are closer to a superparamagnetic blocking temperature in comparison to magnetite [28]. This fact weakens the interparticle interaction between separate nanoparticles and helps in their integration with third objects due to providing easier access to their surface [27]. 3.2. Adsorption Tests In this section, the results of the adsorption of heavy metals on the tested nanoparticles after the physicochemical characterization of the inorganic cores are presented. For this purpose, SEM images and IR spectra of the nanoparticles with proper surface functionalization after exposure to heavy metals are presented. Food samples contaminated with heavy metals before and after contact with the tested nanocomposites were analyzed by FAAS. The results of the percentage of value adsorbed are presented in Table 1. 3.3. Scanning Electron Microscopy The morphology of the tested samples was imaged using SEM. The use of different juices caused significant changes in the particles’ film appearance resulting from the presence of variable organic matrixes that can be loosely adsorbed on the particles. Together with surfactants and juice constituents, the dried particles formed a relatively even film. However, in the solution, nanostructures were separated enough to have free and prolonged access to pollutants. The film of pristine Mn0.2Fe2.8O4 particles (Figure 3A) was very rough because the surfactants used did not appear in large amounts as compared to the particles. Surface functionalization (Figure 3B) already causes the smoothing of the film because it increases the organic over the inorganic contribution. When the amount of surfactants and functional species dominates the system, particles can organize in a more relaxed manner because the interparticle magnetic interaction is weaker in this case. The bathing of particles in juice more strongly influenced the roughness/smoothing of the presented films. It was seen that the particles immersed in tomato and potato juices created a smooth film, while apple juice had the opposite effect regardless of the heavy metal tested. This was caused by the different compositions of the organic matrix of juices used. 3.4. Infrared Spectroscopy In Figure 2B, the IR spectrum of pristine Mn0.2Fe2.8O4 nanoparticles is presented. After surface modification and Pb, Cd, or Cu adsorption (selected spectra—Figure 4), spectra are richer. The more intensive bands at 1640 cm−1 originate from N-H bonds from primary amines, and bands around 1380 cm−1 which respond to C-H deformational vibrations are present [32]. Wide bonds around 3330 cm−1 are typical for O-H bonds in water, which is adsorbed on the nanoparticles’ surface since the organic matrix causes the presence of a very spongy surface coverage where water can be trapped. These bands are clearly related to the residues of the juice samples adsorbed on the surface of nanoparticles. As can be found in the literature, the modification of the IR spectra in the range 1300–1600 cm−1 can be related to the interaction of modified particles with heavy metals [24]. Therefore, the origin of signals in that range is most probably due to heavy ion adsorption. 3.5. Flame Atomic Absorption Spectroscopy Juice solutions purposely contaminated with the respective elements were tested using the FAAS method. For this, each kind of solution was properly diluted and then expanded in flame. The adsorption data shows the following presence of detected ions in the samples (see Table 1 and Figure 5). The data presented in Table 1 clearly indicate the juices in which certain heavy metal detection is the most effective. It is clear that Pb is much more efficiently adsorbed from potato juice in comparison to the other juices used (see Table 1 and Figure 5B). This is clearly connected with the pH value of the potato juice (6.02). The effect of pH on the adsorption of Pb2+ has been studied elsewhere, and it was estimated to be around 6–8 [24]. This is also in alignment with our previous studies, where the detection of heavy metals was tested in model water solutions [27]. Moreover, in this case, the most promising surface functionalization is connected with the presence of SA, 3-PPA, and 16-PHDA (due to its universality). The potato pure organic matrix also allows for the detection of a high number of Pb ions by pristine Mn0.2Fe2.8O4 NPs (almost 63%) and that modified by AA or SA (besides the most effective 16-PHDA). These results also confirm that the most universal functionalization for Pb detection was obtained by 16-PHDA. The situation is different in the case of Cu. Here, adsorption is much lower and the best linker cannot be clearly determined because its efficiency is not much different from the one used. Additionally, the pH effect does not play an equally important role for Pb2+. The general conclusion that can be made is that nanoparticles’ surfaces have to be functionalized, otherwise adsorption will not take place at all. For Cu in each juice (and pH), a different linker is the most active. The case of Cd adsorption is also very clear then; Cd2+ ions cannot be detected at all for a low pH, as is the case for apple juice (around 2) [36]. Similarly to Pb2+, the highest values were obtained in potato juice at pH 6, regardless of surface functionalization. The adsorption of Cd2+ is similar in the case of potato and tomato juices except for unmodified particles and 16-PHDA. The results show that in potato juice, Cd is detected regardless of the modifier used with almost equal efficiency. In this matrix, pristine NPs are also effective, but are very ineffective in tomato juice. All these results suggest that many parameters must be taken into account when proper detectors are planned. All this is important in the interpretation of the adsorption effect. On the contrary, in the model water-based solutions, clear conclusions were obtained [24]. Therefore, a selective but not universal linker has been described. For future studies, the detection of a universal linker is required. Moreover, more studies on the pH effect are needed. Figure 5 shows a graphical presentation of the FAAS results with respect to the identified element (A) or juice (B). In Figure 5B, it is clear that pH strongly governs the adsorption capability of the presented elements more so than linkers. In apple juice, Cu adsorption is equally effective regardless of the linkers used. In contrast, for Pb, it evidently works much better as ‘naked’ particles or coated with 16-PHDA. The least effective is SA. In this environment, Cd is not detectable at all. In potato juice, Pb adsorption is very high, with some Cd adsorption as well. Cu is detected only on modified particles. Tomato juice is the most complex, whereby the adsorption of elements very strongly depends on the linkers present on the particles’ surface. 4. Conclusions Detailed qualitative and quantitative studies show that detection from real matrixes (contaminated fruit extracts) is not an easy task. It is clear that that the analyzed elements, linkers used, organic matrix composition, and pH for detection are all important factors. All this leads to the conclusion that more studies on this subject are necessary, where the step-by-step process of the mentioned parameters are examined. In the studied series, the effective detection of Cd in potato and tomato juices by PA, SA, AA, and 3-PPA was evident. A high efficiency of AA in potato juice for each studied element was seen as well. The selectivity of adsorption related to the extracts and tested elements was also observed. Acknowledgments The authors would like to thank M. Leigh Avera for proofreading the manuscript. Author Contributions Conceptualization, B.K.-S.; methodology; investigation, E.W., E.Z.-S., D.S. and U.K.; data curation, E.W., E.Z.-S., D.S. and U.K.; writing—original draft preparation, U.K., E.W., E.Z.-S., D.S. and B.K.-S.; writing—review and editing, D.S. and B.K.-S.; visualization, U.K. and E.W.; supervision, B.K.-S. All authors have read and agreed to the published version of the manuscript. Funding The work was partially financed by EU funds via project with contract number POPW.01.03.00-20-034/09-00, POPW.01.03.00-20-004/11-00 and by the NSC Poland fund, project number 2014/13/N/ST5/00568. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The raw/processed data required to reproduce these findings cannot be shared at this time as the data also form part of an ongoing study. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic presentation of the possible transport of heavy metals in the environment. Figure 2 (A) TEM images of Mn0.2Fe2.8O4 nanoparticles; (B) IR spectra of pristine nanoparticles and with attached SA, AA, and 16-PHDA linkers, respectively; (C) X-ray diffractogram of Mn0.2Fe2.8O4; (D) Mössbauer spectrum of Mn0.2Fe2.8O4 nanoparticles. Figure 3 SEM images of films of (A) pristine Mn-doped ferrite nanoparticles; (B) nanoparticles after detection tests of heavy metals in selected food samples. Figure 4 IR spectra of ferrite nanoparticles modified by SA after heavy metal detection from tested juices. Figure 5 Graphical presentation of FAAS data: (A) juice dependence, (B) element dependence. sensors-22-03297-t001_Table 1 Table 1 Percentage identification of elements in respective juices (columns) and selected modifiers (rows) (LOD—detection limit [36]). Sample Type % Adsorbed ± 0.05 Apple Potato Tomato I II III Pb Mn0.2Fe2.8O4 NP’s 7.98 62.53 13.80 Mn0.2Fe2.8O4 + PA 3.84 9.19 12.82 Mn0.2Fe2.8O4 + SA 2.22 44.80 4.38 Mn0.2Fe2.8O4 + AA 3.62 48.00 <LOD Mn0.2Fe2.8O4 + 3-PPA 5.83 46.22 37.01 Mn0.2Fe2.8O4 + 16-PHDA 11.52 75.02 23.38 Cu Mn0.2Fe2.8O4 NP’s 2.98 <LOD 0.50 Mn0.2Fe2.8O4 + PA 3.04 7.89 3.76 Mn0.2Fe2.8O4 + SA 5.32 3.72 4.21 Mn0.2Fe2.8O4 + AA 3.64 10.31 4.38 Mn0.2Fe2.8O4 + 3-PPA 5.66 1.97 6.89 Mn0.2Fe2.8O4 + 16-PHDA 4.33 1.69 3.98 Cd Mn0.2Fe2.8O4 NP’s 0.01 13.38 1.33 Mn0.2Fe2.8O4 + PA 0.02 14.3 13.13 Mn0.2Fe2.8O4 + SA 0.02 10.56 9.75 Mn0.2Fe2.8O4 + AA 0.03 14.93 11.47 Mn0.2Fe2.8O4 + 3-PPA 0.01 12.75 8.64 Mn0.2Fe2.8O4 + 16-PHDA <LOD 16.89 0.21 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Masindi V. Muedi K.L. Environmental contamination by heavy metals Heavy Met. 2018 10 115 132 2. Mitra S. Chakraborty A.J. Tareq A.M. Emran T.B. Nainu F. Khusro A. Simal-Gandara J. Impact of heavy metals on the environment and human health: Novel therapeutic insights to counter the toxicity J. King Saud Univ. Sci. 2022 34 101865 10.1016/j.jksus.2022.101865 3. Ibrahim R.K. Hayyan M. AlSaadi M.A. Hayyan A. Ibrahim S. Environmental application of nanotechnology: Air, soil, and water Environ. Sci. Pollut. Res. 2016 23 13754 13788 10.1007/s11356-016-6457-z 27074929 4. Dee G. Gun’ko Y.K. Magnetic nanoparticles and nanoobjects used for medical applications Magnetic Materials and Technologies for Medical Applications School of Chemistry, Trinity College Dublin Dublin, Ireland 2022 59 105 5. Youssef A.M. Malhat F.M. Selective Removal of Heavy Metals from Drinking Water Using Titanium Dioxide Nanowire Macromol. Symp. 2014 337 96 101 10.1002/masy.201450311 6. Almomani F. Bhosale R. Khraisheh M. Kumar A. Almomani T. Heavy metal ions removal from industrial wastewater using magnetic nanoparticles (MNP) Appl. Surf. Sci. 2020 506 144924 10.1016/j.apsusc.2019.144924 7. EFSA Scientific Opinion on the risks to public health related to the presence of nickel in food and drinking water EFSA J. 2015 13 4002 8. Zhong W.-S. Ren T. Zhao L.-J. Determination of Pb (Lead), Cd (Cadmium), Cr (Chromium), Cu (Copper), and Ni (Nickel) in Chinese tea with high-resolution continuum source graphite furnace atomic absorption spectrometry J. Food Drug Anal. 2016 24 46 55 10.1016/j.jfda.2015.04.010 28911408 9. El-Dib F.I. Mohamed D.E. El-Shamy OA A. Mishrif M.R. Study the adsorption properties of magnetite nanoparticles in the presence of different synthesized surfactants for heavy metal ions removal Egypt. J. Pet. 2020 29 1 7 10.1016/j.ejpe.2019.08.004 10. CAS, No. International Agency for Research on Cancer Agents Classified by the IARC Monographs 2012 1 106 Available online: http://monographs.iarc.fr/ENG/Classification/index.php (accessed on 20 January 2022) 11. Hashem E.Y. Seleim M.M. El-Zohry A.M. Environmental method for spectrophotometric determination of copper(II) Green Chem. Lett. Rev. 2011 4 241 248 10.1080/17518253.2010.546370 12. Gouder de Beauregard A.C. Mahy G. Phytoremediation of heavy metals: The role of macrophytes in a stormwater basin Int. J. Ecohydrol. Hydrobiol. 2002 2 1 4 13. Vásquez-Murrieta M. Migueles-Garduño I. Franco-Hernández O. Govaerts B. Dendooven L. C and N mineralization and microbial biomass in heavy-metal contaminated soil Eur. J. Soil Biol. 2006 42 89 98 10.1016/j.ejsobi.2005.10.002 14. Fato F.P. Li S.W. Zhao L.J. Qiu K. Long Y.T. Simultaneous Removal of Multiple Heavy Metal Ions from River Water Using Ultrafine Mesoporous Magnetite Nanoparticles ACS Omega 2019 4 7543 7549 10.1021/acsomega.9b00731 31459847 15. Zhang J. Lin S. Han M. Su Q. Xia L. Hui Z. Adsorption Properties of Magnetic Magnetite Nanoparticle for Coexistent Cr(VI) and Cu(II) in Mixed Solution Water 2020 12 446 10.3390/w12020446 16. Singh R. Kumar N. Mehra R. Kumar H. Singh V.P. Progress and challenges in the detection of residual pesticides using nanotechnology based colorimetric techniques Trends Environ. Anal. Chem. 2020 26 e00086 10.1016/j.teac.2020.e00086 17. Buledi J.A. Amin S. Haider S.I. Bhanger M.I. Solangi A.R. A review on detection of heavy metals from aqueous media using nanomaterial-based sensors Environ. Sci. Pollut. Res. 2021 28 58994 59002 10.1007/s11356-020-07865-7 18. Yang J. Hou B. Wang J. Tian B. Bi J. Wang N. Huang X. Nanomaterials for the Removal of Heavy Metals from Wastewater Nanomaterials 2019 9 424 10.3390/nano9030424 19. Carlos L. Garcia Einschlag F.S.G. Gonzalez M.C. Martire D.O. Applications of Magnetite Nanoparticles for Heavy Metal Removal from Wastewater Waste Water Treat. Technol. Recent Anal. Dev. 2013 3 64 73 20. Tatarchuk T. Myslin M. Lapchuk I. Shyichuk A. Murthy A.P. Gargula R. Pędziwiatr A.T. Magnesium-zinc ferrites as magnetic adsorbents for Cr(VI) and Ni(II) ions removal: Cation distribution and antistructure modeling Chemosphere 2021 270 129414 10.1016/j.chemosphere.2020.129414 33418216 21. Kaur N. Mehta A. Mishra A. Chaudhary S. Rawat M. Basu S. Amphiphilic carbon dots derived by cationic surfactant for selective and sensitive detection of metal ions Mater. Sci. Eng. C 2019 95 72 77 10.1016/j.msec.2018.10.058 22. Wasiewska L.A. Seymour I. Patella B. Inguanta R. Burgess C.M. Duffy G. O’Riordan A. Reagent free electrochemical-based detection of silver ions at interdigitated microelectrodes using in-situ pH control Sens. Actuators B Chem. 2021 333 129531 10.1016/j.snb.2021.129531 23. Klekotka U. Piotrowska B. Satuła D. Giersig M. Kalska-Szostko B. Ferrite Core-Shell Nanoparticles Synthesized by Seed-Based Method Characterization and Potential Application Phys. Status Solidi A 2018 215 1700901 10.1002/pssa.201700901 24. Pirouz M.J. Beyki M.H. Shemirani F. Anhydride functionalised calcium ferrite nanoparticles: A new selective magnetic material for enrichment of lead ions from water and food samples Food Chem. 2015 170 131 137 10.1016/j.foodchem.2014.08.046 25306327 25. McBain S. You H.H.P. Dobson J. Magnetic nanoparticles for gene and drug delivery Int. J. Nanomed. 2008 3 169 26. Bhadani A. Okano T. Ogura T. Misono T. Sakai K. Abe M. Sakai H. Structural features and surfactant properties of core–shell type micellar aggregates formed by gemini piperidinium surfactants Colloids Surf. A Physicochem. Eng. Asp. 2016 494 147 155 10.1016/j.colsurfa.2015.11.073 27. Klekotka U. Wińska E. Zambrzycka-Szelewa E. Satuła D. Kalska-Szostko B. Heavy-metal detectors based on modified ferrite nanoparticles Beilstein J. Nanotechnol. 2018 9 762 770 10.3762/bjnano.9.69 29600137 28. Kalska-Szostko B. Kropiewnicka K. The influence of the transition metal substitution on chemically prepared ferrite nanoparticles—Mossbauer studies Curr. Appl. Phys. 2012 12 896 902 10.1016/j.cap.2011.12.003 29. Kalska-Szostko B. Zubowska M. Satuła D. Studies of the magnetite nanoparticles by means of Mössbauer spectroscopy Acta Phys. Pol. A 2006 109 365 369 10.12693/APhysPolA.109.365 30. Kalska-Szostko B. Rogowska M. Satuła D. Organophosphorous functionalization of magnetite nanoparticles Colloids Surf. B Biointerfaces 2013 111 656 662 10.1016/j.colsurfb.2013.07.004 23907054 31. Namduri H. Nasrazadani S. Quantitative analysis of iron oxides using Fourier transform infrared spectrophotometry Corros. Sci. 2008 50 2493 2497 10.1016/j.corsci.2008.06.034 32. Coates J. Interpretation of Infrared Spectra. A Practical Approach Encyclopedia of Analytical Chemistry John Wiley & Sons Ltd. Chichester, UK 2000 10815 10837 33. Petcharoen K. Sirivat A. Synthesis and characterization of magnetite nanoparticles via the chemical co-precipitation method Mater. Sci. Eng. B Solid-State Mater. Adv. Technol. 2012 177 421 427 10.1016/j.mseb.2012.01.003 34. Panda R.N. Gajbhiye N.S. Balaji G. Magnetic properties of interacting single domain Fe3O4 particles J. Alloys Compd. 2001 326 50 53 10.1016/S0925-8388(01)01225-7 35. Topsoe H. Dumesic J. Boudart M. Mossbauer spectra of stoichiometric and nonstoichiometric Fe3O4 microcrystals J. Phys. Colloq. 1974 35 411 413 10.1051/jphyscol:1974680 36. Thermo Elemental AAS, GFAAS, ICP or ICP-MS? Which Technique Should I Use? Thermo Elemental Waltham, WA, USA 2001 1 11

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093234 sensors-22-03234 Article Automatic Implementation Algorithm of Pressure Relief Drilling Depth Based on an Innovative Monitoring-While-Drilling Method Wu Zheng Zhang Wen-Long * Li Chen Dong Longjun Academic Editor Zhao Yanlin Academic Editor Chen Wenxue Academic Editor School of Energy and Mining Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China; bqt1900101036@student.cumtb.edu.cn (Z.W.); 13120008810@163.com (C.L.) * Correspondence: wenlong0523@163.com 22 4 2022 5 2022 22 9 323422 3 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). An innovative monitoring-while-drilling method of pressure relief drilling was proposed in a previous study, and the periodic appearance of amplitude concentrated enlargement zone in vibration signals can represent the drilling depth. However, there is a lack of a high accuracy model to automatically identify the amplitude concentrated enlargement zone. So, in this study, a neural network model is put forward based on single-sensor and multi-sensor prediction results. The neural network model consists of one Deep Neural Network (DNN) and four Long Short-Term Memory (LSTM) networks. The accuracy is only 92.72% when only using single-sensor data for identification, while the proposed multiple neural network model could improve the accuracy to being greater than 97.00%. In addition, an optimization method was supplemented to eliminate some misjudgment due to data anomalies, which improved the final accuracy to the level of manual recognition. Finally, the research results solved the difficult problem of identifying the amplitude concentrated enlargement zone and provided the foundation for automatically identifying the drilling depth. vibration signals neural network drilling state identification algorithm drilling depth monitoring-while-drilling method ==== Body pmc1. Introduction Vibration signals are often used in sensor monitoring [1,2,3], defect diagnosis [4,5,6,7] and engineering applications, such as gearboxes [8,9,10], aero-engines [11,12] and wind turbines [13]. Vibration signals in underground coal mining are often used to help the analysis of mining dynamic disasters, stress environments, drilling process and the state of surrounding rocks [14,15,16,17,18,19]. Microseismic (MS) monitoring, aimed at monitoring vibration signals, can detect the dynamic event of the surrounding rock and predict the rock burst disaster. Acoustic emission (AE) technology is widely used in the field of geotechnical engineering [20,21,22]. The AE signal contains spatial information about the complex structural distribution inside the material [23,24] and vast key information about the rock fracture evolution process [25]. The AE tomography can detect early internal damages, faults and abnormal regions with the distribution of velocity field in the drilling process [26,27]. A monitoring-while-drilling (MWD) system can employ the drilling signals to monitor the quality of borehole constructions, obtain the information of surrounding rocks and other useful information during the drilling process [28,29]. MS monitoring has gradually become the most conventional means of coal mine vibration signal analysis and is now widely used in China’s underground coal mines [30,31,32,33]. The mature technology of MS monitoring has solved a series of problems for actual underground coal mining. Similarly, drilling construction is an indispensable process for coal mine production, such as providing support, pressure relief and other required drilling engineering. Pressure relief drilling (PRD) is often used to reduce stress concentrations and avoid dynamic hazard events, such as rock bursts [34,35]; signal analysis during the drilling process can provide guidance for the drilling quality analysis and construction process. In the previous studies, Zhou et al. [36] proposed a hybrid rock recognition approach that combined Gaussian process regression with clustering, and employed MWD data and the adjusted penetration rate to achieve automated rock recognition. Liu et al. [37] analyzed the relationship between the transverse, longitudinal and torsional vibration of the drill rod and the properties of the rock being drilled. Zhang et al. [38] studied the drilling amplitude signals collected by the MS equipment, which can determine the drilling difficulty areas, sticking drilling and vibration events. Pu et al. [39] investigated the performance of ten frequently used machine learning models for MS/blasting event recognition. Faradonbeh et al. [40] discussed the applicability of three data mining techniques along with five conventional criteria to predict the occurrence of rock bursts in a binary condition. The study results of [38] (Figure 1) pointed out that the periodic appearance of amplitude clusters can represent the drilling depth, which was of great significance to the automatic statistics of drilling depth and the supervision of workload. However, there is a lack of a method that can automatically and accurately identify amplitude clusters in the entire process of borehole construction. There are misjudgments caused by human subjective consciousness as only relying on the manual identification of amplitude clusters, which is inefficient and cannot meet the requirements of the efficient and safe operation of the mine. In this study, a deep learning method is used to analyze the drilling amplitude signals collected by MS monitoring equipment. A fusion neural network is obtained based on Deep Neural Network (DNN) [41,42,43,44] and Long Short-Term Memory (LSTM) [45,46,47,48] algorithms, which can automatically distinguish and determine drilling information, such as the amplitude clusters, drilling start point, termination point and drilling duration of each section in an efficient and accurate manner. The proposed rig drilling status identification algorithm can efficiently and accurately identify and analyze drilling operations, such as pressure relief drilling, support drilling in the underground coal mine, and obtain the actual construction length, construction sequence, time spent on each process and other details of the construction operations, as well as additional information, such as drilling difficulty and abnormal vibration information. It has far-reaching significance to ensure the quality and safe operation of underground construction and obtaining the properties of the roadway surrounding rocks. The main contributions are as follows:(1) Divide all data into the training set, validation set and test set. The test set is not involved in the training and tuning of the neural network and is only used as the data for the final model effect evaluation to avoid the problem of information leakage that leads to the fake high identification accuracy of the neural network. The training and validation sets are divided by the stratified K-fold cross-validation method to find the optimal hyperparameters in the model training and tuning, which eliminates the influence of the imbalanced amount of data between the two categories on the model. (2) An efficient, automatic and precise neural network model is proposed to identify the drilling status of drilling rigs by drilling amplitude signals, which can fuse the data from single and multiple sensors, and the identification results from different neural networks. (3) An optimization method is presented, which is similar to “submerge” for two types of recognition anomalies caused by data in drilling state recognition by the neural network identification algorithm. The remainder of this paper is organized as follows. In Section 2, we describe where and how we collected the drilling signal data and introduce basic concepts related to the neural network algorithm that is used in this paper. In Section 3, we demonstrate the composition and division of the dataset of the neural network in this paper, the preprocessing of the data and the structure of the proposed neural network recognition algorithm. In Section 4, we present and analyze the recognition results of the proposed algorithm, perform recognition error analysis, propose an error handling method and show the final recognition results. Finally, conclusions and future works are provided in Section 5. 2. Research Methods 2.1. Data Collection Method MS monitoring equipment was selected to monitor the drilling process of PRD boreholes, which were located in three different underground coal mines in the Shandong Province, China. The PRD boreholes were drilled by a CMS1-6500/75 drill rig (shown in Figure 2a) with a length of 1 m per drill rod, and a new drill rod was added after each rod was drilled. The PRD boreholes were located at the side of the roadway, 1.5 m away from the roadway floor, with a drilling diameter of 150 mm and a design drilling depth of 30 m. The MS monitoring system was arranged on one side of the PRD borehole, and contained three sensors, which are arranged as shown in Figure 2b. The three sensors are at different distances with the same PRD drilling hole, and the amplitudes of the drilling signals collected for the same drilling hole are different. When the drilling position changes, it cannot be guaranteed that a certain sensor always collects the maximum, minimum or middle amplitudes. In order to eliminate the influence of the distance from the borehole, the average value of the vibration amplitude signals collected by the three sensors was calculated, so that the amplitude signals of Sensor #1, Sensor #2 and Sensor #3 would be arranged from the smallest to the largest. 2.2. Neural Network Algorithm For the problem of identifying the drilling status of the drilling rig, the collected drilling signals were learned and trained with the help of the excellent judgment accuracy of the deep neural network. For the identification of the drilling state of the drilling rig, it can be simplified as a binary classification [49]: the signal points in the drilling state as 1 (positive sample) and the signal points in extension of the drill rod, the non-drilling state, as 0 (negative sample). The middle layers of the neural network use a Rectified Linear Unit (ReLU) as the activation function, and the last layer uses a sigmoid activation function to output a probability value in the range of 0 to 1. The ReLU function resets all negative values to zero, while the sigmoid function “compresses” any value to the interval [0, 1], and its output value can be regarded as a probability value; the expressions of the two activation functions are given in Equations (1) and (2). Therefore, the network uses a binary cross-entropy loss function to calculate the loss, as in Equation (3). (1) ReLU(x)={xif x>00if x≤0 (2) S(x)=11+e−x (3) loss=−1N[∑i=1Nyi⋅log(p(yi))+(1−yi)⋅log(1−p(yi))] where N represents the number of samples; yi represents the label value of sample i; and p(yi) represents the predicted probability value of the label value of sample i. The practice of training and testing the model on all datasets is problematic, which can lead to the rapid over-fitting of the model on that dataset. Therefore, we divided the dataset into training set, verification set and test set in order to obtain a generalized model. The model was trained and learned on the training set, and the hyperparameters of the model were adjusted using the performance of the model on the validation set as a feedback signal. However, this causes information leakage when the model parameters are tuned multiple times on the validation set, and the model quickly over-fits on the validation set. So, we created a completely unused dataset, a test set, to evaluate the model, and the best parameters were determined by grid search [50] techniques. Then, the optimal parameters were used to re-train the model on all the training sets, and the effect of the model was finally evaluated on the test set. Depending on the number of data points and the way the validation set is divided, it may result in a large variance in the validation scores, which makes it impossible to evaluate the model reliably. In this case, the best practice is to use the K-fold cross-validation [51] shown in Figure 3. This method divides the available data into K folds, instantiates K identical models, trains each model on K-1 folds and evaluates it on the remaining one. The validation score of the model is equal to the average of the K validation scores. However, some classification problems may also show a large imbalance in the distribution of target classes, for example, there may be several times more negative samples than positive ones. In such cases, stratified sampling is used to ensure that the relative class frequencies are approximately the same in each training and validation fold. Stratified K-fold cross-validation [52] (Figure 4) is a variant of K-fold cross-validation, which returns stratified folds, with each fold containing roughly the same percentage of samples for each target category as the entire collection. 3. Design of Experiment 3.1. Composition of Experimental Data We carried out drilling signal data acquisition in three coal mines (marked as mine A, B and C) in the Shandong Province, China. For mines A and B, the drilling signal data of one borehole was collected in each mine, marked as A1, B1. Additionally, the drilling signal data of five boreholes were collected in mine C, marked as C1~C5, with seven boreholes drilling rig amplitude data in total. In order to train and obtain a generalized neural network model, the amplitude data of one borehole A1 in mine A and two boreholes (C1, C3) in mine C were used as training data. The designed neural network was trained and verified by stratified K-fold cross-validation, and the data of one borehole B1 in B mine and three other holes (C2, C4, C5) in C mine are used as the test dataset to test the identification accuracy of the final model. 3.2. Pre-Processing of Experimental Data The PRD drilling amplitude data from the training and validation sets were sorted, and the vibration signals within the drilling time were filtered according to the actual drilling time. The data points were manually labelled as 0 or 1 according to the time corresponding to the drilling state of the rig recorded during the field construction and the size of the drilling signal amplitude value (1 is the drilling state, 0 is the state of connecting the drill rod). The collected raw vibration signal data are used as raw data, as shown in Figure 5. It can be easily seen from the Figure 5 that the collected vibration signal data contain some points with abnormally large amplitude values, which seriously deviate from the range of other amplitude value distributions; these outliers are randomly present in two different drilling states and the locations of outliers collected by different sensors may be different from each other. If these outliers are retained as inputs to the model, they have a great disturbance and impact on the subsequent training of the model and the accuracy of the final model; thus, it is necessary to remove the outliers from the input data before the model training process to avoid the model learning the wrong information and to ensure that the training and accuracy of the model are not affected by the outliers. Therefore, the 3σ principle [53,54] was used to filter the raw data in order to eliminate the influence of outliers on the model, that is, the (μ − 3σ, μ + 3σ) in each set of datasets is taken as the screening criterion for the outlier data. For the vibration signal data collected by each sensor, the abnormal value points exceeding 3σ are removed, which is shown in Figure 6. The distribution of amplitude cluster and intervals can be seen clearly after removing the outliers, and the purpose of removing outliers and revealing the characteristics of the data was preliminarily achieved. To determine whether the two types of labels of the data are distinguishable in terms of the vibration amplitude index, the vibration signals data were represented according to the label classification as shown in Figure 7. For Sensor #1, the average amplitude of the drilling state is 1.85 and the average amplitude of the connecting state is 0.38. For Sensor #2, the average amplitude of the drilling state is 3.04 and the average amplitude of the connecting state is 0.47. For Sensor #3, the average amplitude of the drilling state is 9.87 and the average amplitude of the connecting state is 3.63. The vibration signals of the two states are well differentiated in terms of amplitude mean and maximum amplitude, and the difference features can be trained and learned by the designed neural network. Since the raw data are a combination of drilling amplitude values from three different boreholes in two different mines, there are some differences between the magnitude of amplitude values in different boreholes. In each individual borehole drilling data, the amplitude values of the two drilling states are still well separable. Therefore, the vibration amplitude can be used as a classification indicator to distinguish between the two drilling states. Since the experimental data were divided into two categories and the number of data contained within the two categories was not equal, to make the model fully learn the characteristics of different types of data and improve its prediction accuracy, the stratified K-fold cross-validation method was used to avoid the model learning the characteristics only from one type of data, while the features of the other type are not sufficient learned. This study used stratified 10-fold stratified cross-validation. The training data were divided into training sets and validation sets in order to avoid information leakage caused by the model being adjusted directly on the test set during the learning process, which means that the entire training data were divided into 10 folds and the proportion of the two categories in each fold was approximately the same as the proportion in the total data set. The training was performed on 9 folds of the data each time, and the remaining 1 fold was used as the validation set to verify the model; the model effect was tested on a separate unused test set after the final model was trained. 3.3. Drilling State Identification Neural Network The data, after the outlier removal and normalization process conducted in the previous section, were used as the input data of the neural network, and the neural network model was established using the LSTM and DNN methods. Three independent LSTM networks were built using single data from each of the three sensors as input data; one LSTM network and one DNN network were built using all the amplitude data collected by all three sensors as the input data. A total of five neural networks were established, and the architecture of the neural network is shown in Figure 8. Each neural network model was trained and validated separately, and the five neural networks jointly judged the drilling status of the rig using the respective vibration amplitudes and all vibration amplitudes collected by different sensors at the same moment. The entire process was constructed so that the amplitude data collected by the three sensors as a whole were input to the LSTM network and DNN network as input data, and the three different single sensor data were input to the LSTM networks #1, #2 and #3. The five sub-neural networks reveal the discrimination results of drilling state of drilling rig. For a certain moment, three drilling amplitude signals of the rig and five judgment results are obtained. Then, the three or more than three same drilling states were taken as the final drilling state result according to the majority rule. The five sub-neural network models were trained and evaluated separately using the data in the training set as input data, and the feedback data (accuracy, Receiver Operating Characteristic and Area Under ROC Curve) obtained on the validation set were used to adjust and optimize the structure and parameters of the neural network (such as epochs, number of layers of deep neural network and number of neurons per layer). The training and adjustment were continued until the judgment performance of each neural network reached a good judgment accuracy rate. The final neural network model structure and parameters were determined after the comparison of the accuracy of model prediction results with different parameters. After determining the final parameters, the training and validation sets were integrated into one training set. A new neural network was re-established according to the optimal neural network structure parameters and the training was restarted to ensure that each model could learn from the entire training set. That is, all the data were initially divided into training sets and verification sets to obtain the final neural network model, which was then applied to the data in the test set to finally evaluate the effect of the model. 4. Analysis and Discussion of the Experimental Results 4.1. Analysis of the Experimental Results The four unused borehole data used as the test data were input into the final trained neural network model; the accuracy of the model is shown in Table 1 and the accuracy of each neural network in the model is shown in Table 2. The trained neural network models have a good identification accuracy, which are all over 97.00% and the average is 97.65%; their accuracy can effectively recognize the drilling state of the drilling signals collected in the field. The accuracy of the identification may not be satisfactory when only using single-sensor data for the identification, which is only about 92.72%, and the accuracy may become worse when encountering a more complex situation. Fusing the information of the recognition results of multiple sensors can effectively improve the identification accuracy of the final model and make the identification accuracy of the recognition model more robust. 4.2. Error Analysis Comparing the identification results of the final model with the ground true, it was found that there are some discriminative abnormal points in the result. Taking part of the data in the Test #1 borehole as an example, and the partial discriminant abnormal point data shown in Table 3, we can observe that the data collected by the sensors corresponding to these distinguishing abnormal points are usually very different from the data of the surrounding points, which can also be seen in other datasets. Therefore, it can be assumed that the appearance of these discriminative anomalies has little to do with the discriminative neural network, but there are anomalies in the collected data. The misjudgment of the identification results can be roughly divided into two categories. The first one is the “1110111” type of signals, that is, continuously or discontinuously sporadic signals in the continuous drilling state (1 state) are judged to be in the connecting state (0 state). In fact, the amplitude values of these points are usually very smaller, always one-half or one-third, than other points around them in a time series, so they can be regarded as anomalies. Combined with the actual situation on site, these points may be the sticking drill on-site. The other is the “0001000” type of signals, that is, sporadic signals mixed in the continuous connecting state (0 state) are judged as drilling state (1 state). Similarly, these points are abnormally different from other nearby points, usually 3 times or more higher than nearby points, and have a very short duration of 1 point with occasional cases lasting 2 points (8 s), so they can also be considered as anomalies. In the actual situation, these points may be the percussion made by the rig operator in order to lengthen the drill rod or faraway blasting, rock burst events or other strong vibration events that are collected by the sensor. In order to eliminate the influence of the two types of anomalies mentioned above on the identification of drilling state, we propose an optimization method similar to “submerge”. The idea is that, when the state of a point is different from the state of the two points around it and the state of those two points is the same, the state of the point is modified to be the same as theirs. In addition, sometimes there are two consecutive points that are abnormal points (00011000, 11100111), but, in the actual drilling construction, the drilling state cannot only last for 8 s and the extension of the drill rod only takes 8 s. So, there is also a need for a separate “submerge” process for such consecutive abnormal points. Based on this fact, we wrote a program to perform the “submerge” process of the 0 state abnormal points for each group of identification results, perform the “submerge” process of the 1 state abnormal points for the obtained results and process the points with consecutive outliers. In this way, we optimized the identification results and further improved the final accuracy of the discriminant. The final identification results after the “submerge” smoothing process are, respectively, shown in Figure 9, Figure 10, Figure 11 and Figure 12. The final identification case results of Test #1 are shown in detail, while the results of the other test groups are shown in abbreviated form. The final identification accuracy is almost the same as that of the manually labeled drilling state. As shown in Figure 9, the blue and green rectangles in each graph are the identification results of the drilling status judged by the neural network algorithm. The length of each rectangle on the time axis is the time consumed by that section of the construction. The length of each drilling state is the length of one drill rod. Therefore, the length of each blue rectangle in the graph shows the time consumed by each drill rod, and thus indirectly indicates the drilling difficulty at that depth. The green rectangle between two adjacent blue rectangles is the non-drilling state, such as drill rod connection. Test #1 is the borehole drilling amplitude data collected in mine C. Figure 9a–c shows the amplitude of the vibration signals collected by each sensor, while Figure 9d shows the amplitude signals of the three sensors fused into one graph. Since the three sensors were installed at different distances from the borehole, from Figure 9, we can see that the amplitude of the vibration signals collected by each sensor at the same time are different, but the overall trend is the same. It can be clearly seen that the drilling state identified by the neural network algorithm matches the area with high amplitude values due to the borehole construction, and accordingly, the connecting state matches the area with low amplitude values. Test #2 is the borehole drilling amplitude data collected in mine B. Unlike Test #1, the source of this dataset, mine B, was not trained in the model. The model only learned the vibration amplitude data collected in mines A and C, which means that the model is completely unaware about the information related to mine B. As the four datasets used as the test set were not used in the model training and tuning process, there is no information leakage problem. This set of vibration signal data, from a completely new mine, has greater significance for the evaluation of model performance. This dataset eliminates the problem of the model having better identification accuracy in other boreholes in the same mine due to the knowledge of the mine’s geological conditions. The performance of the model on this dataset can better reflect the generalization ability of the model. As can be seen in Figure 10, the model has very good identification accuracy on this dataset, which comes from a brand new condition. Test #3 and Test #4 are the other two borehole drilling amplitude data collected in mine C. It is also evident from Figure 11 and Figure 12 that the model still has a good recognition accuracy on these two test sets. By using the above method, the state of the drilled hole, the amplitude clusters, intervals and the starting and ending points of drilling or drill rod connecting can be automatically and efficiently recognized with a high recognition accuracy. The vibration signals of downhole drilling can be identified and monitored continuously and efficiently. It can obtain, in a timely and accurate manner, the information of the whole process of the drilling construction, such as the construction depth of borehole drilling construction, construction time of each section of drill rod and the difficulty of construction at different depths. It can also ensure that the underground PRD boreholes are constructed according to the designed depth and the construction quality is effectively monitored, which is of great significance to ensure mine safety and obtain rock mass information. 5. Conclusions and Future Work 5.1. Conclusions A neural network model for drilling rig drilling status identification that fuses single-sensor and multi-sensor prediction results was proposed in this study. The vibration signals of the drilling status of a same borehole were collected using multiple sensors, and the information of the identification results of single and multiple sensors were fused. The method was tested and verified; the identification accuracy of all four test datasets were over 97.00%, and the final identification accuracy was almost the same as that of the manually labeled drilling state after using the “submerge” optimization method. The results show that this method makes up for the deficiency of large errors (up to 6.32%) in the identification results due to the use of a single-sensor data source, and effectively improves the identification accuracy. The study is of great engineering significance to effectively identify and judge the construction length of underground borehole drilling and monitor the drilling information in the entire process of construction. We innovatively proposed a drilling rig with a drilling status identification neural network algorithm that uses single-sensor and multi-sensor data and fuses multiple sub-neural network identification results. Several LSTM and DNN sub-neural networks were constructed using different drilling amplitude signal data sources. A new optimization method was proposed for the misjudgment caused by data anomalies in the identification results. It is a drilling state identification results optimization method that considers both the amplitude data of the time point and its neighboring points in the time dimension. The main conclusions are as follows:(1) A high-accuracy neural network algorithm for the automatic identification of the drilling status of drilling rigs was proposed. The method uses single-sensor and multi-sensor data from the same borehole as input data and fuses the identification results from different types of sub-neural networks using different inputs, effectively improving the final identification accuracy. The identification accuracy of four test datasets of borehole amplitude data from two different mines were all above 97.00%. (2) An optimization method was proposed to deal with two types of misjudgment in the identification results due to data anomalies, and the optimized identification results are almost the same as the drilling status marked manually according to the actual construction status on-site. 5.2. Future Work The underground environment is complex and there are a large number of noise sources, such as coal cutting by shearer loaders, blasting of heading face and overlying rock breaking. The noise signals are inevitably collected by the amplitude sensors, and are not only meaningless for the judgment of the drilling state of the drilling rig, but also affect the accuracy of model judgment. In addition, dynamic events, such as rock burst and coal and gas outburst, are completely eliminated in this study, which is very meaningful for research. Therefore, the next step of this study is to achieve the accuracy of noise elimination and the discriminative analysis of other dynamic events signals. Author Contributions Conceptualization, Z.W. and W.-L.Z.; methodology, Z.W.; software, Z.W.; validation, W.-L.Z. and C.L.; formal analysis, Z.W. and W.-L.Z.; investigation, C.L.; resources, W.-L.Z.; data curation, Z.W.; writing—original draft preparation, Z.W.; writing—review and editing, W.-L.Z. and C.L. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by National Natural Science Foundation of China, grant number 52004289. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available upon request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Amplitude clusters and intervals in amplitude data during drilling. Figure 2 Drill rig and MS equipment layout. (a) CMS1-6500/75 drill rig; (b) Drill hole and MS equipment layout at roadway side. Figure 3 Schematic diagram of the K-fold cross-validation. Figure 4 Schematic diagram of stratified K-fold cross-validation. Figure 5 Original data of all 3 sensors. Figure 6 Amplitude signal data after removing the outliers. Figure 7 Separability of the two states. Figure 8 The architecture of the proposed identification neural network model. Figure 9 Test#1 drilling state final identification results. (a) Drilling state final identification result and vibration signal of Sensor #1. (b) Drilling state final identification result and vibration signal of Sensor #2. (c) Drilling state final identification result and vibration signal of Sensor #3. (d) Drilling state final identification result and vibration signal of all sensors. Figure 10 Test#2 drilling state final identification results. Figure 11 Test#3 drilling state final identification results. Figure 12 Test#4 drilling state final identification results. sensors-22-03234-t001_Table 1 Table 1 The accuracy of the neural network on the test data. Test Data #1 Test Data #2 Test Data #3 Test Data #4 Recognition accuracy 97.00% 98.47% 97.99% 97.15% sensors-22-03234-t002_Table 2 Table 2 The accuracy of each sub-neural network on the test data. Network Type Test Data #1 Test Data #2 Test Data #3 Test Data #4 LSTM #1 93.72% 92.72% 95.61% 97.72% LSTM #2 95.15% 96.17% 97.37% 96.96% LSTM #3 93.44% 92.15% 94.49% 96.20% LSTM all 96.72% 93.10% 98.25% 96.96% DNN 96.86% 98.47% 98.62% 97.15% sensors-22-03234-t003_Table 3 Table 3 Part of the outlier data points in the Test #1 dataset. Data Sequence Number Sensor #1 Amplitude Sensor #2 Amplitude Sensor #3 Amplitude Drilling State Ground True Drilling State Judged by the Network ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ 17 2.707553 2.619514 6.796628 1 1 18 1.930003 2.793286 5.172647 1 1 19 1.963386 2.451638 5.28292 1 1 20 0.502925 0.59154 1.494293 1 0 21 1.324366 2.157405 4.256246 1 1 22 3.292366 3.701357 7.12655 1 1 23 3.088607 3.210542 7.949529 1 1 ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ 94 0.391242 0.756341 0.875585 0 0 95 0.225544 0.427893 0.178449 0 0 96 0.334536 0.450832 0.215356 0 0 97 1.083765 1.435536 2.665392 0 1 98 0.483574 0.586286 0.426804 0 0 99 0.425458 0.389063 0.18947 0 0 100 0.204848 0.269115 0.353566 0 0 ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Fan X. Liang M. Yeap T. A joint time-invariant wavelet transform and kurtosis approach to the improvement of in-line oil debris sensor capability Smart Mater. Struct. 2009 18 085010 10.1088/0964-1726/18/8/085010 2. Zhao Y. Zhang L. Liao J. Wang W. Liu Q. Tang L. Experimental study of fracture toughness and subcritical crack growth of three rocks under different environments Int. J. Geomech. 2020 20 04020128 10.1061/(ASCE)GM.1943-5622.0001779 3. Wang K. Liu Z. Liu G. Yi L. Yang K. Peng S. Chen M. Vibration Sensor Approaches for the Monitoring of Sand Production in Bohai Bay Shock. Vib. 2015 2015 591780 10.1155/2015/591780 4. Zhao Y. Wang Y. Wang W. Tang L. Liu Q. Cheng G. Modeling of rheological fracture behavior of rock cracks subjected to hydraulic pressure and far field stresses Theor. Appl. Fract. Mech. 2019 101 59 66 10.1016/j.tafmec.2019.01.026 5. Feng K. Jiang Z. He W. Qin Q. Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet Measurement 2011 44 1582 1591 10.1016/j.measurement.2011.06.011 6. Sheen Y.-T. An envelope detection method based on the first-vibration-mode of bearing vibration Measurement 2008 41 797 809 10.1016/j.measurement.2007.11.007 7. Baydar N. Ball A. Detection of Gear Failures Via Vibration and Acoustic Signals Using Wavelet Transform Mech. Syst. Signal Processing 2003 17 787 804 10.1006/mssp.2001.1435 8. Singh A. Parey A. Gearbox fault diagnosis under non-stationary conditions with independent angular re-sampling technique applied to vibration and sound emission signals Appl. Acoust. 2019 144 11 22 10.1016/j.apacoust.2017.04.015 9. Li C. Liang M. Time–frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform Mech. Syst. Signal Processing 2012 26 205 217 10.1016/j.ymssp.2011.07.001 10. Yu X. Feng Z. Liang M. Analytical vibration signal model and signature analysis in resonance region for planetary gearbox fault diagnosis J. Sound Vib. 2021 498 115962 10.1016/j.jsv.2021.115962 11. Fei C.W. Bai G.C. Wavelet correlation feature scale entropy and fuzzy support vector machine approach for aeroengine whole-body vibration fault diagnosis Shock. Vib. 2013 20 341 349 10.1155/2013/403920 12. Wang S. Chen X. Tong C. Zhao Z. Matching Synchrosqueezing Wavelet Transform and Application to Aeroengine Vibration Monitoring IEEE Trans. Instrum. Meas. 2017 66 360 372 10.1109/TIM.2016.2613359 13. Koukoura S. Carroll J. McDonald A. Weiss S. Comparison of wind turbine gearbox vibration analysis algorithms based on feature extraction and classification Iet Renew. Power Gener. 2019 13 2549 2557 10.1049/iet-rpg.2018.5313 14. Chen J. Yue Z.Q. Weak zone characterization using full drilling analysis of rotary-percussive instrumented drilling Int. J. Rock Mech. Min. Sci. 2016 89 227 234 10.1016/j.ijrmms.2016.09.012 15. Zhao Y. Zhang L. Wang W. Liu Q. Tang L. Cheng G. Experimental study on shear behavior and a revised shear strength model for infilled rock joints Int. J. Geomech. 2020 20 04020141 10.1061/(ASCE)GM.1943-5622.0001781 16. Chen J. Yue Z.Q. Ground characterization using breaking-action-based zoning analysis of rotary-percussive instrumented drilling Int. J. Rock Mech. Min. Sci. 2015 75 33 43 10.1016/j.ijrmms.2014.11.008 17. Qin M. Wang K. Pan K. Sun T. Liu Z. Analysis of signal characteristics from rock drilling based on vibration and acoustic sensor approaches Appl. Acoust. 2018 140 275 282 10.1016/j.apacoust.2018.06.003 18. Zhao Y. Zhang C. Wang Y. Lin H. Shear-related roughness classification and strength model of natural rock joint based on fuzzy comprehensive evaluation Int. J. Rock Mech. Min. Sci. 2021 137 104550 10.1016/j.ijrmms.2020.104550 19. Zhang W. Ma N. Ren J. Li C. Peak particle velocity of vibration events in underground coal mine and their caused stress increment Measurement 2021 169 108520 10.1016/j.measurement.2020.108520 20. Cheng T. Zhang Z. Yi Q. Yin B. Yuan H. Denoising method of rock acoustic emission signal based on improved VMD J. Min. Strat. Control. Eng. 2022 4 023011 21. Lan S. Song D. Li Z. Liu Y. Experimental study on acoustic emission characteristics of fault slip process based on damage factor J. Min. Strat. Control. Eng. 2021 3 033024 22. Wu Y. Dong Q. He J. The Effect of Chemical Corrosion on Mechanics and Failure Behaviour of Limestone Containing a Single Kinked Fissure Sensors 2021 21 5641 10.3390/s21165641 34451082 23. Dong L. Tong X. Hu Q. Tao Q. Empty region identification method and experimental verification for the two-dimensional complex structure Int. J. Rock Mech. Min. Sci. 2021 147 104885 10.1016/j.ijrmms.2021.104885 24. Suwansin W. Phasukkit P. Deep Learning-Based Acoustic Emission Scheme for Nondestructive Localization of Cracks in Train Rails under a Load Sensors 2021 21 272 10.3390/s21010272 33401611 25. Dong L. Zhang Y. Sun D. Chen Y. Tang Z. Stage characteristics of acoustic emission and identification of unstable crack state for granite fractures Chin. J. Rock Mech. Eng. 2022 41 120 131 26. Dong L. Tong X. Ma J. Quantitative Investigation of Tomographic Effects in Abnormal Regions of Complex Structures Engineering 2021 7 1011 1022 10.1016/j.eng.2020.06.021 27. Su Y. Dong L. Pei Z. Non-Destructive Testing for Cavity Damages in Automated Machines Based on Acoustic Emission Tomography Sensors 2022 22 2201 10.3390/s22062201 35336369 28. Hatherly P. Leung R. Scheding S. Robinson D. Drill monitoring results reveal geological conditions in blasthole drilling Int. J. Rock Mech. Min. Sci. 2015 78 144 154 10.1016/j.ijrmms.2015.05.006 29. Ghosh R. Schunnesson H. Gustafson A. Monitoring of Drill System Behavior for Water-Powered In-The-Hole (ITH) Drilling Minerals 2017 7 121 10.3390/min7070121 30. Ma K. Wang S.-J. Yuan F.-Z. Peng Y.-L. Jia S.-M. Gong F. Study on Mechanism of Influence of Mining Speed on Roof Movement Based on Microseismic Monitoring Adv. Civ. Eng. 2020 2020 8819824 10.1155/2020/8819824 31. Li D. Zhang J. Rockburst Monitoring in Deep Coalmines with Protective Coal Panels Using Integrated Microseismic and Computed Tomography Methods Shock. Vib. 2020 2020 8831351 10.1155/2020/8831351 32. Zhao Y. Wang C. Bi J. Analysis of fractured rock permeability evolution under unloading conditions by the model of elastoplastic contact between rough surfaces Rock Mech. Rock Eng. 2020 53 5795 5808 10.1007/s00603-020-02224-x 33. Jiang R. Dai F. Liu Y. Li A. A novel method for automatic identification of rock fracture signals in microseismic monitoring Measurement 2021 175 109129 10.1016/j.measurement.2021.109129 34. Zhang W. Li C. Jin J. Qu X. Fan S. Xin C. A new monitoring-while-drilling method of large diameter drilling in underground coal mine and their application Measurement 2021 173 108840 10.1016/j.measurement.2020.108840 35. Zhang C. Tu S. Chen M. Zhang L. Pressure-relief and methane production performance of pressure relief gas extraction technology in the longwall mining J. Geophys. Eng. 2017 14 77 89 10.1088/1742-2140/14/1/77 36. Zhou H. Hatherly P. Monteiro S.T. Ramos F. Oppolzer F. Nettleton E. Scheding S. Automatic rock recognition from drilling performance data Proceedings of the 2012 IEEE International Conference on Robotics and Automation Saint Paul, MN, USA 14–18 May 2012 3407 3412 37. Liu S. Fu M. Jia H. Li W. Luo Y. Numerical simulation and analysis of drill rods vibration during roof bolt hole drilling in underground mines Int. J. Min. Sci. Technol. 2018 28 877 884 10.1016/j.ijmst.2018.05.018 38. Zhang W. Li C. Ren J. Wu Z. Measurement and application of vibration signals during pressure relief hole construction using microseismic system Measurement 2020 158 107696 10.1016/j.measurement.2020.107696 39. Pu Y. Apel D.B. Hall R. Using machine learning approach for microseismic events recognition in underground excavations: Comparison of ten frequently-used models Eng. Geol. 2020 268 105519 10.1016/j.enggeo.2020.105519 40. Shirani Faradonbeh R. Taheri A. Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques Eng. Comput. 2018 35 659 675 10.1007/s00366-018-0624-4 41. Feng S. Zhou H.Y. Dong H.B. Using deep neural network with small dataset to predict material defects Mater. Des. 2019 162 300 310 10.1016/j.matdes.2018.11.060 42. Yang Y.L. Fu P.Y. He Y.C. Bearing Fault Automatic Classification Based on Deep Learning Ieee Access 2018 6 71540 71554 10.1109/ACCESS.2018.2880990 43. Li Y. Cheng G. Liu C. Chen X.H. Study on planetary gear fault diagnosis based on variational mode decomposition and deep neural networks Measurement 2018 130 94 104 10.1016/j.measurement.2018.08.002 44. Zhang R. Peng Z. Wu L.F. Yao B.B. Guan Y. Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence Sensors 2017 17 549 10.3390/s17030549 28282936 45. Yu Y. Si X.S. Hu C.H. Zhang J.X. A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures Neural Comput. 2019 31 1235 1270 10.1162/neco_a_01199 31113301 46. Shen S.L. Njock P.G.A. Zhou A.N. Lyu H.M. Dynamic prediction of jet grouted column diameter in soft soil using Bi-LSTM deep learning Acta Geotech. 2021 16 303 315 10.1007/s11440-020-01005-8 47. Yuan X.H. Chen C. Jiang M. Yuan Y.B. Prediction interval of wind power using parameter optimized Beta distribution based LSTM model Appl. Soft Comput. 2019 82 105550 10.1016/j.asoc.2019.105550 48. Yang Y. Zeng Q.L. Yin G.J. Wan L.R. Vibration Test of Single Coal Gangue Particle Directly Impacting the Metal Plate and the Study of Coal Gangue Recognition Based on Vibration Signal and Stacking Integration Ieee Access 2019 7 106783 106804 10.1109/ACCESS.2019.2932118 49. Luo J.-S. Lo D.C.-T. Binary Malware Image Classification Using Machine Learning with Local Binary Pattern Proceedings of the 2017 IEEE International Conference on Big Data (Big Data) Boston, MA, USA 11–14 December 2017 IEEE Piscataway, NJ, USA 2017 4664 4667 50. Huang Q. Mao J. Liu Y. An Improved Grid Search Algorithm of SVR Parameters Optimization Proceedings of the 2012 IEEE 14th International Conference on Communication Technology Chengdu, China 9–11 October 2012 IEEE Piscataway, NJ, USA 2012 1022 1026 51. Wong T.-T. Yeh P.-Y. Reliable accuracy estimates from k-fold cross validation IEEE Trans. Knowl. Data Eng. 2019 32 1586 1594 10.1109/TKDE.2019.2912815 52. Al-Badarneh A. Al-Shawakfa E. Bani-Ismail B. Al-Rababah K. Shatnawi S. The impact of indexing approaches on Arabic text classification J. Inf. Sci. 2017 43 159 173 10.1177/0165551515625030 53. Li L. Wen Z. Wang Z. Outlier detection and correction during the process of groundwater lever monitoring base on pauta criterion with self-learning and smooth processing Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems Springer Berlin/Heidelberg, Germany 2016 497 503 54. Shen C. Bao X.J. Tan J.B. Liu S.T. Liu Z.J. Two noise-robust axial scanning multi-image phase retrieval algorithms based on Pauta criterion and smoothness constraint Opt. Express 2017 25 16235 16249 10.1364/OE.25.016235 28789131

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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092775 molecules-27-02775 Review 1H-Pyrazolo[3,4-b]quinolines: Synthesis and Properties over 100 Years of Research Danel Andrzej 1* Gondek Ewa 1 Kucharek Mateusz 2 Szlachcic Paweł 2 https://orcid.org/0000-0003-2710-7513 Gut Arkadiusz 3 Silva Vera L. M. Academic Editor Silva Artur M. S. Academic Editor 1 Faculty of Materials Engineering and Physics, Cracow University of Technology, Podchorążych Str. 1, 30-084 Krakow, Poland; egondek@pk.edu.pl 2 Faculty of Food Technology, University of Agriculture in Krakow, Balicka Str. 122, 30-149 Krakow, Poland; mateusz.kucharek@urk.edu.pl (M.K.); pawel.szlachcic@urk.edu.pl (P.S.) 3 Faculty of Chemistry, Jagiellonian University, Gronostajowa Str. 2, 30-387 Krakow, Poland; arkadiusz.gut@uj.edu.pl * Correspondence: rrdanela@cyf-kr.edu.pl 26 4 2022 5 2022 27 9 277501 3 2022 22 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This paper summarises a little over 100 years of research on the synthesis and the photophysical and biological properties of 1H-pyrazolo[3,4-b]quinolines that was published in the years 1911–2021. The main methods of synthesis are described, which include Friedländer condensation, synthesis from anthranilic acid derivatives, multicomponent synthesis and others. The use of this class of compounds as potential fluorescent sensors and biologically active compounds is shown. This review intends to summarize the abovementioned aspects of 1H-pyrazolo[3,4-b]quinoline chemistry. Some of the results that are presented in this publication come from the laboratories of the authors of this review. biological properties fluorescence fluorescent sensors Friedländer condensation multicomponent reaction 1H-pyrazolo[3,4-b]quinolines ==== Body pmc1. Introduction 1H-Pyrazolo[3,4-b]quinolines are three-membered azaheterocyclic systems that are composed of a pyrazole-and-quinoline fragment (Figure 1). The parent structure can be modified with a number of substituents that have a great influence on the physical, photophysical and biological properties. The first synthesis of this class of compounds was described in 1911 by Michaelis; however, the author incorrectly presented their structures. He concluded that the obtained compounds were a benzylidene derivative of 5-N-phenylamino-3-methyl-1-phenylpyrazole. This structure is marked in red in Figure 2 [1]. His results were later verified by other researchers. For this reason, the discoverer of this class of compounds should be considered as Niementowski and colleagues, who in their work presented the first structure of 1H-pyrazolo[3,4-b]quinoline in 1928 [2]. In the interwar period, there were some works by Koćwa, who also synthesised this system [3,4]. The remaining works on the synthesis of these compounds were published after 1945. Michaelis noticed that the compounds that were obtained by him were characterised by intense fluorescence, and, indeed, a significant part of pyrazolo[3,4-b]quinolines exhibits emission properties, both in solutions and even in a solid state. These properties have been used in the synthesis of fluorescent sensors for various cations [5]. In addition, pyrazolo[3,4-b]quinolines were tested as emission materials in organic electroluminescent cells (OLEDs). The summary of this research was published some time ago in our review article [6]. It is also necessary to mention the biological properties of this class of compounds, which were largely studied in the first stage of 1H-pyrazolo[3,4-b]quinoline development, and it is now observed that more and more research groups are interested in these heterocycles. This aspect will be discussed later in this review (Figure 2). 2. The Main Synthesis Method of 1H-Pyrazolo[3,4-b]quinoline The following scheme for the synthesis of pyrazoloquinolines is based on the methodology for the synthesis of the quinoline system, which is described in detail in one of the Houben–Weil volumes on quinoline synthesis [7] (Figure 3). The first and oldest method of pyrazoloquinolines synthesis is a two-component reaction (C21), in which the Friedländer condensation of anthranilaldehyde, o-aminoacetophenones and o-aminobenzophenones, and the appropriate pyrazolones, are used (Figure 3; Path 1). As a result of the reaction, a bond is formed between the N9 nitrogen and the C9a carbon, and between the C3a and C4 carbon atoms. The reaction is limited by the availability of o-aminocarbonyl compounds. The synthesis of the Niementowski and Pfitzinger quinolines can also be used here, although to a lesser extent than in the first case. The second path is essentially the reverse of the first methodology, where the o-aminocarbonyl system is linked to the pyrazole moiety. In a two-component reaction (C22), a bond is formed between the C8a carbon and the N9 nitrogen, and between the carbons C4a and C4 (Figure 3; Path 2). The two-component reaction (C23) in which one of the reactants is an aromatic amine and the other is a pyrazole derivative is one of the most valuable syntheses of the pyrazoloquinoline system. The entire spectrum of substituted anilines is commercially available, while the synthesis of pyrazole derivatives that contain an aldehyde or ketone group is not difficult. In this reaction, a bond is formed between C4 and C4a carbon, and between nitrogen N9 and C9a carbon (Figure 3; Path 3). The reaction of 5-aminopyrazoles and the o-halogen derivatives of aromatic carboxylic acids has some importance in the synthesis of pyrazoloquinolines that are substituted at the 4-chlorine/bromine or hydroxyl position. In this two-component reaction (C24), a bond is formed between the nitrogen atom N9 and the carbon C8a, and between the carbon carbon and the carbon C3a (Figure 3; Path 4). After studying the literature on the synthesis of pyrazoloquinolines, it seems that Path 5 is one of the most exploited procedures for synthesising this system. It uses quinoline derivatives (aldehydes, nitriles) and the appropriate hydrazines. The resulting derivatives are later further modified, and most often in terms of the synthesis of biologically active compounds. In this two-component reaction (C25), a bond is formed between the C9a carbon and the N1 nitrogen, and between the N2 nitrogen and the C3 carbon (Figure 3; Path 5). Another synthetic procedure of pyrazoloquinolines is a two-component reaction (C26a) and a one-component reaction (C16b). Both routes are based on 5-N-arylpyrazole derivatives. In the first case, cyclization takes place with the use of an aromatic aldehyde, and, in the second case, an ester group is used, which is attached to the pyrazole ring in position 4. In the first situation, bonds between the C4 and C4a/C3a carbons are formed. In the second case, bonds between C4 and C4a are formed. The ring-closure is also performed by using the Vilsmeier–Haack formylation reaction (Figure 3; Path 6). The use of a one-component system (C17), where the reductive cyclization of the o-nitrobenzylidene system is used, is practically irrelevant when it comes to the synthesis of pyrazoloquinolines. A bond is formed between the nitrogen N9 and the C9a carbon in the pyrazole ring (Figure 3; Path 7). Finally, we should mention multicomponent reactions, which are very popular in the synthesis of heterocyclic systems. This method is suitable for both the synthesis of the fully aromatic pyrazoloquinoline system, or with the hydrogenated moiety in either the middle ring or the carbocyclic system. The N9-nitrogen-contributing system may be an amine pyrazole or an aromatic amine (C38a or C38b). The C4-bound fragment is most often derived from an aromatic or an aliphatic aldehyde (Figure 3; Path 8). 2.1. The Friedländer Synthesis Based on o-Aminoaldehydes, o-Aminoacetophenones and o-Aminobenzophenones The Friedländer condensation of o-aminocarbonyl compounds 1 (R3 = H, alkyl, aryl) with carbonyl systems that contain the active α-methylene group 2 is one of the most important methods of quinoline 3 synthesis [8,9,10,11,12,13] (Figure 4) (Scheme 1). The reaction can be catalysed by acids and bases, but it also takes place in an inert environment. We start the description of synthetic PQ methods with the oldest results that were published by Niementowski and colleagues, who used the Friedländer condensation of anthranilaldehyde 4 and 5-methyl-2-phenyl-4H-pyrazol-3-one 5 (Scheme 2) [2]. As a result, three products were obtained: phenylhydrazone of 3-acetylquinolone 6; 3-methyl-1-phenyl-1H-pyrazolo[4,3-c]quinoline 7; and 3-(2-quinolyl)-quinolin-2-ol 8. The heating of phenylhydrazone 6 in the boiling of C6H5NO2 led to the formation of 1-methyl-3-phenyl-1H-pyrazolo[3,4-b]quinoline 9. Thus, this compound can be described as the first synthesised pyrazoloquinoline. As for further research on the use of the Friedländer condensation for the synthesis of PQs, a mention should be made of the work of Tomasik et al., which describes a complete synthesis that uses nine pyrazolones 10 substituted with the methyl, phenyl and hydrogen groups with o-aminobenzaldehyde 4 (Scheme 3) [14]. The syntheses were conducted within 150–260 °C in melt. The reaction mixtures were separated by column chromatography or crystallisation. PQs 11 were obtained in the cases of five pyrazolones (10: R1,2 = Ph; R1,2 = Me; R1 = Me/R2 = Ph; R1 = H/R2 = Me, Ph). In the case of 1,3-dimethylpyrazol-5-one (10: R1,2 = Me), it was possible to isolate the intermediate product, which was the 4-benzylidene derivative, which suggests that the first step in some of these reactions is the reaction between the aldehyde group and the α-methylene group of the pyrazolone. In the next step, the pyrazolone ring is opened and compound 12 is formed, which then cyclizes to form pyrazoloquinoline 11. In other cases, 3-acylquinoline alkyl/arylhydrazones 12 or other products were obtained, such as 13 (ca. 100%) in the case when pyrazolone 10 (R1 = Ph, R2 = H) is used. Paczkowski et al. investigated pyrazolo[3,4-b]quinolines as potential photoinitiators for free radical polymerisation. They prepared these compounds via Friedländer condensation that was conducted in boiling glacial acetic acid [15]. Danel, as an o-aminocarbonyl component 1, applied o-aminoacetophenone, o-aminobenzophenone and 5-chloro-2-aminobenzophenone, and a complete set of pyrazolones substituted with methyl, phenyl and hydrogen 10 (R1,2 = H, Me, Ph) (Scheme 3) [16]. The reaction was carried out in boiling ethylene glycol. Contrary to the two previously mentioned syntheses, in this case, all pyrazoloquinolines 14 were obtained in a single stage, although with different yields (20–85%). Sabitha et al. applied a microwave-assisted condenstion of 1 (R3 = H, Me; R4 = H) and 10 (R1 = Ph, R2 = Me) that was supported on clay, which led to 1H-pyrazolo[3,4-b]quinolines [17]. As mentioned in the introduction, a significant part of pyrazoloquinolines exhibit intense fluorescence, which makes them good luminophores for the fabrication of electroluminescent devices. However, high luminescence efficiency is only one of the many conditions that must be met by candidates for luminophores. The others are a high thermal stability and a high glass-transition temperature. This can be achieved by using spiro compounds, which are just such systems [18]. The introduction of the 9,9’-spirobifluorene system increases the stiffness of the molecule and prevents packing and the intermolecular interactions in the film (after vacuum sputtering on the ITO anode), which hinders crystallisation and increases the Tg value. The tetrahedral nature of the carbon at the centre of the spiro of the system that links the two coupled systems serves as a breaking fragment for this coupling so that the optical and electronic properties of the system are preserved [19]. Tao et al. synthesised two spiro PQs 16 systems by using the Friedländer condensation of o-aminobenzophenones on the basis of spirobifluorene 15 (Scheme 4) [20]. 2.2. The Friedländer Synthesis Based on Pyrazole Derivatives The previously mentioned Friedländer condensation procedures included either the appropriate aldehyde or ketone attached to a carbocyclic ring. One drawback of this synthesis is that the work of obtaining o-aminocarbonyl systems 1 is quite troublesome, and aldehydes are often not very stable reagents [21]. The reverse approach is also possible, where pyrazole o-aminoaldehyde 18 is used (Figure 5) (Scheme 5 and Scheme 6). Breitmaier and Häuvel prepared pyrazole aldehyde 18 by the formylation of 5-amino-3-metyl-1-phenylpyrazole 17. This aldehyde 18 was condensed with cyclohexanone in glacial acetic acid, which yielded 5,6,7,8-tetrahydro-1H-pyrazolo[3,4-b]quinoline 19 (Scheme 5) [22]. Instead of cyclohexanone, other cyclic ketones can be applied [23]. Higashino et al. prepared pyrazoloquinoline 22 by using aldehyde 21 that was prepared from 1H-pyrazolo [3,4-d]pyrimidine salts 20 and reactive carbonyl compounds, such as cyclohexanone/cyclopentanone with ethoxide ion as a catalyst (Scheme 6) [6]. The authors propose a number of structures (20a–d) that can form as intermediates, but they have not isolated any of them. Aldehyde 21 can also be prepared by reducing 5-amino-1-methyl(phenyl)-1H-pyrazole-4-carbonitrile with Raney-nickel alloy and formic acid [24]. 2.3. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on Anthranilic Acid and Anthranilic Acid Derivatives Path 1: C21: C4-C3a; N9-C9a (Figure 4) Another classic method of synthesising the quinoline 3 is the Niementowski reaction, in which anthranilic acid 23 and ketones 2 (or aldehydes) are used. As a result, 4-hydroxyquinolines 24 are formed (Scheme 7) [25]. The first attempt to synthesise pyrazoloquinoline by using Niementowski’s synthesis was made by Ghosh in 1937 through the reaction of anthranilic acid 23 and pyrazolone 5 in the presence of anhydrous CH3COONa. The product of the reaction was to be 4-hydroxy-3-methyl-1-phenyl-1H-pyrazolo[3,4-b]quinoline 25 (Scheme 8) [26]. The reaction was re-examined by Tomasik and co-workers, and it turned out that compound 25 does not arise under these conditions. In the reaction mixture, only traces of two 1H-pyrazolo[3,4-b]quinolines were found: 1-phenyl-3-methyl-1H-pyrazolo[3,4-b]quinoline (14; R1 = Ph, R2 = Me, R3,4 = H) and 1-phenyl-3,4-methyl-1H-pyrazolo[3,4-b]quinoline (14; R1 = Ph, R2,3 = Me, R4 = H); however, both of them were formed as byproducts. 4-Hydroxy derivative 25 was not formed in this reaction. To prove it, the compound was obtained by another synthetic method, and it was compared to the obtained products by using TLC (Scheme 9); it was not detected in the reaction mixture, according to the Gosh procedure [27,28]. After studying a large number of publications on the synthesis of the compounds that are the subject of this review, it seems that, so far, it has not been possible to obtain pyrazoloquinolines by the direct reaction of anthranilic acid and pyrazolones. On the other hand, anthranilic acid 23 and its derivatives, in turn, are a valuable substrate for the indirect synthesis of pyrazoloquinolines 29 (Scheme 9). Anthranilic acid 23 is reacted with diketene and acetic anhydride, which yields 2-acetonyl-4H-3,1-benzoxazin-4-one 26, which is easily separated from a reaction mixture by filtration. In the next step, 26 is converted to the pyrazole derivative 28 by reaction with the appropriate hydrazine. There is no need to isolate the intermediate 27. The final step in this reaction sequence is heating 28 in polyphosphoric acid (PPA) or phosphorus oxychloride (POCl3), depending on whether we want to obtain the 4-hydroxy derivative or the compound that contains the chlorine atom in the 4 position (29: R2 = OH or R2 = Cl). This reaction cycle was used by Stein et al. and by Crenshaw et al. to prepare 4-hydroxy and 4-chloro derivatives (29: R2 = OH or Cl), which were then used to synthesize a whole range of compounds with biological activity, which will be discussed later in this review [29,30]. The 4-chloro derivatives 29 (R2 = Cl) were then reacted with phenols, thiophenols and amines, which yielded phenoxy 29a, thiophenoxy 29b and amine-substituted 29c derivatives. These compounds showed antimalarial, antibacterial or interferon-inducing effects (Scheme 10). In the previous reaction, acetic anhydride was the reagent in one of several steps where anthranilic acid played an important role. On the other hand, Kim used it to cyclise N-(2-hydroxyphenyl)anthranilic acid 30, which resulted in two derivatives: 31 and a very small amount of 32 (1.7% yield). The reaction of 32 with hydrazine hydrate yielded a derivative of 1,9-dihydro-3-methyl-4H-pyrazolo[3,4-b]quinoline-4-one 33 (Scheme 11) [31]. In concluding the discussion of the use of anthranilic acid derivatives, one could also mention the publication of Gal et al., which concerns the transformation of the modified hydrazides of acid 34. Different products were formed, depending on the reaction conditions (e.g., 35). When the reaction was run in the presence of sodium ethoxide, the product was pyrazolo[3,4-b]quinoline 36 (Scheme 12) [32]. Contrary to the reaction that is shown in Scheme 10, the last two reactions (Scheme 11 and Scheme 12) have no preparative significance. 2.4. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on 4-amino-3-carboxypyrazole Derivatives Path 2: C2,2: C4-C4a; N9-C8a (Figure 5) As in the case of the Friedländer condensation, in this case as well, the derivatives of pyrazoles, such as 5-amino-1H-pyrazole-4-carboxylic acid derivatives 37, can be used. Pedersen obtained 4-N-phenyl-1H-pyrazolo[3,4-b]quinoline 40 by reacting pyrazole derivative 37, cyclohexanone 38 and aniline 39 in the presence of phosphorus pentoxide and N,N-dimethyl-N-cyclohexylamine. This reaction looks similar to a multicomponent one, but all of the atoms that make up the backbone matrix come only from 37 and 38. The next step was to oxidise 5,6,7,8-tetrahydro-1H-pyrazolo[3,4-b]quinolin-4-amine 40 to a fully aromatic 41 with 9,10-phenantrenoquinone 40a (Scheme 13) [33,34]. One of the research groups, which was looking for new drugs for the treatment of Alzheimer’s disease, prepared a series of 5,6,7,8-tetrahydropyrazolo[3,4-b]quinoline derivatives, such as 45 and 46, which were then transformed into other systems (e.g., 47) [35]. Aminopyrazoles 42 were prepared from the appropriate benzylhydrazines and ethoxymethylenemalononitrile (42: R2 = CN) or ethyl ethoxymethylenecyanoacetate (42: R2 = COOEt). In the next turn, they were reacted with 1,3-cyclohexanedione 43 in the presence of p-toluenesulfonic acid (p-TSA). As a result, enamino ketones 44 were formed. In the case of the enemino ketone 44, where R2 was a COOEt substituent, the compound was hydrolysed to produce a derivative with the COOH carboxyl group (44: R2 = COOH). Next, cyclisation was performed in the presence of polyphosphoric esters (PPE) afforded 45. The use of potassium carbonate and copper(I) chloride in the case of 44 (R2 = CN) promotes the formation of 46, respectively (Scheme 14). Campbell and Firor prepared pyrazolo[3,4-b]quinolines 46 by cadmium-chloride- or copper-acetate-promoted cyclisations of pyrazolo enaminones 44 (R2 = CN, R1 = alkyl) [36]. Instead of toxic cadmium chloride, zinc chloride can also be used [37]. The system with the carbocyclic ring without any functional group can be prepared by starting from cyclohexanone 38 and 4-amino-1-methyl-pyrazole-2,3-dicarbonitrile 48 (Scheme 15) [38]. The resulting 2H-pyrazolo[3,4-b]quinoline-3-carbonitriles 49 was subjected to further transformations in order to find new pharmacologically active compounds. 2.5. The Pfitzinger Synthesis of 1H-pyrazolo[3,4-b]quinolines Path 1: C21: C4-C3a; N9-C9a (Figure 4) One of the classic named chemical reactions that leads to the quinoline system is the Pfitzinger synthesis [39,40]. It uses isatin or its derivatives 50, which are easier to obtain than o-aminobenzaldehydes. The reaction is carried out in a basic environment, at which point the opening of the heterocyclic ring takes place to form a keto-acid 51, which is then condensed with aldehydes/ketones 2. Additionally, the final product, 52, can be decarboxylated (Scheme 16). The use of isatin 50 for the synthesis of pyrazolo[3,4-b]quinolines, where this system is built into the backbone, is very limited. One of the reactions is the synthesis that is reported by Fabrini [41]. A reaction between isatine 50 and 1,2-diphenylpyrazolidine-3,5-dione 53 afforded 1H-pyrazolo[3,4-b]quinolin-3-one-4-carboxylic acid 54. In a similar fashion, Seshadri combined isatin 50 and 1,3-disubstituted pyrazolin-5-ones 10 under basic conditions and obtained 4-carboxylic acids 55, and with nitriles 56 after subsequent reactions of 55 with SOCl2 and P2O5 (Scheme 17) [42]. Recently, a few studies have appeared on multicomponent pyrazoloquinolines syntheses where isatins and their derivatives are used. The end product is the spiro-type systems, where isatin brings C-4 carbon to the overall structure. These reactions will be discussed in the final section on the synthesis of this class of compounds. 2.6. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on 5-chloro-4-aroyl/formylpyrazoles and 4-benzylidene-1,3-disubstituted-pyrazol-5-ones Another method of pyrazoloquinolines synthesis is the use of aromatic amines and 4 substituted pyrazole derivatives such as aldehydes, ketones or benzylidene ones (Figure 6). In 1963, Brack published a work on the synthesis of pyrazoloquinolines that was based on the reactions of aromatic amines 39 and 5-chloro-4-formylpyrazoles 58 [43,44]. The latter compounds were obtained by the formylation of the appropriate 5-chloropyrazoles 57 [45]. They can also be obtained in one step in the Vilsmeier–Haack reaction by treating the pyrazolones 10 with a DMF / POCl3 mixture [46]. The original Brack’s reaction was carried out in melt within 110–150 °C (Scheme 18). Two possible schemes for this reaction have been found in the literature. One was proposed by Brack (Scheme 19). The reaction starts from the formation of Schiff base 58a from aniline 39 and aldehyde 58. In the next steps, several rearrangements take place with the formation of the final pyrazoloquinoline 59. Another mechanism was proposed a few years ago that consists of the nucleophilic substitution of the chlorine atom in pyrazole 58 by an amino group in 39 with subsequent ring formation, and the elimination of the water molecule and hydrogen cation, which leads to the aromatisation of the system (intermediates 60-61b) (Scheme 20) [47]. It seems, however, that the experimental data support the former; therefore, it was possible to isolate the intermediate product, which was Schiff’s base 58a, which was formed from pyrazole aldehyde 58 and substituted aniline 39. The authors of the later paper were not able to isolate amine derivative 60. In the original work of Brack, the author limited himself mainly to three 5-chloro-4-formylpyrazole aldehydes (58; R1 = Me, R2 = Ph; R1 = Ph, R2 = Me; R1 = tetrahydro-1,1-dioxo-3-thienyl, R2 = Me) and a few aromatic amines. However, this reaction has many more possibilities, as is shown in several later works by other authors [48]. The use of 5-chloro-4-aroylpyrazoles 64 is an extension of the scope of two-component reactions with aromatic amines R4C6H4NH2 and pyrazole systems with aldehyde function 58 [49] (Scheme 21). Pyrazole derivatives 64 can be synthesised either by the acylation of 5-chloropyrazoles with aromatic acid chlorides 62 and aluminum chloride, or by reacting pyrazolones 10 and acid chlorides 62, followed by chlorination with phosphorus oxychloride [50] (Scheme 21). In contrast to the reaction with aldehydes 58, this reaction required much more severe conditions and it lasted from 2 to 3 h at 220 °C. In one case, the authors isolated an intermediate product, which was the product of the nucleophilic amine substitution of the aromatic chlorine atom at the 5 position of the pyrazole ring. This proves a different mechanism than in the case of the original Brack reaction with pyrazole aldehyde 58 (Scheme 19), and it would, in a way, confirm the mechanism that was proposed for this reaction by Wan et al. (Scheme 20) [50]. Gonzales and El Guero probably describe the only reaction where the 4 acetyl derivatives of chloropyrazole 66 and phenylhydrazine 67 were used for the synthesis of pyrazoloquinoline 69. Depending on the reaction conditions, either the corresponding phenylhydrazone 68 or pyrazoloquinoline 69 are obtained. In the latter case, the authors suggest that phenylhydrazine decomposes under the influence of high temperatures, and the resulting aniline reacts with the chlorine atom with subsequent cyclisation to pyrazoloquinoline [51] (Scheme 22). Crenshaw et al. synthesised 10H-pyrido[2,3-h]pyrazolo[3,4-b]quinoline 73 by starting from 5-aminoquinoline 70 and 5-chloro-1,3-dimethylpyrazolo-4-carboxylic acid 71 [52] (Scheme 23). The purpose of this reaction was to confirm the structure of product 73 that was unexpectedly formed by the ring closure of the derivative 28 (R1 = Me, R = 4-NO2), instead of the expected 4-chloro-7-nitro-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline 29 (R1 = Me, R2 = Cl, R = 7-NO2) (Scheme 9). Regardless of the analysis of the structure of compound 73 by using the 1H NMR spectrum, the authors synthesised it by reactions of aminoquinoline 70 and pyrazole acid 71 in the presence of sodium hydride, and they then cyclised the intermediate 72 with POCl3. Tomasik et al. report a new method toward 1H-pyrazolo[3,4-b]quinolines that uses anilines 39 and benzylidene derivatives 74 (Scheme 24). This reaction produces derivatives that are substituted with a phenyl group (or a substituted phenyl group) in position 4 of the parent backbone 65. As a side product, compound 75 was isolated. It is an excellent alternative to Friedländer condensation, where 2-aminobenzophenones 1 (R3 = Ph) are used (Scheme 3) [1,53]. While searching for the literature on the synthesis of pyrazoloquinolines, we came across a work where a whole series of syntheses of various pyrazole derivatives with potential biological effects were described [54]. Among them was the synthesis that uses the benzylidene derivative 74 (R1 = Ph, R2 = Me, R3 = p-OMe) and 1,4-phenylenediamine 39 (R4 = p-NH2) (Scheme 24). The authors took into account the possibility of the formation of a condensed 76 system, but they did not find it in the reaction products. They only describe that they received compound 77, which was supposed to be a pyrazoloquinoline and a side product 78. However, they did not provide evidence of this in the form of 1H NMR and 13C NMR spectra for both of them. The obtained substance (77) was white, which is in contradiction to our research to date. We have obtained a whole range of variously substituted 1,4-diphenyl-3-methyl-1H-pyrazoloquinolines, which are always yellow crystalline substances, and are, in addition, also strongly fluorescing, which the authors of the publication did not mention. Thus, it seems to us that they failed to obtain 77. 2.7. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on Aminopyrazoles The procedure that was developed by Brack is an extremely effective tool for the synthesis of pyrazoloquinolines. There is also the possibility of using substituted o-halogenobenzoic aldehydes and aminopyrazoles (Figure 7). Szlachcic et al. have published a very extensive work on the use of variously substituted o-halogeno benzaldehydes 79 for the synthesis of pyrazoloquinolines 80 [55] (Scheme 25). The authors focused on regioselective reactions, which would allow the preparation of mono- and disubstituted pyrazoloquinoline halogen derivatives, which could be used later for further reactions (e.g., nucleophilic substitution with aliphatic or aromatic amines), and which could be used, for example, as luminophores for the construction of electroluminescent cells. In the case of monosubstituted aldehydes 79 (R3,4 = H, X = F, Cl, Br, I), it has been observed that, besides pyrazoloquinoline 80, bis-pyrazolo[3,4-b;3′,4′-e]pyridine 81 is also formed; however, in the case of o-fluorobenzaldehyde, pyrazoloquinoline was the final product. The opposite tendency was observed for o-iodobenzaldehyde 79 (R3,4 = H, X = I). Pentafluorobenzaldehyde yielded only pyrazoloquinoline 80. As part of the work, the influence of the base on the course of the reaction was also investigated, and it turned out that bases such as DABCO or quinoline favored the formation of 80 but not of 81.The influence of the substituents in the aminopyrazole 17 was also of some importance, and so the system with the phenyl group in position 3 (17; R2 = Ph) favored the formation of PQ, while the methyl group contributed to the formation of more 81. Dehaen et al. investigated the reaction pentafluorobenzaldehyde and 5-chloro-4-formylpyrazoles 17 with 5-amino-1,2-azoles. Depending on the reaction conditions, the positions of the halogen atom in relation to the carbonyl group pyrazolo[3,4-b]quinolines 80, bis-pyrazolo[3,4-b; 4′,3′-e]pyridines 81 and isoxazolo[5,4-b]quinolines were formed [56]. Another reaction route is the use of o-halogen-substituted benzoic acids 82 and 1,3-disubstituted 5-aminopyrazoles 17. As a result of the Ullmann-type reaction that is catalysed by copper, an intermediate 83 is formed. In the next step, it can be transformed into 84 by heating with POCl3 (Scheme 26). This reaction was used, inter alia, by Siminoff and other researchers for the synthesis of 84 from anthranilic acid 23 and diketene [34,57,58] (Scheme 9). Boruah et al. employed a palladium catalysed reaction of β-bromovinyl aldehyde 85 with 86, which yielded pyrazolo[3,4-b]quinoline 87 and Shiff base 88 (Scheme 27) [59]. The ratio of the products that were obtained depended on the conditions under which the reaction was carried out. Thus, during heating at 120 °C for 24 h, the Schiff’s base 88 dominated in the reaction mixture, while the reaction that was carried out in the microwave field, without a solvent, for 15 min, favored the formation of pyrazoloquinoline 87. As a catalyst, 2.5 mol% palladium acetate has been proven to be the best. At the end of the description of the use of the o-halogen derivatives of acids, esters and aldehydes, we want to mention the use of a benzyl alcohol derivative that has been cyclised to pyrazoloquinoline. In 1974, Horace de Wald synthesised a series of pyrazoloquinolines 93 as potential antidepressants [60]. As a starting material, he applied the methyl ester of 2-chlorobenzoic acid 89. The Ullmann reaction with 1,3-dimethyl-5-amino pyrazole 17 afforded the formation of 90. This compound was reacted with Grignard reagent CH3MgBr, and it was hydrolysed to yield an alcohol 91, which was cyclised to 92 with PPA at 85–110 °C (Scheme 28). 2.8. 1H-Pyrazolo[3,4-b]quinoline Synthes Based on Quinoline Derivatives The most common way to obtain pyrazolo[3,4-b]quinolines by using the fifth path is by the reaction of the hydrazines RNHNH2 (R = H, aryl) with quinoline derivatives (Figure 8). Some modifications are also possible, in which 2-chloro/2-aminoquinolino-3-carbonitrile or 3-acetylquinolin-2(1H)-one can also be used. In 1978, Meth-Cohn et al. described the synthesis of the 5-chloro-4-formylquinoline derivatives 95 by the formylation of Vilsmeier–Haack-substituted acetanilides 94 (Scheme 29) [61,62,63]. The resulting compound, 5-chloro-4-formylquinoline 95, can be transformed into a wide variety of fused heterocyclic derivatives, including 1H- or 2H-pyrazolo[3,4-b]quinolines (Figure 9) [64]. Some simple procedures of transforming 2-chloro-3-formylquinolines 95 into pyrazoloquinolines are depicted in Scheme 30. Thus, Hayes et al. carried out the reaction between 95 and hydrazine 96 or methylhydrazine 97. The immediate attack at the aldehyde group forms 1,7-dimethyl-1H-pyrazolo[3,4-b]quinoline 98. On the other hand, when the aldehyde group is protected, such as in 99, hydrazine substitutes the chlorine atom at position 2, and with the subsequent deacetylisation with acid in alcoholic solution and the cyclisation to the pyrazole ring. The formation of 2H-pyrazolo[3,4-b]quinolines 100 is observed. The third modification consists of reacting the Grignard reagent with an aldehyde group in 95, and the resulting alcohol is oxidised with chromium (VI) compounds to the ketone 101. Reaction with hydrazine or arylhydrazine leads to the formation of 1H-pyrazolo[3,4-b]quinolines 102 [65]. Other researchers have applied the same methodologies, and sometimes with the application of MW irradiation [65,66,67,68,69,70,71,72,73,74]. Mane et al. investigated the influence of baker’s yeast on the synthesis of tetrahydrobenzo[a]xanthene-11-ones and pyrazolo[3,4-b]quinolines. They reacted substituted aldehydes 95 and hydrazine 96 or phenylhydrazine 67 in water and obtained pyrazolo[3,4-b]quinolies 98 (R = H, Me, Cl, OMe, R1 = H, Ph), with the yield of 79–90% [75]. In 1999, Kerry et al. formylated N-acetylo-1-naphthylamine 103 to produce 2-chlorobenzo[h]quinoline-3-carbaldehyde 104. In the next turn, the aldehyde group was protected by transformation into acetal 105 and was reacted with methylhydrazine 97 or hydrazine 96, which formed compound 106. This one was heated in boiling ethanol that was acidified with HCl, which afforded 10-methyl-10H-benzo[h]pyrazolo[3,4-b]quinoline 107 (Scheme 31) [76]. These derivatives were synthesised as potential topoisomerase inhibitors. When 2-naphthylamine 108 is used instead of 1-naphthylamine, the aldehyde 110 can be obtained by carrying out the same chemical transformations (e.g., acetyl derivative 109) as for the previously described reactions. Maheira converted 109 into an oxime by reaction with hydroxylamine hydrochloride and, with the subsequent treatment with SOCl2 in boiling benzene, he obtained 2-chloro-benzo[g]quinoline-3-carbonitrile 111. Further reaction with hydrazine 96 gave 112. In the next turn, 3-aminoderivative 112 was coupled with various pyrazol-5-ones, which formed a series of azo dyes for polyester fibers (Scheme 32) [77,78]. The same synthetic protocol can be used for 95 by the transformation of it into oxime, 2-chloroquinoline-3-carbonitrile and then into 3-amino-1H-pyrazolo[3,4-b]quinoline, which is then modified in various ways to search for potential compounds of biological activity (Scheme 32—structures marked in blue) [79]. Section 2.5 discusses the few cases where isatin and pyrazolones are used in the Pfitzinger reaction for the synthesis of pyrazoloquinolines. Here, we have another one of the few cases that uses this compound, and specifically its derivative 113, which is formed as a result of the reaction of isatin 50 with ethyl cyanoacetate. The reaction with ethanol acidified with sulphuric acid afforded ethyl 3-cyano-2-oxo-1,2-dihydroquinoline-4-carboxylate 114. Heating with a mixture of phosphorus oxychloride and phosphorus trichloride causes the introduction of the chlorine atom in the 2 position of the quinoline system, which results in the formation of compound 115. The last step is the reaction with hydrazine, which gives pyrazoloquinoline 116. This compound offers multiple possibilities for further functionalization and for obtaining a whole range of derivatives (e.g., by modifying the ester and amino groups, or by adding substituents to the nitrogen atom N1 (Scheme 33) [80]). Another substrate for the synthesis of pyrazolo[3,4-b]quinolines is 2-hydroxy-3-acetylquinoline 118, which is easily prepared from ethyl acetoacetate 117 and o-aminoacetophenone/benzophenone 1 (Scheme 34). Arasakumar et al. applied 3-acetyl-4-phenyl-chinolin-2-one 118 and p-chlorophenylhydrazine for the synthesis of substituted 1H-pyrazolo[3,4-b]quinoline 120 [81]. Researchers have studied the effects of various Lewis acids (e.g., SnCl4, AlCl3, TiCl4, etc.), as well as of the microwave field, on the reaction yield. The best results were achieved with indium chloride (InCl3). Compound 118 can be subjected to the reaction with phosphorus trichloride (PCl3) to give 2-chloro-3-acetylquinolines 119, which is reacted with hydrazine. The product is 3,4-disubstituted-1H-pyrazolo[3,4-b]quinoline 121 [82]. The free position in nitrogen N1 allows for numerous modifications of these compounds in terms of the biological properties [83]. 3-Acetyl-4-(methylthio)quinolin-2(1H)-one 124 is an example of another quinolin-2-one-based system that can be used both for the synthesis of pyrazoloquinolines and for other heterocycles as well [84]. It can be easily prepared from acetoacetanilide 122 by reacting with carbon disulfide in the presence of tetrabutylammonium bromide (TBAB), with the subsequent methylation yielding ketene dithioacetal 123. In the next step, the 123 is cyclised by boiling in o-dichlorobenzene. Reactions with hydrazine or phenylhydrazine in acetic acid lead to the formation of the corresponding pyrazoloquinolines 125. On the other hand, when DMF is used as a reaction medium instead, 125 angular pyrazolo[4,3-c]quinolin-2-ones 126 are formed (Scheme 35) [85]. The use of 2-naphthylamine 108 and the Meth-Cohn procedure allows for the synthesis of benzo[h]pyrazolo[3,4-b]quinoline (Scheme 32). Similarly, 1-naphtylamine 127 can be reacted with α-oxoketene dithioacetal 128 and n-BuLi to form α-oxoketene -N,S-naphtyaminoacetal 129, which forms 2-methylthio-3-benzoyl-4-methylquinolines 130 upon the cyclisation by POCl3/DMF. The reaction with hydrazine under microwave irradiation afforded the formation of 131 (Scheme 36) [86]. The same procedure can be applied to aromatic amines or diamines and, as a result, other heterocyclic systems, such as phenanthrolines, can be obtained. 2.9. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on 5-arylaminoaminopyrazoles One of the oldest methods of pyrazoloquinolines synthesis are the two-component reactions of 5-arylamino pyrazoles and aromatic aldehydes (Figure 10). In 1911, Michaelis heated 5-N-arylamino-1,3-disubstituted pyrazoles 132 with some aromatic aldehydes 133 in the presence of anhydrous ZnCl2 and obtained compounds to which he assigned a structure 134 (Scheme 37) [1]. He described them as yellow crystalline substances with a strong blue fluorescence in a toluene solution. Our group was interested in these types of compounds from the point of view of applying them to organic electroluminescent cells. The syntheses described by Michaelis were repeated, and the chemical structures of the compounds that were obtained were analysed by using 1H NMR spectroscopy. It turned out that the structure of Michaelis 134 did not correspond to any of the compounds that he received, but that it did match the pyrazoloquinolines of 65 [87]. In several cases, it was possible to isolate intermediate 135, which oxidises over time to form pyrazolo[3,4-b]quinoline 65. The modified Michaelis method turned out to be a very good method for the synthesis of 65, and it complements the Friedländer condensation, in which o-aminobenzophenones are used. However, it provides more possibilities with regard to the introduction of substituents to the phenyl ring in position 4 and the modification of the carbocyclic ring. The starting 5-N-arylamino-pyrazoles 132 can be obtained from commercial 1,3-disubstituted 5-aminopyrazoles and the corresponding aryl halides by the procedures that are described by Buchwald [88]. The next two-component procedure with N-arylpyrazoles is one of the oldest synthetic pyrazoloquinolines methods (Scheme 38). In 1936, Koćwa published a series of papers in which he obtained 2H-pyrazolo[3,4-b]quinolines 140 by reacting aryl isocyanates 137 or isothiocyanates 138 with N-arylpyrazoles 136 [3,4]. By heating N-[5-methyl-1-phenyl-1,2-dihydro-3H-pyrazol-3-ylidene]aniline 136 with phenyl isocyanate 137 at a temperature of 230–240 °C, product 140 is formed, while, in the case of phenyl isothiocyanate 138, intermediate 139 was isolated, which then cyclised to 140 by heating with PCl5 at a temperature of 100–110 °C in 15 min (Scheme 38). In 1976, Purnaprajna and Seshadri, as a result of the Vilsmeier–Haack formylation of 1-phenyl-3-(p-chloroanilino)-5-pyrazolone 141, isolated 4-dimethylaminomethylene derivative 142. In the next stage, they cyclised it by using phosphorus oxychloride to produce 3,6-dichloro-2-phenyl-2H-pyrazolo[3,4-b]quinoline 143 (Scheme 39) [89]. For a long time, this was only one example of such reaction. It was not until 2021 that Kucharek and colleagues developed a one-step cyclisation reaction of 5-N-arylpyrazoles 132 in the presence of dimethylformamide diethyl acetal (DMF-DEA)/POCl3 at 80 °C. The yields of the obtained pyrazoloquinolines 59 ranged between 27 and 97% [90]. We include in this part one more synthesis, in which the 5-N-arylamino derivatives of pyrazoles with the ester group in the 4 position of the pyrazole ring are obtained (Figure 11. Path 6b). This compound can be easily prepared in a one-pot reaction by starting from aniline 39, carbon disulfide, chloroacetic acid and hydrazine, which yields thiosemicarbazide 144. A subsequent reaction with ethyl 2-chloroacetoacetate 145 produced pyrazole ester 146. The hydrolysis of 146 in EtOH/KOH and the cyclisation of the resulting acid with POCl3 yielded chloro derivative 147 (Scheme 40) [33,91,92,93]. 2.10. 1H-Pyrazolo[3,4-b]quinoline Syntheses Based on 4-arylidenepyrazoles Another one-component procedure is the synthesis which uses 4 arylidene substituted pyrazole derivatives (Figure 12). Coutts and Edwards reacted o-nitrobenzaldehyde 148 and pyrazolone 10, which yielded 4-(2-nitrobenzylidene)-2-pyrazolin-5-ones 149 [94]. The next step was to use several methods of reductive cyclisation, such as cyclohexene/Pd(C), NaBH4 as well as zinc and acetic acid. The end product was 9-hydroxypyrazolo[3,4-b]quinolines 150a. After changing the reaction conditions as a result of reductive cyclisation, they obtained pyrazolo[3,4-b]quinoline 150b [95] (Scheme 41). The prereaction between o-nitrobenzaldehyde 148 and the corresponding pyrazolone 10 may be an alternative to avoid the synthesis of the anthranilic aldehyde 1 (R3 = H, R4 = H, halogen, OMe) that is needed for the Friedländer condensation (Scheme 3). As part of the research on nitrenes, Kametani and colleagues performed reductive cyclisation reactions on 4-(4,5-methylenedioxy-2-nitrobenzylidene)-2-phenyloxazolones by using triethyl phosphite (P(OEt)3). These compounds were prepared from 4,5-dimethoxy-2-nitrobenzaldehyde (145; R3,4 = OMe) and N-benzoylglycine. The reaction resulted in the formation of 2-phenyloxazolo[5,4-b]quinoline [96]. Nishiwaki also tried to cyclise 4-(2-nitrobenzylidene)-2-pyrazolin-5-ones 149 by using P(OEt)3 as the reducing agent. However, instead of the expected pyrazoloquinolines, a whole range of other products were isolated from the reaction mixture, the structures (e.g., 151, 152, 153) of which are shown in Scheme 41 [97]. Tomasik and Danel used reductive cyclisation with iron powder and glacial acetic acid to synthesise pyrazoloquinolines 150 from o-nitrobenzylidene derivatives 149, however with moderate yields [98]. In concluding the discussion of the use of single-component systems, one could mention the work of DeWald on the metabolites of Zolazepam 154 (R1 = Me). After the administration of Zolazepam to rats, the metabolite 154a (R1 = H) was found in their urine. In order to synthesise it, the Zolazepam was demethylated with boiling pyridine hydrochloride; however, the reaction was unsuccessful, and instead of 154a, 155a was obtained (R2 = Me, R1 = H). Compound 156 was synthesised to obtain an isomer 155b (R2 = H, R1 = Me) (Scheme 42) [99]. To sum up, the synthesis of pyrazoloquinolines with the use of a single-component system (e.g., 148) is of no practical importance in the light of other, much more efficient methods. 2.11. Multicomponent 1H-Pyrazolo[3,4-b]quinoline Synthesis In recent years, the significant development of multicomponent reactions in organic chemistry has been observed, including the syntheses of heterocyclic compounds [100,101]. Many review publications and monographs on this issue have been published [102,103]. As far as pyrazoloquinolines are concerned, the multicomponent reactions described so far in the literature are limited to the two methodologies presented below (Figure 13). The first reaction of this type was described by Hormaza et al. in 1998. Pyrazoloquinoline derivatives 158 were obtained by heating the amino pyrazole 17, aromatic aldehyde 138 and the corresponding cyclic 1,3-dione 157. The authors proved that the reaction is regiospecific with the formation of linear pyrazoloquinoline 158 when R1 = H or Ph. The angular derivatives 159 or 160 (for R1 = H) were not formed (Scheme 43) [104]. Nogueras et al. investigated the mechanism of the abovementioned reaction. After carrying out a few experiments, they came to the conclusion that the first step is the Knovenagel condensation between dimedone 157 and aldehyde 133, and then, in the Michael addition, there is the attachment of aminopyrazole 17 with the subsequent cyclocondensation between the dimedone carbonyl group and the pyrazole amino group [105]. This reaction has been modified many times in terms of different reaction conditions. These modifications include conducting reactions in the microwave field, with or without a catalyst such as L-proline [106,107]. One of the important synthetic aspects of green chemistry is the use of ultrasound in organic synthesis. This approach was used by Maddila and colleagues for the synthesis of pyrazoloquinolines. The reactions took several minutes, and the yields of the products that were obtained were relatively high (in the order of 70–98%) [108]. Other modifications to this reaction consisted of the use of various catalysts, such as H3PW12O14 or nanomagnetic celulose in ionic liquids [109,110]. In all mentioned cases, when dimedone 157 was used, the central heterocyclic ring was hydrogenated. In some cases, a fully aromatic ring was produced (Scheme 43). Thus, Shi and Wang used sodium 1-dodecanesulfonate SDS as a catalyst in the aqueous reaction medium for the same components (17, 133 and 157) [111]. The end product was a system with a fully aromatic pyridine fragment 161. The authors mentioned in the paper that the mechanism of this reaction is not fully understood, and especially how the hydrogen molecule is lost from the structure. The same reaction that was carried out in polyethylene glycol PEG-400 yielded the same product with an aromatic pyridine fragment [112]. Contrary to the previously described multicomponent reactions (Path 8a; C4-C4a, C4-C3a, C8a-N9), Tomasik et al. synthesised fully aromatic pyrazolo[3,4-b]quinolines 65 (Path 8b; C4-C4a, N9-C9a, C4-C3a) (Scheme 44) [113]. The final compounds 65 are obtained by heating a mixture of aromatic amine 39, aromatic aldehyde 133 and pyrazolone 10 in ethylene glycol for two hours. After cooling and digestion with methanol/ethanol, the pyrazoloquinolines precipitate as a crystalline solid. The yields of the reactions are in the range of 20–33%, although some authors have claimed that they obtained pyrazoloquinolines 65 in the order of 50–60% by this method [114]. Aromatic amines 39 can contain both electron-donating groups and electron-withdrawing groups in the o, m, or para positions. Aromatic aldehydes 133 can include various benzaldehyde derivatives, as well as naphtalene-1/2-carbaldehyde, but it is unable to obtain derivatives of 9-formylanthracene. Despite moderate yields, it seems to be the best method of obtaining 4 substituted aryl pyrazoloquinolines, which successfully replaces the Friedländer synthesis by using substituted o-aminobenzophenones. Hedge and Shetty describe a multicomponent synthesis of 1,4-diphenyl-3-methyl-4,9-dihydro-1H-pyrazolo[3,4-b]quinolines 135 that used L-proline as the catalyst (Scheme 44) [115]. The components were the same as in Tomasik et al.’s procedure, but the final product was not aromatised in the final step (Path 8b; C4-C4a, N9-C9a, C4-C3a). Another group of multicomponent reactions are those that use 2-hydroxynaphtalene-1,4-dione 163. Li et al. synthesised two series of compounds: benzo[h]isoxazolo[5,4-b]quinolines 164 from 5-amino-3-methyloxazole 162, and benzo[h]pyrazolo[3,4-b]quinolines 165 by applying 5-amino-3-methyl-1-phenylpyrazole 86 (Scheme 45) [116]. In the next stage, the authors subjected the obtained systems (164 and 165) to reactions with 1,2-diaminobenzene in order to obtain the quinoxaline derivatives 166. All the steps that are described were carried out under microwave irradiation. The reaction that was performed by Rajesh et al. is described as a “sequential four-component reaction”, which makes it a kind of record holder among the multicomponent reactions that are used for the synthesis of pyrazoloquinolines 165. They reacted 3-aminocrotononitrile and phenylhydrazine with an addition of L-proline for 10 min in boiling water, and they then added an equimolar mixture of aldehyde 138 and dione 163. The whole mixture was then heated for 1–1.5 h [117]. Quiroga et al. synthesised a series of benzo[h]pyrazolo[3,4-b]quinolines 165 via a three-component reaction under microwave irradiation [118]. When they used 86 (X = NH), the middle heterocyclic ring was unsaturated. The formation of the linear benzo[g]pyrazolo[3,4-b]quinoline system was not observed. The resulting compounds were screened against some Mycobacterium strains. Khalafy et al. conducted research on the influence of silver nanoparticles (AgNPs) on the course of the reaction. The aryl glyoxal hydrates 167 were used as the C-4 carbon incorporation reagent in the three-component reaction. The end product is 7-benzoyl-benzo[h]pyrazolo[3,4-b]quinolin-5,6-diones 168. It should be emphasised that the reactions were carried out in a water–alcohol environment at a temperature of 60 °C, and in most cases, they were completed within 60 min [119] (Scheme 46). Another multicomponent reaction for the synthesis of pyrazoloquinoline derivatives 170 differs from the others by the procedure in which ingredients such as aminopyrazole 86, 2-hydroxy-1,4-napthalenedione 163 and cinnamaldehyde 169 are ground in a mortar with a little addition of water. The authors call it, “liquid assisted grinding or LAG.” After grinding is completed, the product is simply recrystallised from an appropriate solvent (Scheme 46) [120]. The multicomponent reactions with the use of 163 that have been described so far led to the preparation of angular benzo[g]pyrazolo[3,4-b]quinolin-5,6-diones (e.g., 165, 168 or 169). It is also possible to obtain a linear system of the mentioned heterocyclic system. Gutierez, in the three-component reaction of aminopyrazole 86, 2-hydroxy-1,4-napthalenedione 163 and formaldehyde 164, and indium chloride (InCl3) as a catalyst, obtained 3-methyl-1-phenylnaphtalen [2,3-e]pyrazolo[3,4-b]pyridine-5,10-dione 171 (Scheme 47) [121]. The reactions were carried out by using either conventional heating (40–60 h) or by heating in a microwave field (10–20 min). Indium chloride (InCl3), as a catalyst, was also used in the three-component reaction to synthesise not only pyrazoloquinolines, but also pyrimidine derivatives. Instead of formaldehyde, the authors used a number of aromatic aldehydes. In the case of 1,3-cyclohexanedione, a product with a hydrogenated pyridine ring was obtained, and, in the case of 1,3-pentanedione, indane-1,3-dione and naphthalene-2-hydroxy-1,4-dione, which are products with aromatic pyridine fragments, were obtained [122]. Wu et al., as a catalyst, used a 10–15 mol% amount of (NH4)2HPO4 for 2-hydroxynaphthalene-1,4-dione 163, aromatic aldehyde 133 and 5-amino-3-methyl-1-phenylpyrazole 86 three-component reactions [123]. The isolated yields of the benzo[h]pyrazolo[3,4-b]quinolines ranged from 80–95%. Due to the concern for the protection of the natural environment, we have observed an increasing tendency to change the approach to organic synthesis. This is manifested, inter alia, by the use of water as the reaction medium, or by the use of ionic liquids. One such example is PEG1000-based dicationic acid ionic liquid, which has been used by Ren et al. in the synthesis of linear benzo[h]pyrazolo[3,4-b]quinolines 172 in three-component reactions from 163, 133 and 86 [124].The authors presented a possible mechanism of this reaction that consists of the addition of an aldehyde 133 to 163, followed by a Michael’s addition of aminopyrazole 86, the cyclisation of the resulting adduct with the subsequent oxidation with air and the final formation of 172 (Scheme 47). L-proline is a frequently used catalyst in multicomponent reactions. Karamthulla et al. used it in the synthesis of linear 2H-benzo[g]pyrazolo[3,4-b]quinolone-5,10(4H,11H)-dione derivatives [125]. The reaction that was performed differed slightly in terms of the choice of components, and, namely, by the fact that 3-amino-5-methylpyrazole was used instead of the 1-phenyl-3-methyl-5-aminopyrazole 86. Contrary to the reactions that are shown in Scheme 47, no aromatisation of the pyridine ring was observed. In multicomponent reactions where pyrazoloquinolines are synthesised, isatin is sometimes used. We mentioned it in the context of the Pfitzinger reaction that was described earlier. In this case, isatin made a significant contribution to the construction of the pyrazoloquinolines skeleton (Scheme 17). In the three-component reactions that are depicted in Scheme 48, it contributes only carbon 4 in the skeleton (Path 8a; C4-C4a, C4-C3a, C8a-N9). Wu et al. obtained spiro[benzo[h]pyrazolo[3,4-b]quinoline-4,3′-indoline] 173 by reacting dione 163, aminopyrazole 86 and isatin, or its derivative 50, in the presence of wet cyanuric chloride (TCT) [126]. Dabiri conducted the abovementioned reaction in the presence of L-proline (10 mol%) in boiling water for 6–7.5 h. The researchers additionally conducted additional studies by replacing isatin with acenaphtylen-1,2-dione. The yields of the corresponding spiro derivatives were in the range of 50–70% [127]. Spiro compounds based on pyrazoloquinolines (i.e., spiro[indoline-3,4’-pyrazolo[3,4-b]quinoline]-2.5’(6’H) dione) can also be obtained without any catalysts, as was proven by Rong and his colleagues by heating isatin 50, dimedone 157 (or 1,3-cyclohexanedione 43) and 3-amino-1H-pyrazole in water or dilute acetic acid [128]. This reaction meets 100% of the requirements of the so-called “green chemistry”. The catalysts that have been discussed so far in multicomponent reactions were of a homogeneous nature. Baradani and colleagues used Fe3O4@Cu(OH)x as a catalyst in the three-component reaction of dimedone 173, aminopyrazole 86 and 5,6-dihydro-4H-pyrrolo[3,2,1-ij]quinoline-1,2-dione, instead of isatin [129]. The reactions were carried out in the environment of water/ethanol with the addition of a nanocatalyst, and they lasted from 8 to 9 h. After the reaction was completed, the catalyst was removed with a strong magnet. The final product was separated and purified with chromatographic techniques. In the literature, you can find descriptions of three-comonent reactions that use β-tetralone 175 or α-teralone 177 for the synthesis of angular benzo[f]-197 or benzo[g] pyrazoloquinolines 200. The reactions were carried out by melting the reagents [130]. The first of the abovementioned reactions ran smoothly and produced the expected benzo[f] derivative 176 (Scheme 49). Quiroga and co-workers tried to repeat the earlier procedure to obtain the benzo[h]isomer 179, and unfortunately, in this case, they were not successful. The main product turned out to be bis-pyrazolo[3,4-b;3’,4’-e]pyridine 180. Therefore, they changed the procedure and first synthesised a 2-arylidene derivative of α-tetralone 178, which was then reacted with aminopyrazole 17 by melting. This time, a derivative 179 was obtained (Scheme 50). Sathiyanarayanan et al. prepared benzo[f]pyrazolo[3,4-b]quinolines 176 by heating β-tetralone 175, aminopyrazole 17 and aromatic aldehyde 133 in ethanol/CH3COOH and tin chloride (SnCl2) (10 mol%) [131]. The reaction also proceeded with cyclohexanone and cyclopentanone, but it failed with α-tetralone and 2-hydroxynaphtalene-1,4-dione 163. The resulting compounds exhibited intense emission properties in solution, and in the solid state as well. Moreover, when the R3 was NMe2, the compound exhibited aggregation-induced emission AIE. To conclude our review of the most important pyrazoloquinoline reactions in the last 100 years, we were very pleased with the work that was published by Tiwari et al. in 2021 [132]. It is a very universal method that allows one to obtain a whole range of pyrazoloquinolines 59 from commercial ingredients, such as aromatic amines 39, pyrazolones 10 and dimethylsulfoxide 181. The reaction proceeds in the presence of trifluoacetic anhydride TFA. The authors proposed the mechanism of this reaction, where one of the intermediate steps is the azadiene system 182, which is annulated and then aromatised to produce the final pyrazolo[3,4-b]quinoline 59 (Scheme 51). Perhaps this reaction will be an alternative to the procedure that was developed by Brack in 1965 (Scheme 19), which allows the obtainment of all of the possible combinations of the substituents for 10 (R1, R2 = H, Me, Ph) in the pyrazole ring. Tiwari et al. employed only two pyrazolone derivatives 10 (R1 = Ph, R2 = Me and R1,2 = Ph). Finally, it may be mentioned that the authors expected a completely different result; thus, this is an example of serendipity in organic chemistry. 3. Photophysical Physical Properties of 1H-Pyrazolo[3,4-b]quinolines and Their Application In view of the ever-growing demand for many high-tech and biomedical applications, the group of 1H-pyrazolo[3,4-b]quinolines has gained considerable interest from the scientific community, which is mainly due to their intrinsic optical and photophysical characteristics. Over the past decades, many researchers have made some efforts to understand the relationship between the structure and the optical properties of these compounds. However, even though the establishment of the structure obtained by Niementowski was made in 1928 [2], it was only in the late 1990s and mid 2000s that a number of reports related to the spectroscopic characteristics and the computational analysis of 1H-pyrazolo[3,4-b]quinoline derivatives (see Figure 1 in the Introduction) were published [133,134,135,136,137,138]. 3.1. Structure–Property Relationship Structurally, pyrazoloquinolines are the products of the ring fusion of the heteroaromatic pyrazole and quinoline moieties, which gives rise to a rigid D-π-A system (Figure 14). Separately, these building blocks play a crucial role in the design of many functional materials. For instance, quinoline scaffolds are frequently used as electron-accepting components in light-harvesting systems [139,140], or as optical limiters [141]. Furthermore, quinoline-based molecules exhibit highly efficient electron-transporting properties that are combined with thermal and redox robustness and high photoluminescence quantum yields. These features are of paramount importance in the construction of many high-tech devices, such as organic optoelectronics (OLEDs) [142,143], photodiode detectors [144] and photovoltaic cells (OPVs) [145]. On the other hand, the pyrazole unit often acts as an electron donor in chromophore systems, which is due to the presence of two electron-rich adjacent nitrogen atoms [146,147]. Especially in conjunction with various electron acceptors (e.g., electron-deficient aromatics and heteroaromatics), pyrazole derivatives emerge as highly efficient, tunable light emitters [148,149,150]. Such structural motifs, including pyrazoloquinolines, have been intensively studied in the area of advanced dye chemistry, and most recently as electroluminescent materials [6,151,152], fluorescence sensors [153,154] and second-order nonlinear optical materials [155,156,157]. Generally, the absorption spectra of 1H-pyrazolo[3,4-b]quinolines contain two absorption bands in the UV–Vis region of light: I) The broad S0→S1 (π→π*) transition with an absorption maxima that ranges from ca. 380 to 420 nm; and II) More or less pronounced (depending on the substitution pattern) multiple bands at shorter wavelengths (<300 nm), which can be attributed to S0→Sn (mixed π→π* and n→π*) transitions. Furthermore, it can be observed that, in the case of pyrazoloquinolines substituted with donor and/or acceptor groups, the long-wavelength absorption maxima are slightly redshifted, corresponding to their unsubstituted analogues [47,158,159]. In fact, light-induced transitions in D-π-A chromophores are directed from an electron-rich to an electron-deficient unit, which results in a significant charge separation within the excited state (see Figure 14) [160]. In most cases, such a charge separation leads to the formation of conformationally disrupted and poorly emissive intramolecular charge transfer (ICT) states. However, the rigidity of the pyrazoloquinoline skeleton promotes electronically allowed emission, as the frontier orbitals that participate in the 1CT→S0 transition have parallel orientation and are, therefore, markedly overlapped [161]. Subsequently, 1H-pyrazolo[3,4-b]quinolines are highly fluorescent in the blue or greenish-blue parts of the spectrum, with quantum fluorescence yields reaching unity in some cases (Figure 15) [20,158,162]. A tremendous variety of synthetic approaches has led to an extension of the portfolio of pyrazoloquinolines with tunable luminescence features. Exemplarily, an introduction of additional electron-donating and electron-withdrawing groups within the chromophore results in the formation of spatially extended dipolar (or quadrupolar) systems. A considerable charge separation within the electronically excited states of these molecules results in a redshift of the emission bands, which noticeably proceeds with an increase in the solvent polarity [138,159,163]. However, the fluorescence intensity of such organic dyes decreases at the same time, which is due to an enhancement of the rate of nonradiative decay via intramolecular rotations within excited ICT states [164,165]. Another significant process that leads to the rapid deactivation of excited states is referred to as “photoinduced electron transfer (PET)” [166,167,168,169]. In this case, an electron donor (e.g., dialkylamine group) and the luminophore are commonly separated by a short alkyl spacer, which electronically disconnects the π-conjugation between the receptor and the electron donor units. The excitation of such a system is followed by the PET process, which leads to an immediate nonradiative decay to the ground state. However, most of the pyrazoloquinolines that are substituted with dialkyl and diaryl amines are deliberately designed for the in-active interruption of the aforementioned fluorescence-quenching mechanisms, which makes them promising “turn-on” sensors. 3.2. Application of Pyrazoloquinolines in Fluorescence Sensing Since the electroluminescence properties of 1H-pyrazolo[3,4-b]quinolines have been frequently reported for many years [20,47,170,171,172,173,174], in this review, we focus on their use as efficient fluorescence probes. The operation of many fluorescent indicators is based on a noticeable enhancement of the fluorescence emission upon the addition of metal cations to the fluorescing medium. Exemplarily, in 2002, Rurack et al. reported the synthesis of two aza-crown-modified 1,3-diphenyl-pyrazoloquinolines that exhibited high fluorometric sensitivity to Na+ and Ca2+ cations (see Figure 16a) [5]. The main concept of this study relied upon the structural connection between the nitrogen lone pair of the analyte receptor and the chromophore system, either by a σ-spacer (compound PQ 1) or by a perpendicular π-conjugated arrangement (compound PQ 2). Derivative PQ 1 proved to be weakly emissive in polar solvents (Φf = 0.02 in acetonitrile, compared to Φf = 0.54 in hexane), which was mainly due to the PET-fluorescence-quenching mechanism. On the contrary, pyrazoloquinoline PQ 2 showed an intense dual emission from LE and ICT fluorescent species (Φf = 0.18 in acetonitrile, compared to Φf = 0.37 in hexane). Furthermore, both derivatives showed highly desirable effects in the presence of analyte species (i.e., metal ions) on the basis of two different sensing mechanisms. The authors demonstrated that dye PQ 1 readily bound monovalent Na+ and bivalent Ca2+ cations, with a concomitant increase in the fluorescence intensity. These observations were in unambiguous agreement with a proposed PET-signalling mechanism. More interestingly, pyrazoloquinoline PQ 2 performed as a dual emissive sensor with a high fluorescence output for both states of the detection system: bound and unbound. In this case, the presence of bivalent Ca2+ cations alternated the nature of the excited state of the fluorophore from the low-lying ICT state to the blue-shifted LE state, with a significant enhancement in the emission (from Φf = 0.18 to Φf = 0.35 in acetonitrile) at the same time. In contrast, the addition of Na+ ions to PQ 2 did not change its spectral characteristics markedly. Since the aforementioned studies on pyrazoloquinoline-based sensors were reported, almost a decade passed until this stem was followed. Then, between 2010 and 2013, Mac and co-workers published a series of articles on ion-sensitive pyrazoloquinolines, which varied by the molecular architecture of the receptor unit (see Figure 16b) [175,176,177]. All of the sensors presented (PQ 1a–d) were designed for PET signalling, and they maintained the connection between the receptor unit and the pyrazoloquinoline chromophore via the non-conjugated methylene spacer. In addition, the authors extended their studies to a wide range of metal cations, including monovalent Li+, Na+ and Ag+, and bivalent Ca2+, Ba2+, Mg2+, Zn2+, Cd2+ and Pb2+ cations. The results obtained were consistent, which showed that these “turn-on” fluorescent cation indicators were more sensitive to the presence of bivalent cations than to monovalent species. Interestingly, for compound PQ 1c, an increased sensitivity and selectivity to Zn2+ and Mg2+ arose from a predominant complexation of these cations with two molecules of the sensing system. Furthermore, noticeable bathochromic shifts of the fluorescence bands were observed for M2Zn2+ and M2Mg2+ complexes. These findings were explained by the formation of excimer species [M2+(MM)]*, which was confirmed by quantum chemical calculations [177]. In 2013, the same research group demonstrated a detailed study on the pyrazoloquinoline derivative PQ 1d, which was a direct precursor for the synthesis of the aza-crown fluorescence probe PQ 1, previously reported by Rurack [5]. It was found that this compound can act as a highly efficient sensor for many bivalent cations and that, more importantly, its selectivity can be easily enhanced by the addition of small amounts of water to the fluorescing medium. Three years later, Uchacz et al. investigated a series of donor-acceptor 1H-pyrazolo[3,4-b]quinolines that were substituted with different amine donors (i.e., N,N-dimethylamine, N,N-diphenylamine, N,N-phenyl-1-naphthylamine and carbazole groups), with the aim of implementing them as pH-sensitive molecular logic switches [178]. The authors showed that, in the presence of trifluoroacetic acid (the input signal), the fluorescence of the investigated pyrazoloquinolines was almost completely quenched, which was due to the formation of a nonemissive protonated adduct. Interestingly, pyrazoloquinoline substituted with the N,N-dimethylamine group presented a more advanced ternary logic behavior (see Figure 17). The nonprotonated state of this compound showed considerable fluorescence (yellow emission, first logic value), which, upon the first protonation of the nitrogen of the dimethylamino moiety, shifted hypsochromically and slightly decreased (bluish-green emission, second logic value). The second protonation, which involved the nitrogen of the quinoline core, quenched the fluorescence quantitatively (no emission, third logic value). Basically, reading the fluorescence response as an output that is dependent on the presence of proton input signals yielded functional luminescent molecules with the potential for multilevel logic switching, which ranged from binary to ternary responses. With regard to all of these results, it can be concluded that the scope of pyrazoloquinoline-based fluorescence probes is still amenable to further investigation. For instance, the up-to-date studies were mainly focused on the PET-signalling mechanism, with only minute mention of the intramolecular rotation-dependent quenching of the excited ICT states. Currently, a plethora of photophysical studies are devoted to many different ICT state-related phenomena, such as TICT, PICT, PPT, TADF, umpolung-ICT and so forth [179,180,181,182,183], which can be used as output signals for analyte compounds. Furthermore, the presented studies focus mostly on inorganic ion-sensing, which leaves future prospects for the many biomedical applications of pyrazoloquinoline fluorophores, such as fluorescence bioimaging, photosensitized diagnoses or therapies. 4. Biological Properties of 1H-Pyrazolo[3,4-b]quinolines Nitrogen-heterocycles are the most common heterocyclic compounds that occur in living organisms [184], and they are also very often tested as compounds that show biological activity [185,186]. Thus, it is not unusual that pyrazoloquinoline derivatives have attracted the attention of researchers who deal with the biological activity of organic compounds. It is advisable to divide pyrazoloquinoline derivatives into groups according to the kind of biological activity that they possess. 4.1. Hypolipemic and Hypocholesteremic Activity The method of synthesis that was developed by Stein et al. and Crenshaw et al. [29,30] produced, inter alia, 4-chloro-1,3-dimethyl-1H-pyrazolo[3,4-b]quinolines, which, after functionalization with different amine derivatives (Figure 18), were tested for their hypolipemic and hypocholesteremic activity in rats [187]. The compounds were suspended in a carboxymethyl cellulose solution at a dose of 100–400 mg/kg, compared to a carboxymethyl cellulose solution only, and were administrated to rats daily for 4 days. After the administration, the rats were tested for their cholesterol and phospholipid concentrations in serum, and the results show that, with the maximum dose of 400 mg/kg, the concentration was reduced significantly: by −51% for cholesterol and by −47% for phospholipids. 4.2. Interferon-Production-Inducing Activity Interferons are an important group of signalling proteins that are released by cells in response to some viruses [188], and interferon-inducing drugs are one of the weapons in the fight against viruses [189]. 4-[(3-(Dimethyloamino)propyloamino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline (Figure 19), which was obtained by Stein et al. [29], was tested as a low-molecular-weight interferon inducer by Siminoff et al. [190]. The compound was administrated to female mice by the oral or parenteral route, and the administration was repeated. In concentrations of 200 mg/kg or higher, the response of the interferon production was very high, and it protected the mouse L cells against infection by the vesicular stomatotitis virus or the mouse picornavirus. The animals also became hyperesponsive to repeated stimulation. The following research in the Siminoff group also showed that other derivatives of 1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline, which contained the substituent at the 4 position, which is attached by the NH moiety, and with a side chain of at least three carbons and terminating with the second amino function (Figure 19b), also have significant interferon-inducing activity [30]. In the subsequent research, Siminoff analyzed which cells in mice are the major target for interferon induction by 4-[(3-(dimethyloamino)propyloamino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline (Figure 19a) [191]. The analysis of the results shows that the type of adherent leukocytes that are resident in the spleen is a major target of interferon induction. The other derivatives (Figure 19b) were also tested by Siminoff and Crenshaw in the cultures of spleen adherent leukocytes [192]. The results show that some of the derivatives also showed high interferon-inducing activity. One of the derivatives, 4-[(3-(dimethyloamino)propyloamino] -1,3,7-trimethyl-1H-pyrazolo[3,4-b]quinoline hydrochloride (Figure 19c), was also tested by Kern et al. [193], and again, the compound induced high levels of circulating interferon, which effected, with significantly reduced mortality, the mice that were infected with the Rochester mouse virus, Herpesvirus hominis, Semliki forest virus and the vesicular stomatitis virus. The authors also observed the strong hyporeactivity of the interferon after multiple doses of 4-[(3-(dimethyloamino)propyloamino]-1,3,7-trimethyl-1H-pyrazolo[3,4-b] quinoline hydrochloride. 4.3. Antiviral Activity Many virus infections in humans are self-cured by the immune system of the organism, and, for many others, vaccinations provide immunity to infection. However, there are some diseases that must be cured by the use of antivirial drugs (e.g., HIV, herpes viruses, hepatitis). A huge family of 1H-pyrazolo[3,4-b]quinoline derivatves (Figure 20), which were obtained by the method of Stein et al. [29] and then functionalised, were synthesised and tested for antiviral activity by the group from the Research Institute for Pharmacy and Biochemistry in Prague in the 1980s [194,195,196,197,198,199,200,201]. Anilino derivatives were tested against the A2-Hongkong virus and against the encephalomyocarditidis (EMC) virus in vivo in mice. Some of them showed high activity against one or the other virus, and some of them were effective against both. In the case of 4-[(4-methylphenyl)amino]- and 4-[(5-methoxy-2-pyrimidinum)amino]- derivatives, which were administrated orally, the survival time was extended after infection with the A2-Hongkong virus by 50 and 67 days, respectively. In the case of 4-[(4-hydroxyphenyl)amino]-, 4-[(4-octadecaoxyphenyl)amino]- and 4-[(3,4-methylenedioxyphenyl)amino]- derivatives that were administrated subcutaneously, the time of survival against the EMC virus was increased by 70, 83 and 95 days, respectively [194,198]. The keto derivatives (Figure 21) were tested against the same viruses as aniline-derivatives: against the A2-Hongkong virus and against the encephalomyocarditidis (EMC) virus in vivo in mice, and after oral or subcutaneous administration. The most potent against the A2-Hongong virus was 4,9-dihydro-3,9-dimethyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline, which extended the survival by 55%. In the case of the EMC virus, the compounds were much more effective, and for 4,9-dihydro-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline and 4,9-dihydro-6-methoxy-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline, the survival was extended by 96% or by 80–100%, respectively [195,200,201]. Some of the compounds were also tested in vitro against different microbes (e.g., Streptococcus faecalis, Escherichia coli or Candida albicans); however, none of the studied derivatives had significant inhibitory effects [195]. The authors from the Research Institute for Pharmacy and Biochemistry in Prague were so satisfied with the results that they obtained for some of the tested pyrazoloquinoline derivatives that they patented them in Czechoslovakia [202,203,204,205,206,207,208]. One of the compounds that was obtained by Rádl et al. [194], 4-[(4-methoxyphenyl)amino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline (Figure 22, R = OMe), was included in the modeling procedure for the binding site identification and the docking study of human β-arrestin by Chintha et al. [209]. Unfortunately, the results for that compound were not amazing. Another derivative, 4-[(4-ethoxyphenyl)amino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline (Figure 22, R = OEt), was used by Vyas et al. [210] as one of the known potential apoptosis inducers that are used to generate pharmacophore models with their apoptosis-inducing activity, for the same reason that Kemnitzer et al. used 4-[(4-propionylphenyl)amino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline (Figure 22, R = COC2H5) as the reference in apoptosis-inducer studies [211]. Different pyrazoloquinoline derivatives have attracted attention as antiviral compounds against the herpex simplex virus. Albin et al. tested the activity of three earlier synthesized [200,212] derivatives (Figure 23) against herpex simplex virus type 2 (HSV-2) [213]. In vitro tests were performed with African green monkey kidney (Vero) cells, human diploid lung (WI-38) cells, human epithelial (HeLa) cells and human foreskin fibroblast (FS-85) cells. The monolayers of the cells were infected with HSV-2 in the presence or absence of the compounds SCH 43478, 46792 and 49286. The results were compared with those that were obtained with Acyclovir (ACV), which is the most popular drug that is used against herpes simplex. The inhibition of the HSV-2 plaque formation in Vero cells was achieved with concentrations lower than those for ACV; however, for the other cell lines, ACV is more effective. The cytotoxicity of all of the studied compounds against the tested cell lines was comparable to the effect of ACV. It is important to say that the compounds of interest were effective only when added shortly after infection; if added after 3 h or later, they were ineffective, which is a much worse result than that obtained for the ACV. Another broad group of 3-amino-1H-pyrazolo[3,4-b]quinolines (Figure 24) were studied by Bell and Ackerman [214]. The authors tested the synthesised compounds against HSV-2 in vitro on mouse emryo fibroblast monolayers. Some of the studied compounds exhibited high activity (comparable or higher than that of Acyclovir), but they were never tested again. A different group of researchers synthesised 3-amino-1H-pyrazolo[3,4-b]quinoline that was derivatived with monosaccharides at the amino group (Figure 25), and they tested those against herpes simplex virus type 1 (HSV-1) [215]. African green monkey kidney (Vero) cells were infected with HSV-1. From the tested group, most of the compounds did not show significant cytotoxicity at the concentrtations that are safe for living cells. Only two derivatives were borderline cytotoxic: 7-methyl- and 7-methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline that was derivatised with pentoses. The authors from the same research group also tested another group of derivatives, and they found that simple 7-methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline has an in vitro anti-HSV-1 activity that is comparable to Acyclovir [216]. The authors also show that the compound of interest has low toxicity (tested in vivo in male mice), even when administrated through the parenteral route (nontoxic up to 80 mg/kg). The compounds that were obtained by Bekhit et al. [215] (Figure 25) were tested by Arif et al. for their potential cytotoxic activity [217,218]. At a 100 μM concentration, some of the compounds showed high cytotoxicity against human breast carcinoma cell lines (MCF-7 and MDA-MB-231); however, at the same time, they were comparably cytotoxic to normal human breast epithelial cell lines (MCF-10A and MCF-12A). The 7-Methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline antiviral activity against HIV Type 1 was tested together with other different heterocyclic compounds [219]. Unfortunately, the compound did not show significant activity against that type of virus. 4.4. Antibacterial Activity Because of the rising bacterial resistance to antibiotics [220], there is a constant need to invent new drugs. Pyrazoloquinoline derivatives have been also tested in this field. A group of pyrazoloquinoline derivatives was tested by El-Sayed and Aboul-Enein [221]. The authors started with 3-amino-1H-pyrazolo[3,4-b]quinoline and they substituted it at the amino group (Figure 26). The compounds were then tested against E. coli, S. aureus, C. albicans and A. niger, and they were compared with ampicilin and ketoconazole. The preliminary results indicated that none of the tested compounds had activity higher than ampicilin against E. coli. 1-(4-fluorophenyl)- and 1-(4-nitrophenyl)-3-amino-1H-pyrazolo[3,4-b]quinoline achieved results that were comparable to ampicilin against S. aureus. Both compounds also have high activity against C. albicans and A. niger, with the second of them even higher than ketoconazole. In the case of A. niger, 1-(4-chlorophenyl)-3-amino-1H-pyrazolo[3,4-b]quinoline also showed high activity. Another family of differently substituted 3-amino-1H-pyrazolo-[3,4-b]quinolines was synthesised by Lapa et al. [222]. Among the group, one compound, (Figure 27) exhibited in vitro activity against S. aureus, S. epidermidis and S. pneumonia that was comparable to Kanamycin (MIC = 4.0–8.0 μg/mL). Against Mycobacterium smegmatis, the compound was even more active than Kanamycin. A different amino derivative was tested by Hamama et al. [54]. The authors used the Path 3 synthetic methodology (Figure 3), reacted arylidene compound 74 with 1,4-phenylenediamine and obtained 6-amino-3-methyl-1,4-diphenyl-1H-pyrazolo-[3,4-b]quinoline (Figure 28). The in vitro activity of the compound against Bacillus subtilis and Escherichia coli was a little lower than that found for Ampicilin. Pyrazoloquinolines of a totally different structure were studied by Quiroga et al. [118] (Scheme 45). The authors obtained a series of benzo[h]pyrazolo[3,4-b]quinolin-5,6-diones (165), between which 3-methyl-1,4-diphenyl-, 3-methyl-4-(4-methylphenyl)-1-phenyl- and 3-methyl-4-(4-fluorophenyl)-1-phenyl- seemed to be the most promising and presented the strongest in vitro activity against some Mycobacterium spp. For two active compounds, the authors also presented the XRD measurement results. The results indicate that the research should be continued. Another group of pyrazoloquinoline derivatives that were differently substituted at N-1 (Figure 29) were synthesised and tested by Jitender et al. [83]. A group of 32 compounds was tested for antibacterial activity against different Gram-positive (S. aureus, B. subtilis, M. luteus) and Gram-negative (E. coli, K. planticola, P. aeruginosa) bacteria. From the group, only four compounds had some activity, and the most potent was 2-(4-phenyl-3-(trifluoromethyl)-1H-pyrazolo[3,4-b]quinolin-1-yl)-N-(2-(piperazin-1-yl)ethyl) acetamide (Figure 30), which, with an MIC at 3.9–7.8 μg/mL, was a little worse than the value that was found for Ciprofloxacin (the reference in the study). Better results were obtained in the activity against Candida albicans spp.; for all the tested species, 2-(4-phenyl-3-(trifluoromethyl)-1H-pyrazolo[3,4-b]quinolin-1-yl)-N-(2-(piperazin-1-yl)ethyl) acetamide was as active as the Miconazole biofilm inhibition assay of the studied compound, which was comparable to the results for Ciprofloxacin against Gram-positive and Gram-negative bacteria, and to the results for Miconazole against C. albicans. All of the 32 compounds were also tested for their cytotoxicity against the HeLa, HepG2, A549 and COLO 205 cancer cells lines, but the IC50 (μM) values had to be at least one level of magnitude higher than those found for 5-fluorouracil (as a reference) in order to attract more attention as an anticancer drug. 4.5. Anticancer Activity Cancer is a leading cause of death (after cardiovascular diseases), and, in 2020, there were nearly 10 million deaths that were attributed to it (WHO). At the moment, world medicine has many anticancer drugs, but most of them are also cytotoxic to normal cells, and especially to those that are rapidly dividing. Thus, there is still a need for new highly selective anticancer drugs [223,224]. 7-Methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline, which appeared to be as active as Acyclovir against HSV-1 [216], was also tested as an inhibitor of the growth of cancer cells. Karthikeyan et al. tested the cytotoxicity of a group of 3-amino-1H-pyrazolo[3,4-b]quinolines (Figure 31) against ten cancer cell lines, including breast, colon, prostate, brain and ovarian, in comparison to a noncancerous cell line, the human embryonic kidney [225]. The cytotoxicity was determined by MTT assay by using different concentrations for every compound, in the range of 0.1–100 μM. The most potent in the series turned out to be 7-methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline (QTZ05), which was effective against all of the tested colon cancer cell lines (HCT-116, HCT-15, HT-29 and LOVO) and the brain cancer cell line (LN-229) at a concentration of 10.2 μM or lower. As can be seen (Figure 2 and Figure 4 in [225]), the compound of interest decreased the density and the colony size. Additionally, as the authors point out, the HCT116 cells that survived were unable to replicate. The results indicate that 7-methoxy-3-amino-1H-pyrazolo[3,4-b]quinoline produces an increase in the number of cells in the sub G1 phase of the cell cycle. The authors also checked the ability of the studied compound to induce apoptosis. The same authors (Karthikeyan et al.) also studied a different group of 1H-pyrazolo[3,4-b]quinoline derivatives (Figure 32) in the search for an anticancer drug [79,226]. 2-Methylpyrimido[1″,2″:1,5]pyrazolo[3,4-b]quinoline-4(1H)-one (Figure 32a) appeared to be the most active against colon cancer cells (HCT-116 and S1) and prostate cancer cells (PC3 and DU-145) at concentrations of 0.6–1.2 μM. At the same time, it was 10–15 times less cytotoxic to normal cells (canine kidney MDCK, mouse fibroblasts NIH/3T3 and human embryonic kidney HEK293/pcDNA.3.1.). 2-Methylpyrimido-[1″,2″:1,5]pyrazolo[3,4-b]quinoline-4(1H)-one was also found to be the most active in reversing the ABCG-2-mediated resistance to mitoxantrone, doxorubicin and cisplatin, which are common anticancer drugs. Mutations in Ras proteins are able to lead to unregulated cell division and are found in a significant number of human cancers [227]. For this reason, the identification of drugs that inhibit, either directly or indirectly, the transforming activity of the Ras protein is important in the search for an effective treatment of cancer [228]. 6-Methoxy-4-[2-[(2-hydroxyethoxyl)ethyl]amino]-3-methyl-1H-pyrazolo[3,4-b]quinoline (SCH 51344, Figure 33) was one of the compounds that was tested as a possible ras-transformation inhibitor. Kumar et al. carefully studied the mechanism of inhibition [229,230,231,232]. Pyrazoloquinoline SCH 51344, specifically, inhibits the RAS-mediated cell morphology pathway (H-, K- and N-RAS V12-induced membrane ruffling). The treatment of RAS-transformed cells with SCH 51344 restored organised actin filament bundles. Moreover, the anchorage-independent growth of K-RAS, which transformed NIH 3T3 cells and human colon and pancreatic tumor-derived cells (DLD-1, Panc-1, SW-480), was inhibited by SCH 51344. The authors also show that SCH 51344 is not cytotoxic to normal cells. Their studies show that the compound selectively suppressed oncogene-transformed growth without the gross effect on the normal signalling pathway. Gelman et al. also found that SCH 51344 suppresses src-, ras- and raf-induced oncogenic transformation by more than 90% at a 40 μM concentration of the pyrazoloquinoline [233]. The oncogenic growth potentials of rat-6/ras and /raf are more sensitive to SCH 51344 than rat-6/src cells because they are more dependent on pathways that are blocked by the compound. (S)-Crizotinib was tested as an anticancer drug by Huber et al., and the obtained results were compared to (R) enantiomer and SCH 51344 [234,235]. The authors, by using the proteomic approach, identified the target of SCH 51344 as the human mutT homologue MTH1 (NUDT1). The analysis of that pyrazoloquinoline was only one step to the main goal, which was the study concerning (S)-crizotinib. SCH 51344 was also one of the compounds that was tested by Ursu and Waldman as a small molecule target that binds to MTH1, with a comparison to (R)- and (S)-crizotinib [236]. The authors tested a few molecules of different structures by linker-based target identification techniques. The authors attached SCH 51344 to sepharose and proved that MTH1 is a primary target of the compound. The result was also confirmed in vitro by isothermal titration calorimetry and an MTH1 catalytic assay. SCH 51344 (6-methoxy-4-[2-[(2-hydroxyethoxyl)ethyl]amino]-3-methyl-1H-pyrazolo[3,4-b]quinoline) is now commercially available as an MTH1 inhibitor [237]. It is in use as one of the reference compounds in research that concerns anticancer drugs [238,239,240,241,242,243]. Different pyrazoloquinoline derivatives, functionalized with ribose or morpholine moieties (Figure 34), have been also tested as antitumor agents [244,245,246]. The mechanism of inhibition is probably the binding to an allosteric region of the Ras p21 protein, which leads to conformational change and prevents the binding of 3H-GDP to the protein.The best results have been obtained for 1-[4-chloro-3-methyl-6-methoxy-1H-pyrazolo[3,4-b]quinolinyl]-1-riboburanoside-tribenzoate,-tris(2-furoate),-4-(E-2-benzoylethenyl),4-[(1-hydroxy-2-benzoyl)ethyl]-2,3-thiocarbonate: a >70% inhibition at 10, 10.5, 10 and 1.5 μM concentrations, respectively. For the morpholine series, eight derivatives showed >70% inhibition at a <10μM concentration. One of the ways of anticancer drug action is by inducing the apoptosis of tumor cells [247]. 4-Phenylamino pyrazolo[3,4-b]quinolines, which have been tested for their antiviral activity [194,198], have also brought attention to themselves as potential apoptosis inducers. Zhang et al. tested a group of N-phenyl-1H-pyrazolo-[3,4-b]quinolin-4-amines (Figure 35) as potent apoptosis inducers [57]. The authors tested the activity of the synthesised derivatives against the human breast cancer (T47D), colon cancer (HCT116) and liver cancer (SNU 398) cell lines in vitro. The most active against the chosen cancer cells appeared to be 1,3-dimethyl-N-(4-propionylphenyl)-1H-pyrazolo[3,4-b]quinolin-4-amine (Figure 35, X = NH, R1,R2 = Me, R3 = COEt, R4 = H), which was about 6 ÷ 13-fold more potent than the reference, N-(4-acetylphenyl)-2,3-dihydro-1H-cyclopenta[b]quinolin-9-amine. The authors also tested the cell proliferation activity of the same compound and they again obtained very promising results; however, the research has not been continued. 4.6. Antiparasitic Activity Al-Qahtani et al. tested the effect of the series of pyrazoloquinoline derivatives that were obtained earlier by Bekhit et al. [215] (Figure 25) on the growth of Leishmania donovani protozoan parasites [248]. The L. donovani (strain DD8) were cultures in Schneider’s medium with four different concentrations of drugs (50–400 μM), and they were compared to Amphotericin B-treated cells and to an untreated control. The results indicate that some of the derivatives exhibited an activity that was comparable to the classic drug Amphotericin B; however, the effect was observed after 12 h compared to 6 h for Amph. B. The research has been never repeated. 4.7. Treatment of Schizophrenia As schizophrenia is affecting circa 1% of the world’s population [249], and because the already existing drugs enable only a small portion of patients to lead independent lives, there is still the need for improved treatment of schizophrenia. Antipsychotic drugs, which are used in the treatment of schizophrenia, are mostly dopamine 2 (D2) receptor antagonists [250]. PDE10, which is a dual cAMP/cGMP phosphodiesteraze, and which belongs to a family of degradative enzymes that hydrolyse the second messengers that terminate signal transduction, is expressed at high levels in the striatal medium spiny neurons. The inhibition of PDE10, and the following blocking of the degradation of cGMP and cAMP, should mimic the effect of a D2 receptor antagonist and a D1 receptor agonist, which is an ideal profile for an antipsychotic drug. A wide family of different pyrazoloquinoline derivatives was tested in the search for potent PDE10 inhibitors for the treatment of schizophrenia. In the first group, which was analyzed by Yang et al. and Ho et al. [91,92], 3-methyl-1H-pyrazolo[3,4-b]quinolines could be found, which were substituted at position 4 with different saturated heterocyclic rings (Figure 36). The synthesised compounds were tested for their affinity to the cloned human recombinant, PDE10A1, by measuring their ability to compete with [3H]cAMP. The strongest binding affinities were obtained for one pyrrolidine derivative (Figure 37a), three morpholine-derivatized compounds (Figure 37b) and three 1,4-oxazepane-derivatives (Figure 37c) with Ki 0.6–5 nM. One of the following, N-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]-methylmorpholine, was used for co-crystallisation with PDE10A, and the obtained crystals were studied with XRD. The second group was obtained by Ho et al. [92] and it is presented in Figure 38. The strongest binding affinities were obtained for one 1,4-oxazepane-derivative derivative (Figure 39a), one piperazine-derivative (Figure 39b), three piperidine-derivatized compounds (Figure 39c), one pyridyne-derivative (Figure 39d) and one morpholine-derivatised compound (Figure 39e) with Ki 0.6–5 nM. One of the tested piperazine derivatives had been co-crystallised with PDE10A. Both author groups (Yang et al. and Ho et al.) state that they had been planning to perform in vivo evaluations; however, we could not find any further results concerning the pyrazoloquinolines described above. In the different families of pyrazoloquinoline derivatives, the moiety in position 4 was secondary alcohol with an aromatic moiety (Figure 40) or some other substituents (they are not presented here because of worse results). The most potent in in vitro binding to PDE10A appeared to be 4-[(4-pyridyl)hydroxymethyl]- and 4-[[4-(3-fluoropyridyl)] hydroxymethyl]-6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinoline, with a Ki equal to 0.06–0.07 nM. The first of them was explored extensively by Wu et al. by 3D-QSAR, molecular docking and molecular dynamics simulations [251], together with other derivatives that were obtained by McElroy et al. [93]. Three of the derivatives: 4-[(4-pyridyl)hydroxymethyl]-6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinoline, 1-[6-methoxy-3,8-dimethyl-1H-pyrazolo-[3,4-b]quinolinyl]methyl-4-fluoropiperidine and 1-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]-quinolinyl]-4-methoxypiperidine, which were studied earlier [91,92,93], have been used as the reference compounds in the search for new PDE10A inhibitors on the basis of the quinazoline derivatives [252]. 4.8. Treatment of Diabetes Type 2 diabetes is now one of the most prevalent metabolic diseases worldwide [253]. Patients with type 2 diabetes are insulin resistant, and so there is still a need to find drugs that can help to increase insulin sensitivity. C-Jun N-terminal kinase-1 (JNK1) is one of the mitogen-activated protein kinases that probably plays a key role in linking insulin resistance and obesity [254]. Liu et al. synthesised a group of 1,9-dihydro-9-hydroxy pyrazolo[3,4-b]quinolin-4-ones derivatives (Figure 41) and tested themas JNK inhibitors [255]. All of the obtained compounds were tested in a JNK1 enzymatic inhibition assay and in a cell-based assay by measuring the inhibition of the TNFα (tumor necrosis factor)-stimulated phosphorylation of c-Jun in HepG2 (human liver cancer) cells. The most potent (JNK1 IC50 < 1 μM) appeared to be derivatives with R = H, R2 = Me and R1 = Et, and Bu, (CH2)3CONHMe, (CH2)2NHCOMe, (CH2)3NHCONHEt or (CH2)2NHCOOEt. The authors were also able to grow the co-crystals of one of the derivatives (R = H, R1, R2 = Me, JNK1 IC50 = 1.22 μM), bound into the ATP site of JNK1, and they analysed the interactions between the protein and the inhibitor. The most potent against JNK1 and also Pc-Jun proved to be the compound that was serendipitously found by the authors who tried to convert carboxylic acid to amine (Figure 42). 4.9. Benzodiazepine Receptor Inhibitor The group of pyrazoloquinolines that were substituted by fusing the pyrazol ring with a purine moiety were synthesised by the funcionalisation of 3-amino-1H-pyrazolo-[3,4-b]quinoline derivatives by El-Sayed et al. (Figure 43) [256]. The authors tested the benzodiazepine receptor (BZR) binding affinity of nine different derivatives, and they observed the best results for 2-thienyl substituent at the 2 position: an 83% inhibition of specific [3H]Ro15-1788 (Flumazenil) binding at a 10 μM concentration was achieved for 2-(2-thienyl)quinolino[2′,3′-5,4](3-pyrazolino)[3,2-b]purin-4-one (R1 = H, R2 = 2-thienyl). It is important to say that the Ki value for the tested compound is three levels of magnitude higher than that found for Flumazenil. The authors have not continued their research. A different group of pyrazoloquinoline derivatives (Figure 44) were tested by Cappelli et al. as translocator protein (TSPO) ligands [257]. TSPO is an alternative binding site of diazepam [258]; however, what is more important is that a dramatic increase in the TSPO density occurs in glial cells in response to brain inflammation or injury. Many neuropathological conditions (e.g., Alzheimer’s disease, Parkinson’s disease) also increase the TSPO density [259]. The authors decided to synthesise the pyrazoloquinolines that are shown in Figure 44 because they are structurally similar to alpidem, which is a known drug that is used for the treatment of anxiety [260]. The authors performed in vitro binding experiments to rat cerebral cortex membranes together with in vivo light/dark box tests in mice (for the most promising derivatives). Both experiments showed that the highest TSPO binding affinities were achieved in vitro by N-R2-2-[2-(4-X-phenyl)-4-methyl-3-oxo-2H-pyrazolo[3,4-b]quinolin-9(3H)-yl]-N-R1-acetamides (Figure 44b). The IC50 values for all of these derivatives were lower than 1 nM. Moreover, the antianxiety activity of one of the derivatives (N-butyl-2-[2-phenyl-4-methyl-3-oxo-2H-pyrazolo[3,4-b]quinolin-9(3H)-yl]-N-methylacetamide) was high, at 10 mg/kg dose, which was comparable to the value that was found for emapunil with the same dose, and for diazepam with a 1 mg/kg dose. The biological activity studies were combined with a detailed structural analysis, including XRD and computational calculations. The obtained results indicate that these group of pyrazoloquinoline derivatives could be a group of new TSPO modulators, and that they are worth further research. 4.10. Singlet-Oxygen-Generating Activity for SPA A scintillation proximity assay (SPA) is a biochemical screening radio-isotopic method that is used for the sensitive and rapid measurement of a broad range of biological processes [261]. Pai et al. used 4-[(4-aminophenyl)sulfanyl]-6-methoxy-3-methyl-1H-pyrazolo[3,4-b]quinoline (SCH 46891), which was obtained earlier by Afonso et al. [212], as one of the tested potent inhibitors of the phosphopeptide binding to the growth factor receptor-bound protein 2 (Grb2) SH2 domain [262]. The studies reveal that the inhibition of the Grb2 SPA by SCH 46891 was light-dependent. The compound was inactive when the assay plates were kept dark. The same light-dependent inhibition property was found for the tyrosine-protein kinase (Syk) SH2 domain via SPA. The authors concluded that the light-dependent inhibition mechanism is based on the singlet-oxygen-generating property of SCH 46891 upon irradiation (positive reaction with singlet oxygen trap 2-methylfuran, and the suppression of the inhibition activity by singlet oxygen quenchers). 4.11. Pregnancy Interceptive In 1991, Mehrotra et al. [263] tested 3-amino-6,7-dimethoxy-1H-pyrazolo-[3,4-b]quinoline as a potential pregnancy interceptor in vivo in hamsters and guinea pigs. When the compound was used in the early postimplantation schedule, it interrupted the pregnancy partially; however, it was ineffective in the preimplantation schedule. The same compound was tested in vitro on growing trophoblasts, and it appeared to prevent growth and to cause the degeneration of the cells. The results led the authors to the conclusion that the compound intercepts pregnancy probably through a direct effect on the embryo attachment site. The research was never continued or repeated with that, nor with any other pyrazoloquinoline derivative. 5. Conclusions In summary, the main aim of this review was to introduce readers to the methods and procedures that are used for the 1H-pyrazolo[3,4-b]quinoline skeleton synthesis, and to familiarize them with some of the photophysical and biological properties. The work is based on publications that appeared in the years 1911–2021. During this period, approx. 350 publications and patents were published, and, to the best of our knowledge, this is the first study of this type. We wanted to collect, in this review, all of the most important synthetic methods to create a kind of guide for researchers who are involved in the synthesis of nitrogen-condensed heterocycles, and who may decide to direct their interests there. By studying the development of the synthetic methods of 1H-pyrazolo[3,4-b]quinolines over the last one hundred years, a significant revolution in the approach to preparative methods can be noticed, and especially in the last ten years. In the initial period, syntheses based on classical reactions (e.g., the Friedländer condensation or modifications of the Niementowski reaction) were used. Nowadays, an increasing number of publications can be found that describe three-/four-component reactions, and reactions that are carried out in an aqueous environment with the use of a microwave field, or with ultrasounds and ionic liquids, which are catalysed with palladium compounds and nanoparticles, or that are even mediated with baker’s yeast. All of these procedures are part of the so-called “green chemistry”. These methods lead to the synthesis of the basic skeleton, as well as functionalized systems, which offer further possibilities for structural modifications with hydroxyl, halogen or amino moieties. The latter aspect is especially important for chemists in the pharmaceutical industry. The first synthesised 1H-pyrazolo[3,4-b]quinolines attracted the attention of researchers with their emissive properties, and they were applied as optical brighteners in the 1960s. Later studies show that, in some cases, the quantum yield of the fluorescence was equal to one, and that, in addition, these compounds turned out to be very resistant to temperature or oxidation. For this reason, they were used as emission materials for the fabrication of organic light-emitting diodes (OLEDs) that work on the basis of the phenomenon of fluorescence. In recent years, however, very efficient emissive materials that are based on the phenomenon of phosphorescence or thermally activated delayed fluorescence TADF have appeared, and so it should not be expected that pyrazoloquinolines will be used in the future to fabricate OLEDs. However, by taking into account their very good emissive properties and their stability, it can be expected that they will be used as fluorescent sensors for various analytes, as dyes for synthetic fibers, as dyes for fluorescence microscopy or as materials for the security features of banknotes based on fluorescence. The third aspect of the use of pyrazoloquinolines are their biological properties, which have been studied since the 1970s, and which were started by Siminoff and Crenshaw, who investigated the antimalarial properties of these compounds. Currently, the spectrum of biological properties is much broader and includes a variety of tests, among which the research on antibacterial, antiviral and anticancer properties is at the forefront. This resulted in, among other things, the commercialization of some preparations, such as, for example, 6-methoxy-4-[2-[(2-hydroxyethoxyl)ethyl]amino]-3-methyl-1H-pyrazolo[3,4-b]quinoline, which is now commercially available as an MTH1 inhibitor. Therefore, further studies towards the investigation of novel pharmacologically active 1H-pyrazolo[3,4-b]quinolines are highly desirable. Acknowledgments I would like to thank Piotr Tomasik for many years of cooperation and for introducing me to the fascinating world of heterocyclic chemistry (A.D.). The authors (A.D.; E.G; M.K.; P.S.) would like to thank the Krakow University of Technology and the University of Agriculture in Krakow for the financial support. Author Contributions Conceptualisation, A.D.; writing—the synthetic part, A.D. and M.K.; schematic drawing for the synthetic part, E.G.; writing—the photophysical part, A.G.; writing—the pharmacological part, P.S. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Conflicts of Interest The authors declare no conflicts of interst. Figures and Schemes Figure 1 The structure of 1H-pyrazolo[3,4-b]quinoline. Figure 2 Various 1H-pyrazolo[3,4-b]quinoline structures. Figure 3 Various methods for constructing the 1H-pyrazolo[3,4-b]quinoline carbon skeleton. Figure 4 Path 1: C21: C4-C3a; N9-C9a. molecules-27-02775-sch001_Scheme 1 Scheme 1 The Friedländer condensation leading to quinoline derivatives. molecules-27-02775-sch002_Scheme 2 Scheme 2 The first attempt at the Friedländer synthesis of 1H-pyrazolo[3,4-b]quinolines [2]. molecules-27-02775-sch003_Scheme 3 Scheme 3 Friedländer-based synthesis of 1H-pyrazolo[3,4-b]quinolines—an extension. molecules-27-02775-sch004_Scheme 4 Scheme 4 Synthesis of spirobifluorene-based 1H-pyrazolo[3,4-b]quinolines. Figure 5 Path 2: C22: C4-C4a; N9-C8a. molecules-27-02775-sch005_Scheme 5 Scheme 5 1H-Pyrazolo[3,4-b]quinoline synthesis from 2-amino-4-pyrazolecarbaldehyde. molecules-27-02775-sch006_Scheme 6 Scheme 6 1H-Pyrazolo[3,4-b]quinoline synthesis from pyrazolo[3,4-d]pyrimidine derivatives. molecules-27-02775-sch007_Scheme 7 Scheme 7 Niementowski’s quinoline synthesis. molecules-27-02775-sch008_Scheme 8 Scheme 8 An attempt to apply anthranilic acid for 4-hydroxy-1H-pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch009_Scheme 9 Scheme 9 Indirect use of anthranilic acid in synthesis of 1H-pyrazolo[3,4-b]quinolines. molecules-27-02775-sch010_Scheme 10 Scheme 10 4-chloro/hydroxy derivatives of pyrazoloquinolines as a source for biologically active compounds. molecules-27-02775-sch011_Scheme 11 Scheme 11 N-Arylamide of anthranilic acid as a source for pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch012_Scheme 12 Scheme 12 Hydrazide of anthranilic acid as a precursor for pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch013_Scheme 13 Scheme 13 Synthesis of pyrazolo[3,4-b]quinoline based on ethyl ester of 3-amino-4-carboxyethylpyrazole. molecules-27-02775-sch014_Scheme 14 Scheme 14 3-Amino-4-pyrazolo carbocylic acid and its ester as a source for pyrazoloquinoline synthesis. molecules-27-02775-sch015_Scheme 15 Scheme 15 5-Amino-2-methyl-pyrazole-3,4-dicarbonitrile in the synthesis of pyrazolo[3,4-b]quinoline derivatives. molecules-27-02775-sch016_Scheme 16 Scheme 16 The Pfitzinger synthesis of quinoline. molecules-27-02775-sch017_Scheme 17 Scheme 17 Synthesis of pyrazolo[3,4-b]quinolines from isatine. Figure 6 Path 3: C23: N9-C9a; C4-C4a. molecules-27-02775-sch018_Scheme 18 Scheme 18 Synthesis of 1H-pyrazolo[3,4-b]quinolines, according to Brack’s protocol. molecules-27-02775-sch019_Scheme 19 Scheme 19 The possible mechanism of Brack’s synthesis. molecules-27-02775-sch020_Scheme 20 Scheme 20 An alternative mechanism of Brack’s 1H-pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch021_Scheme 21 Scheme 21 Synthesis of 1H-pyrazolo[3,4-b]quinolines based on 4-aroyl-5-chloropyrazoles. molecules-27-02775-sch022_Scheme 22 Scheme 22 Reaction of phenylhydrazine with 4-acetyl-5-chloro-3-methyl-1-phenylpyrazole. molecules-27-02775-sch023_Scheme 23 Scheme 23 Synthesis of 10H-pyrido[2,3-h]pyrazolo[3,4-b]quinoline. molecules-27-02775-sch024_Scheme 24 Scheme 24 Synthesis of pyrazolo[3,4-b]quinolines from 4-benzylidenepyrazol-3-ones and anilines. Figure 7 Path 4; C24: C4-C3a; N9-C8a. molecules-27-02775-sch025_Scheme 25 Scheme 25 Synthesis of pyrazolo[3,4-b]quinolines from 3-aminopyrazoles and halogenated aromatic aldehydes. molecules-27-02775-sch026_Scheme 26 Scheme 26 Synthesis of pyrazolo[3,4-b]quinolines from 3-aminopyrazoles and orto-chloro/bromo benzoic acid. molecules-27-02775-sch027_Scheme 27 Scheme 27 Application of β-bromovinyl aldehyde in synthesis of 1H-pyrazolo[3,4-b]quinolines. molecules-27-02775-sch028_Scheme 28 Scheme 28 Benzyl alcohol derivatives as a substrate for pyrazolo[3,4-b]quinoline synthesis. Figure 8 Path 5; C25:N1-C9a; N2-C3. molecules-27-02775-sch029_Scheme 29 Scheme 29 Synthesis of 5-chloro-4-formyloquinolies, according to Meth-Cohn protocol. Figure 9 Some heterocycles prepared from 2-chloro-4-formyl quinoline [64]. molecules-27-02775-sch030_Scheme 30 Scheme 30 1H-Pyrazolo[3,4-b]quinoline syntheses from 2-chloro-3-formylquinolines [61]. molecules-27-02775-sch031_Scheme 31 Scheme 31 Synthesis of benzo[h]pyrazolo[3,4-b]quinolines. molecules-27-02775-sch032_Scheme 32 Scheme 32 Synthesis of 1H-benzo[g]pyrazolo[3,4-b]quinoline-3-ylamine. molecules-27-02775-sch033_Scheme 33 Scheme 33 Synthesis of ethyl 3-amino-1H-pyrazolo[3,4-b]quinoline-4-carboxylate. molecules-27-02775-sch034_Scheme 34 Scheme 34 Syntheses of 1H-pyrazolo[3,4-b]quinolines from 2-hydroxy-3-acylquinolines. molecules-27-02775-sch035_Scheme 35 Scheme 35 Synthesis of 4-methylthio-1H-pyrazolo[3,4-b]quinolines. molecules-27-02775-sch036_Scheme 36 Scheme 36 Syntheses of 2-methylthio-3-benzoyl-4-methylquinolines and related 1H-pyrazolo[3,4-b]quinolines. Figure 10 Path 6a; C26a: C4-C4a; C4-C3a. molecules-27-02775-sch037_Scheme 37 Scheme 37 Correction and verification of the Michaelis’ 1H-pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch038_Scheme 38 Scheme 38 Reactions of isocyanates and isothiocyanates with N-arylpyrazole with isolation of intermediate products. molecules-27-02775-sch039_Scheme 39 Scheme 39 Ring closure by Vilsmeier–Haack formylation reaction. Figure 11 Path 6b: C16b: C4-C4a. molecules-27-02775-sch040_Scheme 40 Scheme 40 Synthesis of 5-chloro-3-methyl-1H-pyrazolo[3,4-b]quinoline derivatives. Figure 12 Path 7; C17: N9-C3a. molecules-27-02775-sch041_Scheme 41 Scheme 41 o-Nitrobenzaldehyde as an equivalent for o-aminobenzaldehyde in the synthesis of pyrazolo[3,4-b]quinolines. molecules-27-02775-sch042_Scheme 42 Scheme 42 Investigation on Zolazepam metabolites. Figure 13 Path 8a; C4-C4a, C4-C3a, C8a-N9. Path 8b; C4-C4a, N9-C9a, C4-C3a. molecules-27-02775-sch043_Scheme 43 Scheme 43 The first three-component synthesis of 4-aryl-4,7,8,9-tetrahydro-6H-pyrazolo[3,4-b]quinolin-5-ones. molecules-27-02775-sch044_Scheme 44 Scheme 44 The first multicomponent synthesis of aromatic 1H-pyrazolo[3,4-b]quinolines. molecules-27-02775-sch045_Scheme 45 Scheme 45 Syntheses of benzo[h]pyrazolo[3,4-b]quinolin-5,6-diones and derivatives. molecules-27-02775-sch046_Scheme 46 Scheme 46 Syntheses of benzo[h]pyrazolo[3,4-b]quinolin-5,6-diones. molecules-27-02775-sch047_Scheme 47 Scheme 47 Three-component reactions catalysed by InCl3 in synthesis of linear pyrazolo[3,4-b]quinoline skeleton. molecules-27-02775-sch048_Scheme 48 Scheme 48 Synthesis of spiro[benzo[h]pyrazolo[3,4-b]quinoline-4,3′-indoline. molecules-27-02775-sch049_Scheme 49 Scheme 49 β-Tetralone as a substrate for benzo[f]pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch050_Scheme 50 Scheme 50 α-Tetralone as a substrate for benzo[h]pyrazolo[3,4-b]quinoline synthesis. molecules-27-02775-sch051_Scheme 51 Scheme 51 Three-component reaction with DMSO as source of C-4 atom in pyrazolo[3,4-b]quinoline skeleton. Figure 14 General structure and the light-induced formation of brightly emissive D-π-A pyrazoloquinoline species. Figure 15 Structures and photophysical properties of differently substituted 1H-pyrazolo[3,4-b]quinolines. The data presented were measured in chloroform [158]. Figure 16 Structures of pyrazoloquinoline-based cation-sensitive fluorescence probes: (a) aza-crown-modified derivatives, reported by Rurack in 2002 [5]; (b) PET-signalling derivatives, investigated by Mac et al. between 2010 and 2013 [175,176,177]. Figure 17 Schematic representation of 1H-pyrazolo[3,4-b]quinoline-based pH-sensitive ternary logic gate reported by Uchacz et al. in 2016 [178]. Figure 18 4-[(3-(R1,R2-Amino)propyloamino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinolines. Figure 19 (a) 4-[(3-(dimethylamino)propylamino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline; (b) 4-R2-1-methyl-3-R1-(5,6,7 or 8)-R3-1H-pyrazolo[3,4-b]quinoline; and (c) 4-[(3-(dimethylamino)propyloamino]-1,3,7-trimethyl-1H-pyrazolo[3,4-b]quinoline. Figure 20 4-(substituted-phenylamino)-1-R1-3-methyl-1H-pyrazolo[3,4-b]quinolines and 4-(4-substituted-pyrimidine-amino)-1-R1-3-methyl-1H-pyrazolo[3,4-b]quinolines. Figure 21 4,9-dihydro-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinolines. Figure 22 4-[(4-R-phenyl)amino]-1,3-dimethyl-1H-pyrazolo[3,4-b]quinoline. Figure 23 4-chloro-3-methyl-6-methoxy-1H-pyrazolo[3,4-b]quinoline (SCH 43478); 4-[[(furan-2-yl)methyl]sulfanyl]-3-methyl-6-methoxy-1H-pyrazolo[3,4-b]quinoline (SCH 46792); and (2S,3S)-2-amino-1-(4-chloro-6-methoxy-3-methyl-1H-pyrazolo[3,4-b]quinolin-1-yl)-3-methylpentan-1-one (SCH 49286). Figure 24 1H-Pyrazolo[3,4-b]quinoline derivatives examined by Bell and Ackerman in [214]. Figure 25 1H-Pyrazolo[3,4-b]quinoline derivatives examined by Bekhit et al. [215]. Figure 26 1-Substituted-3-amino-1H-pyrazolo[3,4-b]quinolines. Figure 27 3-amino-1-(5-nitro-2-furoyl)-6,7-ethylenedioxy-1H-pyrazolo[3,4-b]quinoline. Figure 28 6-amino-3-methyl-1,4-diphenyl-1H-pyrazolo[3,4-b]quinoline. Figure 29 1H-Pyrazolo[3,4-b]quinoline, synthesised and tested by Jitender et al. [83]. Figure 30 2-(4-phenyl-3-(trifluoromethyl)-1H-pyrazolo[3,4-b]quinolin-1-yl)-N-(2-(piperazin-1-yl) ethyl) acetamide. Figure 31 3-amino-1H-pyrazolo[3,4-b]quinoline derivatives tested by Karthikeyan et al. [225]. Figure 32 The structures of: (a) 2-methylpyrimido[1″,2″:1,5]pyrazolo[3,4-b]quinoline-4(1H)-one; and (b) 4-R-2-methylpyrimido[1″,2″:1,5]pyrazolo[3,4-b]quinolines. Figure 33 The structure 6-methoxy-4-[2-[(2-hydroxyethoxyl)ethyl]amino]-3-methyl-1H-pyrazolo-[3,4-b]quinoline (SCH 51344). Figure 34 Selected (most effective) 1-substituted-4-chloro-3-methyl-6-methoxy-1H-pyrazolo[3,4-b]quinoline derivatives. Figure 35 Pyrazolo[3,4-b]quinolines tested by Zhang et al. [57]. Figure 36 1H-Pyrazolo[3,4-b]quinolines synthesized and tested by Yang et al. and Ho et al. [91,92]. Figure 37 (a) N-[6-Methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]methyl-3-hydroxypyrollidine; (b) N-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]methyl-2-R1-morpholines; (c) N-[6-R2-8-methyl-1H-pyrazolo[3,4-b]quinolinyl]methyl-1,4-oxazepanes. Figure 38 1H-Pyrazolo[3,4-b]quinolines synthesized and tested by Ho et al. [92]. Figure 39 (a) 4-[6-Methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]-1,4-oxazepane; (b) 1-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]-4-carboxamid-3-methylpiperazine; (c) 1-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]-quinolinyl]-4-R-piperidines; (d) 4-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]methylpyridine; and (e) 2-[6-methoxy-3,8-dimethyl-1H-pyrazolo[3,4-b]quinolinyl]methylmorpholine. Figure 40 1H-Pyrazolo[3,4-b]quinolines synthesised and tested by McElroy et al. [93]. Figure 41 The structure of 1,9-dihydro-9-hydroxypyrazolo[3,4-b]quinolin-4-ones derivatives. Figure 42 The most potent unexpected product of acid derivatisation. Figure 43 1H-Pyrazolo[3,4-b]quinolines, synthesised and tested by El-Sayed et al. [256]. Figure 44 Pyrazoloquinoline derivatives obtained by Cappelli et al. [257]. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Michaelis A. Über 5-Aminopyrazole und über Iminopyrine. I. Über substituierte 5-Iminopyrazolone und über 5-Aminopyrazole Justus Lebigs Ann. Chem. 1911 385 1 43 10.1002/jlac.19113850102 2. Musierowicz A. Niementowski S. Tomasik Z. Kondensacja fenylo-1-metylo-3-okso-5[dwuchydropirazolu] i [chloro-2]-fenylo-1-metylo-3-okso-[dwuhydro-4,5-pyrazolu] z o-aminobenzaldehydem Roczn. Chemii 1928 8 325 344 3. Koćwa A. Reactions in the pyrazolone series. II. Reactions of arylimine derivatives of 1-phenyl-5-methyl-3-pyrazolone with carbanilide or phenyl isocyanate, α-naphthyl isocyanate, and thiocarbanilide or phenyl isothiocyanate Bull. Intern. Acad. Polon. Sci. 1936 382 389 4. Koćwa A. Reactions in the pyrazolone series. III. Reactions of arylimine derivatives of 1-phenyl-3-methyl-5-pyrazolone with carbanilide or phenyl isocyanate, α-naphthyl isocyanate, or with thiocarbanilide or phenyl isothiocyanate Bull. Intern. Acad. Polon. Sci. 1936 390 402 5. Rettig W. Rurack K. Danel A. Rotkiewicz K. Grabka D. Spieles M. 1,3-Diphenyl-1H-pyrazolo[3,4-b]quinoline: A versatile fluorophore for the design of brightly emissive molecular sensors Org. Lett. 2002 4 4647 4650 10.1021/ol027025i 12489951 6. Danel A. Gondek E. Kityk I. 1H-pyrazolo[3,4-b]quinoline and 1H-pyrazolo[3,4-b]quinoxaline derivatives as promising materials for optoelectronic applications Opt. Mater. 2009 32 267 273 10.1016/j.optmat.2009.09.008 7. Reimann E. Chinoline Houben-Weyl Methods of Organic Chemistry 4th ed. Hetarenes II-Part 1 Büchel K.H. Falbe J. Hageman H. Hanack M. Klamann D. Krecher R. Kropf H. Regitz M. Schaumann E. Georg Thieme Verlag Stutgart New York, NY, USA 1991 Volume E7a 290 493 8. Friedländer P. Ueber o-Amidobenzaldehyd Chem. Ber. 1882 15 2572 2575 10.1002/cber.188201502219 9. Marco-Contelles J. Perez-Mayoral E. Samadi A. Carreiras M.C. Soriano E. Recent advances in Friedlander reaction Chem. Rev. 2009 109 2652 2671 10.1021/cr800482c 19361199 10. Cheng C.-C. Yan S.-J. The Friedlander synthesis of quinolines Org. React. 1982 28 37 201 10.1002/0471264180.or028.02 11. Fallah-Mehrjarch M. Friedlander synthesis of poly-substituted quinolones: A mini review Mini-Rev. Org. Chem. 2017 14 187 196 10.2174/1570193X14666170206124809 12. Ramann G.A. Cowen B.J. Recent advances in metal-free quinoline synthesis Molecules 2016 21 986 10.3390/molecules21080986 27483222 13. Nainwal L.M. Tasneem S. Akhtar W. Verma G. Faraz Khan M. Parvez S. Shaquiquzzaman M. Akhter M. Amumtaz Alam M. Green recipes to quinoline: A review Eur. J. Med. Chem. 2019 164 121 170 10.1016/j.ejmech.2018.11.026 30594028 14. Abramovitch R. Tomasik P. Tomasik D. Friedländer Condensation of 1H-Pyrazolin-5-ones with o-Aminobenzaldehydes. Synthesis of 1H-Pyrazolo[3,4-b]quinolines J. Heterocycl. Chem. 1983 20 1539 1543 10.1002/jhet.5570200620 15. Kucybała Z. Przyjazna B. Linden L.-A. Paczkowski J. Developmnet of new dyeing photoinitiators for free radical polymerization based on 1H-pyrazolo[3,4-b]quinoline skeleton. IV Polym. Bull. 2000 45 327 334 10.1007/s002890070003 16. Danel A. Synthesis of Pyrazolo[3,4-b]quinolines as Luminophores for Electroluminecent Devices Ph.D. Thesis Jagiellonian University Krakow, Poland 1996 17. Sabitha G. Babu R.S. Reddy S.B.V. Yadav J.S. Microwave Assisted Friedländer Condensation Catalyzed by Clay Synth. Commun. 1999 29 4403 4408 10.1080/00397919908086603 18. Qu Y.-K. Zheng Q. Fan J. Liao L.-S. Jiang Z.-Q. Spiro compounds for organic-light emitting diodes Acc. Mater. Res. 2021 2 1261 1271 10.1021/accountsmr.1c00208 19. Salbeck J. Pudzich R. Fuhrmann T. Spiro compounds for organic electroluminescence and related applications Adv. Polym. Sci. 2006 107 1011 1065 10.1007/12_074 20. Chen C.-H. Wu F.-I. Shu C.-F. Chien C.-H. Tao Y.-T. Spirobifluorene-based pyrazoloquinolines: Efficient blue electroluminescent materials J. Mater. Chem. 2004 14 1585 1589 10.1039/b402584a 21. Caluve P. Heteroannulations with o–aminoaldehydes Tetrahedron 1980 36 2359 2407 10.1016/0040-4020(80)80218-3 22. Häufel J. Breitmaier E. Synthesis of Pyrazolo Heteroaromatic Compounds by Means of 5-Amino-3-methyl-1-phenylpyrazole-4-carbaldehyde Angew. Chem. Int. Ed. 1974 13 604 10.1002/anie.197406041 23. Jachak N.M. Avhale A.B. Medhane V.J. Toche R.B. A convenient route for the synthesis of pyrazolo[3,4-d]pyrimidine, pyrazolo[3,4-b][1,6]naphtiridine and pyrazolo[3,4-b]quinoline derivatives J. Heterocycl. Chem. 2006 43 1169 1175 10.1002/jhet.5570430506 24. Higashino T. Iwai Y. Hayashi E. Studies on Pyrazolo[3,4-d]pyrimidine Derivatives. IV. On 1-methyl- and 1-phenyl-1H-pyrazolo[3,4-d]pyrimidine 5-oxide Chem. Pharm. Bull. 1976 24 3120 3134 10.1248/cpb.24.3120 25. Niementowski S. Synthesen der Chinolinderivate Chem. Ber. 1894 27 1394 1403 10.1002/cber.18940270242 26. Ghosh T.N. Quinoline derivatives J. Indian Chem. Soc. 1937 14 123 126 27. Menzel K.H. Putter R. Wolfrum G. Synthesen und reaktionen neuer ortho-kondensierter pyrazoloverbindungen Angew. Chem. 1962 21 839 847 10.1002/ange.19620742110 28. Danel A. Tomasik P. Kappe T. Gheath A.H. Attempted Niementowski condensation of anthranilic acid and its ester with 3-methyl-1-phenylpyrazolin-5-one Polish J. Chem. 1996 70 302 309 29. Stein R.G. Biel J.H. Singh T. Antimalarials. 4-Substituted 1H-pyrazolo[3,4-b]quinolones J. Med. Chem. 1970 13 153 155 10.1021/jm00295a049 5412098 30. Crenshaw R.R. Luke G.M. Siminoff P. Interferon inducing activities of derivatives of 1,3-dimethyl-4-(3-dimethylaminopropyloamino)-1H-pyrazolo[3,4-b]quinoline and realted compounds J. Med. Chem. 1976 19 262 275 10.1021/jm00224a013 1249806 31. Kim D.H. Further studies on the reaction of N-(2-hydroxyphenyl)anthranilic acid wit acetic anhydride J. Heterocycl. Chem. 1981 18 1389 1392 10.1002/jhet.5570180722 32. Gal M. Feher Ö. Tihanyi E. Horvath G. Jerkovitch G. Argay G. Kálman A. The ring closure and rearrangement of 1-(2-amino)-benzoyl-1-methylhydrazones of β-dicarbonyl compounds: On the formation and crystal structure of 3a,9a-dihydro-1,3,3a,9a-tetramethyl-4H-pyrazolo[3,4-b]quinolin-4-one Tetrahedron Lett. 1980 21 1567 1570 10.1016/S0040-4039(00)92777-1 33. Nielsen S. Pedersen E.B. Synthesis of 4-arylamino-5,6,7,8-tetrahydro-1H-pyrazolo[3,4-b]quinolones and the corresponding N-Mannich bases Liebigs Ann. Chem. 1986 1986 1728 1735 10.1002/jlac.198619861006 34. Nielsen S. Pedersen E.B. Synthesis of 4-arylamino-5,6,7,8-tetrahydro-1H-pyrazolo[3,4-b]quinolones and 5,6,7,8-tetrahydrogenated analogs Chem. Scr. 1986 26 331 336 35. Gatta F. Pomponi M. Maurizio M. Synthesis of 7,8-dihydro-6H-pyrazolo[3,4-b]quinolin-5-ones and related derivatives J. Heterocycl. Chem. 1991 28 1301 1307 10.1002/jhet.5570280523 36. Campbell J.B. Firor J.W. Synthesis of tricyclic aminopyridines by a cadmium promoted cyclization J. Org. Chem. 1995 60 5243 5249 10.1021/jo00121a048 37. Deeb A. El-Mobayed M. Essawy A.N. El-Hamid A.A. Mohamid A. El-Hamid A. Heterocyclic synthesis from 3-amino-4-cyanompyrazole Collect. Czech. Chem. Commun. 1990 55 728 733 10.1135/cccc19900728 38. Silva D. Chioua M. Samadi A. Carreeiras C.M. Jimeno M.-L. Mendes E. De los Rios C. Romero A. Villarroya M. Lopez M.G. Synthesis and pharmacological assessment of diversity substituted pyrazolo[3,4-b]quinoline, and benzo[b]pyrazolo[4,3-g][1,8]naphtyridine Eur. J. Med. Chem. 2011 46 4676 4681 10.1016/j.ejmech.2011.05.068 21715067 39. Pfitzinger W. Chinolinderivate aus isatinsaure J. Prakt. Chem. 1886 33 100 10.1002/prac.18850330110 40. Shvekgheimer M.G.-A. The Pfitzinger reaction Chem. Heterocycl. Compd. 2004 40 257 294 10.1023/B:COHC.0000028623.41308.e5 41. Musante C. Fabbrini L. Contribution to the knowledge of malonyldiphenylhydrazine and its derivatives Gazz. Chim. Ital. 1954 84 595 605 42. Holla D.C. Seshadri S. A new synthesis of pyrazolo[3,4-b]quinoline derivatives Bull. Chem. Soc. Jpn. 1984 57 2984 2986 10.1246/bcsj.57.2984 43. Brack A. Uber kondensierte Pyrazolopyridine Liebigs Ann. Chem. 1965 681 105 110 10.1002/jlac.19656810117 44. Brack A. 1H-Pyrazolo[3,4-b]quinolines DE1186867 11 May 1962 45. Butler D.E. De Wald H.A. New general methods for the substitution of 5-chloropyrazoles. The synthesis of 1,3-dialkyl-5-chloropyrazol-4-yl aryl ketones and new 1,3-dialkyl-2-pyrazolin-5-ones J. Org. Chem. 1971 36 2542 2547 10.1021/jo00816a037 46. Obakachi V.A. Kushwaha N.D. Kushwata B. Mahlalela M.C. Shinde S.R. Kehinde I. Karpoormath R. Design and synthesis of pyrazolone-based compounds as potent blockers of SARS-CoV-2 viral entry into the host cells J. Mol. Struct. 2021 1241 130665 10.1016/j.molstruc.2021.130665 34007088 47. Wan W. Wang H. Lin H. Wang J. Jiang Y. Jiang H. Zhu S. Wang Z. Hao J. Synthesis, electrochemical, photohysical, and electroluminescent properties of organic dyes containing pyrazolo[3,4-b]quinoline chromophore Dyes Pigments 2015 121 138 146 10.1016/j.dyepig.2015.05.002 48. Porai-Koshits B.A. Kvitko I.Y. Shutkova E.A. Synthesis and transformations of chloropyrazolealdehydes Pharm. Chem. J. 1970 4 138 143 10.1007/BF00760971 49. Hennig L. Müller T. Grosche M. Syntheses von Pyrazolo[3,4-b]chinolinen aus 4-Aroyl-5-chloropyrazolen J. Prakt. Chem. 1990 332 693 698 10.1002/prac.19903320518 50. El-Shehry M. El-Telbani E.M. Swellem R. Synthesis of polyfunctional substituted pyrazoles J. Chem. Res. 2009 10 625 629 10.3184/030823409X12523423287039 51. Gonzales E. Elguero J. Action des hydrazines sur les acetyl-4-chloro-5(ou 3)methyl-3 (ou 5) pyrazoles: Formation d’une pyrazolo[3,4-b]quinoleine, d’hydrazzones et de cetazines J. Heterocycl. Chem. 1986 23 999 1001 10.1002/jhet.5570230405 52. Crenshaw R.R. Luke G.M. Whitehead D.F. Unexpected formation of a 10H-pyrido[2,3-h]pyrazolo[3,4-b]quinoline derivative, A new ring system J. Heterocycl. Chem. 1976 13 155 156 10.1002/jhet.5570130134 53. Chaczatrian K. Chaczatrian G. Danel A. Tomasik P. The synyhesis of 4-aryl-1H-pyrazolo[3,4-b]quinolines by cyclization of 4-arylidenepyrazolin-5-ones with anilines ARKIVOC 2001 VI 63 69 10.3998/ark.5550190.0002.605 54. Hamama S.W. El-Gohary H.G. Soliman M. Zoorob H.H. A versatile synthesis, PM-3-Semiempirical, antibacterial, and antitumor evaluation of some bioactive pyrazoles J. Heterocycl. Chem. 2012 49 543 554 10.1002/jhet.806 55. Szlachcic P. Kucharek M. Jarosz B. Danel A. Stadnicka K. Facile and regioselective synthesis of substituted 1H-pyrazolo[3,4-b]quinolones from 2-fluorobenzaldehydes and 1H-pyrazol-5-amines J. Heterocycl. Chem. 2016 54 1729 1745 10.1002/jhet.2751 56. Abramov M.A. Ceulemans E. Jackers C. Van der Auweraer M. Dehaen W. Reactions of 5-amino-1,2-azoles with aromatic and heterocyclic o-chloroaldehydes:[1+1] versus [2+1] cyclocondensation Tetrahedron 2001 57 9123 9129 10.1016/S0040-4020(01)00917-6 57. Zhang H.-Z. Classen G. Crogran-Grundy C. Tsneg B. Drewe J. Cai S.X. Discovery and structure—Activity relationship of N-phenyl-1H-pyrazolo[3,4-b]quinolin amines as a new series of potent apoptosis inducers Bioorg. Med. Lett. 2008 16 222 231 10.1016/j.bmc.2007.09.046 58. Pamukcu R. Piazza A. Method for Inhibiting Neoplastic Cells by Exposure to Substituted N-cycloalkylmethyl-1-H-pyrazolo[3,4-b]quinoline-4-amines U.S. Patent 5,942,520 24 August 1999 59. Shekarro K. Kaishap P.P. Saddanapu A.A. Gogoi S. Boruah R.C. Microwave—Assisted palladium mediated efficient synthesis of pyrazolo[3,4-b]pyridines, pyrazolo[3,4-b]quinolines, pyrazolo[1,5-a]pyrimidines and pyrazolo[1,5-a]quinazolines RSC Adv. 2014 4 24001 10.1039/C4RA02865A 60. De Wald H. 9-Substituted-4,9-dihydro-1,3,4,4-tetraalkyl-1H-pyrazolo[3,4-b]quinolines U.S. Patent 3,790,576 5 February 1974 61. Meth-Cohn O. Narine B. Tarnowski B. A versatile new synthesis of quinolones and related fused pyridines, Part 5. The synthesis of 2-chloroquinolne-3- carbaldehydes J. Chem. Soc. Perkin Trans. 1 1981 1520 1530 10.1039/p19810001520 62. Hayes R. Meth-Cohn O. A versatile new synthesis of quinolones and realted fused pyridines. Part 10. Routes to quinolines with fused azacycles Tetrahedron Lett. 1982 23 1613 1615 10.1016/S0040-4039(00)87172-5 63. Marson C.M. Reactions of carbonyl compounds with(monohalo) methyleniminium salts (Vilsmeier reagents) Tetrahedron 1992 48 3659 3726 10.1016/S0040-4020(01)92263-X 64. Meth-Cohn O. The synthesis of pyridines, quinolones and other realted systems by the Vilsmeier and the reversed Vilsmeier method HeteroCycles 1993 35 539 557 10.3987/REV-92-SR4 65. Bhat B.N. Bhaduri A.P. Syntheses of substituted pyrazolo[3,4-b]quinolines, 3,4-dihydro-4-oxopyrimido[4′,5′:4,5]thieno[2,3-b]quinoline and pyrido[1′,2′:1,2]pyrimido[4,5-b]quinoline J. Heterocycl. Chem. 1986 23 925 928 10.1002/jhet.5570230352 66. Rajendran S.P. Manomani M. Vijayalakshmi S. Synthesis of pyrazolo[3,4-b]quinolines and their 1-phenyl derivatives Org. Prep. Proceures Int. 2009 26 383 385 10.1080/00304949409458445 67. Kidwai M. Negi N. Synthesis of some novel substituted quinolones as potent analgesic agents Monatsh. Chem. 1997 128 85 89 10.1007/BF00807642 68. Mogilaiah K. Sudhakar G.R. Reddy N.V. Microwave assisted synthesis of pyrazolo[3,4-b]quinoline containing 1,8-naphtyridine moiety Indian J. Chem. 2003 42B 1753 1755 69. Selvi S.T. Nadaraj V. Mohan S. Sasi R. Hema M. Solvent free synthesis and evaluation of antimicrobial activity of pyrimido[4,5-b]- and pyrazolo[3,4-b]quinolines Bioorg. Med. Lett. 2006 14 3896 3903 10.1016/j.bmc.2006.01.048 70. Mali J.R. Pratap U.R. Jawale D.V. Mane R.A. Water mediated one-pot synthetic route for pyrazolo[3,4-b]quinolines Tetrahedron Lett. 2010 51 3980 3982 10.1016/j.tetlet.2010.05.117 71. Paul S. Gupta M. Gupta R. Loupy A. Microwave assisted solvent free synthesis of pyrazolo[3,4-b]quinolones and pyrazolo[3,4-c]pyrzoles using p-TsOH Tetrahedron Lett. 2001 42 3827 3829 10.1016/S0040-4039(01)00505-6 72. El-Bordany E.A. Aziz A.A. Abou-Elmagd W.S.I. Hashem A.I. Synthesis and spectroscopic characterization of some novel pyrazoloquinoline, pyrazolotetrazine and thiazolidinone derivatives J. Heterocycl. Chem. 2018 55 291 296 10.1002/jhet.3048 73. Munir R. Javid N. Zia-ur-Rehman M. Zaheer M. Huma R. Roohi A. Athar M.M. Synthesis of novel N-acylhydrazones and their C-N/N-N bond conformational characterization by NMR spectroscopy Molecules 2021 26 4908 10.3390/molecules26164908 34443493 74. Teixeira F.C. Lucas C. Curto M.J.M. Andre V. Duarte T.M. Teixeira A.P.S. Synthesis of novel pyrazolo[3,4-b]quinoline—Bisphosphonic acids and unexpected intramolecular cyclization and phosphonylation reaction Org. Biomol. Chem. 2021 19 2533 2545 10.1039/D1OB00025J 33666215 75. Chavan A.S. Kharat A.S. Bhosle M. Dhumal S.T. Mane R.A. Water mediated and Baker yeast accelerated novel synthestic prtocols for tetrahydrobenzo[a]xanthene -11-ones and pyrazolo[3,4-b]quinolones Synth. Commun. 2021 51 1963 1973 10.1080/00397911.2021.1913606 76. Kerry M. Boyd G.W. Mackay S.P. Meth-Conh O. Platt L. The synthesis of benzo[h]quinolones as topomerase inhibitors J. Chem. Soc. Perkin Trans. 1 1999 2315 2321 10.1039/a903402a 77. Parekh N.M. Sahoo S.K. Maheiria K.C. Qunatum chemical studies and dyeing performance of some novel benzoquinoline based heterocyclic monoazo dyes on polyester fiber Dye. Pigment. 2012 95 142 148 10.1016/j.dyepig.2012.03.014 78. Parekh N.M. Maheira K.C. Synthesis of heterocyclic monoazao dyes derived from 1H-benzo[g]pyrazolo[3,4-b]quinoline-3-ylamine: Their antimicrobial activity and their dyeing performance on various fibers Res. Chem. Intermed. 2012 38 885 901 10.1007/s11164-011-0426-4 79. Karthikeyan C. Lee C. Moore J. Mittal R. Suswam E.A. Abbot K.L. Pondugula S.R. Manne U. Narayanan N.K. Trivedi P. IND-2, a pyrimido[1″,2″:1,5]pyrazolo[3,4-b]quinoline derivative circumvents multi-drug resistance and causes apoptosis in colon cancer cells Bioorg. Med. Chem. 2015 23 602 611 10.1016/j.bmc.2014.11.043 25537531 80. Yoshida K. Otomasu H. Synthesis of 1H-pyrazolo[3,4-b]pyridine and related compounds Yakugaku Zasshi 1976 96 33 36 10.1248/yakushi1947.96.1_33 943506 81. Arasakumar T. Mathusalini S. Lakshmi K. Mohan S.P. Ata A. Lin C.-H. An object oriented synthetic approach toward angular and linear fused pyrazoloquinolines of biological importance with InCl3 catalyst Synth. Commun. 2016 46 232 241 10.1080/00397911.2015.1133827 82. Vostrova L.N. Gerenga S.A. Kiridenk A.M. Grenaderowa M.V. Kharchenko S.L. Abramovitch A.E. Dimitrieva T.N. 2-Heterylquinoline derivatives Ukr. Chim. Zh. 1992 58 578 781 83. Jintender Dev G. Poornachandra Y. Reddy K.R. Kumar R.N. Ravikumar N. Swaroop K. Ranjithreddy P. Kumar G.S. Nanubolu J.B. Ganesh K. Synthesis of novel pyrazolo[3,4-b]quinolinyl acteamide analogs, their evaluation for antimicrobial and anticancer activities, validation by molecular modelling and COMFA analysis Eur. J. Med. Chem. 2017 130 223 239 10.1016/j.ejmech.2017.02.052 28254697 84. Hassan M.M. Othman E. Abass M. Substituted quinolinones. 18. 3-Acetl-4-methylthiquinolin-2(1H)-one as useful synthon intermediate for synthesis of some new quinolinones Res. Chem. Intermed. 2013 39 1209 1225 10.1007/s11164-012-0678-7 85. Abass M. Hassanin H.M. Allimony H. Hassan H. Substituted quinolinones.27. Regioselctive synthesis of pyrazolo-, oxazolo-, and trazepinoquinoline derivatives Chem. Heterocycl. Compd. 2015 51 1023 1029 10.1007/s10593-016-1813-y 86. Mahat P.K. Venkatesh C. Kumar U.K.S. Ila H. Junjappa H. Reaction of α-oxoketene-N,S-arylaminoacetals with Vilsmeier Reagents: An efficient route to highly functionalized quinolones and their benzo/hetero-fused analogues J. Org. Chem. 2003 68 3966 3975 10.1021/jo034053l 12737579 87. Danel A. Chaczatrian K. Tomasik P. Microwave-assisted, facile route to 1H-pyrazolo[3,4-b]quinolines ARKIVOC 2000 I 51 57 10.3998/ark.5550190.0001.108 88. Kucharek M. Danel A. Palladium catalysed amino group arylation of 1,3-disubstituted-1H-pyrazolo-5-amine based on Buchwald-Hartwig reaction Chem. Heterocycl. Compd. 2021 57 633 639 10.1007/s10593-021-02961-z 89. Purnaprajna V. Seshadri S. Studies in the Vilsmeier—Haack reaction: Part XII. Synthesis of the 2-phenylpyrazolo[3,4-b]quinoline system Indian J. Chem. Sect B 1976 14B 971 972 10.1002/chin.197726273 90. Kucharek M. Danel A. Gut A. Synthesis of 1,3,6-trisubstituted -1H-pyrazolo[3,4-b]quinolines based on intramolecular condensation of 5-N-aryl-1H-pyrazole-5-amine derivatives Chem. Heterocycl. Compd. 2021 submitted 91. Yang S.-W. Smotryski J. McElroy W.T. Tan Z. Ho G. Tulshian D. Greeniee W.J. Guzzi M. Zhang X. Mullins D. Discovery of orally active pyrazoloquinolines as potent PDE10 inhibitors for the management of schizophrenia Bioorg. Med. Lett. 2012 22 235 239 10.1016/j.bmcl.2011.11.023 92. Ho G.D. Yang S.-W. Smotryski J. Bercovici A. Nechuta T. Smith E.M. McElroy W. Tan Z. Tulshian D. McKittrick B. The discovery of potent, selective, and orally active pyrazoloquinolines as potent PDE10A inhibitors for the treatment of Schozophrenia Bioorg. Med. Lett. 2012 22 1019 1022 10.1016/j.bmcl.2011.11.127 93. McElroy W.T. Tan Z. Basu K. Yang S.-W. Smotryski J. Ho G.D. Tulshian D. Greenlee W.J. Mullins D. Guzzi M. Pyrazoloquinolines as PDE10A inhibitors: Discover of a tool compound Bioorg. Med. Lett. 2012 22 1335 1339 10.1016/j.bmcl.2011.12.080 94. Coutts R.T. Edwards J.B. The preparation of 9-hydroxypyrazolo[3,4-b]quinolines Can. J. Chem. 1966 44 2009 20014 10.1139/v66-300 95. Coutts R.T. El-Hawari A.-M. Derivatives of 2-pyrazolin-5-one.V. Preparation and properties of 1′,2′-dihydrospiro[[2]pyrazoline-4,3′(4′H)-quinoline]-5-one derivatives and related compounds Can. J. Chem. 1977 55 2856 2866 10.1139/v77-397 96. Kametani T. Yamanaka T. Ogasawara K. Nitrenes. Part IV. Synthesis of oxazolo[5,4-b]quinoline through a nitrene intermediate J. Chem. Soc. C 1969 385 387 10.1039/j39690000385 97. Nishiwaki T. Fukuhara G. Takahashi T. Studies on heterocyclic chemistry. Part XVI. Reaction of 4-o-nitrobenylidene -Δ2-pyrazoli-5-ones with trialkyl phosphites: Synthesis of phosphorus-substituted pyrazolo[3,4-b]quinoline derivatives J. Chem. Soc. Perkin Trans. I 1973 15 1606 1609 10.1039/P19730001606 98. Danel A. Tomasik P. Condensation of 2-nitrobenzaldehyde with pyrazolin-5-ones. Structure of 4-(2-nitrobenzylidene)pyrazolin-5-ones and their reductive cyclization Polish J. Chem. 1995 69 1013 1017 10.1002/chin.199543177 99. DeWald H. The synthesis of 4-(o-fluorohenyl)-6,8-dihydro-3,8-dimethyl-pyrazolo[3,4-e][1,4]diazepin-7(H)one, A metabolite of Zolazepam J. Heterocycl. Chem. 1974 11 1061 1062 10.1002/jhet.5570110637 100. Shi F. Zhang S. Wu S.-S. Gao Y. Tu S.-J. A diversity oriented synthesis of pyrazolo[4,3-f]quinoline derivatives with potential biactivities via microwave—Assisted multicomponent reactions Mol. Divers. 2011 15 497 505 10.1007/s11030-010-9272-3 20814822 101. De Andrade A. Dos Santos G.C. Da Silva-Filho L.C. Synthesis of quinoline derivatives by multicomponent reaction using niobium pentachloride as Lewis Acid J. Heterocycl. Chem. 2015 52 273 277 10.1002/jhet.1980 102. Jiang B. Rajale T. Wever W. Tu S.-J. Li G. Multicomponent reactions for the synthesis of heterocycles Chem. Asian. J. 2010 5 2318 2335 10.1002/asia.201000310 20922748 103. Chebanov V.A. Gura K.A. Desenko S.M. Aminoazoles as key reagents in multicomponent heterocyclizations Synthesis of Heterocycles via Multicomponent Reactions I: Topics in Heterocyclic Chemistry Springer Berlin/Heidelberg, Germany 2010 Volume 23 41 84 10.1007/7081_2009_21 104. Quiroga J. Insuasty B. Hormanza A. Saitz C. Jullian C. Syntheses of 4-Aryl-4,7,8,9-tetrahydro-6H-pyrazolo[3,4-b]quinolin-5-ones J. Heterocycl. Chem. 1998 35 575 578 10.1002/jhet.5570350313 105. Quiroga J. Mejia D. Insuasty B. Abonia R. Nogueras M. Sanchez A. Cobo J. Low N.J. Regioselective synthesis of 4,7,8,9-tetrahydro-2H-pyrazolo[3,4-b]quinolin-5(6H)-ones. Mechanism and structural analysis Tetrahedron 2001 57 6947 6953 10.1016/S0040-4020(01)00649-4 106. Bhattacharjee D. Kshiar B. Myrboh B. L-Proline as an efficient enatioinduction organocatalyst in the solvent-free synthesis of pyrazolo[3,4-b]quinoline derivatives via one-pot multicomponent reaction RSC Adv. 2016 6 95944 10.1039/C6RA22429F 107. Khumalo M.R. Maddila S.N. Maddila S. Jonnalagadda S.B. A multicomponent, facile and catalyst-free microwave-assisted protocol for the synthesis of pyrazolo[3,4-b]quinolines under green conditions RSC Adv. 2019 9 30768 10.1039/C9RA04604F 35529349 108. Devi L. Nagraraju K. Maddila S. Jonnalagadda S.B. A green, efficient protocol for the catalyst free synthesis of tetrahydro-1H-pyrazolo[3,4-b]quinolin-5(4H)-ones supported by ultrasonicirradiation Chem. Data Collect. 2020 30 100566 10.1016/j.cdc.2020.100566 109. Zahedifar M. Shojaei R. Sheibani H. Convenient regioselctive reaction in presence of H3PW12O40: Synthesis and characterization of pyrazolo[3,4-b]quinoline-3,5-diones Res. Chem. Intermed. 2018 44 873 882 10.1007/s11164-017-3141-y 110. Zahedifar M. Pouramiri B. Razavi R. Triethanoloamine lactate-supprted nanomagnetic cellulose: A green and efficient catalyst dor the synthesis of pyrazolo[3,4-b]quinolines and theoretical study Res. Chem. Intermed. 2020 46 2749 2765 10.1007/s11164-020-04117-8 111. Wang H.-Y. Shi D.-Q. Three-component one-pot synthesis of pyrazolo[3,4-b]quinolin-5(6H)-one derivatives in aqueous media J. Heterocycl. Chem. 2012 49 212 216 10.1002/jhet.781 112. Kamakar K. Murthy N.S. Ramesh K. Satish G. Nanubolu J.B. Nageswar Y.V.D. Polyethlene glycol (PEG-400): An efficient and recyclable reaction medium for the synthesis of pyrazolo[3,4-b]quinoline Tetrahedron Lett. 2012 53 2897 2903 10.1016/j.tetlet.2012.03.135 113. Tomasik P. Chaczatrian K. Chaczatrian G. Danel A. Facile synthesis of 4-aryl-1H-pyrazolo[3,4-b]quinolines Polish J. Chem. 2003 77 1141 1147 114. Hu Y. Liu Y.-F. Zhang J. Zhang Y.-Z. Bi F.-L. Synthesis of 1,3,4-triphenyl-1H-pyrazolo[3,4-b]quinoline derivatives under microwave irradiation Ziran Kexueban 2012 42 241 244 115. Hedge H. Shetty N.S. Facile one-pot multicomponent synthesis of 1H-pyrazolo[3,4-b]quinolones using L-proline as a catalyst Chem. Heterocycl. Compd. 2017 53 883 886 10.1007/s10593-017-2152-3 116. Jaing B. Zhang G. Ma N. Shi F. Tu S.-J. Kaur P. Li G. A new rapid multicomponent domino reaction for the foramtion of functinalized benzo[h]pyrazolo[3,4-b]quinolines Org. Biomol. Chem. 2011 9 3834 3838 10.1039/c1ob05034f 21445382 117. Rajesh S.M. Bala B.D. Perumal S. Menedez J.C. L-Proline—Catalysed sequential four component “on water” protocol for the synthesis od structurally complex heterocyclic ortho-quinones Green Chem. 2011 13 3248 3254 10.1039/c1gc15794a 118. Quiroga J. Diaz Y. Bueno J. Insuasty B. Abonia R. Ortiz A. Nogueras M. Cobo J. Microwave induced three-component synthesis and antimicrobacerial activity of benzopyrazolo[3,4-b]quinolindiones Eur. J. Med. Chem. 2014 74 216 224 10.1016/j.ejmech.2013.12.037 24463437 119. Khalafy J. Arlan F.M. Marjani A.P. Sarchami V. One-pot, three-component synthesis of polyfunctionalized benzo[h]pyrazolo[3,4-b][1,6]naphtyridine and benzo[g]pyrazolo[3,4-b]quinoline derivatives in the presence of silver nanoparticles (AgNPs) J. Heterocycl. Chem. 2020 57 3961 3969 10.1002/jhet.4105 120. Yadaw R. Parvin T. Multicomponent synthesis of styryl linked benzo[h]pyrazolo[3,4-b]quinoline-5,6(10H)-diones by liquid assisted grinding New. J. Chem. 2021 45 10388 10395 10.1039/D1NJ00770J 121. Polo E. Ferrer-Perutz K. Trilleras J. Quiroga J. Gutierrez M. Microwave—Assisted one pot synthesis in water carbonylpyrazolo[3,4-b]pyridine derivatives catalysed by InCl3 and sonochemical assisted condensation with aldehydes to obtain new chalcone derivatives containing the pyrazolpyridinic moiety RSC Adv. 2017 7 50044 50055 10.1039/C7RA10127A 122. Khurana J.M. Chaudhary A. Nand B. Lumb A. Aqua mediated indium(II) chloride catalysed synthesis of fused pyrimidines and pyrazoles Tetrahedron Lett. 2012 53 3018 3022 10.1016/j.tetlet.2012.04.001 123. Wu L.-Q. Dong R.-Y. Yang C.-G. Yan F.-L. Synthesis of 4-aryl-3-methyl-1-phenyl-1H-benzo[h]pyrazolo[3,4-b]quinoline-5,10-diones using diammonium hydrogen phosphate as an efficient and versatile catalyst in water J. Chin. Chem. Soc. 2010 57 19 23 10.1002/jccs.201000003 124. Re Y.-M. Jin S. Yan H.-J. Zhang Z. PEG1000-Based dicationic acidic ionic liquid catalysed one-pot synthesis of 4-aryl-3-methyl-1-phenyl-1H-benzo[h]pyrazolo[3,4-b]quinoline-5,10-diones via multicomponent reactions Catalysis 2015 5 1649 1656 10.3390/catal5041649 125. Karamthulla S. Pal S. Parvin T. Choudhury L.H. L-Proline catalysed multicomponent reactions: Facile access to 2H-benzo[g]pyrazolo[3,4-b]quinoline-5,10(4H,11H)-dione derivatives RSC Adv. 2014 4 15319 15324 10.1039/C4RA00876F 126. Yin A. Yang L. Wu L. Synthesis of spiro[pyrazolo[3,4-b]pyridine-4,3′-indoline] and spiro[benzo[h]pyrazolo[3,4-b]quinoline-4,3′-indoline]derivatives using wet cyanuric chloride under solvet free condition J. Chem. Sci. 2013 125 601 606 10.1007/s12039-013-0422-x 127. Dabiri M. Tisseh Z.N. Nobahar M. Bazgir A. Organic reaction in water: A highly efficient and environmentally friendly synthesis of spiro compouns catalysed by L-proline Helv. Chim. Acta 2011 94 824 830 10.1002/hlca.201000307 128. Zhu G. Gao L. Yu Q. Qin Y. Xi J. Rong L. An efficient synthesis of 1′,7′,8′,9′-tetrahydrospiro[indoline-3,4′-pyrazolo[3,4-b]quinoline]2,5′(6′H)-dione derivatives in aqueous medium J. Hetereocycl. Chem. 2018 55 871 878 10.1002/jhet.3111 129. Baradarani M.M. Saatluo B. Ghabeli S. Shokri Z. Shahbazi M. Joule J.A. Synthesis of hexahydrospiro[pyrazolo3,4-b]quinoline-4,1′-pyrrolo[3,2,1-ij]quinoline-2′,5(1H,4′H)-diones] from 5,6 dihydro-4H-pyrrolo[3,2,1-ij]quinoline-1,2-dione using Fe3O4@Cu(OH)x as Nanaocatalyst J. Heterocycl. Chem. 2019 56 1999 2007 10.1002/jhet.3579 130. Quiroga J. Portilla J. Serrano H. Abonia R. Insuasty B. Nogueras M. Cobo J. Regioslective synthesis of fused benzopyrazolo[3,4-b]quinolines under solvent-free conditions Tetrahedron Lett. 2007 48 1987 1990 10.1016/j.tetlet.2007.01.074 131. Manickam S. Balijapalli U. Sathiyanarayan K.I. SnCl2-cataluzed synthesis of dihydro-5H-benzo[f]pyrazolo[3,4-b]quinoline and dihydroindeno[2,1-b]pyrazolo[4,3-e]pyridine with high fluorescence and their photophysical properties New. J. Chem. 2018 42 860 871 10.1039/C7NJ03654J 132. Yadaw P. Awasthi A. Gokulnath S. Tiwari D.K. DMSO as a methine source in TFA-mediated one pot tanden regioselctive synthesis of 3 substiuted -1-aryl-1H-pyrazolo[3,4-b]quinolines from anilines and pyrazolones J. Org. Chem. 2021 86 2658 2666 10.1021/acs.joc.0c02696 33423469 133. Pietrzycki W. Danel A. Tomasik P. Quantum chemical ci-1 analysis of uv absorption spectra of 1h-pyrazolo[3,4-b]quinoline system Bull. Soc. Chim. Belges 1994 103 725 741 10.1002/bscb.19941031205 134. Gondek E. Koścień E. Sanetra J. Danel A. Wisła A. Kityk A.V. Optical absorption of 1H-pyrazolo[3,4-b]quinoline and its derivatives Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2004 60 3101 3106 10.1016/j.saa.2004.02.022 135. Gondek E. Kityk I.V. Sanetra J. Szlachcic P. Armatys P. Wisla A. Danel A. New-synthesized pyrazoloquinoline as promising luminescent materials Opics Laser Technol. 2006 38 487 492 10.1016/j.optlastec.2004.12.011 136. Koścień E. Gondek E. Kityk A.V. Optical absorption of 1-phenyl-3-methyl-1H-pyrazolo[3,4-b]quinoline derivatives: Molecular dynamics modeling Opt. Commun. 2007 280 95 102 10.1016/j.optcom.2007.07.046 137. Koścień E. Gondek E. Pokładko M. Jarosz B. Vlokh R.O. Kityk A.V. Photoluminescence of 1,3-dimethyl pyrazoloquinoline derivatives Mater. Chem. Phys. 2009 114 860 867 10.1016/j.matchemphys.2008.10.062 138. Koścień E. Gondek E. Jarosz B. Danel A. Nizioł J. Kityk A.V. Photoluminescence of 1-phenyl-3-methyl pyrazoloquinoline derivatives Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2009 72 582 590 10.1016/j.saa.2008.10.048 19091627 139. Yu J. He K. Li Y. Tan H. Zhu M. Wang Y. Liu Y. Zhu W. Wu H. A novel near-infrared-emitting cyclometalated platinum (II) complex with donor–acceptor–acceptor chromophores Dyes Pigment. 2014 107 146 152 10.1016/j.dyepig.2014.03.040 140. Slodek A. Matussek M. Filapek M. Szafraniec-Gorol G. Szlapa A. Grudzka-Flak I. Szczurek M. Malecki J.G. Maron A. Schab-Balcerzak E. Small Donor-Acceptor Molecules Based on a Quinoline-Fluorene System with Promising Photovoltaic Properties Eur. J. Org. Chem. 2016 2016 2500 2508 10.1002/ejoc.201600318 141. Yan Z. Guang S. Xu H. Liu X.-Y. Quinoline-based azo derivative assembly: Optical limiting property and enhancement mechanism Dyes Pigment. 2013 99 720 726 10.1016/j.dyepig.2013.07.007 142. dos Santos G.C. Servilha R.O. de Oliveira E.F. Lavarda F.C. Ximenes V.F. da Silva-Filho L.C. Theoretical-Experimental Photophysical Investigations of the Solvent Effect on the Properties of Green- and Blue-Light-Emitting Quinoline Derivatives J. Fluoresc. 2017 27 1709 1720 10.1007/s10895-017-2108-0 28493214 143. Goel A. Kumar V. Singh S.P. Sharma A. Prakash S. Singh C. Anand R.S. Non-aggregating solvatochromic bipolar benzo[f]quinolines and benzo[a]acridines for organic electronics J. Mater. Chem. 2012 22 14880 10.1039/c2jm31052j 144. EL-Shabaan M.M. Gaml E.A. Fluorescent quinoline carboxylate derivative: Study on the optical properties and photo diode application Phys. B Condens. Matter 2022 626 413578 10.1016/j.physb.2021.413578 145. Onozawa-Komatsuzaki N. Funaki T. Kasuga K. Nakazawa Y. Sayama K. Sugihara H. Synthesis and Electrochemical Properties of 2,6-Bis(quinoline-2-yl)pyridyl Ruthenium Complexes as Near-Infrared Sensitizers for Dye-Sensitized Solar Cells Jpn. J. Appl. Phys. 2012 51 10NE11 10.7567/JJAP.51.10NE11 146. Lanke S.K. Sekar N. Pyrazole based NLOphores: Synthesis, photophysical, DFT, TDDFT studies Dye. Pigment. 2016 127 116 127 10.1016/j.dyepig.2015.12.026 147. Barberá J. Clays K. Giménez R. Houbrechts S. Persoons A. Serrano J.L. Versatile optical materials: Fluorescence, non-linear optical and mesogenic properties of selected 2-pyrazoline derivatives J. Mater. Chem. 1998 8 1725 1730 10.1039/a802070a 148. Willy B. Müller T.J.J. Rapid One-Pot, Four-Step Synthesis of Highly Fluorescent 1,3,4,5-Tetrasubstituted Pyrazoles Org. Lett. 2011 13 2082 2085 10.1021/ol2004947 21417307 149. Götzinger A.C. Theßeling F.A. Hoppe C. Müller T.J.J. One-Pot Coupling–Coupling–Cyclocondensation Synthesis of Fluorescent Pyrazoles J. Org. Chem. 2016 81 10328 10338 10.1021/acs.joc.6b01326 27403574 150. Castillo J.-C. Tigreros A. Portilla J. 3-Formylpyrazolo[1,5-a]pyrimidines as Key Intermediates for the Preparation of Functional Fluorophores J. Org. Chem. 2018 83 10887 10897 10.1021/acs.joc.8b01571 30051714 151. Taydakov I.V. Akkuzina A.A. Avetisov R.I. Khomyakov A.V. Saifutyarov R.R. Avetissov I.C. Effective electroluminescent materials for OLED applications based on lanthanide 1.3-diketonates bearing pyrazole moiety J. Lumin. 2016 177 31 39 10.1016/j.jlumin.2016.04.017 152. Lewińska G. Khachatryan K. Danel K.S. Danel Z. Sanetra J. Marszałek K.W. Investigations of the Optical and Thermal Properties of the Pyrazoloquinoline Derivatives and Their Application for OLED Design Polymers 2020 12 2707 10.3390/polym12112707 33207751 153. García M. Romero I. Portilla J. Synthesis of Fluorescent 1,7-Dipyridyl-bis-pyrazolo[3,4-b:4′,3′-e]pyridines: Design of Reversible Chemosensors for Nanomolar Detection of Cu 2+ ACS Omega 2019 4 6757 6768 10.1021/acsomega.9b00226 31459798 154. Orrego-Hernández J. Lizarazo C. Cobo J. Portilla J. Pyrazolo-fused 4-azafluorenones as key reagents for the synthesis of fluorescent dicyanovinylidene-substituted derivatives RSC Adv. 2019 9 27318 27323 10.1039/C9RA04682H 35529179 155. Kanwal I. Rasool N. Zaidi S.H.M. Zakaria Z.A. Bilal M. Hashmi M.A. Mubarik A. Ahmad G. Shah S.A.A. Synthesis of Functionalized Thiophene Based Pyrazole Amides via Various Catalytic Approaches: Structural Features through Computational Applications and Nonlinear Optical Properties Molecules 2022 27 360 10.3390/molecules27020360 35056676 156. Bhalekar S. Bhagwat A. Sekar N. 3 Fluorescent styryl chromophores with rigid (pyrazole) donor and rigid (benzothiophenedioxide) acceptor—Complete density functional theory (DFT), TDDFT and nonlinear optical study Computational Chemistry De Gruyter Berlin, Germany 2021 33 60 157. Makowska-Janusik M. Gondek E. Kityk I.V. Wisła J. Sanetra J. Danel A. Second-order optical effects in several pyrazolo-quinoline derivatives Chem. Phys. 2004 306 265 271 10.1016/j.chemphys.2004.07.034 158. Niziol J. Danel A. Boiteux G. Davenas J. Jarosz B. Wisla A. Seytre G. Optical properties of new pyrazolo[3,4-b] quinoline and its composites Synth. Met. 2002 127 175 180 10.1016/S0379-6779(01)00617-8 159. Gąsiorski P. Danel K.S. Matusiewicz M. Uchacz T. Vlokh R. Kityk A.V. Synthesis and Spectroscopic Study of Several Novel Annulated Azulene and Azafluoranthene Based Derivatives J. Fluoresc. 2011 21 443 451 10.1007/s10895-010-0722-1 20886270 160. Misra R. Bhattacharyya S.P. Intramolecular Charge Transfer: Theory and Applications Wiley-VCH Verlag GmbH & Co. KGaA Weinheim, Germany 2018 978-3-527-34156-6 161. Grabowski Z.R. Rotkiewicz K. Rettig W. Structural Changes Accompanying Intramolecular Electron Transfer: Focus on Twisted Intramolecular Charge-Transfer States and Structures Chem. Rev. 2003 103 3899 4032 10.1021/cr940745l 14531716 162. Gondek E. Danel A. NizioŁ J. Armatys P. Kityk I.V. Szlachcic P. Karelus M. Uchacz T. Chwast J. Lakshminarayana G. Some spirobiindane based 1H-pyrazolo[3,4-b] quinoline chromophore as novel chromophore for light-emitting diodes J. Lumin. 2010 130 2093 2099 10.1016/j.jlumin.2010.05.033 163. Kolbus A. Grabka D. Danel A. Szary K. Spectral properties of 1H-pyrazolo[3,4-b]quinoline substituted with N,N-diethylamine moiety Opt. Mater. 2016 57 102 106 10.1016/j.optmat.2016.04.010 164. Rettig W. Photoinduced charge separation via twisted intramolecular charge transfer states Electron Transfer I. Topics in Current Chemistry Springer-Verlag GmbH Berlin, Heidelberg, Germany 1994 253 299 165. Grabowski Z.R. Rotkiewicz K. Siemiarczuk A. Dual fluorescence of donor-acceptor molecules and the Twisted Intramolecular Charge Transfer (ICT) states J. Lumin. 1979 18–19 420 424 10.1016/0022-2313(79)90153-4 166. Michl J. Electronic structure of aromatic π-electron systems as reflected in their MCD spectra Pure Appl. Chem. 1980 52 1549 1563 10.1351/pac198052061549 167. Miura T. Urano Y. Tanaka K. Nagano T. Ohkubo K. Fukuzumi S. Rational Design Principle for Modulating Fluorescence Properties of Fluorescein-Based Probes by Photoinduced Electron Transfer J. Am. Chem. Soc. 2003 125 8666 8671 10.1021/ja035282s 12848574 168. Fox M.A. Photoinduced Electron Transfer Photochem. Photobiol. 1990 52 617 627 10.1111/j.1751-1097.1990.tb01808.x 169. Rurack K. Resch-Genger U. Rigidization, preorientation and electronic decoupling—the ‘magic triangle’ for the design of highly efficient fluorescent sensors and switches Chem. Soc. Rev. 2002 31 116 127 10.1039/b100604p 12109205 170. Mu L. He Z. Kong X. Liang C. Wang Y. Danel A. Kulig E. Milburn G.H.W. Towards Color Stable Blue Primary for Displays: Suppress Field-Dependent Color Change in a Multilayered Electroluminescent Device J. Disp. Technol. 2011 7 96 104 10.1109/JDT.2010.2096532 171. Gąsiorski P. Gondek E. Danel K.S. Pokladko-Kowar M. Armatys P. Kityk A.V. Green electroluminescence from azafluoranthene derivatives in polymer based electroluminescent devices Opt. Mater. 2013 35 681 684 10.1016/j.optmat.2012.09.027 172. Jaglarz J. Kępińska M. Sanetra J. Thermo-optical properties of 1H[3,4-b] quinoline films used in electroluminescent devices Opt. Mater. 2014 36 1275 1280 10.1016/j.optmat.2014.02.015 173. Tao Y.T. Balasubramaniam E. Danel A. Wisla A. Tomasik P. Pyrazoloquinoline derivatives as efficient blue electroluminescent materials J. Mater. Chem. 2001 11 768 772 10.1039/b007918i 174. Danel K.S. Gondek E. Pokladko M. Kityk I.V. 4-(p-N,N-Diarylphenyl)substituted 1H-pyrazolo[3,4-b]quinolines as novel luminophors for organic light emitting diode—synthesis, electroluminescent devices J. Mater. Sci. Mater. Electron. 2009 20 171 176 10.1007/s10854-008-9677-2 175. Mac M. Uchacz T. Danel A. Musiolik H. Applications of Fluorescent Sensor Based on 1H-pyrazolo[3,4-b]quinoline in Analytical Chemistry J. Fluoresc. 2013 23 1207 1215 10.1007/s10895-013-1251-5 23813235 176. Mac M. Uchacz T. Wróbel T. Danel A. Kulig E. New Fluorescent Sensors Based on 1H-pyrazolo[3,4-b]quinoline Skeleton J. Fluoresc. 2010 20 525 532 10.1007/s10895-009-0576-6 20084438 177. Mac M. Uchacz T. Danel A. Danel K. Kolek P. Kulig E. A New Fluorescent Sensor Based on 1H-pyrazolo[3,4-b]quinoline Skeleton. Part 2 J. Fluoresc. 2011 21 375 383 10.1007/s10895-010-0726-x 20890644 178. Uchacz T. Szlachcic P. Wojtasik K. Mac M. Stadnicka K. Amino derivatives of 1,3-diphenyl-1H-pyrazolo[3,4-b]quinoline—Photophysics and implementation of molecular logic switches Dyes Pigment. 2016 124 277 292 10.1016/j.dyepig.2015.09.016 179. Paisley N.R. Tonge C.M. Hudson Z.M. Stimuli-Responsive Thermally Activated Delayed Fluorescence in Polymer Nanoparticles and Thin Films: Applications in Chemical Sensing and Imaging Front. Chem. 2020 8 229 10.3389/fchem.2020.00229 32328478 180. Gerasimova M.A. Tomilin F.N. Malyar E.Y. Varganov S.A. Fedorov D.G. Ovchinnikov S.G. Slyusareva E.A. Fluorescence and photoinduced proton transfer in the protolytic forms of fluorescein: Experimental and computational study Dyes Pigment. 2020 173 107851 10.1016/j.dyepig.2019.107851 181. Meng X. You L. Li S. Sun Q. Luo X. He H. Wang J. Zhao F. An ICT-based fluorescence enhancement probe for detection of Sn 2+ in cancer cells RSC Adv. 2020 10 37735 37742 10.1039/D0RA07330J 35515174 182. Sasaki S. Drummen G.P.C. Konishi G. Recent advances in twisted intramolecular charge transfer (TICT) fluorescence and related phenomena in materials chemistry J. Mater. Chem. C 2016 4 2731 2743 10.1039/C5TC03933A 183. Yan C. Guo Z. Chi W. Fu W. Abedi S.A.A. Liu X. Tian H. Zhu W.-H. Fluorescence umpolung enables light-up sensing of N-acetyltransferases and nerve agents Nat. Commun. 2021 12 3869 10.1038/s41467-021-24187-5 34162875 184. Jacobi P.A. Introductory Heterocyclic Chemistry John Wiley & Sons Hoboken, NJ, USA 2018 978-1-119-41759-0 185. Kerru N. Gummidi L. Maddila S. Gangu K.K. Jonnalagadda S.B. A Review on Recent Advances in Nitrogen-Containg Molecules and Their Biological Applications Molecules 2020 25 1909 10.3390/molecules25081909 32326131 186. Heravi M.M. Zadsirjan V. Prescribed drugs containing nitrogen heterocycles: An overview RSC Adv. 2020 10 44247 44311 10.1039/D0RA09198G 187. Graeve R.E. Pociask J.R. Stein R.G. Dialkylamino Alkylamino Pyrazolo (3,4b) quinolines U.S. Patent 3600393A 17 August 1971 188. De Andrea M. Ravera R. Gioia D. Gariglio M. Landolfo S. The interferon system: An overview Eur. J. Paediatr. Neurol. 2002 6 (Suppl. A) A41 A46 10.1053/ejpn.2002.0573 12365360 189. Bagheri A. Moezzi S.M.I. Mosaddeghi P. Parashkouhi S.N. Hoseini S.M.F. Badakhshan F. Negahdaripour M. Interferon-inducer antivirals: Potential candidates to combat COVID-19 Int. Immunopharmacol. 2021 91 art.107245 10.1016/j.intimp.2020.107245 190. Siminoff P. Bernard A.M. Hursky V.S. Price K.E. BL-20803, a New, Low-Molecular-Weight Interferon Inducer Antimicrob. Agents Chemother. 1973 3 742 743 10.1128/AAC.3.6.742 4790625 191. Siminoff P. Target Cells for Interferon Induction by BL-20803 J. Infect. Dis. 1976 133 A37 A42 10.1093/infdis/133.Supplement_2.A37 932505 192. Siminof P. Crenshaw R.R. Simulation of Interferon Production in Mice and in Mouse Spleen Leukocytes by Analogues of BL-20803 Antimicrob. Agents Chemother. 1977 11 571 573 10.1128/AAC.11.3.571 856006 193. Kern E.R. Hamilton J.R. Overall J.C. Glasgow L.A. Antiviral Activity of BL-3849A, a Low-Molecular-Weight Oral Interferon Inducer Antimicrob. Agents Chemother. 1976 10 691 696 10.1128/AAC.10.4.691 185953 194. Rádl S. Zikán V. Šmejkal F. Připrava některých 4-anilino-1,3-dimetyl-1H-pyrazolo(3,4-b)chinolinů s protivirovým účinkem Ceskoslov. Farm. 1984 33 429 432 195. Rádl S. Zikán V. Šmejkal F. Syntheses of 1, 2, and 9-methyl derivatives of 4,9-dihydro-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline and their antiviral activity Coll. Czechoslov. Chem. Commun. 1985 50 1057 1063 10.1135/cccc19851057 196. Rádl S. Zikán V. Šmejkal F. Připrava některých 4-fenoxy- a 4-fenylotioderivátů 1H-pyrazolo/3,4-b/chinolinu s protivirovým účinkem Ceskoslov. Farm. 1985 34 119 122 197. Rádl S. Roubinek F. Šmejkal F. Zikán V. Připrava některých 1-substituivaných 4-dialkylaminoalkylamino-3-metyl-1H-pyrazolo/3,4-b/chinolinů s protivirovým účinkem Ceskoslov. Farm. 1985 34 190 193 198. Rádl S. Zikán V. Šmejkal F. Připrava 4-(hydroxyanilino)-a4-(alkoxyanilino)derivátů 1,3-dimetyl-1H-pyrazolo/3,4-b/chinolinu s potenciálním protivirovým účinkem Ceskoslov. Farm. 1985 34 383 385 199. Rádl S. Roubinek F. Zikán V. Šmejkal F. Připrava některých 1-substituivaných 4-alkylamin-3-metyl-1H-pyrazolo(3,4-b)chinolinů s potenciálním protivirovým účinkem Ceskoslov. Farm. 1986 34 105 109 200. Rádl S. Zikán V. Syntheses of 1, 2, and 9-methyl derivatives of 4,9-dihydro-6-methoxy-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline and 4,9-dihydro-6-hydroxy-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinoline and their antiviral activity Coll. Czechoslov. Chem. Commun. 1987 52 788 792 10.1135/cccc19870788 201. Rádl S. Zikán V. Synthesis and biological activity of some basic-substituted 4,9-dihydro-3-methyl-4-oxo-1H(2H)-pyrazolo[3,4-b]quinolines Coll. Czechoslov. Chem. Commun. 1988 53 1812 1819 10.1135/cccc19881812 202. Zikán V. Rádl S. Šmejkal F. Zelená D. Substituované 4-anilino-1,3-dimethyl-1H-pyrazolo/3,4-b/chinoliny a Způsoby Jejich Přípravy CS Patent 233445B1 14 March 1985 203. Zikán V. Rádl S. Šmejkal F. Zelená D. Substituované 4,9-dihydro-3-methyl-4-oxo-1H-pyrazolo(3,4-b)chinoliny a Spůsob Jejich Výroby CS Patent 235167B1 15 May 1985 204. Zikán V. Rádl S. Substituované 4-fenoxy-3-methyl-1H-pyrazolo(3,4-b)chinoliny a Způsoby Jejich Přípravy CS Patent 235176B1 15 May 1985 205. Zikán V. Rádl S. Šmejkal F. Zelená D. 4-Karboxyalkylamino-1,3-dimethyl-1H-pyrazolo(3,4-b)chinoliny a Způsob Jejich Přípravy CS Patent 235177B1 15 May 1985 206. Zikán V. Rádl S. 4-Chlor-6-methoxy-3-methyl-1H-pyrazolo(3,4-b)chinolin a Jeho N1-methylderivát CS Patent 252340B1 13 August 1987 207. Zikán V. Rádl S. O,N-substituované 4,9-dihydro-6-hydroxy-1,3-dimethyl-4-oxo-1H-pyrazolo(3,4-b)chinoliny CS Patent 252341B1 13 August 1987 208. Zikán V. Rádl S. Šmejkal F. 4,9-dihydro-6-methoxy-3-methyl-4-oxo-1H-pyrazolo(3,4-b)chinolin CS Patent 252621B1 17 September 1987 209. Chintha C. Gupta N. Ghate M. Vyas V.K. Homology modeling, binding site identification, and docking study of human β-arrestin: An adaptor protein involved in apoptosis Med. Chem. Res. 2014 23 1189 1201 10.1007/s00044-013-0725-y 210. Vyas V.K. Qureshi G. Dayani H. Jha A. Ghate M. Pharmacophore-based identification and in vitro validation of apoptosis inducers as anticancer agents SAR QSAR Enviromental Res. 2020 31 869 881 10.1080/1062936X.2020.1827030 33100034 211. Kemnitzer W. Kuemmerle J. Zhang H.-Z. Kasibhatla S. Tseng B. Drewe J. Cai S.X. Discovery of 3-aryl-5-aryl-1,2,4-oxadiazoles as a new series of apoptosis inducers. 2. Identification of more aqueous soluble analogs as potential anticancer agents Bioorg. Med. Chem. Lett. 2009 19 4410 5515 10.1016/j.bmcl.2009.05.052 19500976 212. Afonso A. Kelly J.M. Chackalamannil S. 4-Substituted Pyrazoloquinoline Derivatives U.S. Patent 5506236A 9 April 1996 213. Albin R. Chase R. Risano C. Lieberman M. Ferrari E. Skelton A. Buontempo P. Cox S. DeMartino J. Wright-Minogue J. SCH 43478 and analogs: In vitro activity and in vivo efficacy of novel agents for herpesvirus type 2 Antivirial Res. 1997 35 139 146 10.1016/S0166-3542(97)00023-5 214. Bell M.R. Ackerman J.H. Pyrazolo[3,4-b]quinolines and Their Use as Antiviral Agents U.S. Patent 4920128A 24 April 1990 215. Bekhit A.A. El-Sayed O.A. Aboul-Enein H.Y. Siddiqui Y.M. Al-Ahdal M.N. Synthesis of Aldehydo-sugar Derivatives of Pyrazoloquinoline as Inhibitors of Herpes Simplex Virus Type 1 Replication J. Enzym. Inhib. Med. Chem. 2004 19 33 38 10.1080/14756360310001650219 216. Bekhit A.A. El-Sayed O.A. Aboul-Enein H.Y. Siddiqui Y.M. Al-Ahdal M.N. Evaluation of Some Pyrazoloquinolines as Inhibitors of Herpes Simplex Virus Type 1 Replication Arch. Pharm. 2005 338 74 77 10.1002/ardp.200400930 217. Arif J.M. Kunhi M. Subramanian M.P. Bekhit A.A. El-Sayed O.A. Al-Hussein K. Aboul-Enein H.Y. Al-Khodairy F.M. Evaluation of Cytotoxic Potential of Newly Synhtesized Antivirial Aminopyrazoloquinoline Derivatives Int. J. Biomedical Sci. 2007 3 194 198 218. Arif J.M. Kunhi M. Subramanian M.P. Bekhit A.A. El-Sayed O.A. Al-Hussein K. Aboul-Enein H.Y. Al-Khodairy F.M. Cytotoxic and genotoxic potentials of newly synthesized antivirial aminopyrazoloquinoline derivatives Med. Chem. Res. 2008 17 297 304 10.1007/s00044-007-9065-0 219. Shuck-Lee D. Chen F.F. Willard R. Raman S. Ptak R. Hammarskjold M.-L. Rekosh D. Heterocyclic Compounds That Inhibit Rev-RRE Function and Human Immunodeficiency Virus Type 1 Replication Antimicrob. Agents Chemother. 2008 52 3169 3179 10.1128/AAC.00274-08 18625767 220. Magiorakos A.-P. Srinivasan A. Carey R.B. Carmeli Y. Falagas M.E. Giske C.G. Harbarth S. Hindler J.F. Kahlmeter G. Olsson-Liljequist B. Multidrug-resistant, extensively drug-resistnat and pandrug-resistant bacteria: An international expert propos al for interim standard definitions for acquired resistance Clin. Microbiol. Infect. 2012 18 268 281 10.1111/j.1469-0691.2011.03570.x 21793988 221. El-Sayed O.A. Aboul-Enein H.Y. Synthesis and Antimicrobial Activity of Novel Pyrazolo[3,4-b]quinoline Derivatives Arch. Pharm. 2001 334 117 120 10.1002/1521-4184(200104)334:4<117::AID-ARDP117>3.0.CO;2-9 222. Lapa G.B. Bekker O.B. Mirchink E.P. Danilenko V.N. Preobrazhenskaya M.N. Regioselective acylation of congeners of 3-amino-1H-pyrazolo[3,4-b]quinolines, their activity on bacterial serine/threonine protein kinases and in vitro antibacterial (including antimycobacterial) activity J. Enzym. Inhib. Med. Chem. 2012 28 1088 1093 10.3109/14756366.2012.716056 22957725 223. Nurgali K. Jagoe R.T. Abalo R. Editorial: Adverse Effects of Cancer Chemotherapy: Anything New to Improve Tolerance and Reduce Sequelae? Front. Pharmacol. 2018 9 245 10.3389/fphar.2018.00245 29623040 224. Garattini S. Bertele’ V. Effiacy, safety, and cost of new anticancer drugs BMJ 2002 325 269 271 10.1136/bmj.325.7358.269 12153927 225. Karthikeyan C. Amawi H. Viana A.G. Sanglard L. Hussein N. Saddler M. Ashby C.R. Jr. Moorthy N.S.H.N. Trivedi P. Tiwari A.K. 1H-Pyrazolo[3,4-b]quinoline-3-amine derivatives inhibit growth of colon cancer cells via apoptosis and sub G1 cell cycle arrest Bioorg. Med. Chem. Lett. 2018 28 2244 2249 10.1016/j.bmcl.2018.05.045 29853331 226. Karthikeyan C. Malla R. Ashby C.R. Jr. Amawi H. Abbott K.L. Moore J. Chen J. Balch C. Lee C. Flannery P.C. Pyrimido[1″,2″:1,5]pyrazolo[3,4-b]quinolines: Novel compounds that reverse ABCG2-mediated resistance in cancer cells Cancer Lett. 2016 376 118 126 10.1016/j.canlet.2016.03.030 27012188 227. Goodsell D.S. The Molecular Perspective: The ras Oncogene The Oncologist 1999 4 263 264 10.1634/theoncologist.4-3-263 10394594 228. Downward J. Targeting RAS signaling pathways in cancer therapy Nat. Rev. Cancer 2003 3 11 22 10.1038/nrc969 12509763 229. Kumar C.C. Prorock-Rogers C. Kelly J. Dong Z. Lin J.-J. Armstrong L. Kung H.-F. Weber M.J. Afonso A. SCH 51344 Inhibits ras Transformation by a Novel Mechanism Cancer Res. 1995 55 5106 5117 7585559 230. Walsh A.B. Dhanasekaran M. Bar-Sagi D. Kumar C.C. SCH 51344-induced reversal of RAS-transformation is accompanied by the specific inhibition of the RAS and RAC-dependent cell morphology pathway Oncogene 1997 15 2553 2560 10.1038/sj.onc.1201424 9399643 231. Kumar C.C. Ohashi K. Nagata K. Walsh A. Bar-Sagi D. Mizuno K. SCH 51344, An Inhibitor of RAS/RAC-Mediated Cell Morphology Pathway Ann. N. Y. Acad. Sci. 1999 886 122 131 10.1111/j.1749-6632.1999.tb09407.x 10667210 232. Kumar C.C. Inhibition of RAS-transformation by SCH51344 Gan Kagaku Ryoho (Jpn. J. Cancer Chemother.) 1997 24 1503 1511 233. Gelman I.H. Xi Q. Kumar C.C. Reexpression of the Major PKC Substrate, SSeCKS, Correlates with the Tumor-Suppressive Effects of SCH51344 on Rat-6/src and Rat-6/ras Fibroblasts but Not on Rat-6/raf Fibroblasts Ann. N. Y. Acad. Sci. 1999 886 221 224 10.1111/j.1749-6632.1999.tb09421.x 10667224 234. Huber K.V.M. Salah E. Radic B. Gridling M. Elkins J.M. Stukalov A. Jemth A.-S. Göktürk C. Sanjiv K. Strömberg K. Stereosceific targeting of MTH1 by (S)-crizotinib as an anticancer strategy Nature 2014 508 222 227 10.1038/nature13194 24695225 235. Huber K. Superti-Furga G. Aminoheteroaryl Compounds as MTH1 Inhibitors WO Patent 2014/033136A1 6 March 2014 236. Ursu A. Waldmann H. Hide and seek: Identification and confirmation of small molecule protein targets Bioorg. Med. Chem. Lett. 2015 25 3079 3086 10.1016/j.bmcl.2015.06.023 26115575 237. SCH 51344, Cat. No. 5280 Available online: https://www.tocris.com/products/sch-51344_5280 (accessed on 1 March 2022) 238. Nieborowska-Sikorska M. Maifrede S. Dasgupta Y. Sullivan K. Flis S. Le B.V. Solecka M. Belyaeva E.A. Kubovcakova L. Nawrocki M. Ruxolitinib-induced defects in DNA repair cause sensitivity to PARP inhibitors in myeloproliferative neoplasms Blood 2017 130 2848 2859 10.1182/blood-2017-05-784942 29042365 239. Kawamura T. Kawatani M. Muroi M. Kondoh Y. Futamura Y. Aono H. Tanaka M. Honda K. Osada H. Proteomic profiling of small-molecule inhibitors reveals dispensability of MTH1 for cancer cell survival Sci. Rep. 2016 6 art.26521 10.1038/srep26521 240. Papeo G. MutT Homolog 1 (MTH1): The Silencing of a Target J. Med. Chem. 2016 59 2343 2345 10.1021/acs.jmedchem.6b00283 26924380 241. Zhou N. Xu Y. Liu X. Wang Y. Peng J. Luo X. Zheng M. Chen K. Jiang H. Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors Int. J. Mol. Sci. 2015 16 13407 13425 10.3390/ijms160613407 26110383 242. Huber K. Superti-Furga G. Aminoheteroaryl Compounds as MTH1 Inhibitors U.S. Patent 2016/0015702A1 21 January 2016 243. Bôkel C. Weidemann T. Methods and Compositions for Reducing Interleukin-4 or Interleukin-13 Signaling U.S. Patent 2013/0084275A1 4 April 2013 244. Wolin R. Wang D. Kelly J. Afonso A. James L. Kirschmeier P. McPhail A.T. Synthesis and evaluation of pyrazolo[3,4-b]quinoline ribofuranosides and their derivatives as inhibitors of oncogenic Ras Bioorg. Med. Chem. Lett. 1996 6 195 200 10.1016/0960-894X(95)00574-D 245. Wolin R.L. Afonso A. Kelly J.M. Njoroge F.G. Pyrazoloquinolines U.S. Patent 5,595,998A 21 January 1997 246. Wolin R.L. Afonso A. Pyrazoloquinolines U.S. Patent 5597821A 28 January 1997 247. Kaufmann S.H. Earnshaw W.C. Induction of Apoptosis by Cancer Chemotherapy Exp. Cell Res. 2000 256 42 49 10.1006/excr.2000.4838 10739650 248. Al-Qahtani A. Siddiqui Y.M. Bekhit A.A. El-Sayed O.A. Aboul-Enein H.Y. Al-Ahdal M.N. Effect of Pyrazoloquinoline Derivatives on the Growth of Leishmania donovani Promastigotes Arch. Pcharm. 2005 338 484 487 10.1002/ardp.200500147 16211660 249. Javitt D.C. Balancing therapeutic safety and efficacy to improve clinical and economic outcomes in schizophrenia: A clinical review Am. J. Manag. Care 2014 20 (Suppl. 8) 160 165 250. Lally J. MacCabe J.H. Antipsychotic medication in schizophrenia: A review Br. Med Bull. 2015 114 169 179 10.1093/bmb/ldv017 25957394 251. Wu Q. Gao Q. Guo H. Li D. Wang J. Gao W. Han C. Li Y. Yang L. Inhibition mechanism exploration of quinoline derivatives as PDE10A inhibitors by in silico analysis Mol. BioSyst. 2013 9 386 397 10.1039/c2mb25501d 23354020 252. Kjellgren E.R. Glue O.E.S. Reinholdt P. Meyer J.E. Kongsted J. Poongavanam V. A comparative study of binding affinities for 6,7-dimethoxy-4-pyrrolidylquinozalines as phosphodiesterase 10A inhibitors using the linear interaction energy method J. Mol. Graph. Model. 2015 61 44 52 10.1016/j.jmgm.2015.06.010 26188794 253. Khan M.A.B. Hashim M.J. King J.K. Govender R.D. Mustafa H. Al Kaabi J. Epidemiology of Type 2 Diabetes—Global Burden of Disease and Forecasted Trends J. Epidemiol. Glob. Health 2020 10 107 111 10.2991/jegh.k.191028.001 32175717 254. Yung J.H.M. Giacca A. Role of c-Jun N-terminal Kinase (JNK) in Obesity and Type 2 Diabetes Cells 2020 9 706 10.3390/cells9030706 255. Liu M. Xin Z. Clampit J.E. Wang S. Gum R.J. Haasch D.L. Trevillyan J.M. Abad-Zapatero C. Fry E.H. Sham H.L. Synthesis and SAR of 1,9-dihydro-9-hydroxypyrazolo[3,4-b]quinoline-4-ones as novel, selective c-Jun N-terminal kinase inhibitors Bioorg. Med. Chem. Lett. 2006 16 2590 2594 10.1016/j.bmcl.2006.02.046 16527482 256. El-Sayed O.A. Habib N.S. Aboul-Enein H.Y. Costa B. Lucacchini A. Martini C. Synthesis and Benzodiazepine Receptor Binding Activity of 2,9-Disubstituted Quniolino[2′,3′-5,4](3-pyrazolino)[3,2-b]purin-4-ones Arch. Pharm. 2002 335 207 212 10.1002/1521-4184(200205)335:5<207::AID-ARDP207>3.0.CO;2-5 257. Cappelli A. Bini G. Valenti S. Giuliani G. Paolino M. Anzini M. Vomero S. Giorgi G. Giordani A. Stasi L.P. Synthesis and Structure—Activity Relationship Studies in Translocator Protein Ligands Based on a Pyrazolo[3,4-b]quinoline Scaffold J. Med. Chem. 2011 54 7165 7175 10.1021/jm200770f 21916402 258. Papadopoulos V. Baraldi M. Guilarte T.R. Knudsen T.B. Lacapère J.J. Lindemann P. Norenberg M.D. Nutt D. Weizman A. Zhang M.R. Translocator protein (18 kDa): New nomenclature for the peripheral-type benzodiazepine receptor based on its structure and molecular function Trends Pharmacol. Sci. 2006 27 402 409 10.1016/j.tips.2006.06.005 16822554 259. Dimitrova-Shumkovska J. Krstanoski L. Veenman L. Diagnostic and Therapeutic Potential of TSPO Studies Regarding Neurodegenerative Diseases, Psychiatric Disorders, Alcohol Use Disorders, Traumatic Brain Injury, and Stroke: An Update Cells 2020 9 870 10.3390/cells9040870 260. Sanger D.J. Zivkovic B. Discriminative stimulus effects of alpidem, a new imidazopyridine anxiolytic Psychopharmacology 1994 113 395 403 10.1007/BF02245215 7862851 261. Glickman J.F. Schmid A. Ferrand S. Scintillation Proximity Assays in High-Throughput Screening Assay Drug Dev. Technol. 2008 6 433 455 10.1089/adt.2008.135 18593378 262. Pai J.J.-K. Kirkup M.P. Frank E.A. Pachter J.A. Bryant R.W. Compounds Capable of Generating Singlet Oxygen Represent a Source of Artifactual Data in Scintillation Proximity Assays Measuring Phosphopeptide Binding to SH2 Domains Anal. Biochem. 1999 270 33 40 10.1006/abio.1999.4062 10328762 263. Mehrotra P.K. Shukla R. Dwivedi A. Srivastava R.P. Bhat N. Seth M. Bhaduri A.P. Kamboj V.P. Pregnancy interceptive efficacy and biological profile of 3-amino-6,7-dimethyl-1H-pyrazolo[3,4-b] quinoline (compound 85/83) in rodents Contraception 1991 43 507 519 10.1016/0010-7824(91)90140-B 1914462

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095583 ijerph-19-05583 Article High Performance Work Systems, Justice, and Engagement: Does Bullying Throw a Spanner in the Works? https://orcid.org/0000-0003-1865-0450 Baillien Elfi 1* https://orcid.org/0000-0003-4279-3136 Salin Denise 2 Bastiaensen Caroline V. M. 1 Notelaers Guy 3 Tchounwou Paul B. Academic Editor 1 Department of Work and Organisation Studies, Katholieke Universiteit Leuven (KU Leuven), 1000 Brussels, Belgium; caroline.bastiaensen@kuleuven.be 2 Department of Management and Organisation, Hanken School of Economics, 00100 Helsinki, Finland; denise.salin@hanken.fi 3 Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway; guy.notelaers@uib.no * Correspondence: elfi.baillien@kuleuven.be; Tel.: +32-230-022-12 04 5 2022 5 2022 19 9 558301 4 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). High performance work systems (HPWS) have typically been shown to positively influence employee attitudes and well-being. Research in the realm of HPWS has, in this respect, established a clear connection between these systems and employee engagement through organizational justice. In this study, we analyzed if being bullied affects this relationship. Using reasoning from Affective Events Theory (AET), we expected that the positive association between HPWS and engagement through perceptions of organizational justice is impaired by experiences of workplace bullying. Moreover, we expected a remaining direct effect between HPWS and engagement, also attenuated by bullying. Our results in a sample of service workers in Finland (n = 434) could not support the moderating role of bullying in the indirect effect. Workplace bullying did, however, impair the remaining direct relationship indicating it disrupts the positive effect of HPWS on engagement. In all, whereas HPWS were found to be beneficial for not bullied respondents, it was associated with decreased engagement for the bullied. Our findings further underscore the importance of preventing bullying in our workplaces, as it may significantly alter the outcomes of positively intended HR practices into an undesired result. workplace bullying mobbing high performance work practices affective events moderated mediation the Academy of Finland under308843 KU Leuven190256 (C3/19/001) the Research Council of Norway250127 This work was supported by the Academy of Finland under Grant 308843, by KU Leuven under Grant 190256 (C3/19/001), and by the Research Council of Norway, Grant Number 250127. ==== Body pmc1. Introduction While occupational health sciences have been the more traditional arena for developing insight in employee well-being, contemporary research in the field of human resource management (HRM) has been increasingly oriented towards policies and practices beneficial for well-being as well. In this respect, HRM scholars have to a large extent studied high-performance work systems (HPWS): a set of separate yet interconnected HR practices that aim to increase organizational performance by creating skilled, committed, and dedicated employees [1]. HPWS typically include aspects such as flexible work arrangements, valid selection procedures, performance-based reward systems, job-oriented training, and supporting management practices [2,3]. Research has well documented the favorable outcomes of HPWS in terms of the organization’s financial results as well as in terms of employee motivation, positive attitudes, and well-being [4]. A highly crucial factor in these findings pertains to the employee’s work engagement [5]: HPWS are found to be successful—for example, by increasing performance and lowering turnover [6,7]—through creating “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption” [8] (p. 210). Moreover, abundant research ascribed a significant role to organizational justice as a key mediator in the HPWS-engagement relationship (e.g., [9,10]). That is because HPWS signal the organization’s good intentions with its staff [11] and foster a balanced social exchange relationship between employers and employees [12]. Our current study builds on these earlier established insights. It starts from the indirect association between HPWS and work engagement though organizational justice as an important explanatory mechanism and aims to further merge this existing line of research into occupational health and well-being science. While many studies in the realm of HPWS have dug into the ‘why’ of these systems, far less is known about contextual aspects molding the process through which HPWS increase engagement via organizational justice [13]. In addition, even more so, the rather few studies looking at such potential moderators are predominantly framed by HRM’s disciplinary foci; testing factors such as trust in the organization [9], trust in senior management [14], perceived power distance [15], the employee’s age [16], and task proficiency [17]. With this, research to date has ignored that employees are part of a social reality including social interactions, and we are in the dark as to whether the established benefits from HPWS on work engagement persist when the employee is confronted with negative social behavior at work. Therefore, we want to examine whether and how the positive chain of HPWS-justice-engagement is molded by such negative social interactions in the form of workplace bullying, a clearly established topic in occupational health and well-being research [18]. Notably, studying workplace bullying as an issue in the indirect association between HPWS and engagement through justice is important. First, while recent HRM research has acknowledged the impact of how employees perceive their work environment and of their needs during the life and career span, the factors researched are predominantly depicted from a managerial angle looking at issues of organizational climate, policy, and staff subgroups. Moreover, the majority of HPWS research has operated from a motivational perspective and mainly investigated the role of positive factors, i.e., job resources, when looking at the HR systems’ impact on well-being and, more specifically, engagement. A profound knowledge about when HPWS contribute to well-being, however, requires insight in various types of moderators, including negative ones. Given that employees are not working in a social vacuum, social stressors that also significantly attack the employee’s work engagement call for attention. In occupational health research, workplace bullying has been established as one of the most detrimental social stressors at work [19], causing a plethora of negative consequences in its targets [20]. Given its severe impact on motivation and health [21], the evident question is whether the HPWS-engagement process still holds when employees are confronted with such a severe social stressor like bullying. Such insight advances knowledge about how detrimental occupational health phenomena may impact on the effects of—positively intended—organizational staff policies; putting it more central in the overall scientific and practical debates on when policies do and do not work. It can also enrich HPWS research and may further attest workplace bullying as a situation that calls for attention in organizations through prevention. Additionally, we have theoretical reasons to assume workplace bullying could be a significant influencing factor. HRM scholars have typically discussed the relationship between HPWS and engagement through organizational justice using Social Exchange Theory [12] and Signaling Theory [11]. We, however, see that this process can also be clarified by Affective Events Theory (AET) [22]; counterbalancing the former theories that have been applied in research before with a more emotion-driven perspective. That is, HPWS fuel perceptions of organizational justice because employees appraise the events stemming from these practices as helpful in matching their work context with their personal work goals; being the essential aim of HPWS [1,23]). These perceptions of justice entail positive emotions and affect bringing along positive consequences in the form of engagement. However, being targeted with workplace bullying, a situation which has also been linked to AET [24], will bring along negative consequences that impair the positive process stemming from HPWS. Such an event causing strong negative emotions may block the expected effect from the positive emotions part of organizational justice. In conclusion, our current study adds to the literature by introducing experiencing workplace bullying as a moderator that hampers the HPWS-justice-engagement process. With this, we contribute to (a) an improved insight in the interrelatedness of the positive chain stemming from HPWS with a well-known social stressor entailing a negative situation, and (b) a further integration of the occupational health sciences and the HRM research field allowing us to clarify the importance of bullying also in the light of human capital-oriented practices. 1.1. HPWS: Benefits for Work Engagement through Organizational Justice In all, HPWS are designed to enhance organizational output by empowering the employee and many studies have documented their positive outcomes. While, initially, studies have looked at the benefits of the intended (i.e., the policies and practices as developed at the organizational level) and actual (i.e., the practices as enacted and documented by line management) high-performance HRM practices, scholars have more lately focused their attention on how HPWS are perceived by their ultimate recipient, being the employee [25]. This is because, in the end, the employee’s perception of the practices affects how they are thinking, feeling, and behaving, and whether HPWS will lead to the intended outcomes for the staff and the organization [26]. Drawing on the ‘mutual gains’ perspective—the idea that HPWS add to positive employee-related outcomes on top of organizational performance [27]—scholars found a significant impact of HPWS on employee productivity (e.g., [28]), organizational commitment (e.g., [29]), organizational citizenship behavior (e.g., [30]), proactive behavior (e.g., [31]), and decreased turnover (e.g., [32]). Moreover, a plethora of studies indicated that HPWS contribute to increased well-being in the form of work engagement (e.g., [33,34,35]). The employee’s work engagement has been regarded as vital to HPWS as these systems are explicitly designed to have a positive effect on engagement and, in turn, performance [5,36]. In fact, one study detected that, the more well-being-oriented factor of, work engagement offered a more comprehensive explanation of performance as compared to job involvement, job satisfaction, and intrinsic [37]. Abundant research has explored the ‘why’ of HPWS’ impact on positive outcomes, and for work engagement it has pointed at organizational justice as a key explanatory mechanism: HPWS increase the employee’s justice perceptions that, in turn, bring along this perceived work engagement [9]. Organizational justice captures the extent to which employees perceive organizational events as being fair [38] and is typically manifested through three types. Procedural justice—the perceived fairness of decision-making procedures [39]—relates to a transparent decision-making process including the employee’s participation, which is the essence of HPWS. Interactional justice—a fair interpersonal treatment received from the employee’s managers during these procedures—focuses on social sensitivity and informational justification [40]. Such communication, being it to clarify the arguments behind a decision or to signal that management is receptive towards the employee’s input, is also part of HPWS. Finally, distributive justice—the perceived fairness of rewards—is high when the employee receives the correct rewards for the work that has been done, as compared with others in the organization [41]. HPWS integrate many performance-based practices balancing the effort—reward relationship. From a more general perspective, scholars have explained the HPWS-justice-engagement relationship using the Social Exchange Theory [12] that postulates an exchange-relationship between employers and employees. When the organization provides substantial inducements to its employees, they are more likely to reciprocate positively in attitudes and well-being [42]. Additionally, HPWS may signal the organization’s good intention with their employees (Signaling Theory) [43], as such contributing to their well-being. While a great number of studies investigated explanatory mechanisms, the literature on ‘when’ the HPWS foster positive well-being is far less developed. Moreover, this literature focuses on contextual factors fitting HRM scholars’ interest in what strengthens the positive effects of HPWS. For example, building on the proposition that trust molds the association between an interaction partner’s positive action and the receiver’s response, Farndale and colleagues [9] found empirical evidence of the boosting role of the employee’s trust in the organization. Similar results were found for a higher trust in senior management and a lower perceived power distance within the organization [14,15]. A study interested in a possible age-related difference in the positive outcomes of HPWS showed no significant impact of age [16] and concludes towards a seemingly robust desirable effect of HPWS for employees of all ages. Boon and Kalshoven [17] were among the first to indicate that HPWS are especially important for motivating employees who experience challenges in having sufficient skills and abilities in their work (i.e., low task proficiency) as rated by their supervisor. With this, they point at the role of these systems in getting the ‘weaker’ pawns in the organization aligned towards the organization’s goals. While this research has shed some light on how context can influence the HPWS process towards engagement, it falls short in tapping issues that, in the respect of engagement as a well-being outcome, are of particular interest from an occupational health perspective. More specifically, while employees are individuals with certain skills (or not) embedded in an organizational context, they work and interact with others and thus experience a social reality. Drawing on the earlier findings related to, for instance, the boosting impact of perceived trust and power distance in the organization [44], we can rather confidently argue for a beneficial impact in this relationship when looking at indicators of a positive social climate. In contrast, we do not know whether and how exactly the association of HPWS with engagement through justice is influenced when employees are confronted with significant negative events such as workplace bullying. Will the positive chain prevail even under such detrimental circumstances, or will these negative social behaviors block the employee’s opportunities to reap the benefits of HPWS? 1.2. Interference by Workplace Bullying While HPWS have generally been regarded as a positive investment from the organization in its employees and while studies have pointed at the many advantageous consequences of these practices, we thus ask ourselves whether these constructive outcomes remain when employees are confronted with workplace bullying. Workplace bullying refers to interpersonal mistreatment in which an employee is repeatedly targeted with negative social acts at work [45]. While many of these negative acts—including gossiping, spreading rumors, or withholding information—may not be problematic in isolation, they can cause severe harm when an employee experiences these in combination and over a longer period of time (e.g., six months) [46]. Consequently, workplace bullying has been shown to cause impaired well-being, such as physical health problems, burnout, symptoms of post-traumatic stress, increased intentions to leave, absenteeism, reduced job satisfaction and reduced organizational commitment [20]. While bullying can be enacted by any of the organizational members [47], it is typically characterized by a power disparity: the target experiences difficulties in defending him or herself against the perpetrator’s negative social behaviors [48,49]. As to why bullying brings along these negative effects, scholars have argued that it should be considered as an affective event [24,50,51]: experiences of bullying elicit emotions such as fear, anger, irritability, and shame [52,53] that could mold the plethora of negative outcomes in its targets. This reasoning ties in with Affective Events Theory (AET) [22] from which we can derive that what happens at work shapes the employee’s attitudes and well-being through not only cognitive but also emotional information processing. Given that workplace bullying confronts its targets with prolonged negative social acts that threatens the employees’ overall functioning as well as self-esteem and social belongingness [50], a range of studies have successfully applied AET as a framework explaining negative outcomes such as decreased engagement, lowered job satisfaction, higher intention to leave the organization, organizational commitment. AET could even account for notable detrimental outcomes such as accidents and injuries in healthcare (e.g., [24,51,54,55,56]). Interestingly, however, while HRM scholars have mostly looked at the HPWS-justice-engagement chain from the perspectives of social learning [12] or signaling theory [43], we also see an obvious link with AET. More specifically, AET postulates that work attitudes and responses—such as engagement—stem from an accumulation of affective responses elicited by the work environment [22]. In this process, the employee evaluates work events as being helpful versus harmful to reach their relevant goals. Helpful events bring along positive feelings, whereas events hampering goal process result in negative feelings. Then, the employee considers additional details about the events (e.g., who is responsible, or can it be easily addressed) that leads to more specific emotions (e.g., joy, fear, or anger) [22]. Applying this to HPWS, justice, and engagement, it is clear that HPWS are designed with the aim of reaching work goals [23] that—according to AET—add to positive emotions manifested in perceptions of organizational justice [9]. This is because, whereas injustice relates to negative emotions and to undesirable outcomes, justice entails positive emotions and positive outcomes [57,58]. In other words, HPWS are helpful for the employees in reaching their goals and manifest themselves through the positive affective state of perceived organizational justice and the positive outcome of work engagement. Taken together, the association between HPWS and work engagement through organizational justice ties in with a positive affect process, while workplace bullying entails a negative affect process that, as a social, relational stressor, may attenuate the HPWS-justice-engagement chain. From this, we formulate following hypothesis: Hypothesis 1: The indirect association between HPWS and engagement through organizational justice is buffered by the experience of workplace bullying (i.e., moderated mediation). Notably, organizational justice is just one possible manifestation of positive affect and other factors could also be at stake as a potential explanatory mechanism in the link between HPWS and engagement. Consequently, in addition to the indirect association through justice, we still expect a direct relationship between HPWS, and engagement remains which, from an AET lens, could still be impacted by the negative event of workplace bullying; and also include this in our analyses. We, thus, assume: Hypothesis 2: The remaining direct association between HPWS and engagement is buffered by the experience of workplace bullying (i.e., moderation). Our research model is depicted in Figure 1. 2. Method 2.1. Procedure and Sample A survey was conducted in Finland among service workers (n = 434) in collaboration with Service Union United PAM; a Finnish trade union for people working in private service sectors. PAM has almost 200,000 members in total, and these are employed across a large number of private organizations, in sectors such as retail trade (largest sector), hotel and restaurant services, cleaning and property services, and security services. The sample size was determined in negotiation with the union. The research director of PAM distributed an online version of the survey to 5000 randomly selected members. The recipients received a cover letter and a link to the survey. As Finland is a bilingual country, the survey was available in both Finnish and Swedish and the respondents themselves could choose the language. The sample’s mean age was 39 years (SD = 11.69), ranging from 17 to 63 years. About 78% of the participants were female, and 10% of the participants held a supervisory position. Regarding tenure, 34% of the participants were employed within their current organization for more than 10 years, and 20% had worked for their employer for less than one year. 2.2. Measures All concepts part of our research model were measured using internationally validated scales. High-performance work systems (HPWS) (α = 0.93) were assessed using 24 items from Chuang and Liao [59]. On a five-point Likert scale ranging from ‘strongly disagree’ (=1) to ‘strongly agree’ (=5), the respondents replied on statements related to six different areas of HR: staffing (e.g., “Recruitment emphasizes traits and abilities required for performing well in this organization”), training (e.g., “My organization invests considerable time and money in training”), performance appraisal (e.g., “Performance appraisals are based on objective, quantifiable results”), compensation (“Employee salaries and rewards are determined by their performance”), participation (e.g., “If a decision made might affect employees, the organization asks them for opinions in advance”), and caring (e.g., “My organization has formal grievance procedures to take care of employee complaints and appeals”). Organizational justice (α = 0.88) was measured using eight items from Elovainio and colleagues [60]. The respondents indicated on a five-point Likert scale to what extent they agreed (‘strongly disagree’ = 1; ‘strongly agree’ = 5) to statements tapping procedural justice (e.g., “I can express my views and feelings when decisions are made/procedures are applied”), interactional justice (e.g., “My supervisor tailors his/her communications to individuals’ specific needs”), and distributive justice (e.g., “My compensation reflects the effort I have put into my work”). Five items from Utrecht Work Engagement Scale (UWES) [61] were used to measure work engagement (α = 0.94). The items were addressed using a seven-point Likert scale ranging from ‘never’ (=0) to ‘a few times a year or less’ (=1), ‘once a month or less’ (=2), ‘a few times a month’ (=3), ‘once a week’ (=4), ‘a few times a week’ (=5) and ‘every day’ (=6). Example items are “At work, I feel bursting with energy” (vigor), “When I get up in the morning, I feel like going to work” (dedication) and “I am immersed in my work” (absorption). The experience of workplace bullying behaviors (α = 0.93) was assessed using the Short Negative Acts Questionnaire (S-NAQ) [62]. Respondents had to indicate how often, during the last 6 months, they experienced nine bullying behaviors (e.g., “Silence or hostility as a response to your questions or attempts at conversations”). These items were tapped using a five-point Likert scale ranging from ‘never’ (=1) to ‘now and then’ (=2), ‘monthly’ (=3), ‘weekly’ (=4), and ‘daily’ (=5). 2.3. Plan of Analysis Overall, most scholars have applied (mean) sum scores, standard deviations, and analyses of variance when studying workplace bullying. However, bullying typically follows a negative binomial distribution. While valuable in shedding some light on this phenomenon, these more dominantly used techniques generally assume a normal distribution and could therefore challenge their statistical conclusion validity in terms of workplace bullying [63]. Therefore, in this study, we modeled experiencing workplace bullying as several exposure categories (i.e., categorical variable). We followed the upcoming statistical approach in bullying research by applying a Latent Class Cluster Analysis (LCCA) technique: studies using LCCA detected qualitatively different clusters (subgroups of respondents) each showing a different combination and frequency of the various negative social behaviors measured [62,64,65]. Notably, LCCA has particular advantages as compared to classical clustering techniques (e.g., K-means): as a model-based approach it allows for statistical tests in determining the number of clusters [66], and it is insensitive for different variances in the items part of the measurement [67] which suits the S-NAQ [62]. Therefore, in our analyses, we first identified different profiles of bullying using LCCA in Latent Gold 5.0 (Statistical Innovations, Arlington, TX, USA). Then, we tested our hypotheses using Hayes’ [68] PROCESS macro v3.5 (model 15) in SPSS 25 (IBM, Armonk, NY, USA) in which we introduced workplace bullying as a categorical variable accommodating for the possible presence of different profiles. 3. Results 3.1. Identifying the Targets of Bullying LCCA first groups all respondents into one cluster, and sequentially adds clusters until a measurement model is found that fits the data best [67]. Model fit is assessed based on the Bayesian Information Criterion (BIC; this should be low), L2 (using bootstrapping following Langeheine, Pannekoek, & Van de Pol [69]; this should be non-significant), the total amount of bivariate residuals (BVR; should be low), and the bivariate association between the indicators (reduced with at least 85%). Finally, the reduction in L2 signals how much of the association between the indicators is explained by adding an additional cluster. Table 1 lists the statistics of the LCCA for our data, supporting us in selecting the best clustering for our data. First, the criteria indicated that our respondents should be allocated to a number of latent class clusters (instead of one). However, a close inspection of the profiles showed that, from the point that four clusters had been identified, Latent Gold kept extracting extra clusters between the response categories of 1 (never) and 2 (occasionally) without much extra change in the fit criteria, which led us to focus on the first 5 cluster solutions. In the 5-cluster solution, the total amount of bivariate residuals (BVR) decreased strongly, from 7111 to 39.2. However, already in the 4-cluster solution, 99% of the residuals had been accounted for. In addition, the total amount of BVR in the 4-cluster solution was significantly lower (ΔBVR = 61.3) than in the 1-cluster solution. A detailed look at the bivariate associations between the indicators showed that, compared to the 1-cluster model, all bivariate residuals were reduced with a least 97%. Finally, the bootstrap of the L2 was not significant (p = 0.124); and the decrease in L2 notably declined from the 3-cluster to the 4-cluster solution (ΔL2 = 152.7) with ΔL2 from the 4-cluster to the 5-cluster solution reaching only 113. Combining these points—the extra extraction of theoretical less relevant latent clusters when extracting 5 or more clusters combined with satisfactory fit criteria—we concluded that four clusters are sufficient and best suitable to our data. The first cluster (41%) entailed the ‘not bullied’ with showing an average conditional probability of approximately 0.85 to respond ‘never’ to the NAQ-items. The second cluster (40%) were ‘rarely confronted with negative encounters’: their average conditional probability to respond ‘never’ to the items was still 0.25; however, that of responding ‘occasionally’ was approximately 0.50. Their average probability to respond ‘weekly’ or ‘daily’ was less than 0.05. In the third cluster, the ‘occasionally bullied’ (16%), the average probability to respond ‘never’ to the items was close to 0.05. Yet, the average probability of responding ‘occasionally’ or ‘monthly’ was approximately 0.55. The fourth cluster (2%) consisted of ‘severe targets’ of bullying. In this group, the conditional probability to respond ‘never’, ‘occasionally’, or ‘monthly’ to the items is nearly zero. The conditional probability of responding ‘weekly’ or ‘daily’ exposure to the negative acts is close to or higher than 0.90. In all, the analysis showed that there are four different latent profiles reflecting a certain exposure level to bullying. These will be used as the moderator in the subsequent analysis. 3.2. Test of Hypotheses Table 2 summarizes the means, standard deviations, and correlations of our measurements. Overall, HPWS correlated positively with organizational justice and work engagement. Justice correlated positively with engagement. Notably, the probability of being ‘not bullied’ associated positively with HPWS, justice, and engagement. The probability of being ‘rarely confronted with negative encounters’ correlated negatively with HPWS and justice but was unrelated to engagement. The probability of being ‘occasionally bullied’ was negatively related to HPWS, justice, and engagement. Being a ‘severe target’ correlated negatively with justice and engagement, and not with HPWS. These results give a first, more nuanced view on bullying in the context of our study, pointing at the importance of approaching this phenomenon as different exposure groups. We tested our research hypotheses introducing experiencing workplace bullying as a categorical variable in line with the LCCA results. More specifically, bullying was included in the analyses using the following reference coding: (1) ‘rarely confronted with negative encounters’ as compared to the other latent clusters, (2) ‘occasionally bullied’ as compared to all other clusters, and (3) severe targets as compared to the other clusters. The model (see Table 3) explained 32.67% of the variance in engagement: 29% was accounted for by the main effects, while the moderation of the direct paths between HPWS and engagement accounted for 4.69% of the variance explained. The moderation of the indirect path between HPWS and engagement through organizational justice was not significant, with the absolute value of the Index of Moderated Mediation being smaller than 1.96 times the bootstrapped standard error (boot se) (‘rarely confronted with negative encounters’: −0.014, boot se of 0.192; ‘occasionally bullied’: 0.015, boot se of 0.273; ‘severe target’: 2.506, boot se of 2.951); rejecting hypothesis 1. However, and interestingly, when looking at the exposure groups specifically, the indirect effect of HPWS and engagement through organizational justice was significant for the ‘not bullied’ (0.463 **), ‘rarely confronted with negative encounters’ (0.448 **), and ‘occasionally bullied’ (0.478 **). For the ‘severe targets’, organizational justice did not mediate the HPWS-engagement relationship. Our results did reveal a significant interaction of bullying on the remaining direct relationship between HPWS and engagement. Specifically, for the ‘not bullied’ the relationship was not significant (b = 0.268; p = 0.170). For the ‘rarely confronted with negative encounters’, this relationship was positive and significant (b = 0.876; p < 0.001). In contrast, this relationship was slightly negative—yet not significant—for the ‘occasionally bullied’ (b = −0.422; p = 0.157). Finally, among the ‘severe targets’ the relationship was strongly negative and significant (b = −2.847; p < 0.001). These findings correspond with hypothesis 2, and further nuances it in terms of the bullying exposure groups: whereas HPWS were beneficial for the engagement of the ‘non bullied’ and those ‘rarely confronted with negative encounters’, HPWS related to decreased engagement for the ‘severe targets’. In all, the results confirmed a positive relationship between HPWS and engagement, and suggested that workplace bullying acts as a moderator (note that including gender (0 = male; 1 = female), tenure (in years), and supervisory position (0 = no; 1 = yes) in our analyses did not alter our results and conclusions). More precisely, when employees are subjected to high levels of bullying, the positive relationship between HPWS and work engagement diminishes. 4. Discussion The current study aimed to shed light on whether and how the social stressor and negative affective event of workplace bullying molds the manifoldly reported positive association between HPWS and work engagement through organizational justice in HRM research. With this, we introduced an important impairing occupational health issue as to further knowledge on positively intended organizational staff policies and practices. Our study advanced the bullying literature by drawing focus to this form of interpersonal mistreatment, as a social stressor, in the overall scientific debates on when HRM policies do and do not work. Moreover, we adhered to notable considerations regarding the statistical conclusion validity of existing research that has approached workplace bullying through sum scores in analyses of variance: we tied in with the evolution of modeling bullying as several exposure categories established through Latent Class Cluster Analysis [63]. Finally, our study also contributed to HPWS research by responding to several calls for more research on individual-level conditions under which HRM affects employee attitudes [13,15]. In all, our results tie in with the established indirect association between HPWS, organizational justice, and engagement (e.g., [9,10]); yet—contrary to our expectations—we could not detect a significant moderation of the workplace bullying exposure categories. From this, we could derive that the positive chain of HPWS-justice-engagement is not impacted by events of workplace bullying. However, digging into the more detailed situation for each of the bullying exposure groups, we can further nuance this. More specifically, for the employees belonging to the ‘not bullied’, ‘rarely confronted with negative encounters’, and ‘occasionally bullied’ groups, the indirect effect was significant and, thus, remains. This is in contrast with employees in the ‘severe target’ group for whom HPWS did not relate to organizational justice and, subsequently, engagement. In other words, for employees frequently experiencing these negative social behaviors at work, the organization’s investment in HR practices to create committed and engaged employees through increased feelings of justice [1] are not paying off. From a bullying perspective, these findings are highly intriguing as scholars have been trying to gain a better understanding in how exactly organizational justice and its consequences can be grasped in the light of bullying. While some identified bullying as a consequence of injustice (e.g., [70,71]), others have looked at justice as a buffer protecting bullying victims from negative well-being (e.g., [72]). In a recent study of 280 cases, Neall, Li, and Tuckey [73] could add another perspective to this debate: from formally reported bullying, they saw that this—by the target described events of low justice in response to their several complaints as part of a bullying case—fueled further escalation of the bullying and its consequences for these targets. From this and looking at our own results, we might consider the idea that employees yield a qualitatively different interpretation of and focus on their work context, depending on which exposure group they belong to, molding our observed effects. That is, employees belonging to the not-bullied categories (the largest group with no or very limited social issues in this respect) may not be inclined to reflect more critically on the organization’s practices, leading them to acknowledge the HPWS as stemming from good intentions and to perceive organizational justice [74]. In this situation, HPWS was related to engagement through justice. The same was so for the occasionally bullied who might not be questioning the overall organization in the light of their situation, yet could be more drawn towards sensemaking in terms of their more direct social interactions (for example, by attributing the situation to one or more ‘bad apples’) [75]. In contrast, severe targets might have been stranded in a situation in which the nature of bullying directs their sensemaking to negative issues sustaining the events (i.e., no significant indirect path). Clearly, there still is much to unravel when it comes to our understanding of justice in the context of workplace bullying. While the impact of the bullying exposure groups on the indirect association was non-significant, we did find an interaction of bullying on the remaining direct relationship between HPWS and engagement. Again, we see quite an interesting pattern when looking at the groups separately: whereas the relationship between HPWS and engagement was non-significant for the ‘non-bullied’, it was positive for those ‘rarely confronted with negative encounters’, non-significant for the ‘occasionally bullied’, and negative for the ‘severe targets’. These findings support our assumption that bullying can be regarded as a disruptive social factor in reaching the HPWS aims. Interestingly, from our more overall results, it seems that for the ‘non-bullied’ the link between these HR practices and engagement can entirely be explained by justice. Or, when not being confronted with negative social behavior at all, the HPWS do relate to higher perceived justice and, following, engagement. For the ‘rarely confronted with negative encounters’ HPWS related to engagement through justice and directly. The ‘occasionally bullied’ follow the results for the ‘non bullied’, yet they are the first group to show a shift in the remaining direct association between HPWS and engagement. Finally, the severe targets never benefit from the HPWS; neither indirectly nor in the remaining direct effect as these practices will, for them, strongly decrease their engagement. In all, we may conclude from our study that, whereas HPWS are beneficial for the engagement of the non and rarely confronted with negative encounters, they decrease the engagement for the bullied. In formulating our hypotheses, we built on established knowledge on why HPWS may mold engaged employees and subsequently ‘work’ for the organization in terms of performance and much-desired results. Looking at organizational justice as an important mediator in this respect, we broadened the existing theoretical lenses in the HPWS research stream—Signaling Theory [43] and Social Exchange Theory [12]—with Affective Event Theory (AET) [22]. Using AET as a shared framework in explaining effects of both HPWS and bullying helped us in merging and further contextualizing studies that have been conducted in very separate fields of research. Notably, as also indicated when explicating our research hypotheses, justice is but one possible manifestation of positive affect, and other mediators—now part of the remaining direct effect—might play a role as well. Some examples in this respect could perhaps be perceived organizational support or even rebalancing the employee’s psychological contract from transactional to a more relational one [29,44]. However, while AET largely focuses on the affective process behind human responses to situations, it also yields a less developed cognitive path. Or, while events trigger outcomes through affective states, the theory still acknowledges that they could do so through cognitions. From this angle, an explanation for our current findings regarding the direct effect might be a structural aspect: one conceptual paper proposed that HPWS relate positively to what they merge under the term of internal social structure—including facilitating network ties, generalized norms of reciprocity, shared mental models, and role making/taking—thereby reaching positive employee attitudes, well-being, and performance [13]. Going back to the characteristics of the several bullying exposure groups and our results on the direct moderation, we could reason that the components defined as part of this internal social structure are in fact highly challenged because of the pattern of negative social behaviors experienced in the severe target group. From a more meta-theoretical perspective, we could then also think along the lines of Conservation of Resources Theory (COR) [76]. Central to COR are resources, defined as ’those objects, personal characteristics, conditions, or energies that are valued by the individual or that serve as a means for attainment of these objects, personal characteristics, conditions, or energies’ [77] (p. 516). Overall, resources add to positive outcomes such as growth and well-being. A (threat of) resource loss brings along energy depletion, stress, and negative outcomes. Studies to date have successfully applied COR to bullying and their findings established that experiences of bullying trigger a process of resource loss (e.g., [78,79]). Subsequently, adhering to the idea of an improved internal social structure when installing or promoting HPWS, bullying may well be depleting the employees’ accessibility to the beneficial resources part of such a structure. This might explain why the direct association between HPWS and engagement shifted from a positive to a negative association for the ‘occasionally bullied’. In all, from our research we may derive some important points. First, investigating which stress-inducing individual-level events or social situations impact on well-intended organizational policies and practices for improving employee engagement and motivation matters. We were the first to sketch a more nuanced image on HPWS as such a practice, combined with bullying as a social stressor. Notably, the significance of combining motivational and stress-related processes in explaining a range of outcomes has been underscored already many decades ago by Karasek [80]. With this study, we want to encourage scholars to further integrate insights from the occupational health and well-being field into better understanding the impact of motivational organizational policies. Second, looking at bullying as a phenomenon entailing qualitatively different exposure clusters is important. Our findings underscore that the reality when it comes to being bullied is far more complex—with differentiated results over the exposure groups—than a story of low versus high exposure. Research on workplace bullying will undoubtedly benefit from applying a LCCA lens for truly fine graining this form of interpersonal mistreatment. 4.1. Limitations and Future Research As with any research, our study entails some limitations that would be valuable to being addressed in future research. First, we have built on cross-sectional data; implying we could not unravel time-based associations between the concepts part of our study. As we build on the much-established chain of HPWS-organizational justice-engagement, we see no grand issues for the indirect effect. Moreover, given that we are the first to introduce an individual-level social stressor in this indirect chain, we tied in with Spector [81] who indicated that “it makes sense to start new areas of inquiry with the most efficient methods to provide initial evidence that a research question is deserving of attention” [81] (p. 129). Our findings have surely contributed to some first insights on the influence of bullying in HPWS and their presumed beneficial effects. Nevertheless, while having lifted a corner of the veil, future studies could progress our current understanding by longitudinally and more dynamically exploring where in time being bullied plays a role in the indirect process, which might even be different for various exposure groups. Second, we relied on single-source, self-reports and, consequently, our results could have been impacted by common method bias [82]. However, self-reported measures are suitable in this study, given our explicit aim to investigate (a) how HPWS are perceived by the employee (following evolutions in this research stream) [25], (b) how this relates to perceived organizational justice [83], and (c) the employee’s own experience of being bullied. Regarding bullying specifically, meta-analytical evidence [84] underscored that self-reports provide a more reliable and valid assessment of mistreatment than did other-reports when surveys were anonymous, which was the case in our study here. Moreover, we have followed further recommendations to diminish common method bias by, for example, emphasizing the voluntary nature of this study and by ensuring the respondents that there were no correct or wrong answers [82]. In addition, we inspected method bias by comparing the fit of our theoretically expected factor model—χ2(939) = 1738.84, p <0.001; CFI =0.94, TLI = 0.93, RMSEA = 0.04—to a single factor test (Harman, 1979) which produced a significantly poorer fit to our data; χ2(989) = 7733.17, p <0.001; CFI = 0.46, TLI = 0.43, RMSEA = 0.13. In addition, the more advanced approach including a common method factor did not reveal an improved statistical fit. This is because, given the large number of latent factors to be estimated in this latter approach on our sample of 434 respondents, the analyses failed to estimate the model’s standard errors and is therefore poorly defined. Finally, interaction effects are hardly induced by method bias [85] which is, in fact, more likely to attenuate rather than to strengthen interactions [86]. Third, some other limitations relate to our sample. A vast majority of our participants worked in retail trade and that sector was clearly overrepresented compared with other subsectors (when looking at where PAM members in general work). Women made up 78% of the sample compared to 76% in PAM overall so—even while our study’s sample is dominated by female employees—this seems to reflect the real gender distribution quite well. Relatively few (11 out of 434) reported another native language than Finnish or Swedish, suggesting immigrants may have been less likely to respond (5% of all PAM members according to their own reports). In addition, our sample was relatively small in size, due to which we analyzed the mean scores of HPWS and organizational justice. In addition, that hypothesis 1 was rejected while the interaction effect added 1% to the explained variance of engagement might question of whether our study was somewhat underpowered. Future studies could collect larger and more heterogeneous samples that allow for testing the different aspects of HPWS and organizational justice, for further knowledge on how exactly bullying impacts on these components in view of employee well-being. Finally, our reasoning builds on AET [22] without explicitly testing the several components of this theory. Future research could therefore see how AET could be more explicitly applied when integrating the HRM and occupational health and well-being research streams. These studies could, for example, specifically tap the emotions and affects at stake in boosting versus attenuating the positive impact of HPWS on well-being from the perspective of bullying, which would be particularly interesting in more dynamic and shortitudinal research designs [87]. 4.2. Implications for Practice Our findings show that the association between HPWS and work engagement does not always hold: for those severely bullied, we found a negative relationship between HPWS and engagement. This underscores that social relationships are an important part of the equation regarding the effects of such systems. For organizations having already invested in HPWS, it implies that not only investment in the staff’s motivation and engagement matters, yet that they should similarly work on workplace bullying prevention as to ensure the systems will manifest themselves in the desired outcomes. Organizations considering implementing HPWS are encouraged to first assess their situation in terms of bullying to increase the success of this effort. In other words, investing in occupational health outruns merely putting energy in motivational practices: when organizations are aiming at engagement from their staff, they should be aware of how their policies—implemented with good will—are influenced by more individual social stressors, such as workplace bullying. Moreover, our study draws attention to being aware that bullying is not a continuum. In contrast, when categorizing respondents based on the frequency and the nature of the reported negative social behaviors, we see a so much more nuanced picture of what is happening. Either way, we revealed the first evidence of how important being bullied really is in the context of ensuring organizational efforts for motivating staff, such as HPWS, to translate in desired positive outcomes. Or, to put it differently: when it comes to bullying, prevention really is key. 5. Conclusions Our study points at the importance of being bullied as a negative social event experienced by individual workers in disrupting the positive effect of HPWS on engagement (through organizational justice). With this, we demonstrated that bullying does not only lead to negative effects on target attitudes and well-being as shown by previous research, but that it contextualizes the effects of organizational HR practices explicitly designed to advance employee engagement, motivation, and well-being, and are generally associated with positive employee outcomes. Overall, HPWS were beneficial for not bullied respondents, yet decreased engagement in bullied employees. As such, we further attest the value of workplace bullying prevention in organizations, as it may significantly alter the desired results of positively intended HR practices. Acknowledgments The authors would like to thank Robin Sundman for help with data collection. Author Contributions Conceptualization, E.B., D.S. and G.N.; methodology, D.S.; formal analysis, G.N. and C.V.M.B.; data curation, D.S. and G.N.; writing—original draft preparation, E.B.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Hypothesized research model. ijerph-19-05583-t001_Table 1 Table 1 Determining the number of the bullying exposure clusters: LCCA fit statistics. BIC (LL) AIC (LL) AIC3 (LL) Npar L² Total BVR VLMR Class. Err. Entropy R² in % 1-Cluster 9346.3 9200.5 9236.5 36 4760.4 7111.0 - 0.0 100 2-Cluster 8084.2 7898.0 7944.0 46 3437.9 1050.5 1322.5 2.93 90.19 3-Cluster 7719.5 7492.9 7548.9 56 3012.7 143.6 425.1 5.10 88.17 4-Cluster 7627.3 7360.2 7426.2 66 2860.0 61.3 152.6 5.67 87.26 5-Cluster 7574.6 7267.0 7343.0 76 2746.9 39.2 113.1 8.68 84.14 ijerph-19-05583-t002_Table 2 Table 2 Means, SD, and (auto)correlations of the studied concepts. M SD 1 2 3 4 5 6 1. HPWP 2.586 0.739 0.901 2. Organizational Justice 3.049 0.890 0.708 ** 0.878 3. Engagement 5.030 0.527 0.419 ** 0.491 ** 0.923 4. Probability to be not bullied 0.416 0.466 0.303 ** 0.488 ** 0.274 ** - 5. Probability to be rarely exposed 0.402 0.445 −0.132 ** −0.230 ** −0.071 −0.680 ** - 6. Probability to be occasionally bullied 0.159 0.343 −0.198 ** −0.292 ** −0.219 ** −0.415 ** −0.312 ** - 7. Probability to be a target of bullying 0.024 0.151 −0.093 −0.164 ** −0.142 ** −0.140 ** −0.141 ** −0.067 Note. **: 0.001 ≤ p < 0.01. Autocorrelations are presented in italics. ijerph-19-05583-t003_Table 3 Table 3 Results of the Moderation Mediation Analyses for engagement, including workplace bullying as a categorical variable (based on LCCA). Predictors Unstandardized Beta R2 Intercept 5.157 *** HPWS 0.268 Organizational Justice 0.541 ** Rarely confronted with negative encounters −0.043 Occasionally bullied −0.591 * Severe target 0.013 29.03 HPWS * rarely confronted with negative encounters 0.608 * HPWS * occasionally bullied −0.689 * HPWS * severe target −3.115 *** 4.69 *** Organizational Justice * rarely confronted with negative encounters −0.016 Organizational Justice * occasionally bullied 0.018 Organizational Justice * severe target 2.933 * 1.05 Total 32.67 Note. (*): 0.05 ≤ p < 0.10; *: 0.01 ≤ p < 0.05 **: 0.001 ≤ p < 0.01 and ***: p < 0.001. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ogbonnaya C. Daniels K. Connolly S. van Veldhoven M.J. Nielsen K. Employees, Managers, and High Performance Work Practices: A “Win-Win” or the Transformational Leader’s Exploitative Approach to Organizational Performance Understanding the High Performance Workplace: The Line between Motivation and Abuse Ashkanasy N.M. Bennett R.J. Martinko M.J. Routledge London, UK 2016 57 80 2. Kroon B. Van De Voorde K. Timmers J. High performance work practices in small firms: A resource-poverty and strategic decision-making perspective Small Bus. Econ. 2013 41 71 91 10.1007/s11187-012-9425-0 3. Topcic M. Baum M. Kabst R. Are high-performance work practices related to individually perceived stress? A job demands-resources perspective Int. J. Hum. Resour. Manag. 2016 27 45 66 10.1080/09585192.2015.1043136 4. Kehoe R.R. Wright P.M. The impact of high-performance human resource practices on employees’ attitudes and behaviors J. Manag. 2013 39 366 391 10.1177/0149206310365901 5. Rana S. High-involvement work practices and employee engagement Hum. Resour. Dev. Int. 2015 18 308 316 10.1080/13678868.2014.1003698 6. Huselid M.A. The impact of human resource management practices on turnover, productivity, and corporate financial performance Acad. Manag. J. 1995 38 635 672 7. Messersmith J.G. Patel P.C. Lepak D.P. Gould-Williams J.S. Unlocking the black box: Exploring the link between high-performance work systems and performance J. Appl. Psychol. 2011 96 1105 1118 10.1037/a0024710 21787040 8. Demerouti E. Mostert K. Bakker A.B. Burnout and work engagement: A thorough investigation of the independency of both constructs J. Occup. Health Psychol. 2010 15 209 222 10.1037/a0019408 20604629 9. Farndale E. Hope-Hailey V. Kelliher C. High commitment performance management: The roles of justice and trust Pers. Rev. 2011 40 5 23 10.1108/00483481111095492 10. Heffernan M. Dundon T. Cross-level effects of high-performance work systems (HPWS) and employee well-being: The mediating effect of organisational justice Hum. Resour. Manag. J. 2016 26 211 231 10.1111/1748-8583.12095 11. Suazo M.M. Martínez P.G. Sandoval R. Creating psychological and legal contracts through human resource practices: A signaling theory perspective Hum. Resour. Manag. Rev. 2009 19 154 166 10.1016/j.hrmr.2008.11.002 12. Blau P.M. Social exchange Int. Encycl. Soc. Sci. 1968 7 452 457 13. Evans W.R. Davis W.D. High-performance work systems and organizational performance: The mediating role of internal social structure J. Manag. 2005 31 758 775 10.1177/0149206305279370 14. Farndale E. Kelliher C. Implementing performance appraisal: Exploring the employee experience Hum. Resour. Manag. 2013 52 879 897 10.1002/hrm.21575 15. Wu P.C. Chaturvedi S. The role of procedural justice and power distance in the relationship between high performance work systems and employee attitudes: A multilevel perspective J. Manag. 2009 35 1228 1247 10.1177/0149206308331097 16. Veth K.N. Korzilius H.P. Van der Heijden B.I. Emans B.J. De Lange A.H. Which HRM practices enhance employee outcomes at work across the life-span? Int. J. Hum. Resour. Manag. 2019 30 2777 2808 10.1080/09585192.2017.1340322 17. Boon C. Kalshoven K. How high-commitment HRM relates to engagement and commitment: The moderating role of task proficiency Hum. Resour. Manag. 2014 53 403 420 10.1002/hrm.21569 18. Conway P.M. Burr H. Rose U. Clausen T. Balducci C. Antecedents of workplace bullying among employees in Germany: Five-year lagged effects of job demands and job resources Int. J. Environ. Res. Public Health 2021 18 10805 10.3390/ijerph182010805 34682549 19. Hauge L.J. Skogstad A. Einarsen S. The relative impact of workplace bullying as a social stressor at work Scand. J. Psychol. 2010 51 426 433 10.1111/j.1467-9450.2010.00813.x 20338011 20. Nielsen M.B. Einarsen S. Outcomes of exposure to workplace bullying: A meta-analytic review Work. Stress 2012 26 309 332 10.1080/02678373.2012.734709 21. Trépanier S.G. Fernet C. Austin S. Longitudinal relationships between workplace bullying, basic psychological needs, and employee functioning: A simultaneous investigation of psychological need satisfaction and frustration Eur. J. Work. Organ.Psychol. 2016 25 690 706 10.1080/1359432X.2015.1132200 22. Weiss H.M. Cropanzano R. Affective events theory Res. Organ. Behav. 1996 18 1 74 23. Mostafa A.M.S. High-performance HR practices, positive affect and employee outcomes J. Manag. Psychol. 2017 32 163 176 10.1108/JMP-06-2016-0177 24. Glasø L. Vie T.L. Holmdal G.R. Einarsen S. An application of affective events theory to workplace bullying the role of emotions, trait anxiety, and trait anger Eur. Psychol. 2010 16 198 208 10.1027/1016-9040/a000026 25. Wright P.M. Nishii L.H. Strategic HRM and Organizational Behaviour: Integrating Multiple Levels of Analysis. Presented at the International Seminar on ‘HRM. What’s Next?’, Rotterdam, The Netherlands 2004 Available online: https://ecommons.cornell.edu/handle/1813/77351 (accessed on 30 March 2022) 26. Purcell J. Understanding the People and Performance Link: Unlocking the Black Box CIPD Publishing London, UK 2003 27. Valizade D. Ogbonnaya C. Tregaskis O. Forde C. A mutual gains perspective on workplace partnership: Employee outcomes and the mediating role of the employment relations climate Hum. Resour. Manag. J. 2016 26 351 368 10.1111/1748-8583.12113 28. Sikora D.M. Ferris G.R. Van Iddekinge C.H. Line manager implementation perceptions as a mediator of relations between high-performance work practices and employee outcomes J. Appl. Psychol. 2015 100 1908 1918 10.1037/apl0000024 26011722 29. Bal P.M. Kooij D.T. De Jong S.B. How do developmental and accommodative HRM enhance employee engagement and commitment? The role of psychological contract and SOC strategies J. Manag. Stud. 2013 50 545 572 10.1111/joms.12028 30. Wei Y.C. Han T.S. Hsu I.C. High-performance HR practices and OCB: A cross-level investigation of a causal path Int. J. Hum. Resour. Manag. 2010 21 1631 1648 10.1080/09585192.2010.500487 31. Beltrán-Martín I. Bou-Llusar J.C. Roca-Puig V. Escrig-Tena A.B. The relationship between high performance work systems and employee proactive behaviour: Role breadth self-efficacy and flexible role orientation as mediating mechanisms Hum. Resour. Manag. J. 2017 27 403 422 10.1111/1748-8583.12145 32. Thoonen I. Effecten van Human Resource Management op Betrokkenheid, Tevredenheid en Verloop Universiteit van Tilburg Tilburg, The Netherlands 2005 33. Alfes K. Shantz A.D. Truss C. Soane E.C. The link between perceived human resource management practices, engagement and employee behaviour: A moderated mediation model Int. J. Hum. Resour. Manag. 2013 24 330 351 10.1080/09585192.2012.679950 34. Kloutsiniotis P.V. Mihail D.M. Linking innovative human resource practices, employee attitudes and intention to leave in healthcare services Empl. Relat. 2017 39 34 53 10.1108/ER-11-2015-0205 35. Zhang M. Zhu C.J. Dowling P.J. Bartram T. Exploring the effects of high-performance work systems (HPWS) on the work-related well-being of Chinese hospital employees Int. J. Hum. Resour. Manag. 2013 24 3196 3212 10.1080/09585192.2013.775026 36. Fu N. Flood P.C. Bosak J. Rousseau D.M. Morris T. O’Regan P. High-Performance work systems in professional service firms: Examining the practices-resources-uses-performance linkage Hum. Resour. Manag. 2017 56 329 352 10.1002/hrm.21767 37. Rich B.L. Lepine J.A. Crawford E.R. Job engagement: Antecedents and effects on job performance Acad. Manag. J. 2010 53 617 635 10.5465/amj.2010.51468988 38. Colquitt J.A. Greenberg J. Organizational justice: A fair assessment of the state of the literature Organizational Behavior: The state of the Science Greenberg J. Lawrence Erlbaum Associates Publishers Mahwah, NJ, USA 2003 165 210 39. Thibaut J. Walker L. Procedural Justice: A Psychological Analysis Erlbaum/Halstead New York, NY, USA 1975 40. Chang E. Employees’ overall perception of HRM effectiveness Hum. Relat. 2005 58 523 544 10.1177/0018726705055037 41. Ambrose M.L. Arnaud A. Are Procedural Justice and Distributive Justice Conceptually Distinct? Handbook of Organizational Justice Greenberg J. Colquitt J.A. Lawrence Erlbaum Associates Publishers New York, NY, USA 2005 59 84 42. Ang S.H. Bartram T. McNeil N. Leggat S.G. Stanton P. The effects of high-performance work systems on hospital employees’ work attitudes and intention to leave: A multi-level and occupational group analysis Int. J. Hum. Resour. Manag. 2013 24 3086 3114 10.1080/09585192.2013.775029 43. Casper W.J. Harris C.M. Work-life benefits and organizational attachment: Self-interest utility and signaling theory models J. Vocat. Behav. 2008 72 95 109 10.1016/j.jvb.2007.10.015 44. Latorre F. Guest D. Ramos J. Gracia F.J. High commitment HR practices, the employment relationship and job performance: A test of a mediation model Eur. Manag. J. 2016 34 328 337 10.1016/j.emj.2016.05.005 45. Einarsen S. The nature and causes of bullying at work Int. J. Manpow. 1999 20 16 27 10.1108/01437729910268588 46. Leymann H. The content and development of mobbing at work Eur. J. Work. Organ. Psychol. 1996 5 165 184 10.1080/13594329608414853 47. Einarsen S.V. Hoel H. Zapf D. Cooper C.L. The concept of bullying and harassment at work: The European tradition Bullying and Harassment in the Workplace CRC press Boca Raton, FL, USA 2020 3 53 48. Baillien E. Escartín J. Gross C. Zapf D. Towards a conceptual and empirical differentiation between workplace bullying and interpersonal conflict Eur. J. Work. Organ. Psychol. 2017 26 870 881 10.1080/1359432X.2017.1385601 49. Zapf D. Gross C. Conflict escalation and coping with workplace bullying: A replication and extension Eur. J. Work. Organ. Psychol. 2001 10 497 522 10.1080/13594320143000834 50. Branch S. Ramsay S. Barker M. Workplace bullying, mobbing and general harassment: A review Int. J. Manag. Rev. 2013 15 280 299 10.1111/j.1468-2370.2012.00339.x 51. Glasø L. Notelaers G. Workplace bullying, emotions, and outcomes ViolenceVict. 2012 27 360 377 10.1891/0886-6708.27.3.360 52. Lewis D. Bullying at work: The impact of shame among university and college lecturers Br. J. Guid. Couns. 2004 32 281 299 10.1080/03069880410001723521 53. Tracy S.J. Lutgen-Sandvik P. Alberts J.K. Nightmares, demons, and slaves: Exploring the painful metaphors of workplace bullying Manag. Commun. Q. 2006 20 148 185 10.1177/0893318906291980 54. Ciby M.A. Sahai S. Raya R.P. Workplace bullying and turnover intention: Serial multiple mediation model of negative emotions and affective commitment Int. J. Manag. Pract. 2021 14 736 750 10.1504/IJMP.2021.118942 55. Rai A. Agarwal U.A. Linking workplace bullying and work engagement: The mediating role of psychological contract violation South Asian J. Hum. Resour. Manag. 2017 4 42 71 10.1177/2322093717704732 56. Teo S.T. Nguyen D. Trevelyan F. Lamm F. Boocock M. Workplace bullying, psychological hardiness, and accidents and injuries in nursing: A moderated mediation model PLoS ONE 2021 16 1 15 10.1371/journal.pone.0244426 57. Folger R. Cropanzano R. Fairness theory: Justice as accountability Advances in Organization Justice Greenberg J. Cropanzano R. Stanford University Press Stanford, CA, USA 2001 1 55 58. Folger R. Martin C. Relative deprivation and referent cognitions: Distributive and procedural justice effects J. Exp. Soc. Psychol. 1986 22 531 546 10.1016/0022-1031(86)90049-1 59. Chuang C.H. Liao H.U.I. Strategic human resource management in service context: Taking care of business by taking care of employees and customers Pers. Psychol. 2010 63 153 196 60. Elovainio M. Heponiemi T. Kuusio H. Sinervo T. Hintsa T. Aalto A.M. Developing a short measure of organizational justice: A multisample health professionals study J. Occup. Environ. Med. 2010 52 1068 1074 10.1097/JOM.0b013e3181f8447c 21063184 61. Schaufeli W.B. Van Dierendonck D. UBOS, Utrechtse Burnout Schaal, Handleiding Swets Test Publishers Lisse, The Netherlands 2000 62. Notelaers G. Van der Heijden B. Hoel H. Einarsen S. Measuring bullying at work with the short-negative acts questionnaire: Identification of targets and criterion validity Work. Stress 2019 33 58 75 10.1080/02678373.2018.1457736 63. Notelaers G. van der Heijden B. Construct validity in workplace bullying and harassment research Concepts, Approaches and Methods D’Cruz P. Noronha E. Notelaers G. Rayner C. Springer Singapore, USA 2021 1 56 64. Einarsen S. Hoel H. Notelaers G. Measuring exposure to bullying and harassment at work: Validity, factor structure and psychometric properties of the Negative Acts Questionnaire-Revised Work. Stress 2009 23 24 44 10.1080/02678370902815673 65. Notelaers G. Einarsen S. De Witte H. Vermunt J.K. Measuring exposure to bullying at work: The validity and advantages of the latent class cluster approach Work. Stress 2006 20 289 302 10.1080/02678370601071594 66. Vermunt J.K. Magidson J. Latent class cluster analysis Appl. Latent Cl. Anal. 2002 60 89 106 67. Magidson J. Vermunt J.K. Latent class models The Sage Handbook of Quantitative Methodology for the Social Sciences Kaplan D. Sage Publishing Thousand Oaks, CA, USA 2004 175 198 68. Hayes A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach Publications New York, NY, USA 2013 69. Langeheine R. Pannekoek J. Van de Pol F. Bootstrapping goodness-of-fit measures in categorical data analysis Sociol. Methods Res. 1996 24 492 516 10.1177/0049124196024004004 70. Neuman J.H. Baron R.A. Einarsen S. Hoel H. Zapf D. Cooper C. Social antecedents of bullying: A social interactionist perspective Bullying and Harassment in the Workplace: Developments in Theory, Research, and Rractice Einarsen S. Hoel H. Zapf D. Cooper C. CRC Press New York, NY, USA 2011 201 225 71. Samsudin E.Z. Isahak M. Rampal S. Rosnah I. Zakaria M.I. Organisational antecedents of workplace victimisation: The role of organisational climate, culture, leadership, support, and justice in predicting junior doctors’ exposure to bullying at work Int. J. Health Plan.Manag. 2020 35 346 367 10.1002/hpm.2926 72. Hsu F.S. Liu Y. Tsaur S.H. The impact of workplace bullying on hotel employees’ well-being: Do organizational justice and friendship matter? Int. J. Contemp. Hosp. Manag. 2019 31 1702 1719 10.1108/IJCHM-04-2018-0330 73. Neall A.M. Li Y. Tuckey M.R. Organizational justice and workplace bullying: Lessons learned from externally referred complaints and investigations Societies 2021 11 143 10.3390/soc11040143 74. Rousseau D.M. Schema, promise and mutuality: The building blocks of the psychological contract J. Occup. Organ. Psychol. 2001 74 511 541 10.1348/096317901167505 75. Lutgen-Sandvik P. McDermott V. Making sense of supervisory bullying: Perceived powerlessness, empowered possibilities South. Commun. J. 2011 76 342 368 10.1080/10417941003725307 76. Hobfoll S.E. Conservation of resources theory: Its implication for stress, health, and resilience The Oxford Handbook of Stress, Health, and Coping Folkman S. Oxford University Press Oxford, UK 2011 127 147 77. Hobfoll S.E. Conservation of resources: A new attempt at conceptualizing stress Am. Psychol. 1989 44 513 10.1037/0003-066X.44.3.513 2648906 78. Hayat A. Afshari L. Supportive organizational climate: A moderated mediation model of workplace bullying and employee well-being Pers. Rev. 2021 50 1685 1704 10.1108/PR-06-2020-0407 79. Tuckey M.R. Neall A.M. Workplace bullying erodes job and personal resources: Between-and within-person perspectives J. Occup. Health Psychol. 2014 19 413 424 10.1037/a0037728 25151461 80. Karasek R.A. Jr. Job demands, job decision latitude, and mental strain: Implications for job redesign Adm. Sci. Q. 1979 24 285 308 10.2307/2392498 81. Spector P.E. Do not cross me: Optimizing the use of cross-sectional designs J. Bus. Psychol. 2019 34 125 137 10.1007/s10869-018-09613-8 82. Podsakoff P.M. MacKenzie S.B. Lee J.Y. Podsakoff N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies J. Appl. Psychol. 2003 88 879 10.1037/0021-9010.88.5.879 14516251 83. Spector P.E. Using self-report questionnaires in OB research: A comment on the use of a controversial method J. Organ. Behav. 1994 15 385 392 10.1002/job.4030150503 84. Berry C.M. Carpenter N.C. Barratt C.L. Do other-reports of counterproductive work behavior provide an incremental contribution over self-reports? A meta-analytic comparison J. Appl. Psychol. 2012 97 613 636 10.1037/a0026739 22201245 85. Aiken L.S. West S.G. Reno R.R. Multiple Regression: Testing and Interpreting Interactions Sage Publications London, UK 1991 86. Wall T.D. Jackson P.R. Mullarkey S. Parker S.K. The demands—control model of job strain: A more specific test J. Occup. Organ. Psychol. 1996 69 153 166 10.1111/j.2044-8325.1996.tb00607.x 87. Dormann C. Griffin M.A. Optimal time lags in panel studies Psychol. Methods 2015 20 489 505 10.1037/met0000041 26322999

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094741 ijms-23-04741 Article Lifespan Extension of Podospora anserina Mic60-Subcomplex Mutants Depends on Cardiolipin Remodeling Marschall Lisa-Marie https://orcid.org/0000-0001-7358-4180 Warnsmann Verena Meeßen Anja C. https://orcid.org/0000-0002-9950-8175 Löser Timo † https://orcid.org/0000-0002-0360-6994 Osiewacz Heinz D. * Ferramosca Alessandra Academic Editor Institute of Molecular Biosciences, Faculty of Biosciences, Goethe-University, Max-von-Laue-Str. 9, 60438 Frankfurt, Germany; l.marschall@bio.uni-frankfurt.de (L.-M.M.); warnsmann@bio.uni-frankfurt.de (V.W.); meessen@bio.uni-frankfurt.de (A.C.M.); loeserti@uni-mainz.de (T.L.) * Correspondence: osiewacz@bio.uni-frankfurt.de † Current address: Institute for Pathobiochemistry, University Medical Center of the Johannes Gutenberg University, Duesbergweg 6, 55128 Mainz, Germany. 25 4 2022 5 2022 23 9 474122 3 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Function of mitochondria largely depends on a characteristic ultrastructure with typical invaginations, namely the cristae of the inner mitochondrial membrane. The mitochondrial signature phospholipid cardiolipin (CL), the F1Fo-ATP-synthase, and the ‘mitochondrial contact site and cristae organizing system’ (MICOS) complex are involved in this process. Previous studies with Podospora anserina demonstrated that manipulation of MICOS leads to altered cristae structure and prolongs lifespan. While longevity of Mic10-subcomplex mutants is induced by mitohormesis, the underlying mechanism in the Mic60-subcomplex deletion mutants was unclear. Since several studies indicated a connection between MICOS and phospholipid composition, we now analyzed the impact of MICOS on mitochondrial phospholipid metabolism. Data from lipidomic analysis identified alterations in phospholipid profile and acyl composition of CL in Mic60-subcomplex mutants. These changes appear to have beneficial effects on membrane properties and promote longevity. Impairments of CL remodeling in a PaMIC60 ablated mutant lead to a complete abrogation of longevity. This effect is reversed by supplementation of the growth medium with linoleic acid, a fatty acid which allows the formation of tetra-octadecanoyl CL. In the PaMic60 deletion mutant, this CL species appears to lead to longevity. Overall, our data demonstrate a tight connection between MICOS, the regulation of mitochondrial phospholipid homeostasis, and aging of P. anserina. Podospora anserina aging mitochondria cristae MICOS cardiolipin tafazzin ==== Body pmc1. Introduction Aging of biological systems is a complex process leading to irreversible time-dependent decrease of physiological functions and an increase in morbidity and mortality. The process is under the control of environmental, stochastic, and genetic traits. There are a number of genetically controlled pathways influencing aging and lifespan [1,2,3,4]. Pathways involved in keeping a healthy population of mitochondria, the cellular power plants with many essential functions, have been demonstrated to play a key role in aging from yeast to humans [5,6,7,8,9,10,11,12,13]. Podospora anserina is a filamentous fungus with a strong mitochondrial etiology of aging (for review, see [14,15]). Mitochondria form a filamentous network in juvenile hyphae, but during aging, this network disintegrates, resulting in fragmented mitochondria [16]. In the aging process, the ultrastructure changes from lamellar cristae to vesicular units [17,18]. A molecular model explains that the underlying processes result from the dissociation of the F1Fo-ATP-synthase dimers at the cristae tips and of a protein complex at the basis of cristae, followed by the retraction of cristae and the formation of vesicles. The dissociation of F1Fo-ATP-synthase dimers was followed by cryo-electron microscopy [17] and subsequently by studying genetic mutants impaired in dimerization of F1Fo-ATP-synthase. Ablation of the assembly factor PaATPE leads to the loss of lamellar cristae and a mitophagy-dependent decreased lifespan [19,20]. However, the impact of the ‘mitochondrial contact site and cristae organizing system’ (MICOS) complex at the basis of cristae was only recently studied in detail [21]. We identified five homologs of the six well-known yeast MICOS subunits in P. anserina, also organized in two subcomplexes (Mic60-subcomplex: PaMIC60 and PaMIC19 as well as Mic10-subcomplex: PaMIC10, PaMIC26, and PaMIC12). For the first time, a link between MICOS and the aging process was demonstrated. In this study, a counterintuitive lifespan extension was found in mutants in which individual components were ablated. Moreover, it was shown that longevity of Mic10-subcomplex mutants results from mitohormesis, the beneficial effect of mild oxidative stress [21]. Until now, the underlying mechanism of longevity in deletion mutants of the Mic60-subcomplex has not been identified. Here we report evidence demonstrating an important role of phospholipids in the control of the lifespan of the PaMic60 deletion mutant. In this mutant, phospholipid profile and acyl composition of the mitochondrial signature phospholipid cardiolipin (CL) are altered in comparison to the wild type. Our study unraveled an essential role of CL remodeling for longevity of the PaMic60 deletion mutant. In addition, we extended the knowledge about the relevance of mitochondrial phospholipid metabolism for aging of P. anserina. 2. Results and Discussion 2.1. Loss of MICOS Subunits Leads to Changes in Phospholipid Metabolism In a recent study we identified a link between the MICOS complex and aging of P. anserina. We found that loss of each of the two MICOS subcomplexes leads to unexpected longevity. While loss of Mic10-subcomplex results in mitohormesis-induced lifespan extension, the underlying mechanism leading to longevity in Mic60-subcomplex mutants appears to be caused by a different mechanism which may be linked to phospholipid metabolism [21]. This possibility is supported by the demonstration of the interaction between human MIC60 and components of the cardiolipin synthesis pathway, including phosphatidylglycerophosphate synthase (PGS1) and cardiolipin synthase (CRD1) [22]. Moreover, in several organisms, CL is known to stabilize the F1Fo-ATP-synthase as well as the MICOS complex [23,24,25], which is localized at the crista junctions and involved in cristae formation [26,27,28]. In order to investigate the potential impact of MICOS subunits on phospholipid metabolism, we first analyzed the amount of PaCRD1 in isolated mitochondria of the P. anserina wild type and MICOS deletion mutants. Loss of Mic60-subcomplex subunits, PaMIC60 or PaMIC19, led to an approximately 1.8-fold increase of PaCRD1 abundance (Figure 1A,B). Similarly, in the Mic10-subcomplex mutants, we observed a slight 1.3-fold increase in the PaMic10 deletion mutant and a 1.4-fold increase in the ΔPaMic26 mutant, respectively. To determine whether the observed changes lead to altered CL levels, we performed a thin layer chromatography analysis. In the deletion strains of both subcomplexes, the altered PaCRD1 level was associated with an increase of CL (Figure 1C,D). The absence of PaMIC60 or PaMIC19 resulted in an increase in CL abundance of approximately 1.5-fold. Loss of Mic10-subcomplex subunits PaMIC10 or PaMIC26 led to a 1.3-fold increase of CL level. The abundance of other phospholipids such as phosphatidylethanolamine (PE), phosphatidylcholine (PC), and phosphatidylserine (PS) was hardly altered. A link between altered phospholipid composition and extended lifespan was already described in another P. anserina mutant (ΔPaIap) [29]. It appears that the observed significant changes in CL levels of ΔPaMic60 and ΔPaMic19 mutant may contribute to longevity of the Mic60-subcomplex deletion mutants. Since thin layer chromatography allows only a very rough estimation of phospholipid classes without any information about the exact acyl composition, we set out to elucidate the impact of mitochondrial phospholipid composition and the role of CL in MICOS mutants by shotgun lipidomic analysis, which was performed by Lipotype (Dresden, Germany). For this analysis, we isolated and purified mitochondria from 6-day-old P. anserina cultures of the wild type, ΔPaMic60, and ΔPaMic26, respectively. Interestingly, the phospholipid composition was differentially affected in the two MICOS subcomplex mutants (Figure 2A). Compared to the wild type, the phospholipid profile of the PaMic26 deletion strain was only marginally changed. We found a significant reduction of PE and phosphatidylglycerol (PG) as well as a slightly enhanced level of CL. In contrast, ablation of PaMIC60 had a strong effect on phospholipid composition compared to the wild type. There was a slight decrease of the precursor lipid diacylglycerol (DAG), as well as a significant reduction of ceramide, phosphatidic acid (PA), and PS. Since the latter two phospholipids are shuttled between the endoplasmic reticulum (ER) and the inner mitochondrial membrane, their decrease might indicate a reduction in ER/mitochondria contact. The MICOS complex ensures close apposition of mitochondrial membranes and thereby assists phospholipid synthesis in the outer mitochondrial membrane [30]. Therefore, it is possible that ablation of the Mic60-subcomplex impairs the exchange of specific phospholipids between mitochondria and the ER. Beside elevated phosphatidylinositol (PI) levels, a significant increase of approximately 20% of PC (32.4% to 38.1%) and 65% of CL (3.2% to 5.3%) was observed (Figure 2A). Loss of PaMIC60 led to enhanced PC levels, while ablation of PaMIC26 resulted in decreased PE levels. In both cases, these changes resulted in a slight but significant shift of the PE/PC ratio from 0.9 to 1.1 compared to the wild type (Figure 2B). PE is a cone-shaped phospholipid inducing negative membrane curvature, and it contributes to elevated membrane stiffening [31,32]. As a counterpart, the cylindrical bilayer-forming PC increases membrane fluidity. Thus, the PE/PC ratio impacts membrane properties and therefore needs to be tightly controlled [33]. In mice, increased PE/PC ratio was shown to cause loss of membrane integrity, leading to liver failure [34]. Furthermore, studies with mammalian cells demonstrated that changes in PE/PC ratio have a dramatic effect on mitochondrial dynamics, morphology, and ultrastructure. Loss of PE results in fragmented abnormally swollen mitochondria lacking distinct cristae [35]. In addition to PC and PE, also CL has a major impact on membrane properties due to its high content of unsaturated fatty acids and its specific cone-shaped structure. There was a 1.7-fold increase of CL in the PaMic60 deletion strain (Figure 2C). Especially for CL, it has been shown that acyl composition plays a crucial role for survival of P. anserina [29]. Therefore, we analyzed the different species of CL in more detail regarding length and degree of saturation of the attached acyl groups. Loss of MICOS resulted in a slightly altered distribution of CL species compared to the wild type (Figure 2D). Particularly, ablation of both PaMIC60 and PaMIC26 led to a shift from shorter-chained (e.g., CL 66:4, 68:4, 70:6) to rather long-chained acyl groups containing tetra-octadecanoyl residues (CL 72:X). The PaMic60 and PaMic26 deletion mutants both showed a significant increase of tetra-linoleoyl-CL (CL 4 × 18:2 or CL 72:8). In mammalian cardiac mitochondria with high respirational activity, CL 72:8 was found to be the dominant CL species [36,37]. Moreover, an increased abundance of CL 72:8 enhances mitochondrial function in mammalian models upon heart failure [38,39]. In human cells, linoleic acid is preferentially incorporated into CL, resulting in an increased amount of CL 72:8 and promoting CI activity [40]. Thus, it seems that CL 72:8 exerts a beneficial effect on mitochondrial function. Such an effect was also previously observed in a study with P. anserina [29]. Due to the altered phospholipid profile and distribution of CL species, the amount of double bonds in the ΔPaMic60 mutant was slightly but significantly increased across all phospholipids reflected by more unsaturated acyl residues (Figure 2E). Such a moderate higher degree of unsaturation can positively affect the fluidity of membranes [41]. Altogether, our data suggest that in both analyzed MICOS subcomplex mutants, membrane fluidity was increased. 2.2. Cardiolipin Remodeling Is Necessary for Lifespan Extension of ΔPaMic60 A common feature of the two mutants investigated in this study is the upregulation of CL synthesis. Therefore, we analyzed the role of CL synthesis and remodeling in more detail. CL biosynthesis is a process involving several intermediate steps and various enzymes (Figure 3A; reviewed in [42]). CRD1 converts PG into premature CL (pCL). Subsequently, during CL remodeling, pCL is converted into monolysocardiolipin (MLCL) by several phospholipases of the calcium-independent phospholipase A2 (iPLA2) family, followed by the generation of mature CL (mCL) by acyltransferases, such as the transacylase tafazzin (TAZ1) [43,44]. Mitochondria of a yeast Taz1 deletion mutant still possess pCL but no mCL [45]. Previous studies revealed that loss of CRD1, which completely blocks formation of all CL species, leads to a reduced lifespan of Drosophila melanogaster and P. anserina [23,29]. To specifically address the question how MICOS ablation and subsequent lifespan extension as well as CL composition depend on each other, we generated new deletion mutants for further analysis. In order to examine the importance of CL in ΔPaMic60, we generated a ΔPaMic60/ΔPaCrd1 double deletion mutant (Figure S1A). The generation of ΔPaMic60/ΔPaCrd1 was difficult because spores from this strain germinate poorly due to a germination defect (Figure S1B). After initial formation of germination tubes on spore germination medium, growth of the double mutant completely stopped. Only after transfer of the poorly germinated spores to M2 medium and subsequent incubation for at least 5 days growth resumes. This made it impossible to maintain the same growth conditions as the single mutants. Thus, further lifespan and molecular analyses were not possible, but the impairments of the ΔPaMic60 mutant clearly demonstrated that CL plays an important role in germination. To examine the specific role of mCL, we first analyzed a mutant in which PaTaz1 coding for tafazzin (PaTAZ1) is deleted [29]. Compared to the wild type, the lifespan of the ΔPaTaz1 was only slightly reduced, by approximately 10% (mean lifespan: 22 d vs. 24 d; maximal lifespan: 29 d vs. 32 d) (Figure S2A,B). This is similar to the situation in the previously analyzed PaCrd1 deletion mutant [29]. The lifespans of both mutants are slightly shortened, but the general loss of CL results in a stronger lifespan reduction, whereas the effect on lifespan resulting from the loss of mCL in the PaTaz1 deletion mutant is less pronounced. More severe effects of the deletion of Crd1 or Taz1 have been reported in yeast. Here, deletion of the two genes was found to effect growth as well as dramatically decrease chronological lifespan [46,47]. Next, we generated a double deletion mutant lacking PaMIC60 and PaTAZ1 (Figure 3B) and analyzed the lifespan of ΔPaMic60/ΔPaTaz1 (Figure 3C). Interestingly, longevity of the single ΔPaMic60 mutant was abolished in the ΔPaMic60/ΔPaTaz1 double mutant. The simultaneous ablation of PaMIC60 and PaTAZ1 caused a 70% reduced maximal lifespan (29 d vs. 103 d) and a 50% shortened mean lifespan (26 d vs. 49 d) compared to ΔPaMic60, leading to a wild type-like lifespan (Figure 3C,D). Obviously, longevity of the PaMic60 deletion mutant depends on the presence of PaTAZ1. To determine whether mCL also affects lifespan of Mic10-subcomplex mutants, we generated a double deletion mutant lacking PaMIC26 as well as PaTAZ1 (Figure 3E). Lifespan analyses revealed that the mean lifespan of ΔPaMic26/ΔPaTaz1 was reduced by approximately 35% compared to ΔPaMic26 (34 d vs. 53 d) but was still extended by around 40% compared to the wild type (34 d vs. 24 d) (Figure 3F,G). Taken together, these data demonstrate that CL remodeling is crucial for survival of the analyzed MICOS mutants. However, the importance of PaTAZ1-mediated CL remodeling seems to be different in the two MICOS subcomplex mutants. Longevity of the Mic10-subcomplex mutant only partially depends on PaTAZ1-mediated formation of mCL. In contrast, in the PaMic60 deletion mutant, lifespan extension completely depends on PaTAZ1. 2.3. Ablation of PaTAZ1 Dramatically Impacts Phospholipid Metabolism In order to elucidate the PaTAZ1-dependent CL acyl chain composition in more detail, we set out to analyze the phospholipid profile and distribution of CL species in ΔPaTaz1. Compared to wild type, ablation of PaTAZ1 severely impacted phospholipid composition. In addition to elevated PG and lyso-phospholipids (LPL) levels, we found a significant increase of PE by 15%. In addition, a decreased PC amount of approximately 15% was observed (Figure 4A). These changes resulted in an enhanced PE/PC ratio from 1.1 to 1.5 compared to the wild type (Figure 4B). A previous study of a PaCrd1 deletion mutant showed a correlation between an increased PE/PC ratio and accelerated aging of P. anserina [29]. Similar to the ΔPaCrd1 mutant, the lifespan of the PaTaz1 deletion mutant was also shortened. Next, we discriminated the different CL species regarding length and degree of saturation of attached acyl groups. Ablation of PaTAZ1 resulted in a severely altered profile of CL species, with domination of CL 68:4, CL 70:6, and CL 70:7 (Figure 4C). With a total amount of 50% of all CL species, the PaTaz1 deletion mutant exhibited significantly increased CL 70:7 levels. Compared to the wild type, CL 68:4 was also increased by about 45%, and the amount of CL 70:6 was reduced approximately by 35%. Obviously, there were no CL 72:X species due to the loss of PaTAZ1. In particular, the complete absence of CL 72:8 in this mutant was already observed in a recent lipidomic analysis [29]. The apparent strict dependency of CL 72:X formation on the presence of PaTAZ1 differs from what is described in other organisms. In cardiac mitochondria of mice, down-regulation of TAZ1 results only in a strong reduction of CL 72:8 [48], the most common species in this tissue [49]. Nevertheless, CL 72:X species are still present in cardiac as well as in liver and kidney mitochondria of TAZ1-deficient mice [48]. The complete loss of CL 72:X and the overall altered phospholipid profile were accompanied by a significant decrease of double bonds of approximately 10% across all mitochondrial phospholipids of P. anserina (Figure 4D). Overall, our findings suggest that loss of PaTAZ1 dramatically impairs phospholipid metabolism and, in particular, CL remodeling, which is accompanied by a shortened lifespan in P. anserina. Due to the strong impact of PaTAZ1 ablation on the CL profile, the ΔPaTaz1 mutant allowed us to uncover whether or not CL acyl chain composition plays a role in MICOS mutants. 2.4. Simultaneous Loss of PaMIC60 and PaTAZ1 Results in Tafazzin-Independent CL 72:X Formation In order to assess MICOS- and PaTAZ1-dependent changes in mitochondrial phospholipid metabolism, we next investigated the phospholipid profile in ΔPaMic60/ΔPaTaz1 and ΔPaMic26/ΔPaTaz1 double deletion mutants. Exact values of all analyzed phospholipids are shown in Supplementary Materials (Table S1). The most prominent changes were observed with phospholipids of the CDP-DAG pathway (Figure 5A). The amounts of PE and PG were significantly increased in ΔPaMic60/ΔPaTaz1 compared to the single PaMic60 deletion mutant. Furthermore, in addition to decreased PC abundance, we observed a significant reduction of CL level by approximately 60% (2.1% vs. 5.3%). Likewise, the simultaneous loss of PaMIC26 and PaTAZ1 led to reduced PA, PE, and PG levels compared to the PaMic26 deletion mutant. There was also a slight, non-significant reduction in PC amount and an enhanced, significant decrease of CL level by approximately 30% (2.8% vs. 4.0%) observed. Thus, changes in phospholipid composition due to the ablation of PaTAZ1 were similar in the two subcomplex mutants. In both ΔPaMic60/ΔPaTaz1 and ΔPaMic26/ΔPaTaz1, the altered amounts of PE and PC resulted in a significant increase of PE/PC ratio from 0.9 to 1.3 compared to the corresponding single deletion mutant (Figure 5B). Surprisingly, there were pronounced differences in the CL acyl chain composition of the ΔPaMic60/ΔPaTaz1 and ΔPaMic26/ΔPaTaz1 double deletion mutants (Figure 5C and Figure S3). ΔPaMic26/ΔPaTaz1 only exhibited the species CL 68:4, CL 70:7, and CL 70:7 and thereby hardly differed from the single PaTaz1 deletion mutant. In contrast to ΔPaTaz1, the ΔPaMic26/ΔPaTaz1 double mutant still had an extended lifespan (Figure 3E,F), despite the lack of long-chained CL species. Based on our previously described data, we concluded that longevity of the Mic10-subcomplex mutant ΔPaMic26 is the result of ROS-dependent mitohormesis [21] and does not depend on phospholipid metabolism. This conclusion is supported by the finding that loss of long-chained CL species in the mutant background only partially abrogates lifespan extension. A completely different situation was observed in the ΔPaMic60/ΔPaTaz1 mutant. Here, we observed a marked change in the distribution of CL species in ΔPaMic60/ΔPaTaz1 compared to the ΔPaMic60 and ΔPaTaz1 single mutants. The most common species were CL 70:6 and CL 68:4. Further, the CL 70:7 species was not dominating, and therefore the profile was more similar to ΔPaMic60 and wild type than to the ΔPaTaz1 mutant. Interestingly, small amounts of CL 72:X species were found in ΔPaMic60/ΔPaTaz1, although this was not expected from the characteristics of the single PaTaz1 deletion mutant. The most common long-chained CL species in the ΔPaMic60/ΔPaTaz1 double mutant was CL 72:8, with approximately 7%. However, the amount of CL 72:8 was still significantly reduced by 75% compared to the single PaMic60 deletion mutant and by approximately 70% compared to the wild type. This was accompanied by abolished longevity in the ΔPaMic60/ΔPaTaz1 double mutant (Figure 3B,C). Although the CL 72:8 level was lower than in the wild type, the lifespans did not differ. Obviously, concomitant ablation of PaMIC60 and PaTAZ1 resulted in a more wild-type-like CL acyl chain composition and PaTAZ1-independent CL 72:X formation. One possible explanation for the PaTAZ1-independent formation of CL 72:X could be an increased availability of 18-chain acyl residues, possibly caused by the upregulation of corresponding enzymes in fatty acid synthesis. Data from the shotgun lipidomic analysis provided a first indication of this possibility. Loss of PaMIC60 led to a significant increase of approximately 15% in phospholipids with a total chain length of 36 C atoms (2 × 18) compared to the wild type (Figure S3B). However, transcript analyses of genes coding for two enzymes (PaELO1 and PaOLE1) involved in C18 fatty acid biosynthesis argued against this hypothesis (data not shown). Another possible explanation for the formation of CL 72:X species is based on the observation that in addition to the transacylase TAZ1, other enzymes may be implicated in CL remodeling. In mammals, the acyl-CoA:lysocardiolipin acyltransferase 1 (ALCAT1) is located in mitochondria-associated membranes of the ER and shows predominant activity and selectivity towards linoleic acid (18:2) and oleic acid (18:1) [50,51]. Another enzyme in humans is the monolysocardiolipin acyltransferase 1 (MLCLAT1), which is a splice variant of the trifunctional enzyme subunit alpha and is localized in mitochondria [52,53]. In Barth syndrome lymphoblasts, overexpression of Mlclat1 increases the amount of CL as well as the incorporation of linoleic acid into CL [54]. To determine if these alternatives also play a role in P. anserina, we searched for corresponding homologs of human ALCAT1 (UniProt: Q6UWP7) and human MLCLAT1 (UniProt: P40939). In a protein BLAST search [55], we identified Pa_2_4320 (UniProt: B2B5D3, E-value 9 × 10−24) as a homolog to human ALCAT1 and Pa_2_4980 (UniProt: B2B5L0, E-value 2 × 10−33) as a homolog to human MLCLAT1. We speculate that in the absence of Mic60-subcomplex and PaTAZ1, these alternative acyltransferases resume CL remodeling. Taken together, our data show that specifically the simultaneous loss of PaMIC60 and PaTAZ1 leads to an alternative mechanism for the formation of CL 72:X, which emphasizes the importance of CL remodeling in Mic60-subcomplex mutants. 2.5. Linoleic Acid Re-Establishes Longevity of ΔPaMic60/ΔPaTaz1 The simultaneous ablation of PaMIC60 and PaTAZ1 significantly abrogates the lifespan extension observed in a single PaMic60 deletion mutant. We speculate that the reduced level of CL 72:X in the ΔPaMic60/ΔPaTaz1 double mutant compared to ΔPaMic60 is responsible for this effect. Moreover, specifically CL 72:8 consisting of four linoleic acid residues may play an important role in lifespan extension of mutants lacking the Mic60-subcomplex. To test this idea, we first determined the influence of linoleic acid added to the growth medium, which enhances the incorporation of this fatty acid in newly synthesizes phospholipids, thereby increasing the amounts of CL 72:8 [40]. If this assumption is correct, the lifespan of the ΔPaMic60/ΔPaTaz1 double mutant should be extended by treatment with linoleic acid. First, we analyzed linoleic acid uptake in P. anserina. In general, after absorption from the environment, fatty acids are transported or stored in so-called lipid droplets [56]. To find a suitable concentration for further experiments, we performed growth tests using the wild type on medium containing different concentrations of linoleic acid (0.16 mM, 0.8 mM, 1.6 mM) (Figure S4A). All concentrations reduced the growth rate of the wild type. We decided to use 0.8 mM linoleic acid, a concentration at which the growth rate of the wild type was clearly impaired. A beneficial effect of linoleic acid on lifespan of ΔPaMic60/ΔPaTaz1 would strongly argue for a critical role of this specific fatty acid in this mutant. To examine the entry of linoleic acid, the wild type was cultured on standard medium or on standard medium containing linoleic acid (0.8 mM). One day later, we stained the strains with the lipid droplet dye LipidSpot™ and performed fluorescence microscopy. Lipid droplets were only detected in the wild type grown on the linoleic acid-containing medium (Figure S4B), indicating the uptake of linoleic acid from the medium and its storage/transport in lipid droplets. Next, we investigated the effect of supplemented linoleic acid on the lifespan of P. anserina. Lifespan analyses of the wild type revealed a marginal reduction of the mean (20 d vs. 25 d) as well as maximal lifespan (26 d vs. 30 d) compared to the wild type grown on medium without linoleic acid (Figure 6A,B). Similar effects were also observed in single PaTaz1 and PaMic60 deletion mutants. Supplementation with linoleic acid did not affect maximal lifespan of the PaTaz1 deletion mutant (27 d vs. 27 d), but we found an approximately 30% decrease in maximal lifespan of ΔPaMic60 (75 d vs. 103 d) (Figure 6A). Additionally, the mean lifespans of the linoleic acid-treated ΔPaTaz1 (19 d vs. 24 d) and ΔPaMic60 (46 d vs. 59 d) mutants were slightly decreased (Figure 6B). Overall, treatment with linoleic acid led to slight negative effects in the wild type as well as PaTaz1 and PaMic60 single mutants. In these strains, it may be possible that excess linoleic acid is used to form other CL species, which are not beneficial for lifespan. More severe effects of high concentrations of linoleic acid have been demonstrated in other organisms. A previous study in human cells showed that linoleic acid inhibits tumor cell growth at concentrations above 0.3 mM [57]. Furthermore, treatment with conjugated linoleic acid, a derivate of linoleic acid, inhibits hyphal growth of Candida albicans [58]. To experimentally validate our hypothesis that specifically CL 72:8 plays an important role in lifespan extension of mutants lacking the Mic60-subcomplex, we next analyzed the lifespan of the ΔPaMic60/ΔPaTaz1 double mutant grown on linoleic acid supplemented medium. Interestingly, the lifespan of ΔPaMic60/ΔPaTaz1 double mutant was positively affected. We found a 55% prolonged mean lifespan (42 d vs. 27 d) and at least a 115% increased maximal lifespan (74 d vs. 34 d) compared to ΔPaMic60/ΔPaTaz1 without supplemented linoleic acid, resulting in a ΔPaMic60-like lifespan (Figure 6A,B). Obviously, the supplementation with linoleic acid re-established longevity of the ΔPaMic60/ΔPaTaz1 double mutant. All phospholipid classes might incorporate linoleic acid. However, we speculate that the additional linoleic acid finally leads to an increased abundance of CL 72:8, which is crucial in the double mutant for lifespan extension. Our surprising results support the speculation that PaMIC60-ablation channels CL remodeling to other acyltransferases that normally do not preferably remodel CL. One possible explanation might be that the Mic60-subcomplex is part of a CL synthesis scaffold containing PaCRD1 and PaTAZ1. Studies in human cells demonstrated an interaction between MIC60 and components of the cardiolipin synthesis machinery [22], which supports our hypothesis. Since we found no CL 72:X species in the ΔPaTaz1 mutant (Figure 4C), the transacylase PaTAZ1 seems to preferentially use phospholipids with linoleic acid residues for CL remodeling. The formation of especially CL 72:8 is therefore limited by the availability of PaTAZ1 in the proposed CL synthesis scaffold. Upon ablation of PaTAZ1, other acyltransferases cannot take over the remodeling activity since they are not part of the scaffold or, alternatively, are restricted to other membrane structures, e.g., at the interface between mitochondria and ER, as has been described for ALCAT1 [50]. However, loss of the Mic60-subcomplex together with PaTAZ1 ablation seems to allow other acyltransferases to come into close contact with the CL synthesis machinery. Since MICOS ablation not only affects mitochondrial phospholipid composition but also non-mitochondrial phospholipid synthesis [30], the induction of compensatory pathways is reasonable. At this time, this idea is highly speculative and needs to be experimentally addressed in more detail. 3. Conclusions In the current study, we unraveled the underlying mechanism of lifespan extension caused by the loss of the Mic60-subcomplex, thereby uncovering a substantial role of the Mic60-subcomplex in phospholipid homeostasis. This dedicated role makes longevity of the ΔPaMic60 mutant specifically vulnerable against PaTAZ1 ablation. Here, we suggest that the Mic60-subcomplex may form the basis of a CL building block that spatially controls formation of mCL. Furthermore, our data allow us to speculate on the induction of alternative mechanisms for the formation of CL 72:X in the absence of the Mic60-subcomplex and PaTAZ1. Altogether, we demonstrate that mCL is crucial for the healthspan of mutants lacking the Mic60-subcomplex. It will be of interest to see whether this impact of phospholipid metabolism is a mechanism that is specific for P. anserina or whether it is conserved among organisms. 4. Materials and Methods 4.1. P. anserina Strains and Cultivation In this study, the P. anserina wild-type strain ‘s’ [59], ΔPaTaz1 [29], ΔPaMic26, ΔPaMic60, ΔPaMic19, and ΔPaMic10 [21], as well as the newly generated mutants ΔPaMic26/ΔPaTaz1, ΔPaMic60/ΔPaTaz1, and ΔPaMic60/ΔPaCrd1 were used. Strains were cultivated on standard cornmeal agar (BMM) at 27 °C under constant light [60]. Spores were germinated on BMM with 60 mM ammonium acetate (Merck, Darmstadt, Germany; 1116.1000) at 27 °C in the dark for two days. All strains used in this study were derived from monokaryotic ascospores [60]. 4.2. Generation of P. anserina Double Mutants To generate double mutants, the single mutant strains were crossed with each other. From the progeny, strains containing both mutations were selected. 4.3. Southern Blot Analysis DNA isolation from P. anserina was performed according to the protocol from Lecellier and Silar [61]. Digestion of 500 ng DNA, gel electrophoresis, and Southern blotting were carried out by standard protocols. According to the manufacturer’s protocol for Southern blot hybridization and detection, digoxigenin-labeled hybridization probes (DIG DNA Labeling and Detection Kit, Roche Applied Science, Mannheim, Germany, 11175033910) were used. The hygromycin resistance gene (Hph) specific hybridization probe corresponded to the 736 bp XhoI-fragment of the plasmid pSM4 [62]. 4.4. Lifespan Analysis Lifespans of P. anserina cultures derived from monokaryotic ascospores were determined as previously described on M2 medium at 27 °C and constant light [60]. The lifespan was defined as the time period in days (d) until growth stopped. 4.5. Isolation of Mitochondria Mitochondria of P. anserina cultures were isolated and purified as previously described [60]. Disruption of grown mycelia was performed in isotonic mitochondria isolation buffer in the presence of bovine serum albumin (BSA, 0.2% (w/v)) (Sigma-Aldrich, St. Louis, MO, USA, A6003). After filtration through nettle cloth, the filtrate was sedimented by centrifugation (12,000× g) and resuspended in mitochondria isolation buffer without BSA. Separation of intact mitochondria from disrupted mitochondrial fractions was performed by ultracentrifugation (100,000× g) using a sucrose gradient (20–50% sucrose in H2O (w/v)). Intact mitochondria were collected, sedimented (15,000× g), resuspended in mitochondria isolation buffer, and stored at −80 °C. 4.6. Western Blot Analysis Western blot analysis was performed with 50 µg mitochondria as previously described [19]. The primary antibody anti-PaCRD1 (rabbit, dilution 1:5000, peptide: [H]-SKKEKEVVVEEEEGKKKEL-[OH], Davids Biotechnologie GmbH, Regensburg, Germany) was used. As secondary antibodies, IRDye® 680RD anti-rabbit (goat, 1:15,000 dilution, LI-COR Biosciences, Bad Homburg, Germany, 926-68071) and IRDye® 800CW anti-rabbit (goat, 1:15,000 dilution, LI-COR Biosciences, Bad Homburg, Germany, 926-32211) were used. The Odyssey® Fc imaging system (LI-COR Biosciences, Bad Homburg, Germany) was used for detection. Densitometric quantification was performed with the manufacturer’s software Image Studio Lite (Version 5.2). 4.7. Lipidomic Analysis Mass spectrometry-based lipid analysis was performed by Lipotype GmbH (Dresden, Germany) as described [63,64]. Lipids were extracted using a two-step chloroform/methanol procedure [63]. Samples were spiked with internal lipid standard mixture containing CDP-DAG 17:0/18:1, cardiolipin 14:0/14:0/14:0/14:0 (CL), ceramide 18:1;2/17:0 (Cer), diacylglycerol 17:0/17:0 (DAG), lyso-phosphatidate 17:0 (LPA), lyso-phosphatidyl-choline 12:0 (LPC), lyso-phosphatidylethanolamine 17:1 (LPE), lyso-phosphatidylinositol 17:1 (LPI), lyso-phosphatidylserine 17:1 (LPS), phosphatidate 17:0/14:1 (PA), phosphatidylcholine 17:0/14:1 (PC), phosphatidylethanolamine 17:0/14:1 (PE), phosphatidylglycerol 17:0/14:1 (PG), phosphatidylinositol 17:0/14:1 (PI), phosphatidylserine 17:0/14:1 (PS), ergosterol ester 13:0 (EE), triacylglycerol 17:0/17:0/17:0 (TAG), inositolphosphorylceramide 44:0;2 (IPC), mannosyl-inositolphosphorylceramide 44:0;2 (MIPC), and mannosyl-di-(inositolphosphoryl)ceramide 44:0;2 (M(IP)2C). After extraction, the organic phase was transferred to an infusion plate and dried in a speed vacuum concentrator. In the first step, dry extract was re-suspended in 7.5 mM ammonium acetate in chloroform/methanol/propanol (1:2:4, v:v:v); in the second step, dry extract was re-suspended in 33% ethanol solution of methylamine in chloroform/methanol (0.003:5:1; v:v:v). All liquid handling steps were performed using the Hamilton Robotics STARlet robotic platform (Reno, NV, USA) with the Anti Droplet Control feature for organic solvents pipetting. Samples were analyzed by direct infusion on a QExactive mass spectrometer (Thermo Scientific, Waltham, MA, USA) equipped with a TriVersa NanoMate ion source (Advion Biosciences, Ithaca, NY, USA). Samples were analyzed in both positive and negative ion modes with a resolution of Rm/z=200 = 280,000 for MS and Rm/z=200 = 17,500 for MSMS experiments, in a single acquisition. MSMS was triggered by an inclusion list encompassing corresponding MS mass ranges scanned in 1 Da increments [65]. Both MS and MSMS data were combined to monitor EE, DAG, and TAG ions as ammonium adducts; PC as an acetate adduct; and CL, PA, PE, PG, PI, and PS as deprotonated anions. MS only was used to monitor LPA, LPE, LPI, LPS, IPC, MIPC, and M(IP)2C as deprotonated anions; and Cer and LPC as acetate adducts. Data were analyzed with in-house developed lipid identification software based on LipidXplorer [66,67]. Data post-processing and normalization were performed using an in-house developed data management system. Only lipid identifications with a signal-to-noise ratio >5, and a signal intensity 5-fold higher than in corresponding blank samples were considered for further data analysis. 4.8. Thin Layer Chromatography Phospholipid extraction from isolated mitochondria and thin layer chromatography were performed as previously described [29]. 4.9. Fluorescence Microscopy Strains were grown on glass slides with a central depression containing 130 µL M2 medium or linoleic acid-containing M2 medium (0.8 mM) for one day under standard conditions. For the staining of lipid droplets, grown mycelium was incubated with LipidSpot™ 488 (Biotium, Fremont, CA, USA; 70065) for 15 min. Fluorescence microscopic analyses were performed with a fluorescence microscope (DM LB/11888011, Leica, Wetzlar, Germany) and a DFC7000 T camera; image processing was conducted with the corresponding LAS X software from Leica (Leica Microsystems GmbH, Wetzlar, Germany). 4.10. Statistical Analysis Significances between different lifespans were statistically analyzed with the IBM SPSS statistics 19 software package (IBM, Armonk, NY, USA) by generating Kaplan-Meier survival estimates. We used three independent statistical tests (Breslow (generalized Wilcoxon), log-rank (Mantel-Cox), and the Tarone-Ware) with a pairwise comparison. All other statistical significances were performed by the two-tailed Student’s t-test. The respective samples were compared with the appropriate wild type sample. For statistical significance, the minimum threshold was set at p < 0.05. * p < 0.05; ** p < 0.01; and *** p < 0.001. Acknowledgments We are grateful to Andrea Hamann for data discussion. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094741/s1. Click here for additional data file. Author Contributions Conceptualization, H.D.O., V.W. and L.-M.M.; resources, H.D.O.; funding acquisition, H.D.O.; supervision, H.D.O. and V.W.; investigation, L.-M.M., V.W., A.C.M. and T.L.; data analysis, L.-M.M. and V.W.; visualization, L.-M.M. and V.W.; writing—original draft preparation, L.-M.M. and H.D.O.; writing—review and editing, H.D.O., V.W. and L.-M.M. All authors have read and agreed to the published version of the manuscript. Funding This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Os75/17-2 and by the German Federal State of Hesse as part of the LOEWE Main Research Focus Dynamem to H.D.O. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Original data are available upon reasonable request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Loss of MICOS impacts cardiolipin synthesis. (A) Representative western blot analysis of mitochondrial protein extracts of P. anserina wild type, ΔPaMic60, ΔPaMic19, ΔPaMic10, ΔPaMic26 using a PaCRD1 antibody. (B) Quantification of PaCRD1 amount normalized to the Coomassie-stained gel. PaCRD1 amount in wild type cultures was set to 1. Data represent mean ± SD (3 biological replicates each). (C) One-dimensional thin layer chromatography analyses of mitochondrial phospholipids of the wild type, ΔPaMic60, ΔPaMic19, ΔPaMic10 and ΔPaMic26. CL: cardiolipin; PE: phosphatidylethanolamine; PC: phosphatidylcholine; PS: phosphatidylserine. (D) Quantification of phospholipid spots in (C). Intensity of each spot was determined and related to the intensity of the whole track. Phospholipid values of the wild type were set to 1. Data represent mean ± SD (3 biological replicates each). * p < 0.05, ** p < 0.01. Figure 2 Ablation of MICOS subunits alters mitochondrial phospholipid composition. (A) Lipid profile of mitochondrial protein extracts of P. anserina wild type, ΔPaMic60 and ΔPaMic26. Significant differences to the wild type are marked by green (increase) or red (decrease) boxes, respectively. Exact values are shown in Supplementary Materials (Table S1). TAG: triacylglycerol; Cer: ceramide; CL: cardiolipin; DAG: diacylglycerol; IPC: inositol phosphorylceramide; LPL: lyso-phospholipids; PA: phosphatidic acid; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PG: phosphatidylglycerol; PI: phosphatidylinositol; PS: phosphatidylserine. (B) PE/PC ratio of wild type, ΔPaMic60, and ΔPaMic26. (C) Comparative analysis of CL from (A). Total amount of CL in wild-type cultures was set to 1. (D) Graphical illustration of different CL species in wild type, ΔPaMic60, and ΔPaMic26 according to total length of all four acyl chains (66–74) and total degree of unsaturation (4–11). The most abundant CL species are represented. Significant differences to wild type of increased or reduced CL species are marked by green or red boxes, respectively. Exact values are shown in Supplementary Materials (Table S2). (E) Total double bonds across all lipids. Total amount of double bonds in wild type was set to 1. Exact values are shown in Supplementary Materials (Table S3A). Data represent mean ± SD (5 biological replicates each). * p < 0.05, ** p < 0.01. Figure 3 Ablation of PaTAZ1 affects longevity of MICOS mutants. (A) Scheme depicting components of CL biosynthesis and remodeling in the inner mitochondrial membrane. IMS: intermembrane space; IMM: inner mitochondrial membrane; PA: phosphatidic acid; TAM41: PA cytidylyltransferase; PGS1: phosphatidylglycerophosphate synthase; GEP4: phosphatidylglycerophosphatase; PG: phosphatidylglycerol; CRD1: cardiolipin synthase; pCL: premature cardiolipin; iPLA2 family: several phospholipases; MLCL: monolysocardiolipin; TAZ1: tafazzin; mCL: mature cardiolipin. A round head group indicates one phosphate (e.g., PA, PG), and an oval head group indicates two phosphates (e.g., pCL, MLCL, mCL). (B) Southern blot analysis with BamHI-digested DNA to verify the newly generated double mutant ΔPaMic60/ΔPaTaz1 by the use of the hygromycin (Hph) resistance gene. A cross (x) marks an unspecific signal. (C) Survival curves of P. anserina wild type (n = 25), ΔPaTaz1 (n = 26), ΔPaMic60 (n = 24), and ΔPaMic60/ΔPaTaz1 (n = 32) grown on M2 medium. (D) Mean lifespan of cultures from (C). Data represent mean ± SD. (E) Southern blot analysis with EcoRV-digested DNA to verify the newly generated double mutant ΔPaMic26/ΔPaTaz1 by the use of the hygromycin (Hph) resistance gene. (F) Survival curves of P. anserina wild type (n = 24), ΔPaTaz1 (n = 27), ΔPaMic26 (n = 43), and ΔPaMic26/ΔPaTaz1 (n = 50) grown on M2 medium. (G) Mean lifespan of cultures from (F). Data represent mean ± SD. Significant differences to wild type: ** p < 0.01, *** p < 0.001; significant differences to ΔPaTaz1: ## p < 0.01, ### p < 0.001; significant differences to ΔPaMic60 or ΔPaMic26: $$$ p < 0.001. Figure 4 Loss of PaTAZ1 has a dramatic impact on phospholipid metabolism. (A) Lipid profiles of mitochondrial protein extracts of P. anserina wild type (n = 5) and ΔPaTaz1 (n = 3). Significant differences to the wild type are marked with green (increase) or red (decrease) boxes, respectively. Exact values are shown in Supplementary Materials (Table S1). TAG: triacylglycerol; Cer: ceramide; CL: cardiolipin; DAG: diacylglycerol; IPC: inositol phosphorylceramide; LPL: lyso-phospholipids; PA: phosphatidic acid; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PG: phosphatidylglycerol; PI: phosphatidylinositol; PS: phosphatidylserine. (B) PE/PC ratio of wild type and ΔPaTaz1. Data represent mean ± SD. (C) Graphical illustration of different CL species in wild type and ΔPaTaz1 according to total length of all four acyl chains (66–72) and total degree of unsaturation (3–11). The most abundant CL species are represented (proportion > 10%). Significant differences to the wild type are marked by green (increase) or red (decrease) boxes, respectively. CL 72:8 and CL 72:9 are only represented in the wild type and are therefore marked with a red border. Exact values are shown in Supplementary Materials (Table S2). (D) Total double bonds across all lipids. Total amount of double bonds in wild type was set to 1. Data represent mean ± SD. Exact values are shown in Supplementary Materials (Table S3A). * p < 0.05, ** p < 0.01. Figure 5 Simultaneous ablation of PaMIC60 and PaTAZ1 results in PaTAZ1-independent CL 72:X formation. (A) Phospholipid composition of the CDP-DAG pathway using mitochondrial protein extracts of P. anserina wild type (n = 5), ΔPaMic60 (n = 5), ΔPaMic60/ΔPaTaz1 (n = 3), ΔPaTaz1 (n = 3), ΔPaMic26/ΔPaTaz1 (n = 3), and ΔPaMic26 (n = 5). Data represent mean ± SD. Exact values are shown in Supplementary Materials (Table S1). CL: cardiolipin; DAG: diacylglycerol; PA: phosphatidic acid; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PG: phosphatidylglycerol; PS: phosphatidylserine. (B) PE/PC ratio of cultures from (A). Data represent mean ± SD. (C) Graphical illustration of different CL species in wild type, ΔPaMic60, ΔPaMic60/ΔPaTaz1, ΔPaTaz1, ΔPaMic26/ΔPaTaz1, and ΔPaMic26 according to total length of all four acyl chains (66–74) and total degree of unsaturation (3–11). The most abundant CL species are represented. Exact values are shown in Supplementary Materials (Table S2). Significant differences to wild type: * p < 0.05, ** p < 0.01, *** p < 0.001; # significant differences to ΔPaTaz1: # p < 0.05, ## p < 0.01; significant differences to ΔPaMic60: $ p < 0.05, $$ p < 0.01, $$$ p < 0.001; significant differences to ΔPaMic26: § p < 0.05, §§ p < 0.01, §§§ p < 0.001. Figure 6 Linoleic acid leads to lifespan extension of ΔPaMic60/ΔPaTaz1. (A) Survival curves of P. anserina wild type (n = 17), ΔPaTaz1 (n = 14), ΔPaMic60 (n = 16), and ΔPaMic60/ΔPaTaz1 (n = 20) grown on M2 medium without linoleic acid and P. anserina wild type (n = 15), ΔPaTaz1 (n = 15), ΔPaMic60 (n = 14), and ΔPaMic60/ΔPaTaz1 (n = 15) grown on M2 medium with 0.8 mM linoleic acid. (B) Mean lifespan of cultures from (A). Data represent mean ± SD. Significant differences to wild type *** p < 0.001; significant differences to the corresponding strain without linoleic acid # p < 0.05, ### p < 0.001. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Tatsuta T. Langer T. Quality control of mitochondria: Protection against neurodegeneration and ageing EMBO J. 2008 27 306 314 10.1038/sj.emboj.7601972 18216873 2. Fischer F. Hamann A. Osiewacz H.D. Mitochondrial quality control: An integrated network of pathways Trends Biochem. Sci. 2012 37 284 292 10.1016/j.tibs.2012.02.004 22410198 3. López-Otín C. Blasco M.A. Partridge L. Serrano M. Kroemer G. The hallmarks of aging Cell 2013 153 1194 1217 10.1016/j.cell.2013.05.039 23746838 4. Bernhardt D. Hamann A. Osiewacz H.D. The role of mitochondria in fungal aging Curr. Opin. Microbiol. 2014 22 1 7 10.1016/j.mib.2014.09.007 25299751 5. Linnane A.W. Marzuki S. Ozawa T. Tanaka M. Mitochondrial DNA mutations as an important contributor to ageing and degenerative diseases Lancet 1989 1 642 645 10.1016/S0140-6736(89)92145-4 2564461 6. Osiewacz H.D. Mitochondrial functions and aging Gene 2002 286 65 71 10.1016/S0378-1119(01)00804-6 11943461 7. Jazwinski S.M. Kriete A. The yeast retrograde response as a model of intracellular signaling of mitochondrial dysfunction Front. Physiol. 2012 3 139 10.3389/fphys.2012.00139 22629248 8. Osiewacz H.D. Role of mitochondria in aging and age-related disease Exp. Gerontol. 2010 45 465 10.1016/j.exger.2010.05.001 20451599 9. Breitenbach M. Laun P. Dickinson J.R. Klocker A. Rinnerthaler M. Dawes I.W. Aung-Htut M.T. Breitenbach-Koller L. Caballero A. Nyström T. The role of mitochondria in the aging processes of yeast Subcell. Biochem. 2012 57 55 78 10.1007/978-94-007-2561-4_3 22094417 10. Sun N. Youle R.J. Finkel T. The mitochondrial basis of aging Mol. Cell 2016 61 654 666 10.1016/j.molcel.2016.01.028 26942670 11. Kauppila T.E.S. Kauppila J.H.K. Larsson N.G. Mammalian mitochondria and aging: An update Cell Metab. 2017 25 57 71 10.1016/j.cmet.2016.09.017 28094012 12. Cho J. Hur J.H. Walker D.W. The role of mitochondria in Drosophila aging Exp. Gerontol. 2011 46 331 334 10.1016/j.exger.2010.08.010 20832466 13. Kirstein-Miles J. Morimoto R.I. Caenorhabditis elegans as a model system to study intercompartmental proteostasis: Interrelation of mitochondrial function, longevity, and neurodegenerative diseases Dev. Dyn. 2010 239 1529 1538 10.1002/dvdy.22292 20419784 14. Scheckhuber C.Q. Osiewacz H.D. Podospora anserina: A model organism to study mechanisms of healthy ageing Mol. Genet. Genom. 2008 280 365 374 10.1007/s00438-008-0378-6 18797929 15. Osiewacz H.D. Schürmanns L. A network of pathways controlling cellular homeostasis affects the onset of senescence in Podospora anserina J. Fungi 2021 7 263 10.3390/jof7040263 33807190 16. Scheckhuber C.Q. Erjavec N. Tinazli A. Hamann A. Nyström T. Osiewacz H.D. Reducing mitochondrial fission results in increased life span and fitness of two fungal ageing models Nat. Cell Biol. 2007 9 99 105 10.1038/ncb1524 17173038 17. Daum B. Walter A. Horst A. Osiewacz H.D. Kühlbrandt W. Age-dependent dissociation of ATP synthase dimers and loss of inner-membrane cristae in mitochondria Proc. Natl. Acad. Sci. USA 2013 110 15301 15306 10.1073/pnas.1305462110 24006361 18. Brust D. Daum B. Breunig C. Hamann A. Kühlbrandt W. Osiewacz H.D. Cyclophilin D links programmed cell death and organismal aging in Podospora anserina Aging Cell 2010 9 761 775 10.1111/j.1474-9726.2010.00609.x 20626725 19. Warnsmann V. Marschall L.-M. Osiewacz H.D. Impaired F1Fo-ATP-synthase dimerization leads to the induction of cyclophilin D-mediated autophagy-dependent cell death and accelerated aging Cells 2021 10 757 10.3390/cells10040757 33808173 20. Rampello N.G. Stenger M. Westermann B. Osiewacz H.D. Impact of F1Fo-ATP-synthase dimer assembly factors on mitochondrial function and organismic aging Microb. Cell 2018 5 198 207 10.15698/mic2018.04.625 29610761 21. Warnsmann V. Marschall L.M. Meeßen A.C. Wolters M. Schürmanns L. Osiewacz H.D. Disruption of the MICOS complex leads to an aberrant cristae structure and an unexpected, pronounced lifespan extension in Podospora anserina bioRxiv 2022 10.1101/2022.03.21.485166 22. Serricchio M. Vissa A. Kim P.K. Yip C.M. McQuibban G.A. Cardiolipin synthesizing enzymes form a complex that interacts with cardiolipin-dependent membrane organizing proteins Biochim. Biophys. Acta Mol. Cell Biol. Lipids 2018 1863 447 457 10.1016/j.bbalip.2018.01.007 29343430 23. Acehan D. Malhotra A. Xu Y. Ren M. Stokes D.L. Schlame M. Cardiolipin affects the supramolecular organization of ATP synthase in mitochondria Biophys. J. 2011 100 2184 2192 10.1016/j.bpj.2011.03.031 21539786 24. Martensson C.U. Doan K.N. Becker T. Effects of lipids on mitochondrial functions Biochim. Biophys. Acta Mol. Cell Biol. Lipids 2017 1862 102 113 10.1016/j.bbalip.2016.06.015 27349299 25. Rampelt H. Wollweber F. Gerke C. de Boer R. van der Klei I.J. Bohnert M. Pfanner N. van der Laan M. Assembly of the mitochondrial cristae organizer Mic10 Is regulated by Mic26-Mic27 antagonism and cardiolipin J. Mol. Biol. 2018 430 1883 1890 10.1016/j.jmb.2018.04.037 29733859 26. Rampelt H. Zerbes R.M. van der Laan M. Pfanner N. Role of the mitochondrial contact site and cristae organizing system in membrane architecture and dynamics Biochim. Biophys. Acta Mol. Cell Res. 2017 1864 737 746 10.1016/j.bbamcr.2016.05.020 27614134 27. Stephan T. Brüser C. Deckers M. Steyer A.M. Balzarotti F. Barbot M. Behr T.S. Heim G. Hübner W. Ilgen P. MICOS assembly controls mitochondrial inner membrane remodeling and crista junction redistribution to mediate cristae formation EMBO J. 2020 39 e104105 10.15252/embj.2019104105 32567732 28. Anand R. Reichert A.S. Kondadi A.K. Emerging roles of the MICOS complex in cristae dynamics and biogenesis Biology 2021 10 600 10.3390/biology10070600 34209580 29. Löser T. Joppe A. Hamann A. Osiewacz H.D. Mitochondrial phospholipid homeostasis is regulated by the i-AAA protease PaIAP and affects organismic aging Cells 2021 10 2775 10.3390/cells10102775 34685755 30. Aaltonen M.J. Friedman J.R. Osman C. Salin B. di Rago J.P. Nunnari J. Langer T. Tatsuta T. MICOS and phospholipid transfer by Ups2-Mdm35 organize membrane lipid synthesis in mitochondria J. Cell Biol. 2016 213 525 534 10.1083/jcb.201602007 27241913 31. Cullis P.R. de Kruijff B. Lipid polymorphism and the functional roles of lipids in biological membranes Biochim. Biophys. Acta 1979 559 399 420 10.1016/0304-4157(79)90012-1 391283 32. Escriba P.V. Ozaita A. Ribas C. Miralles A. Fodor E. Farkas T. Garcia-Sevilla J.A. Role of lipid polymorphism in G protein-membrane interactions: Nonlamellar-prone phospholipids and peripheral protein binding to membranes Proc. Natl. Acad. Sci. USA 1997 94 11375 11380 10.1073/pnas.94.21.11375 9326617 33. van der Veen J.N. Kennelly J.P. Wan S. Vance J.E. Vance D.E. Jacobs R.L. The critical role of phosphatidylcholine and phosphatidylethanolamine metabolism in health and disease Biochim. Biophys. Acta Biomembr. 2017 1859 1558 1572 10.1016/j.bbamem.2017.04.006 28411170 34. Li Z. Agellon L.B. Allen T.M. Umeda M. Jewell L. Mason A. Vance D.E. The ratio of phosphatidylcholine to phosphatidylethanolamine influences membrane integrity and steatohepatitis Cell Metab. 2006 3 321 331 10.1016/j.cmet.2006.03.007 16679290 35. Tasseva G. Bai H.D. Davidescu M. Haromy A. Michelakis E. Vance J.E. Phosphatidylethanolamine deficiency in mammalian mitochondria impairs oxidative phosphorylation and alters mitochondrial morphology J. Biol. Chem. 2013 288 4158 4173 10.1074/jbc.M112.434183 23250747 36. Oemer G. Koch J. Wohlfarter Y. Alam M.T. Lackner K. Sailer S. Neumann L. Lindner H.H. Watschinger K. Haltmeier M. Phospholipid acyl chain diversity controls the tissue-specific assembly of mitochondrial cardiolipins Cell Rep. 2020 30 4281 4291.e4284 10.1016/j.celrep.2020.02.115 32209484 37. Stefanyk L.E. Coverdale N. Roy B.D. Peters S.J. LeBlanc P.J. Skeletal muscle type comparison of subsarcolemmal mitochondrial membrane phospholipid fatty acid composition in rat J. Membr. Biol. 2010 234 207 215 10.1007/s00232-010-9247-4 20336283 38. Chicco A.J. Sparagna G.C. McCune S.A. Johnson C.A. Murphy R.C. Bolden D.A. Rees M.L. Gardner R.T. Moore R.L. Linoleate-rich high-fat diet decreases mortality in hypertensive heart failure rats compared with lard and low-fat diets Hypertension 2008 52 549 555 10.1161/HYPERTENSIONAHA.108.114264 18663155 39. Mulligan C.M. Sparagna G.C. Le C.H. De Mooy A.B. Routh M.A. Holmes M.G. Hickson-Bick D.L. Zarini S. Murphy R.C. Xu F.Y. Dietary linoleate preserves cardiolipin and attenuates mitochondrial dysfunction in the failing rat heart Cardiovasc. Res. 2012 94 460 468 10.1093/cvr/cvs118 22411972 40. Oemer G. Edenhofer M.L. Wohlfarter Y. Lackner K. Leman G. Koch J. Cardoso L.H.D. Lindner H.H. Gnaiger E. Dubrac S. Fatty acyl availability modulates cardiolipin composition and alters mitochondrial function in HeLa cells J. Lipid Res. 2021 62 100111 10.1016/j.jlr.2021.100111 34450173 41. Ernst R. Ejsing C.S. Antonny B. Homeoviscous adaptation and the regulation of membrane lipids J. Mol. Biol. 2016 428 4776 4791 10.1016/j.jmb.2016.08.013 27534816 42. Dudek J. Role of cardiolipin in mitochondrial signaling pathways Front. Cell Dev. Biol. 2017 5 90 10.3389/fcell.2017.00090 29034233 43. Bissler J.J. Tsoras M. Goring H.H. Hug P. Chuck G. Tombragel E. McGraw C. Schlotman J. Ralston M.A. Hug G. Infantile dilated X-linked cardiomyopathy, G4.5 mutations, altered lipids, and ultrastructural malformations of mitochondria in heart, liver, and skeletal muscle Lab. Investig. 2002 82 335 344 10.1038/labinvest.3780427 11896212 44. Houtkooper R.H. Rodenburg R.J. Thiels C. van Lenthe H. Stet F. Poll-The B.T. Stone J.E. Steward C.G. Wanders R.J. Smeitink J. Cardiolipin and monolysocardiolipin analysis in fibroblasts, lymphocytes, and tissues using high-performance liquid chromatography-mass spectrometry as a diagnostic test for Barth syndrome Anal. Biochem. 2009 387 230 237 10.1016/j.ab.2009.01.032 19454236 45. Gu Z. Valianpour F. Chen S. Vaz F.M. Hakkaart G.A. Wanders R.J. Greenberg M.L. Aberrant cardiolipin metabolism in the yeast taz1 mutant: A model for Barth syndrome Mol. Microbiol. 2004 51 149 158 10.1046/j.1365-2958.2003.03802.x 14651618 46. Ye C. Lou W. Li Y. Chatzispyrou I.A. Huttemann M. Lee I. Houtkooper R.H. Vaz F.M. Chen S. Greenberg M.L. Deletion of the cardiolipin-specific phospholipase Cld1 rescues growth and life span defects in the tafazzin mutant: Implications for Barth syndrome J. Biol. Chem. 2014 289 3114 3125 10.1074/jbc.M113.529487 24318983 47. Zhou J. Zhong Q. Li G. Greenberg M.L. Loss of cardiolipin leads to longevity defects that are alleviated by alterations in stress response signaling J. Biol. Chem. 2009 284 18106 18114 10.1074/jbc.M109.003236 19401462 48. Dudek J. Cheng I.F. Chowdhury A. Wozny K. Balleininger M. Reinhold R. Grunau S. Callegari S. Toischer K. Wanders R.J. Cardiac-specific succinate dehydrogenase deficiency in Barth syndrome EMBO Mol. Med. 2016 8 139 154 10.15252/emmm.201505644 26697888 49. Minkler P.E. Hoppel C.L. Separation and characterization of cardiolipin molecular species by reverse-phase ion pair high-performance liquid chromatography-mass spectrometry J. Lipid Res. 2010 51 856 865 10.1194/jlr.D002857 19965604 50. Cao J. Liu Y. Lockwood J. Burn P. Shi Y. A novel cardiolipin-remodeling pathway revealed by a gene encoding an endoplasmic reticulum-associated acyl-CoA:lysocardiolipin acyltransferase (ALCAT1) in mouse J. Biol. Chem. 2004 279 31727 31734 10.1074/jbc.M402930200 15152008 51. Song C. Zhang J. Qi S. Liu Z. Zhang X. Zheng Y. Andersen J.P. Zhang W. Strong R. Martinez P.A. Cardiolipin remodeling by ALCAT1 links mitochondrial dysfunction to Parkinson’s diseases Aging Cell 2019 18 e12941 10.1111/acel.12941 30838774 52. Wasmus C. Dudek J. Metabolic alterations caused by defective cardiolipin remodeling in inherited cardiomyopathies Life 2020 10 277 10.3390/life10110277 33187128 53. Xia C. Fu Z. Battaile K.P. Kim J.P. Crystal structure of human mitochondrial trifunctional protein, a fatty acid beta-oxidation metabolon Proc. Natl. Acad. Sci. USA 2019 116 6069 6074 10.1073/pnas.1816317116 30850536 54. Taylor W.A. Hatch G.M. Identification of the human mitochondrial linoleoyl-coenzyme A monolysocardiolipin acyltransferase (MLCL AT-1) J. Biol. Chem. 2009 284 30360 30371 10.1074/jbc.M109.048322 19737925 55. Altschul S.F. Gish W. Miller W. Myers E.W. Lipman D.J. Basic local alignment search tool J. Mol. Biol. 1990 215 403 410 10.1016/S0022-2836(05)80360-2 2231712 56. Olzmann J.A. Carvalho P. Dynamics and functions of lipid droplets Nat. Rev. Mol. Cell Biol. 2019 20 137 155 10.1038/s41580-018-0085-z 30523332 57. Lu X. Yu H. Ma Q. Shen S. Das U.N. Linoleic acid suppresses colorectal cancer cell growth by inducing oxidant stress and mitochondrial dysfunction Lipids Health Dis. 2010 9 106 10.1186/1476-511X-9-106 20868498 58. Shareck J. Nantel A. Belhumeur P. Conjugated linoleic acid inhibits hyphal growth in Candida albicans by modulating Ras1p cellular levels and downregulating TEC1 expression Eukaryot. Cell 2011 10 565 577 10.1128/EC.00305-10 21357478 59. Rizet G. Impossibility of obtaining uninterrupted and unlimited multiplication of the ascomycete Podospora anserina Comptes Rendus Hebd. Seances L’academie Des. Sci. 1953 237 838 840 60. Osiewacz H.D. Hamann A. Zintel S. Assessing organismal aging in the filamentous fungus Podospora anserina Methods Mol. Biol. 2013 965 439 462 10.1007/978-1-62703-239-1_29 23296676 61. Lecellier G. Silar P. Rapid methods for nucleic acids extraction from Petri dish-grown mycelia Curr. Genet. 1994 25 122 123 10.1007/BF00309536 8087879 62. Zintel S. Schwitalla D. Luce K. Hamann A. Osiewacz H.D. Increasing mitochondrial superoxide dismutase abundance leads to impairments in protein quality control and ROS scavenging systems and to lifespan shortening Exp. Gerontol. 2010 45 525 532 10.1016/j.exger.2010.01.006 20080171 63. Ejsing C.S. Sampaio J.L. Surendranath V. Duchoslav E. Ekroos K. Klemm R.W. Simons K. Shevchenko A. Global analysis of the yeast lipidome by quantitative shotgun mass spectrometry Proc. Natl. Acad. Sci. USA 2009 106 2136 2141 10.1073/pnas.0811700106 19174513 64. Klose C. Surma M.A. Gerl M.J. Meyenhofer F. Shevchenko A. Simons K. Flexibility of a eukaryotic lipidome--insights from yeast lipidomics PLoS ONE 2012 7 e35063 10.1371/journal.pone.0035063 22529973 65. Surma M.A. Herzog R. Vasilj A. Klose C. Christinat N. Morin-Rivron D. Simons K. Masoodi M. Sampaio J.L. An automated shotgun lipidomics platform for high throughput, comprehensive, and quantitative analysis of blood plasma intact lipids Eur. J. Lipid Sci. Technol. 2015 117 1540 1549 10.1002/ejlt.201500145 26494980 66. Herzog R. Schuhmann K. Schwudke D. Sampaio J.L. Bornstein S.R. Schroeder M. Shevchenko A. LipidXplorer: A software for consensual cross-platform lipidomics PLoS ONE 2012 7 e29851 10.1371/journal.pone.0029851 22272252 67. Herzog R. Schwudke D. Schuhmann K. Sampaio J.L. Bornstein S.R. Schroeder M. Shevchenko A. A novel informatics concept for high-throughput shotgun lipidomics based on the molecular fragmentation query language Genome Biol. 2011 12 R8 10.1186/gb-2011-12-1-r8 21247462

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094682 ijms-23-04682 Article Impact of Fluid Dynamics on the Viability and Differentiation Capacity of 3D-Cultured Jaw Periosteal Cells Cen Wanjing 1 Wang Suya 1 https://orcid.org/0000-0003-2040-7492 Umrath Felix 12 Reinert Siegmar 1 Alexander Dorothea 1* Smeets Ralf Academic Editor Henningsen Anders Academic Editor 1 Department of Oral and Maxillofacial Surgery, University Hospital Tübingen, 72076 Tübingen, Germany; cenwanjingwj@gmail.com (W.C.); suyawang1227@gmail.com (S.W.); felix.umrath@med.uni-tuebingen.de (F.U.); siegmar.reinert@med.uni-tuebingen.de (S.R.) 2 Department of Orthopedic Surgery, University Hospital Tübingen, 72072 Tübingen, Germany * Correspondence: dorothea.alexander@med.uni-tuebingen.de 23 4 2022 5 2022 23 9 468228 3 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Perfused bioreactor systems are considered to be a promising approach for the 3D culturing of stem cells by improving the quality of the tissue-engineered grafts in terms of better cell proliferation and deeper penetration of used scaffold materials. Our study aims to establish an optimal perfusion culture system for jaw periosteal cell (JPC)-seeded scaffolds. For this purpose, we used beta-tricalcium phosphate (β-TCP) scaffolds as a three-dimensional structure for cell growth and osteogenic differentiation. Experimental set-ups of tangential and sigmoidal fluid configurations with medium flow rates of 100 and 200 µL/min were applied within the perfusion system. Cell metabolic activities of 3D-cultured JPCs under dynamic conditions with flow rates of 100 and 200 µL/min were increased in the tendency after 1, and 3 days of culture, and were significantly increased after 5 days. Significantly higher cell densities were detected under the four perfused conditions compared to the static condition at day 5. However, cell metabolic and proliferation activity under dynamic conditions showed flow rate independency in our study. In this study, dynamic conditions increased the expression of osteogenic markers (ALPL, COL1A1, RUNX2, and OCN) compared to static conditions and the tangential configuration showed a stronger osteogenic effect than the sigmoidal flow configuration. perfusion bioreactor system tangential and sigmoidal flow configuration jaw periosteal cells bioresorbable β-TCP scaffold cell proliferation osteogenic differentiation ==== Body pmc1. Introduction Organ loss or failure due to tumor resection, severe trauma, or congenital defects, is one of the most frequent, destructive, and cost-intensive problems, especially with regard to the regeneration of large bone defects. Due to the limitation of spontaneous bone self-healing, regeneration of large bone defects is beyond the normal healing potential [1,2]. For these cases, the tissue engineering approach comprising the use of autologous stem cells and degradable biomaterials represents a suitable and very promising therapeutic option. For bone tissue engineering, 3D porous scaffold materials as supporting structures are usually combined with osteogenic progenitor cells [3,4,5,6,7,8]. Three-dimensional grafts used for transplantations, such as skin flaps, are usually thin due to the limited cell survival in the central area of thick grafts [9]. Most mammalian cells are susceptible to culturing and stimulation conditions. The growth of 3D cultured cells in the static culture environment is limited by insufficient transport of oxygen and nutrients, and removal of waste products and metabolites within the scaffolds [10]. Additionally, in vitro static culture without appropriate mechanical stimulation does not simulate the natural microenvironment of bone tissue resulting in non-functional, poorly cell-colonized constructs [9,11]. To avoid these limitations, bioreactor systems were developed in order to provide dynamic culture conditions and to improve the quality of the tissue-engineered grafts [12,13,14]. In a study by Bruder et al., the implantation of a hydroxyapatite/β-TCP scaffold containing mesenchymal stem cells in a rat femoral gap model showed a positive impact on bone tissue growth around the periphery but lacked mineralization in the central region of the implant [15]. Considering these issues, the quality of tissue-engineered bone grafts has to be improved in terms of cell growth and differentiation within the whole construct. It has been reported that dynamic conditions within bioreactors resulted in a high level of human mesenchymal stem cell viability allowing a maximum size of a half adult femur (∼200 cm3) [16]. Besides improved growth conditions, dynamic culture conditions stimulated stem cell differentiation by enhancing osteogenic gene expression, and consequently promoting tissue maturation within the bioreactor [12,16]. As developments progress, some of the bioreactors were put on the market and there are increasing reports of their clinical usage [17]. Different concepts of dynamic 3D bioreactors were developed in order to simulate the natural microenvironment within the bone tissue, for example, spinner flasks, rotating wall vessel constructs, perfusion bioreactors, and systems allowing mechanical or electromagnetic stimulation of cell/scaffold composites [18]. Beta-tricalcium phosphate (β-TCP) is one of the most used synthetic bone substitute materials in bone tissue engineering due to its good biocompatibility, high osteoconductive and osteoinductive properties. β-TCP is not soluble in physiological conditions, but can be resorbed by osteoclasts, leading to material dissolution and final replacement by new bone formation [19]. Marc Bohner and co-authors has documented the widespread interest in this material, reflected in more than 200 articles published yearly [20]. In previous studies, we used this material for biofunctionalization strategies in order to improve cell functions of jaw periosteal cells (JPCs) [7,21,22,23]. We have shown in numerous studies that JPCs represent a suitable stem cell source for the generation of bone tissue engineering (BTE) constructs which can be used without constraints for bone regeneration purposes in the oral and maxillofacial region [5,24,25]. In the present study, we aimed at establishing an optimal perfusion condition in order to create cell-rich bone-like scaffolds. For this purpose, we used a commercially available perfusion bioreactor for the cultivation of JPCs seeded on β-TCP scaffolds. 2. Results 2.1. Cell Proliferation within JPC-Seeded Scaffolds Cultured in the Perfusion System Cell proliferation was analyzed indirectly by measuring the metabolic activity of JPC-seeded scaffolds under the indicated configuration, flow rate and position within the bioreactor (Figure 1A–C). As shown in Figure 1D, significantly higher metabolic activities were detected within perfused scaffolds in comparison to static conditions at day 5. Compared to day 1, significantly higher metabolic activities were obtained at day 5 under most of the conditions, except under the static condition and sigmoidal configuration with a flow rate of 100 µL/min. No significant differences were detected among dynamically cultured JPC-seeded scaffolds under different flow configurations, different flow rates or different positions within the bioreactor. 2.2. Visualization and Quantitative Analysis of Cell Distribution within β-TCP Scaffolds Cultured under Static and Perfusion Conditions by Crystal Violet Staining To visualize proliferation, density, and distribution of JPCs on β-TCP scaffolds, JPC-seeded scaffolds cultured under different conditions were stained with crystal violet, which binds to proteins and nucleic acids of cells. On day 1 some small crystal violet spots were observed on the top of scaffolds under all conditions while crystal violet plaques were detected only at the bottom edges (side that touches the ground of the well plate) (Figure 2A). During further cultivation, small crystal violet spots became larger and merged on day 3 and day 5. Bigger and deeper violet plaques were observed at the bottom of scaffolds under all conditions on day 5 in comparison to day 1 and 3. Homogenous deep violet staining was visible on the top of the scaffolds under perfused condition on day 10, while lighter violet staining was detected on the top of the scaffolds under static conditions. To better compare cell densities on the JPC-seeded scaffolds cultured under different conditions, crystal violet staining was quantified. According to the absorbance detected at 550 nm, significantly higher densities of JPCs were detected under the four perfused conditions in comparison to the static condition on day 5 (Figure 2B). JPC densities on scaffolds under perfused conditions were shown to be higher in the tendency compared to those detected under static condition on day 10. 2.3. Visualization of Cell Morphology on JPC-Seeded β-TCP Scaffolds and Quantification of Scaffold Porosity by Scanning Electron Microscopy The morphology of the porous JPC-seeded β-TCP scaffolds was analyzed by scanning electron microscopy (SEM) after 1, 3 and 5 days of in vitro culture under the indicated conditions (Figure 3A–C). Differences in cell appearance were observed in different areas of the same scaffold surface, depending on the size of the pores into which the cells grew or which they spanned. In general, the JPCs appeared to preferentially grow inside small pores on the scaffold surface while the cells grew along the rim of the big pores as shown in images with 500-fold magnification. The SEM images revealed that JPCs spread over the pores of β-TCP scaffolds, fully expanded with a flattened morphology. On day 1, the porosity of β-TCP scaffolds appeared to be high under all examined conditions under 200× and 500× magnifications and cell attachment was rarely observed (Figure 3A). During consecutive cell cultivation, the pore size and number decreased due to cell attachment and proliferation. At day 5, JPCs cultured under perfused conditions showed more homogeneous and deeper distribution within the scaffolds in comparison to the JPCs cultured under the static condition. As shown in Figure 3D, porosity of JPC-seeded scaffolds cultivated under perfused conditions decreased significantly at day 3 and 5 compared to the porosity observed at day 1. Significant lower porosity on perfused scaffolds (T + 100 µL/min, T + 200 µL/min and S + 200 µL/min perfused conditions) in comparison to static conditions were detected at day 5. 2.4. Visualization of Cell Density and Distribution within Scaffolds by Fluorescent Staining and Microscopy Since β-TCP scaffolds have a porous and brittle composition, we achieved the best experience with the polymethylmethacrylate (PMMA) embedding procedure. For further information about JPC distribution within the scaffolds under static or different perfusion conditions, sections of PMMA-embedded JPC-seeded scaffolds were stained by Sytox orange to visualize cell nuclei. The images of 1.25-fold magnification showed that JPCs were mainly located on the top (white arrows) and the bottom edge (rectangular boxes) of scaffolds after 5 days of culture. A higher fluorescence intensity was observed on the sections of the scaffolds under perfusion in comparison with scaffolds cultured under the static condition (Figure 4A). After 10 days of culture, cells appeared on both the surface and within the scaffolds under all conditions (Figure 4A). According to the quantification results of Sytox orange staining, means of red fluorescence under perfused conditions were higher than the ones obtained under static condition in the tendency at both day 5 and 10. Mean fluorescence under sigmoidal configuration with a flow rate of 100 μL/min was shown to be significantly higher compared to the detected mean fluorescence under static condition (Figure 4B). 2.5. Gene Expression Analyses of Osteogenic Markers in 3D-Cultured JPCs Growing under Perfusion Conditions JPC-seeded scaffolds were cultured dynamically or statically in osteogenic media and gene expression analysis was performed after 5, 10 and 15 days of 3D culture. mRNA expression levels of alkaline phosphatase (ALPL) and RUNX family transcription factor 2 (RUNX2) were significantly upregulated after 5 days of osteogenic induction under all performed conditions, but no significant differences between perfused conditions and static control (Figure 5A,B and Figure 6A,B) were observed. Gene expression levels of collagen 1α1 (COL1A1) were significantly higher under tangential configuration independently of the flow rates at day 5 (Figure 7A,B). In the case of osteocalcin (OCN), expression levels were increased significantly only under tangential configuration with 200 μL/min compared to obtained levels under static conditions in osteogenic media at day 5 (Figure 8A,B). At day 10, significantly higher ALPL and COL1A1 expression levels under tangential configuration with a flow rate of 100 μL/min were detected compared to levels under static condition in both control and osteogenic media. Further, significantly higher expression levels of OCN were observed under tangential configuration compared to levels detected under static and osteogenic condition. At day 15, significantly higher ALPL expression was detected under tangential configurations in osteogenic medium. Higher expression of RUNX2 was observed under sigmoidal configuration with a flow rate of 200 μL/min in control media, while increased expression of COL1A1 was detected under sigmoidal configuration with a 200 μL/min flow rate after 15 days of osteogenic differentiation (Figure 5, Figure 6, Figure 7 and Figure 8). 3. Discussion Since cell fate and function are susceptible to the cells’ microenvironment, control over the microenvironment is essential in order to regulate cellular activities and behavior [26]. Many studies have shown that fluidic bioreactors are useful to control the microenvironment and have a high impact on promoting cell proliferation and differentiation. Perfusion bioreactor systems have shown promise for the 3D cultivation of stem cells for bone regeneration [27]. Beta-tricalcium phosphate, the scaffold material we used in this study, is a resorbable material that is widely used in clinics as a synthetic bone substitute [28]. It can be biofunctionalized in order to improve functions of the colonizing cells, as we reported in a previous study [7]. The aim of the present study was to establish optimal perfused conditions for the cultivation of JPC-seeded beta-TCP scaffolds, and to compare cell behaviors/functions under different perfusion conditions in comparison to the static culture condition. Flow rates during perfusion have to be optimized, since cells can be damaged at high flow rates, or may not have sufficient nutrients and oxygen supply at low flow rates. In our study, cell metabolic activities were increased in the tendency under dynamic conditions with flow rates of 100 and 200 µL/min after day 1, and 3 of perfusion culture, and reached significantly higher values at day 5 compared to the static culture (Figure 1C). This result was confirmed by the crystal violet staining which showed similar results (Figure 2B) as detected by the colometric assay. The flow rates we used in this study were supposed to be in the range of values reported to promote osteogenic cell proliferation [3,4]. Cartmell et al. [3] reported that a flow rate of 1.0 mL/min led to significant cell death and lowering of flow rate resulted in increased numbers of viable MC3T3-E1 cells. Best results were achieved with a flow rate of 100 μL /min compared to 200 μL /min and to the static controls [3]. However, in our study, very similar cell metabolic activities were obtained under dynamic conditions independently of the used flow rate. An important difference to these studies might be the fact, that perfusion chambers used here were much bigger than the scaffolds, which allowed the medium flow to go around the scaffolds. As a result, we made the observation that cells did not grow into the scaffolds and did not homogeneously cover the scaffolds, as shown by the crystal violet and Sytox orange staining. The flow of our perfusion system exerted shear stress in an unidirectional laminar manner to the scaffold surface under both configuration types (Figure 1A,B). A previous study demonstrated that bone cells respond to fluid-generated shear stress by an increase in intracellular calcium, providing evidence that fluidic flow alone can stimulate bone cells [29]. In our study, we expected that the shear stress exerted by the fluidic flow onto the scaffolds in the same chamber depended on the distance between the scaffolds and the medium inlet. But as shown in Figure 1C, flow configuration made no difference in cell viability of 3D-cultured JPCs, implying that shear stress forces within the chamber were uniformly distributed or too little to direct cell proliferation. Since the amount of medium in the perfusion system was 200 times more than in the cell culture plate for static culture, enhanced cell proliferation on perfused scaffolds can be explained by better supply of nutrients and better transportation of metabolic waste. Cell distribution on the surface of scaffolds was initially determined by the seeding procedure/density in the 96-well plate outside the perfusion system, showing cell-rich distribution on the top and bottom edge of the scaffolds (Figure 2A and Figure 4A). Crystal violet staining and SEM images revealed higher cell densities on scaffolds cultured under dynamic conditions compared to the static controls during the analyzed culture time period. McCoy and co-authors summarized in his review article that cells attached flatly to the rim of the scaffold pores were more prone to active impact of perfusion compared to cells that bridged pores thereupon underwent cytoskeleton deformations due to resistance to flow [30]. We observed JPCs with a flat morphology attached to the side or the inside of the beta-TCP scaffold pores, in the perfusion experiments at day 1 by SEM. At day 5, cells were prone to bridge some of the scaffold pores because of increasing confluence under perfusion conditions resulting in significantly decreased porosity on the perfused scaffolds (Figure 3D). On one hand, achieving higher cell densities is desired. However, reduced scaffold porosity minimizes the nutrient transport and the stimulating effect on the cells growing within the scaffold by flow perfusion. Further experiments are needed to determine the cell viabilities within the scaffolds for long-term culture. Overall, the data suggested that the perfusion system promoted JPCs proliferation in beta-TCP scaffolds under tangential and sigmoidal configuration with flow rates of 100 and 200 μL/min, with no evidence pointing to different effects in different types of configurations or flow rates. Within the osteons, bone cells are exposed to interstitial fluid flow through the bone canaliculi, where they respond to changes in fluid flow shear stress controlling bone formation [31]. Additionally, progenitor cells can be affected in their differentiation by changes in hydrostatic pressure and shear stress within the bone marrow [32]. The perfusion system can also be used to mimic mechanical stimulation to the cells growing within the constructs to promote osteogenic differentiation and extracellular matrix production. In our study, the comparison of static and dynamic cultivation in terms of osteogenic gene expression (ALPL, COL1A1, RUNX2, and OCN) revealed that dynamic conditions obviously increased the expression of the analyzed osteogenic markers and the tangential flow configuration had stronger osteoinductive effect than the sigmoidal configuration. As an early marker of osteogenic differentiation [33,34], alkaline phosphatase is reported to be upregulated by fluidic shear stress both on mRNA and protein expression level in MC3T3-E1 cells [3,4], and human osteoblasts [6] as well as in human MSCs [8,35]. Cartmell and co-authors reported from increased ALPL gene expression levels at 200 μL/min compared to conditions under lower flow rates. In our perfusion system mRNA levels of ALPL significantly increased compared to static conditions, and higher ALPL levels were induced under tangential compared to sigmoidal configuration in the tendency and at significant level under osteogenic condition at day 10. However, no significant change was achieved at different flow rates (100 and/or 200 μL/min). Compared to results obtained under sigmoidal configuration (Figure 6D,E) the tangential configuration setting seemed to be also more effective in the upregulation of COL1A1 gene expression (Figure 6D,E). RUNX2 represents an essential transcription factor involved in osteoblastic differentiation and skeletal morphogenesis [36,37]. Induction of RUNX2 was detected in osteogenic samples compared to the untreated ones, but perfused configurations had no significant effect on it. Osteocalcin (OCN) expression was significantly upregulated in the tangential configuration setting at day 5 and 10 of perfusion culture (Figure 8A,C,D). Taken together, in terms of metabolic activity/proliferation and distribution within the β-TCP scaffolds, we detected significant differences compared to static conditions, but we did not detect any correlation to fluidic dynamics or to the scaffold position within the used bioreactor. The tangential flow configuration seemed to activate osteogenic gene expressions by JPCs at a higher extent than the sigmoidal configuration set-up. 4. Materials and Methods 4.1. Isolation and Expansion of Jaw Periosteal Cells (JPCs) The jaw periosteal tissue of three donors was obtained during routine surgery after informed written consent (approval number 6182017BO2 from the local ethics committee). The tissue (≤1 cm2) was cut into small pieces and washed with Dulbecco’s phosphate buffered saline (DPBS, Lonza, Basel, Switzerland). Then the fragments were enzymatically digested by 1500 U/mL collagenase (Sigma-Aldrich, Darmstadt, Germany) in DMEM/F12 medium for 2 h at 37 °C. After digestion, the cells were centrifuged, and cultured with DMEM/F12, containing the GlutaMAX supplement (Thermo Fisher Scientific, Waltham, MA, USA), 10% fetal bovine serum (Sigma-Aldrich, Darmstadt, Germany), 1% penicillin/streptomycin (Lonza, Basel, Switzerland), and 1% amphotericin B (Biochron GmbH, Berlin, Germany) at 37 °C in a humidified incubator. After 2 weeks of culture, JPCs were harvested for further expansion. The JPCs derived from 3 donors (two donors were 74 and one donor was 80 years old) of passage 5 were used in the experiment and culture medium was changed every other day. 4.2. Cell Seeding of β-TCP Scaffolds The β-TCP scaffolds (Curasan AG, Kleinostheim, Germany) were soaked in culture medium for 1 h in low binding polypropylene 96-well plates before cell seeding. The JPCs were detached from the culture flasks with TrypLE Express (Thermo Fisher Scientific, Waltham, MA, USA) after reaching 80% confluency and resuspended in culture medium at a concentration of 1 × 106 cells/mL. The medium was aspirated from the scaffolds and 50 µL of cell suspension (5 × 104 cells) per scaffold was added. After 2 h of incubation, additional 150 µL of culture medium was added to the cell-seeded scaffolds, resulting in 200 µL final volume. For osteogenic differentiation, JPC-seeded scaffolds were cultured with osteogenic (OB) medium containing DMEM/F12, 10% FBS, 1% penicillin/streptomycin, 1% amphotericin B, 100 µM ascorbic acid 2-phosphate, 10 mM β-glycerophosphate and 4 µM dexamethasone (Sigma-Aldrich, Darmstadt, Germany) for the indicated time periods. 4.3. Cultivation and Configuration of the Perfusion Bioreactor The double flow bioreactor (LB2, IVTech S.r.l., Ospedaletto, Italy), contains two chambers, with two flow inputs and outputs respectively (Figure 1A,B). The JPC-seeded scaffolds were placed in the upper chamber of the bioreactor on a porous nylon mesh (Merck, Darmstadt, Germany) with a pore size of 100 µm. Different set-ups of tangential and sigmoidal configurations (Figure 1A,B) with flow rates of 100 and 200 µL/min were applied (T100, T200, S100, and S200). JPC-seeded scaffolds cultured in a 24-well plate under control (CO) or osteogenic (OB) medium were used as controls for static conditions. 4.4. Cell Metabolic Activity Assay The JPC-seeded scaffolds were cultured within the bioreactor under the indicated flow rate and flow configuration. After 1, 3 and 5 days of culture, JPC-seeded scaffolds were placed in a 96-well plate and incubated with 20 µL substrate (EZ4U, Biozol, Eching, Germany) and 200 µL culture medium for 2.5 h at 37 °C in a humidified incubator. 150 µL mixture of substrate and culture medium was pipetted into a fresh well, and the absorbance at 450 nm was measured using a microplate reader (Biotek, Bad Friedrichshall, Germany). 4.5. Crystal Violet Staining and Quantification JPC-seeded scaffolds cultured under different conditions were fixed with 4% formaldehyde (Otto Fischar GmbH, Saarbrücken, Germany) for 20 min and then washed with PBS twice. 0.1% crystal violet dye (Sigma, St. Louis, MO, USA) was used to stain the fixed scaffolds for 20 min at room temperature. The scaffolds were washed with distilled water overnight on a shaker and dried at room temperature. The dye which was bound by the scaffolds was dissolved in 200 µL methanol for 30 min on a shaker. 150 µL of eluant was pipetted to a fresh well, and absorbance was measured at a wavelength of 550 nm with a microplate reader (Biotek, Bad Friedrichshall, Germany). 4.6. Scanning Electron Microscope (SEM) Analysis of JPC-Seeded Scaffolds The JPC-seeded scaffolds were fixed with 4% glutaraldehyde (Applichem, Darmstadt, Germany) in 0.1 M sodium cacodylate (Merck, Darmstadt, Germany) buffer for 30 min and washed twice with PBS. All scaffolds were dehydrated with an ascending ethanol series (50%, 70%, 80%, 90% and 100%), liquids were completely removed by the critical point drying method and sputtered with a thin gold/palladium layer. The surface of the gold/palladium coated scaffolds was visualized with a scanning electron microscope (Carl Zeiss, Oberkochen, Germany). Scaffold porosities were measured in the 200× images using the quantification tools of the ImageJ software 1.53. 4.7. Embedding and Microtome Sectioning of Embedded JPC-Seeded Scaffolds JPC-seeded scaffolds were fixed with 4% formaldehyde for 30 min, washed twice with PBS, and distilled water, respectively. Then, samples were dehydrated and degreased with an ascending ethanol series (70%, 80%, 96% and 100%) for 15 min, and xylene for 15 min, respectively. Afterwards, all samples were pre-infiltrated with acetone twice for 1h and incubated with solution A of Technovit 9100 (Kulzer, Wehrheim, Germany) overnight at −20 °C. The following day, scaffolds were embedded with nine parts of solution A and one part of solution B in a 5 mL syringe and incubated again at −20 °C overnight. Finally, the syringes containing the scaffolds were incubated at 37 °C in a water bath for 1 h. Embedded scaffolds were cut to 15 µm sections with a microtome before fluorescent cell labeling. 4.8. Fluorescent Cell Labeling with Sytox Orange Microtome sections were stained with 1:1000 Sytox orange dye (Thermo Fisher Scientific, Waltham, MA, USA) in PBS for 15 min and washed with PBS. All slices were mounted with Fluoromount-G (Thermo Fisher Scientific, CA, USA) before visualization by a fluorescent microscope (Carl Zeiss, Oberkochen, Germany). 4.9. Gene Expression Analyses by Quantitative PCR The JPC-seeded scaffolds were placed in Lysing Matrix D microtubes with ceramic beads (MP Biomedicals, Irvine, CA, USA) and lysis buffer (Macherey-Nagel, Dueren, Germany), and shredded by a FastPrep-24 device (MP Biomedicals, Irvine, CA, USA). RNA isolation from the obtained lysates of JPC-seeded scaffolds was carried out using the NucleoSpin RNA Mini kit (Macherey-Nagel, Dueren, Germany) following the manufacturer’s instructions. After RNA quantification using the Nanodrop spectral photometer (Thermo Fisher Scientific, Waltham, USA), 200 ng of RNA was synthesized to cDNA using the SuperScript VILO kit (Thermo Fisher, Darmstadt, Germany) following the manufacturer’s instructions. mRNA transcription levels were quantified by a real-time LightCycler system (Roche Diagnostics, Mannheim, Germany). DNA Master SYBR Green 1 (Roche, Mannheim, Germany) and the primer kits (Search LC, Heidelberg, Germany) for the target genes (ALPL, COL1A1, RUNX2, OCN, GAPDH) were used for the PCR reactions. 35 cycles of amplification were carried out for each mRNA. The ratio of target gene copy numbers to those of the housekeeping gene (GAPDH) were calculated. 4.10. Statistical Analysis Statistical analysis was conducted for three independent experiments using the GraphPad Prism 8.1.0 software (GraphPad, San Diego, CA, USA), and all the results were presented as means ± SD. All data were tested for normality using the Shapiro-Wilk test. Statistical analysis was performed for comparing results of different culture conditions (dynamic conditions and static condition) using one-way ANOVA followed by Tukey’s multiple comparisons tests, for comparing results of osteogenic condition to control using two-tailed Student’s t-test. p values ≤ 0.05 were considered significant. 5. Conclusions In this study, we tested a perfusion system for the simultaneous cultivation of several JPC-seeded beta-TCP scaffolds, which promotes cell proliferation and enhances osteogenic differentiation. Perfusion conditions stimulated cell growth on β-TCP scaffolds independently of the flow configuration and applied flow rates. The tangential configuration of the bioreactor seemed to up-regulate JPC gene expressions at a higher extent than the sigmoidal set-up and seems to be more suitable for the used beta-TCP constructs. Acknowledgments We thank Ernst Schweizer for helping to take SEM images. Author Contributions Conceptualization, D.A.; Methodology, W.C., S.W. and F.U.; Investigation, W.C. and S.W.; Data Curation, W.C., S.W. and D.A.; Writing—Original Draft Preparation, W.C. and D.A.; Writing—Review and Editing, W.C., D.A., F.U. and S.R.; Supervision, D.A.; Project Administration, S.R.; Funding Acquisition, W.C. and D.A. All authors have read and agreed to the published version of the manuscript. Funding This research was partially funded by the China Scholarship Council [CSC No. 201808440394]. W.C. was financed by CSC. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Medical Faculty Tübingen (approval number 618/2017BO2 from March 2019). Informed Consent Statement Written informed consent has been obtained from the patients. Data Availability Statement Obtained data for this study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic illustrations of (A) the tangential configuration and (B) the sigmoidal configuration. β-tricalcium phosphate (β-TCP) scaffolds were placed in the upper chamber of the bioreactor. (C) Position of scaffolds within the upper chamber of the bioreactor. (D) Metabolic activity of JPC-seeded scaffolds (yellow, positioned near the inlet and the outlet) under different culture conditions (static culture, tangential and sigmoidal configurations with flow rates of 100 and 200 µL/min) at day 1, 3 and 5 of in vitro cultivation. Optical density (OD) was measured at 450 nm and values are given as means ± standard deviation (SD). Results were compared using one-way ANOVA followed by Tukey’s multiple comparisons tests, the asterisk character reflects different p-values (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 (n = 3 donors)). Figure 2 Crystal violet staining for the visualization and quantitative analysis of cell distribution within β-TCP scaffolds. (A) JPC-colonized scaffolds cultured under the indicated conditions (static culture, perfusion culture of tangential and sigmoidal configuration with flow rates of 100 and 200 µL/min) were stained with crystal violet dye at day 1, 3, 5 and 10 of in vitro cultivation. (B) Crystal violet staining was dissolved from stained scaffolds and optical density (OD) values were measured at a wavelength of 550 nm. The OD values are given as means ± SD and compared using one-way ANOVA followed by Tukey’s multiple comparisons tests (* p < 0.05, *** p < 0.001, **** p < 0.0001 (n = 3 donors)). Figure 3 SEM micrographs of JPC-seeded scaffolds cultured for (A) 1, (B) 3 and (C) 5 days under the indicated conditions in different magnifications (40×, 200×, 500× and 2000×). Scale bars are 1 mm, 100 µm, 20 µm and 20 µm respectively. Representative images of three independent experiments (n = 3 donors with one experiment for each donor) are shown. (D) Pore areas in the 200× images were quantified with ImageJ software (red columns = day 1, green columns = day 3, blue columns = day 5). The porosity of JPCs-colonized scaffolds was calculated by the ratio of the total pore area to the whole area of the scaffolds. The ratios are given as means ± SD and compared using one-way ANOVA followed by Tukey’s multiple comparisons tests (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 (n = 3 donors)). Figure 4 Visualization of cells in sections of PMMA-embedded scaffolds by Sytox orange nuclear staining. (A) Sytox orange staining was performed on sections of Technovit 9100 embedded JPC-seeded scaffolds that were cultured under the indicated conditions for 5 or 10 days. Bright field images with 1.25× magnification are given. White and yellow arrows point to the top and the bottom of the scaffolds respectively. Images taken with a 10-fold objective represent the area of rectangular box in images taken with a 1.25-fold objective. Scale bars represents 1 mm (1.25× magnification) and 100 µm (10× magnification) respectively. (B) Integrated densities (IntDen) in sections with 1.25 magnification at day 5 and 10 were quantified by the ImageJ software. Mean fluorescence intensities are shown as a ratio of IntDen to the total area of sections. Mean fluorescence intensity values are given as means ± SD and compared using one-way ANOVA followed by Tukey’s multiple comparisons tests (** p < 0.01, *** p < 0.001 (n = 3 donors)). Figure 5 Gene expression levels of alkaline phosphatase (ALPL) in JPC-seeded β-TCP scaffolds after 5 days, 10 days and 15 days of osteogenic differentiation under static or perfusion conditions. mRNA expression levels under (A) tangential and (B) sigmoidal configuration were quantified and normalized to the housekeeping gene GAPDH. To calculate induction indices, gene expression levels were normalized to untreated (co) JPCs or osteogenically induced (ob) under static conditions. Induction indices of tangential (T) and sigmoidal (S) configuration after (C) 5 days, (D) 10 days and (E) 15 days of culture were calculated. The gene expression and induction values are given as means ± SD. Gene expression levels under different culture conditions (dynamic conditions and static condition) are compared using one-way ANOVA followed by Tukey’s multiple comparisons tests. To compare levels of osteogenic to control condition and induction values between T and S configuration condition, two-tailed Student’s t-test was used (* p < 0.05, ** p < 0.01, (n = 3 donors)). Figure 6 Gene expression levels of collagen 1α1 (COL1A1) in JPC-seeded β-TCP scaffolds after 5, 10 and 15 days of osteogenic differentiation under static or perfusion conditions. mRNA expression levels under (A) tangential and (B) sigmoidal configuration were quantified and normalized to the housekeeping gene GAPDH. To calculate induction indices, gene expression levels were normalized to untreated (co) or osteogenically induced (ob) JPCs under static condition. Induction indices of tangential (T) and sigmoidal (S) configuration after (C) 5 days, (D) 10 days and (E) 15 days of culture were calculated. The gene expression and induction values are given as means ± SD. Gene expression levels under different culture conditions (dynamic and static conditions) were compared using one-way ANOVA followed by Tukey’s multiple comparisons tests. For comparing levels of osteogenic condition to control and induction values between T and S, two-tailed Student’s t-test was used (* p < 0.05, ** p < 0.01, *** p < 0.001 (n = 3 donors)). Figure 7 Gene expression levels of runt-related transcription factor 2 (RUNX2) in JPC-seeded β-TCP scaffolds after 5, 10 and 15 days of osteogenic differentiation under static or perfusion conditions. mRNA expression levels under (A) tangential and (B) sigmoidal configuration were quantified and normalized to the housekeeping gene GAPDH. To calculate induction indices, gene expression levels were normalized to untreated (co) or osteogenically induced (ob) JPCs under static condition. Induction indices of tangential (T) and sigmoidal (S) configuration after (C) 5 days, (D) 10 days and (E) 15 days of culture were calculated. The gene expression and induction values are given as means ± SD. Gene expression levels under different culture conditions (dynamic and static condition) are compared using one-way ANOVA followed by Tukey’s multiple comparisons tests. For comparing levels of osteogenic condition to control and induction values between T and S, two-tailed Student’s t-test is using (* p < 0.05, ** p < 0.01, *** p < 0.001 (n = 3 donors)). Figure 8 Relative gene expression levels of osteocalcin (OCN) in JPCs cultured within β-TCP scaffolds after 5, 10 and 15 days of osteogenic differentiation under the indicated conditions. mRNA expression levels under (A) tangential and (B) sigmoidal configuration were quantified and normalized to the housekeeping gene GAPDH. To calculate induction indices, gene expression levels were normalized to untreated (co) or osteogenically induced (ob) JPCs under static condition. Induction indices of tangential (T) and sigmoidal (S) configuration after (C) 5 days, (D) 10 days and (E) 15 days of culture were calculated. The gene expression and induction values are given as means ± SD. Gene expression levels under different culture conditions (dynamic conditions and static condition) were compared using one-way ANOVA followed by Tukey’s multiple comparisons tests. For comparing levels of osteogenic condition to control and induction values between T and S, two-tailed Student’s t-test is using (* p < 0.05, ** p < 0.01, *** p < 0.001 (n = 3 donors)). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Sun J.S. Chen P.Y. Tsuang Y.H. Chen M.H. Chen P.Q. Vitamin-D binding protein does not enhance healing in rat bone defects: A pilot study Clin. Orthop. Relat. Res. 2009 467 3156 3164 10.1007/s11999-009-0864-0 19418105 2. Huey D.J. Hu J.C. Athanasiou K.A. Unlike bone, cartilage regeneration remains elusive Science 2012 338 917 921 10.1126/science.1222454 23161992 3. Cartmell S.H. Porter B.D. Garcia A.J. Guldberg R.E. Effects of medium perfusion rate on cell-seeded three-dimensional bone constructs in vitro Tissue Eng. 2003 9 1197 1203 10.1089/10763270360728107 14670107 4. Leclerc E. David B. Griscom L. Lepioufle B. Fujii T. Layrolle P. Legallaisa C. Study of osteoblastic cells in a microfluidic environment Biomaterials 2006 27 586 595 10.1016/j.biomaterials.2005.06.002 16026825 5. Alexander D. Hoffmann J. Munz A. Friedrich B. Geis-Gerstorfer J. Reinert S. Analysis of OPLA scaffolds for bone engineering constructs using human jaw periosteal cells J. Mater. Sci. Mater. Med. 2008 19 965 974 10.1007/s10856-007-3351-8 18158613 6. Chen C.Y. Ke C.J. Yen K.C. Hsieh H.C. Sun J.S. Lin F.H. 3D porous calcium-alginate scaffolds cell culture system improved human osteoblast cell clusters for cell therapy Theranostics 2015 5 643 655 10.7150/thno.11372 25825603 7. Ardjomandi N. Huth J. Stamov D.R. Henrich A. Klein C. Wendel H.P. Reinert S. Alexander D. Surface biofunctionalization of beta-TCP blocks using aptamer 74 for bone tissue engineering Mater. Sci. Eng. C Mater. Biol. Appl. 2016 67 267 275 10.1016/j.msec.2016.05.002 27287122 8. Filipowska J. Reilly G.C. Osyczka A.M. A single short session of media perfusion induces osteogenesis in hBMSCs cultured in porous scaffolds, dependent on cell differentiation stage Biotechnol. Bioeng. 2016 113 1814 1824 10.1002/bit.25937 26806539 9. Liu Y. Chan J.K. Teoh S.H. Review of vascularised bone tissue-engineering strategies with a focus on co-culture systems J. Tissue Eng. Regen. Med. 2015 9 85 105 10.1002/term.1617 23166000 10. Rouwkema J. Rivron N.C. van Blitterswijk C.A. Vascularization in tissue engineering Trends Biotechnol. 2008 26 434 441 10.1016/j.tibtech.2008.04.009 18585808 11. Kanczler J.M. Oreffo R.O. Osteogenesis and angiogenesis: The potential for engineering bone Eur. Cell Mater. 2008 15 100 114 10.22203/eCM.v015a08 18454418 12. Wu W. Le A.V. Mendez J.J. Chang J. Niklason L.E. Steinbacher D.M. Osteogenic performance of donor-matched human adipose and bone marrow mesenchymal cells under dynamic culture Tissue Eng. Part A 2015 21 1621 1632 10.1089/ten.tea.2014.0115 25668104 13. Nam J. Perera P. Rath B. Agarwal S. Dynamic regulation of bone morphogenetic proteins in engineered osteochondral constructs by biomechanical stimulation Tissue Eng. Part A 2013 19 783 792 10.1089/ten.tea.2012.0103 23198877 14. Zhang Z.Y. Teoh S.H. Chong W.S. Foo T.T. Chng Y.C. Choolani M. Chan J. A biaxial rotating bioreactor for the culture of fetal mesenchymal stem cells for bone tissue engineering Biomaterials 2009 30 2694 2704 10.1016/j.biomaterials.2009.01.028 19223070 15. Bruder S.P. Kurth A.A. Shea M. Hayes W.C. Jaiswal N. Kadiyala S. Bone regeneration by implantation of purified, culture-expanded human mesenchymal stem cells J. Orthop. Res. 1998 16 155 162 10.1002/jor.1100160202 9621889 16. Nguyen B.N. Ko H. Moriarty R.A. Etheridge J.M. Fisher J.P. Dynamic Bioreactor Culture of High Volume Engineered Bone Tissue Tissue Eng. Part A 2016 22 263 271 10.1089/ten.tea.2015.0395 26653703 17. Ravichandran A. Liu Y. Teoh S.H. Review: Bioreactor design towards generation of relevant engineered tissues: Focus on clinical translation J. Tissue Eng. Regen. Med. 2018 12 e7 e22 10.1002/term.2270 28374578 18. Rauh J. Milan F. Gunther K.P. Stiehler M. Bioreactor systems for bone tissue engineering Tissue Eng. Part B Rev. 2011 17 263 280 10.1089/ten.teb.2010.0612 21495897 19. Eggli P.S. Muller W. Schenk R.K. Porous hydroxyapatite and tricalcium phosphate cylinders with two different pore size ranges implanted in the cancellous bone of rabbits. A comparative histomorphometric and histologic study of bony ingrowth and implant substitution Clin. Orthop. Relat. Res. 1988 232 127 138 10.1097/00003086-198807000-00017 20. Bohner M. Santoni B.L.G. Dobelin N. Beta-tricalcium phosphate for bone substitution: Synthesis and properties Acta Biomater. 2020 113 23 41 10.1016/j.actbio.2020.06.022 32565369 21. Dai J. Umrath F. Reinert S. Alexander D. Jaw Periosteal Cells Seeded in Beta-Tricalcium Phosphate Inhibit Dendritic Cell Maturation Biomolecules 2020 10 887 10.3390/biom10060887 32531991 22. Weber M. Umrath F. Steinle H. Schmitt L.F. Yu L.T. Schlensak C. Wendel H.P. Reinert S. Alexander D. Avci-Adali M. Influence of Human Jaw Periosteal Cells Seeded beta-Tricalcium Phosphate Scaffolds on Blood Coagulation Int. J. Mol. Sci. 2021 22 9942 10.3390/ijms22189942 34576103 23. Ardjomandi N. Henrich A. Huth J. Klein C. Schweizer E. Scheideler L. Rupp F. Reinert S. Alexander D. Coating of ss-tricalcium phosphate scaffolds-a comparison between graphene oxide and poly-lactic-co-glycolic acid Biomed. Mater. 2015 10 045018 10.1088/1748-6041/10/4/045018 26238604 24. Brauchle E. Carvajal Berrio D. Rieger M. Schenke-Layland K. Reinert S. Alexander D. Raman Spectroscopic Analyses of Jaw Periosteal Cell Mineralization Stem Cells Int. 2017 2017 1651376 10.1155/2017/1651376 28232849 25. Danalache M. Kliesch S.M. Munz M. Naros A. Reinert S. Alexander D. Quality Analysis of Minerals Formed by Jaw Periosteal Cells under Different Culture Conditions Int. J. Mol. Sci. 2019 20 4193 10.3390/ijms20174193 26. Barthes J. Ozcelik H. Hindie M. Ndreu-Halili A. Hasan A. Vrana N.E. Cell microenvironment engineering and monitoring for tissue engineering and regenerative medicine: The recent advances Biomed Res. Int. 2014 2014 921905 10.1155/2014/921905 25143954 27. Gandhi J.K. Kao S.W. Roux B.M. Rodriguez R.A. Tang S.J. Fisher J.P. Cheng M.H. Brey E.M. Perfusion Bioreactor Culture of Bone Marrow Stromal Cells Enhances Cranial Defect Regeneration Plast. Reconstr. Surg. 2019 143 993e 1002e 10.1097/PRS.0000000000005529 31033820 28. Ishikawa K. Miyamoto Y. Tsuchiya A. Hayashi K. Tsuru K. Ohe G. Physical and Histological Comparison of Hydroxyapatite, Carbonate Apatite, and beta-Tricalcium Phosphate Bone Substitutes Materials 2018 11 1993 10.3390/ma11101993 29. Williams J.L. Iannotti J.P. Ham A. Bleuit J. Chen J.H. Effects of fluid shear stress on bone cells Biorheology 1994 31 163 170 10.3233/BIR-1994-31204 8729478 30. McCoy R.J. O’Brien F.J. Influence of shear stress in perfusion bioreactor cultures for the development of three-dimensional bone tissue constructs: A review Tissue Eng. Part B Rev. 2010 16 587 601 10.1089/ten.teb.2010.0370 20799909 31. Wittkowske C. Reilly G.C. Lacroix D. Perrault C.M. In Vitro Bone Cell Models: Impact of Fluid Shear Stress on Bone Formation Front. Bioeng. Biotechnol. 2016 4 87 10.3389/fbioe.2016.00087 27896266 32. Gurkan U.A. Akkus O. The mechanical environment of bone marrow: A review Ann. Biomed. Eng. 2008 36 1978 1991 10.1007/s10439-008-9577-x 18855142 33. Hoemann C.D. El-Gabalawy H. McKee M.D. In vitro osteogenesis assays: Influence of the primary cell source on alkaline phosphatase activity and mineralization Pathol. Biol. 2009 57 318 323 10.1016/j.patbio.2008.06.004 18842361 34. Farley J.R. Wergedal J.E. Baylink D.J. Fluoride directly stimulates proliferation and alkaline phosphatase activity of bone-forming cells Science 1983 222 330 332 10.1126/science.6623079 6623079 35. Mygind T. Stiehler M. Baatrup A. Li H. Zou X. Flyvbjerg A. Kassem M. Bunger C. Mesenchymal stem cell ingrowth and differentiation on coralline hydroxyapatite scaffolds Biomaterials 2007 28 1036 1047 10.1016/j.biomaterials.2006.10.003 17081601 36. Zeng L. Wei J. Han D. Liu H. Liu Y. Zhao N. Sun S. Wang Y. Feng H. Functional analysis of novel RUNX2 mutations in cleidocranial dysplasia Mutagenesis 2017 32 437 443 10.1093/mutage/gex012 28505335 37. Jung Y.J. Bae H.S. Ryoo H.M. Baek S.H. A novel RUNX2 mutation in exon 8, G462X, in a patient with Cleidocranial Dysplasia J. Cell Biochem. 2018 119 1152 1162 10.1002/jcb.26283 28703881

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==== Front Nanomaterials (Basel) Nanomaterials (Basel) nanomaterials Nanomaterials 2079-4991 MDPI 10.3390/nano12091426 nanomaterials-12-01426 Article Synthesis and Fluorescent Properties of Multi-Functionalized C70 Derivatives of C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 Luan Ke 1 Wang Lu 1 https://orcid.org/0000-0002-8196-8229 Xie Fang-Fang 1 Chen Bin-Wen 1 Chen Zuo-Chang 1 https://orcid.org/0000-0002-8588-1825 Deng Lin-Long 2* Xie Su-Yuan 1 Zheng Lan-Sun 1 Meziani Mohammed Jaouad Academic Editor 1 State Key Laboratory for Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China; luanke9411@163.com (K.L.); 20520201151919@stu.xmu.edu.cn (L.W.); fangfangxie0707@163.com (F.-F.X.); cbw15959235525@163.com (B.-W.C.); zcchem@126.com (Z.-C.C.); syxie@xmu.edu.cn (S.-Y.X.); lszheng@xmu.edu.cn (L.-S.Z.) 2 Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen 361005, China * Correspondence: denglinlong@xmu.edu.cn 22 4 2022 5 2022 12 9 142629 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Due to the partially reduced π-conjugation of the fullerene cage, multi-functionalized fullerene derivatives exhibit remarkable fluorescent properties compared to pristine fullerenes, which have high potential for application in organic light-emitting diodes (OLEDs). In this study two multi-functionalized C70 derivatives, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2, with excellent fluorescence properties, were designed and synthesized. Compared with C70(OCH3)10 containing a single kind of functional group, both the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 exhibited enhanced fluorescence properties with blue fluorescence emission. The fluorescence quantum yields of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were 1.94% and 2.30%, respectively, which were about ten times higher than that of C70(OCH3)10. The theoretical calculations revealed that the multi-functionalization of the C70 increased the S1–T1 energy gap, reducing the intersystem crossing efficiency, resulting in the higher fluorescence quantum yield of the C70 derivatives. The results indicate that multi-functionalization is a viable strategy to improve the fluorescence of fullerene derivatives. fullerene multi-functionalization fluorescence ==== Body pmc1. Introduction Fluorescence studies on fullerenes and their derivatives have attracted great interest from researchers [1,2,3,4,5,6,7,8,9,10,11,12,13], who can not only offer vital information on the excited electronic structures of fullerenes and their derivatives, but can also assess their potential applications in organic electronic devices [14,15]. Due to the renowned electron-accepting ability and small reorganization energy of symmetric fullerenes [16,17], the transition from S0 to S1 is forbidden, and the intersystem crossing (ISC) efficiency from S1 to T1 is very high (close to 100%) [18]. Pristine fullerenes exhibit poor fluorescence properties, such as low-fluorescence quantum yields (Φ of ca. 0.03% for C60 and ca. 0.06% for C70 in toluene) and short fluorescence lifetimes (τ of 1.2 ns for C60 and 0.67 ns for C70) [19,20,21,22]. The functionalization of fullerene is a valid way to increase electronic transition forbiddance and the S1–T1 energy gap by lowering the symmetry of the fullerene. However, the fluorescence of mono-, bis-, and tris-adducts of fullerene derivatives is still extremely weak, since these adducts cannot effectively destroy the symmetric structure of fullerenes [23]. Multi-functionalization with higher adducts has been proven to be an effective methodology to fine-tune the fluorescence properties of fullerene derivatives. For instance, Rubin et al. reported a hexa-adduct of C60 that exhibited much-improved fluorescence intensity [24]. Multi-functionalized C60 derivatives with excellent fluorescence properties were prepared by Nakamura et al. [25,26,27]. Compared with the studies on the fluorescence properties of C60 derivatives, there are few studies on the fluorescence properties of C70 derivatives [28]. Herein, we report the synthesis and fluorescence properties of two multi-functionalized C70 derivatives, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2. By carefully controlling the molar ratio of the reactants, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 can be readily synthesized from C70(OCH3)10 by using the Bingel–Hirsch reaction with high selectivity. Due to the reduced π-conjugated system of C70, the fluorescence quantum yield of C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 was about ten times higher than that of C70(OCH3)10. The results provide a method for synthesizing fullerene derivatives with excellent fluorescence, offering valuable materials for organic light-emitting diodes. 2. Materials and Methods 2.1. Materials and Synthesis C70, iodine monochloride (ICl), silver perchlorate, diethyl bromomalonate, and 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) were purchased from commercial suppliers and used as received without further purification. Solvents were distilled and dried by standard procedures. C70Cl10 and C70(OCH3)10 were prepared according to the procedure in the literature [28,29]. C70(OCH3)10[C(COOEt)2]: Diethyl bromomalonate (12 mg, 0.05 mmol) and DBU (16 mg, 0.1 mmol) were added to a solution of C70(OCH3)10 (58 mg, 0.05 mmol) in anhydrous toluene (50 mL). The mixture was stirred overnight under atmosphere at room temperature. The solvent was removed under reduced pressure and the crude product was purified by column chromatography over silica gel with toluene/acetate (10:1) as the eluents to produce C70(OCH3)10[C(COOEt)2] as a pale-yellow solid (22 mg, 33%). 1H NMR (500 MHz, CDCl3, ppm): δ 4.21 (q, J = 7.0 Hz, 4H), 3.98 (s, 6H), 3.93 (s, 12H), 3.86 (s, 6H), 3.75 (s, 6H), and 1.22 (t, J = 7.0 Hz, 6H). 13C NMR (500 MHz, CDCl3, ppm): δ 163.56, 153.40, 153.07, 151.78, 151.29, 150.78, 150.73, 149.91, 149.40, 148.90, 148.54, 148.42, 148.24, 148.22, 148.11, 147.88, 147.79, 146.61, 146.49, 146.13, 145.41, 145.12, 143.71, 142.96, 139.00, 138.83, 138.58, 137.46, 135.93, 134.20, 129.04, 128.23, 86.18, 81.21, 81.03, 80.81, 80.69, 67.79, 65.89, 63.10, 56.18, 56.11, 55.94, 55.91, 55.85, 43.47, and 14.03. ESI-FT-ICR-HRMS C87H40O14 [M+Na]+ m/z calculated 1331.2310 found 1331.2311. The C70(OCH3)10[C(COOEt)2]2: Diethyl bromomalonate (48 mg, 0.2 mmol) and DBU (60 mg, 0.4 mmol) were added to a solution of C70(OCH3)10 (58 mg, 0.05 mmol) in anhydrous toluene (50 mL). The mixture was stirred overnight under atmosphere at room temperature. The solvent was removed under reduced pressure and the crude product was purified by column chromatography over silica gel with toluene/acetate (5:1) as the eluents to afford C70(OCH3)10[C(COOEt)2]2 as a light-yellow solid (29 mg, 39%). 1H NMR (500 MHz, CDCl3, ppm): δ 4.33 (m, 8H), 4.00–3.77 (m, 30H), and 1.38–1.30 (m, 12H). 13C NMR (500 MHz, CDCl3, ppm): δ 163.70, 163.67, 163.64, 163.21, 154.21, 153.22, 151.89, 151.80, 151.39, 151.34, 150.58, 150.33, 150.00, 149.62, 149.02, 148.90, 148.59, 148.31, 147.83, 147.53, 147.24, 146.91, 146.62, 146.52, 146.44, 146.30, 145.85, 145.60, 145.30, 145.26, 145.01, 144.60, 144.47, 143.67, 142.71, 139.95, 139.66, 139.12, 138.89, 138.14, 137.77, 137.52, 136.59, 136.24, 135.58, 134.38, 133.50, 130.01, 85.49, 84.51, 81.06, 80.94, 80.86, 80.80, 80.76, 80.70, 67.89, 67.80, 63.10, 63.07, 62.94, 62.88, 55.97, 55.93, 55.87, 55.79, 55.71, 55.68, 55.20, 43.44, 41.00, and 14.06. ESI-FT-ICR-HRMS C94H50O18 [M+Na]+ m/z calculated 1490.3847 found 1490.2916. 2.2. Characterization 1H NMR, 13C NMR, and 2D NMR spectra were recorded using Bruker AVⅢ500 spectrometers (Bruker, Billerica, MA, USA). High-resolution mass spectra (HRMS) were recorded on Agilent G6545XT mass spectrometers (Agilent, Santa Clara, CA, USA). UV-vis absorption spectra in solution were recorded using an Agilent Cary 5000 spectrophotometer (Agilent, Santa Clara, CA, USA). The spectra were measured in quartz glass cuvettes using spectroscopic grade solvents. Fluorescence spectroscopy in solution was carried out with an FLS980 spectrometer (Edinburgh Instruments, Livingston, UK). Time-resolved measurements were performed with a PS laser diode and a TCSPC detection unit. Single-crystal X-ray data were collected on a Rigaku Xtalab Synergy diffractometer (Rigaku, Tokyo, Japan). Using Olex2 [30], the initial structure was solved with the SHELX-XT structure solution program using direct method and refined with the XL refinement package using least-squares minimization. 3. Results and Discussion As shown in Scheme 1, the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were synthesized from C70(OCH3)10 by Bingel–Hirsch reaction. The deca-adduct C70 derivative C70(OCH3)10 was readily prepared by treating the C70Cl10 with anhydrous methanol in the presence of silver perchlorate. C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 can be readily synthesized with high selectivity by carefully controlling the molar ratio of the reactants. Their molecular structures were confirmed by 1H, 13C NMR spectroscopy and high-resolution mass spectrometry (Figures S1–S10). The two-dimensional correlated spectroscopy (COSY) showed that there was mutual coupling of the protons between the methyl and the methylene in the ethyl malonate of both the C70(OCH3)10[C(COOEt)2] and the C70(OCH3)10[C(COOEt)2]2 molecules (Figures S4 and S9). The structure of the C70(OCH3)10[C(COOEt)2] was unambiguously determined by X-ray crystallographic analysis (Figure 1 and Table S1). Single crystals were obtained through the slow diffusion of hexane into a toluene solution of C70(OCH3)10[C(COOEt)2]. As shown in Figure 1, all the methoxy groups were distributed on the equatorial region of the C70 cage. The malonate group was added to the pole of the C70 cage, and the ester groups were pointed in different directions to minimize the steric hindrance. In the crystalline state, the C70(OCH3)10[C(COOEt)2] molecules displayed ordered packing in all the directions of the a-, b- and c-axes. Although the single crystal of the C70(OCH3)10[C(COOEt)2]2 was not obtained, the most favorable structure of C70(OCH3)10[C(COOEt)2]2 was determined through a series of theoretical calculations (Figures S11–S13). As shown in Figure S14, the two malonate groups were distributed at the two poles of the C70 cage. Similarly, all the functionalized groups were oriented in different directions to minimize the steric hindrance. The UV-vis absorption spectra of the C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2 were measured at room temperature. As shown in Figure 2, the C70(OCH3)10 exhibited two absorption peaks at 435 and 480 nm in the visible region, and one absorption peak at 315 nm in the ultraviolet region. By contrast, there was no absorption peak in the visible region, but there was one absorption peak in the ultraviolet region (313 nm) for C70(OCH3)10[C(COOEt)2], which was slightly blue-shifted with respect to the C70(OCH3)10. Similarly, the C70(OCH3)10[C(COOEt)2]2 showed an absorption peak at 305 nm, which was further blue-shifted compared with that of the C70(OCH3)10[C(COOEt)2]. Moreover, a broad shoulder peak around 370 nm was observed for the C70(OCH3)10[C(COOEt)2]. The blue-shifting of the absorption peaks of both C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 was caused by the decrease in the π-conjugated system of the C70 cage, indicating that the energy gap between the S1 and S0 became lager. To obtain information about the photophysical properties of the C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2, we measured the steady-state fluorescence spectra of these C70 derivatives. As shown in Figure 3, the emission peak of the C70(OCH3)10 was 498 nm, with a shoulder peak at 521 nm. The major emission peak at 498 nm was ascribed to the S1→S0 transition, and the shoulder peak was ascribed to the transition involving the vibronic interactions [4,5]. The fluorescence spectra of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were rather similar. The major peaks appeared at 451 and 454 nm for the C70(OCH3)10[C(COOEt)2] and the C70(OCH3)10[C(COOEt)2]2, respectively, while the shoulder peaks were shown at 480, and 481 nm. Obviously, the fluorescence emission peaks of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were blue-shifted compared to those of the C70(OCH3)10, indicating that the Bingel–Hirsch reaction can effectively reduce the π-conjugated system of the C70 cage [21]. The fluorescence quantum yields of these fullerene derivatives were obtained with integrating spheres. The fluorescence quantum yields of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were 1.94, and 2.30%, respectively, which were about ten times higher than that of the C70(OCH3)10 (0.25%). However, the fluorescence quantum yields of both the C70(OCH3)10[C(COOEt)2] and the C70(OCH3)10[C(COOEt)2]2 were not particularly high, which made them difficult to use as fluorescent labels. The fluorescent decay profiles of the C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2 in chloroform were recorded using the time-correlated single-photon counting (TCSPC) method. The fluorescence lifetime of the C70(OCH3)10 was described by a single-exponential component with τ = 1.16 ns. However, the fluorescence lifetime of the C70(OCH3)10[C(COOEt)2] (τ = 1.99 ns) was described by double-exponential components with τ1 = 1.18 ns (70.9%) and τ2 = 3.95 ns (29.1%). Similarly, the fluorescence lifetime of the C70(OCH3)10[C(COOEt)2]2 (τ = 1.82 ns) was also described by bi-exponential components with τ1 = 1.18 ns (72.0%) and τ2 = 3.44 ns (28.0%) (Table 1). As shown in Figure 4, the fluorescence lifetimes of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were slightly longer than those of the C70(OCH3)10, which implies that the number of adducts on fullerene can influence the fluorescence lifetime of fullerene derivatives [27]. Fullerene derivatives with more adducts may have higher fluorescence quantum yields and longer fluorescence lifetimes. Therefore, multi-functionalization is a promising strategy to improve the fluorescence of fullerene derivatives. To gain insight into the mechanisms of the fluorescence enhancements, we carried out theoretical calculations. Generally, the compounds with high fluorescence quantum yields had large S1–T1 energy gaps. Furthermore, the larger S1–T1 energy gaps appeared when the excitation was more localized. As shown in Figure 5, the difference S1/S0 electronic densities of the C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2 were computed through TD-DFT. The excitations of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were similar and spatially localized in the same fragment of the molecule, which meant a large S1–T1 energy gap. However, the large spatial extension led to a small S1–T1 energy gap, as with the C70(OCH3)10. Therefore, the further functionalization of the C70(OCH3)10 increased the S1–T1 energy gap, reducing the intersystem crossing efficiency, resulting in the higher fluorescence quantum yield of the C70 derivatives. 4. Conclusions In summary, two multi-functionalized C70 derivatives, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2, were synthesized from C70(OCH3)10 by Bingel–Hirsch reaction with high selectivity. Compared with the C70(OCH3)10, the UV-vis absorption and fluorescence of both the C70(OCH3)10[C(COOEt)2] and the C70(OCH3)10[C(COOEt)2]2 were blue-shifted due to the decrease in the π-conjugated system of the C70. Moreover, the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 showed blue fluorescence, and their fluorescence quantum yield was about ten times higher than that of the C70(OCH3)10. The TD-DFT calculations indicated that the multi-functionalization of the C70 increased the S1–T1 energy gap, reducing the intersystem crossing efficiency, resulting in the higher fluorescence quantum yield of the C70 derivatives. The results reveal that multi-functionalization is an effective strategy to improve the fluorescence of fullerene derivatives, providing novel organic electronic materials for organic light-emitting diodes. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nano12091426/s1. Figure S1: 1H NMR spectrum (500 MHz, CDCl3) of C70(OCH3)10[C(COOEt)2]; Figure S2: 13C NMR spectrum (500 MHz, CDCl3) of C70(OCH3)10[C(COOEt)2]; Figure S3: ESI-FT-ICR-HRMS spectra of C70(OCH3)10[C(COOEt)2], Figure S4: COSY spectra of C70(OCH3)10[C(COOEt)2]; Figure S5: HSQC of C70(OCH3)10[C(COOEt)2]; Figure S6: 1H NMR spectrum (500 MHz, CDCl3) of C70(OCH3)10[C(COOEt)2]2; Figure S7: 13C NMR spectrum (500 MHz, CDCl3) of C70(OCH3)10[C(COOEt)2]2; Figure S8: ESI-FT-ICR-HRMS spectra of C70(OCH3)10[C(COOEt)2]2; Figure S9: COSY spectra of C70(OCH3)10[C(COOEt)2]2; Figure S10: HSQC spectra of C70(OCH3)10[C(COOEt)2]2; Table S1: Crystallographic data for C70(OCH3)10[C(COOEt)2]; Figure S11: Natural Population Analysis (NPA) charge distribution of C70(OCH3)10 (A), C70(OCH3)10[C(COOEt)2]-I (B), C70(OCH3)10[C(COOEt)2]-II (C), C70(OCH3)10[C(COOEt)2]-III (D). And C70(OCH3)10 is shown in three orientations front view, top view and bottom view (E); Figure S12: Electrostatic potentials on the 0.001 a.u. molecular surfaces of C70(OCH3)10 (A), C70(OCH3)10[C(COOEt)2] (B) and C70(OCH3)10[C(COOEt)2]2 (C), calculated at B3LYP-D3BJ/6-31G(d, p) level with toluene solvent; Figure S13: Molecular orbitals (HOMO-1, HOMO, LUMO, and LUMO+1) of C70(OCH3)10 (A), C70(OCH3)10[C(COOEt)2] (B) and C70(OCH3)10[C(COOEt)2]2 (C) calculated at B3LYP-D3BJ/6-31G(d, p) level, in toluene; Figure S14: The most favorable structure of C70(OCH3)10[C(COOEt)2]2. References [31,32,33,34,35,36,37,38,39,40] are cited in supplementary materials. Click here for additional data file. Author Contributions Investigation, writing—original draft, K.L., L.W.; data collection, K.L., L.W., F.-F.X., B.-W.C. and Z.-C.C. Conceptualization, supervision, writing—revision, L.-L.D., S.-Y.X. and L.-S.Z. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the National Nature Science Foundation of China (21721001, 92061122, and 92061204). Data Availability Statement The data presented in this study are available in the article and Supplementary Materials. Conflicts of Interest The authors declare no conflict of interest. Figures, Scheme and Table nanomaterials-12-01426-sch001_Scheme 1 Scheme 1 Synthesis of C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2. Figure 1 Crystal structure of C70(OCH3)10[C(COOEt)2]. (A) ORTEP drawing with 50% ellipsoid probability. The molecular packing along a-axis (B), b-axis (C), and c-axis (D). Figure 2 UV-vis absorption spectra of C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2 in a 1.0 × 10−5 mol/L chloroform solution at room temperature. Figure 3 Normalized steady-state fluorescence spectra of C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2 at room temperature. Figure 4 Time-resolved fluorescence decay profiles of C70(OCH3)10, C70(OCH3)10[C(COOEt)2], and C70(OCH3)10[C(COOEt)2]2. Figure 5 TD-DFT computed difference S1/S0 electronic densities of C70(OCH3)10 (A), C70(OCH3)10[C(COOEt)2] (B), and C70(OCH3)10[C(COOEt)2]2 (C). Positive and negative parts are red and blue, respectively. Each molecule is shown in three orientations: front view, side view, and top view. nanomaterials-12-01426-t001_Table 1 Table 1 Fluorescence lifetimes of C70(OCH3)10, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2. The values in parentheses represent the fractions of each kinetic lifetime. τ1 (ns) τ2 (ns) τ (ns) QY (%) C70(OCH3)10 1.16 (100%) 1.16 0.25 C70(OCH3)10[C(COOEt)2] 1.18 (70.9%) 3.95 (29.1%) 1.99 1.94 C70(OCH3)10[C(COOEt)2]2 1.18 (72.0%) 3.44 (28.0%) 1.82 2.30 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Negri F. Orlandi G. Zerbetto F. Interpretation of the vibrational structure of the emission and absorption spectra of C60 J. Chem. Phys. 1992 97 6496 6503 10.1063/1.463982 2. Van den Heuvel D.J. van den Berg G.J.B. Groenen E.J.J. Schmidt J. Holleman I. Meijer G. Lowest Excited Singlet State of C60: A Vibronic Analysis of the Fluorescence J. Phys. Chem. 1995 99 11644 11649 10.1021/j100030a004 3. Diehl M. Degen J. Schmidtke H.-H. Vibronic structure and resonance effects in the optical spectra of the fullerenes C60 and C70 J. Phys. Chem. 1995 99 10092 10096 10.1021/j100025a008 4. Lin S.-K. Shiu L.-L. Chien K.-M. Luh T.-Y. Lin T.-I. Fluorescence of fullerene derivatives at room temperature J. Phys. Chem. 1995 99 105 111 10.1021/j100001a019 5. Guldi D.M. Asmus K.-D. Photophysical Properties of Mono- and Multiply-Functionalized Fullerene Derivatives J. Phys. Chem. A 1997 101 1472 1481 10.1021/jp9633557 6. Ma B. Bunker C.E. Guduru R. Zhang X.-F. Sun Y.-P. Quantitative Spectroscopic Studies of the Photoexcited State Properties of Methano- and Pyrrolidino-[60]fullerene Derivatives J. Phys. Chem. A 1997 101 5626 5632 10.1021/jp971067k 7. Sun Y.-P. Lawson G.E. Riggs J.E. Ma B. Wang N. Moton D.K. Photophysical and Nonlinear Optical Properties of [60]Fullerene Derivatives J. Phys. Chem. A 1998 102 5520 5528 10.1021/jp9801121 8. Sun Y.-P. Ma B. Bunker C.E. Photoinduced Intramolecular n−π* Electron Transfer in Aminofullerene Derivatives J. Phys. Chem. A 1998 102 7580 7590 10.1021/jp982591+ 9. Williams R.M. Zwier J.M. Verhoeven J.W. Photoinduced Intramolecular Electron Transfer in a Bridged C60 (Acceptor)-Aniline (Donor) System; Photophysical Properties of the First “Active” Fullerene Diad J. Am. Chem. Soc. 1995 117 4093 4099 10.1021/ja00119a025 10. Guldi D.M. Prato M. Excited-State Properties of C60 Fullerene Derivatives Acc. Chem. Res. 2000 33 695 703 10.1021/ar990144m 11041834 11. Giuffreda M.G. Negri F. Orlandi G. Quantum-Chemical Modeling and Analysis of the Vibrational Structure in the Phosphorescence Spectrum of C60 J. Phys. Chem. A 2001 105 9123 9129 10.1021/jp0121769 12. Wang L. Liu B. Yu S. Yao M. Liu D. Hou Y. Cui T. Zou G. Sundqvist B. You H. Highly Enhanced Luminescence from Single-Crystalline C60·1m-xylene Nanorods Chem. Mater. 2006 18 4190 4194 10.1021/cm060997q 13. Accorsi G. Armaroli N. Taking Advantage of the Electronic Excited States of [60]-Fullerenes J. Phys. Chem. C 2010 114 1385 1403 10.1021/jp9092699 14. Hutchison K. Gao J. Schick G. Rubin Y. Wudl F. Bucky Light Bulbs:  White Light Electroluminescence from a Fluorescent C60 Adduct—Single Layer Organic LED J. Am. Chem. Soc. 1999 121 5611 5612 10.1021/ja990608b 15. Matsuo Y. Sato Y. Hashiguchi M. Matsuo K. Nakamura E. Synthesis, Electrochemical and Photophysical Properties, and Electroluminescent Performance of the Octa- and Deca(aryl)[60]fullerene Derivatives Adv. Funct. Mater. 2009 19 2224 2229 10.1002/adfm.200900021 16. Echegoyen L. Echegoyen L.E. Electrochemistry of Fullerenes and Their Derivatives Acc. Chem. Res. 1998 31 593 601 10.1021/ar970138v 17. Hiroshi I. Kiyoshi H. Tsuyoshi A. Masanori A. Seiji T. Tadashi O. Masahiro S. Yoshiteru S. The small reorganization energy of C60 in electron transfer Chem. Phys. Lett. 1996 263 545 550 10.1016/S0009-2614(96)01244-4 18. Orlandi G. Negri F. Electronic states and transitions in C60 and C70 fullerenes Photochem. Photobiol. Sci. 2002 1 289 308 10.1039/b200178k 12653466 19. Arbogast J.W. Darmanyan A.P. Foote C.S. Diederich F.N. Whetten R.L. Rubin Y. Alvarez M.M. Anz S.J. Photophysical properties of sixty atom carbon molecule (C60) J. Phys. Chem. 1991 95 11 12 10.1021/j100154a006 20. Arbogast J.W. Foote C.S. Photophysical properties of C70 J. Am. Chem. Soc. 1991 113 8886 8889 10.1021/ja00023a041 21. Kim D. Lee M. Suh Y.D. Kim S.K. Observation of fluorescence emission from solutions of C60 and C70 fullerenes and measurement of their excited-state lifetimes J. Am. Chem. Soc. 1992 114 4429 4430 10.1021/ja00037a075 22. Catalan J. Elguero J. Fluorescence of fullerenes (C60 and C70) J. Am. Chem. Soc. 1993 115 9249 9252 10.1021/ja00073a046 23. Li Z.J. Yang W.W. Gao X. A room-temperature fluorescence study of organofullerenes: Cis-1 bisadduct with unusual blue-shifted emissions J. Phys. Chem. A 2011 115 6432 6437 10.1021/jp112411h 21591712 24. Schick G. Levitus M. Kvetko L. Johnson B.A. Lamparth I. Lunkwitz R. Ma B. Khan S.I. Garcia-Garibay M.A. Rubin Y. Unusual Luminescence of Hexapyrrolidine Derivatives of C60 with Th and Novel D3-Symmetry J. Am. Chem. Soc. 1999 121 3246 3247 10.1021/ja984329k 25. Li C.Z. Matsuo Y. Nakamura E. Luminescent Bow-Tie-Shaped Decaaryl[60]fullerene Mesogens J. Am. Chem. Soc. 2009 131 17058 17059 10.1021/ja907908m 19894715 26. Matsuo Y. Tahara K. Morita K. Matsuo K. Nakamura E. Regioselective eightfold and tenfold additions of a pyridine-modified organocopper reagent to [60]fullerene Angew. Chem. Int. Ed. 2007 46 2844 2847 10.1002/anie.200604839 17340652 27. Fujita T. Matsuo Y. Nakamura E. Synthesis of Tetradeca- and Pentadeca(organo)[60]fullerenes Containing Unique Photo- and Electroluminescent π-Conjugated Systems Chem. Mater. 2012 24 3972 3980 10.1021/cm3024296 28. Lou N. Li Y. Gan L. Synthesis of C70-Based Fluorophores through Sequential Functionalization to Form Isomerically Pure Multiadducts Angew. Chem. Int. Ed. 2017 56 2403 2407 10.1002/anie.201612054 29. Kornev A.B. Peregudov A.S. Martynenko V.M. Balzarini J. Hoorelbeke B. Troshin P.A. Synthesis and antiviral activity of highly water-soluble polycarboxylic derivatives of [70]fullerene Chem. Commun. 2011 47 8298 8300 10.1039/c1cc12209f 30. Dolomanov O.V. Bourhis L.J. Gildea R.J. Howard J.A.K. Puschmann H. OLEX2: A complete structure solution, refinement and analysis program J. Appl. Crystallogr. 2009 42 339 341 10.1107/S0021889808042726 31. Sheldrick G.M. Crystal structure refinement with SHELXL Acta Crystallogr. Sect. C Struct. Chem. 2015 71 3 8 10.1107/S2053229614024218 25567568 32. Becke A.D. Density-functional exchange-energy approximation with correct asymptotic behavior Phys. Rev. A 1988 38 3098 3100 10.1103/PhysRevA.38.3098 9900728 33. Becke A.D. Density-functional thermochemistry. III. The role of exact exchange J. Chem. Phys. 1993 98 5648 5652 10.1063/1.464913 34. Lee C. Yang W. Parr R.G. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density Phys. Rev. B 1988 37 785 789 10.1103/PhysRevB.37.785 35. Grimme S. Ehrlich S. Goerigk L. Effect of the damping function in dispersion corrected density functional theory J. Comput. Chem. 2011 32 1456 1465 10.1002/jcc.21759 21370243 36. Tomasi J. Mennucci B. Cammi R. Quantum Mechanical Continuum Solvation Models Chem. Rev. 2005 105 2999 3094 10.1021/cr9904009 16092826 37. Humphrey W. Dalke A. Schulten K. VMD: Visual molecular dynamics J. Mol. Graph. 1996 14 33 38 10.1016/0263-7855(96)00018-5 8744570 38. Hirsch A. Lamparth I. Groesser T. Karfunkel H.R. Regiochemistry of Multiple Additions to the Fullerene Core: Synthesis of a Th-Symmetric Hexakis adduct of C60 with Bis(ethoxycarbonyl)methylene J. Am. Chem. Soc. 1994 116 9385 9386 10.1021/ja00099a088 39. Guillot S. Chemelli A. Bhattacharyya S. Warmont F. Glatter O. Ordered Structures in Carboxymethylcellulose−Cationic Surfactants−Copper Ions Precipitated Phases: In Situ Formation of Copper Nanoparticles J. Phys. Chem. B 2009 113 15 23 10.1021/jp805613n 19072022 40. Ovchinnikova N.S. Goryunkov A.A. Khavrel P.A. Belov N.M. Apenova M.G. Ioffe I.N. Yurovskaya M.A. Troyanov S.I. Sidorov L.N. Kemnitz E. Unexpected fullerene dimerizationvia [5,6]-bond upon functionalization of Cs-C70(CF3)8 by the Bingel reaction Dalton Trans. 2011 40 959 965 10.1039/C0DT00777C 21152554

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091088 animals-12-01088 Review An Outstanding Role of Adipose Tissue in Canine Stem Cell Therapy https://orcid.org/0000-0002-1169-2060 Prišlin Marina 1 Vlahović Dunja 2 Kostešić Petar 2 Ljolje Ivana 3 https://orcid.org/0000-0002-7318-8337 Brnić Dragan 1 Turk Nenad 2 https://orcid.org/0000-0003-1559-9020 Lojkić Ivana 1 Kunić Valentina 1 Karadjole Tugomir 2 https://orcid.org/0000-0002-6660-7089 Krešić Nina 1* Iacono Eleonora Academic Editor Merlo Barbara Academic Editor 1 Croatian Veterinary Institute, Savska Cesta 143, 10000 Zagreb, Croatia; prislin@veinst.hr (M.P.); brnic@veinst.hr (D.B.); ilojkic@veinst.hr (I.L.); kunic@veinst.hr (V.K.) 2 Faculty of Veterinary Medicine, University of Zagreb, Heinzelova 55, 10000 Zagreb, Croatia; dvlahovic@vef.unizg.hr (D.V.); kostesic@vef.hr (P.K.); turk@vef.unizg.hr (N.T.); ktugomir@vef.unizg.hr (T.K.) 3 Veterinary Clinic for Small Animals Buba, Dore Pfanove 11, 10000 Zagreb, Croatia; ivana.ljolje@gmail.com * Correspondence: lemo@veinst.hr 22 4 2022 5 2022 12 9 108818 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary Throughout history, the role of adipose tissue has changed for humans, and regarding canines: the role has changed from connective tissue to restoration of physiological functions. The adipose tissue cells have extraordinary mechanisms of healing tissue function, and the most outstanding component of adipose tissue discovered are mesenchymal stem cells. It has been almost fifteen years since their discovery in canine adipose tissue. Since then, numerous studies have investigated the possibilities of adipose-derived mesenchymal stem cells in treating various canine diseases. This review summarised the progress of confirming the therapeutic role of adipose tissue components, focusing on stem cells as the most researched and with the highest potential in enabling a better quality of life for canines. Abstract Adipose tissue, previously known as connective tissue with a role in energy storage, is currently changing the course of treatments in veterinary medicine. Recent studies have revealed one particularly impressive function among all the newly discovered functions of adipose tissue. The interactive cells hosted by adipose tissue, the stromal vascular fraction (SVF), and their role in treating numerous diseases have provided a prospective course of research with positive outcomes in regenerative veterinary medicine (RVM). This review describes the main features of adipose tissue, emphasizing an eclectic combination of cells within the SVF and its thus far researched therapeutic possibilities in canine RVM. An afterwards focus is on a highly researched component of the SVF, adipose-derived mesenchymal stem cells (ASCs), which were shown to have an extraordinary impact relying on several proposed mechanisms of action on mitigating pathologies in canines. Furthermore, ASC therapy showed the most significant results in the orthopaedics field and in neurology, dermatology, ophthalmology, gastroenterology, and hepatology, which elevates the possibilities of ASC therapy to a whole new level. Therefore, this review article aims to raise awareness of the importance of research on cellular components, within abundant and easily accessible adipose tissue, in the direction of regenerative therapy in canines, considering the positive outcomes so far. Although the focus is on the positive aspects of cellular therapy in canines, the researchers should not forget the importance of identifying the potential negative aspects within published and upcoming research. Safe and standardized treatment represents a fundamental prerequisite for positively impacting the lives of canine patients. canine adipose-derived mesenchymal stem cells stem cell therapy regenerative veterinary medicine stromal vascular fraction adipose tissue ==== Body pmc1. Introduction Adipose tissue (AT) was once considered to be the only connective tissue involved in energy storage. Currently, recognition of AT function is beyond simple fat storage, and is well known as a metabolic and endocrine organ [1,2,3]. Consequently, this review aims to raise awareness on the importance of research on cellular components, within abundant and easily accessible adipose tissue, in the direction of regenerative therapy in canines, considering positive outcomes so far and failures of current treatment options. Today it is accepted that adipose tissue is of mesodermal origin. However, there is evidence that craniofacial adipose deposits may originate from the neural crest [4]. Consequently, the origins of adipose tissue are complex and have to be fully explored [5]. Adipose tissue is crucial in maintaining lipid and glucose homeostasis [6]. Endocrine role turnover appears with the possibility of producing oestrogen, resistin, and leptin [1,7] and regulates food intake, body mass, reproductive functioning, foetal growth, pro-inflammatory immune responses, angiogenesis, and lipolysis [8]. Furthermore, it was discovered that AT secretes pro-inflammatory chemokines and cytokines such as interleukins (IL) 1, IL 6, IL 8, tumour necrosis factor-alpha (TNF-α), as well as proteins with a role in lipid metabolism, in vascular haemostasis or the complement system. The mechanism of action of those proteins may be autocrine, paracrine, or distant from AT [9]. To date, several AT types are identified, i.e., white (WAT), brown (BAT), and beige (BGAT) distributed in various anatomical parts throughout the organism [6]. Adult canines contain AT located mainly in subcutaneous and visceral depots [10]. In regenerative veterinary medicine (RVM), AT from the periovarian area, ligament falciform, and subcutaneous area is generally used. It can also be easily obtained during elective surgeries such as ovariotomy and gastropexy where AT is collected as medical waste (Figure 1). 2. Adipocytes—The Main Compound of AT Adipocytes are the main compounds of AT and can exist in almost every organism structure. They occur individually or in small groups scattered throughout the connective tissue. Loose connective tissue contains adipocytes or clusters of multiple cells, but the tissue is referred to as AT when the fat cells outnumber other cell types [11]. WAT cells are formed soon after birth, and their main purpose is to store triglycerides. The formation of adipocytes starts with mesenchymal stem cells turning into adipoblasts which further differentiate into pre-adipocytes. After pre-adipocytes reach growth arrest, they change their appearance, accumulate triglycerides, and become mature adipocytes with lost ability of division [12]. BAT cells develop before birth and specialize in defending mammals against hypothermia [13]. The morphogenetic protein (BMP)-7 is responsible for the differentiation process of brown pre-adipocytes into BAT [14]. BAT is equipped with the metabolic machinery comprising the numerous mitochondria and the appropriate enzymes that allow fatty acids to oxidize at enhanced rates than that of WAT. In addition, the mitochondria of brown adipose tissue cells primarily generate heat rather than adenosine triphosphate (ATP) and can sustain body heat during prolonged periods of cold [15]. The last discovered and current highly researched type of adipocytes are beige orbrite. These have the characteristics of WAT and BAT cells [16]. The synthesis of BGAT is a highly investigated topic in diabetes and metabolism research [17,18]. As mentioned, AT was once viewed as a passive triglyceride depot, but AT is now known as a complex tissue giving residence to various interacting cells, also known as the stromal vascular fraction (SVF) [1,13]. 3. Stromal Vascular Fraction—Interacting Cells Hosted by AT SVF is an eclectic combination of cells, including adipose-derived mesenchymal stem cells (ASCs), blood cells, endothelial precursors, endothelial and smooth muscle cells, pre-adipocytes, pericytes, macrophages and adipocytes [3,19,20] (Figure 2). Although adipocytes account for >90% of AT volume, SVF predominates in overall cell number [13]. In humans, SVF cells isolated from WAT possess more hematopoietic cells, macrophages, hematopoietic progenitors, and immature cells that, together, contribute to a higher degree of plasticity than SVF cells isolated from BAT [3,21]. Isolation of SVF from AT can be obtained by mechanical disruption and enzymatic digestion (Figure 3). The AT disassociation and SVF extraction most often involve a combination of the mechanical disruption of connective tissue, followed by enzymatic digestion with collagenase [22,23]. Both procedures aim to preserve the stem cells, the vascular compartment (stromal cell niche) viability and the therapeutic benefits of SVF products [24]. However, there are differences in outcomes between these two methods. For example, enzymatic digestion provides the phenotype of individual cells, while the mechanical extraction itself preserves interaction between cells and matrix [25]. Nevertheless, enzymatic digestion is considered the “gold standard” since it provides significantly greater cell viability [26]. The tissue harvesting site also presents a challenge since it can impair SVF and ASCs viability, cellular yield and immunophenotype. Recently, Hendawy et al. (2021) found that the peri-ovarian region is the most favourable site for harvesting ASCs in dogs since it contains the highest number of viable cells per gram of AT compared to subcutaneous and falciform ligament sites and also the highest number of CD90+ cells [22]. In 2013, Astor et al. reported similar results; AT collected at the falciform location had significantly fewer viable cells per gram (VCPG) than tissue collected at the thoracic wall and inguinal sites [27]. The same authors also reported the influence of age in SVF cell viability with significantly higher VCPG in dogs up to 4.5 years old; higher VCPG was also noted in non-spayed dogs compared to spayed ones. In addition, other authors noted the significantly higher population doubling and differentiation potentials in young donors [28]. As observed, consideration of many specific factors is needed to provide the best SVF therapy solution. 3.1. Mechanism of Action The existing literature suggests that SVF achieves regeneration and healing through pro-angiogenic and immunomodulatory mechanisms, including differentiation and extracellular matrix secretion [19]. The first study reports the effectiveness of SVF therapy in dogs in 2007 [29]. The effectiveness may be due to the presence of ASCs, the vascular niche cells, and, finally, the interactions between all cells present in SVF [24]. Senesi et al. (2019) retain that the anti-inflammatory and immunoregulatory effect of SVF for osteoarthrosis is more likely than cells’ ability to differentiate in the specific cell lineage [26]. Hendawy et al. (2021) attribute the crucial effects of SVF to the presence of a sufficient number of ASCs, with preserved differentiation capacity. Because of the complex interactions between SVF and specific organs, the function of SVF in the treatment of various pathologies needs further clarification [22,26]. The mentioned mechanisms of action are elaborated in detail in the following sections of this review. 3.2. SVF Clinical Application for Various Conditions Adipose SVF injection proved helpful in the orthopaedic field because it is a favourable, minimally invasive, non-surgical alternative for treating musculoskeletal disorders [26]. Osteoarthritis of the hip joint was significantly improved 24-weeks following treatment with simultaneous intraarticular (IA) and intravenous (IV) injection of autologous adipose-derived SVF and platelet-rich plasma (PRP) [30]. Lameness and range of motion significantly improved, as well as the overall quality of life in a double-blind study of canine hip joint osteoarthritis after 30, 60 and 90 days; although the cells in this study are named ASCs, the study indicates the application of a heterogeneous population of cells, including ASCs [29]. The same research group tested dogs suffering from elbow joint osteoarthritis. The placebo control group was not included in this study, but based on their previous analysis of hip joints, the significant improvement was attributed to the IA injected AT-derived heterogeneous cell population [31]. In four canine patients diagnosed with hip dysplasia, autologous SVF acupoint injection showed marked improvement, compared with baseline results after the first week of treatment [32]. The use of allogenic SVF in degenerative joint disease of the spine in dogs revealed an increased serum level of the vascular endothelial growth factor of affected animals in the second week of treatment. In the eighth week, the levels were decreased [33]. The same study published that decreased pain and reduced lameness were noticed a few days following therapy, overall concluding the improvement of joint regeneration capacity. The lack of research in the veterinary field indicates a significant need for further investigation of SVF benefits. 4. Adipose-Derived Mesenchymal Stem Cells—An Outstanding Component of the SVF It is well known that stem cells provide tissues and organs with a fresh cellular compartment that can replace cells that have expired naturally and provide physiological balance in the organism. In addition, the expiration of cells due to natural processes or damage enables regeneration of the tissues [34]. The significant discovery of a stem cell system within AT occurred twenty years ago [35,36]. This finding raised considerable interest in the veterinary scientific community. The results were first documented in 2008 when scientists successfully isolated and fully described ASCs in canines [37] which laid the foundation for RVM. The ASCs, a subpopulation within SVF, are non-hemopoietic stem cells originating from the mesoderm [38]. What makes them intriguing for cell research and therapy, among MSC properties such as self-renewal, in vitro proliferation, non-specialization, and ability to differentiate in another type of cell, is their easy accessibility. To address AT isolated cells as ASCs, the International Society for Cellular Therapy (ISCT) and The International Federation for Adipose Therapeutics (IFATS) have provided guidelines and recommendations for the minimal essential characterization of human ASCs. The established criteria were: capacity to proliferate as adherent cells in cultures, the ability of minimal three lineages in vitro differentiation (osteogenic, chondrogenic and adipogenic) (Figure 4), phenotypical positivity for CD90, CD73, CD105 and negativity for CD14, CD34, CD45, CD11b, CD19 or CD79α [24,39]. Although scientists apply those rules for canine ASCs research, the exact criteria are still not wholly established for this species. Though, numerous studies are contributing to ASCs characterization. In this context, the investigation of these changes in surface marker expression (CD73, CD90, CD29, CD44, CD271, CD45 and CD14) has been performed through six passages, providing a timeframe the ASCs cultivated in vitro possess optimal surface marker expression for use in therapy [23]. From the moment of their discovery, ASCs features were exploited in vitro to generate sufficient cell numbers to reach therapeutic doses depending on the disease for which the ASCs are being tested; meanwhile, their properties, gene expression and surface marker expression can be heavily influenced by such manipulation. Inevitably, prolonged cultivation in vitro carries side effects in terms of affection of the characteristic ASCs membrane markers responsible for their positive impact [23]. Therefore, basic research on ASCs properties in vitro is needed to further reveal their molecular signatures. 4.1. Mechanism of Action As already well documented for MSC in general, the healing properties are probably a result of the secretion of many factors influencing the immune system, with anti-apoptotic, anti-inflammatory, chemotactic and pro-angiogenic functions [10,40,41,42]. The mechanism of action (Figure 5) operates by sending and receiving autocrine, paracrine, endocrine and intracellular signals [40]. However, the primary therapeutic effect of MSCs is paracrine signalling inducing functional changes in monocytes/macrophages, dendritic cells, T-cells, B-cells, and natural killer cells [42]. Furthermore, MSCs can transfer various molecules through the extracellular vesicles (ECV): exosomes, microvesicles, and apoptotic bodies. ECVs are vesicles produced from the plasma membrane, and carry mRNA, proteins, miRNA, and mitochondria and travel within the body [42]. Except for the two MSC mechanisms of action mentioned above, apoptosis-mediated immunomodulation and mitochondrial transfer are other possible mechanisms of MSC action [42]. 4.1.1. Immunomodulation The interaction of MSCs with the innate and adaptive immune systems usually results in the downregulation of ongoing inflammatory responses, though the immune response can also be upregulated. The MSC immunomodulation is influenced by many factors such as activation, tissue of origin, dose and time of application, and interaction with immune cells [43]. MSC immunomodulation remains yet to be elucidated; however, paracrine signalling via immunomodulatory mediators such as nitric oxide (NO), indoleamine 2,3-dioxygenase (IDO), transforming growth factor-β (TGF-β), hepatocyte growth factor (HGF), hemoxygenase (HO), IL-6 and prostaglandin E2 (PGE2) is believed to be the first stage. In addition, this may also occur through direct contact between cells [43,44,45]. Chow et al. (2017) reported that canine MSC suppressed T cell activation by TGF-b signalling pathways and adenosine signalling [46]. This finding further indicates that canine MSC, unlike human and rodent MSC, relies primarily on cyclooxygenase and TGF-b pathways for T cell suppression rather than on NO or IDO-mediated pathways. Besides suppressing T cells, MSCs suppress B cell activation and proliferation, dendritic cells maturation, inhibit NK cell proliferation and cytotoxicity, and promote regulatory T cell generation via soluble factors or cell-cell contact [44]. T cell necrosis by canine MSC is an additional mechanism of immune modulation [46]. Canine ASCs can suppress lipopolysaccharide mediated activation/maturation of canine dendritic cells (DC). The impact in vivo of such squelched DC activation would undoubtedly result in an attenuated ability to appropriately prime T cell responses. This effect would be exacerbated if the ASCs were first activated with IFNg, suggesting that the suppressive effect would be optimal in an inflammatory environment typical of autoimmune or pro-inflammatory conditions [47]. Another “immune-privileged” MSC property is their low immunogenicity attributed to low expression of MHC I, absence of co-stimulating CD80, CD86 and CD40, MHC II deficiency and whole paracrine spectrum of biomolecules and growth factors through which they establish their action [48,49,50]. Each of the mentioned pathways reflects the possibilities these cells offer to treat various disorders and organ systems. However, all aforementioned mechanisms also imply the differences between species and offer space for new acknowledgements. 4.1.2. Homing The MSCs have a remarkable ability to locate damaged tissues [3,42]. In response to chemotactic signals, MSCs reach the circulation and migrate to the site of injury, where they secrete molecules to promote regeneration. However, it is unclear which chemotactic signals guide MSCs to appropriate microenvironments [51]. The homing of MSCs is currently inefficient, and after they are systemically administered a small percentage of cells reach the target tissue [52]. The process of migration from the bloodstream to tissue involves steps for lymphocyte migration: (1) tethering and rolling, (2) activation, (3) firm adhesion, (4) transmigration or diapedesis, resulting in migration into tissue due to chemotaxis as described by Sackstein [53]. The migration of MSCs occur in response to various chemokines and growth factors, including TNF-α (tumour necrosis factor-α), IL-6, IL-8 [54]. Unlike comprehensive knowledge on blood cell homing, MSC homing remains poorly understood as tethering or rolling and transmigration. The therapy research of MSCs bears one of the most significant aims, i.e., improving their homing efficiency. MSC homing can be categorized into (1) targeted administration—administration of ASCs at or near the target tissue, (2) magnetic guidance—cells labelled with magnetic particles are directed to the organ of interest using an external magnetic field, (3) genetic modification—permanent overexpression of homing factors via viral transduction, (4) cell surface engineering—temporarily chemical engineering by enzymes or ligands, (5) in vitro priming—altering culture conditions to affect gene expression, (6) and modification of the target tissue by direct injection of homing factors, genetic modification of target tissue, scaffold implantation, or using radiotherapeutic and ultrasound techniques[52]. 4.1.3. Pro-Angiogenic and Anti-Apoptotic Mechanism of Action MSCs secrete various cytokines responsible for pro-angiogenic and anti-apoptotic effects and in doing so, MSCs enable tissue regeneration and revascularization. Soluble angiogenic factors secreted by MSCs include fibroblast growth factors, hepatocyte growth factor and the vascular endothelial growth factor. The lack of canine-specific antibodies has hampered identification of growth factors in the secretome of canine MSCs. Likely, secretomes of other species are similar to secretomes secreted by canine MSCs thus there is an idea on the secretome composition of canine MSCs based on this information [55]. Canine MSCs promote nerve growth and endothelial cell proliferation, migration and tubule formation by secretion of neurotrophic and angiogenic factors. Delfi et al., 2016 demonstrated MSC paracrine activity on nerves and blood vessels in the vicinity of the wound site. It was shown that MSC transplants promote increased neuronal function in dogs with central nervous system damage [55]. The following study by the same authors, revealed that the conditioned medium from human and canine MSCs cultures exhibited neurogenic and angiogenic effects and increased SH-SY5Y neuronal proliferation, βIII tubulin immunoreactivity, neurite outgrowth, and EA.hy926 endothelial cell proliferation, migration and the formation of endothelial tubule-like structures, to a significantly greater extent than control medium, indicating marked trophic activity [55]. Regarding anti-apoptotic action, it was shown that ASCs protect against radiation-induced dermatitis by exerting an anti-apoptotic effect through inhibition of cathepsin F (CTSF) expression. In addition, ASCs markedly attenuated radiation-induced apoptosis, downregulated CTSF and downstream pro-apoptotic proteins (Bid, BAX, and caspase 9), and upregulated anti-apoptotic proteins (Bcl-2 and Bcl-XL) [56]. 4.2. ASCs Clinical Application for Various Conditions Since their discovery, the outstanding properties of ASCs have been continuously tested in numerous diseases in dogs. The application of stem cells for therapy can be autologous; when a patient receives their cells, allogeneic therapy refers to cells derived from a donor of the same species as the receiving animal and xenogeneic therapy refers to application of donor cells of a different species. The routes of administration (Figure 6) are most often diverse, but IA, IV, and administration via acupuncture points are most frequently used, as extensively reviewed by Brondeel et al. in 2021 [57]. Clinical trials in which mesenchymal stem cells are used on dogs are available on the first registry set up for animal studies, preclinicaltrials.eu, launched in April 2018. The chronically systematic order of positive outcomes of ASCs therapy for various conditions is presented in Table 1 and a graphic summary in Figure 7. Detail description of the effects within those studies is described in the following sections. 4.2.1. Orthopaedics Therapeutic effects of autologous and allogeneic ASCs applications in orthopaedics have improved pain and lameness in dogs with osteoarthritis [57,58,60,61,64,65,67,68,69,70]. In 2018, a group of scientists described the allogeneic ASCs application on 203 dogs and concluded that IA treatment gave better results when compared with the IV treatment in the polyarthritis condition. The age proved influential as most dogs under the age of five receiving IA treatment showed good improvement [67]. In addition, the canines’ overall health and vitality are significant factors in response to the ASCs therapy. Positive therapeutic outcomes were further observed in chronic osteoarthritis (OA) of the hip and elbow joint [59,63,66]. In addition, ASCs treatment significantly improved the symptoms of hip dysplasia in 60% of treated dogs after one week [32]. This study compared the effects of SVF and ASCs therapy administered to acupuncture points and reported better results for SVF than ASCs therapy. However, it was concluded that SVF or allogeneic ASCs could be safely used as an acupoint injection for treating hip dysplasia in dogs [31]. A follow-up study highlighted the importance of cell administration before the injury becomes severe [59]. Furthermore, significant improvements following ASCs therapy of semitendinosus myopathy are documented [71,72]. 4.2.2. Neurology In dogs with chronic spinal cord injury/intervertebral disc disease, percutaneous intraspinal transplantation of allogeneic ASCs had no adverse effects or complications (infection, neuropathic pain, or worsening neurological function) during the 16-week follow-up period. In addition, three animals improved locomotion, and one animal walked without support. However, no changes in deep pain perception were observed [73]. In the most recent research on lumbosacral spinal cord injury, transplantation of allogeneic ASCs with surgery in four dogs showed significant neurological improvements with normal ambulatory ability (4/4) and urinary control (3/4) three months after the surgery and the first ASCs transplantation [76]. While in the case of acute paraplegia, epidural canine ASCs transplantation with surgical decompression contributed to faster locomotor recovery and reduced the length of post-surgery hospitalization [74]. Another successful case reported the use of cultured autologous ASCs injected bilaterally at the level of L7-S1 in the external aperture of the intervertebral foramen of degenerative lumbosacral stenosis in a canine patient [75]. 4.2.3. Dermatology The stem cell treatment also gained popularity in treating skin pathologies; systemic administration of ASCs had a positive outcome for atopic dermatitis refractory to conventional medications for six months and with no side effects [78]. The prospective role in dermatology was also shown in treating large acute skin defects when corrective surgery offers no solution, as Zubin et al. (2015) [77] reported. In addition, the healing of acute and chronic wounds in 24 dogs of different ages and breeds significantly improved in a manner of contraction and re-epithelialization in the treated group. Furthermore, histopathological findings revealed an inflammatory infiltrate decrease and the presence of multiple hair follicles on day seven after treatment with ASCs [79]. Most recently, Kaur et al. (2022) performed the first double-blinded, placebo-controlled evaluation of the efficacy of allogeneic canine ASCs to treat canine atopic dermatitis. No severe side effects were observed in any patient in this study. Furthermore, the high dose ASCs treatment proved to be efficacious in alleviating the clinical signs of atopic dermatitis until 30 days after the last subcutaneous administration of MSCs[80]. 4.2.4. Ophthalmology Reviewing ophthalmological benefits, an immune-mediated condition common in humans and canines, keratoconjunctivitis sicca (KCS), was studied. Results in canines with KCS revealed that a single infusion of ACSs into lacrimal glands of 15 dogs resulted in no side effects during 12-months follow up. Furthermore, a significant clinical improvement was observed in all patients, single administration was effective, and daily use of corticosteroids was not required [82]. In 2019, topical application into the conjunctival sac resulted in decreased expression of pro-inflammatory markers, which implies ASCs as an adjuvant therapy in treating KCS in dogs and humans. [83]. Another successful study of ASCs for KCS was reported with significant outcomes in canines where allogeneic ASCs were applied [81]. Falcao et al., in 2020, evaluated the use of sub-conjunctival applied ASCs in dogs diagnosed with deep corneal ulcers. Allogeneic ASCs therapy in 22 out of 26 dogs presented complete ulcer wound healing within 14 days, totalling 84.6%, indicating that this therapy is a simple solution to substitute surgery with satisfying results [84]. 4.2.5. Gastroenterology The ASCs therapy was also tested for currently uncurable inflammatory bowel disease (IBD); administration of a single IV ASCs infusion showed no acute reaction or side effects during the follow-up of 11 dogs. Furthermore, 9 out of 11 dogs were in clinical remission. As the primary goal of treatment is to reduce symptoms, achieve and maintain remission, and prevent complications, ASCs were well tolerated and appeared to produce clinical benefits in dogs with severe IBD [85]. 4.2.6. Hepatology Liver diseases share clinical and pathological features in humans and canines, thus, dogs may be a representative model for humans. Autologous ASCs transplantation in dogs with liver diseases significantly ameliorated liver function; decreased liver biomarkers and observed effects seem to be related to stem cells’ immunomodulatory mechanism of action [87,88]. The effects of allogenic ASCs on acute liver injury by carbon tetrachloride in dogs were investigated by Teshima et al. (2017). It was observed that serum liver enzymes decreased significantly. In the liver, the mRNA expression levels of pro-inflammatory cytokines, such as IL-1, IL-6, IL-8, and IFNγ decreased significantly, but anti-inflammatory cytokines such as IL-4 and IL-10, HGF and VEGFA, were significantly increased after the first ASCs injection. The authors suggest that allogenic ASCs ameliorate acute hepatic injury in dogs [86]. 5. The Importance of the Regulatory Considerations and Safety Aspects Using of Animal Cell-Based Products in Regenerative Therapy As demonstrated by these positive examples, the use of ASCs therapy for numerous conditions holds excellent promise and encourages more research to provide safe, effective, and quality treatment. The European Medicines Agency (EMA), 2015, published the first draft problem statement agreed by Ad Hoc Expert Group on Veterinary Novel Therapies (ADVENT), which raised questions concerning the sterility of animal-cell-based products. The conclusion, published in 2019, was that sterility assurance of the finished stem-cell product is critical in light of the fact that the product may be administered prior to final sterility result being obtained [89]. The Novel Therapies and Technologies Working Party (NTWP) of the EMA Committee for Medicinal Products for Veterinary Use is currently preparing scientific guidance on the requirements for authorization of novel therapy veterinary medicines, which involves guidelines on veterinary cell-based therapy products taking into consideration the mechanism of action, potency and clinical effects [90]. In order to implement safe new treatments for animals, the FDA published guidelines for the application and handling of animal-cell-based products, and all cell-based products require premarket review and FDA approval to be legally marketed. Precautionary steps in therapeutic use include the control of transmitting infectious agents, tumorigenicity or unintended tissue formation, immunogenicity, long-term safety, cell survival and biodistribution [91]. 6. Conclusions To conclude, while AT was once considered an energy depot, today it is well known that, among others, AT hosts components with extraordinary potential in relieving pain and treating numerous diseases. The canine SVF and ASCs treatments provide many benefits, starting with the degenerative orthopaedic pathologies, and also regenerative possibilities within other organs such as skin, bowel, and eyes. In addition, although this review focused on positive aspects of therapy in canines, the possible side effects it can carry should not be overlooked, such as the transmission of infectious agents, tumorigenicity, immunogenicity, donor selection, long-term safety, cell survival, biodistribution or ectopic tissue formation [91]. The (NTWP) of the EMA Committee for Medicinal Products for Veterinary Use is currently preparing scientific guidance on the requirements for authorization of novel therapy veterinary medicines, which involves guidelines on veterinary cell-based therapy products taking into consideration the mechanism of action, potency and clinical effects [90]. Although therapy will be available in the near future, there remains much laboratory and clinical work to undertake to better understand the complexity behind the healing mechanisms of canine ASCs. In this context, the development of regenerative veterinary medicine is essential not only for pets and their health but also for humans since canines represent an important model for human conditions. Nevertheless, it is evident that the course of research in this field is expanding, which welcomes further high quality basic, translational, and clinical research in stem cell regenerative therapy. Furthermore, in order to positively impact the lives of canine patients, adequate research for safe and standardized treatment is a fundamental prerequisite. Acknowledgments Graphical illustrations were produced by graphic designer Mirna Mrcelja. Author Contributions Conceptualization: M.P. and N.K.; writing—original draft preparation: M.P. and N.K.; writing—review and editing: M.P., D.V., P.K., I.L. (Ivana Ljolje), T.K., D.B., V.K., I.L. (Ivana Lojkić), N.T. and N.K.; visualization M.P. and N.K.; supervision: N.K. and N.T.; project administration: N.K.; funding: N.K. All authors have read and agreed to the published version of the manuscript. Funding This review article was conducted within the Installation Research Project (UIP-2019-04-2178) “Revealing the adipose-derived mesenchymal stem cell transcriptome and secretome”—SECRET funded by Croatian Science Foundation. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Adipose tissue collection during canine ovariotomy. The routine procedure commonly performed in young females presents an excellent opportunity to collect adipose tissue and store cells for future use in regenerative therapy. Figure 2 Graphical representation of the stromal vascular fraction components. Figure 3 (A,B) represent stromal vascular fraction 24 h post isolation from peri-ovarian and subcutaneous adipose tissue, seeded in T25 flask after mechanical and enzymatic disruption. Cells pointed with a red arrow are plastic adherent cells in expansion; the surrounding cells are nonadherent. Pictures were obtained with Cytosmart Lux2 (CytoSMART Technologies B.V., The Netherlands). Figure 4 (A,B) Successful differentiation of canine adipose-derived mesenchymal stem cells (ASCs) in adipocyte differentiation media. When stained with Oil O Red, accumulated lipid droplets show high-intensity red staining within the cell (A) regarding control cultivated in basal medium (B). (C,D) Canine ASCs after successful osteodifferentiation; cells were stained with substrate to detect alkaline phosphatase activity. Purple strains of canine ASCs showed activity of alkaline phosphatase (C), while cells cultivated in basal medium (negative control) (D), showing low-intensity staining. 4E-H Images of histological sections of paraffin-embedded spheroids (20×, Zeiss, Germany) of canine ASCs three-dimensional culture after successful chondrodifferentiation. ASCs spheroids were stained with Alcian blue to detect the presence of aggrecan (E,G) and with H&E (F,H). Microscopic images (20×) (A–H) were taken with Zeiss Axiovert, Carl Zeiss AG, Jena, Germany. Figure 5 Schematic representation of adipose-derived mesenchymal stem cell features explored within regenerative therapy. Figure 6 Graphical presentation of canine adipose-derived mesenchymal stem cell application strategies and routes of administration applied within available studies described in the literature. Figure 7 Pathological conditions in canines for which adipose-derived mesenchymal stem cell therapy was applied. animals-12-01088-t001_Table 1 Table 1 Studies of canine adipose-derived mesenchymal stem cells (ASCs) and stromal vascular fraction (SVF) applied in canine pathological conditions. Clinical Condition Number of Canines Included Type of Application Route of Administration Number of Cells (×106) Reference Orthopaedics Osteoarthritis of hip joints 21 Autologous SVF Intraarticular 4.2–5 Black et al. (2007) [29] Osteoarthritis of the elbow joint 14 Autologous SVF Intraarticular 3–5 Black et al. (2008) [31] Stifle joint osteoarthrosis 1 Autologous ASCs + hyaluronic acid intraarticular 1 Yoon et al. (2012) [58] Chronic osteoarthritis of the elbow joints 4 Autologous ASCs + hyaluronic acid/PRP Intraarticular 3–5 Guercio et al. (2012) [59] Osteoarthritis of hip joints 13 Autologous ASCs + PRP Intraarticular 15 Vilar et al. (2013) [60] Osteoarthritis of hip joints 18 Autologous ASCs Intraarticular 30 Cuervo et al. (2014) [61] Hip dysplasia SVF = 4 ASCs = 5 Autologous SVF or allogeneic ASCs Acupoint injection SVF = 2–5 ASCs = 0.2–0.8 Marx et al. (2014) [49] Osteoarthritis of hip joints 15 Autologous ASCs Intraarticular 15 Vilar et al. (2014) [62] Osteoarthritis of hip joints 22 Autologous SVF + PRP Intraarticular and intravenous N/A Upchurch et al. (2016) [30] Osteoarthritis of different joints 74 Allogeneic ASCs Intraarticular 12 Harman et al. (2016) [63] Surgical-induced osteoarthritis in Beagle dogs 24 ASCs and/or PRP Intraarticular 10 Yun et al. (2016) [64] Osteoarthritis of hip joints 15 Autologous ASCs Intraarticular 15 Vilar et al. (2016) [65] Osteoarthritis of the elbow joint 30 (39 elbows) Allogeneic ASCs + hyaluronic acid Intraarticular 12 ± 3.2 Kriston-Pal et al. (2017) [66] Osteoarthritis and other joint defects 203 Allogeneic ASCs Intraarticular and/or intravenous N/A Shah et al. (2018) [67] Osteoarthritis of different joints 10 Autologous ASCs Intraarticular 15–30 Srzentić Dražilov et al. (2018) [68] Osteoarthritis of the elbow joint 13 Allogeneic ASCs Intravenous 1–2/kg body weight Olsen et al. (2019) [69] Osteoarthritis of hip joints 12 (24 hips) Allogeneic ASCs Intraarticular 5 Wits et al. (2020) [70] Acute semitendinosus muscle injury 2 Autologous SVF Intramuscular and intravenous 4.7 Brown et al. (2012) [71] Semitendinosus myopathy 11 Autologous ASCs Intramuscular and intravenous N/A Gibson et al. (2017) [72] Neurology Chronic spinal cord injury 6 Allogeneic ASCs Intraspinal N/A Escalhao et al. (2017) [73] Acute thoracolumbar disc disease and spinal cord injury 22 Allogeneic ASCs Epidural 10 Bach et al. (2019) [74] Degenerative lumbosacral stenosis 1 Autologous ASCs Paravertebral and intraarticular Paravertebral = 30.6 Intraarticular = 15.3 Mrkovački et al. (2021) [75] Lumbosacral spinal cord injury 4 Allogeneic ASCs + surgery Nerve roots next to injury, intravenous and epidural Nerve roots next to injury = 5 Intravenous = 4 Epidural = N/A Chen et al. (2022) [76] Dermatology Large skin wound 1 Autologous ASCs + PRP Local dripping or spraying N/A Zubin et al. (2015) [77] Atopic dermatitis 26 Allogeneic ASCs Intravenous 1.5 Villatoro et al. (2018) [78] Acute and chronic skin wound 24 Allogeneic ASCs Intradermal 30 Enciso et al. (2020) [79] Atopic dermatitis 15 Allogeneic ASCs Subcutaneous Low dose = 0.5/kg body weight High dose = 5/kg body weight Kaur et al. (2022) [80] Ophthalmology Keratoconjunctivitis sicca 12 Allogeneic ASCs Around the lacrimal glands 5 Villatoro et al. (2015) [81] Keratoconjunctivitis sicca 15 (24 eyes) Allogeneic ASCs Intralacrimal 1 Bittencourt et al. (2016) [82] Keratoconjunctivitis sicca 22 Allogeneic ASCs Topic in the conjunctival sac 1 Sgrignoli et al. (2019) [83] Corneal wound 26 Allogeneic ASCs Sub-conjunctival 3 Falcao et al. (2020) [84] Gastroenterology Inflammatory bowel disease 11 Allogeneic ASCs Intravenous 2/kg body weight Perez-Merino et al. (2015) [85] Hepatology Acute liver injury 9 Allogeneic ASCs Peripheral vein/splenic vein 2 Teshima et al. (2017) [86] Degenerative hepatopathy 10 Autologous ASCs Portal vein 0.5/kg body weight Gardin et al. (2018) [87] Acute liver injury 6 Allogeneic ASCs Intravenous 10 Yan et al. (2019) [88] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kershaw E.E. Flier J.S. Adipose tissue as an endocrine organ J. Clin. Endocrinol. Metab. 2004 89 2548 2556 10.1210/jc.2004-0395 15181022 2. Esteve Ràfols M. Adipose tissue: Cell heterogeneity and functional diversity Endocrinol. y Nutr. (English Ed.) 2014 61 100 112 10.1016/j.endonu.2013.03.011 23834768 3. Ramakrishnan V.M. Boyd N.L. The Adipose Stromal Vascular Fraction as a Complex Cellular Source for Tissue Engineering Applications Tissue Eng.—Part B Rev. 2018 24 289 299 10.1089/ten.teb.2017.0061 28316259 4. Billon N. Iannarelli P. Monteiro M.C. Glaviuex-Pardanaud C. Richardson W.D. Kessaris N. Dani C. Dupin E. The generation of adipocytes by the neural crest Development 2007 134 2283 2292 10.1242/dev.002642 17507398 5. Trevor L.V. Riches-Suman K. Mahajan A.L. Thornton M.J. Adipose tissue: A source of stem cells with potential for regenerative therapies for wound healing J. Clin. Med. 2020 9 2161 10.3390/jcm9072161 6. Chait A. den Hartigh L.J. Adipose Tissue Distribution, Inflammation and Its Metabolic Consequences, Including Diabetes and Cardiovascular Disease Front. Cardiovasc. Med. 2020 7 22 10.3389/fcvm.2020.00022 32158768 7. Simpson E.R. Sources of estrogen and their importance J. Steroid Biochem. Mol. Biol. 2003 86 225 230 10.1016/S0960-0760(03)00360-1 14623515 8. Obradovic M. Sudar-Milovanovic E. Soskic S. Essack M. Arya S. Stewart A.J. Gojobori T. Isenovic E.R. Leptin and Obesity: Role and Clinical Implication Front. Endocrinol. (Lausanne) 2021 12 585887 10.3389/fendo.2021.585887 34084149 9. Trayhurn P. Beattie J.H. Physiological role of adipose tissue: White adipose tissue as an endocrine and secretory organ Proc. Nutr. Soc. 2001 60 329 339 10.1079/PNS200194 11681807 10. Bahamondes F. Flores E. Cattaneo G. Bruna F. Conget P. Omental adipose tissue is a more suitable source of canine Mesenchymal stem cells BMC Vet. Res. 2017 13 166 10.1186/s12917-017-1053-0 28595579 11. Eurell J.A. Van Sickle D.C. Connective and Supportive Tissues Dellmann’s Textbook of Veterinary Histology Eurell J.A. Freappier B.L. Blackwell Publishing Ames, IA, USA 2006 1 405 9780781741484 12. Otto T.C. Lane M.D. Adipose development: From stem cell to adipocyte Crit. Rev. Biochem. Mol. Biol. 2005 40 229 242 10.1080/10409230591008189 16126487 13. Cohen P. Spiegelman B.M. Cell biology of fat storage Mol. Biol. Cell 2016 27 2523 2527 10.1091/mbc.e15-10-0749 27528697 14. Tseng Y.H. Kokkotou E. Schulz T.J. Huang T.L. Winnay J.N. Taniguchi C.M. Tran T.T. Suzuki R. Espinoza D.O. Yamamoto Y. New role of bone morphogenetic protein 7 in brown adipogenesis and energy expenditure Nature 2008 454 1000 1004 10.1038/nature07221 18719589 15. Lee J.H. Park A. Oh K.J. Lee S.C. Kim W.K. Bae K.H. The role of adipose tissue mitochondria: Regulation of mitochondrial function for the treatment of metabolic diseases Int. J. Mol. Sci. 2019 20 4924 10.3390/ijms20194924 31590292 16. Wu J. Boström P. Sparks L.M. Ye L. Choi J.H. Giang A.H. Khandekar M. Virtanen K.A. Nuutila P. Schaart G. Beige adipocytes are a distinct type of thermogenic fat cell in mouse and human Cell 2012 150 366 376 10.1016/j.cell.2012.05.016 22796012 17. Bargut T.C.L. Souza-Mello V. Aguila M.B. Mandarim-De-Lacerda C.A. Browning of white adipose tissue: Lessons from experimental models Horm. Mol. Biol. Clin. Investig. 2017 31 1 13 10.1515/hmbci-2016-0051 18. Kaisanlahti A. Glumoff T. Browning of white fat: Agents and implications for beige adipose tissue to type 2 diabetes J. Physiol. Biochem. 2019 75 1 10 10.1007/s13105-018-0658-5 30506389 19. Guo J. Nguyen A. Banyard D.A. Fadavi D. Toranto J.D. Wirth G.A. Paydar K.Z. Evans G.R.D. Widgerow A.D. Stromal vascular fraction: A regenerative reality? Part 2: Mechanisms of regenerative action J. Plast. Reconstr. Aesthetic Surg. 2016 69 180 188 10.1016/j.bjps.2015.10.014 20. Bora P. Majumdar A.S. Adipose tissue-derived stromal vascular fraction in regenerative medicine: A brief review on biology and translation Stem Cell Res. Ther. 2017 8 145 10.1186/s13287-017-0598-y 28619097 21. Prunet-Marcassus B. Cousin B. Caton D. André M. Pénicaud L. Casteilla L. From heterogeneity to plasticity in adipose tissues: Site-specific differences Exp. Cell Res. 2006 312 727 736 10.1016/j.yexcr.2005.11.021 16386732 22. Hendawy H. Uemura A. Ma D. Namiki R. Samir H. Ahmed M.F. Elfadadny A. El-husseiny H.M. Chieh-jen C. Tanaka R. Tissue harvesting site effect on the canine adipose stromal vascular fraction quantity and quality Animals 2021 11 460 10.3390/ani11020460 33572472 23. Krešić N. Prišlin M. Vlahović D. Kostešić P. Ljolje I. Brnić D. Turk N. Musulin A. Habrun B. The expression pattern of surface markers in canine adipose-derived mesenchymal stem cells Int. J. Mol. Sci. 2021 22 7476 10.3390/ijms22147476 34299095 24. Andia I. Maffulli N. Burgos-Alonso N. Stromal vascular fraction technologies and clinical applications Expert Opin. Biol. Ther. 2019 19 1289 1305 10.1080/14712598.2019.1671970 31544555 25. van Dongen J.A. Stevens H.P. Parvizi M. van der Lei B. Harmsen M.C. The fractionation of adipose tissue procedure to obtain stromal vascular fractions for regenerative purposes Wound Repair Regen. 2016 24 994 1003 10.1111/wrr.12482 27717133 26. Senesi L. De Francesco F. Farinelli L. Manzotti S. Gagliardi G. Papalia G.F. Riccio M. Gigante A. Mechanical and enzymatic procedures to isolate the stromal vascular fraction from adipose tissue: Preliminary results Front. Cell Dev. Biol. 2019 7 88 10.3389/fcell.2019.00088 31231649 27. Astor D.E. Hoelzler M.G. Harman R. Bastian R.P. Patient factors influencing the concentration of stromal vascular fraction (SVF) for adipose-derived stromal cell (ASC) therapy in dogs Can. J. Vet. Res. 2013 77 177 182 24101793 28. Lee J. Lee K.S. Kim C.L. Byeon J.S. Gu N.Y. Cho I.S. Cha S.H. Effect of donor age on the proliferation and multipotency of canine adipose-derived mesenchymal stem cells J. Vet. Sci. 2017 18 141 148 10.4142/jvs.2017.18.2.141 27456768 29. Black L.L. Gaynor J. Gahring D. Adams C. Aron D. Harman S. Gingerich D.A. Harman R. Effect of adipose-derived mesenchymal stem and regenerative cells on lameness in dogs with chronic osteoarthritis of the coxofemoral joints: A randomized, double-blinded, multicenter, controlled trial Vet. Ther. 2007 8 272 284 18183546 30. Upchurch D.A. Renberg W.C. Roush J.K. Milliken G.A. Weiss M.L. Effects of administration of adipose-derived stromal vascular fraction and platelet-rich plasma to dogs with osteoarthritis of the hip joints Am. J. Vet. Res. 2016 77 940 951 10.2460/ajvr.77.9.940 27580105 31. Black L.L. Gaynor J. Adams C. Dhupa S. Sams A.E. Taylor R. Harman S. Gingerich D.A. Harman R. Effect of intraarticular injection of autologous adipose-derived mesenchymal stem and regenerative cells on clinical signs of chronic osteoarthritis of the elbow joint in dogs Vet. Ther. 2008 9 192 200 19003780 32. Marx C. Silveira M.D. Selbach I. Da Silva A.S. Braga L.M.G.D.M. Camassola M. Nardi N.B. Acupoint injection of autologous stromal vascular fraction and allogeneic adipose-derived stem cells to treat hip dysplasia in dogs Stem Cells Int. 2014 2014 6 10.1155/2014/391274 25180040 33. Kemilew J. Sobczyńska-Rak A. Zylińska B. Szponder T. Nowicka B. Urban B. The use of allogenic stromal vascular fraction (SVF) cells in degenerative joint disease of the spine in dogs In Vivo (Brooklyn) 2019 33 1109 1117 10.21873/invivo.11580 31280199 34. Caplan A.I. Dennis J.E. Mesenchymal stem cells as trophic mediators J. Cell. Biochem. 2006 98 1076 1084 10.1002/jcb.20886 16619257 35. Zuk P.A. Zhu M. Mizuno H. Huang J. Futrell J.W. Katz A.J. Benhaim P. Lorenz H.P. Hedrick M.H. Multilineage cells from human adipose tissue: Implications for cell-based therapies Tissue Eng. 2001 7 211 228 10.1089/107632701300062859 11304456 36. Zuk P.A. Min Z. Ashjian P. De Ugarte D.A. Huang J.I. Mizuno H. Alfonso Z.C. Fraser J.K. Benhaim P. Hedrick M.H. Human Adipose Tissue Is a Source of Multipotent Stem Cells Mol. Biol. Cell 2002 13 4279 4295 10.1091/mbc.e02-02-0105 12475952 37. Neupane M. Chang C.-C. Kiupel M. Yuzbasiyan-Gurkan V. Isolation and Characterization of Canine Adipose–Derived Mesenchymal Stem Cells Tissue Eng. Part A 2008 14 1007 1015 10.1089/ten.tea.2007.0207 19230125 38. Marcoccia R. Nesci S. Merlo B. Ballotta G. Algieri C. Pagliarani A. Iacono E. Biological characteristics and metabolic profile of canine mesenchymal stem cells isolated from adipose tissue and umbilical cord matrix PLoS ONE 2021 16 e0247567 10.1371/journal.pone.0247567 33661930 39. Dominici M. Le Blanc K. Mueller I. Slaper-Cortenbach I. Marini F.C. Krause D.S. Deans R.J. Keating A. Prockop D.J. Horwitz E.M. Minimal criteria for defining multipotent mesenchymal stromal cells. The International Society for Cellular Therapy position statement Cytotherapy 2006 8 315 317 10.1080/14653240600855905 16923606 40. Kulus M. Kulus J. Jankowski M. Borowiec B. Jeseta M. Bukowska D. Brüssow K.P. Kempisty B. Antosik P. The use of mesenchymal stem cells in veterinary medicine Med. J. Cell Biol. 2018 6 101 107 10.2478/acb-2018-0016 41. Gugjoo M.B. Amarpal A. Sharma G.T. Mesenchymal stem cell basic research and applications in dog medicine J. Cell. Physiol. 2019 234 16779 16811 10.1002/jcp.28348 30790282 42. Voga M. Adamic N. Vengust M. Majdic G. Stem Cells in Veterinary Medicine—Current State and Treatment Options Front. Vet. Sci. 2020 7 278 10.3389/fvets.2020.00278 32656249 43. Dias I.E. Pinto P.O. Barros L.C. Viegas C.A. Dias I.R. Carvalho P.P. Mesenchymal stem cells therapy in companion animals: Useful for immune-mediated diseases? BMC Vet. Res. 2019 15 358 10.1186/s12917-019-2087-2 31640767 44. Gao F. Chiu S.M. Motan D.A.L. Zhang Z. Chen L. Ji H.L. Tse H.F. Fu Q.L. Lian Q. Mesenchymal stem cells and immunomodulation: Current status and future prospects Cell Death Dis. 2016 7 e2062 10.1038/cddis.2015.327 26794657 45. Ayala-Cuellar A.P. Kang J.H. Jeung E.B. Choi K.C. Roles of mesenchymal stem cells in tissue regeneration and immunomodulation Biomol. Ther. 2019 27 25 33 10.4062/biomolther.2017.260 46. Chow L. Johnson V. Coy J. Regan D. Dow S. Mechanisms of Immune Suppression Utilized by Canine Adipose and Bone Marrow-Derived Mesenchymal Stem Cells Stem Cells Dev. 2017 26 374 389 10.1089/scd.2016.0207 27881051 47. Wheat W.H. Chow L. Kurihara J.N. Regan D.P. Coy J.W. Webb T.L. Dow S.W. Suppression of Canine Dendritic Cell Activation/Maturation and Inflammatory Cytokine Release by Mesenchymal Stem Cells Occurs Through Multiple Distinct Biochemical Pathways Stem Cells Dev. 2017 26 249 262 10.1089/scd.2016.0199 27842458 48. Herrero C. Pérez-Simón J.A. Immunomodulatory effect of mesenchymal stem cells Brazilian J. Med. Biol. Res. 2010 43 425 430 10.1590/S0100-879X2010007500033 49. Marx C. Silveira M.D. Nardi N.B. Adipose-Derived Stem Cells in Veterinary Medicine: Characterization and Therapeutic Applications Stem Cells Dev. 2015 24 803 813 10.1089/scd.2014.0407 25556829 50. Krešić N. Šimić I. Lojkić I. Bedeković T. Mezenhimske matične stanice u veterinarskoj medicini Vet. Stanica 2019 50 149 154 51. Ponte A.L. Marais E. Gallay N. Langonné A. Delorme B. Hérault O. Charbord P. Domenech J. The In Vitro Migration Capacity of Human Bone Marrow Mesenchymal Stem Cells: Comparison of Chemokine and Growth Factor Chemotactic Activities Stem Cells 2007 25 1737 1745 10.1634/stemcells.2007-0054 17395768 52. Ullah M. Liu D.D. Thakor A.S. Mesenchymal Stromal Cell Homing: Mechanisms and Strategies for Improvement iScience 2019 15 421 438 10.1016/j.isci.2019.05.004 31121468 53. Sackstein R. The lymphocyte homing receptors: Gatekeepers of the multistep paradigm Curr. Opin. Hematol. 2005 12 444 450 10.1097/01.moh.0000177827.78280.79 16217160 54. Kwon Y.W. Heo S.C. Jeong G.O. Yoon J.W. Mo W.M. Lee M.J. Jang I.H. Kwon S.M. Lee J.S. Kim J.H. Tumor necrosis factor-α-activated mesenchymal stem cells promote endothelial progenitor cell homing and angiogenesis Biochim. Biophys. Acta—Mol. Basis Dis. 2013 1832 2136 2144 10.1016/j.bbadis.2013.08.002 23959047 55. Al Delfi I.R. Sheard J.J. Wood C.R. Vernallis A. Innes J.F. Myint P. Johnson W.E.B. Canine mesenchymal stem cells are neurotrophic and angiogenic: An in vitro assessment of their paracrine activity Vet. J. 2016 217 10 17 10.1016/j.tvjl.2016.09.003 27810198 56. Yao C. Zhou Y. Wang H. Deng F. Chen Y. Zhu X. Kong Y. Pan L. Xue L. Zhou X. Adipose-derived stem cells alleviate radiation-induced dermatitis by suppressing apoptosis and downregulating cathepsin F expression Stem Cell Res. Ther. 2021 12 447 10.1186/s13287-021-02516-1 34372921 57. Brondeel C. Pauwelyn G. de Bakker E. Saunders J. Samoy Y. Spaas J.H. Review: Mesenchymal Stem Cell Therapy in Canine Osteoarthritis Research: “Experientia Docet” (Experience Will Teach Us) Front. Vet. Sci. 2021 8 668881 10.3389/fvets.2021.668881 34095280 58. Yoon H.-Y. Lee J. Jeong S. Long-term follow-up after implantation of autologous adipose tissue derived mesenchymal stem cells to treat a dog with stifle joint osteoarthrosis J. Vet. Clin. 2012 29 82 86 59. Guercio A. Di Marco P. Casella S. Cannella V. Russotto L. Purpari G. Di Bella S. Piccione G. Production of canine mesenchymal stem cells from adipose tissue and their application in dogs with chronic osteoarthritis of the humeroradial joints Cell Biol. Int. 2012 36 189 194 10.1042/CBI20110304 21936851 60. Vilar J.M. Morales M. Santana A. Spinella G. Rubio M. Cuervo B. Cugat R. Carrillo J.M. Controlled, blinded force platform analysis of the effect of intraarticular injection of autologous adipose-derived mesenchymal stem cells associated to PRGF-Endoret in osteoarthritic dogs BMC Vet. Res. 2013 9 131 10.1186/1746-6148-9-131 23819757 61. Cuervo B. Rubio M. Sopena J. Dominguez J.M. Vilar J. Morales M. Cugat R. Carrillo J.M. Hip osteoarthritis in dogs: A randomized study using mesenchymal stem cells from adipose tissue and plasma rich in growth factors Int. J. Mol. Sci. 2014 15 13437 13460 10.3390/ijms150813437 25089877 62. Vilar J.M. Batista M. Morales M. Santana A. Cuervo B. Rubio M. Cugat R. Sopena J. Carrillo J.M. Assessment of the effect of intraarticular injection of autologous adipose-derived mesenchymal stem cells in osteoarthritic dogs using a double blinded force platform analysis BMC Vet. Res. 2014 10 143 10.1186/1746-6148-10-143 24984756 63. Harman R. Carlson K. Gaynor J. Gustafson S. Dhupa S. Clement K. Hoelzler M. McCarthy T. Schwartz P. Adams C. A prospective, randomized, masked, and placebo-controlled efficacy study of intraarticular allogeneic adipose stem cells for the treatment of osteoarthritis in dogs Front. Vet. Sci. 2016 3 81 10.3389/fvets.2016.00081 27695698 64. Yun S. Ku S.K. Kwon Y.S. Adipose-derived mesenchymal stem cells and platelet-rich plasma synergistically ameliorate the surgical-induced osteoarthritis in Beagle dogs J. Orthop. Surg. Res. 2016 11 9 10.1186/s13018-016-0342-9 26768536 65. Vilar J.M. Cuervo B. Rubio M. Sopena J. Domínguez J.M. Santana A. Carrillo J.M. Effect of intraarticular inoculation of mesenchymal stem cells in dogs with hip osteoarthritis by means of objective force platform gait analysis: Concordance with numeric subjective scoring scales BMC Vet. Res. 2016 12 223 10.1186/s12917-016-0852-z 27717361 66. Kriston-Pál É. Czibula Á. Gyuris Z. Balka G. Seregi A. Sükösd F. Süth M. Kiss-Tóth E. Haracska L. Uher F. Characterization and therapeutic application of canine adipose Can. J. Vet. Res. 2017 81 73 78 28197017 67. Shah K. Drury T. Roic I. Hansen P. Malin M. Boyd R. Sumer H. Ferguson R. Outcome of allogeneic adult stem cell therapy in dogs suffering from osteoarthritis and other joint defects Stem Cells Int. 2018 2018 7 10.1155/2018/7309201 68. Srzentić Dražilov S. Mrkovački J. Spasovski V. Fazlagić A. Pavlović S. Nikčević G. The use of canine mesenchymal stem cells for the autologous treatment of osteoarthritis Acta Vet. Hung. 2018 66 376 389 10.1556/004.2018.034 30264620 69. Olsen A. Johnson V. Webb T. Santangelo K.S. Dow S. Duerr F.M. Evaluation of Intravenously Delivered Allogeneic Mesenchymal Stem Cells for Treatment of Elbow Osteoarthritis in Dogs: A Pilot Study Vet. Comp. Orthop. Traumatol. 2019 32 173 181 10.1055/s-0039-1678547 30873568 70. Wits M.I. Tobin G.C. Silveira M.D. Baja K.G. Braga L.M.M. Sesterheim P. Camassola M. Nardi N.B. Combining canine mesenchymal stromal cells and hyaluronic acid for cartilage repair Genet. Mol. Biol. 2020 43 1 8 10.1590/1678-4685-gmb-2019-0275 71. Brown G.S. Harman J.R. Black L.L. Adipose-derived stem cell therapy for severe muscle tears in working German shepherds: Two case reports Stem Cell Discov. 2012 02 41 44 10.4236/scd.2012.22007 72. Gibson M.A. Brown S.G. Brown N.O. Semitendinosus myopathy and treatment with adipose-derived stem cells in working German shepherd police dogs Can. Vet. J. 2017 58 241 246 28246410 73. Escalhão C.C.M.I. Ramos I.P. Hochman-Mendez C. Brunswick T.H.K. Souza S.A.L. Gutfilen B. Dos Santos Goldenberg R.C. Coelho-Sampaio T. Safety of allogeneic canine adipose tissue-derived mesenchymal stem cell intraspinal transplantation in dogs with chronic spinal cord injury Stem Cells Int. 2017 2017 11 10.1155/2017/3053759 28611846 74. Bach F.S. Rebelatto C.L.K. Fracaro L. Senegaglia A.C. Fragoso F.Y.I. Daga D.R. Brofman P.R.S. Pimpão C.T. Engracia Filho J.R. Montiani-Ferreira F. Comparison of the Efficacy of Surgical Decompression Alone and Combined With Canine Adipose Tissue-Derived Stem Cell Transplantation in Dogs With Acute Thoracolumbar Disk Disease and Spinal Cord Injury Front. Vet. Sci. 2019 6 383 10.3389/fvets.2019.00383 31781580 75. Mrkovački J. Srzentić Dražilov S. Spasovski V. Fazlagić A. Pavlović S. Nikčević G. Case Report: Successful Therapy of Spontaneously Occurring Canine Degenerative Lumbosacral Stenosis Using Autologous Adipose Tissue-Derived Mesenchymal Stem Cells Front. Vet. Sci. 2021 8 1055 10.3389/fvets.2021.732073 76. Chen C.C. Yang S.F. Wang I.K. Hsieh S.Y. Yu J.X. Wu T.L. Huang W.J. Su M.H. Yang H.L. Chang P.C. The Long-Term Efficacy Study of Multiple Allogeneic Canine Adipose Tissue-Derived Mesenchymal Stem Cells Transplantations Combined With Surgery in Four Dogs With Lumbosacral Spinal Cord Injury Cell Transplant. 2022 31 09636897221081487 10.1177/09636897221081487 77. Zubin E. Conti V. Leonardi F. Zanichelli S. Ramoni R. Grolli S. Regenerative therapy for the management of a large skin wound in a dog Clin. Case Reports 2015 3 598 603 10.1002/ccr3.253 78. Villatoro A.J. Hermida-Prieto M. Fernández V. Fariñas F. Alcoholado C. Isabel Rodríguez-García M. Mariñas-Pardo L. Becerra J. Allogeneic adipose-derived mesenchymal stem cell therapy in dogs with refractory atopic dermatitis: Clinical efficacy and safety Vet. Rec. 2018 183 654 10.1136/vr.104867 30158120 79. Enciso N. Avedillo L. Fermín M.L. Fragío C. Tejero C. Cutaneous wound healing: Canine allogeneic ASC therapy Stem Cell Res. Ther. 2020 11 261 10.1186/s13287-020-01778-5 32600465 80. Kaur G. Ramirez A. Xie C. Clark D. Dong C. Maki C. Ramos T. Izadyar F. Najera S.O.L. Harb J. A double-blinded placebo-controlled evaluation of adipose-derived mesenchymal stem cells in treatment of canine atopic dermatitis Vet. Res. Commun. 2022 46 251–260, 10 10.1007/s11259-021-09853-9 81. Villatoro A.J. Fernández V. Claros S. Rico-Llanos G.A. Becerra J. Andrades J.A. Use of adipose-derived mesenchymal stem cells in keratoconjunctivitis sicca in a canine model Biomed Res. Int. 2015 2015 527926 10.1155/2015/527926 25802852 82. Bittencourt M.K.W. Barros M.A. Martins J.F.P. Vasconcellos J.P.C. Morais B.P. Pompeia C. Bittencourt M.D. Evangelho K.D.S. Kerkis I. Wenceslau C.V. Allogeneic Mesenchymal Stem Cell Transplantation in Dogs with Keratoconjunctivitis Sicca Cell Med. 2016 8 63 77 10.3727/215517916X693366 28003932 83. Sgrignoli M.R. Silva D.A. Nascimento F.F. Sgrignoli D.A.M. Nai G.A. da Silva M.G. de Barros M.A. Bittencourt M.K.W. de Morais B.P. Dinallo H.R. Reduction in the inflammatory markers CD4, IL-1, IL-6 and TNFα in dogs with keratoconjunctivitis sicca treated topically with mesenchymal stem cells Stem Cell Res. 2019 39 101525 10.1016/j.scr.2019.101525 31430719 84. Falcão M.S.A. Brunel H.D.S.S. Peixer M.A.S. Dallago B.S.L. Costa F.F. Queiroz L.M. Campbell P. Malard P.F. Effect of allogeneic mesenchymal stem cells (MSCs) on corneal wound healing in dogs J. Tradit. Complement. Med. 2020 10 440 445 10.1016/j.jtcme.2019.04.006 32953559 85. Pérez-Merino E.M. Usón-Casaús J.M. Zaragoza-Bayle C. Duque-Carrasco J. Mariñas-Pardo L. Hermida-Prieto M. Barrera-Chacón R. Gualtieri M. Safety and efficacy of allogeneic adipose tissue-derived mesenchymal stem cells for treatment of dogs with inflammatory bowel disease: Clinical and laboratory outcomes Vet. J. 2015 206 385 390 10.1016/j.tvjl.2015.08.003 26526522 86. Teshima T. Matsumoto H. Michishita M. Matsuoka A. Shiba M. Nagashima T. Koyama H. Allogenic adipose tissue-derived mesenchymal stem cells ameliorate acute hepatic injury in dogs Stem Cells Int. 2017 2017 12 10.1155/2017/3892514 29445402 87. Gardin C. Ferroni L. Bellin G. Rubini G. Barosio S. Zavan B. Therapeutic potential of autologous adipose-derived stem cells for the treatment of liver disease Int. J. Mol. Sci. 2018 19 4064 10.3390/ijms19124064 88. Yan Y. Fang J. Wen X. Teng X. Li B. Zhou Z. Peng S. Arisha A.H. Liu W. Hua J. Therapeutic applications of adipose-derived mesenchymal stem cells on acute liver injury in canines Res. Vet. Sci. 2019 126 233 239 10.1016/j.rvsc.2019.09.004 31635840 89. Anonymus European Medicines Agency: Questions and Answers on Allogeneic Stem Cell-Based Products for Veterinary Use 2019 Available online: https://www.ema.europa.eu/en/documents/scientific-guideline/questions-answers-allogeneic-stem-cell-based-products-veterinary-use-specific-questions-sterility_en.pdf (accessed on 31 January 2022) 90. Anonymous European Medicines Agency: Concept Paper on the Development and Data Requirements of Potency Tests for Cell-Based Therapy Products and the Relation to Clinical Efficacy 2022 Available online: https://www.ema.europa.eu/en/documents/scientific-guideline/concept-paper-development-data-requirements-potency-tests-cell-based-therapy-products-relation_en.pdf (accessed on 3 February 2022) 91. Lynne Boxer Food and Drug Administration: Guidance for Industry Cell-Based Products for Animal Use 2015 Available online: https://www.fda.gov/media/88925/download?source=govdelivery&utm_medium=email&utm_source=govdelivery (accessed on 21 December 2021)

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094866 ijms-23-04866 Article Effects of Concurrent Exposure to Chronic Restraint-Induced Stress and Total-Body Iron Ion Radiation on Induction of Kidney Injury in Mice Xu Duling 12345† Li Hongyan 12345† https://orcid.org/0000-0002-6374-4272 Katsube Takanori 6 Huang Guomin 12345 Liu Jiadi 12345 https://orcid.org/0000-0002-7180-639X Wang Bing 6* Zhang Hong 12345* Osipov Andreyan N. Academic Editor Klokov Dmitry Academic Editor 1 Department of Medical Physics, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China; xuduling21@mails.ucas.ac.cn (D.X.); lihy@impcas.ac.cn (H.L.); huangguomin@impcas.ac.cn (G.H.); liujiadi21@mails.ucas.ac.cn (J.L.) 2 Key Laboratory of Heavy Ion Radiation Biology and Medicine, Chinese Academy of Sciences, Lanzhou 730000, China 3 Key Laboratory of Basic Research on Heavy Ion Radiation Application in Medicine, Lanzhou 730000, China 4 School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 101408, China 5 Advanced Energy Science and Technology Guangdong Laboratory, Huizhou 516029, China 6 National Institute of Radiological Sciences, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; katsube.takanori@qst.go.jp * Correspondence: wang.bing@qst.go.jp (B.W.); zhangh@impcas.ac.cn (H.Z.); Tel.: +81-43-206-3093 (B.W.); +96-931-4969344 (H.Z.) † These authors contributed equally to this work. 27 4 2022 5 2022 23 9 486623 3 2022 25 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Concurrent exposure to ionizing radiation (IR) and psychological stress (PS) may affect the development of adverse health consequences in scenarios such as space missions, radiotherapy and nuclear accidents. IR can induce DNA damage and cell apoptosis in the kidneys, thus potentially leading to renal fibrosis, which is the ultimate outcome of various chronic progressive nephropathies and the morphological manifestation of a continuous coordinated response after renal injury. However, little is known regarding the effects of concurrent IR exposure and PS on renal damage, particularly renal fibrosis. In this study, using a chronic restraint-induced PS (CRIPS) model, we exposed Trp53-heterozygous mice to total body irradiation with 0.1 or 2 Gy 56Fe ions on the eighth day of 28 consecutive days of a restraint regimen. At the end of the restraint period, the kidneys were collected. The histopathological changes and the degree of kidney fibrosis were assessed with H&E and Masson staining, respectively. Fibronectin (FN) and alpha smooth muscle actin (α-SMA), biomarkers of fibrosis, were detected by immunohistochemistry. Analysis of 8-hydroxy-2 deoxyguanosine (8-OHdG), a biomarker of oxidative DNA damage, was performed with immunofluorescence, and terminal deoxynucleotidyl transferase-mediated nick end labeling assays were used to detect apoptotic cells. Histopathological observations did not indicate significant structural damage induced by IR or CRIPS + IR. Western blotting revealed that the expression of α-SMA was much higher in the CRIPS + IR groups than the CRIPS groups. However, no differences in the average optical density per area were observed for FN, α-SMA and 8-OHdG between the IR and CRIPS + IR groups. No difference in the induction of apoptosis was observed between the IR and CRIPS + IR groups. These results suggested that exposure to IR (0.1 and 2 Gy 56Fe ions), 28 consecutive days of CRIPS or both did not cause renal fibrosis. Thus, CRIPS did not alter the IR-induced effects on renal damage in Trp53-heterozygous mice in our experimental setup. chronic restraint psychology stress ionizing radiation National Natural Science Foundation of China11875061 National Key R&D Program of China2018YFE0205100 Talent Project of Longyuan (Gansu province) Youth Innovation and EntrepreneurshipE139222SR0 National Natural Science Foundation of Gansu province20JR5RA550 National Laboratory of Heavy Ion Accelerator of LanzhouE0HIRFL03P Guangdong Basic and Applied Basic Research Foundation2021A1515010027 Key Program of the National Natural Science Foundation of ChinaU1632270 Ministry of Education, Culture, Sports, Science and Technology Grant-in-Aid for Scientific Research on Innovative AreasJP15K21745 15H05935 HIMAC Research Project Grant16J295 This research was partially funded by the National Natural Science Foundation of China (11875061), the National Key R&D Program of China (2018YFE0205100), the Program of the Local Science and Technology Development (Gansu province) Guided by Central Government (GSCK2021-51-11), the Talent Project of Longyuan (Gansu province) Youth Innovation and Entrepreneurship (E139222SR0), the National Natural Science Foundation of Gansu province (20JR5RA550), the National Laboratory of Heavy Ion Accelerator of Lanzhou (E0HIRFL03P), the Guangdong Basic and Applied Basic Research Foundation (2021A1515010027), and the Key Program of the National Natural Science Foundation of China (U1632270), and was partially funded by both the Ministry of Education, Culture, Sports, Science and Technology Grant-in-Aid for Scientific Research on Innovative Areas, Grant Numbers JP15K21745 and 15H05935 “Living in Space” and a HIMAC Research Project Grant (16J295). ==== Body pmc1. Introduction A variety of psychological stress (PS) suppresses the immune system [1] and has gradually become the main risk factor of several physiological disorders, which might result in diabetes, metabolic syndrome [2] and the diseases of central nervous and cardiovascular systems, and even cancer. With the rapid development of space technology, an increasing number of astronauts have to suffer from the harmful exposure to cosmic radiation (CR) [3]. CR affects astronaut health, especially the high atomic number and high-energy (HZE) particles that are often referred to as high linear energy transfer (LET) radiation or densely ionizing [4]. High LET ion exposure can lead to damage that is more difficult to repair than X-ray and γ-ray damage [5]. Among the particles of CR, 13% of the dose during manned long-term deep-space Mars missions was from Fe particles alone [6], thus, Fe particles are of great research interest in CR. Inevitably, astronauts are exposed to LET ion radiation [7], microgravity and an enclosed environment during long-term space missions [8]. The exposure to an enclosed environment in space flights might lead to PS. In reality, astronauts are exposed to the dual harms of PS and ionizing radiation (IR) exposure on space missions, and the PS could exacerbate the detrimental effects induced by IR that could result in an additive or even synergistic effect. However, little is known about the combined health consequences of exposure to PS and IR. Therefore, assessing the possible harmful effects of IR and PS and investigating whether PS might modify IR-induced toxicity are important for understanding the possible effects of these exposures on human health. Chronic restraint-induced PS (CRIPS) models have been successfully used in previous studies, and results show that CRIPS could enhance the frequency of chromosomal exchange induced by 56Fe ion irradiation in Trp53-heterozygous mice [8]. Although CRIPS has no additive effects beyond the radiation-induced detrimental effects on the hematopoietic system in Trp53-wildtype mice [9] and spermatogenic cells in Trp53-heterozygous mice [10], the effects from concurrent exposure to CRIPS and IR on other organs and systems are still unclear. Since the kidney is an important organ that regulates body fluid, electrolyte and acid-base metabolism, kidney function and water and electrolyte balance are crucially important in space flights [11]. In the present study, effects from concurrent exposure to CRIPS and IR on kidney were investigated in Trp53-heterozygous mice. According to the documented data, CRIPS increases the aldosterone levels that were related with metabolic syndrome and renal injury [12]. Moreover, renal fibrosis is a common outcome of many chronic kidney diseases, independently of the underlying etiology [13]. In chronic renal injury, a fibrous matrix is continually deposited, thus destroying the tissue structure, decreasing the blood supply, interfering with organ function and, finally, leading to renal failure [14]. Chronic toxicity induced by radiation in the kidneys is generally characterized by fibrogenesis and extracellular matrix deposition [15]. However, whether PS is a modifying factor in IR-induced renal injury remains unknown. Thus, we investigated whether PS exacerbates the renal fibrosis induced by 56Fe ion irradiation, to better understand whether CRIPS is an additive factor in renal fibrosis induced by IR in Trp53+/− mice. High LET ions cause direct damage by destroying chemical bonds, and also induce indirect damage through the production of reactive oxygen species (ROS) [15]. When ROS exceeds the antioxidant capacity, oxidative stress and DNA damage increase [16]. After radiation injury, renal dysfunction due to DNA damage leads to cell apoptosis and, eventually, renal fibrosis [17]; moreover, the cost of treatment is expensive. These factors interact with mental stress, thus affecting the progression and prognosis of renal fibrosis [18]. Here, we used 56Fe ion radiation to induce DNA damage in mice to explore whether CRIPS might alter the effects of IR on renal fibrosis. We used a chronic restraint model to simulate CRIPS and used an 56Fe ion beam to deliver total-body irradiation (TBI) with 0.1 and 2 Gy in Tp53-heterozygous male mice. Fibronectin (FN) [19] and alpha smooth muscle actin (α-SMA) [20], biomarkers of fibrosis, were detected by immunohistochemistry. The expression of α-SMA was detected by western blotting, and the levels of 8-hydroxy-2 deoxyguanosine (8-OHdG) were used to assess DNA damage [21] by immunofluorescence. We hypothesized that IR causes DNA damage, thus inducing apoptosis and enhancing renal fibrosis, and that CRIPS and concurrent exposure to IR might have additive effects on renal fibrosis. 2. Materials and Methods 2.1. Animal Treatment The animal experiments were conducted at the National Institute of Radiological Science (NIRS) of Japan. Four-week-old C57BL/6N TP53 heterozygous (Trp53+/−) mice (BRC NO. 01361) were used in the experiments. From 07:00 to 19:00, we placed one or two mice in an autoclaved cage maintained under controlled temperature (23 ± 2 °C) and humidity (50 ± 10%) under 12 h continuous light/dark cycle conditions, and allowed them to freely consume standard laboratory chow (MB-1; Funabashi Farm Co., Funabashi, Chiba, Japan) and acidified water (pH 3.0 ± 0.2). One week before the experiment, the mice were randomly divided into six groups (Table 1): a control group (n = 6), which did not receive restraint and 56Fe ion radiation; a 0.1 Gy 56Fe ion radiation group (n = 6); a 2 Gy 56Fe ion radiation group (n = 6); a CRIPS group (n = 6), receiving only chronic restraint; a CRIPS + 0.1 Gy 56Fe ion radiation group (n = 6); and a CRIPS + 2 Gy 56Fe ion radiation group (n = 6). In the restraint group, a flat-bottomed rodent holder (RSTR541; Kent Scientific Co., United States) placed horizontally in the cage was used for chronic restraint for 28 days for 6 h per day (09:30–15:30). The mice were then placed in the same cage for free activity (15:30–09:30), during which the mice were allowed to eat and drink freely. In the early morning (3:30–04:30 a.m. or 6:00–7:00 a.m.), on day 8 of the 28-day restraint regimen, 56Fe ions of TBI were irradiated at NIRS with a heavy ion medical accelerator in Chiba (HIMAC) at doses of 0.085 Gy/min, 1.1–2.7 Gy/min and 0.1 and 2 Gy (500 MeV/nucleon, 200 keV/µm). 2.2. The Histological Observation The mice were anesthetized by inhalation of carbon dioxide and then euthanized by cervical dislocation. The kidneys were separated and fixed in 4% paraformaldehyde (Solarbio Life Sciences, Beijing, China), then embedded in paraffin and cut into sections with 4 µM thickness. The sections were stained with hematoxylin and eosin (H&E) (Solarbio) after paraffinization and rehydration, then mounted with neutral gum [22]. 2.3. Masson Staining The Masson staining method was used to detect collagen fibers in the kidneys. Paraffin embedded renal tissue sections were used for dewaxing and hydration. Hematoxylin was used to stain nuclei for 5 min and was washed away with Tris Buffered Saline (TBS) for 10 min. Subsequently, Masson solution staining (Servicebio Technology Co., Wuhan, Hubei province, China) was performed for 5 min. The sections were then placed in 1% glacial acetic acid solution (Servicebio), differentiated for 5–10 s, then mounted with neutral gum. Images were taken under an optical microscope. Four fields were randomly selected from each section for analysis [23]. 2.4. TUNEL Assay Detection of apoptosis was performed with a TdT-mediated dUTP nick end labeling (TUNEL) assay kit (Servicebio). The sections were deparaffinized and hydrated, then permeabilized with proteinase K at 37 °C for 15 min and treated with 3% H2O2 for 15 min. After being washed with 0.01 M phosphate-buffered saline, the sections were incubated with TUNEL reaction mixture (1:5:50 ratio of TDT enzyme, dUTP and buffer) for 1 h at 37 °C in a dark humidified plastic container. Reagent Streptavidin-Horseradish Peroxidase (HRP) (Servicebio) and Tris Buffered Saline with Tween (TBST) were mixed at a ratio of 1:200, added to the sections and incubated in a 37 °C incubator for 30 min. Then, sections were dried slightly, and freshly prepared 3, 3′-diaminobenzidine (DAB) (Servicebio) chromogenic reagent was added to marked sections. Finally, the sections were stained with hematoxylin after paraffinization and rehydration, then mounted with neutral gum [24]. 2.5. Immunofluorescence The sections were deparaffinized and hydrated, then immersed in 3% H2O2 for 30 min, then incubated in 1% Triton X-100 for 30 min, blocked for 25 min at room temperature in 5% bovine Serum Albumin (BSA) (Solarbio) (5 g BSA in 100 mL TBS) and incubated in primary antibody in TBS at 4 °C. Sections were stained with 5 g/mL 4′, 6-diamidino-2-phenylindole (DAPI) (Soliabo) for 10 min, washed with TBS twice for 5 min, then mounted with glycerin–sodium bicarbonate wet sealant [25]. 2.6. Immunohistochemistry Immunohistochemistry was used to detect the expression of fibronectin (ab268020) and α-SMA (ab124964) (Abcam, Cambridge, UK). The renal sections were deparaffinized and hydrated, then maintained at 96 °C for 12 min for antigen repair. After being treated with 3% hydrogen peroxide for 15 min, the primary antibody (1:500) was incubated with the sections at 4 °C overnight, and then a Streptavidin-Peroxidase kit (Bioss Biotechnology Co., Beijing, China) was used for immunoreaction. Bound peroxidase activity was visualized with a DAB detection kit (Bioss). Sections were then counterstained with hematoxylin and mounted [26]. 2.7. Western Blotting Two samples were randomly selected as one independent sample for protein extraction per group. The total protein of renal tissue from two samples was extracted with RIPA buffer (Solarbio), and the protein concentration was measured with the BCA Kit (Solarbio). A total of 40 μg of protein was separated on 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), then transferred to 0.45 µM polyvinylidene fluoride (PVDF) membranes (Millipore, Billerica, MA, USA). The membranes were blocked with 5% skimmed milk for 1 h at room temperature, then washed with TBST. Primary antibody (α-SMA, 1:2000, Servicebio) was incubated at 4 °C overnight. After secondary antibody binding, a chemiluminescent reagent kit (New Cell and Molecular Biotech, Suzhou, China) was used to detect protein bands. β-actin was used as a control, and the intensity of protein bands was analyzed in Amersham Imager 680 software (GE Healthcare Bio-Sciences AB, Uppsala, Sweden). 2.8. Statistical Analysis The sections were scanned with Panoramic MIDI software (3DHISTECH, Budapest, Hungary). Image-Pro Plus software (Media Cybernetics, Inc, Bethesda, MD, USA) was also used to analyze and the average optical density (AOD) (Integrated optical density/area) to indicate the level of protein expression. Five different visual immunohistochemistry fields were taken from each sample (200×), and the average AOD was calculated. The statistical data for each group were analyzed in Statistical Package for Social Sciences (SPSS) 23.0 (IBM Corp., Armonk, NY, USA), and the statistical data are expressed as mean ± standard deviation. The means across multiple groups were analyzed with one-way analysis of variance (ANOVA), and the means between two groups were analyzed with t-test, with p < 0.05 indicating significance. 3. Results 3.1. The Histopathological Observation H&E staining was used to compare the renal structural changes between the control group and the experimental groups (Figure 1). The cortical glomeruli were normal, and the basement membrane was clear in the control and CRIPS groups. Compared with the control group, the IR and CRIPS + IR groups had smaller volumes of glomeruli, and the differences were more pronounced in the 2 Gy and 2 Gy + IR groups, in which renal interstitial inflammatory cell infiltration was also observed. 3.2. The 8-OHdG Expression As a marker of DNA damage, 8-OHdG is highly reliable and abundant. Thus, we assessed 8-OHdG expression with immunofluorescence. The 8-OHdG fluorescence was detected almost exclusively in the cell nuclei on the surface of the renal cortex in the control and CRIPS groups. The fluorescence signal was greater in the eosinophils or basophils on the surface of the renal cortex in the IR and CRIPS + IR groups than the control group (Figure 2A). However, no significant differences in fluorescence intensity were observed among groups (Figure 2B). 3.3. The Apoptotic Cells Detection Apoptotic renal cells were detected with TUNEL assays. Eosinophils or basophils were observed in the control and CRIPS groups, and no clear differences in apoptotic cell types were observed between the IR and CRIPS + IR groups, including the 2 Gy and CRIPS + 2 Gy groups and the control group (Figure 3). 3.4. The Evaluation of Renal Fibrosis Renal fibrosis was evaluated with Masson staining. The collagen fibers in the glomeruli and renal tubules showed weak blue staining in the six groups (Figure 4A). The basement membrane was stained blue in only the control and CRIPS groups. The degree of staining showed no clear differences between the 0.1 Gy or CRIPS + 0.1 Gy groups and the control group. The area of collagen fibers in the 2 Gy and 2 Gy + IR groups was greater than that in the 0.1 Gy and CRIPS + 0.1 Gy groups. However, no differences were observed among all groups after statistical analysis (Figure 4B). 3.5. The FN and α-SMA Expression FN and α-SMA are important biomarkers of fibrosis [18]. Thus, the expression and distribution of FN and α-SMA were detected by immunohistochemistry. FN was expressed in the renal tubular basement membrane, adventitia and glomerular mesangium, but the staining was weak in the control and CRIPS groups (Figure 5A). The FN staining was mainly located in the glomeruli, mesangium and renal tubular basement membrane in the IR and CRIPS + IR groups (Figure 5A). However, no significant differences were observed among all groups (Figure 5B). α-SMA was expressed in arterial middle smooth muscle cells but not renal stroma in the control and CRIPS groups (Figure 6A). The expression of α-SMA was elevated in renal tubules and the renal interstitium in the IR and CRIPS + IR groups, and no difference in the AOD of α-SMA expression was observed among groups (Figure 6B). However, the expression of α-SMA was higher in the CRIPS + IR groups than the CRIPS groups (Figure 7B). 4. Discussion Radiation-induced fibrosis is a late sequela of both therapeutic and accidental irradiations, which has been described in various tissues, including the lung, liver, kidney and skin [27]. The altered renal lipid metabolism induced by chronic restraint stress may contribute to renal injury [12]. Thus, the harmful effects from concurrent exposure to IR and PS on renal injury and fibrosis cannot be ignored during long-term space missions. The present study explored the effects of a low dose of 56Fe ion radiation combined with CRIPS on renal fibrosis, and whether CRIPS might be an additive factor in the renal fibrosis induced by IR in Trp53+/− mice. Radiation nephritis (RN) is a clinical syndrome caused by acute or chronic kidney injury after IR. The effects in patients include fatigue, shortness of breath, edema and significant renal failure [3]. Chronic RN may be caused by the long-term evolution and aggravation of acute RN, including renal fibrosis [28]. In this study, we used a chronic restraint experimental device to generate a model of Trp53+/− male mice exposed to 56Fe radiation under PS, in which we observed the renal fibrosis. At the end of the 28-day experimental period, we conducted histochemical experiments on the renal tissue, which indicated no structural differences between the control group and the experimental groups. FN and α-SMA staining revealed no significant differences in fibrosis between the control group and the experimental groups, including the 2 Gy and CRIPS + 2 Gy groups. The above results indicated that CRIPS, IR and CRIPS + IR did not damage the renal structure or induce the renal fibrosis. The early biological response to high LET radiation exposure, namely the induction of ROS, has been demonstrated in previous studies, suggesting that ROS and nitrogen species formed after IR might trigger DNA damage and lead to localized inflammation [29]. This inflammatory process ultimately evolves into a fibrotic process characterized by increased collagen deposition, poor vascularity and scarring [29]. Previous work has indicated that CR causes oxidative damage by increasing ROS in the kidneys [30]. Therefore, in this study, we explored the process through which IR-induced DNA damage leads to renal cell apoptosis, thus accelerating renal fibrosis. We examined the renal cell distribution of the oxidative DNA damage marker protein 8-OHdG (Figure 2A), which was present in the nucleus, thus indicating that oxidative DNA damage destroyed the nucleoli of renal cells. However, no significant differences in the AOD of 8-OHdG were observed between the control group and the experimental groups, including the 2 Gy and CRIPS + 2 Gy groups. TUNEL assays also indicated few apoptotic cells in the IR and CRIPS + IR groups, including the 2 Gy and CRIPS + 2 Gy groups. These results indicated that CRIPS, IR and CRIPS + IR did not induce DNA damage and cell apoptosis. Fe particles, as one of the important components of HZE particles in space, are gradually attracting researchers’ interest [31]. Similar to other heavy ions, 56Fe ions also cause damage that is more difficult to repair than conventional radiation-induced damage from X-rays and γ-rays. Turker et al. (2017) explored the effects of 56Fe ion exposures on Aprt mutant frequency and toxicity in the kidney epithelium. They found that significantly increased levels of apparent mitotic recombination events were observed for the 0.5, 1.0 and 2.0 Gy doses, and a significant reduction in clone of kidney epithelial cells was observed at 1.0 and 2.0 Gy groups [32]. In the present study, we used 0.1 and 2 Gy TBI to simulate the space radiation; no significant differences in histopathological and fibrotic changes, DNA damage and renal cell apoptosis were observed between the IR and CRIPS + IR groups, for two possible reasons. Radiation dose is a major factor in the induction of RN, and the dose used in the present study was not sufficient to cause renal fibrosis. Larger doses appear to be more efficient for IR-induced renal fibrosis. Second, studies on radiation damage in animal experiments have shown more severe damage over time. A previous study indicated injury to renal tubules occurring 3 months after radiation [33], but observed only minor changes in glomeruli. Rats have been found to show proteinuria within 6 weeks after irradiation and uremic morbidity after 26 weeks [27]. Less positive staining of 8-OHdG has been observed in severely atrophic tubules at 24 weeks after irradiation [34]. Our findings are in agreement with the above observations, indicating less positive immunofluorescence staining for 8-OHdG in the nuclei of cells in the 2 Gy and CRIPS + 2 Gy groups. Although the fluorescence intensity of 8-OHdG did not significantly differ among experimental groups, the fluorescence signal of 8-OHdG was enhanced in these groups compared with the control, thus indicating persistent oxidative stress in the kidneys after irradiation. Therefore, observation time is another important factor for studying renal fibrosis. In addition, recovery may occur; thereby, continuous observation over a longer duration after exposure is required. It should be noted that, for flight crew in a manned long-duration deep-space mission, radiation exposure is chronic and at very low fluences and fluence rates. However, it is very hard, technically, to simulate the exposure in space in experimental studies using heavy ion accelerators. In further studies, it would be practical to use fractionated exposure in combination with longer restraint time to simulate the exposure in space. On the other hand, to verify whether PS could modify radiation-induced renal fibrosis, a larger dose and a longer study duration should be applied to induce renal fibrosis in the experimental model. This is because, clinically, a dose at 23 Gy caused chronic kidney disease in 5% of cases [35], and patients who received total doses of 18.8 Gy with fractional irradiation showed no change in lipid peroxidation or protein oxidation in urine 42 days after radiation [36]. 5. Conclusions The histopathological observations revealed no structural changes, and immunohistochemical analysis showed no significant differences in FN and α-SMA expression between the CRIPS + IR and IR groups (compared at the same 56Fe ion dose). Although exposure to IR (0.1 and 2 Gy 56Fe ions), 28 consecutive days of CRIPS or both did not cause renal fibrosis, these results provide a reference for exploring the renal fibrosis induced by CRIPS, IR and CRIPS + IR. Further studies should be performed to verify the effects of concurrent exposure to both PS and IR under different experimental conditions, such as using lager doses of IR, chronic or fractioned exposures and a longer-term CRIPS model. Acknowledgments We thank Seiji Kito for timely preparation of the animals, and Hirokazu Hirakawa, Cuihua Liu, Kouichi Maruyama, Yasuharu Ninomiya, Akira Fujimori, Tetsuo Nakajima and Mitsuru Nenoi for performing a part of experiment. The expert technical assistance and administrative support of Hiromi Arai, Sadao Hirobe, Mikiko Nakajima and Yasuko Morimoto are gratefully acknowledged. Author Contributions Formal analysis, visualization, original draft, software, writing—review and editing, D.X.; conceptualization, resources, writing—original draft, writing—review and editing, H.L.; writing—original draft, writing—review and editing, T.K.; investigation, G.H.; investigation, J.L.; conceptualization, resources, writing—original draft, supervision, writing—review and editing, B.W.; writing—original draft, supervision, writing—review and editing, H.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Care and Use of Laboratory Animals, NIRS, QST, Japan. All experimental protocols involving mice were reviewed and approved by The Institutional Animal Care and Use Committee of the NIRS, QST, Japan (Experimental Animal Research Plan and Protocol Code 12-1026-3 on 22 September 2014 and Research Plan Using Genetically Modified Organisms Code H26-8 on 1 October 2014). Informed Consent Statement Not applicable. Data Availability Statement The authors confirm that the data supporting the findings of this study are available within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 H&E staining of renal sections from Trp53+/− mice (magnification, 200×; scale bar = 100 µM). CRIPS, chronic restraint-induced stress. Figure 2 Expression of 8-OHdG, detected in renal sections in Trp53+/− mice. (A), the expression of 8-OHdG was analyzed by immunofluorescence (magnification, 200×; scale bar = 100 µM); (B), the average AOD of 8-OHdG in each group. CRIPS, chronic restraint-induced stress; AOD, the average optical density (Integrated optical density/area). Figure 3 The apoptotic cells of renal sections detected by TUNEL assay in Trp53+/− mouse (magnification, 200×; scale bar = 100 µM). Arrows indicate apoptotic cells (red arrow indicates renal tubular epithelial cells; black arrow indicates eosinophils; blue arrow indicates basophils). CRIPS, chronic restraint-induced stress. Figure 4 Masson staining of renal sections in Trp53+/− mice. (A), the blue staining indicates collagen fibers (magnification, 200×; scale bar = 100 µM); (B), the average AOD of blue staining in each group. CRIPS, chronic restraint-induced stress; AOD, the average optical density (Integrated optical density/area). * p < 0.05. Figure 5 Expression of FN, detected in renal sections in Trp53+/− mice. (A), the expression of FN was analyzed by immunohistochemistry (magnification, 200×; scale bar = 100 µM); (B), the average AOD of FN in each group. CRIPS, chronic restraint-induced stress; FN, Fibronectin; AOD, the average optical density (Integrated optical density/area). Figure 6 Expression of α-SMA, detected in renal sections in Trp53+/− mice. (A), the expression of α-SMA was analyzed by immunohistochemistry (magnification, 200×; scale bar = 100 µM); (B), the average AOD of α-SMA in each group. CRIPS, chronic restraint-induced stress; AOD, the average optical density (Integrated optical density/area). Figure 7 Expression of α-SMA, detected by Western blotting in Trp53+/− mouse kidneys. (A), the representative images of Western blotting, three replicates in each group; (B), the relative expression of α-SMA in each group. CRIPS, chronic restraint-induced stress. * p < 0.05, ** p < 0.01. ijms-23-04866-t001_Table 1 Table 1 Experimental group. Group Treatment Control (n = 6) Receiving neither chronic restraint nor TBI with 56Fe irradiation 0.1 Gy (n = 6) Receiving only 56Fe-TBI at 0.1 Gy 2.0 Gy (n = 6) Receiving only 56Fe-TBI at 2.0 Gy CRIPS (n = 6) Receiving only chronic restraint to simulate chronic restraint-induced psychological stress CRIPS + 0.1 Gy (n = 6) Receiving 0.1 Gy 56Fe-TBI on day 8 of the 28-day restraint regimen CRIPS + 2.0 Gy (n = 6) Receiving 2.0 Gy 56Fe-TBI on day 8 of the 28-day restraint regimen TBI, total-body irradiation; CRIPS, chronic restraint-induced psychological stress. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kemeny M.E. Schedlowski M. Understanding the interaction between psychosocial stress and immune-related diseases: A stepwise progression Brain Behav. Immun. 2007 21 1009 1018 10.1016/j.bbi.2007.07.010 17889502 2. Schoenfeld T.J. McCausland H.C. Morris H.D. Padmanaban V. Cameron H.A. Stress and Loss of Adult Neurogenesis Differentially Reduce Hippocampal Volume Biol. Psychiatry 2017 82 914 923 10.1016/j.biopsych.2017.05.013 28629541 3. Pandey B.N. Kumar A. Tiwari P. Mishra K.P. Radiobiological basis in management of accidental radiation exposure Int. J. Radiat. Biol. 2010 86 613 635 10.3109/09553001003746059 20673129 4. Li M. Gonon G. Buonanno M. Autsavapromporn N. de Toledo S.M. Pain D. Azzam E.I. Health Risks of Space Exploration: Targeted and Nontargeted Oxidative Injury by High-Charge and High-Energy Particles Antioxid. Redox Signal. 2014 20 1501 1523 10.1089/ars.2013.5649 24111926 5. Duan X. Zhang H. Liu B. Li X.-D. Gao Q.-X. Wu Z.-H. Apoptosis of murine melanoma cells induced by heavy-ion radiation combined with Tp53 gene transfer Int. J. Radiat. Biol. 2008 84 211 217 10.1080/09553000801902117 18300021 6. Furukawa S. Nagamatsu A. Nenoi M. Fujimori A. Kakinuma S. Katsube T. Wang B. Tsuruoka C. Shirai T. Nakamura A.J. Space Radiation Biology for “Living in Space” BioMed Res. Int. 2020 2020 4703286 10.1155/2020/4703286 32337251 7. Madrazo A. Schwarz G. Churg J. Radiation nephritis: A review J. Urol. 1975 114 822 827 10.1016/S0022-5347(17)67152-0 1104899 8. Katsube T. Wang B. Tanaka K. Ninomiya Y. Hirakawa H. Liu C. Maruyama K. Vares G. Liu Q. Kito S. Synergistic Effects of Chronic Restraint-Induced Stress and Low-Dose 56Fe-particle Irradiation on Induction of Chromosomal Aberrations in Trp53-Heterozygous Mice Radiat. Res. 2021 196 100 112 10.1667/RADE-20-00218.1 33901294 9. Wang B. Tanaka K. Katsube T. Ninomiya Y. Vares G. Liu Q. Morita A. Nakajima T. Nenoi M. Chronic restraint-induced stress has little modifying effect on radiation hematopoietic toxicity in mice J. Radiat. Res. 2015 56 760 767 10.1093/jrr/rrv030 26045492 10. Li H. Wang B. Zhang H. Katsube T. Xie Y. Gan L. Apoptosis Induction by Iron Radiation via Inhibition of Autophagy in Trp53+/− Mouse Testes: Is Chronic Restraint-Induced Stress a Modifying Factor? Int. J. Biol. Sci. 2018 14 1109 1121 10.7150/ijbs.22805 29989073 11. Liakopoulos V. Leivaditis K. Eleftheriadis T. Dombros N. The kidney in space Int. Urol. Nephrol. 2012 44 1893 1901 10.1007/s11255-012-0289-7 23001611 12. Sánchez-Solís C.N. Romero E.C. Soto-Rodríguez I. Arteaga-Castañeda M.D.L. De León-Ramírez Y.M. Rodríguez-Antolín J. Nicolás-Toledo L. High-sucrose diet potentiates hyperaldosteronism and renal injury induced by stress in young adult rats Clin. Exp. Pharmacol. Physiol. 2020 47 1985 1994 10.1111/1440-1681.13394 32911579 13. Nastase M.V. Zeng-Brouwers J. Wygrecka M. Schaefer L. Targeting renal fibrosis: Mechanisms and drug delivery systems Adv. Drug Deliv. Rev. 2018 129 295 307 10.1016/j.addr.2017.12.019 29288033 14. Humphreys B.D. Mechanisms of Renal Fibrosis Annu. Rev. Physiol. 2018 80 309 326 10.1146/annurev-physiol-022516-034227 29068765 15. Klaus R. Niyazi M. Lange-Sperandio B. Radiation-induced kidney toxicity: Molecular and cellular pathogenesis Radiat. Oncol. 2021 16 43 10.1186/s13014-021-01764-y 33632272 16. Wei J. Wang B. Wang H. Meng L. Zhao Q. Li X. Xin Y. Jiang X. Radiation-Induced Normal Tissue Damage: Oxidative Stress and Epigenetic Mechanisms Oxidative Med. Cell. Longev. 2019 2019 3010342 10.1155/2019/3010342 17. Wyld M. Morton R. Hayen A. Howard K. Webster A. A Systematic Review and Meta-Analysis of Utility-Based Quality of Life in Chronic Kidney Disease Treatments PLoS Med. 2012 9 e1001307 10.1371/journal.pmed.1001307 22984353 18. Wang A.Y.-M. Kalantar-Zadeh K. Fouque D. Wee P.T. Kovesdy C.P. Price S.R. Kopple J.D. Precision Medicine for Nutritional Management in End-Stage Kidney Disease and Transition to Dialysis Semin. Nephrol. 2018 38 383 396 10.1016/j.semnephrol.2018.05.008 30082058 19. Zhou Y. Chai P. Wang J. Li L. Chen M.H. Wingless/int-1induced secreted protein-1: A new biomarker for renal fibrosis J. Biol. Regul. Homeost. Agents 2021 34 97 103 10.23812/20-459-A 20. Qi W. Chen X. Poronnik P. Pollock C.A. The renal cortical fibroblast in renal tubulointerstitial fibrosis Int. J. Biochem. Cell Biol. 2006 38 1 5 10.1016/j.biocel.2005.09.005 16230044 21. Huang C.-Y. Su C.-T. Chung C.-J. Pu Y.-S. Chu J.-S. Yang H.-Y. Wu C.-C. Hsueh Y.-M. Urinary total arsenic and 8-hydroxydeoxyguanosine are associated with renal cell carcinoma in an area without obvious arsenic exposure Toxicol. Appl. Pharmacol. 2012 262 349 354 10.1016/j.taap.2012.05.013 22659136 22. Wang Z. Zhang B. Chen Z. He Y. Ru F. Liu P. Chen X. The long noncoding RNA myocardial infarction-associated transcript modulates the epithelial-mesenchymal transition in renal interstitial fibrosis Life Sci. 2020 241 117187 10.1016/j.lfs.2019.117187 31863776 23. Huang C.-C. Lin Y.-Y. Yang A.-L. Kuo T.-W. Kuo C.-H. Lee S.-D. Anti-Renal Fibrotic Effect of Exercise Training in Hypertension Int. J. Mol. Sci. 2018 19 613 623 10.3390/ijms19020613 29461477 24. Zhang Y.-L. Qiao S.-K. Wang R.-Y. Guo X.-N. NGAL attenuates renal ischemia/reperfusion injury through autophagy activation and apoptosis inhibition in rats Chem. Biol. Interact. 2018 289 40 46 10.1016/j.cbi.2018.04.018 29704511 25. Xiang C.Y. Yan Y. Zhang D.G. Alleviation of the doxorubicin-induced nephrotoxicity by fasudil in vivo and in vitro J. Pharmacol. Sci. 2021 145 6 15 10.1016/j.jphs.2020.10.002 33357780 26. Huang J. Shang Q.H. Chen C.Y. Effects of short-term high salt diet on tubule epithelial mesenchymal transformation and renal fibrosis in C57BL/6J mice Chin. J. Hypertens. 2020 28 757 766 10.1016/j.jphs.2020.10.002 27. Cohen E.P. Lenarczyk M. Fish B.L. Jia S. Hessner M.J. E Moulder J. Evaluation of Genomic Evidence for Oxidative Stress in Experimental Radiation Nephropathy J. Genet. Disord. Genet. Rep. 2013 2 1000101 10.4172/2327-5790.1000101 24818171 28. Yan Y. Zhang K. Zhou G. Hu W. MicroRNAs Responding to Space Radiation Int. J. Mol. Sci. 2020 21 6603 10.3390/ijms21186603 29. Straub J.M. New J. Hamilton C.D. Lominska C. Shnayder Y. Thomas S.M. Radiation-induced fibrosis: Mechanisms and implications for therapy J. Cancer Res. Clin. Oncol. 2015 141 1985 1994 10.1007/s00432-015-1974-6 25910988 30. Pavlakou P. Dounousi E. Roumeliotis S. Eleftheriadis T. Liakopoulos V. Oxidative Stress and the Kidney in the Space Environment Int. J. Mol. Sci. 2018 19 3176 10.3390/ijms19103176 31. Durante M. Kronenberg A. Ground-based research with heavy ions for space radiation protection Adv. Space Res. 2005 35 180 184 10.1016/j.asr.2004.12.034 15934192 32. Turker M.S. Grygoryev D. Lasarev M. Ohlrich A. Rwatambuga F.A. Johnson S. Dan C. Eckelmann B. Hryciw G. Mao J.-H. Simulated space radiation-induced mutants in the mouse kidney display widespread genomic change PLoS ONE 2017 12 e0180412 10.1371/journal.pone.0180412 28683078 33. Stone H.B. Moulder J.E. Coleman C.N. Ang K.K. Anscher M.S. Barcellos-Hoff M.H. Dynan W.S. Fike J.R. Grdina D.J. Greenberger J.S. Models for evaluating agents intended for the prophylaxis, mitigation and treatment of radiation injuries. Report of an NCI Workshop, December 3–4 2003 Radiat. Res. 2004 162 711 728 10.1667/RR3276 15548121 34. Robbins M.E. Zhao W. Davis C.S. Toyokuni S. Bonsib S.M. Radiation-induced kidney injury: A role for chronic oxidative stress? Micron 2002 33 133 141 10.1016/S0968-4328(01)00006-3 11567882 35. Emami B. Lyman J. Brown A. Coia L. Goitein M. Munzenrider J.E. Shank B. Solin L.J. Wesson M. Tolerance of normal tissue to therapeutic irradiation Int. J. Radiat. Oncol. Biol. Phys. 1991 21 109 122 10.1016/0360-3016(91)90171-Y 2032882 36. Lenarczyk M. Cohen E.P. Fish B.L. Irving A.A. Sharma M. Driscoll C.D. Moulder J.E. Chronic Oxidative Stress as a Mechanism for Radiation Nephropathy Radiat. Res. 2009 171 164 172 10.1667/RR1454.1 19267541

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094942 ijms-23-04942 Article Cell Model of Depression: Reduction of Cell Stress with Mirtazapine https://orcid.org/0000-0002-8231-1560 Correia Ana Salomé 12 Fraga Sónia 345 https://orcid.org/0000-0001-8693-5250 Teixeira João Paulo 345 https://orcid.org/0000-0002-1283-1042 Vale Nuno 167* Gulyaeva Natalia V. Academic Editor Retta Saverio Francesco Academic Editor 1 OncoPharma Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Dr. Plácido da Costa, 4200-450 Porto, Portugal; anncorr07@gmail.com 2 Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Rua de Jorge Viterbo Ferreira, 228, 4050-313 Porto, Portugal 3 Department of Environmental Health, National Institute of Health Dr. Ricardo Jorge, 4000-053 Porto, Portugal; sonia.fraga@insa.min-saude.pt (S.F.); jpft12@gmail.com (J.P.T.) 4 EPIUnit-Instituto de Saúde Pública, University of Porto, 4050-600 Porto, Portugal 5 Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), 4050-600 Porto, Portugal 6 Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Al. Prof. Hernâni Monteiro, 4200-319 Porto, Portugal 7 Associate Laboratory RISE—Health Research Network, Faculty of Medicine, University of Porto, Al. Prof. Hernâni Monteiro, 4200-319 Porto, Portugal * Correspondence: nunovale@med.up.pt 29 4 2022 5 2022 23 9 494208 2 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Depression is a very prevalent and complex disease. This condition is associated with a high rate of relapse, making its treatment a challenge. Thus, an intensive investigation of this disease and its treatment is necessary. In this work, through cell viability assays (MTT and neutral red assays) and alkaline comet assays, we aimed to test the induction of stress in human SH-SY5Y cells through the application of hydrocortisone and hydrogen peroxide and to test the reversal or attenuation of this stress through the application of mirtazapine to the cells. Our results demonstrated that hydrogen peroxide, and not hydrocortisone, can induce cellular stress, as evidenced by DNA damage and a global cellular viability reduction, which were alleviated by the antidepressant mirtazapine. The establishment of a cellular model of depression through stress induction is important to study new possibilities of treatment of this disease using cell cultures. depression SH-SY5Y cells comet assay mirtazapine hydrogen peroxide stress FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operational Programme for Competitiveness and Internationalisation (POCI)Portuguese funds through Fundação para a Ciência e a Tecnologia (FCT)IF/00092/2014/CP1255/CT0004 This research was financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operational Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through Fundação para a Ciência e a Tecnologia (FCT) in the framework of the project IF/00092/2014/CP1255/CT0004 and CHAIR in Onco-Innovation. ==== Body pmc1. Introduction Major depressive disorder is a highly debilitating disease that is very prevalent throughout the world. This disease is characterized by symptoms that include anhedonia, sadness, lack of energy, difficulty in performing daily tasks and fluctuations in one’s weight and sleep cycle. In severe cases, this disorder may even culminate in death by suicide. It is a highly complex and heterogeneous disease in which several biological systems and molecular pathways are involved, making its study very complicated and challenging [1]. Indeed, one of the major problems associated with this pathology is the resistance to treatments and a high rate of relapse when treatments are discontinued, supporting the importance of an intensive and deep investigation of this disease and its therapeutic modalities [1,2]. It is important to establish methodologies for the study of this complex illness. As a behavioral condition, animal studies are crucial. However, a focus on the 3Rs policy of scientific investigation (replacement, reduction, and refinement) is increasingly important [3]. Thus, it is important to implement preliminary study strategies, such as research on cells, namely the neuronal and glial cell lines. Some examples are the rat clonal PC12 pheochromocytoma, human SH-SY5Y neuroblastoma, mouse HT-22 hippocampal, glioma C6 and BV2 microglial cell lines [4]. By using cell models, it is important to focus on biomarkers associated with depression. Thereby, it is possible to study these molecular mechanisms in detail at the cellular level. Theoretically, this type of study can be achieved, for example, with the use of hydrogen peroxide and glucocorticoids as stress inducers in cells, which is observed in vivo and has also been verified in some research studies [5,6,7,8,9,10,11]. In fact, the role of oxidative stress in depression has been studied and recognized. Individuals with depression typically have high levels of oxidative stress as well as low levels of antioxidant defenses, such as ascorbic acid and superoxide dismutase [12]. For example, a recent study on rats highlighted that the administration of N-acetylcysteine, an antioxidant, leads to an inhibition of neuronal injuries through its capacity to reduce oxidative stress, leading to antidepressant effects and supporting the involvement of oxidative stress in major depressive disorder [13]. Furthermore, it is important to mention that the presence of oxygen free radicals leads to the disease’s progression, contributing to the exacerbation of the effects mediated by pro-inflammatory pathways, culminating in an abnormality of brain functions and neuronal signaling [14]. Glucocorticoids (such as cortisol) are also known to be involved in the stress response through the hypothalamus-hypophysis–adrenal (HPA) axis [15]. Indeed, the presence of dysfunctions in this system and the presence of depression are correlated. Several studies demonstrate that chronic glucocorticoid exposure leads to disturbances in the HPA axis, which can lead to depression-like phenotypes [16]. Indeed, cortisol hypersecretion is considered a biological risk factor of depression [17]. In this work, focusing on cell viability and DNA damage, we aimed to test the induction of stress in human SH-SY5Y neuroblastoma cells by exposing cells to glucocorticoids (hydrocortisone, the synthetic form of cortisol) and hydrogen peroxide (H2O2) as well as to test the reversal of this stress through the application of a clinically well-characterized antidepressant drug (mirtazapine) to the cells. Figure 1 illustrates the hypothesis in this work. Considering the obtained results, we proposed the study of depression using an in vitro model based on the oxidative stress that was effectively induced by using H2O2 and reverted by using mirtazapine. With this established model, the preliminary study of major depressive disorder becomes easier, making it possible to repurpose other drugs with potential in the treatment of this condition before the use of animals and more complex models of study. 2. Results 2.1. Effects of Hydrocortisone, Hydrogen Peroxide and Mirtazapine on Cellular Viability To assess the effects of hydrocortisone, H2O2 (Figure 2 and Figure 3) and mirtazapine (Figure 4 and Figure 5) on the viability of SH-SY5Y cells, these compounds were added to the cells in increasing concentrations within a 48 h incubation period. After this period, morphological observations of the cells exposed with the different compounds under study were carried out. Then, the percentages of the viable cells were obtained using different cell viability methodologies: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) and Neutral Red (NR) assays, as described in the materials and methods section. For the H2O2, concentration-response curves (Figure S1) and half-maximal inhibitory concentration (IC50) values were also determined. Our results revealed that hydrocortisone (Figure 2 and Figure 3), at any of the concentrations tested, did not lead to a decrease in cell viability, excluding its use as a stress-provoking agent in the proposed cellular model of stress. However, H2O2 (Figure 2 and Figure 3) significantly decreased cellular viability in a concentration-dependent manner, as observed in both cell viability methodologies. Analyzing the MTT concentration-response curve of this compound, an IC50 value of 132 µM was obtained. Additionally, analyzing the morphologies of the cells treated with this agent, it was clear that higher concentrations of H2O2 led to fewer cells as well as more damaged cells. Regarding the results obtained with the addition of mirtazapine (Figure 4 and Figure 5) to the cells, at any of the concentrations tested, this drug did not lead to a decrease in cell viability, consistent with the mechanism of action as an antidepressant, making this drug an ideal candidate for reversing the stress caused by the stress-provoking agent H2O2. Taken together, these results reveal that H2O2, and not hydrocortisone, is an ideal candidate for the proposed model of stress. Additionally, these results also show that mirtazapine does not lead to a decrease in cell viability and can be used as an antidepressant in the proposed model of stress. 2.2. Effects of the Combination of Mirtazapine with Hydrogen Peroxide in Cellular Viability To evaluate the effects of mirtazapine in combination with H2O2 on the viability of SH-SY5Y cells, mirtazapine was added to the cells in crescent concentrations in combination with H2O2, that was added to the cells in a concentration of 132 µM (representing the obtained IC50 value) for an incubation period of 48 h. After this period, morphological observations of the cells treated with this drug combination were carried out (Figure 6). Then, the percentages of viable cells were determined using the MTT assay (Figure 7), as described in the materials and methods section. Analyzing the obtained results, it can be observed that mirtazapine, at any of the concentrations tested, was able to alleviate the decrease in the cell viability caused by H2O2 alone, leading to an increase in the cell viability to values similar to those obtained in the vehicle. Taken together, these results support the antidepressant activity of mirtazapine. 2.3. Effects of Hydrocortisone, Hydrogen Peroxide, Mirtazapine and the Combination of Mirtazapine with Hydrogen Peroxide on DNA Integrity To assess the effect of hydrocortisone, H2O2, mirtazapine, and the combination of mirtazapine with H2O2 (Figure 8 and Figure 9) on the DNA integrity of the SH-SY5Y cells, these drugs were added to the cells in increasing concentrations for 48 h. After this period, the percentage of DNA damage (% tail intensity) of each cell was obtained using alkaline comet assays, as described in the materials and methods section. Our results revealed that the H2O2 led to DNA damage in a concentration-dependent manner. Indeed, pronounced comet tails can be observed in the cells, representing more DNA damage (Figure 9G–J). The mirtazapine, as well as the hydrocortisone, did not lead to DNA damage, presenting similar values with the vehicle. Regarding the combination of mirtazapine with H2O2, these results confirm that mirtazapine was able to alleviate the DNA damage caused by increasing concentrations of H2O2. All these results support the cell viability studies, highlighting the role of mirtazapine as a drug able to reduce DNA damage caused by H2O2. 3. Discussion Depression is a very prevalent and highly debilitating illness. Two of the major problems associated with this disease lie in a high rate of therapeutic failure and a strong difficulty in studying this condition from its molecular characterization to its treatment [1]. Thus, this work aimed to study depression using a cellular model to allow the study of this disease in a simpler, faster and more reproducible way with respect to the characteristics associated with the use of cell cultures in biomedical research. Therefore, we used well-characterized stress-provoking agents (cortisol and H2O2) related to the pathophysiology of depression [5,6,7,8,9,10,11]. Using these agents, we aimed to test the reversal/attenuation of this cellular stress through the application of antidepressant agents, such as mirtazapine, a known and well-characterized antidepressant [19]. Through cell viability methodologies (MTTs and neutral red assays) and alkaline comet assays, we aimed to characterize this model of cellular stress to make possible the use of other agents that may be promising in the treatment of depression. In summary, our results suggest that H2O2, not hydrocortisone, leads to a general decrease in cellular viability and DNA integrity, phenomena alleviated by the application of mirtazapine. These results were previously confirmed by cell viability techniques [11], but now they are also supported by the alkaline comet assays, highlighting the DNA damage present in the cells (Figure 10). The obtained results with the use of hydrocortisone may be explained by the ability of the cells to defend against the oxidative damage caused by cortisol in short periods. Furthermore, studies revealed that the increase in stress-induced cortisol is more pronounced at longer exposures, leading to increased levels of oxygen free radicals and DNA damage [20]. Thus, under our experimental conditions, cortisol exposure seems to not be enough to cause cell stress to the point of leading to significant damage to DNA (verified by using comet assays) and the cells’ viability (verified by using cell viability assays), even in high concentrations. Using H2O2, it was clear that this agent caused cell damage, compromising cell viability and the integrity of the cells’ DNA. Regarding DNA integrity, previous studies have already reported increased levels of DNA strand-break cells after exposures to H2O2 [21,22,23,24]. However, the concentrations that were used were far higher (up to 1 mM) than the concentration tested in our study (132 μM). Additionally, most of the studies reported short incubation periods for H2O2. Nevertheless, we chose a 48 h period because we could observe if there was any cellular recovery from the damage caused by H2O2 in a longer period than most of the studies in that regard. This compound leads to an increase in oxidative stress, leading to an increase in free oxygen radicals, a phenomenon that is implicated in depression [13]. Thus, the application of H2O2 induces oxidative stress, similar to what is observed in individuals with this condition. In turn, mirtazapine leads to a protective effect on cells against this oxidative stress, highlighting the role of oxidative stress in depression and enabling the study of new therapeutic agents in its attenuation and reversal. Possibly, mirtazapine, by acting on serotonergic receptors [19], induces neuroprotection mechanisms that manage to oppose the harmful effects of H2O2. Furthermore, it is known that this antidepressant drug acts on the gene expressions of pro-apoptotic (Bax and p53) proteins, reducing their expressions [11]. With the application of this drug, there is also evidence of reduced neurite atrophy, a phenomenon that is evidenced in depression [25,26,27]. By establishing a stress model that is similar to the oxidative stress that occurs in individuals with depression, the doors were opened to the studying of other compounds that may be able to reverse or attenuate this damage. This study allows us to broaden the screening of drugs that can be repurposed in the context of depression, allowing the preliminary study of this disease to be more simplified, faster, and reproducible, focusing on individual molecular mechanisms. However, it is always important to keep in mind that depression is a highly complex disease in which several molecular/cellular mechanisms are involved. Several molecular biology studies as well as animal studies are crucial in the context of this disease. 4. Materials and Methods 4.1. Materials Dulbecco’s Modified Eagle’s Medium (DMEM), Fetal Bovine Serum (FBS) and penicillin-streptomycin mixture were obtained from Millipore Sigma (Merck KGaA, Darmstadt, Germany). Thiazolyl blue tetrazolium bromide (MTT; cat. no. M5655), neutral red solution (cat. no. N2889), mirtazapine (cat. no. M0443), hydrocortisone (cat. no. H0888), hydrogen peroxide (30%; Perhydrol™; cat. no. 1.07209), Methyl Methanesulfonate (MMS; cat. no. 129925) and low melting point (LMP) agarose were purchased from Sigma-Aldrich (Merck KGaA, Darmstadt, Germany). SYBR® Gold solution was obtained from Invitrogen (Waltham, MA, USA). Normal Melting Point (NMP; SeaKem LE agarose) agarose was supplied by Lonza (Basel, Switzerland). Formamidopyrimidine-DNA Glycosylase (FPG) enzyme was obtained from New England Biolabs (Ipswich, MA, USA). 4.2. Cell Culture Human SH-SY5Y neuroblastoma cells (American Type Culture Collection, Manassas VA, USA) were maintained at 37 °C in 95% air and 5% CO2. These cells grew in DMEM (10% of FBS and 1% of a mixture of penicillin (1000 U/mL)/streptomycin (10 mg/mL)). SH-SY5Y cells are adherent cells; they were cultured in a monolayer and subcultured when the cells reached a confluence of 75–80%. Before each experiment, trypsin was added to the cells (0.25% trypsin-EDTA). Next, cells were centrifuged (1100 rpm for 5 min; Hettich, Tuttlingen, Germany) and seeded at a density of 4.2 × 104 cells/cm2 in 96-well plates for the viability assays or in 48-well plates for the comet assays. Cells were used with a maximum passage number of 15. 4.3. Cell Treatment Mirtazapine and hydrocortisone were dissolved in DMSO (0.1% in cell culture medium). The concentrations tested in the cells ranged between 0.01 µM–20 µM and 50 µM–500 µM, respectively. H2O2 (10 µM–300 µM) was dissolved in sterilized water (0.1% in cell culture medium). A stock solution of MMS (11.795 M) was prepared in sterilized water and further diluted in cell culture medium to a working concentration of 0.5 mM. For mirtazapine, hydrocortisone and mirtazapine/H2O2 combinations, vehicles were composed of 0.1% DMSO in cell culture medium. For H2O2, vehicle was composed of 0.1% of sterilized water in cell culture medium. All the treatments were tested in a period of 48 h after the cell attachment to the plates except MMS, which was used as a positive control for comet assays, being in contact with the cells for 1 h. For all the combinations tested, both agents were added simultaneously. 4.4. Cell Morphology Assessments Cell morphologies were assessed using the Leica DMI6000 B Automated Microscope (Wetzlar, Germany) to observe and capture images of SH-SY5Y cells after all the treatment conditions. 4.5. Cell Viability Assays After the 48 h cell treatments, cellular viabilities were evaluated by using MTT and NR assays. For the MTT assays, following the removal of the culture medium, 100 µL of MTT (0.5 mg/mL in PBS) was added to each well. Then, protected from the light, the cells were incubated for 3 h. Next, MTT was removed and 100 µL of DMSO was added to each well. Finally, absorbance values (570 nm) were obtained in the automated microplate reader (Tecan Infinite M200, Zurich Switzerland). For the NR assay, following the removal of the culture medium, 100 µL of NR medium (1:100 in culture medium) was added to each well. Then, the cells were incubated for a period of 3 h (protected from the light). After that, the cells were washed in PBS (150 µL), and NR destain solution (50% of 96% ethanol, 49% deionized water and 1% glacial acetic acid; 150 µL per well) was added to the cells. Next, absorbance at 540 nm was obtained in the automated microplate reader. 4.6. Alkaline Comet Assays DNA damage after exposure to the tested agents was assessed by using the alkaline comet assays, as previously described [28]. Cells exposed to MMS (0.5 mM, 1 h) served as positive controls. Briefly, after their exposures, cells were washed with pH 7.4 PBS (without calcium/magnesium), detached by using trypsinization (150 µL/well for 5 min) and suspended in pH 7.4 PBS (without calcium/magnesium). Cells were then centrifuged (300× g for 5 min), the supernatant was discarded and the pellets were resuspended in ice-cold pH 7.4 PBS (without calcium/magnesium). Cells were counted in a Neubauer chamber and 6.0 × 103 cells were transferred to a microcentrifuge tube, centrifuged at 400× g for 5 min and then embedded in 100 μL of 0.6% LMP agarose. Next, 5 μL of each sample was placed on the slides precoated with 1% NMP agarose using a high-throughput system of 12-minigel comet assay unit (Severn Biotech Ltd.®, Kidderminster, UK). Then, after agarose polymerization (4 °C for 10 min), the slides were incubated at 4 °C for 1 h, protected from light in lysis solution (2.5 M of NaCl, 100 mM of Na2EDTA, 10 mM of Tris-base, 250 mM of NaOH at pH of 10 and 1% Triton-X 100). Next, the slides were washed with cold H2O (4 °C for 3 × 5 min) and then immersed in electrophoresis buffer (1 mM of Na2EDTA and 300 mM of NaOH at pH of 13) for 30 min at 4 °C in the electrophoresis platform for DNA unwinding. Then, the electrophoresis ran for 20 min at constant 30 V (0.9 v/cm). At the end of the electrophoresis, the slides were washed with PBS (pH of 7.4; 2 × 5 min) and deionized H2O (1 × 10 min), followed by fixations in 70% and 96% ethanol (5 min each). Then, the slides were dried overnight and protected from light at room temperature. Finally, all the slides were stained with a 1:10,000 dilution of SYBR® Gold in TE buffer (Tris-HCl (10 mM) and EDTA (1 mM) at pH of 7.5–8) for 20 min, observed in the Motic BA410 ELITE series microscope, equipped with a complete EPI fluorescence kit, and analyzed using the image analysis software Comet Assay IV (Perceptive Instruments, Staffordshire, UK). The DNA percentages in the comet tails (% tail intensity) were obtained for 100 cells per experimental condition. 4.7. Statistical and Data Analyses The obtained results were represented as mean ± SEM of three independent cell culture preparations. Statistical analyses between control and treatment conditions were performed with Student’s t-test and one-way ANOVA tests. The differences were considered statistically significant when p value was <0.05. All the statistical analyses, constructions of graphs and calculations of IC50 values were performed using software GraphPad Prism 8 (San Diego, CA, USA). Acknowledgments This article was supported by National Funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., within CINTESIS, R&D Unit (reference UIDB/4255/2020). Ana Salomé Correia also acknowledges FCT for funding her PhD grant (SFRH/BD/146093/2019). Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094942/s1. Click here for additional data file. Author Contributions Conceptualization, N.V.; methodology A.S.C. and S.F.; formal analysis, A.S.C., S.F., J.P.T. and N.V.; investigation, A.S.C., S.F., J.P.T. and N.V.; resources, S.F., J.P.T. and N.V.; writing—original draft preparation, A.S.C.; writing—review and editing, A.S.C., S.F., J.P.T. and N.V.; supervision, N.V.; project administration, N.V.; funding acquisition, N.V. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 In this work, to establish an in vitro model of depression in human SH-SY5Y neuroblastoma cells, two stress inducers (hydrogen peroxide and glucocorticoids, particularly hydrocortisone) were used and antidepressant mirtazapine’s effectiveness against the induced oxidative stress was tested. Created with Biorender.com [18]. Figure 2 Representative images (100× total magnification) of SH-SY5Y cell morphologies after exposures to varied concentrations of hydrocortisone and H2O2. Cells were incubated with (A) vehicle (0.1% DMSO) (B) hydrocortisone 100 µM, (C) hydrocortisone 200 µM, (D) hydrocortisone 300 µM, (E) hydrocortisone 400 µM, (F) hydrocortisone 500 µM, (G) H2O2 50 µM, (H) H2O2 100 µM, (I) H2O2 150 µM, (J) H2O2 200 µM, (K) H2O2 250 µM, and (L) H2O2 300 µM. scale bar = 50 μm. Figure 3 Effect of increasing concentrations of H2O2 and hydrocortisone on the viability of SH-SY5Y cells, for 48 h, obtained by the NR and MTT assays. The results are expressed as the percentage of each respective vehicle (0.1% DMSO for hydrocortisone and 0.1% sterilized water for H2O2) and represent the mean ± SEM of three independent cell culture preparations. Statistically significant * p< 0.05, ** p < 0.01, *** p < 0.001 and **** p < 0.0001 vs. vehicle. Figure 4 Representative images (100× total magnification) of SH-SY5Y cell morphologies after exposures to varied concentrations of mirtazapine. Cells were incubated with (A) vehicle (0.1% DMSO) (B) mirtazapine 0.01 µM, (C) mirtazapine 0.1 µM, (D) mirtazapine 1 µM, (E) mirtazapine 10 µM, and (F) mirtazapine 20 µM. Figure 5 Effects of increasing concentrations of mirtazapine on the viabilities of SH-SY5Y cells for 48 h obtained by NR and MTT assays. The results are expressed as the percentage of vehicle and represent the mean ± SEM of three independent cell culture preparations. Figure 6 Representative images (100× total magnification) of SH-SY5Y cell morphologies after exposures to varied concentrations of the combination of mirtazapine with H2O2. Cells were incubated with (A) vehicle (0.1% DMSO) (B) H2O2 132 µM, (C) H2O2 132 µM + mirtazapine 0.01 µM, (D) H2O2 132 µM + mirtazapine 0.1 µM, (E) H2O2 132 µM + mirtazapine 1 µM (F) H2O2 132 µM + mirtazapine 10 µM, and (G) H2O2 132 µM+ mirtazapine 20 µM. scale bar = 50 μm. Figure 7 Effects of increasing concentrations of mirtazapine in combination with H2O2 on the viabilities of SH-SY5Y cells for 48 h obtained by using an MTT assay. The results are expressed as the percentage of vehicle (0.1% DMSO) and represent the mean ± SEM of three independent cell culture preparations. Statistical significance: **** p < 0.0001 vs. vehicle. Figure 8 Effect of hydrocortisone, H2O2, mirtazapine and the combination of mirtazapine with H2O2 on the DNA integrity of SH-SY5Y cells for 48 h, as assessed by using alkaline comet assays. The results are expressed as the percentage of the tail intensity and represent the mean ± SEM of three independent cell culture preparations. Statistical significance: * p < 0.05 and **** p < 0.0001 vs. each respective vehicle. Figure 9 Representative images (200× total magnification) of SH-SY5Y cells after applications of increasing concentrations of hydrocortisone, H2O2, mirtazapine and the combination of mirtazapine with H2O2. These cells were stained with SYBR Gold, as described in the materials and methods section. Cells were treated with (A) 0.1% sterilized water vehicle, (B) 0.1% DMSO vehicle, (C) MMS 0.5 mM (positive control) (D) hydrocortisone 50 µM, (E) hydrocortisone 100 µM, (F) hydrocortisone 150 µM, (G) H2O2 10 µM, (H) H2O2 66 µM, (I) H2O2 132 µM, (J) H2O2 200 µM, (K) mirtazapine 0.01 µM (L) mirtazapine 20 µM, (M) H2O2 132 µM + mirtazapine 0.01 µM, (N) H2O2 132 µM + mirtazapine 20 µM, and (O) H2O2 200 µM + mirtazapine 20 µM. Figure 10 SH-SY5Y cells treated with (A) H2O2 (132 µM) presented more DNA damage than the cells treated with (B) mirtazapine (20 µM). This damage was evidenced by the comet tails, which reflect more DNA damage. When the (C) combination of mirtazapine (20 µM) and H2O2 (132 µM) was applied to the cells, the DNA damage was attenuated, which was confirmed with the presence of lower intensity of comet tails (compared to H2O2 alone). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Otte C. Gold S.M. Penninx B.W. Pariante C.M. Etkin A. Fava M. Mohr D.C. Schatzberg A.F. Major depressive disorder Nat. Rev. Dis. Prim. 2016 2 16065 10.1038/nrdp.2016.65 27629598 2. Blackburn T.P. Depressive disorders: Treatment failures and poor prognosis over the last 50 years Pharmacol. Res. Perspect. 2019 7 e00472 10.1002/prp2.472 31065377 3. The 3Rs|NC3Rs Available online: https://nc3rs.org.uk/the-3rs (accessed on 25 November 2021) 4. Jantas D. Cell-Based Systems of Depression: An Overview Herbal Medicine in Depression Springer International Publishing Cham, Switzerland 2016 75 117 9783319140216 5. Tian J. Liu S. He X. Xiang H. Chen J. Gao Y. Zhou Y. Qin X. Metabolomics studies on corticosterone-induced PC12 cells: A strategy for evaluating an in vitro depression model and revealing the metabolic regulation mechanism Neurotoxicol. Teratol. 2018 69 27 38 10.1016/j.ntt.2018.07.002 30076895 6. Rossato R.C. Granato A.E.C. Moraes C.D.G.O. Salles G.N. Soares C.P. Neuroprotective effects of taurine on SH-SY5Y cells under hydrocortisone induced stress Res. Soc. Dev. 2021 10 e55510918426 10.33448/rsd-v10i9.18426 7. Lee W.J. Lee G.H. Hur J. Lee H.G. Kim E. Won J.P. Cho Y. Choi M.J. Seo H.G. Taurine and Ginsenoside Rf Induce BDNF Expression in SH-SY5Y Cells: A Potential Role of BDNF in Corticosterone-Triggered Cellular Damage Molecules 2020 25 2819 10.3390/molecules25122819 8. Tian W. Zhao J. Lee J.-H. Akanda M.R. Cho J.-H. Kim S.-K. Choi Y.-J. Park B.-Y. Neuroprotective Effects of Cornus officinalis on Stress-Induced Hippocampal Deficits in Rats and H2O2-Induced Neurotoxicity in SH-SY5Y Neuroblastoma Cells Antioxidants 2019 9 27 10.3390/antiox9010027 9. Xiong Y. Ding H. Xu M. Gao J. Protective effects of asiatic acid on rotenone- or H2O2-induced injury in SH-SY5Y cells Neurochem. Res. 2009 34 746 754 10.1007/s11064-008-9844-0 18802751 10. Wang C.-M. Yang C.-Q. Cheng B.-H. Chen J. Bai B. Orexin-A protects SH-SY5Y cells against H2O2-induced oxidative damage via the PI3K/MEK 1/2 /ERK 1/2 signaling pathway Int. J. Immunopathol. Pharmacol. 2018 32 205873841878573 10.1177/2058738418785739 11. Lieberknecht V. Engel D. Rodrigues A.L.S. Gabilan N.H. Neuroprotective effects of mirtazapine and imipramine and their effect in pro- and anti-apoptotic gene expression in human neuroblastoma cells Pharmacol. Rep. 2020 72 563 570 10.1007/s43440-019-00009-w 32240535 12. Bajpai A. Oxidative Stress and Major Depression J. Clin. Diagn. Res. 2014 8 CC04 10.7860/JCDR/2014/10258.5292 13. Fan C. Long Y. Wang L. Liu X. Liu Z. Lan T. Li Y. Yu S.Y. N-Acetylcysteine Rescues Hippocampal Oxidative Stress-Induced Neuronal Injury via Suppression of p38/JNK Signaling in Depressed Rats Front. Cell. Neurosci. 2020 14 375 10.3389/fncel.2020.554613 33262689 14. Bhatt S. Nagappa A.N. Patil C.R. Role of oxidative stress in depression Drug Discov. Today 2020 25 1270 1276 10.1016/j.drudis.2020.05.001 32404275 15. Russell G. Lightman S. The human stress response Nat. Rev. Endocrinol. 2019 15 525 534 10.1038/s41574-019-0228-0 31249398 16. Qin D. Li Z. Li Z. Wang L. Hu Z. Lü L. Wang Z. Liu Y. Yin Y. Li Z. Chronic Glucocorticoid Exposure Induces Depression-Like Phenotype in Rhesus Macaque (Macaca Mulatta) Front. Neurosci. 2019 13 188 10.3389/fnins.2019.00188 30906247 17. Qin D. Rizak J. Feng X. Yang S. Lü L. Pan L. Yin Y. Hu X. Prolonged secretion of cortisol as a possible mechanism underlying stress and depressive behaviour Sci. Rep. 2016 6 30187 10.1038/srep30187 27443987 18. BioRender Available online: https://biorender.com/ (accessed on 20 January 2022) 19. Correia A.S. Vale N. Antidepressants in Alzheimer’s Disease: A Focus on the Role of Mirtazapine Pharmaceuticals 2021 14 930 10.3390/ph14090930 34577630 20. Şimşek Ş. Yüksel T. Kaplan İ. Uysal C. Aktaş H. The Levels of Cortisol and Oxidative Stress and DNA Damage in Child and Adolescent Victims of Sexual Abuse with or without Post-Traumatic Stress Disorder Psychiatry Investig. 2016 13 616 10.4306/pi.2016.13.6.616 21. Zhao X. Fang J. Li S. Gaur U. Xing X. Wang H. Zheng W. Artemisinin Attenuated Hydrogen Peroxide (H2O2)-Induced Oxidative Injury in SH-SY5Y and Hippocampal Neurons via the Activation of AMPK Pathway Int. J. Mol. Sci. 2019 20 2680 10.3390/ijms20112680 22. Garcimartín A. Merino J.J. González M.P. Sánchez-Reus M.I. Sánchez-Muniz F.J. Bastida S. Benedí J. Organic silicon protects human neuroblastoma SH-SY5Y cells against hydrogen peroxide effects BMC Complement. Altern. Med. 2014 14 384 10.1186/1472-6882-14-384 25293674 23. Czarny P. Kwiatkowski D. Kacperska D. Kawczyńska D. Talarowska M. Orzechowska A. Bielecka-Kowalska A. Szemraj J. Gałecki P. Śliwiński T. Elevated Level of DNA Damage and Impaired Repair of Oxidative DNA Damage in Patients with Recurrent Depressive Disorder Med. Sci. Monit. 2015 21 412 10.12659/MSM.892317 25656523 24. Pohl F. Goua M. Yates K. Bermano G. Russell W.R. Maciel P. Kong Thoo Lin P. Impact of rapeseed pomace extract on markers of oxidative stress and DNA damage in human SH-SY5Y cells J. Food Biochem. 2021 45 e13592 10.1111/jfbc.13592 33349958 25. Qiao H. Li M.X. Xu C. Chen H.B. An S.C. Ma X.M. Dendritic Spines in Depression: What We Learned from Animal Models Neural Plast. 2016 2016 8056370 10.1155/2016/8056370 26881133 26. Fabbretti E. Antognolli G. Tongiorgi E. Amyloid-β Impairs Dendritic Trafficking of Golgi-Like Organelles in the Early Phase Preceding Neurite Atrophy: Rescue by Mirtazapine Front. Mol. Neurosci. 2021 14 100 10.3389/fnmol.2021.661728 34149353 27. Khan A.R. Hansen B. Danladi J. Chuhutin A. Wiborg O. Nyengaard J.R. Jespersen S.N. Neurite atrophy in dorsal hippocampus of rat indicates incomplete recovery of chronic mild stress induced depression NMR Biomed. 2019 32 e4057 10.1002/nbm.4057 30707463 28. Bessa M.J. Brandão F. Fokkens P.H.B. Leseman D.L.A.C. Boere A.J.F. Cassee F.R. Salmatonidis A. Viana M. Vulpoi A. Simon S. In Vitro Toxicity of Industrially Relevant Engineered Nanoparticles in Human Alveolar Epithelial Cells: Air–Liquid Interface versus Submerged Cultures Nanomaterials 2021 11 3225 10.3390/nano11123225 34947574

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092527 jcm-11-02527 Systematic Review Association between Physical Activity and Telomere Length in Women with Breast Cancer: A Systematic Review https://orcid.org/0000-0003-0858-2124 Min Jihee 12† Kim Ji Young 3† Choi Ji Yeong 12 https://orcid.org/0000-0002-9821-6103 Kong In Deok 12* Hargreaves Iain P. Academic Editor 1 Department of Convergence Medicine, Wonju College of Medicine, Yonsei University, Wonju 26426, Korea; jihee8700@yonsei.ac.kr (J.M.); 0527cjy@yonsei.ac.kr (J.Y.C.) 2 Yonsei Institute of Sports Science and Exercise Medicine (YISSEM), Wonju 26426, Korea 3 Department of Physiology, College of Medicine, Korea University, Seoul 02841, Korea; skyditto01@korea.ac.kr * Correspondence: kong@yonsei.ac.kr † These authors contributed equally to this work. 30 4 2022 5 2022 11 9 252702 3 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The association between physical activity and telomere length (TL) has been continuously reported. However, the interplay of physical activity and TL among women with breast cancer has not been elucidated. Thus, the purpose of this systematic review was to synthesize the evidence for the association of physical activity with TL in women with breast cancer. Systematic searches were conducted to identify quantified studies using MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, and Clinical Trials.gov. Five studies were included in this systematic review. Three of the five studies reported that physical activity has a significant relationship in delaying TL shortening, but others observed no association between physical activity and TL in breast cancer survivors. Although the heterogeneous studies acted as limitations in drawing clear conclusions, physical activity strategies show encouraging impacts in delaying TL shortening. To understand the effects of physical activity on TL shortening in breast cancer survivors, further studies are needed considering the tissue site, treatments for breast cancer, DNA extraction methods, and tools for measuring physical activity. breast cancer physical activity exercise telomere length/single-copy gene (T/S) ratio National Research Foundation of Korea (NRF)Korean governmentNRF-2020R1I1A3070520 This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government [No. NRF-2020R1I1A3070520]. ==== Body pmc1. Introduction Telomeres are nucleoprotein structures located at the end of human eukaryotic chromosomes, and they protect against genome instability and damage [1]. Telomeres shorten with each cell cycle in most cells; thus, telomere length (TL) represents the proliferative history of the cell [2,3]. Once telomeres approach a critical size, cell-signaling events occur and induce cellular senescence or apoptosis [4]. TL is negatively associated with biological aging and age-related diseases such as diabetes [5], dementia [6], cancer [7,8], and chronic psychiatric disorders [9,10]. In particular, there is growing evidence of the association between breast cancer and telomere length. Previous studies reported that an increase in inflammatory markers [11], an increased mitochondrial dysfunction [12], and the accumulation [13] of reactive oxygen species not only increase the risk of breast cancer but have a close relationship with telomere shortening. Furthermore, it has been shown that telomere shortening is related to the mutation of the breast cancer susceptibility gene 2 (BRCA2), which is highly associated with the recurrence of breast cancer [14]. A recent review reported that TL could be a valuable prognostic marker of breast cancer despite major methodological differences in measuring TL [15]. Physical activity and exercise are important modifiable factors in breast cancer prevention [16], prognosis [17,18], and mortality [19]. They also have a strong association with delayed telomere shortening. A meta-analysis revealed that active individuals had significantly longer telomeres compared to inactive individuals regardless of the intensity of exercise (mean difference 0.15, 95% CI 0.05–0.24, I2 = 99%) [20]. However, studies on the effect of physical activity or exercise on TL in breast cancer survivors are limited, and inconsistent results have been obtained [21,22,23,24,25]. Therefore, we aimed to comprehensively analyze the association and effect of physical activity or exercise on delaying telomere shortening in women with breast cancer. 2. Materials and Methods 2.1. Search Strategy The current study protocol was registered in the PROSPERO database (No. CRD42021253013), and the study was conducted according to the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) checklist [26]. We searched the following databases: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library), Web of Science, and http://ClinicalTrials.gov (accessed on 23 April 2021) from inception up to April 2021. We also reviewed the reference lists of recent systematic reviews. All articles that assessed the relationship between physical activity and TL or the effects of exercise on TL in breast cancer survivors were included in this review. The search was performed using the following terms: “breast cancer” AND “physical activity” OR “exercise” AND “telomere length”. The full search strategy is available in the Table S1. This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. 2.2. Eligibility Criteria We included studies that (1) were quantitative studies, including cross-sectional, case-control, and intervention studies, and (2) reported TL as mean ± standard deviation or median (interquartile range) or TL/single-copy gene (T/S) ratio. 2.3. Data Extraction and Quality Assessment Two reviewers (J.M. and J.K.) independently screened all titles, abstracts, and full texts to identify studies based on the inclusion criteria using the Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia, www.covidence.org accessed from 25 April 2021 to 7 May 2021). Any disagreement between the reviewers was resolved through discussion. The information obtained from each selected study included the first author’s name, year of publication, study design, population, patients’ ages, method of TL evaluation, tissue where TL measurement was conducted, tool for assessing physical activity, intervention (i.e., type of exercise, frequency, intensity, time), main results, and any other information considered relevant. The quality of eligible studies was assessed with the Newcastle-Ottawa Scale (NOS). Considering the different study designs, we used three versions of the NOS for randomized controlled trials, cross-sectional studies, and case-control studies, respectively [27]. NOS scales for non-randomized studies and randomized controlled trials consist of three domains: selection, comparability, and outcome/exposure. We defined NOS ≥ 7 as high quality and 4 < NOS < 7 as low to moderate quality. 3. Results 3.1. Study Search and Selection A total of 331 studies were retrieved using the search strategy (Table S1), of which 293 were retained after the title and abstract were screened and duplicates were removed. Of these 293 studies, 269 were excluded because they were considered non-relevant. After a full-text review of the 24 papers considered relevant, 19 studies were excluded (2 with duplicate data, 4 without TL results, 3 conference abstracts, and 8 protocol, editorial papers, and review papers). Finally, 5 studies (2099 participants) were included in this review (Figure 1). 3.2. Description of the Studies and Quality Assessment Table 1 shows the summary of the included studies and the results of the quality assessment. Of the five studies, two were randomized controlled trials, two were cross-sectional studies, and one was a case-control study. For the TL assessment, three studies used quantitative-polymerase chain reaction, one used a fluorescence in situ hybridization assay, and one used the terminal restriction fragment method. The mean NOS score was 6.2 (range: 5–7), and all included studies had moderate to high scores (Table 1). 3.3. Effects of Exercise on Telomere Length in Women with Breast Cancer Of the two randomized controlled trial studies, one reported that exercise intervention had a significant effect on delaying TL shortening, while the other reported no intervention effect on TL (Table 2). Santa-Maria et al. [21] conducted a 12-month web-based exercise intervention on 96 obese breast cancer survivors treated in their region. The intervention group received a total of 21 phone consultations consisting of 20 min weight-loss counseling once a week for the first 3 months and once a month for the remaining 9 months. Professional exercise coaches monitored the exercise log, meal log, and weight on the web-based platform. The control group was advised by medical staff to maintain a healthy weight and was provided with weight loss consultations from exercise professionals once. After a 6-month intensive lifestyle intervention, TL in the intervention group reduced by 3% while TL in the usual care group reduced by 5% (p > 0.05). In addition, when classifying by stage of breast cancer, stage 0 or 1 showed a significantly lower reduction in TL for the intervention group than for the control group after 6 months (p < 0.05). However, there were no significant differences between the groups for breast cancer survivors who were diagnosed with cancer exceeding stage 2. Sanft et al. [24] conducted an exercise intervention on 151 obese breast cancer survivors who had been involved in dietary regulation and exercise to achieve weight loss over 6 months. The weight loss strategy included attaining 150 min/week of moderate-intensity activity and 10,000 steps per day as well as reducing calories to 1200–2000 kcal/day. In addition, the patients were advised to reduce dietary fat to <25% of the total energy intake and participate in behavior modification sessions once or twice every month. No significant difference was noted in the change in TL between the intervention and control groups. In addition, the TL was not significantly associated with weight loss or chemotherapy. 3.4. Association between Physical Activity and Telomere Length in Women with Breast Cancer Three cross-sectional or case-control studies were conducted to analyze the associations between physical activity or exercise and TL among breast cancer patients or survivors (Table 3). Two studies showed a significant quantitative correlation between physical activity and TL in breast cancer patients, while one reported that no association existed between exercise and TL. A study of 162 breast cancer patients, who were scheduled to undergo surgery, identified linear trends in the positive association between total physical activity and TL (p < 0.05). Moreover, linear trends for increasing TL were observed for physical activity at the transportation-related physical activity (p < 0.05). However, age, stage of cancer, and menopausal status were not significantly associated with TL [27]. Garland et al. [22] used the International Physical Activity Questionnaire (IPAQ) to analyze the association between physical activity and TL among 392 postmenopausal breast cancer survivors. Compared to those who participated in any physical activity, breast cancer survivors who participated in moderate to vigorous physical activity had significantly longer TL (p < 0.05). However, a case-control study by Qu et al. [25] announced no significant association between TL and exercise. 4. Discussion This systematic review was conducted to clarify the association between physical activity and TL in breast cancer patients and survivors. Five papers were reviewed and there was difficulty in synthesizing the research results because of heterogeneity between the studies. Previous studies reported that physical activity may compensate for shortened TL in cancer survivors [24,28,29,30]. Physical activity may alleviate the decrease in TRF-2 [31]. Furthermore, exercise can help reduce oxidative stress [32] and inflammatory responses [21] which contribute to telomere damage. The stress response can damage cells, releasing damaged cell components, while exercise promotes autophagy [33]. Increased physical activity has been reported to reduce factors related to oxidative stress and inflammation, such as high-sensitivity C-reactive protein, insulin resistance, interleukin-6, tumor necrosis factor-alpha, granulocyte colony-stimulating factor, and F2-isoprostane [11,34,35]. Although we examined the correlation between physical activity and TL of breast cancer patients and survivors, it was challenging to derive consistent results owing to interstudy heterogeneity. There are three prominent reasons for why the results differed among the studies. First, the effect of the mediator variables on the length of the telomeres should be considered. Factors such as ethnicity [36], cancer stage distribution [37], radiation therapy [38], chemotherapy [39], and menopause [40] affect breast cancer prognosis and treatment and are also related to TL. In addition, breast cancer survivors experience a mix of both cancer- and metabolic- related problems. Heo, J et al. [41] reported that 36.7% of breast cancer survivors had been newly diagnosed with comorbidities such as diabetes, hypertension, and metabolic syndrome. Second, we could consider the difference in intervention effectiveness across studies. In our extracted intervention studies, the participants of both studies [21,24] experienced significant weight loss. While 20% of the participants showed a reduction in their body fat by more than 5% in the study by Sanft et al. [24], change in body composition was not reported in the study by Santa-Maria et al. [21]. If the participants’ weight loss in the Santa-Maria et al. [21] was derived from muscle reduction, the effect could be considered relatively weak. As breast cancer prognosis is highly related to body fat and muscle, it is necessary to carefully monitor body composition rather than simply focus on weight loss. Third, there were differences in the evaluation of TL and physical activity due to a variety of measurement tools. Diverse methods were used for the TL analysis in our extracted studies, and the specimen types employed were also different. Generally, TL could differ depending on the tissue [42] and the analysis approach [43]. In this review, three out of five studies used the qPCR method for the evaluation of TL. qPCR has advantages because (1) TL can be measured even in small amounts of DNA and (2) the process is less labor-intensive. However, it has a limitation, since (1) there are variations between and within “batches” and (2) there is a lack of reference standards. The TRF method is the golden standard, but it has the cons of intensive labor and requires a large amount of DNA [44]. In addition, the whole blood and PBMCs have good DNA yield and quality, while salivary samples could destabilize DNA yields depending on temperature [45]. In the cross-sectional studies, the heterogeneity of the research results arose from the difference in the physical activity measurement tools that were used. The two cross-sectional studies analyzed the amount of physical activity using the Past Year Total Physical Activity Questionnaire (PYTPAQ) and the IPAQ short form, respectively. Since the amount of physical activity was measured using the questionnaires, the results may have been subject to self-reporting bias. Indeed, the contents of the questionnaires such as “physical activity domain” or “intensity”, and the recall period such as “during the past year” or “during the last 7 days”, could affect the amount of physical activity declared. Lee et al. [43] showed that questionnaires tend to overestimate the amount of physical activity performed by subjects compared to when an accelerometer is used. Therefore, more studies need to analyze the association between the intensity of physical activity and TL with an accelerometer. The current study has several limitations. First, there is heterogeneity among the extracted studies. There are differences in the specimen, characteristics of participants, and variability of measurement tools in each study. Secondly, we should be cautious of generalizing the results, given that the included studies were exclusively published in English. Third, the method used to search the literature and retrieve from published articles may have caused reporting bias. Despite the limitations, it is meaningful in that it confirmed the tendency of the association between physical activity or exercise and the TL of breast cancer survivors. Future studies need to clarify the effects of various confounding variables such as extracted tissues, characteristics of the participants, treatment modalities for breast cancer, and physical activity measurement tools. In addition, rigorous efforts are required to address existing challenges associated with TL sample storage and processing in all tissue types to ensure reproducibility and reliability of telomere samples and analytical methods. Acknowledgments The authors would like to thank Myung Ha Kim (librarian) for help with the systematic review search. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm11092527/s1, Table S1: Search strategy. Click here for additional data file. Author Contributions Conceptualization, J.M. and J.Y.K.; methodology, J.M., J.Y.C. and I.D.K.; writing—original draft preparation, J.M.; writing—review and editing, J.M., J.Y.C. and I.D.K., visualization, J.M.; supervision, I.D.K.; funding acquisition, I.D.K. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PRISMA flow diagram for systematic review. jcm-11-02527-t001_Table 1 Table 1 Characteristics and quality assessment of included studies. Author (Year) Country Study Design Number of Subject Specimen Type Method of Evaluation of Telomere Quality Assessment Santa-Maria, C. A. et al. (2020) [21] USA Randomized controlled trial (RCT) 96 breast cancer survivors Lymphocytes and granulocytes Fluorescence in situ hybridization (FISH) assay 5 Sanft, T. et al. (2018) [24] USA Randomized controlled trial (RCT) 151 breast cancer survivors Peripheral blood samples Quantitative-polymerase chain reaction (qPCR), T/S 6 Ennour-Idrissi, K., et al. (2016) [27] Canada Cross-sectional study 164 women who underwent surgery for unilateral breast cancer Peripheral white blood cells Quantitative-polymerase chain reaction (qPCR), T/S 7 Garland, S. N. et al. (2014) [22] USA Cross-sectional study 392 postmenopausal women with stage I–III breast cancer Peripheral blood mononuclear cells (PBMCs) Terminal restriction fragment (TRF) 7 Qu, S. et al. (2013) [25] China Case-control study 1296 (601 incident breast cancer cases, 605 control) Peripheral blood samples Monochrome multiplex quantitative polymerase chain reaction (qPCR), T/S 6 PBMCs—peripheral blood mononuclear cell, qPCR—real-time quantitative PCR detecting system, TRF—terminal restriction fragment, T/S ratio—telomere (T), single copy gene (S) ratio T/S. Quality assessments were conducted using Newcastle-Ottawa Scale (NOS). jcm-11-02527-t002_Table 2 Table 2 The summary of the included randomized controlled trials studies. Author (Year) Subject Age Purpose of Intervention Contents of Intervention Duration Result Santa-Maria, C. A. et al. (2020) [21] 96 obese a breast cancer survivors with stage I–III breast cancer Median (range) intervention 53 (33–71) self-directed 55 (30–73) Weight loss POWER-Remote- Frequency: weekly for 3 months, monthly for additional 9 months - Intensity: unknown - Type: telephone and web-based platform - Time: unknown 12-month - NS. Change TL: 0.1 ± 0.7 in POWER-remote group, 0.1 ± 0.7 in self-directed group (p = 0.76) Sanft, T. et al. (2018) [24] 151 obese a breast cancer survivors Mean ± SD 57.8 ± 7.7 Weight loss Weight loss intervention group (WL) ㆍDiet: reducing calorie intake ㆍPhysical activity- Frequency: individualized counseling sessions weekly - Intensity: moderate intensity - Type: combined - Time: 30 min 6-month - TL shortening in total: NS. Change TL: −3% in WL vs. −5% in control (p = 0.12). - TL shortening in stage 0/1: WL < Control Change TL: −7% in WL vs. −8% in control (p = 0.01). a Body mass index ≥ 25 kg/m2, abbreviations: NS—non-significant, TL—telomere length. jcm-11-02527-t003_Table 3 Table 3 The summary of the included non-randomized controlled trials studies. Author (Year) Study Design Subject Age PA Measurement Tool Result Ennour-Idrissi, K., et al. (2016) [27] Cross-sectional study 162 women who underwent surgery for unilateral breast cancer Mean ± SD 52.6 ± 7.9 - Past Year Total Physical Activity Questionnaire - PA↑ = TL↑ TPA (rs = 0.17, p = 0.033), occupational PA (rs = 0.15, p = 0.054) and transportation-related PA (rs = 0.19, p = 0.019). Garland, S. N. et al. (2014) [22] Cross-sectional study 392 postmenopausal women with stage I–III breast cancer Mean ± SD 61.97 ± 10.36 - Physical activity: International Physical Activity Questionnaire (IPAQ) - TL shortening: No PA > MVPA (mean 5.84 kb versus 6.11 kb; p = 0.006).- PA↓ = TL↓ (Adjusted coefficient (Adj β) = −0.22; 95% CI, −0.41 to −0.03; p = 0.03) Qu, S. et al. (2013) [25] Case-control study 601 incident breast cancer cases 695 matched as controls Mean ± SD 52.7 ± 8.8 in case 53.4 ± 9.0 in control - Unknown - NS. (exercise and telomere length p for interaction = 0.612) Abbreviations: SD—standard deviation, NS—non-significant, TL—telomere length, PA—physical activity, TPA—total physical activity, MVPA—moderate to vigorous physical activity, CI—confidence interval, PA↑—high levels of physical activity, PA↓—low level of physical acitivity, TL↑—long TL, TL↓—short TL. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Blackburn E.H. Epel E.S. Lin J. Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection Science 2015 350 1193 1198 10.1126/science.aab3389 26785477 2. Calado R.T. Young N.S. Telomere diseases N. Engl. J. Med. 2009 361 2353 2365 10.1056/NEJMra0903373 20007561 3. Turner K.J. Vasu V. Griffin D.K. Telomere Biology and Human Phenotype Cells 2019 8 73 10.3390/cells8010073 30669451 4. Zakian V.A. Telomeres: The beginnings and ends of eukaryotic chromosomes Exp. Cell Res. 2012 318 1456 1460 10.1016/j.yexcr.2012.02.015 22391099 5. Cheng F. Carroll L. Joglekar M.V. Januszewski A.S. Wong K.K. Hardikar A.A. Jenkins A.J. Ma R.C.W. Diabetes, metabolic disease, and telomere length Lancet Diabetes Endocrinol. 2021 9 117 126 10.1016/S2213-8587(20)30365-X 33248477 6. Liu Y. Ma C. Li P. Ma C. He S. Ping F. Zhang H. Li W. Xu L. Li Y. Leukocyte Telomere Length Independently Predicts 3-Year Diabetes Risk in a Longitudinal Study of Chinese Population Oxid. Med. Cell Longev. 2020 2020 9256107 10.1155/2020/9256107 32215181 7. Ma H. Zhou Z. Wei S. Liu Z. Pooley K.A. Dunning A.M. Svenson U. Roos G. Hosgood H.D. 3rd Shen M. Shortened telomere length is associated with increased risk of cancer: A meta-analysis PLoS ONE 2011 6 e20466 10.1371/journal.pone.0020466 21695195 8. Zhang C. Chen X. Li L. Zhou Y. Wang C. Hou S. The Association between Telomere Length and Cancer Prognosis: Evidence from a Meta-Analysis PLoS ONE 2015 10 e0133174 10.1371/journal.pone.0133174 26177192 9. Guo Y. Yu H. Leukocyte Telomere Length Shortening and Alzheimer’s Disease Etiology J. Alzheimer’s Dis. 2019 69 881 885 10.3233/JAD-190134 31156167 10. Lin P.Y. Huang Y.C. Hung C.F. Shortened telomere length in patients with depression: A meta-analytic study J. Psychiatr. Res. 2016 76 84 93 10.1016/j.jpsychires.2016.01.015 26919486 11. O’Donovan A. Pantell M.S. Puterman E. Dhabhar F.S. Blackburn E.H. Yaffe K. Cawthon R.M. Opresko P.L. Hsueh W.C. Satterfield S. Cumulative inflammatory load is associated with short leukocyte telomere length in the Health, Aging and Body Composition Study PLoS ONE 2011 6 e19687 10.1371/journal.pone.0019687 21602933 12. Zhu Y. Liu X. Ding X. Wang F. Geng X. Telomere and its role in the aging pathways: Telomere shortening, cell senescence and mitochondria dysfunction Biogerontology 2019 20 1 16 10.1007/s10522-018-9769-1 30229407 13. Chakravarti D. LaBella K.A. DePinho R.A. Telomeres: History, health, and hallmarks of aging Cell 2021 184 306 322 10.1016/j.cell.2020.12.028 33450206 14. Thorvaldsdottir B. Aradottir M. Stefansson O.A. Bodvarsdottir S.K. Eyfjord J.E. Telomere Length Is Predictive of Breast Cancer Risk in BRCA2 Mutation Carriers Cancer Epidemiol. Biomark. Prev. 2017 26 1248 1254 10.1158/1055-9965.EPI-16-0946 15. Ennour-Idrissi K. Maunsell E. Diorio C. Telomere Length and Breast Cancer Prognosis: A Systematic Review Cancer Epidemiol. Biomark. Prev. 2017 26 3 10 10.1158/1055-9965.EPI-16-0343 16. Chen X. Wang Q. Zhang Y. Xie Q. Tan X. Physical Activity and Risk of Breast Cancer: A Meta-Analysis of 38 Cohort Studies in 45 Study Reports Value Health 2019 22 104 128 10.1016/j.jval.2018.06.020 30661625 17. Peterson L.L. Ligibel J.A. Physical Activity and Breast Cancer: An Opportunity to Improve Outcomes Curr. Oncol. Rep. 2018 20 50 10.1007/s11912-018-0702-1 29713835 18. Patterson R.E. Cadmus L.A. Emond J.A. Pierce J.P. Physical activity, diet, adiposity and female breast cancer prognosis: A review of the epidemiologic literature Maturitas 2010 66 5 15 10.1016/j.maturitas.2010.01.004 20097494 19. Nascimento W. Ferrari G. Martins C.B. Rey-Lopez J.P. Izquierdo M. Lee D.H. Giovannucci E.L. Rezende L.F.M. Muscle-strengthening activities and cancer incidence and mortality: A systematic review and meta-analysis of observational studies Int. J. Behav. Nutr. Phys. Act. 2021 18 69 10.1186/s12966-021-01142-7 34051796 20. Lin X. Zhou J. Dong B. Effect of different levels of exercise on telomere length: A systematic review and meta-analysis J. Rehabil. Med. 2019 51 473 478 10.2340/16501977-2560 31093683 21. Santa-Maria C.A. Coughlin J.W. Sharma D. Armanios M. Blackford A.L. Schreyer C. Dalcin A. Carpenter A. Jerome G.J. Armstrong D.K. The Effects of a Remote-based Weight Loss Program on Adipocytokines, Metabolic Markers, and Telomere Length in Breast Cancer Survivors: The POWER-Remote Trial Clin. Cancer Res. 2020 26 3024 3034 10.1158/1078-0432.CCR-19-2935 32071117 22. Garland S.N. Johnson B. Palmer C. Speck R.M. Donelson M. Xie S.X. DeMichele A. Mao J.J. Physical activity and telomere length in early stage breast cancer survivors Breast Cancer Res. 2014 16 413 10.1186/s13058-014-0413-y 25074648 23. Hagstrom A.D. Denham J. The effect of resistance training on telomere length in women recovering from breast cancer J. Funct. Morphol. Kinesiol. 2018 3 9 10.3390/jfmk3010009 24. Sanft T. Usiskin I. Harrigan M. Cartmel B. Lu L. Li F.Y. Zhou Y. Chagpar A. Ferrucci L.M. Pusztai L. Randomized controlled trial of weight loss versus usual care on telomere length in women with breast cancer: The lifestyle, exercise, and nutrition (LEAN) study Breast Cancer Res. Treat. 2018 172 105 112 10.1007/s10549-018-4895-7 30062572 25. Qu S. Wen W. Shu X.O. Chow W.H. Xiang Y.B. Wu J. Ji B.T. Rothman N. Yang G. Cai Q. Association of leukocyte telomere length with breast cancer risk: Nested case-control findings from the Shanghai Women’s Health Study Am. J. Epidemiol. 2013 177 617 624 10.1093/aje/kws291 23444102 26. Moher D. Shamseer L. Clarke M. Ghersi D. Liberati A. Petticrew M. Shekelle P. Stewart L.A. Group P.-P. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement Syst. Rev. 2015 4 1 10.1186/2046-4053-4-1 25554246 27. Ennour-Idrissi K. Tetu B. Maunsell E. Poirier B. Montoni A. Rochette P.J. Diorio C. Association of Telomere Length with Breast Cancer Prognostic Factors PLoS ONE 2016 11 e0161903 10.1371/journal.pone.0161903 27571273 28. Wang Z. Zhang Z. Guo Y. Shui H. Liu G. Jin T. Wang H. Shorter Telomere Length Is Associated with Increased Breast Cancer Risk in a Chinese Han Population: A Case-Control Analysis J. Breast Cancer 2018 21 391 398 10.4048/jbc.2018.21.e52 30607160 29. Dickinson S.L. Golzarri-Arroyo L. Brown A.W. McComb B. Kahathuduwa C.N. Allison D.B. Change in study randomization allocation needs to be included in statistical analysis: Comment on ‘Randomized controlled trial of weight loss versus usual care on telomere length in women with breast cancer: The lifestyle, exercise, and nutrition (LEAN) study’ Breast Cancer Res. Treat. 2019 175 263 264 10.1007/s10549-019-05155-6 30721442 30. Nomikos N.N. Nikolaidis P.T. Sousa C.V. Papalois A.E. Rosemann T. Knechtle B. Exercise, Telomeres, and Cancer: “The Exercise-Telomere Hypothesis” Front. Physiol. 2018 9 1798 10.3389/fphys.2018.01798 30618810 31. Khan S. Chuturgoon A.A. Naidoo D.P. Telomeres and atherosclerosis Cardiovasc. J. Afr. 2012 23 563 571 10.5830/CVJA-2012-056 23192261 32. Friedenreich C.M. Pialoux V. Wang Q. Shaw E. Brenner D.R. Waltz X. Conroy S.M. Johnson R. Woolcott C.G. Poulin M.J. Effects of exercise on markers of oxidative stress: An Ancillary analysis of the Alberta Physical Activity and Breast Cancer Prevention Trial BMJ Open Sport Exerc. Med. 2016 2 e000171 10.1136/bmjsem-2016-000171 27900199 33. Dethlefsen M.M. Halling J.F. Moller H.D. Plomgaard P. Regenberg B. Ringholm S. Pilegaard H. Regulation of apoptosis and autophagy in mouse and human skeletal muscle with aging and lifelong exercise training Exp. Gerontol. 2018 111 141 153 10.1016/j.exger.2018.07.011 30030137 34. Campbell P.T. Gross M.D. Potter J.D. Schmitz K.H. Duggan C. McTiernan A. Ulrich C.M. Effect of exercise on oxidative stress: A 12-month randomized, controlled trial Med. Sci. Sports Exerc. 2010 42 1448 1453 10.1249/MSS.0b013e3181cfc908 20139793 35. Zhao J. Miao K. Wang H. Ding H. Wang D.W. Association between telomere length and type 2 diabetes mellitus: A meta-analysis PLoS ONE 2013 8 e79993 10.1371/journal.pone.0079993 24278229 36. Brown L. Needham B. Ailshire J. Telomere Length Among Older U.S. Adults: Differences by Race/Ethnicity, Gender, and Age J. Aging Health 2017 29 1350 1366 10.1177/0898264316661390 27469599 37. Fordyce C.A. Heaphy C.M. Bisoffi M. Wyaco J.L. Joste N.E. Mangalik A. Baumgartner K.B. Baumgartner R.N. Hunt W.C. Griffith J.K. Telomere content correlates with stage and prognosis in breast cancer Breast Cancer Res. Treat. 2006 99 193 202 10.1007/s10549-006-9204-1 16752076 38. Gallicchio L. Gadalla S.M. Murphy J.D. Simonds N.I. The Effect of Cancer Treatments on Telomere Length: A Systematic Review of the Literature J. Natl. Cancer Inst. 2018 110 1048 1058 10.1093/jnci/djy189 30272225 39. Dalgard C. Benetos A. Verhulst S. Labat C. Kark J.D. Christensen K. Kimura M. Kyvik K.O. Aviv A. Leukocyte telomere length dynamics in women and men: Menopause vs. age effects Int. J. Epidemiol. 2015 44 1688 1695 10.1093/ije/dyv165 26385867 40. Friedrich U. Griese E. Schwab M. Fritz P. Thon K. Klotz U. Telomere length in different tissues of elderly patients Mech. Ageing Dev. 2000 119 89 99 10.1016/S0047-6374(00)00173-1 11080530 41. Heo J. Chun M. Oh Y.T. Noh O.K. Kim L. Metabolic comorbidities and medical institution utilization among breast cancer survivors: A national population-based study Korean J. Intern. Med. 2020 35 421 428 10.3904/kjim.2018.172 31480826 42. Lai T.P. Wright W.E. Shay J.W. Comparison of telomere length measurement methods Philos. Trans. R Soc. Lond. B Biol. Sci. 2018 373 20160451 10.1098/rstb.2016.0451 29335378 43. Lee P.H. Macfarlane D.J. Lam T.H. Stewart S.M. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): A systematic review Int. J. Behav. Nutr. Phys. Act. 2011 8 115 10.1186/1479-5868-8-115 22018588 44. Montpetit A.J. Alhareeri A.A. Montpetit M. Starkweather A.R. Elmore L.W. Filler K. Mohanraj L. Burton C.W. Menzies V.S. Lyon D.E. Telomere length: A review of methods for measurement Nurs. Res. 2014 63 289 299 10.1097/NNR.0000000000000037 24977726 45. Lin J. Smith D.L. Esteves K. Drury S. Telomere length measurement by qPCR—Summary of critical factors and recommendations for assay design Psychoneuroendocrino 2019 99 271 278 10.1016/j.psyneuen.2018.10.005

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091197 animals-12-01197 Article Establishment and Application of an Indirect Enzyme-Linked Immunosorbent Assay for Measuring GPI-Anchored Protein 52 (P52) Antibodies in Babesia gibsoni-Infected Dogs Liu Qin 12 Zhan Xueyan 12 Li Dongfang 12 Zhao Junlong 123 Wei Haiyong 4 https://orcid.org/0000-0002-0260-7813 Alzan Heba 567 He Lan 123* Ma Guangxu Academic Editor Xie Yue Academic Editor 1 State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; lq1319529141@163.com (Q.L.); xueyan09172022@163.com (X.Z.); dongfang0216@webmail.hzau.edu.cn (D.L.); zhaojunlong@mail.hzau.edu.cn (J.Z.) 2 Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Wuhan 430070, China 3 Key Laboratory of Development of Veterinary Diagnostic Products, Ministry of Agriculture of the People’s Republic of China, Wuhan 430070, China 4 Liuzhou Animal Husbandry Station in Guangxi Province, Liuzhou 545025, China; lzsxmz@126.com 5 Department of Veterinary Microbiology and Pathology, College of Veterinary Medicine, Washington State University, Pullman, WA 99163, USA; heba.alzan@wsu.edu 6 Parasitology and Animal Diseases Department, National Research Center, Dokki, Giza 12622, Egypt 7 Tick and Tick-Borne Disease Research Unit, National Research Center, Dokki, Giza 12622, Egypt * Correspondence: helan@mail.hzau.edu.cn 06 5 2022 5 2022 12 9 119712 1 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary In this study, a novel BgGPI52-WH antigen was identified and evaluated as an immunodiagnostic candidate. An indirect ELISA was established based on the BgGPI52-WH antigen. The results showed that the iELISA had good sensitivity, specificity and reproducibility, and the signal could be detected as early as the sixth day after infection. Clinical samples were tested using the established method, and 11.41% of the samples were positive. The results suggested that BgGPI52-WH is a good immunodiagnostic marker and the iELISA is a practical method for early diagnosis. Abstract Babesia gibsoni is a malaria-like protozoan that parasitizes the red blood cells of canids to cause babesiosis. Due to its high expression and essential function in the survival of parasites, the Glycosylphosphatidylinositol (GPI) anchor protein family is considered an excellent immunodiagnostic marker. Herein, we identified a novel GPI-anchored protein named as BgGPI52-WH with a size of 52 kDa; the recombinant BgGPI52-WH with high antigenicity and immunogenicity was used as a diagnostic antigen to establish a new iELISA method. The iELISA had a sensitivity of 1:400, and no cross-reaction with other apicomplexan parasites occurred. We further demonstrated that the degree of variation was less than 10% using the same samples from the same or different batches of an enzyme-labeled strip. It was found that the method was able to detect early infection (6 days after infection) in the sera of the B. gibsoni-infected experimental dogs in which antibody response to rBgGPI52-WH was evaluated. Clinical sera from pet hospitals were further tested, and the average positive rate was about 11.41% (17/149). The results indicate that BgGPI52-WH is a reliable diagnostic antigen, and the new iELISA could be used as a practical method for the early diagnosis of B. gibsoni. babesiosis Babesia gibsoni GPI anchor protein ELISA diagnosis method National Natural Science Foundation of China31930108 Top-notch Young Talent Supporting Program to Lan HeThis work was supported by the National Natural Science Foundation of China (Grant No. 31930108), and Top-notch Young Talent Supporting Program to Lan He. ==== Body pmc1. Introduction Babesiosis in dogs is a febrile tick-born disease caused by infections from the Babesia species. These parasites are parasitic in the red blood cells (RBCs) of dogs [1,2]. Babesia gibsoni (B. gibsoni) is one of the main Babesia species that causes babesiosis in dogs. Dogs infected with Babesia may have hyperacute infections, acute infections, or more commonly chronic infections [3,4]. The main clinical symptoms are fever, hemolytic anemia, and hemoglobinuria. Severe cases can lead to the death of dogs, which brings great spiritual and economic losses to pet owners [5,6]. Babesia, which infects dogs, was first discovered in India in 1910 and has since been reported in countries around the world [7,8]. In China, B. gibsoni was reported for the first time in 1987, and the disease was subsequently found throughout the country [9]. In 2017, the strain of B. gibsoni in Wuhan (B. gibsoni-Wuhan) was reported [10]. In recent years, the incidence of babesiosis in dogs has been increasing, and the number of working and pet dogs has also risen rapidly [10,11]. Therefore, the development of effective diagnosis and treatment of babesiosis is particularly important. The diagnosis of babesiosis in dogs is currently mainly performed by microscopy (microscopic examination “ME”), which cannot be used for the detection of chronic infection or low-infected samples, and is not appropriate for epidemiological studies of large numbers of samples. In addition, external factors such as environment and personnel can interfere with ME as a diagnostic method. It is worth mentioning that dogs infected with B. gibsoni have the characteristics of lifelong premunition immunity and easy relapse. Therefore, it is necessary to develop an accurate and simple diagnostic method that can be used in clinical detection. The first step in establishing a new diagnostic method is to screen excellent candidates as diagnostic antigens [12]. Studies have shown that, when parasites invade the host, parasite surface proteins are most easily discovered by the host immune system, and thus play a major role in the host’s immune response [13]. So, parasite surface proteins are generally recognized as important candidates for diagnostic antigens [14,15,16]. GPI is a glycolipid structure added to the carboxyl terminus of most eukaryotic proteins after translation [17,18]. This modification is responsible for anchoring the protein on the outer side of the cell membrane to become the surface protein of the parasite [19,20,21,22]. Moreover, the GPI site of the GPI-anchored protein is released from the surface of the cell membrane after being cut and exposed to the host immune system directly, which theoretically can effectively cause the immune protection mechanism of the host [22]. GPI-anchored proteins are reported to be abundant on the membranes of apicomplexan parasites. They have been shown to have good immunogenicity and are suggested to be important virulence components of parasites [20,23]. For example, the merozoite surface proteins (MSPs) in Plasmodium falciparum (P. falciparum), the surface antigens (SAGs) in Toxoplasma gondii, and the merozoite surface antigens (MSAs) in Babesia have typical GPI anchor modification structures [24,25,26]. Therefore, this type of GPI-anchoring protein is considered to be an excellent candidate vaccine and detection antigen for apicomplexan protozoa [17,19]. Previous studies have shown that GPI-anchored proteins have a great immunogenicity in many Babesia spp. For example, the merozoite surface antigen (MSA-2C protein), as a highly immunogenic protein, has been successfully used in the development of serological diagnostic methods such as iELISA of B. bovis [27,28,29]. For B. microti, it was found that the BmGPI12 protein alone or in combination with other B. microti GPI-anchored proteins has great potential as a diagnostic biomarker, in addition to being a drug target [19]. Therefore, a class of proteins containing GPI anchor sites may play an important role in the detection of Babesiosis. There is no complete diagnostic kit for B. gibsoni in China. In this study, the BgGPI52-WH-anchored protein was screened using bioinformatics methods, then cloned and expressed to identify its antigenicity and immunogenicity as a potential diagnostic antigen. Finally, an iELISA diagnostic method was established using the BgGPI52-WH-anchored protein to explore its possibility as an immunodiagnostic marker. This provides a theoretical basis for the clinical detection, treatment and prevention of B. gibsoni, and provides a candidate target for the diagnosis of B. gibsoni. 2. Materials and Methods 2.1. Parasites and Animal Experiments B. gibsoni-Wuhan strain was stored in liquid nitrogen in our laboratory, the State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, China. We purchased three healthy beagles of about one year of age from the Anlu Laboratory Animal Center. Then, 5 mL of B. gibsoni-infected blood (~2.5 × 108 parasites) was injected into the experimental beagles by subcutaneous injection. PCR and microscopy were used to detect the parasite infection. In the early stage of infection, the specific fragments of B. gibsoni were amplified by conventional PCR to test whether the experimental dogs were successfully infected. When the positive bands of B. gibsoni were detected by PCR, they were stained with Giemsa solution and directly observed for B. gibsoni under a microscope. 2.2. Bioinformatics Analysis The GPI-anchored proteins of the genus Piroplasma (such as B. microti, B. bovis, etc.) were researched online using the NCBI, Uniprot and PirolplasmaDB databases to identify possible surface proteins of B. gibsoni [30]. The signal peptides and transmembrane regions of the surface proteins of B. gibsoni were predicted using bioinformatics methods. The GPI anchor points of the candidate proteins were predicted by bioinformatics software such as GPI-SOM, PredGPI and bigPI to prove that these candidate proteins were GPI-anchored proteins. The acquired results were compared with the genome database of the B. gibsoni-Wuhan strain (data unpublished), and the GPI-anchoring protein gene of the B. gibsoni-Wuhan strain was obtained. Bioinformatics methods were subsequently performed to analyze the presence of the signal peptide, transmembrane region, GPI anchor positions, and B cell epitopes. The bioinformatics analysis website and the software used in this research are presented in Table 1. 2.3. Extraction of Total RNA and gDNA The total RNA was extracted from the infected RBCs (iRBCs) using TRIzol®RNA (Thermo Fisher, Waltham, CA, USA). Then, we used the PrimeScript™ RT reagent kit with the gDNA Eraser kit (TaKaRa, China) to reverse transcribe the extracted RNA to obtain B. gibsoni cDNA, which we then stored at −80 °C. Genomic DNA (gDNA) was extracted from the iRBCs of dogs using the QIAamp DNA Kit (Qiagen, Shanghai, China). Follow-up experiments were performed following the success of the quality test. After concentration measurements, the DNA was stored at −20 °C. 2.4. Cloning, Expression and Purification of rBgGPI52-WH The BgGPI52-WH gene sequence was obtained by PCR with B. gibsoni gDNA and cDNA as templates, using the specific primers of the BgGPI52-WH gene (Table 2). The PCR product was detected by 1% agarose gel (TSINGKE Biological Technology, Beijing, China), and subsequently recovered by the Easy Pure® PCR Purification Kit (TransGEN, Beijing, China). The recovered products were connected and transformed into the pEASY-Blunt vector (TaKaRa Biotechnology, Beijing, China), and the sequence of BgGPI52-WH gene was confirmed after sequencing. After correct sequencing, BamHI and XhoI were used as restriction sites, and the pET-28a expression vector was used for protein expression. The recombinant protein with His-tag (rBgGPI52-WH) was expressed in E. coli BL21 cells. The normal expression of BL21 was induced after extended culture, and the protein was identified by SDS-PAGE gel pattern with His-tag and its expression in the supernatant. The supernatant was centrifuged at 4 °C after pressure crushing. The supernatant was combined with the nickel-affinity chromatography column (GE Healthcare, Uppsala, Sweden) then eluted and purified with imidazole at different concentrations. The eluents of each gradient were recovered and visualized by SDS-PAGE. The concentration was determined BCA method (Beyotime, Shanghai, China) according to manufacturer’s instruction. After protein purification with a nickel column, the target protein was obtained and stored at −80 °C until further use. 2.5. Production of Mouse Anti-rBgGPI52-WH Immune Serum Five KunMing mice were used for the preparation of antibodies against rBgGPI52-WH. The target protein and Freund’s complete adjuvant (Sigma, Shanghai, China) was mixed in a ratio of 1:1 for protein emulsification, and then each mouse was subcutaneously immunized with 100 μg of rBgGPI52-WH. Thereafter, on days 14, 28, 42, 56, 70 and 84, the booster doses were administrated. The serum samples were collected one week after the sixth immunization. 2.6. Preparation of B. gibsoni Lysates Next, 1 mL of fresh red blood cells (RBCs) was collected from the B. gibsoni-infected dogs and resuspended in an equal volume of PBS, and 18 mL of RBCs lysis buffer was added (Tris/EDTA/NaCl). Then, the supernatant was preheated for 5 min in a 37 °C water bath and centrifuged at 2450 r/min for 5 min. After collecting the supernatant, the supernatant was centrifuged at 12,000 r/min for 20 min to retain the pellet. The obtained pellet was washed by PBS 3 times. Then, 5 mL PBS was added to resuspend the pellet, then centrifuged at 15,000 r/min for 20 min. We discarded the supernatant then resuspended the pellet with 1 mL of PBS. The lysate of B. gibsoni merozoites was used directly, or stored at −20 °C. 2.7. Western Blot Analysis To detect the antigenicity of BgGPI52-WH, the rBgGPI52-WH protein was electrophoresed onto SDS-PAGE gel. The primary antibodies were the positive serum of B. gibsoni-infected dogs and the negative serum of pre-infection dogs. The secondary antibody was goat anti-canine IgG (HRP) (Southern Biotech, Birmingham, USA). To preliminarily determine the immunogenicity of rBgGPI52-WH, SDS-PAGE gel electrophoresis was performed with erythrocyte lysates from normal dogs and B. gibsoni-infected dogs. Mouse anti-BgGPI52-WH polyclonal antibodies (PcAb) and pre-immune mouse serum were used as the primary antibody, in addition to the secondary antibody of goat anti-mouse IgG (HRP) (Southern Biotech, USA). The electrochemiluminescence (ECL) method was used for developing the target band. 2.8. Establishing iELISA Based on rBgGPI52-WH In this study, the rBgGPI52-WH target protein was coated on the microplate as previously described [29]. The primary antibody comprised the serum of healthy dogs and B. gibsoni-infected dogs, and the secondary antibody was goat anti-canine IgG (HRP) (Southern Biotech, USA). The optimization steps were as follows: (1) the optimum concentration of antigen envelope and serum dilution ratio were screened. The purified rBgGPI-WH protein was diluted to different concentrations with the coating buffer according to doubling dilution, and the serum was also diluted to different concentrations by doubling dilution, and then screened by cross-square titration. (2) The second step was to screen the best time for antigen blocking. The protein was coated with the optimal coating concentration screened above, and the protein was blocked at different times while fixing other experimental conditions. The closing time at the maximum P/N value (P/N value = (mean value of positive OD630/mean value of negative control OD630)) was regarded as the best antigen blocking time. (3) Next, we screened the optimal incubation time for the primary antibody. Screening was performed by adjusting the serum action time of the different gradients after determining the optimal coating concentration of the antigen, the optimal serum dilution ratio, and the optimal antigen blocking time. (4) Likewise, under the fixed conditions of the other experimental conditions, single factors were screened one by one. The screening work consists of the best working concentration of the secondary antibody, the best incubation time, and the best working time of the color substrate solution. After multiple optimizations, the established iELISA method was used to detect the infection using multiple sera, and the cut-off value was determined after a fixed formula calculation. 2.9. Sensitivity and Speficity of the iELISA Assy The sensitivity of the established iELISA method was determined by using B. gibsoni-positive sera. We diluted the known positive sera and negative sera from our laboratory in the ratio of 1:200, 1:400, 1:800, 1:1600, 1:3200, and 1:6400 with the incubation solution to perform the iELISA test. After terminating the reaction, we read it with a microplate reader. Values of S/P (S/P value = mean value of sample OD630/mean value of positive control OD630) were calculated to determine the sensitivity. For the specificity assay, seven different sera, including B. gibsoni, Toxoplasma gondii (T. gondii), Echinococcus granulosus, Strongyloides stercoralis (S. stercoralis), Rabies virus (RABV), Canine Parvovirus (CPV), and Babesia canis (B. canine) were used. Serum from healthy dogs without any known disease was considered as a negative serum. The iELISA test was performed according to the optimized conditions. After the reaction was terminated, the plates were read at the OD630 nm value with a microplate reader. The S/P value were calculated, and the negative or positive values were estimated according to the cut-off value standard to the established test in this study to determine the specificity of the ELISA method. 2.10. Repeatability of the iELISA Assay Four positive sera and two negative sera known in our laboratory were used to perform the intra-batch reproducibility experiments and the inter-batch reproducibility experiments. After the reaction was terminated, reading was established at the OD630 nm value with a microplate reader. The average (x) and standard deviation (SD) of each serum were calculated at OD630 nm, and the coefficient of variation was calculated using the following formula CV = (SD/x) × 100%. 2.11. Detection of Antibodies against BgGPI52-WH in Experimental Infected Dog Samples Three experimental beagles (A, B, C) were infected with the B. gibsoni-Wuhan strain under laboratory conditions. Serum samples from the infected dogs were collected at intervals of 3 or 7 days, up to 101 days after infection. The antibodies in the serum of the B. gibsoni-infected beagles were detected by the established iELISA to study the production of anti-BgGPI52-WH antibodies in beagles infected with B. gibsoni. 2.12. Evaluating the iELISA by Clinical Sample Testing A total of 149 clinical sera samples with clinical symptoms of fever and anemia were donated by veterinary hospital in Wuhan, China. The clinical sera samples were tested by iELISA based on rBgGPI52-WH and rBgSA1-WH (unpublished data), respectively, and the iELISA detection results of the two proteins were compared. All the performed work was repeated 3 times. Data analyses were performed using Excel 2019 (Microsoft Corporation, Redmond, WA, USA) and graph generation was performed using GraphPad Prism 8 (Graph Pad Software, San Diego, CA, USA). S/P values were calculated by Excel 2019 (Microsoft Corporation, Redmond, WA, USA), and the figures were generated by GraphPad Prism 8 (Graph Pad Software, San Diego, CA, USA) by using XY tables (points only graph). 3. Results 3.1. Gene Sequence Analysis of BgGPI52-WH Five GPI anchor proteins of B. gibsoni were screened by bioinformatics. The results of the analysis showed that these five candidate antigens were potential diagnostic candidates. Previous research on one of the GPI-anchored proteins, BgGPI47-WH, has shown that it is a good diagnostic antigen, and related research content has been published [29]. In the present work, the gene sequence of BgGPI52-WH was obtained by PCR amplification from B. gibsoni gDNA and cDNA with specific primers (Table 1). The full length of the BgGPI52-WH gene is 1453 bp, and it contains an intron of 37 bp (Figure 1a). A signal peptide was predicted in the first 1–19 aa of the BgGPI52-WH amino acid sequence, containing at least two transmembrane regions (3–21 aa, 454–471 aa) at the C-terminal. The GPI anchor point was located at the C-terminus, and the length was approximately 21–22 aa (Figure 1b). The epitope of BgGPI52-WH was predicted by DNAStar software. The results revealed that the BgGPI52-WH protein has a good epitope, and could be used as a high-quality antigen molecule for the development of novel diagnostic methods (Figure 1c). 3.2. Cloning and Expression of BgGPI52-WH Recombinant Protein The full ORF of BgGPI52-WH gene contained 1416 bp, encoding 471 aa with a molecular weight of ~52 kDa. The recombinant protein was mainly expressed in the supernatant of E. coli BL21 (DE3) lysate induced by isopropyl beta-D-thiogalactopyranoside (IPTG) (Figure 2). A specific band was observed around 52 kDa by a 12% SDS-PAGE analysis, which is consistent with the predicted size (Figure 2). For protein extraction, the rBgGPI52-WH was purified using a Ni-agarose column and stored in −80 °C for the subsequent experiment. 3.3. Western Blot Analysis of rBgGPI52-WH Protein For the evaluation of the potential antigenicity and immunogenicity of BgGPI52-WH, we performed a Western blot analysis for rBgGPI52-WH (Figure 3). The infected B. gibsoni serum and the noninfected B. gibsoni serum were used as primary antibodies to react with rBgGPI52-WH, respectively. A band of ~52 kDa was observed using the positive serum, and no reaction was detected using the negative serum (Figure 3a). Interestingly, the polyclonal antibody (PcAb) of mouse anti-BgGPI52-WH could recognize the native BgGPI52-WH from the lysate of B. gibsoni-infected RBCs, and the size was ~52 kDa. No signal was detected in the B. gibsoni-free RBCs lysates (Figure 3b). 3.4. Optimization of Experimental Conditions of Indirect ELISA Based on the data above, we attempted to establish an iELISA method using the newly identified BgGPI52-WH. After the optimization, the best experimental conditions were acquired. The optimal coating concentration of the rBgGPI52-WH was determined as 1 μg/mL, and the optimal blocking time was 30 min using 1% BSA. The best dilution ratio and reaction time for the primary antibodies were determined as 1:200 and 60 min, respectively. The best dilution ratio of secondary antibodies was 1:4000, when the incubation time was 30 min. The reaction time of TMB substrate solution was optimized as 10 min. The cut-off value was calculated using the following equation: X + 3SD. The critical value was determined as 0.296. Hence, the S/P value (>0.296) was used as a reasonable standard to distinguish that of B. gibsoni-infected and B. gibsoni-free samples. 3.5. Sensitivity and Specificty Detection of BgGPI52-WH iELISA For evaluating the reliability of the established iELISA, we used the new method to examine five B. gibsoni-infected samples to evaluate its sensitivity and specificity detection ability. These samples were further diluted by the doubling dilution method, and the S/P values were calculated after reading with a microplate reader at OD630 nm. According to the S/P value, the sensitivity of the novel iELISA was greater than 1:400 (Figure 4). In addition, the established iELISA method was also used to detect the positive sera of T. gondii, Echinococcus granulosus, S. stercoralis, RABV, CPV and B. canine. After the reaction was terminated, the absorbances were acquired at OD630 nm and the S/P values were calculated. The results demonstrated that the method based on BgGPI52-WH had high specificity, and no cross reaction was observed with that of the positive sera of T. gondii, Echinococcus granulosus, S. stercoralis, RABV, CPV or B. canine. (Figure 5). Together, the results indicated that BgGPI52-WH is a reliable diagnostic antigen, and the novel iELISA method could be used as a cost-effective way to diagnose B. gibsoni. 3.6. Repeatability Detection of iELISA The repeatability of the iELISA was carried out based on the intra-batch and inter-batch repeatability experiments. Four positive sera and two negative sera samples were used in the following experiment, and the repeatability was tested using the strategy of the same batch and different batches of enzyme plates. After the reaction was terminated the absorbances were acquired at OD630 nm. The mean value (x) and standard deviation (SD) of the absorbance of each serum were calculated, and the consequent values were further used to determine the coefficient of variation (CV). By comparison, we found that the degree of variation of the same sample from the same or different batch of enzyme-labeled strips was less than 10%, and the results indicated that the new iELISA had good repeatability (Table 3 and Table 4). 3.7. iELISA Evaluation Using Clinical and Experimental Infected Samples For evaluating the application value of the new iELISA, we used the established iELISA method to detect the antibodies from three experimental dogs in different infection stages of B. gibsoni. Based on the continuous detection of parasitized rate by B. gibsoni, we found that the percentage of parasitized erythrocytes (PPEs) was 0.3% on day 9, 4% on day 10, and up to 33% on day 19. To control the infection, we treated the dogs with intravenous azithromycin, glucose, and other nutrients. Following the treatment, PPE decreased rapidly until it reached almost zero by a microscopic examination, and the dogs entered the lifetime status of B. gibsoni infection. As a result, the antibody levels in these dogs will remain high for a long time. In the study, PPEs were combined for a comprehensive analysis, and the new method based on rBgGPI52-WH distinguished the positive sera of three experimental dogs during the early infection stage (Figure 6). Interestingly, the method could detect the B. gibsoni-infected sera at day 6 of the early infection stage. The results demonstrated that BgGPI52-WH could detect the positive sera of dogs at the initial stage of infection, and this early detection will contribute to the clinical treatment of babesiosis. In addition, a total of 149 clinical pet dog blood samples were donated by a veterinary hospital in Wuhan, China. These blood samples were tested using the iELISA methods based on BgGPI52-WH and BgSA1-WH, respectively. The results showed that the positive rate of the clinical samples was ~11.41%, and the agreement rate of two iELISA methods was 83.89% (Figure 7). 4. Discussion Babesia gibsoni is one of the most widespread sources of Babesia infection in dogs. Several different geographic isolates have been obtained from South Asia, East Asia and Southeast Asia [31,32]. It is reported that, with the development of globalization, the infection, morbidity, and mortality rates of babesiosis in dogs in China are on the rise. Among the sera samples of working dogs (26.1%), fighting dogs (39.8%), and pet dogs (3.47%), the highest positive rate was found in the sera samples of the fighting dogs [33]. This could cause economic losses to pet owners and threaten public health. It is therefore necessary to establish a detection method with good specificity and sensitivity for early diagnosis to prevent the outbreak of babesiosis. Microscopy is simple and convenient, and has a high detection rate in acute infections, but chronic infections or carrier dogs cannot be detected. Molecular diagnostic methods have high sensitivity and specificity, but low clinical applicability and high cost, in addition to being time consuming. Compared with other molecular biological detection methods, the ELISA method is easier to operate and more specific for the detection of a large number of samples, especially in large-scale epidemiological investigations. The key to establishing an effective diagnostic method is to screen high-quality immunodiagnostic markers. The BgTRAP (TRAP of B. gibsoni) antigen detected by indirect ELISA has been recognized as the best immunodiagnostic marker for this infection. However, the recombinant expression of BgTRAP is difficult and the sensitivity is not ideal, which requires further research and the development of more prospective antigens [34]. The GPI anchor site helps the antigen anchored to the cellular membrane, and works as a surface protein or secreted protein which plays an important role when the protozoa invade the host. It also has potential to be used as an immunodiagnostic marker [35,36,37]. Therefore, this study was based on the fact that there are no large-scale clinical diagnosis methods for the early stage of Babesiosis in dogs [38]. The GPI-anchored protein BgGPI52-WH was screened by bioinformatics methods and experimental validation. The rBgGPI52-WH protein was expressed and purified. Western blot analysis showed that it has good antigenicity and immunogenicity, and could be used as an immunodiagnostic marker. The above results of the characterization of the BgGPI52-WH protein were similar to BgP50 in the Japanese strain [39]. A method of iELISA detection based on BgGPI52-WH was established. The sensitivity, repeatability, and specificity of the assay were evaluated, as were sera samples from experimental dogs of different infection cycles, and large clinical sera samples. During natural canine infection with B. gibsoni, coinfection with other related parasites usually occurs [40]. It is important to distinguish between pathogens based on epidemiology, and identify other parasites that are closely genetically related to infection by B. gibsoni. In this regard, we evaluated the cross-reaction of the diagnostic antigen BgGPI52-WH with the positive sera of other pathogens and found that the iELISA method established with BgGPI52-WH did not react with the positive sera of Toxoplasma gondii, Hydatid Canis, Roundworm coelata, rabies virus, canine parvovirus or Babesia canis. This test was performed to avoid false positive misdiagnosis results for symptomatic treatment, and the results proved the specificity of BgGPI52-WH for only B. gibsoni. The repeatability and sensitivity experiments proved that the method had good repeatability and sensitivity. To detect the serum status of the experimental dogs in different infection cycles, the iELISA method established by BgGPI52-WH, PCR, and microscopy were used to detect the infected dogs. The results showed that the iELISA method established by BGGPI52-WH and PCR were suitable for the early stage of infection. Microscopic examination was not suitable. BgGPI52-WH antibodies could be detected on the sixth day at the earliest, and at the latest on the eighth day of infection. The specific antibody reaction could be detection detected up to day 101, but PCR and microscopy did not work during this period, suggesting that the established method based on BgGPI52-WH is useful for chronic infection. Moreover, PCR and microscopy are more complicated than iELISA, so they are not applicable in general clinics. In clinical applications, diagnosing the disease in its early stage is important for treatment and disease control [41,42,43]. One hundred and forty-nine clinical samples donated by a veterinary hospital in Wuhan, China, were tested with two different diagnostic antigens. The positive rates of BgGPI52-WH and BgSA1-WH were 11.41% and 17.45%, respectively. The coincidence rate of the two detection methods was 85.23%. This indicates that the test based on the diagnostic antigen BgGPI52-WH had lower false positives, and is thus more consistent with tests suitable for clinical samples. 5. Conclusions In conclusion, an antigen named BgGPI52-WH was identified from the B. gibsoni-Wuhan strain. Antigenicity and immunogenicity evaluation demonstrated that it was a potential diagnostic marker. An iELISA with high sensitivity and specificity was established based on the recombinant BgGPI52-WH, which can be used for the clinical diagnosis of early and chronic infections. Early detection means that babesiosis in dogs can be treated quickly which, in turn, reduces the mortality and infection rate of the disease. We believe the iELISA based on the BgGPI52-WH antigen is conducive to the prevention and control of babesiosis in dogs. Author Contributions Conceptualization, Q.L., L.H. and J.Z.; software, Q.L.; validation, Q.L., X.Z., D.L. and H.W.; data curation, Q.L.; writing—original draft preparation, Q.L.; writing—review and critical revision, L.H. and H.A.; visualization, Q.L.; supervision, Q.L.; funding acquisition, L.H. and J.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement During the experiment, a cautious attitude was taken to each experimental animal to minimize the harm to the experimental animals. The feeding environment and experimental operation of all experimental animals were in accordance with and strictly abide by the stipulated rules for the Regulation of the Administration of Affairs Concerning Experimental Animals of PR China, the laboratory Animals Research Centre of Hubei province and the Ethics Committee of Huazhong Agricultural University (license number: HZAUDO-2017-005). Informed Consent Statement Not applicable. Data Availability Statement The sequence was submitted to NCBI GenBank (Accession number: MZ773409). The data involved in this study are available through the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Sequence analysis of BgGPI52-WH. (a) Identification of target gene sequences. Lane M—marker; lane 1—the BgGPI52-WH target band amplified from B. gibsoni gDNA; lane 2—the BgGPI52-WH target band amplified from B. gibsoni cDNA; lane 3—control group. (b) A schematic diagram showing the TM domain, signal peptide (SP) and GPI anchor site of the target protein sequence. (c) Prediction of the antigen epitopes of the BgGPI52-WH protein. Purple represents the antigenic index; the higher the antigenic index, the better the antigenicity. Yellow represents the probability index of protein on the surface. Figure 2 Prokaryotic expression of recombinant protein BgGPI52-WH. M—marker; 1—non-induced BgGPI52-WH; 2—induced BgGPI52-WH; 3—induced BgGPI52-WH precipitate; 4—induced BgGPI52-WH supernatant; 5—purified recombinant BgGPI52-WH protein. Figure 3 The antigenic properties of BgGPI52-WH were detected by Western blot. (a) Immunogenicity detection of B. gibsoni BgGPI52-WH protein. Lane M—marker; lane 1, 3—the iRBC lysates of dogs detected by mouse anti-BgGPI52-WH serum; lane 2, 4—the RBC lysates of uninfected dogs detected by mouse anti-BgGPI52-WH serum. (b) Antigenicity detection of B. gibsoni BgGPI52-WH protein. Lane M—marker; lane 1—recombinant BgGPI52-WH protein detected by the serum of B. gibsoni-infected dogs; Lane 2—recombinant BgGPI52-WH protein detected by normal serum from uninfected dogs. Figure 4 Sensitivity of indirect ELISA to BgGPI52-WH. Serum1–Serum5—five known positive sera; cut-off—cut-off value obtained from the above experiment (0.296). Figure 5 Indirect ELISA specific test. Bands 1–7 reflect serum from dogs infected with Toxoplasma gondii, Echinococcus granulosus, Strongyloides stercoralis, Rabies virus, Canine Parvovirus, Babesia canis, and Babesia gibsoni (positive control), respectively. Point 8—negative control. Figure 6 The antibody change curve of BgGPI52-WH detected by BgGPI52-WH-ELISA. The three experimental beagles infected with B. gibsoni under laboratory conditions are labelled A, B, and C. Figure 7 The detection of BgGPI52-WH-ELISA from a clinical sample. The dashed read line indicates the cut-off value. The critical value is X + 3SD = 0.296. Results criteria: serum samples with S/P values greater than 0.296 could be judged as positive. The positive rate after the ELISA test was 11.41% (17/149). animals-12-01197-t001_Table 1 Table 1 Bioinformatics analysis websites and software. Function Category Website/Software Nucleotide sequence https://www.ncbi.nlm.nih.gov/, accessed on 12 December 2019 http://piroplasmadb.org/piro/, accessed on 12 December 2019 http://www.uniprot.org/, accessed on 12 December 2019 Sequence alignment http://mafft.cbrc.jp/alignment/server/index.htmL, accessed on 12 December 2019 http://www.ncbi.nlm.nih.gov/blast/, accessed on 12 December 2019 SignalP http://www.cbs.dtu.dk/services/SignalP/, accessed on 12 December 2019 Transmembrane prediction https://embnet.vital-it.ch/software/TMPRED_form.html, accessed on 12 December 2019 ProtScale https://web.expasy.org/protscale/, accessed on 12 December 2019 GPI anchor site prediction http://mendel.imp.ac.at/gpi/plant_server.htm, accessed on 12 December 2019 http://gpi.unibe.ch/, accessed on 12 December 2019 http://gpcr.biocomp.unibo.it/predgpi/, accessed on12 December 2019 B cell epitope prediction DNASTAR Primer design Clone Manager animals-12-01197-t002_Table 2 Table 2 Primers used for the amplification of the partial BgGPI52-WH gene. Primers Primer Sequences (5′–3′) Restriction Enzyme BgGPI52-WH-F 5′-ATGAGACTAGTTCGTGCATTCC-3′ BgGPI52-WH-R 5′-TTAAAATACAGCGACAGCCACAG-3′ BgGPI52-WH-BamH I-F 5′-CAGGATCCACTGGTGATGGGAATATGACAG-3′ BamH I BgGPI52-WH-Xho I-R 5′-TCCTCGAGTTAAAATACAGCGACAGCCACAG-3′ Xho I animals-12-01197-t003_Table 3 Table 3 Intra-batch repeatability test. Average Value SD CV% Serum 1 0.943 0.038 4.03 Serum 2 0.989 0.028 2.83 Serum 3 0.501 0.043 8.58 Serum 4 0.088 0.003 3.41 Serum 5 0.121 0.007 5.79 animals-12-01197-t004_Table 4 Table 4 Inter-batch repeatability test. Average Value SD CV% Serum 1 0.992 0.043 4.335 Serum 2 0.997 0.025 2.508 Serum 3 0.588 0.013 2.192 Serum 4 0.057 0.004 7.144 Serum 5 0.133 0.010 7.519 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Singh M.N. Raina O.K. Sankar M. Rialch A. Tigga M.N. Kumar G.R. Banerjee P.S. Molecular detection and genetic diversity of Babesia gibsoni in dogs in India Infect. Genet. Evol. 2016 41 100 106 10.1016/j.meegid.2016.03.025 27020545 2. Schnittger L. Rodriguez A.E. Florin-Christensen M. Morrison D.A. Babesia: A world emerging Infect. Genet. Evol. 2012 12 1788 1809 10.1016/j.meegid.2012.07.004 22871652 3. Irwin P.J. Canine babesiosis Vet. Clin. N. Am. Small Anim. Pract. 2010 40 1141 1156 10.1016/j.cvsm.2010.08.001 20933141 4. Uilenberg G. Babesia—A historical overview Vet. Parasitol. 2006 138 3 10 10.1016/j.vetpar.2006.01.035 16513280 5. Casapulla R. Baldi L. Avallone V. Sannino R. Pazzanese L. Mizzoni V. Canine piroplasmosis due to Babesia gibsoni: Clinical and morphological aspects Vet. Rec. 1998 142 168 169 10.1136/vr.142.7.168 9519430 6. Wozniak E.J. Barr B.C. Thomford J.W. Yamane I. McDonough S.P. Moore P.F. Naydan D. Robinson T.W. Conrad P.A. Clinical, anatomic, and immunopathologic characterization of Babesia gibsoni infection in the domestic dog (Canis familiaris) J. Parasitol. 1997 83 692 699 10.2307/3284248 9267413 7. Groves M.G. Yap L.F. Babesia gibsoni (Patton, 1910) from a dog in Kuala Lumpur Med. J. Malaya 1968 22 229 8. Kjemtrup A.M. Kocan A.A. Whitworth L. Meinkoth J. Birkenheuer A.J. Cummings J. Boudreaux M.K. Stockham S.L. Irizarry-Rovira A. Conrad P.A. There are at least three genetically distinct small piroplasms from dogs Int. J. Parasitol. 2000 30 1501 1505 10.1016/S0020-7519(00)00120-X 11428342 9. Wenxiang L. Xinshe L. A case of Babesia gibsoni in a hunting dog Chin. J. Vet. Sci. Technol. 1987 5 45 46 10. He L. Miao X. Hu J. Huang Y. He P. He J. Yu L. Malobi N. Shi L. Zhao J. First Molecular Detection of Babesia gibsoni in Dogs from Wuhan, China Front. Microbiol. 2017 8 1577 10.3389/fmicb.2017.01577 28871243 11. Cannon S.H. Levy J.K. Kirk S.K. Crawford P.C. Leutenegger C.M. Shuster J.J. Liu J. Chandrashekar R. Infectious diseases in dogs rescued during dogfighting investigations Vet. J. 2016 211 64 69 10.1016/j.tvjl.2016.02.012 27056107 12. Lequin R.M. Enzyme immunoassay (EIA)/enzyme-linked immunosorbent assay (ELISA) Clin. Chem. 2005 51 2415 2418 10.1373/clinchem.2005.051532 16179424 13. Xu J. Wang J. Li Z. He X. Zhao S. Ma Q. Li X. Liu J. Liu A. Li Y. A universal ELISA assay for detecting six strains of ovine Babesia species in China Vet. Parasitol. 2021 300 109616 10.1016/j.vetpar.2021.109616 34781076 14. Howe D.K. Crawford A.C. Lindsay D. Sibley L.D. The p29 and p35 immunodominant antigens of Neospora caninum tachyzoites are homologous to the family of surface antigens of Toxoplasma gondii Infect. Immun. 1998 66 5322 5328 10.1128/IAI.66.11.5322-5328.1998 9784539 15. Atkinson R. Harper P.A. Reichel M.P. Ellis J.T. Progress in the serodiagnosis of Neospora caninum infections of cattle Parasitol. Today 2000 16 110 114 10.1016/S0169-4758(99)01604-X 10689330 16. Schares G. Rauser M. Sondgen P. Rehberg P. Barwald A. Dubey J.P. Edelhofer R. Conraths F.J. Use of purified tachyzoite surface antigen p38 in an ELISA to diagnose bovine neosporosis Int. J. Parasitol. 2000 30 1123 1130 10.1016/S0020-7519(00)00092-8 10996331 17. Rodriguez A.E. Florin-Christensen M. Flores D.A. Echaide I. Suarez C.E. Schnittger L. The glycosylphosphatidylinositol-anchored protein repertoire of Babesia bovis and its significance for erythrocyte invasion Ticks Tick Borne Dis. 2014 5 343 348 10.1016/j.ttbdis.2013.12.011 24642346 18. Chatterjee S. Mayor S. The GPI-anchor and protein sorting Cell. Mol. Life Sci. CMLS 2001 58 1969 1987 10.1007/PL00000831 11814051 19. Cornillot E. Dassouli A. Pachikara N. Lawres L. Renard I. Francois C. Randazzo S. Bres V. Garg A. Brancato J. A targeted immunomic approach identifies diagnostic antigens in the human pathogen Babesia microti Transfusion 2016 56 2085 2099 10.1111/trf.13640 27184823 20. McGwire B.S. O’Connell W.A. Chang K.P. Engman D.M. Extracellular release of the glycosylphosphatidylinositol (GPI)-linked Leishmania surface metalloprotease, gp63, is independent of GPI phospholipolysis: Implications for parasite virulence J. Biol. Chem. 2002 277 8802 8809 10.1074/jbc.M109072200 11777912 21. Orlean P. Menon A.K. Thematic review series: Lipid posttranslational modifications. GPI anchoring of protein in yeast and mammalian cells, or: How we learned to stop worrying and love glycophospholipids J. Lipid Res. 2007 48 993 1011 17361015 22. Suzuki K.G. Kasai R.S. Hirosawa K.M. Nemoto Y.L. Ishibashi M. Miwa Y. Fujiwara T.K. Kusumi A. Transient GPI-anchored protein homodimers are units for raft organization and function Nat. Chem. Biol. 2012 8 774 783 10.1038/nchembio.1028 22820419 23. Hung C.Y. Yu J.J. Seshan K.R. Reichard U. Cole G.T. A parasitic phase-specific adhesin of Coccidioides immitis contributes to the virulence of this respiratory Fungal pathogen Infect. Immun. 2002 70 3443 3456 10.1128/IAI.70.7.3443-3456.2002 12065484 24. Lekutis C. Ferguson D.J. Grigg M.E. Camps M. Boothroyd J.C. Surface antigens of Toxoplasma gondii: Variations on a theme Int. J. Parasitol. 2001 31 1285 1292 10.1016/S0020-7519(01)00261-2 11566296 25. Wahlgren M. Goel S. Akhouri R.R. Variant surface antigens of Plasmodium falciparum and their roles in severe malaria Nat. Rev. Microbiol. 2017 15 479 491 10.1038/nrmicro.2017.47 28603279 26. Florin-Christensen M. Schnittger L. Dominguez M. Mesplet M. Rodriguez A. Ferreri L. Asenzo G. Wilkowsky S. Farber M. Echaide I. Search for Babesia bovis vaccine candidates Parassitologia 2007 49 (Suppl. S1) 9 12 17691600 27. Bono M.F. Mangold A.J. Baravalle M.E. Valentini B.S. Thompson C.S. Wilkowsky S.E. Echaide I.E. Farber M.D. Torioni de Echaide S.M. Efficiency of a recombinant MSA-2c-based ELISA to establish the persistence of antibodies in cattle vaccinated with Babesia bovis Vet. Parasitol. 2008 157 203 210 10.1016/j.vetpar.2008.07.025 18783887 28. Carcy B. Precigout E. Schetters T. Gorenflot A. Genetic basis for GPI-anchor merozoite surface antigen polymorphism of Babesia and resulting antigenic diversity Vet. Parasitol. 2006 138 33 49 10.1016/j.vetpar.2006.01.038 16551492 29. Zhan X. Yu L. An X. Liu Q. Li M. Nie Z. Zhao Y. Wang S. Ao Y. Tian Y. Evaluation of Babesia gibsoni GPI-anchored Protein 47 (BgGPI47-WH) as a Potential Diagnostic Antigen by Enzyme-Linked Immunosorbent Assay Front. Vet. Sci. 2019 6 333 10.3389/fvets.2019.00333 31681802 30. Nathaly Wieser S. Schnittger L. Florin-Christensen M. Delbecq S. Schetters T. Vaccination against babesiosis using recombinant GPI-anchored proteins Int. J. Parasitol. 2019 49 175 181 10.1016/j.ijpara.2018.12.002 30684517 31. Goo Y.K. Xuan X. New Molecules in Babesia gibsoni and their application for diagnosis, vaccine development, and drug discovery Korean J. Parasitol. 2014 52 345 353 10.3347/kjp.2014.52.4.345 25246713 32. Bostrom B. Wolf C. Greene C. Peterson D.S. Sequence conservation in the rRNA first internal transcribed spacer region of Babesia gibsoni genotype Asia isolates Vet. Parasitol. 2008 152 152 157 10.1016/j.vetpar.2007.11.024 18207327 33. Cao J. Yang Q. Zhang J. Zhou Y. Zhang H. Gong H. Zhou J. Seroprevalence survey of Babesia gibsoni infection and tick species in dogs in East China Vet. Parasitol. 2015 214 12 15 10.1016/j.vetpar.2015.10.002 26483164 34. Goo Y.K. Jia H. Aboge G.O. Terkawi M.A. Kuriki K. Nakamura C. Kumagai A. Zhou J. Lee E.G. Nishikawa Y. Babesia gibsoni: Serodiagnosis of infection in dogs by an enzyme-linked immunosorbent assay with recombinant BgTRAP Exp. Parasitol. 2008 118 555 560 10.1016/j.exppara.2007.11.010 18155197 35. Hafalla J.C. Silvie O. Matuschewski K. Cell biology and immunology of malaria Immunol. Rev. 2011 240 297 316 10.1111/j.1600-065X.2010.00988.x 21349101 36. Goodswen S.J. Kennedy P.J. Ellis J.T. A guide to in silico vaccine discovery for eukaryotic pathogens Brief. Bioinform. 2013 14 753 774 10.1093/bib/bbs066 23097412 37. Man S. Fu Y. Guan Y. Feng M. Qiao K. Li X. Gao H. Cheng X. Evaluation of a Major Surface Antigen of Babesia microti Merozoites as a Vaccine Candidate against Babesia Infection Front. Microbiol. 2017 8 2545 10.3389/fmicb.2017.02545 29312230 38. Karasova M. Tothova C. Grelova S. Fialkovicova M. The Etiology, Incidence, Pathogenesis, Diagnostics, and Treatment of Canine Babesiosis Caused by Babesia gibsoni Infection Animals 2022 12 739 10.3390/ani12060739 35327136 39. Goo Y.K. Aboge G.O. Terkawi M.A. Jia H. Yamagishi J. Sunaga F. Namikawa K. Cha S.Y. Jang H.K. Kim S. Four promising antigens, BgP32, BgP45, BgP47, and BgP50, for serodiagnosis of Babesia gibsoni infection were classified as B. gibsoni merozoite surface protein family Parasitol. Int. 2012 61 364 368 10.1016/j.parint.2011.11.007 22172478 40. Liu M. Igarashi I. Xuan X. Babesia gibsoni  Trends Parasitol. 2022 in press 10.1016/j.pt.2022.03.001 41. Kirk S.K. Levy J.K. Crawford P.C. Efficacy of Azithromycin and Compounded Atovaquone for Treatment of Babesia gibsoni in Dogs J. Vet. Intern. Med. 2017 31 1108 1112 10.1111/jvim.14777 28625019 42. Chen J. Wang L. Chen J.J. Sahu G.K. Tyring S. Ramsey K. Indrikovs A.J. Petersen J.R. Paar D. Cloyd M.W. Detection of antibodies to human immunodeficiency virus (HIV) that recognize conformational epitopes of glycoproteins 160 and 41 often allows for early diagnosis of HIV infection J. Infect. Dis. 2002 186 321 331 10.1086/341661 12134228 43. Eichenberger R.M. Stefanic S. Naucke T.J. Sarkunas M. Zamokas G. Grimm F. Deplazes P. An ELISA for the early diagnosis of acute canine babesiosis detecting circulating antigen of large Babesia spp. Vet. Parasitol. 2017 243 162 168 10.1016/j.vetpar.2017.06.030 28807287

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095212 ijerph-19-05212 Article Impact of Short-Term Intensive-Type Cognitive Behavioral Therapy Intervention on Internet Addiction among Chinese College Students: A Randomized Controlled Trial Yang Wenjie 12 Hu Wenyan 3* Morita Nobuaki 2 Ogai Yasukazu 2 Saito Tamaki 2 Wei Yan 4 Jiang Shan Academic Editor Li Chunkai Academic Editor 1 The Mental Health Center, Yunnan University, Kunming 650091, China; niujiazu2022@126.com 2 Department of Social Psychiatry and Mental Health, Faculty of Medicine, University of Tsukuba, Tsukuba 305-0006, Japan; nobuakim@nifty.com (N.M.); ogai.ys@md.tsukuba.ac.jp (Y.O.); hhd02063@gmail.com (T.S.) 3 Mental Health Education Center for College Students, Zhejiang Gongshang University, Hangzhou 310018, China 4 Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba 305-0006, Japan; wy1930380@gmail.com * Correspondence: hwy-81@163.com; Tel.: +86-571-2800-8801 25 4 2022 5 2022 19 9 521207 4 2022 24 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The object of this study is to examine the effects of a short-term intensive-type Cognitive Behavioral Therapy (CBT) intervention to prevent internet addiction among Chinese college students. We conducted a randomized controlled trial applying a group counseling intervention program based on CBT. Data included 21 participants in the intervention group and 22 participants in the control group. The results showed that the intervention program reduced college students’ internet addiction symptoms and procrastination and improved their sense of coherence. Regarding the sustained effect, internet addiction symptoms decreased and perceived social support from significant others improved in college students. However, the intervention program did not significantly reduce their average daily internet use time and psychological stress. Overall, this study developed a short-term intensive-type intervention program based on CBT theory, which is complementary for Chinese college students with internet addiction. group intervention program internet addiction strengths perspective cognitive behavioral therapy randomized controlled trial ==== Body pmc1. Introduction The flourishing of the internet is one of the most prominent features of the information society. In recent years, access to the internet has become widespread with the rapid development of smartphones. The number of internet users reached approximately 4.39 billion worldwide by 2019 [1], and internet usage in developing countries increased from 7.7% to 45.3% between 2005 and 2018 [2]. According to recent data released by the China Internet Network Information Center [3], the number of Chinese internet users has reached 1.011 billion, and the internet penetration rate reached 71.6% by June 2021, more than one-fourth of whom were students. The percentage of internet users using smartphones to access the internet was as high as 99.6%, with 26.9 h of internet access per person per week. Nowadays, people’s daily lives have become inseparable from the internet, and the internet is widely used by college students for multiple purposes, including learning, entertainment, and communication [4]. In mainland China, college students have relatively less supervision from parents and teachers than elementary and middle school students and have more preference and capability to follow digital device updates, but have less self-control than adults [5]. Easy and regular access to the internet may foster excessive internet use, which has proven to be a potential risk factor for the development of Internet Addiction (IA) [4,6]. Research has shown that college students aged 18 to 25 are vulnerable to addictive behaviors [7]. Young (1998) defined IA as “an impulse control disorder unaffected by addictive substances” [8]. Kwok et al. (2017) found that IA results in various negative effects, including sleep deprivation, lack of exercise, eye discomfort, stiff shoulders, cyberbullying victimization, and debt problems [9]. A survey of 8098 Chinese college students showed that 21.4% of IA students had suicidal thoughts, significantly higher than 5.6% of non-IA students. IA students were also at risk for anxiety and depression, with a prevalence of 43.7% and 37.5%, respectively [10]. Therefore, it is important to take appropriate measures to prevent Chinese college students from IA. 1.1. Prevention of Internet Addiction The prevalence of IA among college students is 11.3% in China [11], and it is still increasing [12,13]. The International Classification of Diseases 11th classifies internet users into four layers [14]. From the first to the fourth layers are “Healthy user”, “Hazardous user”, “Internet addiction disorder”, and “Complication & Comorbidity”. Prior prevention research on IA focuses on early detection and treatment of the second and the third layer internet users and attempts to conduct appropriate intervention programs to prevent them from becoming severely addicted. Vondráčková and Gabrhelík (2016) reviewed 108 studies and suggested that for those at high risk for IA, specific skills to prevent IA fall into four basic areas, including skills related to (a) internet use, (b) coping with stress and emotions, (c) interpersonal relationships, and (d) daily life routines [15]. 1.2. Interventions for Internet Addiction Group counseling, CBT, reality therapy, psychological health education, anthropological methods, camp therapy, family therapy, self-help groups, sports therapy, acupuncture, pharmacotherapy, and comprehensive intervention have been used as prevention or intervention programs for IA [16]. A meta-analysis of randomized controlled trial (RCT) studies showed that group counseling and CBT are the most widely used methods to reduce IA [17]. Group counseling aims to provide psychological help and guidance in groups, where helpers form target groups based on the similarity of participants’ problems. It also addresses common developmental problems and psychological disorders of the group members through joint discussion, training, and guidance [18]. Huang et al. (2015) conducted a meta-analysis of 11 group counseling intervention studies for IA among Chinese college students and showed that group counseling is effective in enhancing the communication skills of students with IA and decreasing their obsessions and anxiety symptoms [19]. In addition, another meta-analysis found that group counseling intervention programs were effective in reducing four aspects of IA, including time management, interpersonal and health issues, tolerance, and compulsive online use [17]. The cognitive-behavioral model proposed by Davis (2001) points out that maladaptive cognitions are the proximal causes of pathological internet use. Maladaptive cognitions include distorted perceptions of oneself and the outside world, such as self-doubt, low self-efficacy, negative self-esteem, or the idea that people can only be respected on the internet [20]. In addition, individuals’ psychopathology (i.e., depression, social anxiety) and stressors from the external environment, such as families and school, are considered distal causes of IA [20]. CBT intervention programs for IA developed based on the cognitive–behavioral model consist of identifying the individual’s maladaptive cognitions, emotional and behavioral factors that trigger addiction, restructuring cognitions, learning appropriate behavioral skills, and receiving social support. Meta-analysis indicated that CBT programs showed positive changes in depression, anxiety, aggression, somatization, social anxiety, fearful anxiety, paranoid ideation, and psychoticism in individuals with IA [17]. However, Malinauskas and Malinauskiene (2019) conducted a meta-analysis that did not conclude that the CBT intervention group had a significant effect on the severity of IA, although CBT was the most used compared to other psychotherapies [21]. 1.3. Interventions for Internet Addiction among Chinese College Students For more than a decade, researchers have been developing various CBT group counseling intervention programs and examining their effectiveness among Chinese college students with IA. For example, Bai and Fan (2007) performed an intervention study of 48 college students with IA tendencies, 24 each in the intervention and control groups. A group counseling intervention program based on CBT was implemented for the intervention group, while the control group received no intervention. The results showed that in the post-intervention and 6-week follow-up surveys, the intervention group reported significantly lower IA scores than the control group [22]. Li and Huang (2017) performed an intervention study of 60 poor college students with IA. The intervention and control groups each consisted of 30 participants. Compared to the control group, the intervention group showed positive changes in self-esteem, mental health status, depression, and anxiety, as well as symptoms of IA after the intervention, and these effects were sustained for 2 months [23]. 1.4. The Present Study There are some issues that have not been adequately examined in previous intervention studies on IA. Firstly, the prevalence of IA among college students is becoming more pronounced with smartphones, and the prevalence of IA among female students is also gradually increasing [24]. Most intervention programs to date have targeted IA on computer terminals; therefore, programs with mobile device-based content are needed for IA prevention. In addition, previous intervention studies have included a high proportion of male participants and even exclusively male participants [25], which may create bias in the accuracy of the study results. Moreover, most intervention programs on IA to date have focused on the risk factors for IA, attempting to change problem behaviors of college students with IA through interventions such as alternative behaviors, skills training, and even cognitive restructuring. Few studies have considered “problem behaviors” from a positive perspective and focused on college students’ own strengths and resilience. Previous intervention programs neglect to guide college students to take a broad perspective on current situations by reflecting on the meaning of life. Furthermore, rigorous and high-quality RCT trials are still rare due to various limitations in the previous study design [26]. Most of the previous studies have involved intervention programs lasting eight or more sessions and several weeks, and no RCT studies have been found to examine the effects of short-term intensive-type intervention programs. To address the above research gaps, this study aims to examine the effects of a short-term intensive-type CBT intervention with the purpose of preventing IA among Chinese college students. The results of this study will provide a basis for developing preventive education for IA among Chinese college students and will also offer new options for psychological health education. 2. Methods 2.1. Study Design This was a randomized controlled trial comparing an intervention group with a control group. After informed consent was given to participants who met the selection criteria, the intervention group received an intervention program in addition to a training course on IA, while the control group received only the training course on IA. Data were collected three times for both groups: pre-intervention, post-intervention, and one month later. 2.2. Participants 2.2.1. Selection Criteria Students who scored above the cut-off value of 50 on Young’s Internet Addiction Test (YIAT); Students in their second year of college or above who have taken the required course of college psycho-health education in their first year; Students who understand the purpose of this study and can give informed consent to participate in this study; Students who are available to participate during the determined group intervention time frame. 2.2.2. Exclusion Criteria Students who are undergoing treatment for mental disorders; Students who are receiving other counseling or group activities related to IA. 2.2.3. Dropout Criteria After the intervention program started, the individual requested to withdraw from the program; The individual had difficulty continuing to participate in this program due to severe changes in his/her physical and mental conditions; Absence from at least two of the five intervention sessions. 2.2.4. Basis for Setting Sample Size We performed a preliminary analysis using G*Power 3.1.9.7 software (Kiel University, Kiel, Germany), taking into account the two-way analysis of variance with correspondence. Effect size f = 0.25 (Medium); Significance level = 0.05; Power (1−β) = 0.80. Under these conditions, the sample size was calculated to require a total of at least 28 participants (14 each in the intervention and control groups). The study was set up with a total size of 44 participants to account for dropouts in follow-up. 2.2.5. Method of Recruiting Study participants were recruited in two ways: by posting recruitment posters at the university and by recommendations from tutors. The participants were divided into an intervention group (group A) and a control group (group B) and were randomized separately for males and females, with gender as a stratification factor to avoid differences in gender proportions between the intervention and control groups. In this case, the “Randomized Stratified Substitution Block Allocation Table” prepared in advance was used. Participants were recruited in December 2020. The flowchart of the study participants is presented in Figure 1. A total of 50 college students were eligible to participate in this study, but 6 students were excluded due to personal reasons. As a result, 44 participants were eligible for random assignment, 22 in the intervention group and 22 in the control group. Of those who participated in the intervention program, 1 intervention group participant was excluded because she missed 2 sessions, and a total of 43 participants, 21 in the intervention group and 22 in the control group were finally included in the analysis. The study was approved by the ethics review committee of the university where the authors are affiliated. 2.3. Intervention Program Contents 2.3.1. Intervention Program Implementers We employed a group counseling intervention. The study was conducted under the leadership of two group leaders (both certified psychotherapists by the Japanese Health Counseling Association and certified psychological counselors by China) and with the assistance of four assistants (graduate students in psychology). 2.3.2. Theory and Techniques of the Intervention Program CBT Theory Yang et al. (2021) have identified risk factors that contribute to IA and protective factors that reduce IA in previous studies [27]. Based on the cognitive–behavioral model of Davis [20], we developed an intervention program focusing on learning problem-solving skills, restructuring social support cognitions, and promoting students’ awareness of alternative behaviors. Group Counseling Techniques The plan for group counseling includes three phases: an initiation phase, a work phase, and a termination phase [18]. In this study, the initiation phase was designed to create a group environment, help members get to know each other, provide a sense of security and belonging, and create interests and expectations to participate in group activities. Next, the work phase was designed to help members increase their affirmation of self and others through special games, discussions, and growth experience sharing, to make them aware of their own way of life, and to use group counseling as a place to practice so that members can apply what they learn in their daily lives. Finally, the termination phase was intended to allow members to reflect on each session, share their own impressions and takeaways, and cope with feelings of separation through mutual encouragement. Single Session Counseling Model Philosophy The Single Session Counseling Model (SSCM) is a short-term, intensive counseling model that not only incorporates the professional therapeutic perspective of Western culture (i.e., positive psychology) but also explores professional therapeutic perspectives from a Chinese cultural perspective [28]. The overall goals of SSCM are divided into three dimensions. The surface goal focuses on solving the clients’ specific problems; the middle goal focuses on improving the clients’ lifestyle, and the deep goal focuses on the clients’ discovery of the meaning and power of life as the key to counseling success. In this process, the counselor does not assume a professional role but rather respects the clients’ existential value, free will, and search for meaning in life in order to achieve the deeper goal of discovering the meaning and power of life and trusts in their ability to make decisions actively and constructively [28]. Our study incorporated the SSCM philosophy. Integration of Psychotherapy Techniques The intervention program consisted of five themes, with three to four different group activities for each theme. The main group activities were developed by the researchers using group counseling techniques, but we also established our own activities using different psychotherapy techniques to achieve specific thematic goals. For example, “metaphorical story” is an activity that applies the hypnotherapy techniques developed by American psychiatrist Milton Erickson, and the “Ikiru” film viewing program was developed based on the philosophy of existential therapy proposed by American psychiatrist Irvin D. Yalom. Furthermore, “stress temperament coaching” is a technique of the Structured Association Technique [29] proposed by Japanese psychologist Tsunetugu Munakata. In summary, the overall design of this intervention program was a group counseling intervention program based on CBT theory, and the SSCM philosophy was consistent throughout. In addition, the specific activities were an integrated intervention approach, with various psychotherapy techniques applied. A conceptual diagram of the intervention program is presented in Figure 2. 2.3.3. Intervention Program Goals The overall goal of the group counseling was to promote college students’ personal growth, break away from their IA, and better adapt to college life. The expected effect was that in the intervention group, college students would be able to find their superior resources, figure out how to cope with stress, improve their problem-solving skills and lifestyles, and find meaning in life. The frequency and duration of the intervention program was 90 min per session for a total of 5 sessions (7.5 h), delivered centrally over 1 weekend day. The first session was titled “E-Net Sharing”, and was designed to allow group members to get to know each other, sign group agreements, and share their histories, experiences, resources, and impressions about internet use. The second session was “Know Yourself”, and the goals were to learn the characteristics of one’s stress disposition and self-care behaviors, recognize one’s predominant resources, and increase one’s sense of self-esteem. The third session was “Problem Solving”, and the goals were to inspire the wisdom of group members to seek out each other’s superior resources and confront practical concerns. The fourth session was “Meaning of Life”, and the goals were to get the group members to think deeply about the meaning and values of life through sharing with each other and to increase their sense of meaning. The fifth session was “True Confessions”, and the goals were to share their insights with each other and process their feelings of separation among group members. The composition of the intervention program and the general content of the main activities are presented in Table 1. 2.4. Measurements 2.4.1. Internet Addiction Tendency IA tendencies were measured by Average Daily Internet Use Time (1 item) and Young’s Internet Addiction Test (YIAT) [30], which includes 20 items that are rated on a 5-point Likert scale. The total score ranges from 20 to 100, with high scores indicating high levels of IA. The cut-off value of 50 was used to identify IA in the present study [11]. 2.4.2. Psychological State Indicators Psychological state indicators were measured by the scales as follows. The K6 [31] is a 6-item short-form screening scale designed to measure psychological distress. This study uses the Chinese version of the K6, which has demonstrated acceptable reliability and validity [32]. Participants were requested to rate how often they felt the following six feelings over the past month: “nervous”, “hopeless”, “restless or fidgety”, “so depressed that nothing can cheer you up”, “everything was an effort”, and “worthless”. Each feeling was rated on a 5-point Likert scale. The total score ranges from 0 to 24, with high scores indicating a high degree of psychological stress. Sense of Coherence (SOC) is a global orientation that expresses the extent to which one has pervasive, enduring, and dynamic feelings of confidence, and it is considered part of personal resilience [33]. The participants’ SOC levels were measured using SOC-13 [34], which is the revised version of the 13-item Orientation of Life Questionnaire [33] for the Chinese. SOC-13 has three dimensions (i.e., comprehensibility, manageability, and meaningfulness). Each item was assessed on a 7-point Likert scale. The total score ranges from 13 to 91, with high scores indicating high levels of SOC. The Multidimensional Scale of Perceived Social Support (MSPSS) [35] is a self-administered measure of social support. It includes 12 items rated on a 7-point Likert scale measuring three sources of support, namely, Family, Friends, and Significant Other. The total score ranges from 12 to 84, with high scores indicating high levels of perceived social support. The General Procrastination Scale (GPS) [36] is a 20-item measure designed to measure procrastination traits across different situations. This study used the Chinese version translated and revised by Chu et al. (2010) [37]. Each item was assessed on a 5-point Likert scale. The total score ranges from 20 to 100, with high scores indicating high levels of procrastination. 2.4.3. Internet Addiction Improvement Motivation IA Improvement Motivation was measured by the Internet Addiction Improvement Motivation Scale (IAIMS) [38], which was developed based on a standardized smoking cessation motivation scale to measure motivation to improve IA behaviors. It consists of 10 questions that reflect the characteristics of thoughts and behaviors observed in the first three stages of the five-stage change model: Pre-contemplation (i.e., I do not want to reduce my internet use.), Contemplation (i.e., I have many resources to succeed in reducing my internet use.), and Preparation (i.e., I want to receive professional help to reduce my internet use.). Each item was assessed on a 6-point scale. The total score of each sub-scale was calculated, with high scores in the Contemplation and Preparation indicating high motivation to receive treatment for IA. 2.4.4. Subjective Evaluation of Self-status Stress (1 item), which measured the degree of stress currently felt by the individual. A higher score from 0 to 10 indicated a higher degree of stress currently being felt. Life Satisfaction (1 item), which measured the degree of life satisfaction currently felt by the individual. A higher score from 0 to 10 indicated greater current life satisfaction. 2.5. Statistical Analysis At baseline, we performed independent samples t-test between the two groups. To test the intervention effects, we applied analysis of covariance (ANCOVA) with the baseline scores of both groups as input covariates. First, we tested whether the assumptions of the ANCOVA were met for the scores of each item. If the interaction p > 0.05 for group x prior scores, ANCOVA was applied, and if p < 0.05, ANCOVA was considered unsuitable. To examine the follow-up effects of the intervention program, we conducted one-factor analysis of variance with repeated measures at three time points (pre-intervention, post-intervention, and one month later, respectively) for both groups and performed Bonferroni multiple comparisons for items for which the main effects were significant. The significance level was set at p < 0.05, with 0.05 < p< 0.10 being considered a significant trend and used as a reference to determine the overall trend. Analysis was performed using SPSS Ver 27.0. 3. Results 3.1. Participants The demographic characteristics of both groups are shown in Table 2. In addition, the mean age of the two groups was compared using a t-test, and the gender and grade headcount percentages were compared using the χ2 test. No significant differences were found. Therefore, random assignment confirmed that participants in both groups were homogeneous in their characteristics at baseline. 3.2. Baseline Characteristics Table 3 shows the mean values of the effectiveness indicators measured at baseline. Significant differences were found between the intervention and control groups at baseline in “Average Daily Internet Use Time” and “Contemplation” of IAIMS (p < 0.05). Other variables did not differ significantly between the two groups. 3.3. Intervention Effects We used analysis of covariance (ANCOVA) to examine changes in scores of the intervention and control groups from pre-intervention to post-intervention. The results showed that the “average daily internet use time” was 5.7 ± 2.2 h at baseline and 5.4 ± 1.3 h afterward for the intervention group, and 7.1 ± 2.1 h at baseline and 7.5 ± 2.9 h afterward for the control group. The interaction p = 0.015 (p < 0.05) for group x hours of baseline “average daily internet use time” was not suitable for ANCOVA. From paired-sample t-tests, no significant differences were found between baseline and posterior scores for both groups (p > 0.05). Mean YIAT scores for the intervention group were 59.7 ± 8.5 at baseline and 52.3 ± 8.2 at post, while the control group scores were 59.9 ± 6.1 at baseline and 58.8 ± 7.0 at post. Post scores for the intervention group were significantly lower than for the control group (p < 0.01, η2 = 0.16). The intervention group had baseline scores of 56.3 ± 9.6 and post scores of 59.8 ± 9.5 on the SOC-13, while the control group had baseline scores of 54.0 ± 10.1 and post scores of 53.4 ± 9.5. The intervention group’s post scores were significantly higher than the control group (p < 0.05, η2 = 0.07). Post scores for the intervention group showed a significant decreasing trend over the control group on GPS (56.1 ± 9.3 vs. 60.2 ± 11.8, p = 0.073, η2 = 0.02). For the “Preparation” of IAIMS’ scores, the post score for the intervention group was significantly higher than the control group (15.8 ± 2.7 vs.12.9 ± 3.8, p < 0.05, η2 = 0.08). For the “Stress” score, the intervention group’s post score was significantly lower than the control group (6.6 ± 1.7 vs. 7.3 ± 1.3, p < 0.05, η2 = 0.08). No other significant differences were found between the two groups in the K6, MSPSS, Pre-contemplation and Contemplation of IAIMS, and Life Satisfaction (Table 3). 3.4. Sustained Effects We performed one-factor analysis of variance with repeated measures and performed Bonferroni multiple comparisons for items for which the main effect was significant to examine the sustained effects of the intervention program. Significant differences in main effects were found in the intervention group for items such as YIAT, MSPSS, and Preparation of IAIMS. For YIAT scores, the main effect of the intervention program was significant at F (2,40) = 7.76, p < 0.01. Multiple comparisons showed that scores were significantly lower at the 5% level than before the intervention, both after the intervention and one month later. For MSPSS scores, the main effect of the intervention program was significant at F (2,40) = 4.87, p < 0.05. Multiple comparisons showed that scores were significantly higher after the intervention than before the intervention at the 5% level. In addition, for the 3 sub-scales of MSPSS, the results showed significant differences in the main effects in the “Friends” (F (2,40) = 3.86, p < 0.05) and the “Significant Others” (F (2,40) = 6.68, p < 0.01) perception of support. The multiple comparisons showed that it was significantly higher at the 5% level after intervention than before intervention for the “Friends”, and it was significantly higher at the 10% level after the intervention than before the intervention, and significantly higher at the 5% level one month later for the “Significant Others”. For the Preparation of IAIMS, the main effect of the intervention program was significant at F (2,40) = 4.26, p < 0.05. The multiple comparisons showed that it was significantly higher after the intervention than before the intervention at the 5% level. No significant differences were found among the three time points for the other scales based on repeated measurements (Table 4). In the control group, there were no significant differences among the three time points in repeated measures for any of the scales (Table 5). 4. Discussion Through Randomized Controlled Trial, this study examined the effects of the short-term intensive-type CBT intervention program for Chinese college students with IA. The results suggested that the intervention program may reduce Chinese college students’ IA symptoms and improve their SOC, and have the potential to decrease their tendency to procrastinate. In addition, sustained effects were shown to have the potential to improve students’ tendency toward IA and the perception of social support from significant others. The main results were discussed as follows. 4.1. Internet Addiction Tendency Previous studies on group counseling intervention with CBT [17,22,23] reported a reduction in IA symptoms in the intervention group after receiving the intervention program, and similar results were obtained in the present study. YIAT—the main outcome of this study—was used to measure the three-factor model classified as (a) Withdrawal and Social problems, (b) Time management and Performance, and (c) Reality substitute [39]. “Withdrawal” refers to the difficulties and bad mood one experiences when restricted from using the internet. “Social problems” refer to the use of the internet for social comfort and social interaction as a substitute for real-life social activities. “Time management” refers to compulsive internet use and an inability to control the amount of time one spends online. “Performance” is defined as neglecting one’s studies or work due to a lack of self-control. “Reality substitution” refers to viewing the internet as another reality and using it to avoid real-life problems [39]. Based on the above, we believe that a reduction in IA symptoms means a reduction in the symptoms exhibited by these factors. Before participating in this study, many participants had a vague sense of possible problems, such as excessive smartphone use, but did not have a proper awareness of IA and its impact on their physical and mental health. In the training course, the participants learned the correct knowledge about IA and became aware of their own IA problems. The main activity of the first session was titled “He/She is in my mind”. The participants directly role-played the smartphones, computers, or internet services that they were most immersed in their daily lives, allowing them to objectively observe their own IA behaviors from the perspective of the object of their addiction and inspiring them to think critically about their relationship with IA. In the second session, through learning self-care behaviors and discussion among group members, the participants developed their own list of effective health behaviors, such as writing, speaking, dancing, singing, drawing, exercising, and making videos, which could replace their IA behaviors. We think it worked directly on the “Reality substitution” factor of IA. The main activity of the third session, called “ Exchange of characters”, helped the participants find solutions to their current issues and improve their self-esteem through role-playing and brainstorming. We think it might be helpful in improving the “Withdrawal and Social problems” factor of IA. The theme of the fourth session was “The Meaning of Life”, which aimed at getting the participants to think about their meaning of life. Since it also included the concept of “Valuing time”, we thought it could be effective for the “Time management and Performance” factor of IA. The main activity of the fifth session was “Looking forward to the Future”, which prompted the participants to own sense of direction and goals for the future. Based on the above, we believe that this intervention program was effective in reducing IA symptoms among Chinese college students. 4.2. Psychological State Indicators The intervention improved the participants’ SOC, especially their meaningfulness. Based on the feedback, we think that the main effect came from the fourth session—“The Meaning of Life”. The philosophy of SSCM, which runs throughout the whole intervention program, also had a positive effect. Through the intervention, participants felt respected and understood, which motivated them to believe in their own strengths and innate resources, and inspired them to be willing to embrace a “meaningful” life. The reduction of participants’ procrastination was attributed to the third session—“Problem Solving”. In this session, the participants selected the “tendency to procrastinate” as a common problem they wanted to solve. Then the group leader used brainstorming to stimulate the potential of group members to find a solution together. We believe this was much more effective than delivering the answer directly. In terms of sustained effects, the intervention program had a significant effect on improving the participants’ perceptions of social support from “Significant Others”. Meta-analysis of group counseling intervention studies of Chinese college students’ IA showed that the intervention had effects on improving students’ communication skills and interpersonal relationships [17,19], and similar results were observed in the present study. Participants in the intervention group realized that they were not isolated, and each group member had similar problems, which could help them rapidly increase their sense of identity and belonging and present their deeper problems in a safe atmosphere. The support of group members allowed the participants to feel great interpersonal warmth. Furthermore, the mutual imitation and guardianship not only enable their personal growth, but the friendships formed through the activities also have an impact on their real lives. We think this increased their perceived social support from significant others. 4.3. Items with No Significant Improvement Effect The present intervention program did not result in a significant decrease in “Average Daily Internet Use Time” of college students. The internet is an important tool for modern education and entertainment; it is an integral part of college students’ daily life. A previous study suggested that internet use and online gaming had many beneficial effects on individuals [40]. King and Delfabbro (2016) emphasized that even in the case of gaming addiction, “online gaming time” was not equivalent to the dose of substance abuse and could not adequately represent the reality of an individual’s usage [41]. Fhkps and Leung (2013) suggested that complete abstinence was not a viable solution for any intervention [42]. In fact, some participants reported that their internet use time actually increased after the intervention because they needed to use the internet to study English and gather information for writing papers. Therefore, when evaluating the effectiveness of an intervention program, it was important to discern what use should be restricted, rather than only the hours spent online. The results of the present study showed that the K6 scale, which measured the psychological distress of college students, had no significant improvement after the intervention and one month later, which was different from the results of previous studies [17,23]. We think the main reason might be related to the timing of the intervention. It was implemented in mid-December 2020, when final examinations were approaching. The tension caused by the exams was high for many college students. Furthermore, the one-month follow-up period was around mid-January 2021, exactly when new waves of COVID-19 spread in mainland China; thus, people became more nervous about being infected. College students had to stay at home, which may not only lead to an increase in their internet use but also had a significant impact on psychological distress. Although the intervention program was designed with a stress management component aimed at improving the psychological distress of college students, its ameliorative effect was proven to be insufficient in the specific context of COVID-19. We should consider enhanced intervention programs in future studies. 4.4. Limitations and Future Directions The first limitation of this study is the potential bias in participants’ motivation. Although randomization was implemented in this study to assign subjects to intervention and control groups, neither participants, implementers, nor evaluators were blinded. Furthermore, when recruiting participants, some applied from a “Recruitment Poster”, while others were recommended by their academic tutors. Therefore, sampling bias may exist. The third limitation is the magnitude of power. Although the 28 participants satisfied the requirement to verify the effectiveness of the intervention program in this randomized controlled trial, the actual sample size of 43 participants was still small, making it difficult to confirm significant differences in the effectiveness in clinical practice, which may reduce the power of the study. Therefore, future studies should increase the number of participants and test intervention effects at multiple universities. The final limitation is the timing of implementation. It was a period of heightened tension over the COVID-19 infection in many countries, and Chinese college students were forced to stay at home, causing them to feel stressed. Due to the need to develop a short-term, intensive intervention program that could be implemented over a weekend for the duration of COVID-19, the five sessions were all important, yet the volume was undeniably enormous to implement all at once over one day. Intervention programs conducted for 8 weeks or longer have been shown to be more effective than interventions of shorter duration [43]. In the future, we think it is necessary to consider a program that provides a certain period of time for systematic intervention with the aim of achieving sufficient sustained effects. Finally, limited by the effects of short-term focused interventions, indicators of the effects of personality traits were not addressed in this study, and we will consider this component in future long-term intervention programs. 4.5. Contributions and Implications Despite some limitations, as noted above, there were several contributions that should not be neglected. Firstly, there were innovations and developments based on the conventional CBT intervention programs. Similar to the conventional CBT interventions, this program attempted to make participants aware of their attitudes toward internet use and IA symptoms through specific activities with the aim of eliminating “cognitive distortions”, and thus improving their problem-solving and adaptation skills. The difference was that instead of simply considering IA as a problem, we helped the college students think about their own lives from a broader perspective, which we thought may help improve their SOC while reducing their IA symptoms. Secondly, this study introduced the SSCM philosophy into a group counseling intervention program for the first time. That was, the group leader did not assume the role of an expert but rather believed in the problem-solving abilities of the participants and respected their own resources [28]. By reaching the three goals of SSCM, the results were expected to have a long-term positive impact on their lives. Thirdly, in addition to CBT and group counseling techniques, this intervention program also incorporated various psychotherapy techniques. These psychotherapies had the common therapeutic perspective of positive psychology and focused on positive resources rather than negative issues, which was consistent with the overall philosophy of this intervention program. This allowed the group leaders to focus on stimulating the group’s resources and creativity without criticizing or blaming the participants, and in an atmosphere where participants felt respected and understood, became aware of their own problems and resources, and that being proactive in finding solutions to problems can be useful in maintaining a positive outlook on their future lives. 5. Conclusions We developed a short-term intensive-type CBT intervention program for Chinese college students with IA. The results showed that the intervention program reduced college students’ internet addiction symptoms and procrastination and improved their sense of coherence. The intervention had sustained effects on internet addiction symptoms and perceived social support among Chinese college students. Acknowledgments The authors would like to thank all the participants for their participation in this research. Author Contributions Conceptualization, W.Y., W.H. and N.M.; methodology, W.Y., N.M. and W.H.; validation, W.Y. and Y.O.; formal analysis, W.Y. and N.M.; investigation, W.Y. and W.H.; resources, W.Y. and W.H.; data curation, W.Y., W.H. and Y.O.; writing—original draft preparation, W.Y. and N.M.; writing—review and editing, W.Y., N.M., T.S. and Y.W.; visualization, W.Y., N.M. and Y.W.; supervision, N.M., Y.O. and T.S.; project administration, W.Y. and W.H. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Medical Ethics Review Committee of the University of Tsukuba, Japan (Protocol Code 1541-1; approved on 24 November 2020). The international clinical trial registration number was UMIN000047480. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement No new data were created or analyzed in this study. Data sharing is not applicable to this article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart of Randomized Controlled Trial Participants. Figure 2 Conceptual diagram of the intervention program. ijerph-19-05212-t001_Table 1 Table 1 Intervention Program Composition. Phase Theme Composition The General Content of the Main Activities Initiation phase The 1st session E-Net Sharing Icsebreaker (Name yourself) Role play (He/She is in my mind) Metaphorical story (A pine in Huangshan Mountain) Role play (He/She is in my mind) Participants were asked to choose one object they are addicted to from smartphone, computer, online game, application, etc., name it, and write a monologue about what are his/her expectations, what kind of journey he/she has been on, and what are his/her feelings … Sign his/her name. Then discussion in the group. Work phase The 2nd session Know Yourself Icebreaker (Chicken evolution) Exercise (Stress temperament coaching) Group feedback Exercise (Stress temperament coaching) The group leader introduced participants to the characteristics of three kinds of stress temperaments and self-care behaviors. Then, participants shared with group members what they had learned about their own temperaments and stress coping strategies for themselves. The 3rd session Problem Solving Icebreaker (Rotten water in your house) Role play (Exchange of characters) Metaphorical story (Inner power) Role play (Exchange of characters) Participants were asked to fill out a list of roles and pick the roles they would like to play (i.e., child, old person, wise person, artist, dreamer, perfectionist, parent, clown, hero, etc.). Then write down the problems and challenges they were facing, and draw out three common problems among the group members, using brainstorming, or imagining the personality of their chosen roles, to find solutions to these problems one by one. The 4th Session Meaning of Life Icebreaker (A thousand knots in the heart) Film viewing (“Ikiru”) Group sharing (Before I die...) Metaphorical story (The Life Train) Film viewing (“Ikiru”) By viewing Japanese film director Akira Kurosawa’s masterpiece “Ikiru,” we explored the following themes. (i) Loneliness, (ii) Fear of death, (iii) Antidote to the fear of death, (iv) Bringing meaning to our lives, (v) Why does death promote growth in life? Termination phase The 5th Session True Confessions Icebreaker (your body) Group Activity (True Confessions) Group Activity (Looking forward future) Review (My harvest) Group Activities The group members wrote down the strengths they noticed about each other and their blessings for each other. They then formed a circle, and each member expressed what they were looking forward to in the new year and how they wanted to change themselves through gestures and slogans. Before the session ended, they reviewed all the intervention sessions and recorded their insights and impressions. ijerph-19-05212-t002_Table 2 Table 2 Demographic characteristics of the sample (n = 43). Variable Intervention Group (n = 21) Control Group (n = 22) p Age, Year ± SD 19.5 ± 0.8 19.9 ± 0.8 0.184 a Gender, n (%) Male 7 (33.3) 6 (27.3) 0.665 b Female 14 (66.7) 16 (72.7) Grade, n (%) 2nd year 17 (81.0) 15 (68.2) 0.576 b 3rd year 3 (14.3) 6 (27.3) 4th year 1 (4.8) 1 (4.5) a. independent samples t-test, b. χ2 test. ijerph-19-05212-t003_Table 3 Table 3 Results of the evaluation of the effects before and after the intervention. Measurements Baseline p a Post-Intervention p b Effect Sizes η2 Intervention Group (n = 21) Control Group (n = 22) Intervention Group (n = 21) Control Group (n = 22) Mean (SD) Mean (SD) Mean (SD) Mean (SD) IA Tendency Internet Use Time 5.7 (2.2) 7.1 (2.1) 0.042 * 5.4 (1.3) 7.5 (2.9) - YIAT 59.7 (8.5) 59.9 (6.1) 0.931 52.3 (8.2) 58.8 (7.0) 0.005 ** 0.16 Psychological State Indicators K6 6.5 (3.3) 6.1 (2.9) 0.649 5.9 (3.2) 6.5 (4.0) 0.389 SOC 56.3 (9.6) 54.0 (10.1) 0.451 59.8 (9.5) 53.4 (9.5) 0.048 * 0.07 MSPSS 55.3 (13.5) 54.0 (10.1) 0.715 61.0 (12.1) 57.0 (11.6) 0.223 GPS 58.0 (9.9) 58.9 (11.6) 0.783 56.1 (9.3) 60.2 (11.8) 0.073 † 0.02 IA Improvement Motivation Pre-contemplation 9.1 (3.0) 10.5 (4.2) 0.214 9.1 (3.2) 10.1 (3.8) 0.992 Contemplation 12.3 (2.8) 10.8 (2.0) 0.048 * 13.2 (2.2) 11.6 (3.2) 0.138 Preparation 13.7 (2.8) 12.0 (3.9) 0.114 15.8 (2.7) 12.9 (3.8) 0.029 * 0.08 Subjective Evaluation Stress 6.9 (2.0) 6.7 (1.5) 0.677 6.6 (1.7) 7.3 (1.3) 0.038 * 0.08 Life Satisfaction 6.8 (1.9) 6.7 (1.7) 0.814 7.7 (1.6) 6.9 (1.9) 0.106 ** p < 0.01; * p < 0.05; † p < 0.10, a t-test, b analysis of covariance (ANCOVA), IA = Internet Addiction, YIAT = Young’s Internet Addiction Test, SOC = Sense of Coherence, MSPSS = Multidimensional Scale of Perceived Social Support, GPS = General Procrastination Scale. ijerph-19-05212-t004_Table 4 Table 4 Results of Follow-up Effectiveness Evaluation of Intervention Group (n = 21). Measurements Intervention Group (n = 21) F Main Effect Multiple Comparisons Pre-Intervention (a) Post-Intervention (b) One Month Later (c) Mean (SD) Mean (SD) Mean (SD) IA Tendency IUT 5.8 (2.2) 5.4 (1.3) 5.8 (1.7) 0.55 n.s. YIAT 59.7 (8.5) 52.3 (8.2) 52.5 (9.1) 7.76 0.001 ** a > b *, a > c * Psychological State Indicators K6 6.5 (3.3) 5.9 (3.2) 6.6 (3.9) 0.55 n.s. SOC 56.3 (9.6) 59.8 (9.5) 58.1 (10.4) 1.32 n.s. MSPSS 55.3 (13.5) 61.0 (12.1) 59.5 (14.6) 4.87 0.013 * a < b * Family 17.8 (5.5) 19.5 (4.5) 18.9 (5.1) 2.35 n.s. Friends 20.0 (4.2) 21.2 (3.9) 20.0 (5.3) 3.86 0.029 * a < b * Significant Other 17.5 (5.8) 20.2 (4.5) 20.6 (5.3) 6.68 0.003 ** a < b †,a < c * GPS 58.0 (9.9) 56.1 (9.3) 56.9 (9.1) 0.94 n.s. IA Improvement Motivation Pre-contemplation 9.1 (3.0) 9.1 (3.2) 9.0 (2.9) 0.03 n.s. Contemplation 12.3 (2.8) 13.2 (2.2) 12.5 (2.3) 1.16 n.s. Preparation 13.7 (2.8) 15.8 (2.7) 14.5 (3.5) 4.26 0.021 * a < b * Subjective Evaluation Stress 6.9 (2.0) 6.6 (1.7) 7.3 (1.4) 2.36 n.s. Life Satisfaction 6.8 (1.9) 7.7 (1.6) 7.3 (1.9) 3.35 n.s. ** p < 0.01; * p < 0.05; † p < 0.10, n.s. = non-significant, IA = Internet Addiction, IUT = Internet Use Time, YIAT = Young’s Internet Addiction Test, SOC = Sense of Coherence, MSPSS = Multidimensional Scale of Perceived Social Support, GPS = General Procrastination Scale. ijerph-19-05212-t005_Table 5 Table 5 Results of Follow-up Effectiveness Evaluation of Control Group (n = 22). Measurements Control Group (n = 22) F Main Effect Pre-Intervention Post-Intervention One Month Later Mean (SD) Mean (SD) Mean (SD) IA Tendency IUT 7.1 (2.1) 7.5 (2.9) 7.4 (2.1) 0.30 n.s. YIAT 59.9 (6.1) 58.8 (7.0) 58.0 (10.1) 0.79 n.s. Psychological State Indicators K6 6.1 (2.9) 6.5 (4.0) 6.6 (3.6) 0.25 n.s. SOC 54.0 (10.1) 53.4 (9.5) 55.0 (7.6) 0.40 n.s. MSPSS 54.0 (10.1) 57.0 (11.6) 56.6 (9.6) 2.10 n.s. GPS 58.9 (11.6) 60.2 (11.8) 59.0 (11.2) 1.05 n.s. IA Improvement Motivation Pre-contemplation 10.5 (4.2) 10.1 (3.8) 10.1 (3.0) 0.33 n.s. Contemplation 10.8 (2.0) 11.6 (3.2) 11.4 (2.0) 1.14 n.s. Preparation 12.0 (3.9) 12.9 (3.8) 13.2 (3.6) 1.35 n.s. Subjective Evaluation Stress 6.7 (1.5) 7.3 (1.3) 7.0 (1.7) 1.65 n.s. Life Satisfaction 6.7 (1.7) 6.9 (1.9) 7.1 (1.8) 0.80 n.s. n.s. = non-significant, IA = Internet Addiction, IUT = Internet Use Time, YIAT = Young’s Internet Addiction Test, SOC = Sense of Coherence, MSPSS = Multidimensional Scale of Perceived Social Support, GPS = General Procrastination Scale. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kemp S. Digital 2019: Global Internet Use Accelerates Available online: https://wearesocial.com/blog/2019/01/digital-2019-global-internet-use-accelerates (accessed on 30 March 2020) 2. Hussain Z. Pontes H.M. Personality, internet addiction, and other technological addictions: An update of the research literature Multifaceted Approach to Digital Addiction and Its Treatment IGI Global Hershey, PA, USA 2019 46 72 3. China Internet Network Information Center (CNNIC) The 48th China Statistical Report on Internet Development 2021 Available online: http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202109/t20210915_71543.htm (accessed on 15 March 2022) 4. Chen B. Liu F. Ding S. Ying X. Wang L. Wen Y. Gender differences in factors associated with smartphone addiction: A cross-sectional study among medical college students BMC Psychiatry 2017 17 341 10.1186/s12888-017-1503-z 29017482 5. Akin A. Arslan S. Arslan N. Uysal R. Sahranç Ü. Self-control management and Internet addiction Int. Online J. Educ. Sci. 2015 7 95 100 10.15345/iojes.2015.03.016 6. Young K. Policies and procedures to manage employee Internet abuse Comput. Hum. Behav. 2010 26 1467 1471 10.1016/j.chb.2010.04.025 7. Cui L.J. Liu L. The influence of the Internet on the sociality development of undergraduates Psychol. Sci. 2003 26 64 66 8. Young K.S. Internet addiction: The emergence of a new clinical disorder Cyberpsychol. Behav. 1998 1 237 244 10.1089/cpb.1998.1.237 9. Kwok S.W.H. Lee P.H. Lee R.L.T. Smart Device Use and Perceived Physical and Psychosocial Outcomes among Hong Kong Adolescents Int. J. Environ. Res. Public Health 2017 14 205 10.3390/ijerph14020205 10. Shen Y. Meng F. Xu H. Li X. Zhang Y. Huang C. Luo X. Zhang X.Y. Internet addiction among college students in a Chinese population: Prevalence, correlates, and its relationship with suicide attempts Depression Anxiety 2020 37 812 821 10.1002/da.23036 32400075 11. Li L. Xu D.-D. Chai J.-X. Wang D. Li M.S. Zhang L. Lu L. Ng C. Ungvari G.S. Mei S.-L. Prevalence of Internet addiction disorder in Chinese university students: A comprehensive meta-analysis of observational studies J. Behav. Addict. 2018 7 610 623 10.1556/2006.7.2018.53 30010411 12. Shao Y.-J. Zheng T. Wang Y.-Q. Liu L. Chen Y. Yao Y.-S. Internet addiction detection rate among college students in the People’s Republic of China: A meta-analysis Child Adolesc. Psychiatry Ment. Health 2018 12 25 10.1186/s13034-018-0231-6 29849754 13. Liu Y. Li L. Ma Y. Liang Z.H. Sun Z.F. Cui J.G. Liu Z.Y. Zhao F.Y. Incidence rate of college students’ internet addiction in China: A meta-analysis Chin. J. Evid. Based Med. 2021 21 61 68 14. World Health Organization International Classification of Diseases for Mortality and Morbidity Statistics (11th Revision) 2019 Available online: https://icd.who.int/browse11/l-m/en (accessed on 15 July 2021) 15. Vondráčková P. Gabrhelik R. Prevention of Internet addiction: A systematic review J. Behav. Addict. 2016 5 568 579 10.1556/2006.5.2016.085 27998173 16. Qiao S.S. Li Y.Q. Liu L. A network Mete-analysis of the intervention effect of various measures on adolescents’ Internet addiction Chin. J. Sch. Health 2020 41 1167 1173 17. Liu J. Nie J. Wang Y. Effects of group counseling programs, cognitive behavioral therapy, and sports intervention on internet addiction in East Asia: A systematic review and meta-analysis Int. J. Environ. Res. Public Health 2017 14 1470 10.3390/ijerph14121470 29182549 18. Fan F.M. Theory and Practice of Group Counseling Tsinghua University Press Publishing Beijing, China 1996 13 15 19. Huang H.L. Su N.N. Zheng L.Y.U. A systematic review of domestic group counseling to the Internet addiction disorder of college students Chin. J. Sch. Health 2015 04 495 498 20. Davis R. A cognitive-behavioral model of pathological Internet use Comput. Hum. Behav. 2001 17 187 195 10.1016/S0747-5632(00)00041-8 21. Malinauskas R. Malinauskiene V. A meta-analysis of psychological interventions for Internet/smartphone addiction among adolescents J. Behav. Addict. 2019 8 613 624 10.1556/2006.8.2019.72 31891316 22. Bai Y. Fan F. The effects of group counseling on internet-dependent college students Chin. Ment. Health J. 2007 21 247 250 23. Li L. Huang Y. Research of Cognitive Behavioral Group Counseling’s Intervention on Poor College Students with Internet Addiction Mod. Educ. Sci. 2017 4 117 121 24. Yang W. Morita N. Zuo Z. Kawaida K. Ogai Y. Saito T. Hu W. Maladaptive Perfectionism and Internet Addiction among Chinese College Students: A Moderated Mediation Model of Depression and Gender Int. J. Environ. Res. Public Health 2021 18 2748 10.3390/ijerph18052748 33803092 25. Liu D. Lu N. He J. Tang H. Zhou L. Effects of internet addiction group counseling on internet using and study management in college students Chin. Ment. Health J. 2013 27 496 501 26. Yuan K.Z. Wen C. Dai Y. Zhu T.M. Assessing clinical intervention trials of pathological Internet use: A systematic review Chin. Ment. Health J. 2016 09 664 670 27. Yang W. Morita N. Ogai Y. Saito T. Hu W. Associations between sense of coherence, psychological distress, escape motivation of internet use, and internet addiction among Chinese college students: A structural equation model Curr. Psychol. 2021 1 10 10.1007/s12144-021-02257-7 28. Wang Z.H. Yang C.F. Single Session Counseling Model: With a Chinese Cultural Perspective Teacher Chang Culture Company Publishing Taiwan, China 1996 29. Munakata T. Learning Structured Association Technique Kanekoshobo Publishing Tokyo, Japan 2007 113 117 30. Young K.S. Caught in the Net: How to Recognize the Signs of Internet Addiction—And a Winning Strategy for Recovery Wiley New York, NY, USA 1998 31. Kessler R.C. Andrews G. Colpe L.J. Hiripi E. Mroczek D.K. Normand S.-L. Walters E.E. Zaslavsky A.M. Short screening scales to monitor population prevalences and trends in non-specific psychological distress Psychol. Med. 2002 32 959 976 10.1017/S0033291702006074 12214795 32. Xu H. Xiong H.Y. Chen Y.H. Wang L. Liu T. Kang Y.K. Fu L.L. Kang L. Xie L. Li N. The application of the Chinese version of K6 and K10 screening scales for psychological distress on the psychological investigation of college students Modem Prev. Med. 2013 40 4493 4496 33. Antonovsky A. Unraveling the Mystery of Health: How People Manage Stress and Stay Well Jossey-Bass San Francisco, CA, USA 1987 34. Dou W.J. Li H.P. Yang Y.J. Su D. Zhang T. Mei Y.Q. Ma L. Related factors of sense of coherence among patients with breast cancer living in rural areas during chemotherapy Chin. Ment. Health J. 2016 30 91 96 35. Zimet G.D. Dahlem N.W. Zimet S.G. Farley G.K. The multidimensional scale of perceived social support J. Personal. Assess. 1988 52 30 41 10.1207/s15327752jpa5201_2 36. Lay C.H. At last, my research article on procrastination J. Res. Pers. 1986 20 474 495 10.1016/0092-6566(86)90127-3 37. Chu Q. Xiao R. Lin Q. Research on the procrastination behavior and characteristics of university students China J. Health Psychol. 2010 18 970 972 38. Park J.W. Park K.H. Lee I.J. Kwon M. Kim D.J. Standardization Study of Internet Addiction Improvement Motivation Scale Psychiatry Investig. 2012 9 373 10.4306/pi.2012.9.4.373 39. Chang M.K. Law S.P.M. Factor structure for Young’s Internet Addiction Test: A confirmatory study Comput. Hum. Behav. 2008 24 2597 2619 10.1016/j.chb.2008.03.001 40. Carras M.C. Van Rooij A.J. Van de Mheen D. Musci R. Xue Q.L. Mendelson T. Video gaming in a hyper-connected world: A cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents Comput. Hum. Behav. 2017 68 472 479 10.1016/j.chb.2016.11.060 28260834 41. King D.L. Delfabbro P.H. Defining tolerance in Internet Gaming disorder: Isn’t it time? Addiction 2016 111 2064 2065 10.1111/add.13448 27297731 42. Fhkps B. Leung H. Development of an integrated intervention model for Internet addiction in Hong Kong Int. J. Child Adolesc. Health 2013 6 475 43. Chun J. Shim H. Kim S. A meta-analysis of treatment interventions for internet addiction among Korean adolescents Cyberpsychol. Behav. Soc. Netw. 2017 20 225 231 10.1089/cyber.2016.0188 28263660

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093532 sensors-22-03532 Article The Development and Concurrent Validity of a Multi-Sensor-Based Frailty Toolkit for In-Home Frailty Assessment https://orcid.org/0000-0002-2653-0523 Bian Chao 12* Ye Bing 23 Mihailidis Alex 123 Gambi Ennio Academic Editor 1 Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 1A1, Canada; alex.mihailidis@utoronto.ca 2 Toronto Rehabilitation Institute, University Health Network, Toronto, ON M5G 2A2, Canada; bing.ye@utoronto.ca 3 Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, ON M5S 1A1, Canada * Correspondence: chao.bian@mail.utoronto.ca 06 5 2022 5 2022 22 9 353204 4 2022 02 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Early identification of frailty is crucial to prevent or reverse its progression but faces challenges due to frailty’s insidious onset. Monitoring behavioral changes in real life may offer opportunities for the early identification of frailty before clinical visits. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioral and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor measurements. The sensor system consisted of multiple types of ambient sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioral and physical signs associated with frailty. Older adults’ perspectives were also included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen’s Kappa and Bland–Altman Plot were used to evaluate the agreements between the sensor and ground truth measurements. Excellent concurrent validity was achieved for all sensors except for the smart weight scale. The bivariate correlation between the smart and traditional weight scales showed a strong, positive correlation between the two measurements (r = 0.942, n = 24, p < 0.001). Overall, this work showed that the Frailty Toolkit (FT) is reliable for monitoring physical and behavioral signs of frailty in home settings. frailty sensors measurement validity internet of things smart home telehealth AGE-WELL NCE499052 This research was funded by AGE-WELL NCE (Aging Gracefully across Environments using Technology to Support Wellness, Engagement and Long Life NCE Inc.)—Networks of Centres of Excellence of Canada Grant Number 499052. The APC was funded by AGE-WELL NCE. ==== Body pmc1. Introduction According to World Population Prospects: the 2019 Revision, one in six people in the world will be over age 65 by 2050 (16%), up from one in 11 in 2019 (9%) [1]. Older adults are at a high risk of disability, long-term hospitalization, unfavorable discharge, and death after injury. However, age itself is a poor risk indicator because of the heterogeneity of older adults [2,3,4]. The concept of “frailty” identifies older adults with low physiological reserves, vulnerability to illness, and a high risk of disability, institutionalization, and death [5,6]. People in a state of frailty are vulnerable to stressful situations and gradual decline towards dependence if the frailty state is not detected early enough. Frailty will put an enormous burden on older adults and their family caregivers including impaired quality of life, loneliness [7], and increased healthcare costs [8]. The incremental 1-year healthcare costs associated with frailty went from CAD 10,845 to CAD 12,360 in Canada [9]. In Germany, progression from non-frailty to frailty caused healthcare costs to increase by 54% if three or four frailty symptoms were present, and 101% if five frailty symptoms were present [10]. Despite the adverse outcomes, there is an opportunity to prevent or remedy frailty [11]. Studies have shown that frailty is a dynamic process characterized by frequent transitions between frailty states over time [11,12]. Fried et al. defined three frailty states based on the number of phenotypic criteria that a person meets, such as slowness, weakness, or shrinking [6]. A person is frail if meeting three to five phenotypic criteria, pre-frail if meeting one or two criteria, and non-frail if none of the phenotypic criteria are present. The dynamic transitions between frailty states mean that pre-frail people can transition to non-frail with intervention. The likelihood of transition between frailty states depends highly on one’s preceding frailty state [11]. For older adults living with frailty, the probability of transitioning to the prefrail state decreases over time, while the probability of dying increases. Therefore, early detection is critical for preventing or reversing frailty. Monitoring older adults’ behavioral changes could provide insight into how frailty develops [13]. Assessing these changes in real life may help identify frailty early [13]. Technologies may offer cost-effective opportunities for assessing frailty in older adults’ real lives, such as home environments. Recent developments in sensor technologies for health monitoring have shown opportunities to monitor frailty signs at home. Wearable sensors from different manufacturers (e.g., BioSensics, Newton, MA, USA; Shimmer, Dublin, Ireland; Actibelt, Munich, Germany) were used to measure frailty criteria such as muscle strength [14], gait [15], and physical activities [16]. Researchers also used wearable sensors during standardized physical tests, such as Timed Up and Go to assess frailty [17]. However, research on technologies for assessing frailty at home is still in its infancy. Most existing systems focused on a single dimension of the multidimensional frailty and only on homogenous sensors such as wearables [18,19,20]. Very few studies used non-contact ambient sensors that can be set up in living environments to assess frailty [21]. Many frailty criteria and early signs associated with frailty were not studied using heterogeneous technologies in home settings. Examples of these criteria or early signs include sedentary behavior [22], constricted life space [13], declined Activities of Daily Living (ADLs) (e.g., stair climbing) [23], or self-report exhaustion [6]. Many of these criteria are measurable by off-the-shelf sensors. For example, wearable sensors, such as Fitbit [23] or force sensors [24], can assess sedentary behavior. Accelerometers and GPS [25] can measure life-space mobility. Moreover, inertial sensors [26,27,28] or cameras [29] can measure ADLs such as chair stand or stair climbing. Additionally, previous studies have used speech-recognition technology to capture health data for cancer, diabetes, or heart failure [30]. Similar technology could also collect self-report data for assessing frailty. Moreover, while Internet connectivity and remote access should become an essential design requirement for remote health monitoring systems [31,32], most existing systems for assessing frailty lack telecommunication capability, making the systems not convenient or scalable for real-life home deployment. Modern technologies such as the Internet of Things (IoT) and Cloud Computing have demonstrated their capabilities to overcome the remote access barrier in many health care applications (e.g., telemedicine, medical imaging, public health, and patient self-management) [33]. This paper introduces a home-based frailty assessment system named Frailty Toolkit (FT). FT adopts the following design principles to fill some of the gaps identified above:FT consists of a unique and new collection of heterogeneous customized sensors that use off-the-shelf sensing modules. FT was tailored for home-based frailty assessment by measuring early behavioral signs of frailty under free-living conditions in older adults’ daily lives. The system does not require older adults to perform standardized physical tests, such as gait speed tests or chair stand tests, which could need extra supervision and compliance to perform correctly. FT consists of a unique and new collection of heterogeneous off-the-shelf sensors tailored for home-based frailty assessment. The sensors measure early behavioral signs of frailty in older adults’ daily lives. FT uses state-of-the-art cloud services from major commercial cloud service providers. The cloud technologies enable real-time telecommunication and the use of advanced data analytics. The use of cloud services can benefit research data analysis for this study and future real-world deployment of similar systems in terms of implementation process and lessons learned. FT makes no use of cameras or wearable sensors. Such devices are perceived to have privacy and obtrusiveness concerns, undermining user acceptance. Instead, ambient sensors require minimal effort from end-users to monitor frailty. Users are not required to carry any device. The design of FT involves older adults’ perspectives from the beginning to enhance its usability. The overall objective of FT research is to design and develop a multi-sensor-based system for use in homes and evaluate the system’s effectiveness in assessing frailty. The specific objective of this paper is to validate the concurrent validity of measuring frailty criteria using multiple sensors in a simulated home lab environment. Analyzing habits or daily patterns related to frailty was not the focus in the current stage. The rest of this article is structured as follows: Section 2 presents the design method and experiment protocol. Section 3 reports the statistical results. Section 4 discusses our study with guidance for future work. Finally, Section 5 presents the conclusions. 2. Materials and Methods 2.1. Frailty Criteria and Sensor Selection The sensor selection for FT was based on frailty criteria defined in existing clinical frailty scales and signs that were significantly associated with frailty by previous studies. We used Fried’s frailty phenotype model [6] as the primary reference clinical model. We also referenced the cycle of frailty theory [34] and phenotypes that are significantly associated with frailty, such as life-space mobility [13] and ADLs [23]. The goal of the design was not to include all related frailty criteria but certain highly related ones that can be measured by sensors meeting the design principles above. Certain frailty criteria were not included due to not satisfying the design principles described above. For instance, despite being an effective criterion for identifying frailty [35], walking speed measurement requires a wearable, a vision-based sensor, or a mat sensor (e.g., GAITRite) [36,37]. When used in unsupervised home settings, these sensors are subject to difficult user acceptance, declining adherence, and privacy concerns [38,39,40,41]. The design of the FT focused on ambient sensors without using cameras or wearable sensors. FT also does not require a fixed space from home settings for using the GAITRite-like mat sensor. The selection of frailty criteria aims to build a new frailty assessment paradigm by combining selected frailty criteria from different models tailored for ambient-based frailty assessment under free-living conditions. Accordingly, we can identify effective off-the-shelf sensing modules to measure those criteria or phenotypes and customize the sensors for FT using the sensing modules. We chose ambient sensors instead of wearable or vision-based sensors because they are non-invasive and can preserve privacy. 2.1.1. Strength Handgrip strength was one of the five phenotypes defined in Fried’s frailty model. However, the hand dynamometer’s absence of remote communication, inadequate user-friendliness, and rare availability even in primary care settings limit its usage in the home by older adults without assistance [42]. To find a home-friendly sensor to measure strength, we looked into the cycle of frailty theory shown in Figure 1, which defines a progressing cycle and a broader range of interrelated frailty phenotypes that include the five criteria in Fried’s phenotype model. We found that strength and immobilization belong to the same progressing cycle (see Figure 1). Immobilization is the exogenous cause of sarcopenia characterized by progressive and generalized loss of skeletal muscle mass and strength [43,44,45,46]. Moreover, another study found that immobilization was associated with sedentary behavior [47]. As sedentary behavior is associated with frailty [22], it may be an alternative underlying strength indicator for off-the-shelf sensors to measure at home. We, therefore, designed a mat sensor to monitor sedentary behavior instead of straight measuring handgrip strength. Equation (1) calculates the sedentary duration. Sedentary duration, s = tunoccupied − tpre_occupied(1) where: tunoccupied = the time when a mat sensor detects an unoccupied seat tpre_occupied = the time when a mat sensor detects a previously occupied seat In addition to sedentary behavior, strength can also be measured by physical performance tests such as standing balance, chair stand, and stair climbing [48]. Among these tests, stair climbing time was significantly associated with the early onset of frailty [23]. A frail person would take a longer time to climb stairs compared with a non-frail person [23]. Similar to sedentary behavior, stair climbing can also be measured by off-the-shelf sensors more easily than handgrip strength in an unsupervised home environment if a flight of stairs is available. In this study, we chose to use ultrasonic distance sensors to detect human presence on a flight of stairs for calculating stair climbing time. We used two distance sensors and placed them at the first and last step of a flight of stairs to capture the start and end of a stair-climbing event. Equation (2) calculates the stair climbing time. Stair climbing time, sc = tdistance_sensor2 − tdistance_sensor1(2) where: tdistance_sensor1 = the time when the first distance sensor detects a person’s proximity tdistance_sensor2 = the time when the second distance sensor detects a person’s proximity 2.1.2. Self-Report Exhaustion A customized Raspberry Pi-based smart speaker collects the self-report exhaustion data. The smart speaker was programmed to collect users’ speech through a 6-mic audio board (ReSpeaker 6-Mic Circular Array Kit for Raspberry Pi, Seeed Technology Inc., Shenzhen, China). The smart speaker used a customized cloud-based Amazon Lex chatbot to manage the conversation with its users. Amazon Lex is an Amazon Web Service that provides automatic speech recognition and natural language understanding technologies to create a Speech–Language Understanding system or a chatbot. The Lex chatbot was built to ask two questions from the Center for Epidemiological Studies-Depression (CES-D) scale [49] for the self-report exhaustion data collection. Unlike the commercial smart speakers, such as Google Home or Amazon Echo, that must be triggered using a keyword from a user, the smart speaker in this study was developed to be easier to use by older adults. Firstly, the smart speaker was programmed to proactively initiate conversations and ask questions without using a wake-up word from older adults. The conversation would be initiated when other sensors in FT detected a person. Secondly, the smart speaker only asked three questions that accepted single-word answers. The first question was an availability confirmation question that asked users if they were available to answer questions at the moment. If the user answered “yes”, the following two questions were asked sequentially: “Do you feel that everything you did was an effort, or you could not get going in the last week?” and “How often in the last week did you feel this way?”. Answer options (e.g., yes or no) were prompted to the users following each question. The prompts guided older adults to choose the right words to minimize potential misunderstandings in the conversation when answering the questions. While the first two questions were a “yes” or “no” question, the third question expected users to answer one of three words: “always”, “sometimes”, or “rare”. Users who responded “sometimes” or “always” were categorized as frail for this criterion. Lastly, the AWS Lex chatbot was programmed with a fallback plan to repeat questions if the first attempt was not successful. A sample interaction between the smart speaker and a user is illustrated in Figure 2. 2.1.3. Physical Activity Fried’s phenotype model uses calorie consumption per week to measure physical activity. Technologies such as smartwatches or computer vision can measure calorie consumption or estimate consumption by identifying activities or food [50,51]. However, these technologies either require high compliance from users or violate user privacy. Instead of measuring calorie consumption, we proposed to use motion sensors to measure gross movement at room levels through the number of sensor triggers. Information such as presence duration in a room (e.g., bedroom, living room) and frequency of room transitions can be obtained. An earlier study has shown the potential of using room transition data to distinguish frailty statuses [52]. The study used Bluetooth beacons placed in each room and a smartphone carried by users to detect room transitions. This study used motion sensors as they may be a more effortless and unobtrusive alternative to capture similar information. Each functional room has one motion sensor installed. The room presence duration can be calculated using the Equation (3). In addition, the mat sensor can also be used to provide additional information on low physical activity, as immobilization described in Section 2.1.1. (Strength) is related to low activity in Figure 1. Room presence duration, r = tnext_motion_sensor − tpre_motion_sensor,(3) where:tnext_motion_sensor = the first confirmed time when the next motion sensor detects a person tpre_motion_sensor = the first confirmed time when the previous motion sensor detects a person. 2.1.4. Weight Weight loss can be easily measured by tracking weight changes using a bathroom scale. To facilitate the use of a low-cost home bathroom scale, we modified a standard digital bathroom scale by adding an Arduino-based microcontroller with a wireless communication module and a LED light. With the modification, the scale can initiate and prompt the weight measuring process by working with other FT sensors and sending weight data to the IoT platform. For example, once the motion sensor in the bathroom detects a person’s presence, the smart weight scale would receive a command from the motion sensor immediately to blink the LED light prompting the start of the weight measuring process. The smart weight scale was factory calibrated as the weighing module was not modified. 2.1.5. Life Space Mobility Life space is one of the behavioral precursors of frailty, as a large cohort study found that women who left the neighborhood less frequently were 1.7 times more likely to become frail than those who left the neighborhood four or more times per week [13]. To estimate life space from home without using wearable technology such as GPS, we used a simple door sensor installed at the entrance door to monitor home entry and exit. Thus, parameters associated with life space, such as frequency and duration of being away from home within a specific time frame, can be estimated. The outing duration can be calculated using the Equation (4). However, as not every door event indicates a real outing, a confirmed outing can be determined by combining the door event with information from other sensors as shown in the Equation (5). Table 1 shows the final selection of sensors. Outing duration, od = tdoor_event − tpre_door_event(4) where: tdoor_event = the time when a door sensor detects a door opening event tpre_door_event = the time of a previous door opening event (5) Outing, o=1,  if od>5 min and no events from other sensors0,  if od≤5 min or events from other sensors 2.2. User-Centred Design Deploying technologies into older adults’ homes faces many challenges caused by older adults’ physiological impairments, stigma concerns, obtrusiveness, or technical barriers [53]. The technology design process should involve older adults and other stakeholders to understand their living habits and home environments, their preferred ways of interacting with the technologies, and their preferred functionalities and deployment process [53]. We conducted focus group interviews with older adults before the start of the design [54] and adopted the following practical design recommendations learned from the focus groups. Each sensor in FT operated autonomously after powering on. No further interventions were needed. The software running on the sensors could be updated remotely without user interaction. The only requirement from the users was to recharge the batteries or plug in the power adapter, which was found acceptable by older adults [54]. Long battery life was essential for the long-term use of health monitoring devices, with a minimum of 1 week considered ideal [55]. Low-power sensors and microcontrollers enable sensors in the toolkit to run for months before recharging. For instance, a similar passive infrared motion sensor can last at least 3 months using two AA batteries [56]. This minimal effort from the users was positioned to reduce the user-perceived complexity of the system and potential operating errors. Moreover, the smart speaker in FT could be placed in a convenient location according to the older adults’ lifestyles. For example, some older adults preferred to interact with the speaker in the kitchen while preparing food. Others chose to put the speaker near the bed for a quick conversation before sleeping. In addition, to enhance usability, the smart speaker would play a soft prompting ringtone before the frailty conversation, resembling the one used in the airport before any announcements. At the end of the conversation, the speaker would confirm all information was received and appreciate users’ responses. Additionally, we gave users’ feedback on the smart weight scale by using an LED light to show weight measurement progress. When the IoT platform received the weight data successfully, the LED light turned green to tell the user that the measurement was complete. An audio prompt can be added in the future iteration of the development to further enhance usability for older adults with sight problems. Other design considerations that have not been incorporated into the current system but will be in the following design iteration include: (1) Adding physical buttons to the smart speaker for those older adults who prefer the familiar, simple button press to the verbal conversation with the smart speaker. The goal here was to reduce the complexity or probability of confusion to enhance usability. (2) Using existing technologies such as smartphones to improve data collection and communication. The use of smartphones, in this case, does not mean older adults have to carry smartphones as the earlier studies did [57,58]. Instead, the under-used smartphone or other existing technologies at home could be reused to enhance data collection in a user-familiar way, such as text messaging or app notification. For instance, an AI-powered text messaging chatbot can ask self-report questions and obtain user responses by text messages. Information about frailty can also be shared by text messages or an app notification. (3) Adding warming functionality into the mat sensor to enhance technology enjoyment. (4) Adding enjoyable functions to the smart speaker, such as playing music and telling jokes [54]. 2.3. Protocol As this study aims to validate the sensor measurements but not frailty assessment results, a convenient sample of healthy young participants is sufficient to achieve the goal. A convenience sample of nine healthy, young adults was recruited by sending group emails to research labs and posting flyers in hospitals of the University Health Network (UHN), Toronto. The recruitment lasted from May to August 2021. Participant’s inclusion and exclusion criteria are as follows: Inclusion criteria Minimum 18 years old; Able to understand and speak English; Able to give informed consent; Able to attend at least one experiment session. Exclusion criteria Have trouble getting in and out of bed without assistance; Have trouble walking or always use a wheelchair; Cannot speak due to speech impairment; Cannot hear due to hearing impairment. Participants’ demographic information was collected to determine their eligibility. Each participant attended one experiment session in a simulated home called HomeLab at KITE Research Institute of Toronto Rehabilitation Institute, UHN, Toronto, Canada. The HomeLab is a “home within a lab”, resembling a typically furnished single-story one-bedroom apartment with functional plumbing and wiring. Figure 3 illustrates the HomeLab layout and sensor setup. Each participant performed a series of daily activities during the experiment session to test pre-installed sensors in HomeLab. These activities included room transitions (to test motion sensors), main entrance entry and exit (to test the door sensor), stair climbing (to test distance sensors), weight measuring (to test the smart weight scale), sitting (to test the mat sensor), and exhaustion question answering (to test the smart speaker). Each participant completed three runs of the experiment. Each run of the experiment took at least 15 min. In the first run, each participant was given detailed verbal instructions by a researcher (CB) on the activities to be performed. The instructions included going to a particular room (e.g., living room), measuring weight using the smart weight scale, climbing a flight of stairs, sitting on a chair with a mat sensor, and conversing with the smart speaker. Participants were then asked to perform similar activities based on their own decision and pace in the second and third runs. A summary of the experimental protocol is shown in Table 2. Participants were required to perform the activities defined in the protocol at least once. It was expected that participants would repeat these activities multiple times. These activities triggered the sensors to generate sensor data. Depending on the sensor type, the data could contain information about the room where a participant is present (e.g., living room or dining room), weight, occupancy status for the first or last step of the flight of stairs, chair occupancy, or door opening status. All data were transmitted to a cloud-based IoT platform and immediately timestamped when stored in a cloud database attached to the IoT platform. The sensor data were then transferred to a server at the UHN, Toronto, Canada. All experiment sessions were video and audio recorded. The video and audio recordings were used to extract ground truth data for the activities performed by each participant except for the weight. For instance, the ground truth data for the room-level physical activity were the room presence in each room in HomeLab for an individual. The weight ground truth data were manually collected using a traditional non-digital weight scale in HomeLab at the end of each session. All activities were performed under the supervision of a researcher (C.B.). During the experiment, the researcher was not in HomeLab but stood at a catwalk overhanging around the lab with a bird’s-eye view of the lab. Break periods were preserved between different test runs. A schematized protocol for the experimentation is shown in Figure 4. 2.4. Data Processing The sensor measurement for each frailty criterion was compared with the corresponding ground truth measurement (i.e., video or audio recordings, traditional mechanical weight scale). The agreements between the two approaches were assessed using the Cohen’s Kappa test and Bland Altman plots. The Cohen’s Kappa test was used for categorical data from the motion sensor. The Bland Altman plots were used for continuous data, such as sedentary time and stair climbing time. Bivariate correlation was used to analyze weight data. All statistical tests were performed by the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA). The interpretation of agreement strength for Cohen’s Kappa was following Landis and Koch’s guidelines (1977) [59]. Cohen’s Kappa was calculated using the Equation (6). Cohen’s Kappa, k = (po − pe)/(1 − pe)(6) where: po = the relative observed agreement between the sensor and ground truth measurement pe = the hypothetical probability of chance agreement For Bland Altman plots, more than 20% of the value that fell outside the limits of agreement (LoA) would be considered no agreement between the two methods. p values less than 0.05 were considered to be statistically significant. The upper and lower LoA were calculated using the Equations (7) and (8). Lower Limit = Mean of difference − (1.96 × Standard deviation of difference)(7) Upper Limit = Mean of difference + (1.96 × Standard deviation of difference) (8) Once the sensor measurements are validated, the toolkit will be tested with older adults living with and without frailty to validate clinical effectiveness in detecting frailty. We plan to use the sensor data to train classic machine learning models such as logistic regression, tree-based classifiers, and support vector machines. Models’ sensitivity and specificity will be estimated. 3. Results The three repeated runs of the experiment from nine participants generated 580 activities in total. 3.1. The Smart Speaker for Self-Report Exhaustion The smart speaker recognized and recorded participants’ answers to the two questions from the CES-D Depression scale. The recognized answers by the smart speaker had a 100% agreement with those recorded in the audio recordings (n = 27). 3.2. The Motion Sensor for Room-Level Physical Activity Cohen’s Kappa was used to analyze the agreement in room-level physical activity measurements between motion sensors and video recordings. The proportion of observations in agreement po = 0.9558 and the proportion in agreement due to chance pe = 0.2882. According to the Equation (6), the two methods generated a kappa value of k = (0.9558 − (0.2882))/(1 − (0.2882)) = 0.938 which showed an almost perfect agreement. The kappa value was significantly different from zero (k = 0.938, p < 0.001). 3.3. The Door Sensor for Life-Space Mobility The door sensor had an 87.5% successful rate in detecting a door entry/exit event. However, the five undetected door entry/exit events were caused by a technical issue in the door sensor and solved immediately during the experiment. Therefore, the accuracy reaches 100% when excluding these outliers. See Table 3 of the percentage agreement. 3.4. The Mat Sensors for Sedentary Behavior The Bland–Altman plot was used to assess the agreement of the data from the mat sensor (n = 42) and distance sensor (n = 38) with their corresponding ground truth data extracted from the video recordings. Figure 5 shows the plot of sedentary time duration between the two methods. The plot shows a mean difference, also called bias, of −0.286, presenting as a solid, purple line. The standard deviation is 8.046. According to the Equations (7) and (8), the upper LoA was calculated as −0.286 + (1.960 × 8.046) = 15.485. The lower LoA was calculated as −0.286 − (1.960 × 8.046) = −16.057. LoA is shown as the area between the two solid, green lines with 95% LoA. Only 4.8% (2 out of 42) values fall outside the LoA, suggesting a good agreement between the two methods [60,61]. As Figure 5 shows, the values are uniformly spread below and above the bias/mean difference within the LoA, suggesting no proportional bias. The result is also confirmed by linear regression (t = 1.097, p = 0.279). 3.5. The Distance Sensors for Stair Climbing Time The distance sensor had a 50% success rate in detecting a stair-climbing event, including climbing up or down a flight of stairs, as shown in Table 4. The detected stair climbing time and ground truth time were compared using the Bland–Altman plot. Figure 6 reports a mean difference of 0.526 between the two measurements, shown as a solid, purple line. The standard deviation is 4.273. According to the Equations (7) and (8), the upper LoA was calculated as 0.526 + (1.960 × 4.273) = 8.901. The lower LoA was calculated as 0. 526 − (1.960 × 4.273) = −7.848. LoA is shown as the area between the two solid, green lines with 95% LoA. Most of the values are inside the LoA, suggesting a good agreement between the two methods. As Figure 6 shows, the values are uniformly spread below and above the bias within the LoA, suggesting no proportional bias. The result is also confirmed by linear regression (t = 0.653, p = 0.518). 3.6. The Smart Weight Scale for Weight There is a significant difference in the data generated from the two measurements. The difference could be caused by the incorrect operation or inaccurate readings of the traditional mechanical weight scale. However, bivariate correlation shows a strong, positive correlation between the two measurements, r = 0.942, n = 24, p < 0.001 (see Figure 7). This suggests that the smart weight scale can still track an individual’s weight change, but the measurement accuracy should be reexamined. 4. Discussion The FT has been designed to monitor frailty in home settings and assess it remotely before clinical visits. The toolkit helps identify frailty early, which can increase awareness of heightened vulnerability for older adults, allow for the institution of appropriate care plans, and allow for newly emerging evidence for the treatment of those who are frail to be readily implemented [62]. This work contributes a unique and novel selection of different ambient sensors and a customized smart speaker, extending the perspective of a home-based frailty assessment that was previously focused on IMU sensors and mobility-related parameters [63]. FT can therefore collect a broader set of behavioral and physical signs of frailty from older adults’ daily lives without being as intrusive as wearable or camera-based sensors. We intended to design the FT to require zero to minimal effort from older adults and passively monitor frailty from the living environment. The findings of this research will benefit clinicians, older adults, or family caregivers to remotely assess and monitor for frailty. FT can be used as a digital pre-clinical frailty screening tool at home by clinicians and older adults. It can also be used in collaboration with comprehensive clinical frailty assessment to monitor frailty progression and intervention effectiveness. This study is an essential foundational work in determining the system’s clinical effectiveness in assessing frailty. This phase of the research tested the concurrent validity of the sensor measurements of the proposed system. The statistical analysis showed that excellent measurement agreements were achieved for motion, mat, distance, and door sensors. This indicated that most of the sensors in the toolkit can generate correct readings for calculating frailty indicators, such as room presence duration, stair climbing time, and sedentary duration. However, there were missed detections from the motion sensors in the experiments. Most of the missed detections came from the first two participants. This problem turned out to be loose jumper wire connections that were not found in the dry run but revealed with the first two participants. After fixing the problem, no glitches were found for the rest participants. If the first two participants were excluded from the analysis, the agreements should be higher. Moreover, the distance sensor had only a 50% success rate in detecting a stair-climbing event. We found that the missed detection was because some participants used one side (e.g., left) of the stair to climb, whereas the sensors were installed on the opposite side (e.g., right). This caused the distance between the participants and the sensors to be beyond the distance threshold (60 cm), which did not trigger the sensors. In the future, different distance thresholds and mounting locations on the wall will be tested to find the ideal settings. The smart weight scale did not show a good agreement with the traditional mechanical weight scale based on the Bland Altman plot method. As mentioned in the Results section, this lack of statistical agreement could be caused by inaccurate readings from the traditional weight scale during the experiments. However, the bivariate correlation between the two devices was strong and positive. The correlation coefficient of r = 0.942 is close to the one achieved (r = 0.993) in a previous study that tested the agreements between a modified bathroom scale and a traditional weight scale for frailty assessment purposes [64]. A highlight of the proposed system is the smart speaker. We successfully tested a customized smart speaker that uses context information that other ambient sensors provide to initiate conversations instead of a wake word required by commercial smart speakers. This is the first time a smart speaker was used for collecting self-report exhaustion data for frailty assessment. The role of the smart speaker in FT can be extended well beyond the data collection for self-report exhaustion. The smart speaker opens up new possibilities for collecting data from a multidimensional perspective around physical activity, food intake, life space, and more frailty indicators. The technical capabilities of the smart speaker also allow more functions to be added in the future. For example, more enjoyment features, such as playing music, can be integrated into the chatbot to enhance its usability. In addition, the smart speaker can be more helpful by giving users prompts or reminders about their health changes identified by FT and recommending interventions. One strength of the study is that the design of FT involved older adults’ voices from the beginning, which has not been found in similar technologies for assessing frailty. Flexible sensor placement, simplified human-computer interaction, and LED light prompting were some of the recommendations from the focus group study and were incorporated into the FT design. Another strength from the technical perspective is that we successfully implemented and tested the “trigger-action” mechanism between the IoT sensors to improve system usability and enhance the precision of data collection for particular sensors, such as the smart weight scale and smart speaker. With the mechanism, triggering a motion sensor or a mat sensor can further activate a smart weight scale, prompting the user for weight measuring or a smart speaker to initiate a conversation for collecting self-report exhaustion data, respectively. The sensor communication used the MQTT (MQ Telemetry Transport) protocol. This inter-sensor communication capability is the first time applied in similar systems. Lastly, participants were given opportunities to freely perform activities in HomeLab based on their paces. The freedom allowed the system to be tested in different scenarios closest to real life. FT also has some limitations. The testing was only done with young, healthy participants. It would have been more informative to have a comparison group of older participants tested in HomeLab. However, the recruitment was under COVID-19 restrictions to keep older adults safe. Moreover, as the objective of this study was to validate the sensor’s binary measurements but not the frailty assessment, the young, healthy participants should be sufficient. We took several measures to address the limitation from experiment protocol and system design perspectives. The study participants were asked to mimic common mobility characteristics of people living with frailty. These characteristics include slow walking speed, stair climbing, and longer sedentary behavior. Additionally, the smart speaker was designed to be easy to use for older adults. It initiated the conversation to bring the user’s attention. Only single-word answers (e.g., yes or no) for each of the three questions were required. The speaker was also programmed to prompt users with the expected answer options (i.e., “yes or no”, “always, sometimes, rare”). If the user missed the first attempt, the question would be repeated once again to provide another answer opportunity. Therefore, we believe it is very unlikely there would be a significant difference between young and older adults in responding to the questions asked by the smart speaker. Another limitation is that the FT system can only work for single-person dwellings as no sensors in the current FT can distinguish different persons. Indeed, the Radio Frequency Identification technology can be used to provide a unique ID for identifying different people. Computer vision technology can also provide personal identity through face recognition. However, both technologies can bring compliance or privacy concerns, making them not ideal for an application with older adults in home settings. Moreover, as FT is a proof-of-concept system, the current energy management for each sensor is not ideal for extending the battery life. The improvement in battery life can be made by removing unused electronic components on the current micro-controllers or using more energy-efficient micro-controllers. Furthermore, mat and distance sensors can only use time but not event signals to control their deep sleep mode. Unnecessary power waste using time-based sleep mode can shorten battery life. A comparator circuit with relays and logic gates could be one way to improve to allow pin interrupt-based sleep control. Future work includes: Test the system in HomeLab with non-frail and frail participants to validate the effectiveness of the frailty assessment. The test would also allow more data collection for training a machine learning model for classifying non-frail and frail older adults. Move the system from the simulated home to an actual home of an older adult who lives alone. While older adults continue to live their own lives, the system will continuously run for a week to collect data. The data will be compared with the older adult’s frailty status measured by a reference clinical frailty scale. Develop sensors to measure new frailty criteria or phenotypes in different domains and identify other persons living in the same household. Compare sensors in FT with wearable sensors to validate the effectiveness of measuring certain frailty signs such as physical activity using ambient sensors. Consult with clinicians to investigate how the data provided by FT would be made palatable and useful for them. 5. Conclusions This study presented the design, development, and validation of a sensor-based toolkit for assessing frailty in home settings. The toolkit’s design focused on ambient sensing of behavioral and physical signs of frailty using different ambient sensors, a smart speaker, and a smart weight scale. The choice of heterogeneous sensors, a diverse set of frailty criteria, and the involvement of older adults’ perspectives in the design made this work unique from previous studies that mostly focused on wearable sensors and a single dimension of frailty. The prototype of the toolkit was deployed and tested in a simulated home lab. Statistical analysis of sensor data showed excellent concurrent validity for the ambient sensors and the smart speaker. The smart weight scale strongly correlated with its gold-standard measurement, but more validation is needed to confirm its concurrent validity. Overall, FT is reliable for monitoring physical and behavioral signs of frailty in home settings. The next step is to test the toolkit with older adults living with and without frailty to validate the system’s clinical effectiveness. Machine learning techniques will be used with the sensor data to build models and estimate classification performance for frailty. Acknowledgments The authors would like to extend our sincere thanks to all study participants, for their time and contributions. We are also grateful to staff at the KITE Machine Shop at KITE Research, Toronto Rehabilitation Institute, for their help in machining sensor enclosures. Author Contributions Conceptualization, C.B. and A.M.; methodology, C.B., B.Y. and A.M.; software, C.B.; validation, C.B. and B.Y.; formal analysis, C.B. and B.Y.; investigation, C.B. and B.Y.; resources, A.M.; data curation, C.B. and B.Y.; writing—original draft preparation, C.B.; writing—review and editing, B.Y. and A.M.; visualization, C.B. and B.Y.; supervision, A.M.; project administration, C.B. and B.Y.; funding acquisition, A.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of University Health Network (protocol code 20-5806 and date of approval 26 January 2021). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the subjects to publish this paper. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality protocol. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 The cycle of frailty, adapted with permission from Ref. [29]. Copyright 2022 Elsevier. Figure 2 Sample smart speaker conversation. Figure 3 Sensor setup layout in HomeLab. Figure 4 The schematized protocol for the experimentation. Figure 5 The Bland–Altman plot of agreement between mat sensor and video recording. Figure 6 The Bland–Altman plot of agreement between distance sensor and video recording. Figure 7 Scatterplot of the weight measured by traditional mechanical weight scale against smart digital weight scale. sensors-22-03532-t001_Table 1 Table 1 Sensors’ hardware components, corresponding frailty criteria. Sensor Frailty Criteria Mat sensor Strength through sedentary behavior Distance sensor Strength through stair climbing performance (ADL) Smart speaker Self-report exhaustion Motion sensor Physical activity, life-space mobility (indoor) Door sensor Life space mobility (outdoor) Smart weight scale Weight sensors-22-03532-t002_Table 2 Table 2 Experiment Protocol for Testing the Sensors in FT. Run Run #1 Run #2 Run #3 Run Type Guided, normal pace Self-paced, normal Self-paced, slow (mimicking frail older adults) Activity Type Activities Physical activity Go to a room (e.g., living room) in HomeLab and do whatever activities in the room for 2 min. Sedentary behavior Sit on a chair that has a mat sensor. Weight measuring Measure weight using the smart weight scale. Stair climbing Climb a flight of stairs. Self-report exhaustion Have a conversation with the smart speaker. Life space Enter or exit HomeLab through the main entrance door. sensors-22-03532-t003_Table 3 Table 3 Frequency and percentage of successfully detecting door entry/exit event by the door sensor. Frequency Percentage Detected 35 87.5 Undetected 5 12.5 Total 40 100 sensors-22-03532-t004_Table 4 Table 4 Frequency and percentage of successfully detecting stair-climbing events by the distance sensors. Frequency Percentage Detected 38 50 Undetected 38 50 Total 76 100 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. United Nations, Department of Economic and Social Affairs, P.D World Population Prospects 2019: Highlights (ST/ESA/SER.A/423) 2019 Available online: https://population.un.org/wpp/Publications/Files/WPP2019_Highlights.pdf (accessed on 26 April 2022) 2. Polanczyk C.A. Marcantonio E. Goldman L. Rohde L.E.P. Orav J. Mangione C.M. Lee T.H. Impact of Age on Perioperative Complications and Length of Stay in Patients Undergoing Noncardiac Surgery Ann. Intern. Med. 2001 134 637 10.7326/0003-4819-134-8-200104170-00008 11304103 3. Davenport D.L. Bowe E.A. Henderson W.G. Khuri S.F. Mentzer R.M. National Surgical Quality Improvement Program (NSQIP) Risk Factors Can Be Used to Validate American Society of Anesthesiologists Physical Status Classification (ASA PS) Levels Ann. Surg. 2006 243 636 644 10.1097/01.sla.0000216508.95556.cc 16632998 4. Makary M.A. Segev D.L. Pronovost P.J. Syin D. Bandeen-Roche K. Patel P. Takenaga R. Devgan L. Holzmueller C.G. Tian J. Frailty as a Predictor of Surgical Outcomes in Older Patients J. Am. Coll. Surg. 2010 210 901 908 10.1016/j.jamcollsurg.2010.01.028 20510798 5. Rockwood K. Andrew M. Mitnitski A. A Comparison of Two Approaches to Measuring Frailty in Elderly People J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2007 62 738 743 10.1093/gerona/62.7.738 17634321 6. Fried L.P. Tangen C.M. Walston J. Newman A.B. Hirsch C. Gottdiener J. Seeman T. Tracy R. Kop W.J. Burke G. Frailty in Older Adults: Evidence for a Phenotype J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2001 56 M146 M157 10.1093/gerona/56.3.M146 11253156 7. Hoogendijk E.O. Afilalo J. Ensrud K.E. Kowal P. Onder G. Fried L.P. Frailty: Implications for Clinical Practice and Public Health Lancet 2019 394 1365 1375 10.1016/S0140-6736(19)31786-6 31609228 8. Maresova P. Javanmardi E. Barakovic S. Barakovic Husic J. Tomsone S. Krejcar O. Kuca K. Consequences of Chronic Diseases and Other Limitations Associated with Old Age—A Scoping Review BMC Public Health 2019 19 1431 10.1186/s12889-019-7762-5 31675997 9. Mondor L. Maxwell C.J. Hogan D.B. Bronskill S.E. Campitelli M.A. Seitz D.P. Wodchis W.P. The Incremental Health Care Costs of Frailty Among Home Care Recipients With and Without Dementia in Ontario, Canada Med. Care 2019 57 512 520 10.1097/MLR.0000000000001139 31107398 10. Hajek A. Bock J.-O. Saum K.-U. Matschinger H. Brenner H. Holleczek B. Haefeli W.E. Heider D. König H.-H. Frailty and Healthcare Costs—Longitudinal Results of a Prospective Cohort Study Age Ageing 2018 47 233 241 10.1093/ageing/afx157 29036424 11. Gill T.M. Gahbauer E.A. Allore H.G. Han L. Transitions Between Frailty States Among Community-Living Older Persons Arch. Intern. Med. 2006 166 418 10.1001/archinte.166.4.418 16505261 12. Fallah N. Mitnitski A. Searle S.D. Gahbauer E.A. Gill T.M. Rockwood K. Transitions in Frailty Status in Older Adults in Relation to Mobility: A Multistate Modeling Approach Employing a Deficit Count J. Am. Geriatr. Soc. 2011 59 524 529 10.1111/j.1532-5415.2011.03300.x 21391943 13. Xue Q.L. The Frailty Syndrome: Definition and Natural History Clin. Geriatr. Med. 2011 27 1 15 10.1016/j.cger.2010.08.009 21093718 14. Toosizadeh N. Mohler J. Najafi B. Assessing Upper Extremity Motion: An Innovative Method to Identify Frailty J. Am. Geriatr. Soc. 2015 63 1181 1186 10.1111/jgs.13451 26096391 15. Soaz C. Diepold K. Step Detection and Parameterization for Diagnosis and Monitoring of Functional Decline Using a Single Waist-Worn Accelerometer IEEE Trans. Biomed. Eng. 2015 63 933 942 10.1109/TBME.2015.2480296 26394415 16. Schwenk M. Mohler J. Wendel C. D’’Huyvetter K. Fain M. Taylor-Piliae R. Najafi B. Wearable Sensor-Based in-Home Assessment of Gait, Balance, and Physical Activity for Discrimination of Frailty Status: Baseline Results of the Arizona Frailty Cohort Study Gerontology 2015 61 258 267 10.1159/000369095 25547185 17. Greene B.R. Doheny E.P. O’Halloran A. Kenny R.A. Frailty Status Can Be Accurately Assessed Using Inertial Sensors and the TUG Test Age Ageing 2014 43 406 411 10.1093/ageing/aft176 24212918 18. Gianaria E. Grangetto M. Roppolo M. Mulasso A. Rabaglietti E. Kinect-Based Gait Analysis for Automatic Frailty Syndrome Assessment Proceedings of the 2016 IEEE International Conference on Image Processing (ICIP) Phoenix, AZ, USA 25–28 September 2016 1314 1318 10.1109/ICIP.2016.7532571 19. Jaber R. Chkeir A. Hewson D.J. Duchene J. A New Device to Assess Gait Velocity at Home IFMBE Proc. 2014 41 670 673 10.1007/978-3-319-00846-2 20. Ferre X. Villalba-Mora E. Caballero-Mora M.-A. Sanchez A. Aguilera W. Garcia-Grossocordon N. Nuñez-Jimenez L. Rodríguez-Mañas L. Liu Q. del Pozo-Guerrero F. Gait Speed Measurement for Elderly Patients with Risk of Frailty Mob. Inf. Syst. 2017 2017 1310345 10.1155/2017/1310345 21. Chang Y.C. Lin C.C. Lin P.H. Chen C.C. Lee R.G. Huang J.S. Tsai T.H. EFurniture for Home-Based Frailty Detection Using Artificial Neural Networks and Wireless Sensors Med. Eng. Phys. 2013 35 263 268 10.1016/j.medengphy.2011.09.010 21981806 22. del Pozo-Cruz B. Mañas A. Martín-García M. Marín-Puyalto J. García-García F.J. Rodriguez-Mañas L. Guadalupe-Grau A. Ara I. Frailty Is Associated with Objectively Assessed Sedentary Behaviour Patterns in Older Adults: Evidence from the Toledo Study for Healthy Aging (TSHA) PLoS ONE 2017 12 e0183911 10.1371/journal.pone.0183911 28892505 23. Tuttle L.J. Bittel D.C. Bittel A.J. Sinacore D.R. Early-Onset Physical Frailty in Adults With Diabesity and Peripheral Neuropathy Can. J. Diabetes 2018 42 478 483 10.1016/j.jcjd.2017.12.001 29567079 24. Merry K.J. Macdonald E. MacPherson M. Aziz O. Park E. Ryan M. Sparrey C.J. Classifying Sitting, Standing, and Walking Using Plantar Force Data Med. Biol. Eng. Comput. 2021 59 257 270 10.1007/s11517-020-02297-4 33420617 25. Zijlstra W. Giannouli E. Mobility in Community-Dwelling Older Adults; What Are Its Determinants? BMC Geriatr. 2021 21 228 10.1186/s12877-021-02174-1 33827438 26. Ganea R. Paraschiv-Ionescu A. Büla C. Rochat S. Aminian K. Multi-Parametric Evaluation of Sit-to-Stand and Stand-to-Sit Transitions in Elderly People Med. Eng. Phys. 2011 33 1086 1093 10.1016/j.medengphy.2011.04.015 21601505 27. Millor N. Lecumberri P. Gómez M. Martínez-Ramírez A. Izquierdo M. An Evaluation of the 30-s Chair Stand Test in Older Adults: Frailty Detection Based on Kinematic Parameters from a Single Inertial Unit J. NeuroEngineering Rehabil. 2013 10 86 10.1186/1743-0003-10-86 28. Hellmers S. Kromke T. Dasenbrock L. Heinks A. Bauer J.M. Hein A. Fudickar S. Stair Climb Power Measurements via Inertial Measurement Units—Towards an Unsupervised Assessment of Strength in Domestic Environments Proceedings of the 11th International Conference on Health Informatics (HEALTHINF) Madeira, Portugal 19–21 January 2018 Volume 5 39 47 29. Allin S. Mihailidis A. Low-Cost, Automated Assessment of Sit-To-Stand Movement in “Natural” Environments Proceedings of the IFMBE Springer Berlin/Heidelberg, Germany 2009 30. Bérubé C. Schachner T. Keller R. Fleisch E. v Wangenheim F. Barata F. Kowatsch T. Voice-Based Conversational Agents for the Prevention and Management of Chronic and Mental Health Conditions: Systematic Literature Review J. Med. Internet Res. 2021 23 e25933 10.2196/25933 33658174 31. Piau A. Charlon Y. Campo E. Vellas B. Nourhashemi F. A Smart Insole to Promote Healthy Aging for Frail Elderly Individuals: Specifications, Design, and Preliminary Results JMIR Rehabil. Assist. Technol. 2015 2 e5 10.2196/rehab.4084 28582238 32. Dasios A. Gavalas D. Pantziou G. Konstantopoulos C. Hands-On Experiences in Deploying Cost-Effective Ambient-Assisted Living Systems Sensors 2015 15 14487 14512 10.3390/s150614487 26094631 33. Griebel L. Prokosch H.-U. Köpcke F. Toddenroth D. Christoph J. Leb I. Engel I. Sedlmayr M. A Scoping Review of Cloud Computing in Healthcare BMC Med. Inform. Decis. Mak. 2015 15 17 10.1186/s12911-015-0145-7 25888747 34. Xue Q.L. Bandeen-Roche K. Varadhan R. Zhou J. Fried L.P. Initial Manifestations of Frailty Criteria and the Development of Frailty Phenotype in the Women’s Health and Aging Study II J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2008 63 984 990 10.1093/gerona/63.9.984 18840805 35. Piau A. Mattek N. Crissey R. Beattie Z. Dodge H. Kaye J. When Will My Patient Fall? Sensor-Based In-Home Walking Speed Identifies Future Falls in Older Adults J. Gerontol. Ser. A 2020 75 968 973 10.1093/gerona/glz128 31095283 36. Stone E. Skubic M. Rantz M. Abbott C. Miller S. Average In-Home Gait Speed: Investigation of a New Metric for Mobility and Fall Risk Assessment of Elders Gait Posture 2015 41 57 62 10.1016/j.gaitpost.2014.08.019 25245308 37. Freire Junior R.C. Porto J.M. Rodrigues N.C. Brunelli R.D.M. Braga L.F.P. Abreu D.C.C. Spatial and Temporal Gait Characteristics in Pre-Frail Community-Dwelling Older Adults Geriatr. Gerontol. Int. 2016 16 1102 1108 10.1111/ggi.12594 26338502 38. Klebbe R. Steinert A. Müller-Werdan U. Wearables for Older Adults: Requirements, Design, and User Experience Perspectives on Wearable Enhanced Learning (WELL) Springer International Publishing Cham, Switzerland 2019 313 332 39. Schreier G. Eckmann H. Hayn D. Kreiner K. Kastner P. Lovell N. Web versus App—Compliance of Patients in a Telehealth Diabetes Management Programme Using Two Different Technologies J. Telemed. Telecare 2012 18 476 480 10.1258/jtt.2012.gth112 23209270 40. Cruz-Sandoval D. Favela J. Lopez-Nava I.H. Morales A. Adoption of Wearable Devices by Persons with Dementia: Lessons from a Non-Pharmacological Intervention Enabled by a Social Robot IoT in Healthcare and Ambient Assisted Living Springer Singapore 2021 145 163 41. Li L. Peng W. Kamp K. Bowen M. Cotten S.R. Rikard R.V. Kononova A. Poster: Understanding Long-Term Adoption of Wearable Activity Trackers among Older Adults Proceedings of the 2017 Workshop on Wearable Systems and Applications Niagara Falls, NY, USA 19 June 2017 33 34 42. Jaber R. Chkeir A. Hewson D. Duchene J. ARPEGE: Assessment of Frailty at Home Proceedings of the 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services Lisbon, Portugal 9–12 October 2013 Healthcom Sullivan, IL, USA 434 438 10.1109/HealthCom.2013.6720715 43. Bautmans I. van Puyvelde K. Mets T. Sarcopenia and Functional Decline: Pathophysiology, Prevention and Therapy Acta Clin. Belg. 2009 64 303 316 10.1179/acb.2009.048 19810417 44. Santilli V. Bernetti A. Mangone M. Paoloni M. Clinical Definition of Sarcopenia Clin. Cases Miner. Bone Metab. 2014 11 177 180 10.11138/ccmbm/2014.11.3.177 25568649 45. Mohlberg W. Sieber C. Sarcopenia and Frailty in Geriatric Patients: Implications for Training and Prevention Z. Für Gerontol. Und Geriatr. 2004 37 2 8 10.1007/s00391-004-0203-8 46. BELL K.E. von Allmen M.T. Devries M.C. Phillips S.M. Muscle Disuse as a Pivotal Problem in Sarcopenia-related Muscle Loss and Dysfunction J. Frailty Aging 2016 1 9 10.14283/jfa.2016.78 47. Charansonney O.L. Després J.-P. Disease Prevention—Should We Target Obesity or Sedentary Lifestyle? Nat. Rev. Cardiol. 2010 7 468 472 10.1038/nrcardio.2010.68 20498671 48. Nightingale E.J. Pourkazemi F. Hiller C.E. Systematic Review of Timed Stair Tests J. Rehabil. Res. Dev. 2014 51 335 350 10.1682/JRRD.2013.06.0148 25019658 49. Orme J.G. Reis J. Herz E.J. Factorial and Discriminant Validity of the Center for Epidemiological Studies Depression (CES-D) Scale J. Clin. Psychol. 1986 42 28 33 10.1002/1097-4679(198601)42:1<28::AID-JCLP2270420104>3.0.CO;2-T 3950011 50. Fuller D. Colwell E. Low J. Orychock K. Tobin M.A. Simango B. Buote R. van Heerden D. Luan H. Cullen K. Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review JMIR Mhealth Uhealth 2020 8 e18694 10.2196/18694 32897239 51. Myers A. Johnston N. Rathod V. Korattikara A. Gorban A. Silberman N. Guadarrama S. Papandreou G. Huang J. Murphy K. Im2Calories: Towards an Automated Mobile Vision Food Diary Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV) Santiago, Chile 7–13 December 2015 1233 1241 52. Tegou T. Kalamaras I. Tsipouras M. Giannakeas N. Votis K. A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults Sensors 2019 19 452 10.3390/s19030452 30678280 53. Doyle J. Bailey C. Ni Scanaill C. van den Berg F. Lessons Learned in Deploying Independent Living Technologies to Older Adults’ Homes Univers. Access Inf. Soc. 2013 13 191 204 10.1007/s10209-013-0308-1 54. Bian C. Ye B. Hoonakker A. Mihailidis A. Attitudes and Perspectives of Older Adults on Technologies for Assessing Frailty in Home Settings: A Focus Group Study BMC Geriatr. 2021 21 298 10.1186/s12877-021-02252-4 33964887 55. Keogh A. Dorn J.F. Walsh L. Calvo F. Caulfield B. Comparing the Usability and Acceptability of Wearable Sensors Among Older Irish Adults in a Real-World Context: Observational Study JMIR Mhealth Uhealth 2020 8 e15704 10.2196/15704 32310149 56. Kovacshazy T. Fodor G. New Approach to Passive Infrared Motion Sensors Signal Processing for Ambient Assisted Living Applications Proceedings of the 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings Graz, Austria 13–16 May 2012 2521 2525 57. Galán-Mercant A. Cuesta-Vargas A.I. Clinical Frailty Syndrome Assessment Using Inertial Sensors Embedded in Smartphones Physiol. Meas. 2015 36 1929 1942 10.1088/0967-3334/36/9/1929 26245213 58. Fontecha J. Navarro F.J. Hervás R. Bravo J. Elderly Frailty Detection by Using Accelerometer-Enabled Smartphones and Clinical Information Records Pers. Ubiquitous Comput. 2013 17 1073 1083 10.1007/s00779-012-0559-5 59. Landis J.R. Koch G.G. The Measurement of Observer Agreement for Categorical Data Biometrics 1977 33 159 10.2307/2529310 843571 60. Krakowiak P. Walker C.K. Tancredi D.J. Hertz-Picciotto I. Maternal Recall Versus Medical Records of Metabolic Conditions from the Prenatal Period: A Validation Study Matern. Child Health J. 2015 19 1925 1935 10.1007/s10995-015-1723-0 25656730 61. Pursey K. Burrows T.L. Stanwell P. Collins C.E. How Accurate Is Web-Based Self-Reported Height, Weight, and Body Mass Index in Young Adults? J. Med. Internet Res. 2014 16 e4 10.2196/jmir.2909 24398335 62. Muscedere J. Andrew M.K. Bagshaw S.M. Estabrooks C. Hogan D. Holroyd-Leduc J. Howlett S. Lahey W. Maxwell C. McNally M. Screening for Frailty in Canada’s Health Care System: A Time for Action Can. J. Aging/La Rev. Can. Du Vieil. 2016 35 281 297 10.1017/S0714980816000301 27211065 63. Bian C. Ye B. Chu C.H. McGilton K.S. Mihailidis A. Technology for Home-Based Frailty Assessment and Prediction: A Systematic Review Gerontechnology 2020 19 3 10.4017/gt.2020.19.003.06 64. Chkeir A. Novella J.L. Dramé M. Bera D. Collart M. Duchêne J. In-Home Physical Frailty Monitoring: Relevance with Respect to Clinical Tests BMC Geriatr. 2019 19 34 10.1186/s12877-019-1048-8 30717696

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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092188 cancers-14-02188 Article Biomarkers Associated with Lymph Nodal Metastasis in Endometrioid Endometrial Carcinoma Mairé Mathilde 1* Bourdon Aurélien 2 Soubeyran Isabelle 3 https://orcid.org/0000-0001-6657-2341 Lucchesi Carlo 2 Guyon Frédéric 1 Babin Guillaume 1 Floquet Anne 4 Petit Adeline 5 https://orcid.org/0000-0002-9752-5561 Baud Jessica 67 Velasco Valérie 3 Querleu Denis 89† Croce Sabrina 37† De Iaco Pierandrea Academic Editor Perrone Anna Myriam Academic Editor 1 Department of Surgery, Institut Bergonie, 33076 Bordeaux, France; f.guyon@bordeaux.unicancer.fr (F.G.); g.babin@bordeaux.unicancer.fr (G.B.) 2 Department of Bioinformatics, Institut Bergonie, 33076 Bordeaux, France; a.bourdon@bordeaux.unicancer.fr (A.B.); carlo.lucchesi.lc@gmail.com (C.L.) 3 Department of Biopathology, Institut Bergonie, 33076 Bordeaux, France; i.soubeyran@bordeaux.unicancer.fr (I.S.); v.velasco@bordeaux.unicancer.fr (V.V.); s.croce@bordeaux.unicancer.fr (S.C.) 4 Department of Oncology, Institut Bergonie, 33076 Bordeaux, France; a.floquet@bordeaux.unicancer.fr 5 Department of Radiotherapy, Institut Bergonie, 33076 Bordeaux, France; a.petit@bordeaux.unicancer.fr 6 Department of Life and Health Sciences, Université de Bordeaux, 146 rue Léo Saignat, 33000 Bordeaux, France; j.massiere@bordeaux.unicancer.fr 7 INSERM U1218, Biopathology Department, Institut Bergonie, 33076 Bordeaux, France 8 Department of Gynecologic Oncology, Agostino Gemelli University Hospital, 00168 Rome, Italy; denis.querleu@esgo.org 9 Gynecology Department, Hôpital de Hautepierre, 67200 Strasbourg, France * Correspondence: m.maire@bordeaux.unicancer.fr † These authors contributed equally to this work. 27 4 2022 5 2022 14 9 218817 3 2022 23 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary In endometrial cancer, lymph node invasion assessed through surgical lymphadenectomy or sentinel lymph node biopsy is a determinant factor for the prognosis and planification of adjuvant treatment. Those surgical procedures are associated with short- and long-term complications. Recent advances in molecular characterization of endometrial cancer have provided important insights into the biological nature of tumors but have not improved the pre-operative prediction of LND. This study is a description of the transcriptomic landscape associated with lymph node metastases in endometroid endometrial carcinomas. A 54-genes expression signature was generated at analysis of the primary tumor. Differential gene expression was found between patients with and without lymph node metastasis, with an 87% accuracy. Our findings provide a basis for the development of a gene expression-based signature that can be used to pre-operatively select patients for whom surgical assessment of lymph node status is of little value, and, consequently, an unfavorable risk–benefit balance. Abstract Introduction. Lymph node metastasis is determinant in the prognosis and treatment of endometrioid endometrial cancer (EEC) but the risk–benefit balance of surgical lymph node staging remains controversial. Objective. Describe the pathways associated with lymph node metastases in EEC detected by whole RNA sequencing. Methods. RNA-sequencing was performed on a retrospective series of 30 non-metastatic EEC. N+ and N− patients were matched for tumoral size, tumoral grade and myometrial invasion. Results. Twenty-eight EECs were analyzable (16 N+ and 12 N−). Bioinformatics Unsupervised analysis revealed three patterns of expression, enriched in N+, mix of N+/N− and enriched in N−, respectively. The cluster with only N+ patient overexpressed extra cellular matrix, epithelial to mesenchymal and smooth muscle contraction pathways with respect to the N− profile. Differential expression analysis between N+ and N− was used to generate a 54-genes signature with an 87% accuracy. Conclusion. RNA-expression analysis provides a basis to develop a gene expression-based signature that could pre-operatively predict lymph node invasion. endometrial cancer lymph node metastasis RNA sequencing prediction model INSTITUT BERGONIEThis research was funded by INSTITUT BERGONIE. ==== Body pmc1. Introduction Endometrial cancer is the most common gynecological tumor in developed countries, and was the fourth most frequently diagnosed neoplasm in European women in 2018 (122,000 cases; 6.6%) [1]. Although in the majority of the cases, the cancer is diagnosed at an early stage and shows a favorable prognosis, 25% of the patients present with stage III or IV disease and impaired survival [2]. The mainstay of management of endometrial cancer is hysterectomy and bilateral salpingo-oophorectomy with or without lymph node staging depending on the pre-operative risk classification [3]. According to recently published European guidelines, the type of lymph node dissection (sentinel lymph node biopsy, pelvic lymphadenectomy and para-aortic lymphadenectomy) depends on the pre-operative risk assessment. No evidence of benefit in terms of survival has yet been associated with systematic lymphadenectomy [4] but knowledge of pathological lymph node status is relevant to plan adjuvant therapy. Morbidities associated with lymph node dissection include perioperative systemic morbidity and lymphoedema [5]. Although morbidity appears to be reduced with sentinel lymph node biopsy, the risk of surgical complications is still present [6]. At present, before surgery, the risk of lymphatic spread is indirectly assessed on the basis of the combination of tumor invasion depth, tumor grade, tumor size and histotype. However, preoperative workup has limitations, including interobserver variation in the assessment of histotype and histological grade, lack of accuracy of imaging techniques regarding myometrial invasion and lymph nodal metastasis [7]. Lymphovascular invasion, a strong independent pathological feature associated with lymph nodal disease, is not available before a definitive pathological examination of the hysterectomy specimen [8]. Recent advances in the molecular characterization of endometrial cancer [9] have provided important insight into the biological nature of tumors. Different diagnostic algorithms have been proposed using three immunohistochemical markers (p53, MSH6 and PMS2) and one molecular test (mutation of the exonuclease domain of POLE) to identify prognostic groups analogous to the TCGA molecular-based classification [10]. Thus far, molecular subgroups have been demonstrated to improve the prediction of survival outcomes but were not identified as independent predictors of stage IIIC–IV disease [11]. Hence, additional tools including highly specific and sensitive molecular biomarkers are needed to more accurately select the women for whom complete surgical staging should be performed to adapt adjuvant therapy. Whole RNA-sequencing is an essential part of high throughput sequencing, as it provides biological information of gene expression regulation. In this study, we used whole RNA sequencing to describe the transcriptomic landscape associated with lymph node metastases in endometroid endometrial carcinomas. This study is a pilot study to investigate the genes of interest in order to develop a gene signature predictive of lymph node involvement. 2. Materials and Methods 2.1. Patients Selection We conducted a monocentric case-control study at the Institut Bergonie, Comprehensive Cancer Center, Bordeaux, France. Patients’ inclusion criteria included (1) Clinical stage I–II endometrial cancer treated between January 2010 and February 2017; (2) initial surgery performed at the Institut Bergonie, pathological tissue available and confirmed diagnosis of endometrioid endometrial carcinoma; (3) surgical staging performed with total hysterectomy, bilateral salpingo-oophorectomy and lymph node evaluation with either bilateral pelvic lymph node dissection with or without para-aortic lymphadenectomy or sentinel-node biopsy. Exclusion criteria were: non-endometrioid carcinoma, metastatic cancer (FIGO stage IV). Information regarding the patient’s characteristics, pre-operative tumor characteristics, type of surgery, definitive tumoral staging, adjuvant therapy and outcomes was collected retrospectively from medical records and entered into a REDCAP database after anonymization. 2.2. Histopathological Assessment and Molecular Features All slides of selected patients were reviewed by a gynecopathologist (SC) to confirm the histological subtype, the tumor grade, the presence of lymphovascular invasion, stromal reaction, MELF pattern and the depth of invasion (according to the fifth edition of Female Genital Tumors [12]). Substantial lymphovascular invasion (LVSI) was defined by the presence of tumor cells in five or more lymphovascular spaces [3]. For each patient, the tumoral area was selected for RNA-extraction by macro-dissection. Immunohistochemistry (IHC) was performed on paraffin-embedded (FFPE) tissue samples using the following antibodies: MLH1, MSH2, PMS2, MSH6 (clones M1, G219-1129, A16-4,SP93; Roche Diagnostics Gmbh, D-68305 Mannheim, Germany) and p53 (clone DO7, Dako, Glostrup, Denmark) to assess the MMR protein status and p53 expression [13,14]. MMR protein status was considered deficient (MMR-D) when a complete loss of nuclear expression was observed in carcinoma cells of one or more MMR protein (MLH1, MSH2, MSH6, PMS2). A weak/patchy/cytoplasmic/punctate or dot-like nuclear pattern was considered as abnormal MMR expression [15]. Particular attention was reserved for the subclonal/heterogeneous pattern of MMR staining abnormality. Aberrant p53 staining (p53abn) was defined as: (1) in case of strong and diffuse nuclear staining (p53 strong); (2) or completely negative staining (P53 absent) in the presence of internal positive control; (3) cytoplasmic and nuclear pattern in carcinoma cells [13]. As the positive internal control the normal myometrium or normal endometrium was used. As external control a case of serous carcinoma with TP53 mutation with overexpression and a case of serous carcinoma with a TP53 mutation with p53 absent and a normal tonsilla were used. Because the POLE mutation screening was not available in routine practice at the time of the diagnosis, we screened for 11 known POLE hotspots mutation by RNA-sequencing (on cDNA) [16]. Patients were classified into two groups according to lymph node involvement. In order to avoid any bias for the known factors associated with lymph node metastasis and available before surgery, each patient with confirmed lymph node metastasis was matched to a control patient without lymph node metastases with similar definitive tumoral size (0–20 mm, 20–35 mm and over 35 mm), tumoral grade and myometrial invasion (less than 50% or over 50%). Definitive tumoral size was available from the initial pathological record, and the tumoral grade and myometrial invasion were issued for pathological review. Because it is usually non-available before surgery, lymphovascular invasion was not used in the matching protocol. 2.3. Matching and Initial Statistical Analysis All initial statistical analysis was performed on SAS Pro and R version 3.6.1. (Packages epiDisplay, prettyR, epiR, gtsummary, dplyr, survival). Patients were matched 1:1 between N+ and N− according to definitive tumoral size (0–20 mm, 20–35 mm and over 35 mm), tumoral grade (FIGO 1, 2 or 3) and myometrial invasion (less than 50% or over 50%). For each case, only two to three control cases were available. Three samples with lymph node metastases had no matching pair found in the control group but were conserved for RNA extraction. Quantitative variables are presented as mean with standard deviation and were compared using t-test. Qualitative variables are presented as percentages and compared using Chi-2 or Fisher’s test. 2.4. RNA Sequencing Formalin-fixed and paraffin-embedded (FFPE) tissue samples of primary tumor, selected by the pathologist, were used for whole RNA-sequencing. All RNA extraction, sequencing and data analysis were performed at the Institut Bergonie, Bordeaux. Extraction of RNA was realized with the Maxwell® RSC RNA FFPE Kit (Promega). Library preparations were performed according to the True Seq RNA Exome Library Prep Guide, Illumina, and then sequenced (2 × 75 bp, paired-end) in a Nextseq 500 sequencer, Illumina. All analysis was performed at the Institut Bergonie. 2.5. NGS RNAseq Sequence Alignment and Quality Control Pipeline Raw RNAseq sequences were controlled for quality using a set of published tools to produce curated reads. Firstly, reads with low quality bases at 5′ and 3′ were trimmed using the Sickle package (Phred cut off 20, max trim size 30 nc) [17]. The SeqPrep package was used to remove sequencing adaptors from raw reads [18]. This package also detected an important proportion of RNA fragments whose R1 and R2 paired-end reads were overlapping and merged them into single-end reads. To keep exploiting those fragments, a home-made python script was developed that split those merged reads into new non-overlapping R1 and R2 paired-end reads. Curated reads were aligned using TOPHAT2 (based on BOWTIE2) on both the UCSC hg19 reference genome and transcriptome [19]. Finally, we applied a post-alignment quality control of aligned reads by removing reads with mapping scores lower than 20 using Samtools [20]. PCR duplicate reads were identified and removed using Picard MarkDuplicates (https://broadinstitute.github.io, accessed on 24 January 2017). Read counts were enumerated using HTSeq [21]. In order to avoid normalization bias between samples, due to an imbalanced number of genes with zero aligned sequences per sample, samples were included in analysis if and only if their total count of aligned sequences was greater than 5 M PE and the number of genes with zero counts in the sample was lower than 3500 (Figure S1). 2.6. Differential Analysis Transcript count data were normalized according the VOOM method, which transforms raw count values to log2-counts per million (logCPM), estimates the mean-variance relationship and uses this relationship to compute appropriate observational-level weights [22]. The RNAseq differential gene expression between groups of samples was performed using the statistical t-test from the R package LIMMA, which calculates fold changes and nominal p-values related to each gene starting from raw expression values and the normalization weights produced by VOOM [23]. The set of nominal p-values from each test were adjusted according to the Benjamini–Hochberg adjustment [24]. We defined the significantly up- or downregulated transcripts using an FDR threshold of 0.05. The fold-change used to further filter the differential gene expression was set to a minimum value of 2. To obtain discriminant signature of gene expression between two groups of samples we used the shrunken centroids method (pamr R package) from Tibshirani and et al. [25] that provides an estimate of the misclassification error of the signature by splitting the data into training ad validation sets using cross-validation. To challenge the performance measured by the pamr signature, a homemade performance visualization method was used (Centroid Validator). Briefly, this method takes in as input the expression data set of the samples used during training, the expression data set of the validation samples, the list of genes that represent the signature and the labels for each training and validation sample indicating their membership group (N+ and N− in our study). Using the training data set, the method calculates the centroids of each group, represented by the mean expression of each gene in the signature for each group of samples. A score is calculated to predict the classification of a validation sample to a specific group. The score of a given validation sample is calculated by the distance, in terms of the Mean Square Error (MSE), between the value of each gene in the validation sample and the value of the centroid for the same gene in each group in the training data. The statistical significance of the score is assessed by randomization of the MSE. Finally, a confusion matrix between the predicted and expected classification of the validation samples is created to provide an additional measure of performance of the gene expression signature. 2.7. Gene Set-Enrichment Analysis MSigDB [26] was used to identify pathways or gene ontologies in which the genes of an identified group were enriched. Oncogene and Tumor Suppressor Gene status (approximately 800 known genes) was assigned according to the annotation in the Cancer Gene Panel [27,28]. 2.8. Mutations Analysis Production of raw genetic alteration files (.vcf/.bcf) was performed via Samtools/Bcftools with a quality cut-off per base of Phred 20. Calculation of the number of aligned reads covering each exon was performed via HtSeq. Quality reports of raw reads were built with FastQC (FastQC—https://www.bioinformatics.babraham.ac.uk/projects/fastqc/, access on 27 January 2017). Annotation of SNV and InDel genetic variants was reported by Annovar [29]. 2.9. Unsupervised Clustering Unsupervised clustering analysis of RNA-Sequencing expression data was performed using agglomerative hierarchical clustering with distance criteria (1-Pearson_Correlation) and linkage criteria equal to average via the function hclust available in R [30]. We performed this procedure iteratively on a subset of genes with increasing variability based on their standard deviation. The choice of the number of genes to use for freezing the clustering configuration was determined empirically, as follows. For each clustering performed at a given standard deviation cut-off, we measured the anti-correlation between the two groups placed at the highest level in the clustering hierarchy. We assumed that clustering with anti-correlations close to 0 were associated with grouping by chance between samples. We selected the SD cutoff for which sample anti-correlation was at the lowest negative level whilst the number of genes left was no less than 3000. This procedure was meant to remove genes with weak variability that could bias clustering via spurious random correlations and, at the same time, assuring that sample grouping was determined by the largest as possible number of genes. To assess the robustness of clustering results at a given SD threshold, we performed consensus clustering via the package ConsensusClusteringPlus available in BioConductor [31]. Consensus was established after 10,000 iterations on the subset of samples obtained by leave-n-out of 40% of samples. 3. Results 3.1. Patients and Clinical Characteristics Of the 380 patients with non-metastatic endometrial cancer presented in our multidisciplinary tumor board between 2010 and 2017, 290 had endometrioid endometrial carcinoma (EEC). Thirty-five patients (12.1%) had lymph node metastasis (N+) and among them, 17 had surgery in our center. They were paired with a control group of thirty-nine lymph node negative patients (N−), who had their primary surgery within our center as well, including a lymph node dissection. Three samples with lymph node involvement could not be paired to a control but were included in the final population (Figure 1). Patients with (N+) and without (N−) lymph node metastases were not different for age at diagnosis, body mass index, menopausal status and smoking status (Table 1). Four patients (33.3%) in the N− group and 10 (62.5%) in the N+ group underwent pelvic and para-aortic lymphadenectomy, and seven (58.9%) patients underwent isolated pelvic lymphadenectomy in the N− group and three (18.8%) in the N+ group. The reasons for omitting paraaortic lymphadenectomy were comorbidity and morbid obesity. An average of 15 pelvic lymph nodes and 18 para-aortic lymph nodes were removed in the population, and laparoscopic surgery was the preferred technique. 3.2. Patients’ Histological and Molecular Classification Mean tumor size was 46.8 mm in the N− group and 50.1 mm in the N+ group. A total of 20 EEC patients (71.4% of the overall cohort) had high histological grade and 18 (64.3%) had more than 50% of myometrial invasion (Table 2 and Table S1). Angioinvasion was more frequent when lymph node metastases were present: nine patients (56.2%) in the N+ patients had substantial lymphovascular invasion versus only two patients (16.7%) in the N− group (p = 0.013). The MELF pattern was also more often described in the N+ group (62.5% versus 25.0% in the N− group) but this difference was non-significant (p = 0.07). Stromal invasion, peri nervous invasion and inflammatory infiltration were not different between the two groups. No pathogenic POLE mutation was found in our study population. Thirteen EEC patients were characterized by defective MMR and classified as hypermutated: four (33.3%) in the N− group and nine (56.2%) in the N+ group. TP53 pathogenic mutations were identified in three EEC, two of them had abnormal p53 staining pattern (two were absent and one overexpressed) and one a normal wild-type staining pattern. The three EEC with TP53 mutation were N+ patients. Molecular classification distribution between the N+ and N− patients was not statistically different (p = 0.06), hence it did not have a predictive value. We searched for pathogenic mutation of CTNNB1, a predictor of poor prognostic in endometrial cancer [32]. Pathogenic mutation of CTNNB1 was identified in five (41.7%) N− patients and two (12.5%) N+ patients and was not statistically different between the two groups. 3.3. RNA Extraction, Sequencing, Bioinformatics Quality Control RNA extraction was performed for 31 tumor samples (14 N− and 17 N+). After bioinformatics quality control, three samples were not interpretable because of lack of a sufficient gene coverage and were excluded from the analysis. 3.4. Differential Gene Expression (DGE) Analysis between N+/N− Samples In order to identify differences of expression between the two major clinical groups, we performed differential expression analysis between the 16 N+ and 12 N−. Eleven genes were significantly different between the two groups, of which WTIP, FIGN, PRX, AVR1A, LTBP3, ASPN, EFEMP1 and MGP were upregulated in N+ patients and LIN28B, C1orf64 which were upregulated in the N− patients. However, after applying a machine learning method, no gene was found to be discriminant between the two groups (See Material and Methods-Differential analysis). Hence, this first analysis was not conclusive. 3.5. Unsupervised Analysis In order to check if other molecular factors associated with gene expression regulation might be the cause of the limited results of the DGE analysis between the major clinical classes, we applied an unsupervised consensus and hierarchical clustering of RNA-sequencing data. This method allows the classification of samples only, based on gene expression data without considering the a priori N+/N− classification. This method identified three groups of patients with associated gene-clusters (Figure 2). Cluster A included 7 samples all with lymph node metastases, cluster B included 10 samples, 4 N− and 6 N+ and cluster C included 11 samples, 3 N+ and 8 N−. For the following analysis, cluster A is considered as N+ cluster, cluster C as N− and cluster B as mixed. Apart from the lymph node invasion, no other histopathological characteristic was found statistically different between the three clusters (Table S2). We then performed DGE analysis between the three groups, which identified 1491 genes between A and B (Figure S3), 1416 genes between A and C (Figure S2), 956 genes between B and C (Figure S4) and 1348 genes between A and B + C (Figure S5). These results show that, once the initial N+/N− cohort has been reorganized by regrouping samples which have mixed N+/N− characteristics, as the B group, then strong gene expression differences could be identified. 3.6. Pathway Analysis In order to identify the biological pathway characterizing the groups A, B and C we performed Gene Set Enrichment Analysis (GSEA) (17) (See Material and Methods). Cluster A (only N+ patients) was mainly enriched in genes from Extra Cellular Matrix (ECM), Epithelial to Mesenchymal (EMT) and Smooth Muscle Contraction (SMC) (Figure 3). In the EMT pathway, we found that MSX1 and LAMA1 genes were downregulated and SFR4, DCN, CXCL2, FAP genes were upregulated in the N− patients. In the ECM pathway, we identified that the MUC2 gene was downregulated, and COL4A3, SGCA, COL4A4 TNXB, MGP, EFEMP1 genes were upregulated in the N+ patients. In the Smooth Muscle Contraction pathway, MYH11, LMOD1, ACTG2, ACTA2 belonged to the set of genes upregulated in the N+ samples. L1CAM (L1 cell adhesion molecule), which has already been described as predictive of worse outcomes in endometrial carcinoma [33], was upregulated in cluster A (N+ patients) with a fold change of 7.8. Two pathways were upregulated in cluster C (enriched in N−): the Cell Proliferation and Beta Cells pathways. Cluster B (a mix of N+ and N− samples) broadly overexpressed all Immune Cell types (See Material and Methods) as well as the Cell Death pathway (Figure 3). 3.7. Potential Gene Signature Because the interest was in comparing groups only enriched in N+ and N−, DGE was performed between group A (N+) and C (N−). In cluster C, we compared the three N+ patients with the rest of the group (Table S3). The three N+ patients in cluster C were classified hypermutated according to TCGA molecular classification. Those three patients were different from the eight others in terms of MELF pattern, angioinvasion, myometrial invasion and TCGA molecular classification. To generate an accurate molecular signature and compare the N+ and N− homogeneous groups, we removed three N+ samples from group C to define the group C’ containing only N− samples. DGE analysis performed between A (N+) and C’ (N−) groups identified 1047 differentially expressed genes (Figure S6). Using a Machine Learning method (See Material and Methods), a gene expression signature of 54 genes was found (Table S4), which could discriminate the N+ and N− samples with a cross validated accuracy of 87%, a specificity of 86% and a sensitivity of 88% (Table S5) [25]. Three of the genes in the signature were those associated to the EMT, nine genes to the ECM and five genes to the SMC pathways. 4. Discussion Surgical assessment of lymph node involvement is an essential parameter to guide the therapeutic strategy in endometrial cancer. The sentinel lymph node (SLN) biopsy has emerged as an alternative to complete lymphadenectomy, with an overall detection rate over 80% and a specificity of 100% [34]. Although surgical complication rate appears to be reduced when SLN biopsy is performed compared to lymphadenectomy [35], they are not zero [36]. Lymph node dissection prolongs the duration of surgery, the risk of pre- and post-operative complications and may be difficult to complete in obese patients with prior surgeries or patients with major co-morbidities. We performed a genome-wide analysis in order to describe the molecular landscape associated with lymph node metastases. RNA-sequencing data were comprehensively analyzed to identify genes of interest for a potential molecular signature predictive of lymph node metastasis. Unsupervised analyses found three distinct clusters, one of them was significantly enriched in lymph node involvement. Comparison of those two specific groups allowed us to identify three overexpressed pathways in patients with lymph node metastases and a potential gene signature for lymph node involvement of 54 genes with an 87% accuracy. In the study’s population, 12% of EEC presented with lymph node metastases and the major clinical and histologic difference between the two groups was lymphovascular space invasion (LVSI). In 2017, a Cochrane database review by Frost et al. noted that lymph node metastases were found in approximately 10% of women who, before surgery, were thought to have cancer confined to the uterus [5]. Substantial LVSI is the strongest prognostic factor for lymph node recurrence [8], but is not available on initial biopsy. Another recently identified prognostic factor, MELF pattern, is not available before final pathology of the hysterectomy specimen [37]. The three overexpressed pathways in the group with lymph node involvement are EMT, ECM and SMC, and these data are consistent with the literature. The ECM networks create a microenvironment for cell growth and development, favorable for tumoral invasion [38]. EMT has been identified as a principal component of tumor metastasis, by increasing the motility and invasiveness of cancer cells [39]. The SMC pathway regroups genes that control the interaction between cancer and stromal cells, found to have an impact on cancer invasion [40]. The immune cells’ pathway was overexpressed in cluster B, and they are known to shape the immune environment in endometrial cancer and predict the prognosis [41]. In particular, the MSX1 (EMT pathway) was found to be downregulated in EEC with lymph node metastasis. The gene MSX1 (Msh homeobox 1) encodes the homonymous protein MSX1, a transcription repressor, that has an inhibitory effect on the cell cycle [42]. Eppich et al. found that higher MSX1 expression (assessed by immunochemistry) correlates with improved long-term survival [42]. In a study by Yang et al. the research team developed a nine-transcription factors’ prognostic signature, and MSX1 was one of them. However, the eight other genes from Yang’s signature were not differentially expressed in our study. Furthermore, this study evaluated gene expressions associated with prognosis but not lymph node metastases and was developed with data obtained in silico from the TCGA, with all histologic types of EC (not only endometrioid histotype, as in our series). Other differentially expressed genes found in our study were previously described as associated with tumorigenesis or poor prognosis. Fibroblast Activation Protein (FAP), from the EMT pathway, was significantly upregulated in EEC with lymph node metastasis. It had been described as predictive of poor prognosis in high-grade serous ovarian carcinomas [43]. MGP (Matrix G1a protein), from the ECM pathway, was upregulated in samples with lymph node metastasis and its role of promoting proliferation, migration and transformation processes in triple negative breast cancer was assessed by Kong et al. [44]. ACTGA (SMC pathway) was also upregulated in our population N+, and was identified as a promoter of cells’ migration and tumor metastasis in hepatocellular cancer [45]. Our study is focused on lymph node metastasis prediction. A few previous papers have investigated the same topic. Huang et al. established an eight-gene biomarkers panel for predicting lymph node metastasis in patients with early stage endometrial cancer [46]. They used RNA-sequencing data from TCGA and a small panel of their own patients’ samples. None of the eight genes they selected was found in our signature. Only three genes of this signature (EYA2, MSX1 and STX18) were differentially expressed between N+ and N− in our population. In their study, samples were mixed between local patients and TCGA patients, clinical data in TCGA are missing and comparison of characteristics between the two different population is difficult. Population disparities (Asian patients in Huang et al. and European patients in our study) could account for differences with our study. A few studies tried to develop a gene signature for lymph node involvement but none found the same differentially expressed genes that we did in our study. Kang et al. in 2019 developed a 12 gene signature predicting lymph node metastasis with 100% sensibility and 41% specificity in the validation set [47]. None of those 12 genes were differentially expressed in our groups. However, no information on other clinical predictors was available in this study and the training and validation cohort had the same origin with a risk of overfitting. Other developed signatures were often developed using data from TCGA patients without information on the surgical techniques of the center, fixation’s delays and clinical data [46,48]. Those parameters (in particular the time of ischemia before the formol fixation) are critical and could dramatically affect the gene expression in endometrial cancer. In this study, the only patients who were selected were those for whom surgery was performed in Institut Bergonie, with guaranteed homogeneity in terms of surgical technique and sample processing in pathology laboratory. Our population was uniformly treated, with complete clinical data. The diagnosis of EEC and, in particular, the evaluation of histological parameters which have risk factors’ value such as myometrial invasion, histological grade and the assessment of lymphovascular space invasion are subject to interobserver variability [49,50]. Moreover, diagnostic criteria have evolved during the selection period. Currently, lymph node invasion risk is assessed pre-operatively on the basis of tumor size, histological grade and myometrial invasion. Our study population of N+ patients was matched to N− patients with the same tumoral characteristics. This method ensures the comparability of our two study groups, to prevent confusion bias. Non-endometrioid endometrial cancers were excluded from our analysis to guarantee homogeneity between the different groups and to ensure that differential expression found between the groups was exclusively due to lymph nodal metastases. This preliminary study to assess molecular markers of lymph node invasion focused on post-operative samples. Considering that evaluation of molecular alteration in pre-operative endometrial specimens shows a high concordance with the definitive hysterectomy specimen [51], this paves the way for a preoperative assessment of the risk of lymph node metastasis. One of the limitations of our study is the low number of patients that would not allow us to test and validate a gene expression signature. For three N+ subjects, no control was found but extraction was performed to maximized RNA-expression data for the N+ patients. This could introduce confusion bias, however the N+ and N− groups were still comparable for tumor size, tumor grade and myometrial invasion. Our study focused mainly on potential biomarkers and pathways’ description. Cross-validated accuracy of the gene expression signature between the enriched groups is 87%. An additional validation of this signature on an independent test set is needed before we could use them in clinical practice. 5. Conclusions In this study, we described the differential gene expression related to lymph node invasion. Our description of the molecular landscape related to lymph node metastasis highlights the role of three pathways: extracellular matrix; epithelial to mesenchymal and smooth muscle contraction, and those results are consistent with literature. This RNA-expression profile may provide a basis for further study to develop a gene expression-based signature that could pre-operatively select patients in whom surgical assessment of lymph node status has a low yield and, consequently, an unfavorable risk–benefit balance. In order to assess reproducibility of our results, we will have to test our gene signature prospectively on an independent population. Acknowledgments We thank V. Brouste from UREC for statistical analysis. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14092188/s1, Figure S1: Quality control proportion on gene to zero according to coverage; Figure S2: Differential gene expression of cluster A and C found 1416 genes, Institut Bergonie, 2010–2017; Figure S3: Differential gene expression of cluster A and B found 1491genes, Institut Bergonie, 2010–2017; Figure S4: Differential gene expression of cluster B and C found 956 genes, Institut Bergonie, 2010–2017; Figure S5: Differential gene expression of cluster A and B + C found 1348 genes, Institut Bergonie, 2010–2017; Figure S6: Differential gene expression of cluster A and C’ (N− patients only in C group) found 1047 genes, Institut Bergonie, 2010–2017. Table S1: Detailed histological and molecular characteristics of patients with EEC treated at Institut Bergonie selected after matching and quality control (n = 28), France, 2010–2017; Table S2: Comparison of histopathological characteristics and molecular patterns of cluster A (n = 8), cluster B (n = 10) and cluster C (n = 11) defined in unsupervised analysis, Institut Bergonie, 2010–2017; Table S3: Comparison of histopathological characteristics and molecular patterns of EEC from cluster C without lymph node involvement (n = 8) and with lymph node involvement (n = 3), Institut Bergonie, 2010–2017; Table S4: Fifty-four genes signature to discriminate N+ and N− patients, Institut Bergonie, 2010–2017; Table S5: Confusion matrix of cross validated 54 genes Click here for additional data file. Author Contributions D.Q. and M.M. designed the study; D.Q., S.C. and M.M. contributed to funding acquisition; S.C., M.M., G.B., F.G., A.F. and A.P. participated in data collection; S.C., M.M., A.B., V.V., C.L. and I.S. contributed to histologic and immunochemistry analysis; J.B. contributed to RNA extractions, A.B., C.L., A.B., M.M. and I.S. performed development of method analysis, quality control and interpretation; A.B. and C.L. performed statistical analysis; D.Q., S.C. and M.M. wrote the draft of the manuscript; S.C., D.Q., G.B., F.G., A.P., A.F., A.B., C.L., I.S. and J.B. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the institutional review board of Institut Bergonie, France and the samples from the tumor archives were centralized in the Biological Resources center of Institut Bergonie, which the French authorities authorized for scientific research (AC-2008-812). Informed Consent Statement Informed non-opposition was obtained from all subjects involved in the study. Data Availability Statement The datasets generated and/or analyzed in this study are available upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow chart, Institut Bergonie, France, 2010–2017. Figure 2 (a). Unsupervised analysis of our population highlights 3 groups A (N = 7), B (N (N = 10) and C (N = 11) (b). Heatmap of differentially expressed genes between the 3 identified clusters (A, B and C) (c). Volcano plots of up-regulated (red) and down-regulated (green) differentially expressed genes between the three clusters, Institut Bergonie, 2010–2017. Figure 3 Summary pathway analysis differentially expressed between cluster A (N+), cluster B (MIX) and cluster C (N−). cancers-14-02188-t001_Table 1 Table 1 Clinical characteristics of EEC without lymph node involvement (n = 12) and with lymph node involvement (n = 16), Institute Bergonie, 2010–2017. Characteristics EEC with Negative Lymph Nodes (n = 12) EEC with Positive Lymph Nodes (n = 16) n (%) Mean (SD) n (%) Mean (SD) Patient’s characteristics Age at diagnosis 63.2 (10.7) 67.8 (6.9) Comorbidities Cardiovascular disease 4 (33.3) 7 (43.8) History of cancer 2 (16.7) 2 (12.5) Thyroid pathology 3 (25.0) 4 (25.0) Chronic renal failure 1 (8.3) 0 (0.0) Diabetes 1 (8.3) 1 (6.2) Pulmonary pathology 1 (8.3) 0 (0.0) Neurological pathology 1 (8.3) 0 (0.0) Menopaused at diagnosis 10 (83.3) 16 (100.0) Smokers 2 (16.7) 1 (7.7) Body mass index (kg/m2) 26.3 (5.7) 28.2 (5.9) Surgical characteristics Type of initial surgery Laparoscopic surgery 9 (75.0) 10 (62.5) Open surgery 3 (25.0) 6 (37.5) Initial lymph node staging Sentinel lymph node biopsy 1 (8.3) 1 (6.2) Pelvic and para-aortic lymphadenectomy 4 (33.3) 10 (62.5) Pelvic lymphadectomy alone 7 (58.3) 3 (18.8) No initial lymph node dissection 0 (0.0) 1 (6.2) Digestive resection 0 (0.0) 2 (12.5) Omentectomy 4 (33.3) 7 (43.8) Surgical re-staging 1 (8.3) 4 (25.0) Proportion of removed pelvic lymph nodes 14 (8.9) 16 (7.0) Proportion of removed para-aortic lymph nodes 22 (8.3) 15 (11.1) cancers-14-02188-t002_Table 2 Table 2 Comparison of histopathological characteristics and molecular patterns of EEC without lymph node involvement (n = 12) and with lymph node involvement (n = 16), Institut Bergonie, 2010–2017. Pathological Characteristics EEC with Negative Lymph Nodes (n = 12) EEC with Positive Lymph Nodes (n = 16) n (%) Mean (SD) n (%) Mean (SD) p-Value 1 Tumoral size 46.8 (22.5) 50.1 (25.9) 0.7 Histological grade 0.9 Low grade (grade 1 and grade 2) 3 (25.0) 5 (31.2) High grade (grade 3) 9 (75.0) 11 (68.8) Myometrial invasion 0.9 ≤50% 4 (33.3) 6 (37.5) >50% 8 (66.7) 10 (62.5) Angioinvasion 0.013 Absence 9 (75.0) 3 (18.8) Non-substantial 1 (8.3) 4 (25.0) Substantial 2 (16.7) 9 (56.2) Number of angioinvasion (if presence of angioinvasion) 3.9 (9.4) 7.2 (8.4) 0.3 Stromal Reaction 0.12 Presence 5 (41.7) 12 (75.0) Absence 7 (58.3) 4 (25.0) MELF pattern 0.07 Presence 3 (25.0) 10 (62.5) Absence 9 (75.0) 6 (37.5) Inflammatory infiltration 0.9 Presence 5 (41.7) 6 (37.5) Absence 7 (58.3) 10 (62.5) Peri nervous invasion 0.4 Presence 1 (8.3) 4 (25.0) Absence 11 (91.7) 12 (75.0) Molecular classification group (TCGA) 0.06 Ultramutated (POLE mutation) 0 (0.0) 0 (0.0) Hypermutated (MSI) 4 (33.3) 9 (56.2) Serous-like (TP53 mutation) 0 (0.0) 3 (18.8) Non specific molecular profile 8 (66.7) 4 (25.0) CTNNB1 mutation 0.1 Pathogenic mutation 5 (41.7) 2 (12.5) No pathogenic mutation 7 (58.3) 14 (87.5) 1 Fisher’s exact test; Two Sample t-test. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ferlay J. Colombet M. Soerjomataram I. Dyba T. Randi G. Bettio M. Gavin A. Visser O. Bray F. Cancer incidence and mortality patterns in Europe: Estimates for 40 countries and 25 major cancers in 2018 Eur. J. Cancer 2018 103 356 387 10.1016/j.ejca.2018.07.005 30100160 2. Morice P. Leary A. Creutzberg C. Abu-Rustum N. Darai E. Endometrial cancer Lancet 2016 387 1094 1108 10.1016/S0140-6736(15)00130-0 26354523 3. Concin N. Matias-Guiu X. Vergote I. Cibula D. Mirza M.R. Marnitz S. Ledermann J. Bosse T. Chargari C. Fagotti A. ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma Int. J. Gynecol. Cancer 2021 31 12 39 10.1136/ijgc-2020-002230 33397713 4. ASTEC Study Group Kitchener H. Swart A. Qian Q. Parmar M. Amos C. Efficacy of systematic pelvic lymphadenectomy in endometrial cancer (MRC ASTEC trial): A randomised study Lancet 2009 373 125 136 10.1016/S0140-6736(08)61766-3 19070889 5. Frost J.A. Webster K.E. Bryant A. Morrison J. Lymphadenectomy for the management of endometrial cancer Cochrane Database Syst. Rev. 2015 2015 CD007585 6. Leitao M.M. Jr. Zhou Q.C. Gomez-Hidalgo N.R. Iasonos A. Baser R. Mezzancello M. Chang K. Ward J. Chi D.S. Roche K.L. Patient-reported outcomes after surgery for endometrial carcinoma: Prevalence of lower-extremity lymphedema after sentinel lymph node mapping versus lymphadenectomy Gynecol. Oncol. 2020 156 147 153 10.1016/j.ygyno.2019.11.003 31780238 7. Bendifallah S. Canlorbe G. Collinet P. Arsene E. Huguet F. Coutant C. Hudry D. Graesslin O. Raimond E. Touboul C. Just how accurate are the major risk stratification systems for early-stage endometrial cancer? Br. J. Cancer 2015 112 793 801 10.1038/bjc.2015.35 25675149 8. Bosse T. Peters E.E. Creutzberg C.L. Jürgenliemk-Schulz I.M. Jobsen J.J. Mens J.W.M. Lutgens L.C. van der Steen-Banasik E.M. Smit V.T. Nout R.A. Substantial lymph-vascular space invasion (LVSI) is a significant risk factor for recurrence in endometrial cancer—A pooled analysis of PORTEC 1 and 2 trials Eur. J. Cancer 2015 51 1742 1750 10.1016/j.ejca.2015.05.015 26049688 9. Levine D.A. Integrated genomic characterization of endometrial carcinoma Nature 2013 497 67 73 10.1038/nature12113 23636398 10. Talhouk A. McConechy M.K. Leung S. Yang W. Lum A. Senz J. Boyd N. Pike J. Anglesio M. Kwon J.S. Confirmation of ProMisE: A simple, genomics-based clinical classifier for endometrial cancer Cancer 2017 123 802 813 10.1002/cncr.30496 28061006 11. Kolehmainen A.M. Pasanen A.M. Koivisto-Korander R.L. Bützow R.C. Loukovaara M.J. Molecular characterization in the prediction of disease extent in endometrial carcinoma Eur. J. Obstet. Gynecol. Reprod. Biol. 2021 256 478 483 10.1016/j.ejogrb.2020.10.031 33189427 12. Board WC of TE Female Genital Tumours [Internet] Available online: https://publications.iarc.fr/Book-And-Report-Series/Who-Classification-Of-Tumours/Female-Genital-Tumours-2020 (accessed on 18 January 2021) 13. Köbel M. Ronnett B.M. Singh N. Soslow R.A. Gilks C.B. McCluggage W.G. Interpretation of P53 Immunohistochemistry in Endometrial Carcinomas: Toward Increased Reproducibility Int. J. Gynecol. Pathol. 2019 38 S123 S131 10.1097/PGP.0000000000000488 29517499 14. Stelloo E. Jansen A.M. Osse E.M. Nout R.A. Creutzberg C.L. Ruano D. Church D.N. Morreau H. Smit V.T. van Wezel T. Practical guidance for mismatch repair-deficiency testing in endometrial cancer Ann. Oncol. 2017 28 96 102 10.1093/annonc/mdw542 27742654 15. Singh N. Wong R. Tchrakian N. Allen S. Clarke B. Gilks C. Interpretation and Reporting Terminology for Mismatch Repair Protein Immunohistochemistry in Endometrial Cancer Br. Assoc. Gynaecol. Pathol. 2020 21 Available online: https://www.thebagp.org/wp-content/uploads/download-manager-files/1593411202wpdm_BAGP%20MMR%20IHC%20Interpretation%20June%202020.pdf (accessed on 31 July 2021) 16. León-Castillo A. Britton H. McConechy M.K. McAlpine J.N. Nout R. Kommoss S. Brucker S.Y. Carlson J.W. Epstein E. Rau T.T. Interpretation of somatic POLE mutations in endometrial carcinoma J. Pathol. 2020 250 323 335 10.1002/path.5372 31829442 17. GitHub—Najoshi/Sickle: Windowed Adaptive Trimming for Fastq Files Using Quality [Internet]. GitHub Available online: https://github.com/najoshi/sickle (accessed on 31 July 2021) 18. GitHub—Jstjohn/SeqPrep: Tool for Stripping Adaptors and/or Merging Paired Reads with Overlap into Single Reads. [Internet]. GitHub Available online: https://github.com/jstjohn/SeqPrep (accessed on 31 July 2021) 19. Langmead B. Salzberg S.L. Fast gapped-read alignment with Bowtie 2 Nat. Methods 2012 9 357 359 10.1038/nmeth.1923 22388286 20. Li H. Handsaker B. Wysoker A. Fennell T. Ruan J. Homer N. Marth G. Abecasis G. Durbin R. The Sequence Alignment/Map format and SAMtools Bioinformatics 2009 25 2078 2079 10.1093/bioinformatics/btp352 19505943 21. Anders S. Pyl P.T. Huber W. HTSeq—A Python framework to work with high-throughput sequencing data Bioinformatics 2015 31 166 169 10.1093/bioinformatics/btu638 25260700 22. Law C.W. Chen Y. Shi W. Smyth G.K. Voom: Precision weights unlock linear model analysis tools for RNA-seq read counts Genome Biol. 2014 15 R29 10.1186/gb-2014-15-2-r29 24485249 23. Ritchie M.E. Phipson B. Wu D.I. Hu Y. Law C.W. Shi W. Smyth G.K. Limma powers differential expression analyses for RNA-sequencing and microarray studies Nucleic Acids Res. 2015 43 e47 10.1093/nar/gkv007 25605792 24. Benjamini Y. Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing J. R. Stat. Soc. Ser. B Methodol. 1995 57 289 300 10.1111/j.2517-6161.1995.tb02031.x 25. Tibshirani R. Hastie T. Narasimhan B. Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression Proc. Natl. Acad. Sci. USA 2002 99 6567 6572 10.1073/pnas.082099299 12011421 26. Subramanian A. Tamayo P. Mootha V.K. Mukherjee S. Ebert B.L. Gillette M.A. Paulovich A. Pomeroy S.L. Golub T.R. Lander E.S. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles Proc. Natl. Acad. Sci. USA 2005 102 15545 15550 10.1073/pnas.0506580102 16199517 27. Singh R.R. Patel K.P. Routbort M.J. Aldape K. Lu X. Manekia J. Abraham R. Reddy N.G. Barkoh B.A. Veliyathu J. Clinical massively parallel next-generation sequencing analysis of 409 cancer-related genes for mutations and copy number variations in solid tumours Br. J. Cancer 2014 111 2014 2023 10.1038/bjc.2014.518 25314059 28. Vogelstein B. Papadopoulos N. Velculescu V.E. Zhou S. Diaz L.A. Kinzler K.W. Cancer Genome Landscapes Science 2013 339 1546 1558 10.1126/science.1235122 23539594 29. Wang K. Li M. Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data Nucleic Acids Res. 2010 38 e164 10.1093/nar/gkq603 20601685 30. R Core Team European Environment Agency [Internet] 2020 Available online: https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006 (accessed on 31 July 2021) 31. Wilkerson M.D. Hayes D.N. ConsensusClusterPlus: A class discovery tool with confidence assessments and item tracking Bioinformatics 2010 26 1572 1573 10.1093/bioinformatics/btq170 20427518 32. Kurnit K.C. Kim G.N. Fellman B.M. Urbauer D.L. Mills G.B. Zhang W. Broaddus R.R. CTNNB1 (beta-catenin) mutation identifies low grade, early stage endometrial cancer patients at increased risk of recurrence Mod. Pathol. 2017 30 1032 1041 10.1038/modpathol.2017.15 28281553 33. Kommoss F.K. Karnezis A.N. Kommoss F. Talhouk A. Taran F.A. Staebler A. Gilks C.B. Huntsman D.G. Krämer B. Brucker S.Y. L1CAM further stratifies endometrial carcinoma patients with no specific molecular risk profile Br. J. Cancer 2018 119 480 486 10.1038/s41416-018-0187-6 30050154 34. Della Corte L. Giampaolino P. Mercorio A. Riemma G. Schiattarella A. De Franciscis P. Bifulco G. Sentinel lymph node biopsy in endometrial cancer: State of the art Transl. Cancer Res. 2020 9 7725 7733 10.21037/tcr.2020.04.21 35117375 35. Capozzi V.A. Riemma G. Rosati A. Vargiu V. Granese R. Ercoli A. Cianci S. Surgical complications occurring during minimally invasive sentinel lymph node detection in endometrial cancer patients. A systematic review of the literature and metanalysis Eur. J. Surg. Oncol. 2021 47 2142 2149 10.1016/j.ejso.2021.03.253 33820674 36. Cibula D. Borčinová M. Marnitz S. Jarkovský J. Klát J. Pilka R. Torné A. Zapardiel I. Petiz A. Lay L. Lower-Limb Lymphedema after Sentinel Lymph Node Biopsy in Cervical Cancer Patients Cancers 2021 13 2360 10.3390/cancers13102360 34068399 37. Hertel J.D. Huettner P.C. Pfeifer J.D. Lymphovascular Space Invasion in Microcystic Elongated and Fragmented (MELF)-Pattern Well-differentiated Endometrioid Adenocarcinoma is Associated with a Higher Rate of Lymph Node Metastasis Int. J. Gynecol. Pathol. 2014 33 127 134 10.1097/PGP.0b013e318285657b 24487466 38. Yadav V.K. Lee T.-Y. Hsu J.B.-K. Huang H.-D. Yang W.-C.V. Chang T.-H. Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression PLoS ONE 2020 15 e0231594 10.1371/journal.pone.0231594 32315343 39. Bilyk O. Coatham M. Jewer M. Postovit L.-M. Epithelial-to-Mesenchymal Transition in the Female Reproductive Tract: From Normal Functioning to Disease Pathology Front. Oncol. 2017 7 145 10.3389/fonc.2017.00145 28725636 40. Tsukamoto H. Shibata K. Kajiyama H. Terauchi M. Nawa A. Kikkawa F. Uterine smooth muscle cells increase invasive ability of endometrial carcinoma cells through tumor–stromal interaction Clin. Exp. Metastasis 2007 24 423 429 10.1007/s10585-007-9079-5 17587187 41. Li B.-L. Wan X.-P. Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer J. Cell. Mol. Med. 2020 24 7767 7777 10.1111/jcmm.15408 32424934 42. Eppich S. Kuhn C. Schmoeckel E. Mayr D. Mahner S. Jeschke U. Gallwas J. Heidegger H.H. MSX1-A Potential Marker for Uterus-Preserving Therapy of Endometrial Carcinomas Int. J. Mol. Sci. 2020 21 4529 10.3390/ijms21124529 43. Li M. Cheng X. Rong R. Gao Y. Tang X. Chen Y. High expression of fibroblast activation protein (FAP) predicts poor outcome in high-grade serous ovarian cancer BMC Cancer 2020 20 1032 10.1186/s12885-020-07541-6 33109151 44. Gong C. Zou J. Zhang M. Zhang J. Xu S. Zhu S. Yang M. Li D. Wang Y. Shi J. Upregulation of MGP by HOXC8 promotes the proliferation, migration, and EMT processes of triple-negative breast cancer Mol. Carcinog. 2019 58 1863 1875 10.1002/mc.23079 31264274 45. Wu Y. Liu Z.G. Shi M.Q. Yu H.Z. Jiang X.Y. Yang A.H. Fu X.S. Xu Y. Yang S. Ni H. Identification of ACTG2 functions as a promoter gene in hepatocellular carcinoma cells migration and tumor metastasis Biochem. Biophys. Res. Commun. 2017 491 537 544 10.1016/j.bbrc.2017.04.007 28385530 46. Huang C.Y. Liao K.W. Chou C.H. Shrestha S. Yang C.D. Chiew M.Y. Huang H.T. Hong H.C. Huang S.H. Chang T.H. Pilot Study to Establish a Novel Five-Gene Biomarker Panel for Predicting Lymph Node Metastasis in Patients with Early Stage Endometrial Cancer Front. Oncol. 2020 9 1508 10.3389/fonc.2019.01508 32039004 47. Kang S. Thompson Z. McClung E.C. Abdallah R. Lee J.K. Gonzalez-Bosquet J. Wenham R.M. Chon H.S. Gene Expression Signature-Based Prediction of Lymph Node Metastasis in Patients with Endometrioid Endometrial Cancer Int. J. Gynecol. Cancer 2018 28 260 266 10.1097/IGC.0000000000001152 29194195 48. Yang X. Cheng Y. Li X. Zhou J. Dong Y. Shen B. Zhao L. Wang J. A Novel Transcription Factor-Based Prognostic Signature in Endometrial Cancer: Establishment and Validation OncoTargets Ther. 2021 14 2579 2598 10.2147/OTT.S293085 33880037 49. Peters E.E. Bartosch C. McCluggage W.G. Genestie C. Lax S.F. Nout R. Oosting J. Singh N. Smit H.C. Smit V.T. Reproducibility of lymphovascular space invasion (LVSI) assessment in endometrial cancer Histopathology 2019 75 128 136 10.1111/his.13871 31155736 50. Guan H. Semaan A. Bandyopadhyay S. Arabi H. Feng J. Fathallah L. Pansare V. Qazi A. Abdul-Karim F. Morris R.T. Prognosis and reproducibility of new and existing binary grading systems for endometrial carcinoma compared to FIGO grading in hysterectomy specimens Int. J. Gynecol. Cancer 2011 21 654 660 10.1097/IGC.0b013e31821454f1 21543931 51. Stelloo E. Nout R.A. Naves L.C. Ter Haar N.T. Creutzberg C.L. Smit V.T. Bosse T. High concordance of molecular tumor alterations between pre-operative curettage and hysterectomy specimens in patients with endometrial carcinoma Gynecol. Oncol. 2014 133 197 204 10.1016/j.ygyno.2014.02.012 24556061

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095509 ijerph-19-05509 Article The Role of Motor Coordination, ADHD-Related Characteristics and Temperament among Mothers and Infants in Exclusive Breastfeeding: A Cohort Prospective Study Freund-Azaria Adi 12 https://orcid.org/0000-0003-1494-2640 Bar-Shalita Tami 1 Regev Rivka 3 Bart Orit 1* Tchounwou Paul B. Academic Editor 1 Occupational Therapy Department, School of Health Professions, Faculty of Medicine, Tel-Aviv University, Ramat Aviv, Tel-Aviv 6997801, Israel; freundazaria@tauex.tau.ac.il (A.F.-A.); tbshalita@post.tau.ac.il (T.B.-S.) 2 Department of Neonatology, Meir Medical Center, Kfar-Saba 4428164, Israel 3 Clalit Health Organization and Neonatal Follow-Up Clinic, Kfar-Saba 4428164, Israel; regevdr@netvision.net.il * Correspondence: oritbert@tauex.tau.ac.il 01 5 2022 5 2022 19 9 550903 3 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Although exclusive breastfeeding is recommended for the first 6 months of life, breastfeeding rates are low. Motor skills and ADHD-related characteristics have not yet been examined as breastfeeding barriers. The aim of this study was to explore whether mothers’ and infants’ motor skills, mothers’ ADHD-related characteristics and infants’ temperament are associated with exclusive breastfeeding at 6 months after birth. Participants were 164 mothers and their infants recruited 2 days after birth. Mothers completed a demographic and delivery information questionnaire, the Infant Feeding Intentions Scale and the Iowa Infant Feeding Attitude Scale. At 6 months, mothers completed the Adult DCD (developmental coordination disorder)/Dyspraxia Checklist, the Adult ADHD (attention deficit hyperactivity disorder) Self-Report Scale Symptom Checklist-v1.1, and the Infant Characteristics Questionnaire, and provided information about their breastfeeding status. They were then divided into two groups accordingly: EBF (exclusive breastfeeding) and NEBF (non-exclusive breastfeeding). Infants were observed using the Test of Sensory Functions in Infants and the Alberta Infant Motor Scale. At 6 months, NEBF mothers reported higher prevalence of DCD (10.2% vs. 1.9%, χ2 = 5.561, p = 0.018) and ADHD (20.3% vs. 8.6%, χ2 = 4.680, p = 0.030) compared to EBF mothers. EBF infants demonstrated better motor coordination (t = 2.47, p = 0.016, d = 0.511), but no temperament differences compared to NEBF infants. Maternal DCD, ADHD and poor infant motor coordination are associated with non-exclusive breastfeeding and may become exclusive breastfeeding barriers. These findings may assist in identifying women at risk of not exclusively breastfeeding and encourage tailoring interventions for achieving higher exclusive breastfeeding rates. exclusive breastfeeding breastfeeding intentions attitudes toward breastfeeding motor coordination developmental coordination disorder (DCD) attention deficit hyperactivity disorder (ADHD) breastfeeding barriers infants mothers This research received no external funding. ==== Body pmc1. Introduction Exclusive breastfeeding is defined as a newborn receiving only breast milk and no other liquids or solids except for vitamins, minerals or medicines. Exclusive breastfeeding is recommended for the first 6 months of life by both the World Health Organization [1] and the American Academy of Pediatrics due to well-established benefits for mothers’ and infants’ health and for infants’ growth and development [2,3,4]. Despite these proven advantages, breastfeeding rates in most developed countries are low. For example, in the United States the rate of exclusive breastfeeding at the age of 6 months is currently only 25%, according to the Centers for Disease Control and Prevention (2020). Therefore, the Healthy People initiative has set a goal of 42% exclusive breastfeeding to be achieved by 2030 [5]. In order to succeed in increasing breastfeeding rates and to achieve the Healthy People’s goal, understanding the reasons for early cessation of breastfeeding is necessary. Indeed, studies have found correlations between exclusive breastfeeding duration and maternal factors such as: mothers’ intention to breastfeed [6,7], their attitudes toward breastfeeding [8], postnatal depression, anxiety [9,10], and the breastfeeding-related pain involved [11,12,13]. Mothers have also reported reasons for ceasing to breastfeed, such as not having enough milk [12,14,15,16], breastfeeding difficulties such as latching issues [17], their infants not gaining enough weight, medical reasons, difficulties with pumping breast milk, and the desire that others would feed the baby [11,15]. Additional factors that have emerged as related to discontinuation of breastfeeding in a qualitative study include: body image, discomfort, and difficulties and lack of confidence in breastfeeding [18]. Maternal obesity [17,19], being a single mom [15] and undergoing a C-section [6,7,16] were also found to be potential risk factors to early cessation of exclusive breastfeeding. The few studies that have examined infant-related factors to explain early cessation of breastfeeding indicate that using a pacifier and bottle feeding in the first few days might be risk factors [20,21,22]. However, to the best of our knowledge, there have been no studies examining infants’ abilities and characteristics as reasons for not being exclusively breastfed or for being breastfed for a short period of time. To date, the examined factors, while extremely important, are not sufficient to satisfactorily explain the reasons for earlier-than-recommended cessation of breastfeeding [23,24], including when the mother wishes to continue [11]. In fact, these refer primarily to circumstantial factors and do not address the abilities and characteristics of mothers and infants required for breastfeeding activity and may affect breastfeeding duration and exclusivity. Breastfeeding is a co-occupation in which both the mother and the infant are required to be mutually responsive and physically active over time [25]. Mutual responsiveness occurs when mother and infant are reciprocally responsive to each other’s emotional tones, mainly while mother recognizes her infant’s hunger and satiety cues and readily responds. Breastfeeding, then, becomes a means for soothing and providing confidence and not only a nutritive act. Shared physical activity refers to mother and infant engaging in a reciprocal, close, linked motor activity. While the infant focuses mainly on the coordinated and efficient latching and sucking, his mother assists him in latching onto the nipple and maintaining adequate posture [26]. Thus, breastfeeding as a co-occupation consists of motor aspects and sustained attention of both mothers and infants, which have not yet been examined in this context. Developmental coordination disorder (DCD), is characterized by an impairment in motor coordination, and attention deficit hyperactivity disorder (ADHD) is characterized by symptoms of inattention, impulsivity and hyperactivity [27]. Both diagnoses are common neurodevelopmental disorders that have a marked impact on daily activities and function throughout the lifespan [28,29,30,31]. The prevalence in the adult general population is 4.2–6.8% [32,33] and 5–6% [34] for ADHD and DCD, respectively. Although in the adult population both disorders have been extensively studied in different contexts, their impact on mothers’ propensity to breastfeed has not yet been examined. Therefore, the aim of this study was to better understand whether and how early cessation of breastfeeding is associated with mothers’ and infants’ motor skills, mothers’ ADHD-related characteristics, and infants’ temperament. The latter includes infants’ activity level, intensity of reaction, distractibility, attention span and persistence, which may be the closest measures to reflect infants’ attention and activity characteristics at this early age [35]. We hypothesized that attitudes toward breastfeeding and breastfeeding intentions, as well as motor coordination and ADHD-related characteristics, will differ between exclusively breastfeeding (EBF) mothers and non-exclusively breastfeeding (NEBF) mothers of 6-month-old infants. We also hypothesized that 6-month-old infants of EBF and NEBF mothers will differ in their gross motor development, motor coordination and temperament. 2. Methods 2.1. Design This study is a cohort prospective study, designed to have data collected at two time points: at 2 days and 6 months after birth, acquire relevant study factors on both infants and mothers, and follow feeding-method status at 6 months after birth. The study was conducted between June 2019 and January 2021 in a leading medical center, where the hospitalization period is 48 h after vaginal birth and 96 h after cesarean birth. 2.2. Sample Mothers hospitalized at the maternity ward between June 2019 and August 2020 were recruited 2 days after birth, using a convenience sampling method. Mothers’ inclusion criteria were desire to initiate breastfeeding, more than 20 years of age, no language barriers, healthy and gave birth to a healthy single newborn between 36–42 weeks of gestation. Mothers’ exclusion criteria were undergoing chemotherapy, HIV positive, and gave birth to a newborn who needed to be fed partially or fully with a tube. Sample size was calculated based on power analyses via G*Power 3 Software derived from p value of 0.05 and statistical power of 0.80. Aligned with the derived recommendations, 174 mothers and their newborn infants were recruited. Ten mothers dropped out during the first few months and did not reach the second data collection time point, resulting in a sample of 164 mothers for the final analysis. The mothers’ age ranged from 21 to 43 years (Mean (SD) 32.4 (4.2)). Infants were born between 36–42 weeks of gestation (Mean (SD) 39.0 (1.2)). Mothers were divided into two groups according to their breastfeeding status at 6 months after birth, following the WHO definitions: (i) EBF group who exclusively breastfed [36]; specifically, in the current study EBF was limited to human milk only, mainly direct from the breast and not expressed, no complementary feeding or feeding by a wet nurse. (ii) NEBF group who did not breastfeed at all (formula feeding only) or partially breastfed (one or more formula feedings per day). The EBF group consisted of 105 mothers and their infants, and the NEBF group consisted of 59 mothers and their infants. 2.3. Data Collection On the second day after birth in the maternity ward, all participating mothers provided written consent and completed self-administered paper questionnaires handed out by the main researcher. Six months after birth, participating mothers completed online self-administered questionnaires. Following the questionnaires submission, two qualified occupational therapists conducted infant assessments through home visits. In all phases of the study, the researcher collecting the data and examiners assessing the infants were blinded to the breastfeeding status and duration. The examiners were not exposed to data collected in questionnaires from the two time points. The mothers were instructed to attain for evaluation after feeding the infant and not to reveal how their infant was being fed. The examiners did not discuss with the mothers their feeding method or breastfeeding status before completing and documenting the infant’s evaluation. 2.4. Ethical Considerations All aspects of the study were approved by the Institutional Ethics Review Board of the Meir Medical Center (reference number 0302-14-MMC) and by the Tel-Aviv University. Written informed consent was obtained from participating mothers, who had been assured that participation was voluntary and that they could choose to withdraw from the study at any time. Mothers’ and infants’ privacy was ensured and kept confidential. 2.5. Measurements On the second day after birth in the maternity ward, participating mothers reported demographic and delivery information and completed the following questionnaires: The Infant Feeding Intentions Scale (IFIS), a standardized, reliable and valid self-report questionnaire [37], was developed to assess the strength of intention to exclusively breastfeed during the first 6 months after birth. Mothers rated how much they agree with 5 statements on a 5-point Likert scale. Total score ranges from 0 (no intention to breastfeed) to 16 (very strong intention to exclusively breastfeed). Internal consistency was demonstrated (Cronbach α = 0.9) as well as a strong significant relationship between total score and actual duration of exclusive breastfeeding [38]. Cronbach’s α for the IFIS in this study was 0.820. The Iowa Infant Feeding Attitude Scale (IIFAS) [39], a standardized, reliable and valid self-report questionnaire was developed to assess maternal attitudes toward breastfeeding. Mothers rated to what extent they agree with 17 statements on a 5-point Likert scale. Total score ranges from 17 (positive formula feeding attitudes) to 85 (positive breastfeeding attitudes). The IIFAS has been demonstrated to have an internal consistency (Cronbach α > 0.8) as well as an excellent ability to predict intent to breastfeed [40]. The questionnaire Cronbach’s α in this study was 0.754. Six months after birth, participating mothers completed the following online questionnaires: The Adult Developmental Coordination Disorders/Dyspraxia Checklist (ADC) [41] is a standardized, reliable and valid self-report screening questionnaire, assessing mothers’ motor coordination. The questionnaire consists of two sections: Section A (10 questions) relates to childhood history (motor coordination experiences as a child); section B (30 questions) relates to current motor coordination functioning as an adult. Mothers rated the 40 items on a 4-point scale, describing the frequency of difficulties experienced (0 = never, 1 = sometimes, 2 = frequently, 3 = always). The total score (sections A + B) ranges from 0 to 120, where higher scores indicate more motor coordination difficulties. In addition, a participant must score at least 17 in section A and 56 or above in total in order to screen positive for DCD [42]. The ADC has been demonstrated to have an internal consistency (Cronbach α = 0.87–0.95) and is able to differentiate between a group of adults with and without DCD [41]. Cronbach’s α for the ADC in this study was 0.793, 0.889 and 0.915 for child, adult and total score, respectively. The Adult ADHD Self-Report Scale Symptom Checklist (ASRS-v1.1) [43] is a standardized, reliable and valid self-report screening questionnaire used to assess symptoms of ADHD based on the 18 DSM-IV symptom criteria. This tool comprises two parts: Part A (6 questions) and part B (12 questions). For each item, mothers rated how often the stated symptom occurred over the prior 6 months, using the following rating scale: 0 = never, 1 = rarely, 2 = sometimes, 3 = often, and 4 = very often. A total score of the 18 questions ranges from 0 to 72, where higher scores indicate more ADHD-related characteristics. In addition, part A ratings of “sometimes”, “often” or “very often” on items 1–3 are assigned one point. For the remaining 4–6 items, ratings of “often” or “very often” are assigned one point. Gaining a score of 4 or more on part A is a strong indication of adult ADHD [44,45]. The ASRS has been demonstrated to have an internal consistency (Cronbach α = 0.63–0.72) and test-retest reliability (r = 0.58–0.77) as well as a strong concordance with clinician diagnoses [46]. Cronbach’s α for the ASRS continuous total scale in this study was 0.927. The Infant Characteristics Questionnaire (ICQ) [47] is a standardized, reliable and valid 24-item caregiver questionnaire that assesses an infant’s temperament in 4 dimensions: ability to calm, adaptivity, activity level and ability to predict infant’s needs. Mothers rated their infant’s behavior and responses during daily routine on a 7-point scale, with the rating of 1 describing an optimal temperamental trait and 7 a difficult temperament. The ICQ has been demonstrated to have an internal consistency (Cronbach α = 0.39–0.79) and test-retest reliability (r = 0.47–0.70) as well as a convergent validity [47,48]. The questionnaire Cronbach’s α in this study was 0.771–0.892. Additionally, at 6 months after birth, two observational tools were conducted at the homes of participating mothers and their infants. The Test of Sensory Functions in Infant (TSFI), a standardized, reliable and valid tool [49] was developed to asses sensory processing and motor coordination in infants. In this study we conducted the adaptive motor part, consisting of 5 items, which is used to evaluate motor coordination. We interpreted the scores as two categories according to the TSFI age range norm: typical (score of 7–15) vs. at risk or deficient performance (score of 0–6). The TSFI has been demonstrated to have a test-retest reliability (ICC = 0.88–0.99) and inter-rater reliability (ICC = 0.26–0.84). Content and construct validity were established [50]. The Alberta Infant Motor Scale (AIMS) [51] was developed to asses infant gross motor development and is a norm-referenced, observational, reliable and valid tool. It consists of 58 items at 4 different positions (prone, supine, sitting, standing). For any item observed by the examiner, 1 point is given, whereas 0 points are given when the item is not observed. The sum of all items observed gives the total raw score, ranging from 0 to 58. The total raw score is converted into a percentile rank. High percentile ranks indicate better gross motor development. The AIMS has been demonstrated to have an inter-rater reliability (ICC = 0.97–0.99), test-retest reliability (ICC = 0.85–0.99) as well as content and concurrent validity [51,52,53]. Current Infant breastfeeding Status (exclusive, partial or none) was reported by mothers at 6 months. 2.6. Data Analysis Statistical analyses were performed with SPSS® V27 (IBM Corp., Armonk, NY, USA). Data were summarized with descriptive statistics by data type. Normality for quantitative continuous variables was tested using the Shapiro–Wilk test for normality. For variables that failed to meet the normality assumption of the test, we used the common procedures to deal with distribution patterns according to their skewness (Sk) and kurtosis (K) [54,55]. The choice of the analysis scheme followed the methodological guidelines suggested by [56,57]. The sample was divided into two groups, according to their breastfeeding status at 6 months after birth: EBF and NEBF groups. Differences between groups were tested using an independent sample t-test for continuous variables, and effect size was calculated via Cohen’s d where values are considered small (0.2), medium (0.5) and large (0.8) [58]. Chi-square tests of independence were used to analyze binary and polytomous variables. Linear dependency between the quantitative study variables was tested using Pearson’s correlation coefficient. A 2-sided 5% level of significance was used in all hypothesis tests. Nominal p-values are presented. 3. Results 3.1. Analysis of Demographic and Delivery-Related Factors No statistically significant group differences were found in the mothers’ education, family status, family income, type of delivery, and whether breastfeeding occurred in the delivery room (Table 1). Furthermore, no significant group differences were found for the mothers’ age (Mean (SD) EBF 32.1 (4.1) years vs. NEBF 33.0 (4.4) years; t = −1.28, p > 0.05). In addition, no statistically significant group differences were found in infant sex, birth order (Table 1), gestational age (Mean (SD) EBF 39.1 (1.2) vs. NEBF 38.8 (1.2); t = 1.84, p > 0.05), and birth weight (kg) (Mean (SD) EBF 3.336 (0.428) vs. NEBF 3.205 (0.369); t = 1.96, p > 0.05). As no statistically significant differences were found between EBF and NEBF, the use of covariates or confounders in the statistical analysis is redundant. 3.2. Analysis of Maternal Factors Maternal factors were mostly moderately skewed: attitudes toward breastfeeding (Sk = −0.17, K = 0.42); breastfeeding intentions (Sk = −0.86, K = −0.09); motor coordination-section A (Sk = 1.6, K = 3.1); motor coordination-section B (Sk = 1.22, K = 1.60); motor coordination-total score (Sk = 1.35, K = 2.0); ADHD-related characteristics (Sk = −0.49, K = −0.05). The Shapiro–Wilk test indicated that “attitudes toward breastfeeding” was normally distributed. Statistically significant differences between groups in attitudes toward breastfeeding were found at the first time point (i.e., on the second day after birth), demonstrating that the EBF mothers had more positive attitudes toward breastfeeding than the NEBF mothers. Furthermore, statistically significant differences between groups were found in the mothers’ scores on breastfeeding intentions at the first time point, namely the EBF group reported higher intentions to breastfeed compared to the NEBF group. We also revealed a large effect size in both attitudes and intentions (Table 2). Maternal motor coordination was analyzed as both a continuous and binary variable (DCD/non-DCD). Statistically significant differences between groups and medium effect size were also found at the second time point (i.e., at 6 months after birth) in mothers’ motor coordination; the EBF group reported lower scores indicating better motor coordination skills, both in section B (current functioning) and in the total score (Table 2). Using the standard cut-off of >17 ADC section A items and >56 ADC total score to indicate a positive DCD screen, statistically significant differences between groups were found (χ2 = 5.561, p = 0.018), demonstrating 1.9% of mothers in the EBF group vs. 10.2% of mothers in the NEBF group screening DCD positive. These findings correspond to a 2.21 Odds Ratio (OR). Hence, for mothers with DCD, the likelihood to belong to the NEBF group 6 months after birth is 2.21 times higher than for mothers without DCD. Similarly, “ADHD-related characteristics” was analyzed as both a continuous and binary variable (ADHD/non-ADHD). Statistically significant differences between groups as well as medium effect size were found in ADHD-related characteristics (summing both part A and part B ASRS-v1.1 items), indicating fewer ADHD-related characteristics in EBF mothers compared to NEBF mothers (Table 2). Using the standard cut-off of ≥4 ASRS-v1.1 part A items to indicate a positive ADHD screening, statistically significant differences between groups were found (χ2 = 4.68, p = 0.03) demonstrating 8.6% of mothers in the EBF group vs. 20.3% of mothers in the NEBF group screening ADHD positive. These findings correspond to a 1.74 Odds Ratio (OR). Thus, for mothers with ADHD, the likelihood to belong to the NEBF group 6 months after birth is 1.74 times higher than for mothers without ADHD. 3.3. Analysis of Infant Factors Infant factors were mostly moderately skewed: motor coordination (Sk = −0.88, K = 0.07); gross motor development (Sk = −1.18, K = 1.68); temperament: ability to calm (Sk = 0.19, K = −0.76), adaptivity (Sk = 0.98, K = 0.36), activity level (Sk = 1.12, K = 0.57), ability to predict infant’s needs (Sk = 0.82, K = 0.72). The Shapiro–Wilk test indicated that “ability to calm” was normally distributed. Infant motor coordination was analyzed as both a continuous and binary variable (typical/at risk or deficient). Statistically significant differences between groups and medium effect size were found in infants’ motor coordination (Table 3). Using the TSFI standard cut-off demonstrated that 12.5% of infants in the EBF group vs. 32.5% of infants in the NEBF group were found at risk or deficient motor performance (χ2 = 6.11, p = 0.013). No differences between groups were found in infants’ gross motor development, as well as in the infants’ temperament on the four subscales of the ICQ (Table 3). 3.4. Relations between Attitudes toward Breastfeeding and Breastfeeding Intentions, Motor Coordination and ADHD-Related Characteristics A statistically significant strong positive correlation was found between attitudes toward breastfeeding and breastfeeding intentions (r = 0.575, p > 0.001). Namely, the more positive the attitudes toward breastfeeding, the greater the intentions to breastfeed exclusively and for a longer duration. Moreover, a statistically significant weak-to-moderate negative correlation was found between mothers’ attitudes toward breastfeeding and current motor coordination (r = −0.249, p = 0.001), and between attitudes toward breastfeeding and ADHD-related characteristics (r = −0.228, p = 0.003). In other words, fewer motor coordination difficulties and fewer maternal ADHD-related characteristics correlated with more positive maternal attitudes toward breastfeeding. Negative correlations were found between breastfeeding intentions and current motor coordination (r = −0.214, p = 0.006), and between breastfeeding intentions and ADHD-related characteristics (r = −0.185, p = 0.018), so that fewer motor coordination difficulties and ADHD-related characteristics correlated with greater breastfeeding intentions. In addition, statistically significant differences were found between DCD and non-DCD mothers in attitudes toward breastfeeding and breastfeeding intentions, indicating more positive attitudes and higher breastfeeding intentions among the non-DCD mothers. Moreover, statistically significant differences were also found between ADHD and non-ADHD mothers in breastfeeding intentions, indicating higher breastfeeding intentions among the non-ADHD mothers (Table 4). We also revealed medium (Cohen’s d > 0.4) to large (Cohen’s d > 0.9) effect size in both attitudes and breastfeeding intentions for ADHD and DCD, respectively (Table 4). 4. Discussion In line with our hypotheses, the mothers’ and infants’ abilities and characteristics examined in this study were associated with breastfeeding exclusivity 6 months after birth, as discussed in detail below. 4.1. Motor Coordination and Breastfeeding We found differences between groups in maternal motor coordination, such that EBF mothers showed better motor coordination skills than NEBF mothers, along with lower prevalence of DCD positive screening among NEBF mothers compared to EBF mothers. This association may be due to the motor nature of breastfeeding, whereby efficient and successful breastfeeding requires a maternal bilateral motor coordination of the hands as well as eye-hand coordination. In addition, to enable the infant to latch onto the nipple, mothers are required to precisely time and coordinate their infant’s spontaneous mouth opening with their latching [26,59]. Motor coordination history, i.e., motor coordination difficulties as a child, was not found to be associated with breastfeeding exclusivity at 6 months. Despite the importance of maternal motor coordination, this is the first study, to our knowledge, to report its benefit for breastfeeding. In examining differences between groups in the infant motor coordination at 6 months, we found that the percentage of infants in the typical range was higher in the EBF group compared to the NEBF group. On the other hand, there were no differences between groups in gross motor development. Previous studies, which have retrospectively linked infant motor development and breastfeeding, have concluded that longer exclusive breastfeeding was associated with better gross and fine motor development [60,61,62]. Conversely, other studies concluded no such association [63,64]. In our study, the findings indicate that specific difficulties in infant motor coordination, but not gross motor developmental milestones, are associated with less exclusive breastfeeding at 6 months. These findings may suggest a cause and effect whereby infant motor coordination skills may affect the establishment of effective, exclusive and prolonged breastfeeding. This is likely due to infant motor coordination skills, which encompass adequate muscle tone, postural control, and bilateral integration and endurance, having a vital role in the breastfeeding activity [26,59]. In the breastfeeding co-occupation, both mother and infant are physically active and are engaged in a reciprocally linked motor behavior [25]. Both of their motor efforts are focused on the achievement of an efficient latch onto the nipple, followed by a coordinated sucking. This needs to occur in an organized and convenient manner for both mother and infant for as long as the infant is hungry and desires to nurse [26,59]. Therefore, this co-occupation may explain our findings where mothers and infants with motor coordination difficulties experience less exclusive breastfeeding 6 months after birth compared to mothers and infants with fewer motor coordination difficulties. 4.2. ADHD-Related Characteristics, Temperament and Breastfeeding Our study found that EBF mothers showed fewer ADHD-related characteristics compared to NEBF mothers, along with lower prevalence of ADHD positive screening. As of yet, studies examining the link between breastfeeding exclusivity and ADHD explored the children population solely [65,66]. Few studies suggested that children with ADHD may be at risk of not being breastfed as infants compared to children with typical development [20,67]. This current study seems to indicate that the same is true for mothers. Namely, mothers with ADHD-related characteristics may be at risk for providing their infants with a short duration of exclusive breastfeeding or for not breastfeeding at all. Since the ability to persist in exclusive breastfeeding over time requires attention, perseverance, and focus [26], mothers with more ADHD-related characteristics may lack these capabilities and accordingly may provide little or no exclusive breastfeeding to their infants. We found no differences between groups in all four subscales of infant temperament. Although previous studies have reported associations between infant temperament and breastfeeding exclusivity and duration [35,68,69,70], our results suggest that the nature of this relationship is still unclear. The results of our study may suggest that different types of infant temperament may lead to the same breastfeeding outcome. For example, an infant with a more “calm” temperament might be very easy and satisfying to breastfeed and therefore his mother could nurse him relatively easily over time. However, a mother to an infant with a “fussy” temperament may choose to nurse as much as possible in an attempt to calm and adapt her infant into a daily routine. Therefore, the different breastfeeding outcomes may be related to other maternal behavioral factors such as their personality trait and self-efficacy [71] which should be examined in further studies. 4.3. Attitudes toward Breastfeeding and Breastfeeding Intentions As expected, attitudes toward breastfeeding were associated with breastfeeding exclusivity at 6 months. In addition, significant associations were found between breastfeeding intentions and breastfeeding exclusivity. These findings are consistent with previous reports that have found that higher positive attitudes toward breastfeeding and breastfeeding intentions prior to and immediately after birth were associated with higher breastfeeding rates and breastfeeding duration [6,7,8,72]. The inter-relation between breastfeeding attitudes and breastfeeding intentions has also been demonstrated in previous studies [6,24]. However, we show novel findings with regard to maternal motor coordination and ADHD-related characteristics. Our findings suggest that mothers with more ADHD-related characteristics or mothers with a greater difficulty in motor coordination may develop more negative attitudes toward breastfeeding even before attempting to nurse. Indeed, they might perceive breastfeeding as too difficult and complex due to previous unsuccessful experiences requiring motor coordination and attention. This perception might decrease the likelihood of breastfeeding intentions and as a result, the extent of exclusive breastfeeding duration. 4.4. Limitations Our study has some limitations: mothers’ motor coordination and ADHD-related characteristics were examined by self-reported questionnaires. While the subjective experience is of utmost importance, using objective assessments may broaden the understanding of the breastfeeding phenomenon. In addition, despite being a prospective study, due to the difficulty of diagnosing temperament, motor coordination and gross motor development at an early age, these assessments were obtained only at 6 months, leaving the direction of the effect not entirely clear. 5. Conclusions Due to the substantial proven benefits of breastfeeding for both mothers and infants, increasing breastfeeding rates should be a major societal target. The more we explore and understand the potentially influential factors to promoting successful and sufficient breastfeeding duration, the better we will be able to address and overcome the barriers and achieve higher exclusively breastfeeding rates for 6-month-old infants. Therefore, there is a need for a continued thorough analysis of breastfeeding as a common, fundamental co-occupation of mothers and infants. Future studies should examine additional maternal and infant abilities, skills and characteristics required for exclusive and extended breastfeeding. Acknowledgments We wish to thank participating mothers for their time and effort. We would also like to thank Ita Litmanovitz, Sofia Bauer, Janice Zausmer and Yonat Madai and the medical and nursing staff of the maternity and neonatal ward at Meir Medical Center for their generous collaboration. This work was performed in partial fulfilment of the requirements of a degree of Adi Freund-Azaria at The Stanley Steyer School of Health Professions, Sackler Faculty of Medicine, Tel Aviv University, Israel. Author Contributions Conceptualization, A.F.-A., T.B.-S., R.R. and O.B.; methodology, A.F.-A., T.B.-S., R.R. and O.B.; software, A.F.-A., T.B.-S. and O.B.; validation, A.F.-A., T.B.-S. and O.B.; formal analysis, A.F.-A., T.B.-S. and O.B.; investigation, A.F.-A.; resources, A.F.-A., T.B.-S., R.R. and O.B.; data curation, A.F.-A., T.B.-S. and O.B.; writing—original draft preparation, A.F.-A., T.B.-S. and O.B.; writing—review and editing, A.F.-A., T.B.-S., R.R. and O.B.; visualization, A.F.-A., T.B.-S. and O.B.; supervision, A.F.-A., T.B.-S. and O.B.; project administration, A.F.-A.; All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Meir Medical Center (reference number 0302-14-MMC) and by the Tel Aviv University Ethics Committee. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicity available due to participants privacy. Conflicts of Interest The authors declare no conflict of interest. ijerph-19-05509-t001_Table 1 Table 1 Mothers’ and infants’ demographic and delivery-related characteristics. EBF (n = 105) NEBF (n = 59) Total Sample (n = 164) n % n % p n (%) Mothers’ education 0.749 High school 7 6.7 5 8.5 12 (7.3) Higher education 7 6.7 5 8.5 12 (7.3) University education 91 86.6 49 83 140 (85.4) Family status 0.609 Married 95 90.5 53 89.8 148 (90.2) In a relationship 8 7.7 4 6.8 12 (7.3) Single 1 1 2 3.4 3 (1.8) Divorced 1 1 1 (0.7) Family income 0.832 Below Average 5 4.8 3 5.1 8 (4.9) Average 10 9.5 4 6.8 14 (8.5) Above Average 90 85.7 52 88.1 142 (86.6) Planned Pregnancy 0.828 Yes 92 87.6 51 86.4 143 (87.2) No 13 12.4 8 13.6 21 (12.8) Pregnancy type 0.445 Spontaneous 98 93.3 52 88.1 150 (91.4) With fertility treatment 4 3.8 3 5.1 7 (4.3) With IVF 3 2.9 4 6.8 7 (4.3) Delivery type 0.936 Vaginal 79 75.2 42 71.2 121 (73.8) Vacuum 11 10.5 7 11.9 18 (11.0) C-Section (Epidural) 14 13.3 9 15.2 23 (14.0) C-Section (Full anesthesia) 1 1 1 1.7 2 (1.2) Breastfeeding in delivery room 0.324 Yes 60 57.1 29 49.2 89 (54.3) No 45 42.9 30 50.8 75 (45.7) Infant’s sex 0.719 Boy 60 57.1 32 54.2 92 (56.1) Girl 45 42.9 27 45.8 72 (43.9) Birth order 0.531 First 46 43.8 19 32.2 65 (39.6) Second 36 34.3 27 45.8 63 (38.4) Third 17 16.2 10 16.9 27 (16.5) Fourth 6 5.7 3 5.1 9 (5.5) Note. Exclusively Breastfeeding (EBF), Non-Exclusively Breastfeeding (NEBF) at 6 months after birth. ijerph-19-05509-t002_Table 2 Table 2 Differences between groups in maternal attitudes toward breastfeeding, breastfeeding intentions, motor coordination and ADHD-related characteristics. EBF (n = 105) NEBF (n = 59) Total Sample (n = 164) Mean (SD) Mean (SD) t p Cohen’s d Mean (SD) Breastfeeding-related factors (Measured at 2 days) Breastfeeding attitudes (IIFAS) 67.7 (6.7) 60.6 (8.4) 5.94 <0.001 0.934 65.2 (8.1) Breastfeeding intentions (IFIS) 13.6 (2.7) 9.1 (4.2) 7.39 <0.001 1.27 11.9 (4.0) Motor and behavioral factors (Measured at 6 months) Motor coordination (ADC, section A) 4.6 (4.3) 6.1 (5.6) −1.91 0.079 0.300 5.2 (4.9) Motor coordination (ADC, section B) 14.8 (10.4) 19.7 (12.7) −2.49 0.014 0.422 16.6 (11.5) Motor coordination (ADC, total score) 19.4 (13.4) 25.8 (17.7) −2.39 0.019 0.407 21.7 (15.3) ADHD-related characteristics (ASRS-v1.1) 21.6 (11.9) 25.7 (12.2) −2.08 0.039 0.340 23.1 (12.2) Note. Exclusively breastfeeding (EBF), Non-exclusively breastfeeding (NEBF) at 6 months after birth; Iowa Infant Feeding Attitude Scale (IIFAS); Infant Feeding Intentions Scale (IFIS); Adult Developmental Coordination Disorders/Dyspraxia Checklist (ADC) (section A-childhood history, section B-current functioning); Adult ADHD Self-Report Scale Symptom Checklist (ASRS-v1.1). ijerph-19-05509-t003_Table 3 Table 3 Differences between groups in infant motor coordination, gross motor development and temperament at 6 months. EBF (n = 105) NEBF (n = 59) Total Sample (n = 164) Mean (SD) Mean (SD) t p Cohen’s d Mean (SD) Motor coordination (TSFI) 8.7 (1.8) 7.7 (2.1) 2.47 0.016 0.511 8.3 (2.0) Gross motor development (AIMS) 54.6 (16.6) 55.3 (14.6) −0.22 0.828 0.044 54.8 (15.8) Temperament (ICQ): Ability to calm 25.4 (8.8) 23.6 (7.6) 1.32 0.190 0.218 24.8 (8.4) Adaptivity 10.0 (4.2) 10.2 (4.5) −0.30 0.763 0.045 10.1 (4.3) Activity level 7.5 (3.1) 7.4 (3.3) 0.20 0.845 0.031 7.5 (3.2) Ability to predict infant’s needs 10.1 (3.7) 10.9 (4.2) −1.30 0.194 0.202 10.3 (3.9) Note. Exclusively breastfeeding (EBF), Non-exclusively breastfeeding (NEBF) at 6 months after birth; Test of Sensory Functioning in Infants (TSFI, adaptive-motor subtest); Alberta Infant Motor Scale (AIMS, percentage score); Infant characteristics Questionnaire (ICQ). ijerph-19-05509-t004_Table 4 Table 4 Differences between DCD and non-DCD mothers; ADHD and non-ADHD mothers in attitudes toward breastfeeding and breastfeeding intentions. DCD Mothers (n = 8) Non-DCD Mothers (n = 155) Mean SD Mean SD t p Cohen’s d Breastfeeding attitudes (IIFAS) 58.5 5.5 65.5 8.1 2.42 0.017 1.01 Breastfeeding intentions (IFIS) 8.4 4 12.1 3.9 2.61 0.010 0.936 ADHD Mothers (n = 21) Non-ADHD Mothers (n = 142) Mean SD Mean SD t p Cohen’s d Breastfeeding attitudes (IIFAS) 62.4 7.3 65.6 8.1 −1.69 0.092 0.415 Breastfeeding intentions (IFIS) 10.2 4.5 12.2 3.8 −2.14 0.034 0.480 Note. Developmental coordination disorder (DCD); Attention deficit hyperactivity disorder (ADHD); Iowa Infant Feeding Attitude Scale (IIFAS); Infant Feeding Intentions Scale (IFIS). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kramer M.S. Kakuma R. Optimal duration of exclusive breastfeeding Cochrane Database of Systematic Reviews John Wiley & Sons, Ltd. Hoboken, NJ, USA 2012 10.1002/14651858.cd003517.pub2 2. American Academy of Pediatrics Section on Breastfeeding Breastfeeding and the Use of Human Milk Pediatrics 2012 129 e827 e841 10.1542/peds.2011-3552 22371471 3. Horta B.L. Loret De Mola C. Victora C.G. Long-term consequences of breastfeeding on cholesterol, obesity, systolic blood pressure and type 2 diabetes: A systematic review and meta-analysis Acta Paediatr. 2015 104 30 37 10.1111/apa.13133 26192560 4. Victora C.G. Bahl R. Barros A.J. França G.V. Horton S. Krasevec J. Murch S. Sankar M.J. Walker N. Rollins N.C. Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect Lancet 2016 387 475 490 10.1016/S0140-6736(15)01024-7 26869575 5. Office of Disease Prevention and Health Promotion. Healthy People 2030. Increase the Proportion of Infants who Are Breastfed Exclusively through Age 6 Months 2020 Available online: https://health.gov/healthypeople/objectives-and-data/browse-objectives/infants/increase-proportion-infants-who-are-breastfed-exclusively-through-age-6-months-mich-15 (accessed on 27 January 2021) 6. Balogun O.O. Kobayashi S. Anigo K.M. Ota E. Asakura K. Sasaki S. Factors influencing exclusive breastfeeding in early infancy: A prospective study in north central Nigeria Matern. Child Health J. 2015 20 363 375 10.1007/s10995-015-1835-6 7. Santacruz-Salas E. Aranda-Reneo I. Segura-Fragoso A. Cobo-Cuenca A.I. Laredo-Aguilera J.A. Carmona-Torres J.M. Mothers’ Expectations and factors influencing exclusive breastfeeding during the first 6 months Int. J. Environ. Res. Public Health 2019 17 77 10.3390/ijerph17010077 31861896 8. Ho Y.-J. McGrath J.M. Predicting breastfeeding duration related to maternal attitudes in a Taiwanese sample J. Périnat. Educ. 2011 20 188 199 10.1891/1058-1243.20.4.188 22942621 9. Mikšić Š. Uglešić B. Jakab J. Holik D. Milostić Srb A. Degmečić D. Positive effect of breastfeeding on child development, anxiety, and postpartum depression Int. J. Environ. Res. Public Health 2020 17 2725 10.3390/ijerph17082725 10. Gila-Díaz A. Carrillo G.H. López de Pablo Á.L. Arribas S.M. Ramiro-Cortijo D. Association between maternal postpartum depression, stress, optimism, and breastfeeding pattern in the first six months Int. J. Environ. Res. Public Health 2020 17 7153 10.3390/ijerph17197153 11. Odom E.C. Li R. Scanlon K.S. Perrine C.G. Grummer-Strawn L. Reasons for earlier than desired cessation of breastfeeding Pediatrics 2013 131 e726 e732 10.1542/peds.2012-1295 23420922 12. Morrison A.H. Gentry R. Anderson J. Mothers’ reasons for early breastfeeding cessation MCN Am. J. Matern. Nurs. 2019 44 325 330 10.1097/NMC.0000000000000566 13. Brown A. Rance J. Bennett P. Understanding the relationship between breastfeeding and postnatal depression: The role of pain and physical difficulties J. Adv. Nurs. 2015 72 273 282 10.1111/jan.12832 26494433 14. Chang P.C. Li S.F. Yang H.Y. Wang L.C. Weng C.Y. Chen K.F. Chen W. Fan S.Y. Factors associated with cessation of exclusive breastfeeding at 1 and 2 months postpartum in Taiwan Int. Breastfeed. J. 2019 14 18 10.1186/s13006-019-0213-1 31080493 15. Rozga M.R. Kerver J.M. Olson B.H. Self-reported reasons for breastfeeding cessation among low-income women enrolled in a peer counseling breastfeeding support program J. Hum. Lact. 2014 31 129 137 10.1177/0890334414548070 25158829 16. Shi H. Yang Y. Yin X. Li J. Fang J. Wang X. Determinants of exclusive breastfeeding for the first six months in China: A cross-sectional study Int. Breastfeed. J. 2021 16 40 10.1186/s13006-021-00388-y 34001155 17. Moss K.M. Dobson A.J. Tooth L. Mishra G.D. Which Australian women do not exclusively breastfeed to 6 months, and why? J. Hum. Lact. 2020 37 390 402 10.1177/0890334420929993 32484717 18. Brown A. Raynor P. Lee M. Healthcare professionals’ and mothers’ perceptions of factors that influence decisions to breastfeed or formula feed infants: A comparative study J. Adv. Nurs. 2011 67 1993 2003 10.1111/j.1365-2648.2011.05647.x 21507050 19. Fan W.Q. Molinaro A. Maternal obesity adversely affects early breastfeeding in a multicultural, multi-socioeconomic Melbourne community Aust. N. Z. J. Obstet. Gynaecol. 2021 61 78 85 10.1111/ajo.13232 32789926 20. Sabuncuoglu O. Orengul C. Bikmazer A. Kaynar S.Y. Breastfeeding and Parafunctional Oral Habits in Children with and without Attention-Deficit/Hyperactivity Disorder Breastfeed. Med. 2014 9 244 250 10.1089/bfm.2014.0014 24841034 21. Raihan M.J. Choudhury N. Haque A. Farzana F.D. Ali M. Ahmed T. Feeding during the first 3 days after birth other than breast milk is associated with early cessation of exclusive breastfeeding Matern. Child Nutr. 2020 16 e12971 10.1111/mcn.12971 32048470 22. Zarshenas M. Zhao Y. Scott J.A. Binns C.W. Determinants of breastfeeding duration in Shiraz, Southwest Iran Int. J. Environ. Res. Public Health 2020 17 1192 10.3390/ijerph17041192 23. Brown C.R. Dodds L. Legge A. Bryanton J. Semenic S. Factors influencing the reasons why mothers stop breastfeeding Can. J. Public Health 2014 105 179 185 10.17269/cjph.105.4244 25165836 24. Lau C.Y.K. Lok K.Y.W. Tarrant M. Breastfeeding duration and the theory of planned behavior and breastfeeding self-efficacy framework: A systematic review of observational studies Matern. Child Health J. 2018 22 327 342 10.1007/s10995-018-2453-x 29427014 25. Pickens N.D. and Pizur-Barnekow, K. Co-occupation: Extending the dialogue J. Occup. Sci. 2009 16 151 156 10.1080/14427591.2009.9686656 26. Pitonyak J.S. Occupational therapy and breastfeeding promotion: Our role in societal health Am. J. Occup. Ther. 2014 68 e90 e96 10.5014/ajot.2014.009746 24797203 27. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders: DSM-5 5th ed. American Psychiatric Association Washington, DC, USA 2013 28. Butzbach M. Fuermaier A.B.M. Aschenbrenner S. Weisbrod M. Tucha L. Tucha O. Metacognition, psychopathology and daily functioning in adult ADHD J. Clin. Exp. Neuropsychol. 2021 43 384 398 10.1080/13803395.2021.1940104 34157944 29. Engel-Yeger B. The role of poor motor coordination in predicting adults’ health related quality of life Res. Dev. Disabil. 2020 103 103686 10.1016/j.ridd.2020.103686 32417632 30. Cleaton M.A. Tal-Saban M. Hill E.L. Kirby A. Gender and age differences in the presentation of at-risk or probable Developmental Coordination Disorder in adults Res. Dev. Disabil. 2021 115 104010 10.1016/j.ridd.2021.104010 34139601 31. Roselló B. Berenguer C. Baixauli I. Mira Á. Martinez-Raga J. Miranda A. Empirical examination of executive functioning, ADHD associated behaviors, and functional impairments in adults with persistent ADHD, remittent ADHD, and without ADHD BMC Psychiatry 2020 20 134 10.1186/s12888-020-02542-y 32204708 32. Song P. Zha M. Yang Q. Zhang Y. Li X. Rudan I. The prevalence of adult attention-deficit hyperactivity disorder: A global systematic review and meta-analysis J. Glob. Health 2021 11 04009 10.7189/jogh.11.04009 33692893 33. London A.S. Landes S. Cohort change in the prevalence of ADHD among U.S. Adults: Evidence of a gender-specific historical period effect J. Atten. Disord. 2019 25 771 782 10.1177/1087054719855689 31189421 34. Saban M.T. Kirby A. Empathy, social relationship and co-occurrence in young adults with DCD Hum. Mov. Sci. 2018 63 62 72 10.1016/j.humov.2018.11.005 30503983 35. Kielbratowska B. Kazmierczak M. Michalek J. Preis K. Temperament and the mother-infant dyad: Associations with breastfeeding and formula feeding with a bottle Infant Ment. Health J. 2015 36 243 250 10.1002/imhj.21508 25973840 36. WHO UNICEF USAID Indicators for Assessing Infant and Young Child Feeding Practices WHO Geneva, Switzerland 2010 37. Nommsen-Rivers L.A. Dewey K.G. Development and validation of the Infant Feeding Intentions Scale Matern. Child Health J. 2008 13 334 342 10.1007/s10995-008-0356-y 18473131 38. Nommsen-Rivers L.A. Cohen R.J. Chantry C.J. Dewey K.G. The Infant Feeding Intentions scale demonstrates construct validity and comparability in quantifying maternal breastfeeding intentions across multiple ethnic groups Matern. Child Nutr. 2009 6 220 227 10.1111/j.1740-8709.2009.00213.x 20929494 39. de la Mora A. Russell D.W. Dungy C.I. Losch M. Dusdieker L. The Iowa Infant Feeding Attitude Scale: Analysis of reliability and validity1 J. Appl. Soc. Psychol. 1999 29 2362 2380 10.1111/j.1559-1816.1999.tb00115.x 40. Twells L.K. Midodzi W.K. Ludlow V. Murphy-Goodridge J. Burrage L. Gill N. Halfyard B. Schiff R. Newhook L.A. Assessing infant feeding attitudes of expectant women in a provincial population in Canada: Validation of the Iowa Infant Feeding Attitude Scale J. Hum. Lact. 2016 32 NP9 NP18 10.1177/0890334414559647 25425631 41. Kirby A. Edwards L. Sugden D. Rosenblum S. The development and standardization of the Adult Developmental Co-ordination Disorders/Dyspraxia Checklist (ADC) Res. Dev. Disabil. 2010 31 131 139 10.1016/j.ridd.2009.08.010 19819107 42. Kirby A. Williams N. Thomas M. Hill E.L. Self-reported mood, general health, wellbeing and employment status in adults with suspected DCD Res. Dev. Disabil. 2013 34 1357 1364 10.1016/j.ridd.2013.01.003 23417140 43. Kessler R.C. Adler L. Ames M. Demler O. Faraone S. Hiripi E. Howes M.J. Jin R. Secnik K. Spencer T. The World Health Organization adult ADHD self-report scale (ASRS): A short screening scale for use in the general population Psychol. Med. 2005 35 245 256 10.1017/S0033291704002892 15841682 44. Adler L.A. Faraone S.V. Sarocco P. Atkins N. Khachatryan A. Establishing US norms for the Adult ADHD Self-Report Scale (ASRS-v1.1) and characterising symptom burden among adults with self-reported ADHD Int. J. Clin. Pract. 2018 73 e13260 10.1111/ijcp.13260 30239073 45. Dunlop B.W. Wu R. Helms K. Performance of the adult ADHD self-report scale-v1.1 in adults with major depressive disorder Behav. Sci. 2018 8 37 10.3390/bs8040037 29596328 46. Kessler R.C. Adler L.A. Gruber M.J. Sarawate C.A. Spencer T. Van Brunt D.L. Validity of the World Health Organization Adult ADHD Self-Report Scale (ASRS) Screener in a representative sample of health plan members Int. J. Methods Psychiatr. Res. 2007 16 52 65 10.1002/mpr.208 17623385 47. Bates J.E. Freeland C.A.B. Lounsbury M.L. Measurement of infant difficultness Child Dev. 1979 50 794 803 10.2307/1128946 498854 48. Guerin D.W. Gottfried A.W. Temperamental consequences of infant difficultness Infant Behav. Dev. 1994 17 413 421 10.1016/0163-6383(94)90033-7 49. DeGangi G.A. Greenspan S.I. The development of sensory functions in infants Phys. Occup. Ther. Pediatr. 1989 8 21 33 10.1080/J006v08n04_02 50. Eeles A.L. Spittle A.J. Anderson P.J. Brown N. Lee K.J. Boyd R.N. Doyle L.W. Assessments of sensory processing in infants: A systematic review Dev. Med. Child Neurol. 2013 55 314 326 10.1111/j.1469-8749.2012.04434.x 23157488 51. Piper M.C. Darrah J. Maguire T.O. Redfern L. Motor Assessment of the Developing Infant Saunders Philadelphia, PA, USA 1994 52. Lackovic M. Nikolic D. Filimonovic D. Petronic I. Mihajlovic S. Golubovic Z. Pavicevic P. Cirovic D. Reliability, consistency and temporal stability of Alberta Infant Motor Scale in Serbian infants Children 2020 7 16 10.3390/children7030016 53. Jeng S.F. Yau K.I.T. Chen L.C. Hsiao S.F. Alberta infant motor scale: Reliability and validity when used on preterm infants in Taiwan Phys. Ther. 2000 80 168 178 10.1093/ptj/80.2.168 10654063 54. Glass G.V. Peckham P.D. Sanders J.R. Consequences of failure to meet assumptions underlying the fixed effects analyses of variance and covariance Rev. Educ. Res. 1972 42 237 10.3102/00346543042003237 55. Harwell M.R. Rubinstein E.N. Hayes W.S. Olds C.C. Summarizing Monte Carlo results in methodological research: The one- and two-factor fixed effects ANOVA cases Am. Educ. Res. Assoc. Am. Stat. Assoc. 1992 17 315 339 56. Curran P.J. West S.G. Finch J.F. The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis Psychol. Methods 1996 1 16 29 10.1037/1082-989X.1.1.16 57. Blanca M.J. Alarcón R. Arnau J. Bono R. Bendayan R. Non-normal data: Is ANOVA still a valid option? Psicothema 2017 29 552 557 10.7334/psicothema2016.383 29048317 58. Schelly D. Ohl A. Examining clinical meaningfulness in randomized controlled trials: Revisiting the well elderly II Am. J. Occup. Ther. 2019 73 7301205120p1 7301205120p13 10.5014/ajot.2019.030874 30839267 59. Genna C.W. Supporting Sucking Skills in Breastfeeding Infants Jones and Bartlett Publishers, Inc. Burlington, MA, USA 2013 60. Grace T. Oddy W. Bulsara M. Hands B. Breastfeeding and motor development: A longitudinal cohort study Hum. Mov. Sci. 2017 51 9 16 10.1016/j.humov.2016.10.001 27821311 61. Sacker A. Quigley M.A. Kelly Y.J. Breastfeeding and developmental delay: Findings from the millennium cohort study Pediatrics 2006 118 e682 e689 10.1542/peds.2005-3141 16950960 62. Tinius R. Rajendran N. Miller L. Menke B. Esslinger K. Maples J. Furgal K. Maternal factors related to infant motor development at 4 months of age Breastfeed. Med. 2020 15 90 95 10.1089/bfm.2019.0243 31944825 63. Michels K.A. Ghassabian A. Mumford S.L. Sundaram R. Bell E.M. Bello S.C. Yeung E.H. Breastfeeding and motor development in term and preterm infants in a longitudinal US cohort Am. J. Clin. Nutr. 2017 106 1456 1462 10.3945/ajcn.116.144279 29092884 64. Stelmach I. Kwarta P.E. Jerzyńska J. Stelmach W. Krakowiak J. Karbownik M. Podlecka D. Hanke W. Polańska K. Duration of breastfeeding and psychomotor development in 1-year-old children—Polish Mother and Child Cohort Study Int. J. Occup. Med. Environ. Health 2019 32 175 184 10.13075/ijomeh.1896.01328 30829342 65. Brasfield J. Goulding S.M. Kancherla V. Duration of breast feeding and attention-deficit/hyperactivity disorder in United States preschool-aged children Res. Dev. Disabil. 2021 115 103995 10.1016/j.ridd.2021.103995 34049210 66. Zeng Y. Tang Y. Tang J. Shi J. Zhang L. Zhu T. Xiao D. Qu Y. Mu D. Association between the different duration of breastfeeding and attention deficit/hyperactivity disorder in children: A systematic review and meta-analysis Nutr. Neurosci. 2018 23 811 823 10.1080/1028415X.2018.1560905 30577717 67. Stadler D.D. Musser E.D. Holton K.F. Shannon J. Nigg J.T. Recalled initiation and duration of maternal breastfeeding among children with and without ADHD in a well characterized case–control sample J. Abnorm. Child Psychol. 2015 44 347 355 10.1007/s10802-015-9987-9 25749651 68. Taut C. Kelly A. Zgaga L. The association between infant temperament and breastfeeding duration: A cross-sectional study Breastfeed. Med. 2016 11 111 118 10.1089/bfm.2015.0184 26910409 69. de Lauzon-Guillain B. Wijndaele K. Clark M. Acerini C.L. Hughes I.A. Dunger D.B. Wells J.C. Ong K.K. Breastfeeding and infant temperament at age three months PLoS ONE 2012 7 e29326 10.1371/journal.pone.0029326 22253712 70. Abuhammad S. Khraisat O. Joseph R. Al Khawaldeh A. Factors that predict infant temperament: A Jordanian Study J. Pediatr. Nurs. 2020 51 e45 e49 10.1016/j.pedn.2019.08.002 31421919 71. Brown A. Maternal trait personality and breastfeeding duration: The importance of confidence and social support J. Adv. Nurs. 2013 70 587 598 10.1111/jan.12219 23919294 72. Callaghan S. Geraghty A.A. Moore R.L. McAuliffe F.M. Exploration of factors associated with intention, initiation and duration of breastfeeding Ir. Med. J. 2020 113 1 8 32298555

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094515 ijms-23-04515 Article Effect of Sample Transportation on the Proteome of Human Circulating Blood Extracellular Vesicles https://orcid.org/0000-0003-2820-0277 Uldry Anne-Christine 12 Maciel-Dominguez Anabel 12 Jornod Maïwenn 12 Buchs Natasha 12 Braga-Lagache Sophie 12 https://orcid.org/0000-0003-0970-7048 Brodard Justine 3 Jankovic Jovana 3 https://orcid.org/0000-0001-8761-2066 Bonadies Nicolas 23 https://orcid.org/0000-0002-6364-7325 Heller Manfred 12* Costanzo Michele Academic Editor Caterino Marianna Academic Editor Santorelli Lucia Academic Editor 1 Proteomics and Mass Spectrometry Core Facility, Department for BioMedical Research (DBMR), University of Bern, 3008 Bern, Switzerland; anne-christine.uldry@dbmr.unibe.ch (A.-C.U.); anabel.macield@gmail.com (A.M.-D.); maiwenn.jornod@gmail.com (M.J.); natasha.buchs@dbmr.unibe.ch (N.B.); sophie.lagache@dbmr.unibe.ch (S.B.-L.) 2 Department for BioMedical Research, University of Bern, 3008 Bern, Switzerland; nicolas.bonadies@insel.ch 3 Department of Hematology and Central Hematology Laboratory, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland; justine.brodard@insel.ch (J.B.); jovana.jankovic@students.unibe.ch (J.J.) * Correspondence: manfred.heller@dbmr.unibe.ch; Tel.: +41-31-684-04-82 19 4 2022 5 2022 23 9 451524 3 2022 09 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Circulating extracellular vesicles (cEV) are released by many kinds of cells and play an important role in cellular communication, signaling, inflammation modulation, coagulation, and tumor growth. cEV are of growing interest, not only as biomarkers, but also as potential treatment targets. However, very little is known about the effect of transporting biological samples from the clinical ward to the diagnostic laboratory, notably on the protein composition. Pneumatic tube systems (PTS) and human carriers (C) are both routinely used for transport, subjecting the samples to different ranges of mechanical forces. We therefore investigated qualitatively and quantitatively the effect of transport by C and PTS on the human cEV proteome and particle size distribution. We found that samples transported by PTS were subjected to intense, irregular, and multidirectional shocks, while those that were transported by C mostly underwent oscillations at a ground frequency of approximately 4 Hz. PTS resulted in the broadening of nanoparticle size distribution in platelet-free (PFP) but not in platelet-poor plasma (PPP). Cell-type specific cEV-associated protein abundances remained largely unaffected by the transport type. Since residual material of lymphocytes, monocytes, and platelets seemed to dominate cEV proteomes in PPP, it was concluded that PFP should be preferred for any further analyses. Differential expression showed that the impact of the transport method on cEV-associated protein composition was heterogeneous and likely donor-specific. Correlation analysis was nonetheless able to detect that vibration dose, shocks, and imparted energy were associated with different terms depending on the transport, namely in C with cytoskeleton-regulated cell organization activity, and in PTS with a release of extracellular vesicles, mainly from organelle origin, and specifically from mitochondrial structures. Feature selection algorithm identified proteins which, when considered together with the correlated protein-protein interaction network, could be viewed as surrogates of network clusters. circulating extracellular vesicles pneumatical tube system transport acceleration forces vibration label-free proteomics clinical blood samples ==== Body pmc1. Introduction Extracellular vesicles (EV) are spherical particles that are derived from shedding parts of intracellular compartments or plasma membrane through endosomal or ectosomal pathways, respectively [1]. They are enclosed by a lipid bilayer membrane and stabilized by membrane-associated proteins. EV contain a variety of cellular components including metabolites, proteins, and polynucleotides. Essentially all cells produce EV, which act as inter-cellular transport vehicles that convey highly active biological molecules on a variety of biological systems, for instance in the context of cancer [2], plant-microbe interactions [3], inflammation [4], and coagulation [5]. EV that are shed from tissues and cells with access to the circulating blood become cEV and have the potential to accumulate in the peripheral blood (PB). The multiplicity of cell origins and production sites means that the pool of cEV in PB is an extremely heterogeneous mixture containing a variety of biological effectors, which are involved in tissue regeneration or regulation of the tumor microenvironment [1,6]. cEV are, therefore, increasingly recognized as potential biomarkers and targets for treatment in human diseases. The poorly understood influence of pre-analytical factors as well as the application of a variety of down-stream read-outs, including analytical methods based on fluorescent-activated cell sorting, RNA expression, vesicle size distribution, or coagulation all challenge the establishment of standardized protocols for cEV isolation in a clinical context [7,8,9]. Some of us (Heller, Braga, and Buchs) have previously developed an untargeted approach of label-free proteomics using nanoflow liquid chromatography coupled to tandem mass spectrometry (nLC-MS2) for the semi-quantitative protein profiling of cEV in human PB. By this means, correlations of cEV quantity and their protein content with arteriogenesis in the human heart muscle were identified [10]. Moreover, by characterizing cEV-associated proteins based on gene ontology terms, known cellular location and cell type specificity, we demonstrated that quantitative proteomics enables profiling of the cell origin of cEV, that a single freeze/thaw cycle of blood samples activates coagulation, and the method of freezing of blood samples causes damage to cEV integrity, as indicated by increasing losses of cytosolic proteins between slow freezing at −80 °C and snap-freezing in liquid nitrogen [11]. Many pre-analytical conditions influence the interpretation of blood analyses. These include mainly patient-based factors but also procedural factors, such as the devices that are used, skills of medical staff, lag time, and temperature [12]. Mechanical forces that are associated with PB transport can have a relevant impact on diagnostic tests as well. Most hospitals are fitted with a pneumatic tube system (PTS) which guarantees a fast and efficient delivery of samples from the clinics to the laboratory. However, the pre-analytical impact that is associated with mechanical forces has to be investigated for all potentially susceptible laboratory tests [13] before samples are transported by PTS [14,15,16]. As examples, Kocak and colleagues could not find any statistically significant impact on blood cell counts or erythrocyte sedimentation and standard coagulation tests between samples that were transported by PTS or human carrier (C) [17]. Correspondingly, Phelan et al. did not detect any influence on hemolysis [18]. In contrast, acceleration forces had a relevant impact on platelet aggregometry [19,20], thromboelastometry, and thrombin generation [21], for which reason samples have to be transported by C for these tests. Due to the biological interconnection of platelets with the coagulation system, it is important to investigate whether the transport mode influences the cEV proteome. Only few groups have systematically addressed this question [22,23,24]. They reported an increase in procoagulant activity, along with an increase of annexin-V positive vesicles. However, rather artificial conditions were used, such as extensive stair walking by a carrier or strong agitations on orbital shakers. To close this gap, we set out to investigate the impact of transport by PTS and C on the cEV proteome in a representative clinical context, by untargeted label-free mass spectrometry and recording of the energy levels that were impacted on the blood samples. 2. Results 2.1. PTS and C Exhibit Substantially Different Transport Metrics The visual examination of the 3D accelerations that were measured during the transport of the 12 donors’ samples revealed important differences between C and PTS (Supplementary Materials Figure S1 for one representative example). The acceleration signal of all PTS transports exhibited irregular patterns with several peaks of large amplitude and short duration, which occurred in any possible direction. In contrast, the C samples showed more gentle patterns, regular but complex oscillatory signatures that were typical of a walker (Supplementary Tables S2 and S3). There were three metrics integrating the acceleration signal over time that were calculated for each transport event (see Section 4.2 and Methods section of Supplementary Materials): mean Teaker–Kaiser operator (TK), root mean square (RMS), and vibration dose value (VDV). A boxplot of those transport metrics is shown in Figure 1. Transportation through PTS lasted on average less than half as long as by C (2.4 ± 0.3 min compared to 5.5 ± 0.5 min). PTS subjected probes to substantially higher accelerations than C, with maximum amplitudes per journey > 17 g in PTS and <2.4 g in C. Moreover, PTS signals exhibited a significantly skewed distribution towards higher g-forces with a mean of 116 shocks having an amplitude >2.5 g. Transport metrics TK, RMS, VDV were significantly higher by approximately one order of magnitude in PTS compared to C (Supplementary Table S3 and Figure S1). In spite of this, the median accelerations of both modes of transport through the transport event time were in a similar low range (0.1–0.4 g). Since the same carrier transported all the samples, it was not too surprising that the ground frequencies in C were all very similar at 3.98 ± 0.07 Hz. This ground frequency appears to be characteristic of the gait and speed of the walker, as tests that were performed with two other carriers gave 2 Hz and 4.3 Hz, respectively (not shown). In summary, transport metrics were substantially different between PTS and C, with low intensity, regular oscillations for C compared to very high, irregular, and multidirectional accelerations of short duration for PTS, respectively. 2.2. PFP Centrifugation Protocol Isolates Pure cEV A total of two plasma preparation procedures were considered in this work (see Materials and Methods), namely platelet-poor (PPP) and platelet-free plasma (PFP). While our laboratory has shown earlier that the applied centrifugation protocol does successfully isolate cEV from PFP [11], the concept behind the use of PPP is that it contains cell fragments, an indicator of differential cell damage in case one transportation mode is more damaging to cells than the other. The demonstration by Braga-Lagache et al. [11] that the centrifugation protocol applied to PFP does indeed isolate cEV was based on mathematical vesicle sedimentation modelling and transmission electron microscopy imaging; it was shown that larger vesicles of diameters >500 nm are almost entirely removed by the short high-speed centrifugation of PPP, and part of the smallest vesicles (<200 nm) are lost due to their low sedimentation speed. Here, the same operator applied the exact same cEV isolation procedure using the same centrifuges as in Braga-Lagache et al. In order to confirm that the conclusions that were drawn earlier [11] still apply here, we reprocessed the 400 μL PFP data, consisting of 12 healthy donors, with the same data interpretation pipeline as described here in the Materials and Methods section and made a correlation analysis of the log2-transformed median protein intensities of proteins that were quantified at least three times in both datasets (N = 1009, Supplementary Figure S2). The squared correlation coefficient (R2) of 0.49 of the cell surface protein class was poor, but the serum/plasma, cell part, and cell membrane proteins scored with R2 of 0.70, 0.77, and 0.75, respectively. The cell surface protein class contained the least members (N = 70) and had three extreme outliers in form of isoform 2 of ficolin-3, hornerin, and platelet factor 4 variant-1. By excluding these three proteins, the R2 value increased to 0.75. Due to the large number of overlapping proteins showing a good correlation of their intensities with Braga-Lagache et al. data [11], we can conclude that the particles that were isolated from PFP in this study are true and pure cEV. 2.3. Nanoparticle Size Distribution Is Influenced by Transport in PFP The particle size distribution of all samples was measured in order to characterize the potential differences that were conferred by plasma preparation and/or transport method. Visual inspection revealed that most of the donor samples had a particle size distribution peaking in the range of 70–130 nm (Supplementary Figure S3). We note that this is somewhat lower than the 200 nm that was determined in an earlier study [11] using cryo-transmission microscopy imaging of isolated cEV. We also note in Figure S3 that in PFP increased irregularities were seen in PTS compared to C in PFP. Figure 2 presents an overview of features that were extracted from the ZetaView® distributions. Inspection of the AUC per donor showed that we identified consistently less particles in the PPP samples compared to the PFP, with the exception of donor BE351, who generated the two outliers in the PPP AUC plot. Generally, we found more differences between the transportation methods using PFP (upper row of Figure 2) compared to PPP (lower row of Figure 2). In PFP the particle size distribution in PTS compared to C was (figures in brackets are mean ± standard deviation) (i) wider (113 ± 14 vs. 66 ± 10 nm), (ii) less skewed (1.7 ± 0.4 vs. 2.7 ± 0.9 nm), and (iii) peaking at a larger size (116 ± 21 vs. 84 ± 7 nm). In PFP, PTS also had a larger median particle size distribution than C (134 ± 13 vs. 100 ± 5 nm). Again, healthy donor BE351 was an exception with similar medians in both transportation methods. The particle numbers were not significantly different (8 × 1012 ± 2 × 1012 vs. 6 × 1012 ± 3 × 1012), although we observed in PFP a trend towards more particles in PTS compared to C. No significant differences of the ZetaView® metrics were identifiable in the PPP samples. In summary, using a nano-particle detection method, we detected counter-intuitively higher numbers of particles in PFP compared to PPP. We also saw a wider size distribution in PTS compared to C, but this transport effect on the cEV particle distribution is only detectable in PFP. We concluded that non-cEV plasma constituents are a pre-analytical confounding factor for nano-particle detection technology. 2.4. cEV Isolated from PPP Are Contaminated by Platelet, Lymphocyte and Monocyte Remnants A total of 2216 protein groups were identified by mass spectrometry when combining all PFP and PPP samples together; 2144 of them were detected in at least two out of the three technical replicates of at least one donor and were further considered for analysis. In general, the number of quantified protein groups were lower in PFP compared to PPP (Supplementary Table S4). The only exception was donor BE140, for whom we could quantify 209 more proteins in PFP. An overview of the number of protein groups that were found in each protein class and category is shown in Table 1a, while Table 1b gives the numbers per cell type; the complete annotated protein list is in Supplementary File proteinGroups_DE_test.xlsx. We observed that the total number of cell type specific markers is very similar in PFP and in PPP, and so is the number of serum/plasma proteins. However, PPP had a markedly higher number of cellular class proteins (membrane, cell part, cell surface) than PFP. In total, there were 52 protein groups that were exclusively quantified in PFP (unique-to-PFP) and 456 in PPP (unique-to-PPP). We found 12 platelet-specific proteins in the unique-to-PFP and 393 in the unique-to-PPP set, resulting in a much higher ratio for platelet-specific proteins in PPP (393/456 = 86.2%) compared to PFP (12/52 = 23.1%). A further confirmation of the prevalence of platelet remnants in PPP is that four out of the six unique-to-PPP markers were of platelet origin (CD93, CD224, CD244, and CD274) [25], while only one out of the six unique-to-PFP markers was with a platelet annotation (CD81, as listed in Supplementary File proteinGroups_DE_test.xlsx). Additional information regarding the cell origin of differentially abundant cEV was gained by comparing PFP_C, PFP_PTS, PPP_C, and PPP_PTS iTop3 intensities of a choice of proteins that can be regarded as cell-type specific (Table 2 and Figure 3). The top row of Figure 3 shows the markers that are enriched in PFP compared to PPP, the bottom row those that are enriched in PPP compared to PFP; we note that the enrichment in each case is significant for both transport modes. The top row consists of specific markers for erythrocytes (CD233), macrophages (CD14), endothelial cells (HSPG2), and exosomes (CD81). The markers in the second row can be catalogued as platelets (CD41, CD62P), as well as lymphocytes and monocytes (CD40, CD102). We noted no significant intensity difference between PTS and C, neither in PFP nor in PPP; this subject is treated in the next section. Although this was not confirmed by nanoparticle tracking, one can assume that, independently of the mode of transport, larger vesicles that are derived from cell damage were present in PPP, but had been removed in PFP by the second centrifugation step. We can therefore interpret any transport-independent increase in PPP as stemming from cell fragments, while an increase in PFP can be seen as originating from actual cEV. In summary, we can conclude that (i) cEV that are isolated from PPP contain more platelet remnants and lymphocyte/monocyte components compared to PFP, independently of the transport method, and (ii) the increased intensity in PFP of erythrocyte (CD235a), endothelial cell (HSPG2), macrophage (CD14), and the exosomal marker CD81 indicates an enrichment of true cEV proteins in PFP. Overall, our data let us conclude that further analyses should be focused on the purer PFP-derived cEV. 2.5. Non-Consistent Impact of Transport Method on Individual cEV Protein Compositions We had hypothesized that the differential cell damage that is caused by the modes of transports would be detected in the cEV proteome and be interpretable as different formations of cell debris or stimulations of blood cells (especially platelets). However, the differential protein quantification analysis of PFP samples showed, in all donors except BE351, only very few significant differences between PTS and C (Supplementary File proteinGroups_DE_test.xlsx and summarized in Supplementary Table S4). There was just one, albeit different, protein that was enriched in C of BE354 (healthy) and BE363 (secondary AML), and five that were enriched in PTS of BE354; the case of the outlier BE351 is discussed in Supplementary Results. We then looked in more detail at the behavior of the detected CD markers; their relative PTS to C changes (log2 fold change) is shown, per donor, in Supplementary Figure S4. The plots revealed that PTS transport enriched for erythrocyte-derived cEV (CD233) in half of the donor samples, independently of the plasma preparation. No other trend seemed to emerge from any other markers. Interestingly however, the platelet markers CD41 and CD62P appeared well correlated: if one marker was enriched, respectively depleted, for one donor, the other marker was enriched, respectively depleted as well. While very few changes in protein abundance turned out to be significant, there were nonetheless a number of proteins that were not detected in either C (median of 21, range 6–271) or PTS (36.5, 8–584) (Supplementary Table S4). A vast majority of those on-off proteins were detected only once (92% in PTS with a total of 487 on-off proteins, and 73% in C with 575 proteins), and 7% and 24% detected twice, respectively (excluding BE351). The fact that those on-off proteins were randomly occurring between the donors and did not reach statistical significance indicates low intensities, therefore can be considered as being missed by chance during mass spectrometric analysis. As BE351 and BE140 were identified as outliers by particle size distributions and enrichment of proteins in PFP or PTS, we argue (Supplementary Results) that cEV damages in these two cases occurred during blood collection or processing of the sample. For this reason, we decided to remove these samples from the subsequent analysis. In summary, no consistent statistical protein differential expression could be detected in PFP between PTS and C. 2.6. Blood Cell Counts and Nanoparticle Features Do Not Correlate with cEV-Associated Protein Intensities A question of interest is whether cEV-associated protein intensities, aggregated by relevant subclasses or annotations, are able to predict the number of nanoparticles, hemoglobin concentrations, or blood cell counts as determined by Sysmex and ZetaView®. To this purpose, Spearman’s rank correlations were calculated between all these quantities, including transport metrics as well, based on the 10 remaining donor values and focusing exclusively on PFP (Supplementary Table S5). The result, in the form of an unsupervised cluster of correlation coefficients, is shown in Figure 4. Anti-correlations are colored blue, positive correlations range from green to red as the coefficient increases. There are four distinct clusters of various sizes that are discernible in this picture. The largest cluster (top right corner) was formed by cell-derived protein classes and cell markers. Leukocyte and granulocyte cell markers correlated weakly, respectively not at all, with cell part, cell membrane, cell surface, and exosome protein abundances. Platelet markers on the other side showed good to very good correlations with these features, indicating that a large part of cEV were probably of platelet origin. Interestingly, coagulation factors were part of this cluster too; they correlated with platelet markers, suggesting that such factors are indeed associated with platelet-derived cEV. We additionally noted that the cEV-associated protein intensities did not correlate with blood cell count or nanoparticle features. The second largest cluster (lower left to center) was formed by blood cell counts, including hemoglobin (HBG), and surprisingly by apolipoproteins intensities that were determined by our proteomics approach. Apolipoproteins correlated with all cell type counts except granulocytes (Gc) and monocytes (Mc). Erythrocyte (Ec) cell counts correlated weakly with the erythrocyte cell markers that were quantified by proteomics. The small 2 × 2 cluster on the lower left corner consisted of proteins that were annotated with the GO term “blood microparticles” and immunoglobulins. The small size of this cluster comes as a surprise, as one would expect more correlations with “blood microparticles” in this context. The last cluster (middle of lower left quadrant) was formed by a sub-cluster of the transport metrics and a sub-cluster of values that were derived from the nano-particle tracking system. Interestingly, the two sub-clusters were fused via the calculated particle volume, which significantly correlated with the transport metrics VDV, RMS, and TK, while the particle concentration also correlated with the VDV metric. This corroborates somehow our observation that PTS transport does lead to a widening of particle size, hence transport mode can have an influence on particle volume in PFP as stated above (Figure 2, Supplementary Figure S3). Furthermore, particle concentrations showed a correlation with “other plasma proteins”, which included serum albumin and alpha-2-macroglobulin, as two examples with high proteomics determined intensity and of larger molecular weight. Additionally, the original particle volume correlated with the proteomics-derived apolipoprotein intensities and lymphocyte cell counts. While the latter is difficult to explain, the apolipoprotein and other plasma protein correlations do indicate that they may play a role as a confounding factor in nanoparticle tracking measurements as already indicated in above Section 2.3. We also noted that keratin did not correlate with any other features, which supports the notion that keratins may be contaminants rather than products that are released into cEV. In summary, we concluded that a significant proportion of cellular proteins in the cEV fraction of PFP is originating from all blood cell types, but with the exception of erythrocytes there is no general correlation between cell counts in blood and the corresponding proteomics-based cell enumeration in cEV. 2.7. Transport Metric Correlations and Lasso Reveal Specific Effects on cEV Proteome While no statistically significant groups of proteins emerged from the differential analysis between PTS and C, consistent abundance changes correlating with transport metrics can provide insight into the impact of transport on the cEV proteome. Spearman’s rank correlation tests were, therefore, performed between the transport metrics (TK, RMS, and VDV) and all the detected protein intensities. The number of protein groups correlating, or anti-correlating significantly with either one, two or three transport metrics is reported in Table 3. C and PTS results were at first pooled together (C+PTS), then considered separately. We noticed indeed that by considering C and PTS together we had three to five times less correlations than by looking at C or PTS individually, an indication that C and PTS followed distinct patterns. Another observation was that in C a high number of proteins correlated concurrently with all the transport metrics, while in PTS two distinct groups of proteins were seen, one correlating only with VDV and another one with both TK and RMS. The same applied to the negatively correlating proteins, albeit with much fewer proteins involved. We established three ranked lists for GO term enrichment analyses (see the Methods section), containing the proteins correlating (i) in C with all three metrics TK, RMS, and VDV (C_TK/RMS/VDV); (ii) in PTS with both TK and RMS (PTS_TK/RMS); and (iii) in PTS with VDV alone (PTS_VDV). The resulting unique GO term list with the calculated p-values and the numbers of proteins/gene products is given in Table 4. Based on these GO terms, it appeared that increased oscillations associated with C induced an increased level of cEV-associated proteins which regulated the cytoskeleton and were involved in cellular organization (including cell projections and anchoring junctions). An increase of shocks, as recorded by TK and RMS during PTS transport, appeared on the other hand to induce an increased level of cEV from organelle origin, and of cEV that is involved in the metabolism of proteins and nucleic acids. High vibration doses (VDV) during PTS transport seemed to have a specific impact on mitochondrion-associated cellular respiration, together with increased membrane assembly by cell junction proteins. The least absolute shrinkage and selection operator (Lasso) algorithm was applied in order to select EV-associated proteins that could classify the transport type. Although the leave-one-out misclassification error was high (Supplementary Figure S5), the global response (predictor) provided a good separation between C and PTS, in particular with the pure Lasso approach. Between the pure Lasso and the elastic net approaches, we identified altogether 12 proteins that could be used as classifiers (Supplementary Table S6); five had a positive (CFHR1, KRT1, FLOT1, HRG, SERPINC1) and seven a negative (CORO1A, ATP5PF, ST6GAL1, HSPA1A, EFEMP1, OIT3, C4BPB) coefficient. Complement factor H-related protein 1 (CFHR1), histidine-rich glycoprotein (HRG), and antithrombin-III (SERPINC1) are proteins that are adherent to the extracellular matrix and secreted. SERPINC1 is localized in the endoplasmatic lumen and a inhibitor of coagulation, HRG acts as a versatile adaptor protein regulating, amongst others, cell adhesion processes, and CFHR1 is involved in the complement regulation. KRT1 (keratin type II cytoskeletal 1) and FLOT1 (flottilin-1) are associated with cellular membranes, with FLOT1 cooperating in the process of caveolae-like vesicle formation, while KRT1 may regulate the activity of kinases via binding to integrin beta-1. Among the proteins with a negative coefficient, Coronin-1A (CORO1A) is part of the cytoskeleton that is involved in the invagination or protrusion of plasma membrane, and mitochondrial ATP synthase-coupling factor 6 isoform 2 (ATP5J or ATP5PF) is part of the ATP-synthase complex at the inner membrane of mitochondria, respectively. Oncoprotein-induced transcript 3 (OIT3), C4b-binding protein beta isoform 2 (C4BPB), beta-galactosidase alpha-2,6-sialyltranferase 1 (ST6GAL1), and EGF-containing fibulin-like extracellular matrix protein isoform 2 (EFEMP1) are annotated as being secreted, but are also found with the following cellular association: the extracellular matrix for C4BPB and EFEMP1, the Golgi apparatus for ST6GAL1, and the nucleus envelope for OIT3, respectively. The elastic net method retained only three proteins, two of which, ST6GAL1 and SERPINC1, had already been selected by the pure Lasso procedure. The remaining one, HSPA1A (heat shock 70 kDa protein 1A), is a multi-functional protein located at many sites within a cell, namely the cytoplasm, cytoskeleton, microtubule organizing center, and centrosome. CORO1A and FLOT1 were also proteins significantly correlating in C with all transport metrics (C_TK/RMS/VDV) or in PTS with the vibrational dose values (PTS_VDV). In summary, the Lasso proteins directed towards an association of cellular organelles with transport metrics, supporting the correlation analysis between protein intensity and the transport metrics as shown above. 2.8. Protein-Protein Interaction Network Conclusions A STRING network analysis was then performed in order to study the interactions between the proteins of interest that were identified by the correlation analysis and the Lasso algorithm. The Lasso proteins were added to each of the three correlation lists C_TK/RMS/VDV, PTS_TK/RMS, and PTS_VDV and the three completed lists were submitted to the STRING database. A first impression that was given by all three networks was that the Lasso proteins were distributed throughout the network in different clusters. In order to highlight this fact, the three STRING networks, which were based on combined confidence score levels ≥ 0.70, are visualized in Figure 5, Figure 6 and Figure 7 after the application of the GLay community clustering algorithm [26]. When separated in clusters by this algorithm, we noted that apart from SERPINC1 and HRG, who are known interactors, the Lasso proteins were indeed spread out through different community structures of the networks. The Lasso proteins were identified in the figures by a red border, and all the proteins were annotated with a selected minimal GO term list, as explained in the Methods section (color coded as given in Table 4). The clusters often had a dominant set of GO terms/colors, and most clusters integrated at most one, in some cases up to three Lasso proteins. Proteins with no interaction partners were omitted; this was the case for the Lasso proteins OIT3, C4BPB, ST6GAL1, and EFEMP1. CORO1A, CFHR1, and KRT1 only have interactions in the PTS_VDV network, while SERPINC1-HRG, ATP5PF (aka ATP5J), HSPA1A, and FLOT1 were part of all three networks. In the C_TK/RMS/VDV network, SERPINC1-HRG were attached to a cluster dominated by anchoring junction proteins (color 8); ATP5J was part of a small cluster of regulation of cellular component proteins (color 1); HSPA1A sat in a cluster with many establishment of localization in cell (color 3) and nitrogen compound transport proteins (color 4); and FLOT1 and CORO1A were both linked independently to a multi-component cluster of regulation of cellular component organization (color 1), cytoskeleton organization (color 2), actin filament-based process (color 6) and actin cytoskeleton proteins (color 9). In the PTS_TK/RMS network, SERPINC1-HRG were not attached to any further proteins; ATP5J formed a hub between organelle envelope proteins (color 4); HSPA1A was integrated in a cluster that was dominated by organelle organization (color 1); FLOT1 was connected to a single protein annotated to the latter term. In the PTS_VDV network, SERPINC1-HRG as well as FLOT1 were attached to a cluster that was dominated by cell junction proteins (color 6), although the connection by SERPINC1-HRG is made through a non-distinct subunit of intrinsic components of membrane proteins (color 5); CFHR1 was also linked to a predominantly cell junction cluster of which CORO1A was also part of (color 6), and KRT1 to a predominantly intrinsic component of membrane cluster (color 5); ATP5J was associated to clusters of many mitochondrial protein-containing complex (color 8) and cellular respiration proteins (color 3); HSPA1A was included in a cluster that was dominated by cellular localization proteins (color 1). In summary, the Lasso algorithm identified a set of proteins that can be regarded as representing the community clusters that were extracted from the protein-protein interaction networks created from the transport metric correlation analyses. 3. Discussion To the best of our knowledge, only a few studies have investigated the influence of transport on cEV integrity and composition, with important limitations in the applied experimental design. Lacroix et al. [22] attempted to measure the impact of carrier transportation. They studied five modes of transportation: (i) gentle tube conversion, (ii) strong agitation by rotating the tubes for two hours on a wheel, and human carrier transport three floors down in tubes, (iii) unsupported, (iv) horizontally, or (v) vertically fixed in a box. All the tubes were incubated for two hours at room temperature before centrifugation, which is not standard clinical practice and might have introduced a bias in the study results. They measured an increase in annexin-V positive microvesicles (analyzed by flow cytometry) and an increased procoagulant activity in the case of strong agitation and carrier transport, except when the tubes were kept fixed in a vertical position. Gyorgy et al. simulated transport by 50 Hz amplitude on an orbital shaker for one hour at 37 °C [23] and Baek et al. used 450 rpm for one hour at RT [24]. Gyorgy et al. also found increased annexin-V-positive microvesicles by flow cytometry and a significant increase of vesicles by agitation in citrated blood, similar to Lacroix et al. Baek and colleagues used a protein microarray-based analysis platform, which detects exosomes based on binding to several cluster of differentiation markers and annexin-V. They determined a not statistically significant tendency of increased exosome binding with citrated blood after agitation. Overall, all these studies had a very artificial design with long blood incubation times and application of forces and oscillation frequencies that are not occurring during routine clinical transport scenarios. A more comprehensive and clinically appropriate study is presented here. Blood samples from twelve donors, six of which with hematological disorders, were transported from the identical collection point to the wet lab both by either a foot carrier (C) or by the pneumatic tube system (PTS) of the hospital. The transport forces were measured and recorded. Both PPP and PFP plasma types were prepared so as to investigate the impact of transportation on cEV on both plasma preparation methods. Nanoparticles were analyzed by ZetaView® and the protein profile was determined with a semi-quantitative, label-free proteome approach. We discuss in the following some of the caveats of the methods that were considered and the conclusions drawn from the study. The isolation of cEV can be a difficult task, as blood contains other sorts of nanoparticles or large protein complexes which are difficult to separate from the cEV by physical means. For this aim, we chose an earlier established centrifugation protocol [11], where we have shown that several consecutive washing steps in PBS are suitable for cEV isolation and subsequent proteome analysis; the procedure, however, does not eliminate some major plasma protein contaminations such as lipoproteins, coagulation, or complement factors as well as immunoglobulins. Size exclusion chromatography (SEC) has been recommended as an alternative isolation option with good recoveries of EV [7]. We have tested SEC and compared the resulting cEV proteomes with the ones that were achieved with our centrifugation-based method (see Supplementary Methods and Results). We found that SEC did not result in more specific cEV isolation. Furthermore, the reproducibility was also compromised, when compared with our centrifugation protocol (Supplementary Figures S6–S8). For these reasons we used our earlier developed protocol for this study, although one might ask whether it makes any sense to analyze differences that are caused by transport accelerations, when the samples are later subjected to much higher accelerations in the centrifuge. We must remember, however, that centrifugation generates a mostly constant and unidirectional acceleration; this is qualitatively completely different to transportation, where the samples are shaken and hit from any possible direction. Perhaps more importantly, while it can be possible that centrifugation does alter the size distribution and eventually the cEV composition, all the samples experienced the same treatment, hence the impact on cEV integrity during the centrifugations was the same for all the samples. As suspected, the measurement of mechanical forces during transport revealed extremely different patterns depending on the transport mode: C samples were subjected to regular oscillations of moderate amplitude, while PTS samples were subjected to successive shocks of high amplitude. The relatively rough transport of blood specimens through the PTS has been known to affect thrombin activation [21]. Otherwise, only little is known about the molecular impact on other blood components. The gentler transportation by a human courier appears as the more adequate way of transporting blood from bedside into laboratories for subsequent molecular characterization, which was advocated in the past by different laboratories that were interested in the analysis of cEV. One interesting point, however, should be noted: in our study we observed a higher relative variability of the mechanical forces in C compared to PTS (relative standard deviation RSD in Supplementary Tables S2 and S3), meaning that the impact on cEV-associated proteins is relatively more variable in C than in PTS. PTS would, therefore, be the preferable choice in the context of using the cEV proteome composition in biomarker discovery projects. The RSD that was obtained here was of course conditioned by the design of this study, with blood samples all sent along the same path each time. Based on our nanoparticle tracking results, we concluded that strong transport forces occurring during PTS induced the spreading of the cEV size distribution towards both smaller and larger particles, with a shift of the median size to larger values (Figure 2). This observation can be explained by the destruction of some vesicles, which end up forming smaller fragments, together with the concomitant formation of larger aggregates due to the possible activation of thrombin [21]. The significant correlation between all three calculated transport metrics with the particle volume that was derived from nanoparticle tracking measurements underlines that the formation of particle aggregates might be the biological phenomenon that could explain this finding (Figure 4). Other observations were that (i) PTS-induced particle spreading in PFP could not be detected in PPP, (ii) the area under the curve increased in PFP compared with PPP (Figure 2, Supplementary Figure S3), and (iii) there exists a correlation between the original particle concentration that was determined by ZetaView® and apolipoproteins and other plasma proteins (Figure 4). The increase of the measured number of particles when the plasma contaminations are actually partially removed by additional centrifugation indicates that confounding factor(s) in plasma suppress(es) the detectability of nanoparticles (see also Supplementary Figure S8). Particles that were removed by additional centrifugation are most likely lipoproteins and aggregates of plasma proteins. We showed with our label-free proteomics approach that the different modes of transportation do not have an impact on the plasma membrane-embedded cell type-specific cEV-associated proteins, but rather on proteins from subcellular structures, such as organelles, their membranes, and the cytoskeleton. However, the individual patterns were highly heterogeneous and distinct between different donors. The GO term analysis revealed an increase in the cytoskeleton-regulated plasma membrane and cell organization activity that was caused by gentle oscillatory forces during C, in contrast to the release of intracellular vesicles from organelles, including mitochondrial structures, that was caused by the high energy vibration dose during PTS transports. It is generally assumed that mechanical forces induce activation of platelets. One could, therefore, expect that the number and intensity of platelet-derived proteins correlate with the recorded energy impacting on blood during PTS transportation. However, we could not confirm such a trend (Figure 3 and Figure 4, Supplementary Figure S4, and Supplementary File proteinGroups_DE_test.xlsx). Moreover, we did not measure a significant correlation between the cellular protein intensities and the platelet numbers, neither in cEV that were isolated from PFP (Figure 4), and more intriguingly not in PPP (not shown), where more platelet fragments are present (Figure 3). In fact, we could only find a significant correlation between the proteome-based quantification of erythrocyte origin, based on erythrocyte-specific cell surface proteins, and erythrocyte numbers that were measured in whole blood, which might indicate that cell type-specific proteins from cEV do not reflect the concentration of cell types in blood, with the exception of erythrocytes (Figure 4). On the other hand, existing cEV might be destroyed by higher energy that is associated with harsher transport conditions, resulting in a decrease of cellular proteins in the cEV fraction of blood. With the cell origin profiling, we found no generalizable pattern between the blood samples from the twelve donors. We, therefore, conclude that transport-related forces do not have a consistent impact on cEV composition, and that cEV integrity is an individual trait. Additionally, there might be other underlying factors that we do not yet fully understand, as for instance the aggregation of cEV that is induced by freeze-thawing of PFP and during isolation by centrifugation, as observed earlier [11]. 4. Materials and Methods 4.1. Study Design, Study Participants, Blood Sampling and Ethics Approval This is a monocentric, exploratory study using peripheral blood (PB) that was transported either by the hospital pneumatic tubing system (PTS) or a human courier (C). Platelet-poor (PPP) or platelet-free (PFP) plasmas were subsequently prepared and the nanoparticle size distribution and protein composition of the isolated cEV were analyzed for each of the four combinations of plasma type and transport mode PPP_C, PPP_PTS, PFP_C, and PFP_PTS. A total of six hematologically healthy volunteers (three females and three males between age 39 and 56, mean of 46) and six patients with myeloid malignancies (one female and five males between age 31 and 82, mean of 60) were included in this study (Supplementary, Table S1). The PB of each donor was drawn by venipuncture at the same ward in the hospital and collected into four 4.3 mL S-Monovette 3.2% citrated tubes, plus one 4.3 mL S-Monovette EDTA tube (Sarstedt, Germany). Of these, two of the citrated S-Monovettes were immediately sent to the proteomics laboratory through PTS, including a sensor unit that was fixed within the transport tube. The same sensor unit was subsequently attached to a recipient rack holding the two remaining citrated and the EDTA S-Monovettes in an upright position. The same carrier walked the samples with the attached sensors to the proteomics laboratory following the same route as much as possible. Immediately after transportation, the EDTA sample was used for blood cell counting with a Sysmex XN-1000 instrument (Sysmex Suisse AG, Horgen, Switzerland). Clinical data were collected on the Swiss Myelodysplastic Syndromes (MDS) Registry/Biobank platform, where patients with MDS, acute myeloid leukemia (AML), and healthy volunteers were included. MDS patients were risk-stratified according to IPSS-R using a cut-off between 4 and 4.5 points for lower and higher risk disease [27]. 4.2. Determination of Transport Metrics A sensor unit consisting of a Raspberry Pi Zero mini-computer that was equipped with a SenseHat (RPi0-SH) add-on board was used for the acceleration measurements. The acceleration events over time during transport of a sample can be summarized by different metrics. There are three transport metrics that are commonly used in the context of shocks and vibrations that were extracted (detailed in the Methods section of Supplementary Materials): (i) mean Teaker–Kaiser operator (TK), a measure of the mean energy of the signal; (ii) root mean square (RMS), a measure of the mean acceleration; and (iii) vibration dose value (VDV), a quantifier for the sum of vibration events. Further transport features were determined, such as duration, ranges, and distribution of signals. Since the C transports exhibited several periods of regular, sustained oscillations, a period of 0.5–3 min duration was chosen for each C transport and the corresponding signal Fourier-transformed in order to extract the ground frequency. The calculations were performed using base R functions (version 3.6.3) as well as caTools, e1071 and signal packages. There are two sensor limitations that have to be noted. Firstly, the sampling rate of the sensors is such that no frequency higher than 12 Hz can be measured. Tests with a different accelerator of higher sampling rate did not, however, detect substantial Fourier components in the 15–32 Hz range (not shown). Secondly, the peak values that were measured during PTS were at the upper limit of the detection power of the accelerometer, and therefore, higher accelerations may have occurred. 4.3. Reagents, Software and Data All the reagents were of analytical purity grade. Dithiothreitol (DTT), iodoacetamide (IAA), and LC-MS grade acetonitrile were purchased from Fluka (Buchs, Switzerland); urea, trifluoroacetic acid (TFA), and formic acid from Merck (Zug, Switzerland); TRIS and acetone from Sigma (Buchs, Switzerland); and sequencing-grade endoproteinase LysC and porcine trypsin from Promega (Dübendorf, Switzerland). Phosphate-buffered saline solution was from Gibco (Life Technologies, Zug, Switzerland) and sterile filtered through 0.2 μm pore size membrane (Millipore, Zug, Switzerland). Normalization, imputation, statistical tests, and Spearman rank correlations were calculated using base R with following additional packages: vsn, MSnbase, and limma. All protein expression data are provided in the Supplementary File proteinGroups_DE_test.xlsx. Lasso feature selection was performed using the R package glmnet (version 4.0-2). Community clustering was calculated by the GLay app [26] from Cytoscape [28]. Graphics art were designed in Photoshop using figures that were produced with R, Excel, and Cytoscape. 4.4. Preparation of Platelet-Poor (PPP) and Platelet-Free Plasmas (PFP) We prepared plasma samples as PPP and PFP from both citrated S-Monovettes that were transported either by C or PTS. All the samples were centrifuged in a swing out rotor (Labofuge 400R function line) at 1500 g for 10 min at room temperature to separate the plasma from the cell fraction. PPP was carefully extracted, without disturbing the cellular fraction, leaving 0.5 cm of liquid above the buffy coat. The collected PPPs from the two S-Monovettes deriving from the same transport type were mixed, aliquots of 400 μL were taken, and the remaining volume was distributed in 2mL tubes with a volume of 1.8mL per tube and further centrifuged for 2 min at 16,000g (Eppendorf, centrifuge 5415 R). After this second centrifugation step, the PFP was carefully removed, leaving 50–100 μL back in the tube, mixed, and dispersed into 400 μL aliquots. The PPP and PFP aliquots were frozen at −80 °C until further use. 4.5. Nanoparticle Tracking Analysis Nanoparticle tracking was performed on a ZetaView® (Particle Metrix, Inning am Ammersee, Germany) instrument using an embedded laser (488 nm) and a CMOS camera with the following settings: autofocus on, camera sensitivity at 85, shutter 100, scattering intensity 4, and cell temperature at 25 °C. PPP and PFP were diluted in sterile filtered PBS using a 0.22 μm membrane. Several dilutions were made targeting at least 1000 particle traces. The tracing videos were analyzed by ZetaView® software (version 8.05.05 SP2) limiting the particle size range to 10–1000 nm with a minimum particle brightness of 30. Particle counts and concentrations were averaged from several dilution measurements and the original particle volume was calculated by the particle volume that was corrected by the dilution factor used to dilute the plasma samples before nanoparticle tracking. All distribution features (such as mean particle size, distribution width etc.) were calculated using base R functions and the caTools package on the binned particle concentration curve. The total amount of particles was defined as the area under the curve (AUC) by applying the trapezoidal integration rule. 4.6. Isolation of cEV and Protein Digestion Isolation of cEV and protein digestion were performed as previously reported [11]. Briefly, PFP or PPP aliquots of 400 μL were slowly defrosted on ice, then centrifuged for 40 min at 16,000× g and 20 °C followed by three washing cycles of the resulting pellets with 250 uL PBS and centrifugation for 20 min at 16,000× g and 20 °C. The final pellets containing cEVs were dissolved in 10 μL 8 M urea/100 mM Tris*HCl pH 8.0, reduced with DTT, alkylated with IAA, and double digested by a combination of LysC and trypsin protease (100 ng each). From each donor, both transport types, as well as PFP and PPP samples, we isolated cEVs from three different aliquots (technical replicates) resulting in a total of 144 cEV samples for mass spectrometry analysis. 4.7. Mass Spectrometry and Label-Free Protein Profiling Shotgun nLC-MS2 was used in a data-dependent acquisition (DDA) mode. Peptide sequencing was performed on an Orbitrap Fusion LUMOS mass spectrometer that was coupled with a Dionex Ultimate 3000 nano-UPLC system (ThermoFischer Scientific, Reinach, Switzerland) as described elsewhere [29]. Each protein digest was run two times by loading 5 μL onto the pre-column. The mass spectrometry data of all runs (288 files) were processed with MaxQuant/Andromeda (version 1.6.6.0) searching against the concatenated forward and reversed SwissProt human protein database (release 2019_07) with the following parameters: Mass error tolerance for parent ions of 10 ppm and fragment ions of 0.4 Da, strict trypsin cleavage mode with 3 missed cleavages allowed, static carbamidomethylation on Cys, variable oxidation on Met and acetylation of protein N-termini. The match-between-runs option in MaxQuant was allowed only within PFP, respectively PPP samples, by allocating non-consecutive fraction numbers for PFP and PPP. Otherwise, the default MaxQuant settings were used. Identification results were filtered on the peptide spectrum match, peptide, and protein identification level to a 1% false discovery rate (FDR). In addition, only the protein groups that were identified with at least two distinct peptides were accepted. All mass spectrometry data are available via ProteomeXchange (identifier PXD033117). 4.8. Protein Classification The identified proteins were manually classified using information that was retrieved from the Uniprot database in the following manner: transmembrane or intramembrane annotations in conjunction with subcellular location were considered first; if not conclusive or not present, GO:CC terms were considered next, then GO:BP terms; if still no determining terms could be extracted, then either tissue specificity, keywords, or protein description were used instead. All but three proteins could be attributed to either one of the following protein classes: (1) association with cell membranes, (2) being part of the intracellular compartment of cells (organelles and cytoplasm), (3) attached to the cell surface (equivalent to extracellular matrix), or (4) serum or plasma, respectively. Proteins of the latter class were furthermore ascribed, whenever possible, to either one of the serum or blood plasma factor apolipoprotein, coagulation, complement, or immunoglobulin. The protein origin was, therefore, either cellular or serum/plasma, and a protein category was given directly by the class for classes 1–3, and by the serum/blood plasma factor for class 4. The cluster of differentiation (CD) annotation was used as a surrogate for the cell origin of cEV for proteins of the cell membrane category. Annotations were decided according to the Human Cell Differentiation Molecules organization (hcdm.org), and the normalized mRNA expression levels in single cells from the human protein atlas (www.proteinatlas.org) accessed on 26 December 2021. Basement membrane-specific heparan sulfate proteoglycan core protein (HSPG2) was added as an endothelial cell-specific marker. A special focus in our study was on platelets, as they are regarded as the most vulnerable cells to mechanical forces. The platelet proteome that was published by Burkhart et al. [25] was, therefore, used to annotate separately the possible origin of cEVs from platelets. An additional set of annotations were keratin (potential contaminant), blood microparticle, and exosome GO annotation. All annotations are provided in the Supplementary File proteinGroups_DE_test.xlsx. 4.9. Differential Protein Abundance Testing Label-free protein abundances were calculated from the sum of the intensities of the three most intense peptides of each protein group (Top3 approach), after summing two injections (mass spectrometry replicates) and normalizing the peptide intensities by variance stabilization (vsn R package). PFP and PPP plasma types were considered as different experimental sets and normalized independently for most of the study, except when comparisons were made between the two preparation methods, in which case all the samples were normalized together. The missing peptide intensities were imputed in the following manner: if at least two values were missing in one group of technical replicates, then these values were replaced by drawing random numbers from a Gaussian distribution of width 0.3 × sample standard deviation and centered at the sample distribution mean minus 2.5 × sample standard deviation; otherwise the missing value was replaced by the method of maximum likelihood estimation (MLE, MSnbase R package). The imputed Top3 protein intensities were called iTop3 in all accompanying documents. Differential abundance tests between each patient’s C and PTS samples of same plasma type were performed using empirical Bayes statistics (limma R package) on log-2 transformed iTop3 intensities, provided the protein groups were detected at least in one sample triplicate. Protein abundance differences were reported as the difference between the log2-transformed iTop3 intensities (log2fc), and adjusted p-values accounting for multiple testing were calculated using the FDR-controlled Benjamini and Hochberg correction (R base function p.adjust). Significance of the differential expression was defined by the combined criteria of |log2fc| ≥ 1 and adjusted p-value ≤ 0.05, such that the adjusted p-value must be zero for |log2fc| = 1 and 0.05 for asymptotically large fold changes. The curvature of the significance curve in between the extrema was determined by the overall variance. In order to overcome the stochasticity that was introduced by imputation, the imputation and significance test were repeated 20 times. Only those protein groups that were consistently reported as significantly differentially expressed throughout the imputation cycles were accepted as truly significant. The protein groups that were reported by MaxQuant as being identified only by site were excluded from statistical testing and downstream data evaluation. Contaminants of non-human origin were subsequently discarded. For comparisons between PPP and PFP, the post-hoc ANOVA tests were performed [30] with the Tukey’s honestly significant difference test using R base function TukeyHSD. 4.10. Functional Analysis of Proteins For functional analyses, we collapsed the protein groups representing the same gene product (proteins annotated with same gene name in Uniprot) into one entry by summing their corresponding iTop3 intensities, provided there was at least one detection in the replicate group. The median of the log2 of the aggregated intensities of the three technical replicates was then used in the rest of the analysis and, where it could be determined, a corresponding median intensity value for each donor, mode of transport, and plasma type. Furthermore, an intensity that was representative of each protein subclass was calculated as the average of the log2 iTop3 intensities of the protein members. The same was done for the additional set of annotations. Spearman’s rank correlations were calculated between a set of features including these representative intensities and transport metrics, blood count, and ZetaView® measurements. The correlation coefficient rho was recorded only if the test p-value was ≤ 0.05, otherwise it was set to 0; the matrix of resulting correlation coefficients was used to perform an unsupervised clustering analysis. Spearman rank correlations between the gene product intensities and the transport metrics TK, RMS, and VDV were then calculated separately for the PFP_C and PFP_PTS groups. A correlation coefficient rho was returned only if there were at least three gene product intensity values that were available in this group and considered significant if p-value ≤ 0.05. For each plasma type/transport group and transport metric, the gene products were ranked by 1 minus p-value, multiplied by the sign of the rho correlation, so that the proteins highly correlating with the transport metric were at the top of the list, and those most strongly anti-correlating at the bottom. For those lists where more than one transport metric was included, the lowest transport metric rank value was used for each gene product. The ranked lists were submitted to a statistical enrichment test of the gene ontology (GO) terms biological process and cellular component using the online PANTHER classification system [31], applying a 1% FDR control for multiple testing correction. The GO term lists were filtered by preferring those terms with the smallest p-values and highest number of significantly correlating gene products. Furthermore, only GO terms that were unique to one enrichment test were kept. To account for redundancy, we filtered the GO terms to the smallest possible list explaining all the involved gene products. With the resulting gene product lists, protein interaction network analyses were performed on the STRING database (string-db.org). 4.11. Defining EV-Associated Protein Transport Markers by Feature Selection Method The least absolute shrinkage and selection operator (Lasso) algorithm was applied [32] in order to determine the selection of cEV proteins whose intensities discriminate the best between PTS and C. The calculations were performed in R using the glmnet package [33], both with an elastic net penalty of 0 (pure Lasso), in order to find a shortest selection, as well as with 0.5 (elastic net), in order to account to some extent for correlated variables. The optimal overall strength of the coefficient penalty, the parameter lambda, was determined by the “leave-one-out” cross validation method, whereby the model was calculated on n-1 samples, and the miss-classification error on the remaining sample. The process is repeated n times, and the optimized lambda was determined from the minimum mean error. The response function aimed to take either the value of 0 for C, or 1 for PTS. The starting data set was, as for the functional analysis, all gene products with their corresponding median intensity per donor, and transport mode; here however, only the complete data (no missing intensities anywhere) were considered, so that a total of 349 gene products were retained for the analysis. 5. Conclusions We can summarize that mechanical forces occurring during human carrier transport might affect the composition of cEV proteome profile by influencing plasma membrane reorganization and release of EV by an ectosomal pathway from blood cells. In contrast, PTS rather activated endosomal pathways due to the transport metric correlations with proteins of organelle origin. However, these processes might be biased by the cEV composition and stability of each person, which seems to be a consequence of health condition, other individual traits, and pre-analytical impacts during blood sample procurement. Acknowledgments We would like to thank the staff at the Department of Hematology and Central Hematology Laboratory, Inselspital, Bern for their help in collecting blood samples as well as the healthy participants and MDS patients providing them. A special thanks goes to Paola Luciani and Cristina Zivko from the Department of Chemistry and Biochemistry at the University of Bern for providing access to their ZetaView® instrument and the generous assistance setting up and operating the instrument. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094515/s1. References [11,34] are cited in the Supplementary Materials. Click here for additional data file. Author Contributions A.-C.U.: Designing experiments, carrying out experiments, data interpretation, manuscript writing; A.M.-D.: Carrying out experiments; M.J.: Data interpretation with machine learning algorithm; N.B. (Natasha Buchs): Carrying out experiments; S.B.-L.: Carrying out experiments, data acquisition; J.B.: Coordination of blood sampling, collecting data; J.J.: Coordination of blood sampling, collecting data; N.B. (Nicolas Bonadies): Provided infrastructure for collection of patient samples and clinical data, designing experiments, manuscript writing; M.H.: Designing experiments, data interpretation, manuscript writing. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The collection of human blood samples with clinical data was approved by the local ethical committee (2016-01917; 2017-02299; 2016-01052; 2017-00699). Informed Consent Statement Informed consent was obtained from all subjects that were involved in this study. Data Availability Statement The proteomics data (consisting of 288 LC-MS/MS files) have been deposited to the ProteomeXchange Consortium via the PRIDE [35] partner repository with the dataset identifier PXD033117. Conflicts of Interest All authors declare no conflict of interest for this study. Potentially perceived conflicts of interests according to the definitions and terms of the International Committee of Medical Journal Editors are for NBo: Alexion: research funding to institution; Amgen: financial support for travel; Astellas: research funding to institution; Celgene/BMS: financial support for travel, research funding to institution; consultancy honoraria; Janssen: financial support for travel; Keros: consultancy honoraria; Novartis: financial support for travel, research funding to institution, consultancy honoraria; Roche: financial support for travel, research funding to institution; Sandoz: research funding to institution; Servier: research funding to institution; Takeda: research funding to institution. Figure 1 Boxplot representation of the transport metrics. The 12 C values were compared to the 12 PTS values for each transport metrics TK (a), RMS (b), and VDV (c) with C on the left and PTS on the right of each graph. The mean of Teaker–Kaiser operator for C ranged from 0.008 to 0.032 g2. All three metrics showed highly significant differences between C and PTS with Welch’s t-test p-values of 3.5 × 10−9 for mean of Teaker–Kaiser operator, 1.5 × 10−13 for root mean square, and 1.2 × 10−13 for vibration dose value, respectively. Figure 2 Extracted features from ZetaView® nanoparticle size distributions for PFP (upper row) and PPP (lower row) samples. The samples are further separated by transport mode C (left boxes) or PTS (right boxes). From left to right the following features were extracted from the ZetaView® size distribution: area under the curve (AUC), standard deviation of the particle size distribution, skewness of the size distribution, the size at maximum intensity, and the median particle size. The number above each boxplot is the p-value of the Welch’s t−test between the C and PTS values. Figure 3 Abundance comparison of cell-type-specific proteins. Each boxplot shows, on the same scale, the spread of log2 iTop3 intensities of cell-type-specific proteins (indicated above the plot), for, from left to right, PFP_C (light red), PFP_PTS (dark red), PPP_C (light blue), and PPP_PTS (dark blue). Segments within the plots indicate when the one-way ANOVA post hoc pair-wise tests between the groups were significant (p ≤ 0.01). Protein intensities from all the samples have been normalized together. The top row of plots presents cells that were enriched in PFP with erythrocytes represented by CD233, macrophages by CD14, endothelial cells by HSPG2, and CD81 being a more ubiquitous marker that is generally considered to represent exosomes. The cell-types that are represented in the second row of plots is platelets with CD41 and CD62P, and lymphocytes and monocytes with CD40 and CD102, respectively. Figure 4 Unsupervised clustering of Spearman rank correlation rho values that were calculated from a variety of quantified features using PFP samples. The following features that were measured for each donor went into the correlation analysis: ZetaView® nanoparticle tracking numbers (original particle concentration, non-corrected particle concentration and particle volume), blood cell counts of monocytes (Mc), lymphocytes (Ly), leukocytes (Lc), granulocytes (Gc), platelets (Tc), erythrocytes (Ec), hemoglobin concentration (HGB), transport metrics (VDV, RMS, TK), and label-free proteomics-determined protein category and cell type-specific marker intensities. The resulting correlation coefficients with p-value ≤ 0.05 are color-coded as shown on top of figure. All values are given in Supplementary Table S5. Figure 5 STRING protein-protein interaction network composed of proteins that were significantly correlating with all C transport metrics (C_TK/RMS/VDV) and the Lasso proteins. Edges represent a STRING combined score ≥ 0.7; they are drawn thick within community clusters, and thin across community clusters. The Lasso proteins are marked with a red border (gray otherwise). Node colors at the bottom right refer to GO terms given in Table 4, with 1–6 standing for biological process and 7–12 cellular component. Figure 6 STRING protein-protein interaction network composed of proteins that were significantly correlating with the PTS metrics TK and RMS (PTS_TK/RMS) and the Lasso proteins. Edges represent a STRING combined score ≥ 0.7; they are drawn thick within community clusters, and thin across community clusters. Lasso proteins are marked with a red border (gray otherwise). Node colors at the bottom right refer to GO terms given in Table 4, with 1–3 standing for biological process and 4–6 cellular component. Figure 7 STRING protein-protein interaction network composed of proteins that were significantly correlating with the PTS transport metric VDV (PTS_VDV) and the Lasso proteins. Edges represent a STRING combined score ≥ 0.7; they are drawn thick within community clusters, and thin across community clusters. Lasso proteins are marked with a red border (gray otherwise). Node colors at the bottom right refer to GO terms given in Table 4, with 1–4 standing for biological process and 5–9 cellular component. ijms-23-04515-t001_Table 1 Table 1 Number of protein groups quantified in all cEV isolates. (a) Classification by origin and category Protein Origin Protein Category Combined Data PFP PPP Plasma C PTS C PTS unique-to-PFP unique-to-PPP Cellular Cell membrane 772 561 570 746 750 16 179 Cell part 1030 723 752 991 992 23 248 Cell surface 138 106 110 129 129 7 26 Total cellular 1940 1390 1432 1866 1871 46 453 Serum/plasma Apolipoprotein 19 19 19 18 19 0 0 Coagulation factor 23 23 23 23 23 0 0 Complement factor 26 26 26 26 26 0 0 Immunoglobulin 75 73 74 69 71 4 1 Other 58 56 56 56 56 2 2 Total serum/plasma 201 197 198 192 195 6 3 Unknown 3 3 3 3 3 0 0 Total 2144 1590 1633 2061 2069 52 456 (b) Cell type specific proteins (markers) *. Cell Origin Combined Data PFP PPP Plasma C PTS C PTS unique-to-PFP unique-to-PPP T Cell 41 37 38 37 38 3 3 B Cell 36 32 33 32 33 3 3 NK cell 30 27 28 27 28 2 2 Dendritic cell 18 16 16 15 16 2 2 Monoc./Macroph. 50 44 45 44 46 4 5 Granulocyte 35 31 32 31 33 2 3 Platelet 34 33 33 34 34 0 1 Erythrocyte 13 13 13 12 12 1 0 Endothial cell 39 36 36 35 35 4 3 Stem/Progenitor 32 30 30 28 28 4 2 Total markers 70 63 64 62 64 6 6 * Most proteins have more than one cell type specificity. ijms-23-04515-t002_Table 2 Table 2 cEV-associated cell-type specific proteins that were used to assess cell-type specific damage by way of transport. CD GN nTPM, Cell Type * Functional Annotation Excerpt from uniport.org CD14 CD14 Mp = 653 Mc = 285 Mediates the innate immune response to bacterial lipopolysaccharide (LPS) CD40 CD40 Mc = 242 Bc = 148 Ec = 62 Transduces TRAF6- and MAP3K8-mediated signals that activate ERK in Mp and Bc, leading to induction of immunoglobulin secretion CD41 ITGA2B Pl Gc = 65 Ec = 2 Part of receptor for fibronectin, fibrinogen, plasminogen, prothrombin, thrombospondin and vitronectin CD62P SELP Pl Ec = 52 Tc = 9 Gc = 8 Mediates the interaction of activated Ec or Pl with Lc CD81 CD81 Ec = 345 Mp = 278 Dc = 267 Tc = 137 Bc = 88 Gc = 82 Structural component of specialized membrane microdomains known as tetraspanin-enriched microdomains, which act as platforms for receptor clustering and signaling. CD102 ICAM2 Nk = 114 Ec = 109 Tc = 60 Mp = 57 Bc = 48 Mc = 26 Mediates adhesive interactions important for antigen-specific immune response, NK-cell mediated clearance, lymphocyte recirculation, and other cellular interactions important for immune response and surveillance CD233 SLC4A1 Ery = 1623 Major integral membrane glycoprotein of the erythrocyte membrane HSPG2 HSPG2 Ec = 323 Role in vascularization, basement membrane localization * Normalized mRNA expression levels in single cells (nTPM) as published on the Human Protein Atlas organization website accessed on 26 December 2021 (https://www.proteinatlas.org/) in combination with information from the Human Cell Differentiation Molecules organization (hcdm.org). Bc = B-cells, Dc = dendritic cells, Ec = Endothelial/Epithelial cells, Ery = Erythrocytes, Gc = Granulocytes, Mc = Monocytes, Mp = Macrophages, Nk = natural killer cells, Pl = Platelets, Tc = T-cells. ijms-23-04515-t003_Table 3 Table 3 Correlations of protein group intensities with transport metrics. The numbers of protein groups significantly correlating (p ≤ 0.05) with transport metrics are reported on the left for positive correlation, and on the right for anti-correlation. C and PTS were both pooled (C + PTS) and considered separately. Positive Correlations Negative Correlations Transport Metrics C + PTS C PTS C + PTS C PTS TK only 14 43 31 1 3 2 RMS only 1 3 15 0 2 3 VDV only 10 7 158 2 1 20 TK + RMS 12 12 144 5 4 16 RMS + VDV 0 6 0 1 2 0 TK + VDV 8 36 32 0 4 0 TK + RMS + VDV 27 181 4 2 11 0 Total TK 61 202 194 8 19 20 Total RMS 40 202 163 8 19 19 Total VDV 45 230 194 5 18 20 ijms-23-04515-t004_Table 4 Table 4 Significantly enriched GO terms in correlating transport metric lists. The network color code refers to Figure 5, Figure 6 and Figure 7. Network Color Biological Process p-Value # of Genes Network Color Cellular Component p-Value # of Genes C_TK/RMS/VDV 1 regulation of cellular component organization 1.3 × 10−6 82 7 plasma membrane bounded cell projection 9.8 × 10−7 63 2 cytoskeleton organization 3.8 × 10−7 52 8 anchoring junction 2.1 × 10−10 59 3 establishment of localization in cell 3.7 × 10−8 51 9 actin cytoskeleton 1.2 × 10−9 44 4 nitrogen compound transport 1.2 × 10−4 40 10 myofibril 2.6 × 10−7 19 5 cell cycle 9.5 × 10−5 23 11 chromosome 1.1 × 10−4 15 6 actin filament-based process 2.2 × 10−7 43 12 cluster of actin-based cell projections 1.9 × 10−4 12 PTS_TK/RMS 1 organelle organization 5.0 × 10−5 56 4 organelle envelope 6.7 × 10−5 31 2 nucleobase-containing compound metabolic process 6.9 × 10−5 22 5 ficolin-1-rich granule 1.2 × 10−4 16 3 proteasomal protein catabolic process 3.5 × 10−5 9 6 endoplasmic reticulum protein-containing complex 1.0 × 10−4 11 PTS_VDV 1 cellular localization 2.8 × 10−5 63 5 intrinsic component of membrane 8.3 × 10−6 76 2 intracellular signal transduction 4.8 × 10−5 37 6 cell junction 7.9 × 10−5 64 3 cellular respiration 2.2 × 10−6 19 7 organelle sub compartment 2.5 × 10−4 35 4 mitochondrial transmembrane transport 5.6 × 10−5 12 8 mitochondrial protein-containing complex 3.9 × 10−8 21 9 catalytic complex 2.9 × 10−4 19 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Han L. Xu J. Xu Q. Zhang B. Lam E.W.-F. Sun Y. Extracellular vesicles in the tumor microenvironment: Therapeutic resistance, clinical biomarkers, and targeting strategies Med. Res. Rev. 2017 37 1318 1349 10.1002/med.21453 28586517 2. Xu R. Rai A. Chen M.S. Suwakulsiri W. Greening D.W. Simpson R.J. Extracellular vesicles in cancer—Implications for future improvements in cancer care Nat. Rev. Clin. Oncol. 2018 15 617 638 10.1038/s41571-018-0036-9 29795272 3. Rutter B. Innes R.W. Extracellular vesicles as key mediators of plant-microbe interactions Curr. Opin. Plant Biol. 2018 44 16 22 10.1016/j.pbi.2018.01.008 29452903 4. Hosseinkhani B. Kuypers S. van den Akker N.M.S. Molin D.G.M. Michiels L. Extracellular Vesicles Work as a Functional Inflammatory Mediator Between Vascular Endothelial Cells and Immune Cells Front. Immunol. 2018 9 1789 10.3389/fimmu.2018.01789 30131806 5. Zarà M. Guidetti G.F. Camera M. Canobbio I. Amadio P. Torti M. Tremoli E. Barbieri S.S. Biology and Role of Extracellular Vesicles (EVs) in the Pathogenesis of Thrombosis Int. J. Mol. Sci. 2019 20 2840 10.3390/ijms20112840 31212641 6. Sabin K. Kikyo N. Microvesicles as mediators of tissue regeneration Transl. Res. 2014 163 286 295 10.1016/j.trsl.2013.10.005 24231336 7. Coumans F.A.W. Brisson A.R. Buzas E.I. Dignat-George F. Drees E.E.E. El-Andaloussi S. Emanueli C. Gasecka A. Hendrix A. Hill A.F. Methodological Guidelines to Study Extracellular Vesicles Circ. Res. 2017 120 1632 1648 10.1161/CIRCRESAHA.117.309417 28495994 8. Clayton A. Buschmann D. Byrd J.B. Carter D.R.F. Cheng L. Compton C. Daaboul G. Devitt A. Falcon-Perez J.M. Gardiner C. Summary of the ISEV workshop on extracellular vesicles as disease biomarkers, held in Birmingham, UK, during December 2017 J. Extracell. Vesicles 2018 7 11 10.1080/20013078.2018.1473707 9. Shah R. Patel T. Freedman J.E. Circulating Extracellular Vesicles in Human Disease N. Engl. J. Med. 2018 379 958 966 10.1056/NEJMra1704286 30184457 10. Al Kaabi A. Traupe T. Stutz M. Buchs N. Heller M. Cause or Effect of Arteriogenesis: Compositional Alterations of Microparticles from CAD Patients Undergoing External Counterpulsation Therapy PLoS ONE 2012 7 e46822 10.1371/journal.pone.0046822 23056467 11. Braga-Lagache S. Buchs N. Iacovache M.-I. Zuber B. Jackson C.B. Heller M. Robust Label-free, Quantitative Profiling of Circulating Plasma Microparticle (MP) Associated Proteins Mol. Cell. Proteom. 2016 15 3640 3652 10.1074/mcp.M116.060491 27738094 12. Magnette A. Chatelain M. Chatelain B. Ten Cate H. Mullier F. Pre-analytical issues in the haemostasis laboratory: Guidance for the clinical laboratories Thromb. J. 2016 14 49 10.1186/s12959-016-0123-z 27999475 13. Le Quellec S. Paris M. Nougier C. Sobas F. Rugeri L. Girard S. Bordet J.C. Negrier C. Dargaud Y. Pre-analytical effects of pneumatic tube system transport on routine haematology and coagulation tests, global coagulation assays and platelet function assays Thromb. Res. 2017 153 7 13 10.1016/j.thromres.2016.12.022 28292729 14. Ando H. Nieminen K. Toppila E. Starck J. Ishitake T. Effect of impulse vibration on red blood cells in vitro Scand. J. Work Environ. Health 2005 31 286 290 10.5271/sjweh.884 16161711 15. Monteiro MO B. Pinto N.D. Marin P.J. Santos S.D. Bernardo M. Effect on osmotic fragility of red blood cells of whole blood submitted to vibrations in an oscillating platform Afr. J. Biotechnol. 2011 10 14197 14202 16. Monteiro M.D.O.B. Sá-Caputo D.D.C.D. Carmo F.S.D. Bernardo R.M. Pacheco R. Arnobio A. Guimarães C.A.S. Bernardo L.C. Santos-Filho S.D. Asad N.R. Effects of Short-Period Whole-Body Vibration of 20 Hz on Selected Blood Biomarkers in Wistar Rats Chin. J. Physiol. 2015 58 211 218 10.4077/CJP.2015.BAD303 26211644 17. Kocak F.E. Yontem M. Yucel O. Cilo M. Genc O. Meral A. The effects of transport by pneumatic tube system on blood cell count, erythrocyte sedimentation and coagulation tests Biochem. Med. 2013 23 206 210 10.11613/BM.2013.024 18. Phelan M.P. Reineks E.Z. Hustey F.M. Berriochoa J.P. Podolsky S.R. Meldon S. Schold J.D. Chamberlin J. Procop G.W. Does Pneumatic Tube System Transport Contribute to Hemolysis in ED Blood Samples? West. J. Emerg. Med. 2016 17 557 560 10.5811/westjem.2016.6.29948 27625719 19. Dyszkiewicz-Korpanty A. Quinton R. Yassine J. Sarode R. The effect of a pneumatic tube transport system on PFA-100 trade mark closure time and whole blood platelet aggregation J. Thromb. Haemost. 2004 2 354 356 10.1111/j.1538-7836.2004.0584e.x 14996012 20. Hubner U. Bockel-Frohnhofer N. Hummel B. Geisel J. The effect of a pneumatic tube transport system on platelet aggregation using optical aggregometry and the PFA-100 Clin. Lab. 2010 56 59 64 20380360 21. Lance M.D. Kuiper G.J. Sloep M. Spronk H.M. van Oerle R. ten Cate H. Marcus M.A. Henskens Y.M. The effects of pneumatic tube system transport on ROTEM analysis and contact activation assessed by thrombin generation test Thromb. Res. 2012 130 e147 e150 10.1016/j.thromres.2012.05.002 22633532 22. Lacroix R. Judicone C. Poncelet P. Robert S. Arnaud L. Sampol J. Dignat-George F. Impact of pre-analytical parameters on the measurement of circulating microparticles: Towards standardization of protocol J. Thromb. Haemost. 2012 10 437 446 10.1111/j.1538-7836.2011.04610.x 22212198 23. György B. Pálóczi K. Kovács A. Barabás E. Bekő G. Várnai K. Pállinger É. Szabó-Taylor K. Szabó T.G. Kiss A.A. Improved circulating microparticle analysis in acid-citrate dextrose (ACD) anticoagulant tube Thromb. Res. 2014 133 285 292 10.1016/j.thromres.2013.11.010 24360116 24. Bæk R. Søndergaard E.K. Varming K. Jørgensen M.M. The impact of various preanalytical treatments on the phenotype of small extracellular vesicles in blood analyzed by protein microarray J. Immunol. Methods 2016 438 11 20 10.1016/j.jim.2016.08.007 27568281 25. Burkhart J.M. Vaudel M. Gambaryan S. Radau S. Walter U. Martens L. Geiger J. Sickmann A. Zahedi R.P. The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways Blood 2012 120 e73 e82 10.1182/blood-2012-04-416594 22869793 26. Su G. Kuchinsky A. Morris J.H. States D.J. Meng F. GLay: Community structure analysis of biological networks Bioinformatics 2010 26 3135 3137 10.1093/bioinformatics/btq596 21123224 27. Greenberg P.L. Stone R.M. Al-Kali A. Barta S.K. Bejar R. Bennett J.M. Carraway H. De Castro C.M. Deeg H.J. DeZern A.E. Myelodysplastic Syndromes, Version 2.2017, NCCN Clinical Practice Guidelines in Oncology J. Natl. Compr. Cancer Netw. 2016 15 60 87 10.6004/jnccn.2017.0007 28. Shannon P. Markiel A. Ozier O. Baliga N.S. Wang J.T. Ramage D. Amin N. Schwikowski B. Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks Genome Res. 2003 13 2498 2504 10.1101/gr.1239303 14597658 29. Buchs N. Braga-Lagache S. Uldry A.C. Brodard J. Debonneville C. Reynard J.S. Heller M. Absolute Quantification of Grapevine Red Blotch Virus in Grapevine Leaf and Petiole Tissues by Proteomics Front. Plant Sci. 2018 9 17 10.3389/fpls.2018.01735 29449849 30. Muller J. Braga S. Uldry A.C. Heller M. Muller N. Comparative proteomics of three Giardia lamblia strains: Investigation of antigenic variation in the post-genomic era Parasitology 2020 147 1008 1018 10.1017/S0031182020000657 32338227 31. Mi H. Muruganujan A. Huang X. Ebert D. Mills C. Guo X. Thomas P.D. Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0) Nat. Protoc. 2019 14 703 721 10.1038/s41596-019-0128-8 30804569 32. Tibshirani R. Regression Shrinkage and Selection Via the Lasso J. R. Stat. Soc. Ser. B 1996 58 267 288 10.1111/j.2517-6161.1996.tb02080.x 33. Friedman J.H.H.T. Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent J. Stat. Softw. 2010 33 1 22 10.18637/jss.v033.i01 20808728 34. Greganova E. Heller M. Butikofer P. A structural domain mediates attachment of ethanolamine phosphoglycerol to eukaryotic elongation factor 1A in Trypanosoma brucei PLoS ONE 2010 5 e9486 10.1371/journal.pone.0009486 20209157 35. Vizcaino J.A. Csordas A. del-Toro N. Dianes J.A. Griss J. Lavidas I. Mayer G. Perez-Riverol Y. Reisinger F. Ternent T. 2016 update of the PRIDE database and its related tools Nucleic Acids Res. 2016 44 D447 D456 10.1093/nar/gkv1145 26527722

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094616 ijms-23-04616 Article The P2X7 Receptor Promotes Colorectal Inflammation and Tumorigenesis by Modulating Gut Microbiota and the Inflammasome Bernardazzi Claudio 12 Castelo-Branco Morgana Teixeira Lima 23 Pêgo Beatriz 2 Ribeiro Beatriz Elias 2 Rosas Siane Lopes Bittencourt 2 https://orcid.org/0000-0001-7888-5249 Santana Patrícia Teixeira 2 https://orcid.org/0000-0003-2747-1702 Machado João Carlos 4 Leal Camille 5 Thompson Fabiano 5 https://orcid.org/0000-0002-7318-0204 Coutinho-Silva Robson 6 https://orcid.org/0000-0002-3647-7324 de Souza Heitor Siffert Pereira 27* Serena Carolina Academic Editor 1 Department of Pediatrics, University of Arizona, Tucson, AZ 85724, USA; claudiobma1@gmail.com 2 Department of Clinical Medicine, Federal University of Rio de Janeiro, Rio de Janeiro 21941-913, Brazil; morgcb@gmail.com (M.T.L.C.-B.); biapdamasceno@gmail.com (B.P.); bakerribeiro@gmail.com (B.E.R.); sianeros@gmail.com (S.L.B.R.); pattsant@gmail.com (P.T.S.) 3 Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil 4 Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil; jcm@peb.ufrj.br 5 Institute of Biology, Federal University of Rio de Janeiro, Rio de Janeiro 21941-599, Brazil; camille.victoria@gmail.com (C.L.); fabianothompson1@gmail.com (F.T.) 6 Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil; rcsilva@biof.ufrj.br 7 D’Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro 30, Botafogo, Rio de Janeiro 22281-100, Brazil * Correspondence: heitor.souza@gmail.com; Tel.: +55-21-39382669 21 4 2022 5 2022 23 9 461628 3 2022 14 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Background: Given the role of the P2X7 receptor (P2X7R) in inflammatory bowel diseases (IBD), we investigated its role in the development and progression of colitis-associated colorectal cancer (CA-CRC). Methods: CA-CRC was induced in P2X7R+/+ and P2X7R−/− mice with azoxymethane (AOM) combined with dextran sodium sulfate (DSS). In a therapeutic protocol, P2X7R+/+ mice were treated with a P2X7R-selective inhibitor (A740003). Mice were evaluated with follow-up video endoscopy with endoluminal ultrasound biomicroscopy. Colon tissue was analyzed for histological changes, densities of immune cells, expression of transcription factors, cytokines, genes, DNA methylation, and microbiome composition of fecal samples by sequencing for 16S rRNA. Results: The P2X7R+/+ mice displayed more ulcers, tumors, and greater wall thickness, than the P2X7R−/− and the P2X7R+/+ mice treated with A740003. The P2X7R+/+ mice showed increased accumulation of immune cells, production of proinflammatory cytokines, activation of intracellular signaling pathways, and upregulation of NLRP3 and NLRP12 genes, stabilized after the P2X7R-blockade. Microbial changes were observed in the P2X7R−/− and P2X7R+/+-induced mice, partially reversed by the A740003 treatment. Conclusions: Regulatory mechanisms activated downstream of the P2X7R in combination with signals from a dysbiotic microbiota result in the activation of intracellular signaling pathways and the inflammasome, amplifying the inflammatory response and promoting CA-CRC development. colitis-associated colorectal cancer gut microbiota inflammatory bowel disease P2X7R purinergic signaling ==== Body pmc1. Introduction One of the most feared complications resulting from chronic colonic inflammation in ulcerative colitis (UC) and Crohn’s disease (CD), collectively known as inflammatory bowel disease (IBD), is the development of colitis-associated colorectal cancer (CA-CRC). Although improvements in endoscopic surveillance protocols have allowed the earlier detection of dysplasia and subsequent CA-CRC [1], the diagnosis and management of dysplasia is still a major challenge in patients with IBD [2]. In addition to the increased risk in patients with UC [3] and with colonic CD [4], some studies have indicated that patients with CA-CRC have inferior survival compared to patients with sporadic CRC [5]. While the development of sporadic CRC is well established and characterized by histological and genetic changes known as the adenoma-carcinoma sequence, CA-CRC develops through a different sequence. Chronic inflammation of IBD induces mutations and creates a regenerative background resulting in a distinctive selective pressure that may lead to CA-CRC [6]. Although mutations leading to CRC are similar in IBD and in the sporadic type, the order by which they occur appears to be different [7]. These observations indicate the need to elucidate the pathogenesis of CA-CRC, including the molecular and immunologic mechanisms underlying the chronic inflammatory process of IBD, to guide the development of new therapies to reach deep remission and lower the risk of CA-CRC. Extracellular adenosine triphosphate (ATP) released from tissue injury resulting from infection or cellular stress is regarded as a damage-associated molecular pattern (DAMP) capable of regulating several physiological cell functions through the interaction with the purinoreceptor P2X7 (P2X7R), an extracellular ATP-gated cation channel expressed on both epithelial and immune effector cells [8]. The modulatory effect of the ATP-P2X7R pathway in T regulatory cell function [9], the production of proinflammatory cytokines [10], the regulation of cell death [11], the elimination of infectious pathogens [12,13,14], and inflammasome activation [15,16] indicates its role in the pathogenesis of autoimmune diseases [17,18] and chronic inflammatory disorders such as IBD [19]. Given the already mentioned information regarding the ATP-P2X7R pathway and our previous findings demonstrating site-specific modulation of P2X7 in intestinal epithelial cells [11], we hypothesized that purinergic signaling through P2X7R plays a critical role in the regulation of chronic intestinal inflammation and consequently may be involved in the pathogenesis of CA-CRC. Therefore, in the present study, we investigated the potential therapeutic effect of P2X7R blockade in an experimental model of CA-CRC. 2. Results 2.1. P2X7R Blockade Attenuated Inflammation and Tumorigenesis and Reduced Morbidity and Mortality in the Mouse Model of AOM/DSS-Induced CA-CRC Video Colonoscopy Associated with eUBM To follow up on the development of CA-CRC in vivo, we periodically examined the mice by video colonoscopy during the intervals of DSS administration. As in previous works from our group [20], colonoscopy was associated with eUBM, a device that utilizes a high-frequency ultrasound system that allows the acquisition of detailed cross-sectional images (Supplementary Figure S1). After the first cycle of DSS (3rd week), most animals presented mucosal edema and an abnormal vascular pattern. Ultrasonic images revealed a practically normal wall thickness and a clear distinction between the hyperechoic and hypoechoic layers. After the second cycle of DSS (6th week), all P2X7R+/+ wild-type mice displayed mucosal granularity and friability, and most of them also had ulcers and bleeding. The P2X7R+/+ wild-type mice treated with A740003 did not present the entire range of abnormalities observed in the untreated animals. However, in some cases, the colonic mucosa showed friability, and edema was also corroborated by the ultrasonic images showing focal increases in the wall thickness. Similar changes were observed among the AOM/DSS-induced P2X7R−/− animals, while no change was detected among the P2X7R−/− control animals. After the third cycle of DSS (week 9), the colonic abnormalities were strongly aggravated in the AOM/DSS-treated P2X7R+/+ animals. The colonic mucosa showed advanced inflammatory changes but also the formation of polyps. The ultrasonic images revealed wall thickening of the hyper- and hypoechoic layers, lacking a clear distinction among each other. Some of the induced wild-type mice treated with A740003 showed mucosal edema, vascular changes, and discrete elevations in the colonic mucosa without clear inflammatory abnormalities; however, the well-defined layers under the ultrasonic images were preserved, indicating superficial changes only. Most P2X7R−/− mice showed a normal colon during the whole experiment, but in some cases, mild inflammatory changes could be detected at the end of the protocol; however, there were no ulcers or polyps (Figure 1). 2.2. Survival, Body Weight, Colon Length, and Number of Tumors As shown in Figure 1C, the AOM/DSS-induced P2X7R+/+ mice treated with A740003 had a longer survival than the AOM/DSS-induced P2X7R+/+ mice during the experimental period. Body weight significantly decreased at the end of week 4 (Day 28) in the AOM/DSS-induced P2X7R+/+ mice compared to the control P2X7R+/+ mice. Upon treatment termination at the end of week 8 (Day 56), body weight changed even more in the AOM/DSS-induced P2X7R+/+ mice than in the A740003-treated and control P2X7R+/+ mice (Figure 1D). The colon length shortened more in the AOM/DSS-induced P2X7R+/+ mouse group than in the control group and in the A740003-treated mouse group (Figure 1E,F). Furthermore, the number of polyps/tumors was significantly greater in the AOM/DSS-treated P2X7R+/+ mice than in the A740003-treated mice. The control P2X7R+/+ mice and the P2X7R−/− mice with or without AOM/DSS induction presented no tumors (Figure 1G). Polypoid tumors were found in the middle and distal colon in the AOM/DSS-treated mice (80% of the animals); however, A740003 treatment significantly prevented the development of tumors in the AOM/DSS-treated mice (33% of the animals). Multiple tumors occurred in 41.6% of the AOM/DSS-induced P2X7R+/+ mice, whereas the A740003-treated group had only single tumors, whenever present. Upon histological evaluation, we found no metastatic tumors in other tissues, such as the liver or spleen, of the AOM/DSS-treated mice (data not shown). In the AOM/DSS-treated mice, 90% of the lesions were adenomas, and 10% were adenocarcinomas. In contrast, in the A740003-treated animals, no adenocarcinomas were detected, with increases in lesions that were either hyperplastic polyps (50%) or adenomas (50%). 2.3. P2X7R Blockade Attenuated Colonic Injury in the AOM/DSS-Treated Mice Histopathologic Assessment of Tissue Samples The histological assessment confirmed significantly increased inflammation and the development of hyperplastic changes, including tumors, in the AOM/DSS-induced P2X7R+/+ mice compared with the control mice and with the AOM/DSS-induced mice treated with A740003. However, no tumor formation and practically no inflammatory response were observed in the AOM/DSS-induced P2X7R−/− mice (Figure 2). These data suggest that the P2X7R−/− mice and the P2X7R+/+ mice treated with the P2X7R antagonist (A740003) develop less inflammation and consequently less hyperplasia and tumors following AOM/DSS induction. Analysis of the density of collagen fibers in the colon tissue revealed enhancement of fibrosis in the AOM/DSS-induced P2X7R+/+ mice compared with the control mice and with the AOM/DSS-induced mice treated with A740003. In the epithelial compartment of the colon, the density of mucous-secreting goblet cells was significantly lower in the AOM/DSS-induced P2X7R+/+ mouse samples than in the samples from the normal control group or the AOM/DSS-induced mice treated with A740003. No significant changes were detected between the P2X7−/− groups (Supplementary Figure S2). 2.4. Regulation of Cell Proliferation and Apoptosis in the Colon To determine the role of cell proliferation and cell death in this model, we stained cells with an anti-Ki67 antibody by immunohistochemistry and used a TUNEL assay to label apoptotic cells. Colon samples from nondysplastic inflamed areas of the AOM/DSS-induced P2X7R+/+ mice showed significantly lower rates of Ki67-positive cells than those of the control group. Regarding apoptosis, colon samples from nondysplastic inflamed areas of the AOM/DSS-induced P2X7R+/+ mice showed significantly higher rates than those of the control group and the AOM/DSS-induced mice treated with A740003. In contrast to the inflamed areas, the analysis of samples from tumor areas revealed an opposite result, with less apoptosis and more Ki67-positive proliferating cells, as expected (Figure 3). 2.5. P2X7R Blockade Attenuated the Accumulation of Immune Cells and the Production of Inflammatory Cytokines in the Colon 2.5.1. Accumulation of Immune Cells in the Colon To characterize the different cell populations present in the colonic lamina propria, we labeled CD4 and CD11b cells by immunohistochemistry. The inflammatory cell infiltrates observed within the lamina propria of nondysplastic inflamed areas of the AOM/DSS-induced P2X7R+/+ mice showed an increased concentration of both CD4- and CD11b-positive cells. Treatment with A740003 significantly attenuated the accumulation of CD4- and CD11b-positive cells in the AOM/DSS-induced mice. In contrast to the inflamed areas, the analysis of samples from tumor areas revealed sparsely distributed CD4- and CD11b-positive cells (Supplementary Figure S3). 2.5.2. Production of Inflammatory Cytokines in the Colon Next, we investigated whether P2X7R could affect the production of inflammatory mediators potentially involved in the inflammatory and hyperplastic changes associated with AOM/DSS induction. For this purpose, we used a mouse Th1/Th2/Th17 cytokine kit based on bead array technology to simultaneously detect IFN-gamma, TNF, IL-2, IL-4, IL-6, IL-10, and IL-17A. The analysis of the supernatants obtained from colon explant cultures revealed that the concentrations of TNF-alpha, IL-17A, and IL-6 were significantly increased in the samples from the P2X7R+/+ AOM/DSS-treated mice compared to the samples from the controls and the A74003-treated mice. However, the concentration of IL-10 was significantly lower in the P2X7R+/+ AOM/DSS-treated mice than in the control mice. The P2X7R−/− samples did not show any significant changes. Only the quantifiable results were analyzed (Figure 4). 2.6. P2X7R Blockade Modulated the Expression of Genes Related to Inflammation and Cancer in the Colon To investigate the possible mechanisms by which AOM/DSS might regulate the inflammatory response and dysplastic changes in the colon, we examined the mRNA expression of genes potentially involved in tissue remodeling and inflammatory and protumorigenic processes. The results showed an overall tendency for upregulation of the expression of all target genes studied in the P2X7+/+ AOM/DSS-induced mice. However, significant changes compared to the controls and the A74003-treated mice were observed only for the NLRP3, NLRP12, MAPK14, and IL-1beta genes (Figure 5). Other genes analyzed in this study, including AKT-1, BCL-2, TP-53, CXCR3, STAT-3, and CASP-1, did not show significant changes among the experimental groups (Supplementary Figure S4). 2.7. P2X7R Blockade Reduced the Activation of Intracellular Pathways in the Colon To reinforce the findings obtained with qPCR, we also investigated the NF-kappa B and phosphorylated ERK MAP kinase intracellular signaling pathways at the protein level by immunohistochemistry. NF-kappa B and p-ERK displayed similar expression patterns and tissue distributions. NF-kappa B and p-ERK were present in the epithelium and the lamina propria mononuclear cells at significantly higher densities in the nondysplastic inflamed areas of the P2X7+/+ AOM/DSS-induced mice than those of the controls and the A740003-treated mice. However, the tumor areas showed only a limited number of NF-kappa B- and p-ERK-positive cells (Figure 6). 2.8. The Expression of P2X7R and Beta-Catenin in the Colon Wnt/beta-catenin signaling, another critical pathway in the development of CRC, was analyzed by immunohistochemistry. Beta-catenin was detected among lamina propria mononuclear cells and in the epithelial compartment, particularly toward the bottom of the crypts in the nondysplastic inflamed colon, compared to strong staining of the dysplastic epithelium in tumors. Although the semiquantitative analysis showed that the overall expression of beta-catenin did not differ significantly between the groups, they were clearly qualitatively distinct. While beta-catenin distribution showed a diffuse pattern in the nondysplastic inflamed colon, in the tumor, in addition to cytosolic localization, strong nuclear staining was observed in the dysplastic epithelium. However, parallel staining with anti-P2X7R antibody revealed significantly higher expression in the lamina propria and the epithelial compartment of nondysplastic inflamed tissue than in the epithelium of the tumors, which showed faint coloration (Supplementary Figure S5). 2.9. P2X7R Blockade Changed the Methylation Patterns of Specific Genes in the Colon To evaluate the DNA methylation status of CRC-related genes in the experimental groups, we assessed the promoter regions of p53, p16, MLH1, Gja9, Igfbp3, and APC in a semiquantitative fashion. Of all target genes studied, we identified differential methylation only in the Gja9 gene, which was more pronounced in the P2X7+/+ AOM/DSS-induced mice (Supplementary Figure S6). 2.10. P2X7R Blockade Modulated the Microbiota Associated with Inflammation and Tumors in the Colon High-throughput sequencing produced 4,335,464 16S rRNA sequences (185 nt length) after Deblur quality control clean-up from 36 samples (P2X7R+/+ control 8797 ± 1889; P2X7R+/+ AOM/DSS 110,042 ± 15,288; A740003-treated P2X7R+/+ AOM/DSS 122,288 ± 26,596; P2X7R−/− control 166,007 ± 52,738; P2X7R−/− AOM/DSS 173,031 ± 68,893; values represent the mean ± SD). The reads were delineated into 493 operational taxonomy units (OTUs). Estimators of alpha diversity were calculated according to the Shannon index. Although no significant difference was detected among the groups, we observed a trend toward a decreased diversity in the AOM/DSS-induced P2X7R+/+ group (Figure 7A). Principal coordinate analysis (PCoA) revealed a clear clustering of P2X7R−/− (triangles) away from P2X7R+/+ samples (circles). Among the P2X7R+/+ samples, unique structural changes in the fecal microbiota appear to have occurred after P2X7R blockade with A740003, as most samples shifted away from AOM/DSS-induced P2X7R+/+ (highlighted with colored oval forms). However, the P2X7R+/+ controls were distributed unevenly, revealing the heterogeneity within that group, which might have prevented a more comprehensive and accurate analysis. In summary, we found a dissimilarity in the fecal microbiota between the A740003-treated and untreated AOM/DSS-induced P2X7R+/+ mice and between the P2X7R+/+ and P2X7−/− controls (Figure 7B). The Venn diagram showed that only a minority of OTUs were preserved and shared among groups, with a greater superimposition observed among the AOM/DSS-induced P2X7R+/+ (53%) and P2X7−/− (44%) groups (Figure 7C). As expected, the fecal microbiota was mainly composed of Bacteroidetes and Firmicutes in all groups, followed by less abundant Proteobacteria and Epsilonbacteraeota, among others (Supplementary Figures S7 and S8A). At the phylum level, compared to the P2X7+/+ control group, the AOM/DSS-induced P2X7R+/+ group presented a trend toward a higher relative abundance of Firmicutes (4–20% vs. 13–31%) and Tenericutes (0–0.4% vs. 0.1–1.4%), whereas Fusobacterium was exclusively identified in the AOM/DSS-induced P2X7R+/+ group (Figure 7D). Furthermore, we observed that bacteria belonging to the Mycoplasma and Mucispirillum genera (of the Tenericutes and Deferribacteres phyla, respectively) had a higher relative abundance in the AOM/DSS-induced P2X7R+/+ group than in the P2X7+/+ control group. In contrast, compared to the P2X7R+/+ control group, the P2X7R−/− group presented a trend toward a higher relative abundance of Cyanobacteria (0–1.9% vs. 0.3–4.3%) and Spirochaetes (0–0 vs. 0.1–0.4) (Figure 7D, and Supplementary Figure S7). The Firmicutes:Bacteroidetes ratio was not significantly different among the groups (Supplementary Figure S8B). 3. Discussion In this study, we investigated whether purinergic signaling through P2X7R could play a role in the development of tumors in a murine model of CA-CRC. The results showed that chemical P2X7R blockade markedly abrogated the development of tumors, whereas the P2X7R−/− mice did not develop CA-CRC. In particular, we demonstrated that prophylactic treatment with the P2X7R antagonist stabilized mucosal cell turnover and substantially attenuated morphologic and molecular abnormalities underlying the chronic inflammatory process of the colon. Moreover, we detected subtle changes in intestinal microbial components and the methylation patterns of genes related to CRC. Current data regarding the role of P2X7R in human CRC derive basically from descriptive studies associating the increased expression of P2X7R in tumors with the poorer survival and prognosis of patients [21,22,23]. Previous studies investigating the potential role of the P2X7R in tumorigenesis, provided contradictory results. However, only a few studies have investigated the role of the P2X7R in CRC. For example, in an animal model of tumor growth using B16 melanoma and CT26 colon carcinoma cells, the absence of the P2X7R correlated with increased growth, metastasis, and an inefficient antitumor immune response [24]. In another study, anticancer chemotherapy was shown to be less responsive against tumors established in P2X7R-deficient animals [25]. On the other hand, Sougiannis et al., recently showed that emodin, an anthraquinone with antitumorigenic properties, was effective against the onset of genetic and AOM/DSS-induced CRC, via the reduction of M2-like protumorigenic macrophages [26]. These data appear to corroborate the results from a previous study demonstrating that emodin could inhibit carcinogenesis-associated intestinal inflammation, preventing the development of CA-CRC in an AOM/DSS model [27]. The effect of P2X7R activation by ATP in CRC in vitro with cancer cell lines and in vivo using xenograft tumor models has been investigated recently. In one of the studies, the investigators concluded that ATP-P2X7R activation promotes the migration and invasion of CRC cells, possibly through the activation of the STAT3 pathway [28]. In another study, Zhang et al. demonstrated that A438079, another selective PX7R antagonist, inhibited cell proliferation, migration, and invasion, but promoted cell death in the CRC cell lines, HCT-116 and SW620, and in SW620 cell xenografted BALB/c nude mice [29]. Taken together, these data appear to support our findings on the influence of P2X7R in the development of CRC. However, we utilized a model based on a chronic inflammatory background to mimic human CA-CRC. In fact, upon tissue collection on week eight, after the third cycle of DSS, we continued to detect inflammation and demonstrated that most components involved in the chronic inflammatory process, including the overexpression of P2X7R, were predominantly located in the nondysplastic surroundings of the tumors. This finding appears to be consistent with the idea that high concentrations of ATP, within the inflammatory process and in close vicinity of inflammation, open large pores that release inflammatory mediators and can result in apoptotic cell death. In contrast, low concentrations of ATP, distant from inflammatory hotspots, open cation channels that may result in cell proliferation [30]. However, in contrast to our findings, in a previous study using the AOM/DSS model including P2X7R−/− mice and treating animals with the selective PX7R antagonists A438079 and A740003, the investigators achieved opposing results. More tumors were detected among the P2X7R−/− mice and the animals treated with P2X7R antagonists, including a large number of adenocarcinomas [31]. It is possible that differences in the protocols, such as therapeutic versus prophylactic intervention, and animal housing and care, for example, may have influenced the different outcomes. However, the diametrical opposing results of the two studies led us to search for another more reasonable explanation. In fact, our analysis of the intestinal microbiota appears to have shed important light on the critical role of microbial signaling and its presence in the inflammatory process and in tumorigenesis in the CA-CRC model. Hence, it is likely that differential profiles of the intestinal microbiota in the experimental groups constituting the two studies might contribute to the distinct outcomes but render data difficult to compare directly. Moreover, these discrepant results may indicate the likely need for previous conditioning of animals and possibly also analyzing the microbiota before experimental induction. Similar to previous publications using the AOM/DSS model [32,33], this study showed that animals developing tumors invariably displayed inflammatory changes in the colon and lost more weight, had shorter colon lengths, and showed overall reduced survival. In particular, the endoscopic follow-up carried out in this study showed that most tumors developed after the third cycle of DSS in the P2X7R+/+, but not in the P2X7R−/− mice, and at significantly lower rates in the P2X7R+/+-induced mice treated with the selective blockade of P2X7R. Similar to previous studies reporting the effects of P2X7R activation in the intestine, the nondysplastic areas of the colon of the AOM/DSS-induced P2X7R+/+ animals displayed characteristic chronic inflammatory changes combined with epithelial cell loss [34], including mucous-producing cells, increased fibrogenesis [35], and accumulation of mononuclear cells, with increased production of Th1 and Th17 proinflammatory cytokines [36,37], decreased production of IL-10 [9], and upregulation of IL-1 beta expression [19,31]. A prolonged imbalance of cytokines and chemokines within the intestinal mucosa is thought to favor CA-CRC development by various mechanisms affecting epithelial cells. For example, signals from TNF-alpha, IL-17, and IL-6 appear to foster a tumor-supportive microenvironment, probably via mitogenic changes [38], which can impact epithelial cell migration and survival programs [39]. In addition, TNF-alpha, IL-17, and IL-6 have also been shown to induce tumor growth through NF-kappa B and STAT3 activation [40,41]. Regarding the activation of intracellular signaling pathways, this study investigated several molecules usually involved in tumorigenesis, including CRC development, such as STAT3, p53, Akt1, and Bcl2. Nevertheless, the analysis showed that the levels of NF-kappa B and mitogen-activated protein kinases (MAPK) are upregulated in the colon of the P2X7R+/+ AOM/DSS-induced mice. NF-kappa B represents a well-established proinflammatory and protumor pathway both in humans and in experimental IBD [42,43] and was increased in the intestinal mucosa of the mice developing tumors in this study. In the AOM/DSS mouse model, the canonical NF-kappa B pathway was previously shown to promote tumorigenesis through the stimulation of myeloid cells, mediating the production of IL-1-beta and proinflammatory cytokines, including TNF-alpha, and acting on epithelial cells by inhibiting apoptosis [44]. In addition, NF-kappa B signaling enhanced Wnt activation and promoted dedifferentiation of non-stem cells, which developed a tumorigenic capacity [45]. Concerning MAP kinases, we demonstrated that the colon of the P2X7R+/+ AOM/DSS-induced mice shows upregulation of MAPK14 expression and overexpression of extracellular signal-regulated kinase (ERK). The upregulation of both MAPK14 and ERK expression was blocked in the P2X7R−/− mice and in the mice treated with the P2X7R antagonist. ERK is a downstream protein belonging to the Ras-Raf-MEK-MAPK/ERK signaling pathway and commonly shows upregulated expression in tumorigenesis [46,47]. Similar to our results, previous data have shown that the AOM/DSS experimental model enhances the production of ERK, which is involved in cell proliferation [48]. Characteristically, NF-kappa B and phosphorylated-ERK were strongly expressed in lamina propria mononuclear cells in inflamed areas and epithelial cells of the tumors. Our data suggest that purinergic signaling through P2X7R may modulate the activation of intracellular signaling pathways involved in the inflammatory and tumorigenic response in the intestinal mucosa. Although the participation of the inflammasome in the pathogenesis of IBD and CRC has been investigated in recent years, its intricate mechanisms have resulted in some contradictory results in both humans and experimental models [49]. Regarding NLR molecules involved in the inflammasome activation investigated here, NLRP6 and NLRC4 mRNA levels did not differ among the experimental groups, while upregulated NLRP12 expression paralleled that of NLRP3 in the P2X7R+/+ AOM/DSS-induced mice. Interestingly, the cytosolic recognition of microbial components resulting in NLRP3 activation was promoted by pannexin-1 in the presence of ATP [50]. Taken together, these findings strongly suggest that P2X7R associated with pannexin-1 and the consequent downstream NLRP3 activation are implicated in the pathogenesis of AOM/DSS-mediated inflammation and tumor development. Although dysfunction of NLRP12 has been reported in some inflammatory disorders [51], in vitro studies demonstrated that NLRP12 could inhibit canonical and noncanonical NF-kappa B pathways [52]. Moreover, mice deficient in NLRP12 were more susceptible to colitis and colorectal tumorigenesis [53]. Although caspase-1 expression was not significantly upregulated in the current study, IL-1 beta, a downstream molecule critically involved in inflammasome activation, showed strongly upregulated expression. Nonetheless, the differential upregulation of NLR expression observed at the end of the protocol may not reflect the dynamic changes that might have occurred during the experiment and may represent a limitation of this study. The mechanism by which DSS induces colitis in mice is still poorly understood; however, studies have identified several factors, including changes in the intestinal microbiota [54], an effect partially prevented by treatment with antibiotics [55]. In particular, DSS-induced colitis has been shown to favor an increase in the abundance of Enterobacteriaceae, Bacteroidaceae, and Clostridium spp. [56]. In contrast to our results, most AOM/DSS model investigations identified an increased relative abundance of Proteobacteria, Deferribacteres, Verrucomicrobia, and Bacteroides and a decreased abundance of Prevotella [57]. In a previous study, the chemical blockade of P2X7R reversed the taxonomic alterations of Bacteroidetes and Verrucomicrobia as well as Akkermansia in ethanol-fed mice [58]. This finding appears to be in accordance with our results, at least in part, showing dissimilarity of gut microbiota between the A740003-treated and untreated AOM/DSS-induced P2X7R+/+ mice and between the P2X7R+/+ and P2X7−/− controls. In addition, bacteria belonging to the Mycoplasma and Mucispirillum genera had a higher relative abundance, whereas Fusobacterium was exclusively identified in the AOM/DSS-induced P2X7R+/+ group. Similar to our results, the phylum Tenericutes was positively associated with CA-CRC incidence and tumor burden in the AOM/DSS experimental model [55]. Among the Tenericutes, the genus Mycoplasma has also been recently associated with CRC, suggesting a potential role in colonic tumorigenesis [59]. Corroborating our findings, Mucispirillum has also been associated with the development of CA-CRC [60]. Here, we show for the first time, to the best of our knowledge, a trend toward a higher relative abundance of Cyanobacteria and Spirochaetes among the P2X7R−/− samples, suggesting a possible protective role against the development of CA-CRC. However, the lack of statistical significance and the only partial restoration with the chemical antagonist of P2X7R suggest that bacterial changes observed in this study may represent a secondary phenomenon and are not tumorigenic per se in isolation. In fact, the results appear to reinforce the fundamental role of the ATP/P2X7R pathway in the underlying context of tumor development in this model. Selective hypermethylation of the promoter regions of tumor suppressor genes with hypomethylation of the tumor genome has been previously reported as a common epigenetic modification in CRC. Moreover, mutations involved in the pathogenesis of CRC are usually regarded as similar to those underlying CA-CRC, but the order in which they arise is rather different [7]. In this study, our results involving p53, p16, MLH1, Igfbp3, and APC were less consistent than those of Gja9 and did not allow clear differentiation among the experimental groups. In turn, Gja9 was shown to be relatively hypermethylated in the AOM/DSS-induced P2X7R+/+ mice. Gja9 belongs to the connexin family of proteins that constitute gap junctions, often compromised in cancers, including CRC [61]. However, the overexpression of beta-catenin shown here is compatible with the aberrant Wnt/beta-catenin signaling pathway possibly triggered by the loss of APC function [62]. The relatively low expression of P2X7R in the dysplastic area, where beta-catenin expression is high, with a strong presence in the nuclei, suggests that P2X7R may not participate directly in the growth of the dysplastic epithelium. In addition, the neighboring inflammation with an active ATP/P2X7R pathway might have fueled tumor growth with the additional or alternative participation of the activated NF kappa-B pathway [63]. Taken together, these data highlight the complexity of tumor development in the context of colitis, particularly amplified by the dynamic nature of interactions and epigenetic modifications during the process. Therefore, it is likely that data regarding gene methylation in this study should be interpreted with caution, not only due to the semiquantitative nature of the experiments but also because our protocol was restricted to a transversal analysis at the end of the protocol when the most critical interactions and transformations might have occurred, and cumulative effects cannot be distinguished. Although this study presents a successful approach for the development of CA-CRC and its association with the ATP/P2X7R pathway, important limitations should be acknowledged. First, the number of experiments and animals per experiment was relatively small, mainly owing to technical difficulties regarding the care of animals and the long-term follow-up. However, the overall results were broadly consistent and showed several significant differences. Therefore, the successful data generated in this study should serve, at least in part, as a pilot for further investigations. Future studies on the subject should also consider other dosages and other P2X7R antagonists, different animal models, and protocols, including a collection of samples throughout the study, to evaluate the dynamic changes that might occur in the parameters analyzed, particularly in the microbiota. Finally, antibiotics could provide additional relevant information on the exact role of the microbiota in the model and possibly confirm its potential synergism with the ATP/P2X7R pathway for the activation of the inflammasome and the full development of colitis and CA-CRC. 4. Materials and Methods 4.1. Ethics Statement The ethics statement regarding animal experiments is provided in the Supplementary Methods. 4.2. Animal Model and P2X7R-Blockade Age-matched male 6-week-old (18–20 g) C57BL/6 P2X7+/+ and C57BL/6 P2X7−/− mice (originally from The Jackson Laboratory, Bar Harbor, ME, USA) were maintained under specific pathogen-free conditions on a 14-h/10-h light and dark cycle in a temperature-controlled room (20–25 °C) with a relative humidity of 44–55%. After an acclimation period of 1 week, mice were randomly assigned to 1 of 5 groups of 3–5 animals each (in 5 experiments). CA-CRC was induced with a single intraperitoneal (i.p.) injection of 12.5 mg/kg azoxymethane (AOM) (Sigma Aldrich, St. Louis, MO, USA). After seven days, the animals were given drinking water containing 2.5% dextran sodium sulfate (DSS) salt, 40–50 kDa (Spectrum, Gardena, CA, USA), for seven days in three cycles, with two intervals of 14 days each (between cycles 1 and 2 and between cycles 2 and 3) with drinking water without DSS. In a therapeutic protocol, P2X7R+/+ mice were treated with intraperitoneal injections of A-740003 (Tocris Bioscience, Bristol, UK), a P2X7R-selective antagonist, 1 h prior to the second and third cycles of DSS. The mice were weighed weekly and euthanized between Days 56 and 57 by inhalation of carbon dioxide (CO2). Additional details on the care of animals and study protocols are presented in Supplementary Methods [64,65,66]. 4.3. Colonoscopy Assessment The details regarding the colonoscopy assessment are provided in Supplementary Methods [20,67]. 4.4. Histological Analysis The distal 2 cm of the colon was divided into portions to perform all the experimental procedures. Colon samples were fixed in 40 g/L formaldehyde saline, embedded in paraffin, and 5 μm sections were then stained with H&E, periodic acid of Schiff (PAS), and phosphomolybdic acid picrosirius red dye and examined microscopically by two independent observers. Details regarding the histologic assessment are provided in Supplementary Methods [33,68]. 4.5. Immunohistochemistry and Assessment of Apoptosis The details regarding immunohistochemistry and evaluation of apoptosis are provided in the Supplementary Methods. 4.6. Quantitative Assessment of Colon Sections The details of the quantitative analysis of tissue sections are described in Supplementary Methods. 4.7. Assessment of Cytokines Cytokine concentrations in 24 h culture supernatants of colon explants were measured via flow cytometry using the BD™ Cytometric Bead Array (CBA) Mouse Th1/Th2/Th17 Cytokine Kit (BD Biosciences, San Jose, CA, USA). 4.8. Analysis of Messenger RNA Expression Gene expression was assessed by real-time reverse-transcription (RT) polymerase chain reaction (PCR). The procedures are described in the Supplementary Methods. 4.9. Methylation Studies The details regarding the methylation studies are described in Supplementary Methods [69]. 4.10. Microbiome Composition Details regarding the sequencing of the variable V3–V4 regions of the 16S rRNA gene are described in Supplementary Methods [70,71,72,73,74,75,76,77]. 4.11. Statistical Analysis The details regarding the statistical analysis are provided in the Supplementary Methods. 5. Conclusions Taken together, these findings support the participation of the ATP-P2X7R pathway in establishing an inflammatory microenvironment favoring the development of CA-CRC. These regulatory mechanisms activated downstream of P2X7R, in combination with signals from a dysbiotic microbiota, probably contribute to the maintenance and amplification of the inflammatory response resulting from the crosstalk of converging intracellular signaling pathways and the inflammasome. In addition, these mechanisms conveyed by P2X7R activation may be involved in the disruption of immune surveillance against tumor cells. Thus, we speculate that targeting P2X7R in IBD may constitute a potential new approach not only for preventing and treating inflammation but also for preventing and even contributing to the treatment of CA-CRC. Acknowledgments This work was supported by grants from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001, National Council for Scientific and Technological Development (CNPq) (306634/2019-8) and the FAPERJ (Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro) (E26/202.781/2017, E-26/202.774/2018, E-26/010.001279/2015 and E26/210.886/2014). We thank Kalil Madi for his assistance with the tissue analysis and Jose Nazioberto D. de Farias, Ygor Marinho and Alyson do Rosario Jr for their technical assistance with the tissue processing. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094616/s1. Click here for additional data file. Author Contributions Conceptualization, R.C.-S. and H.S.P.d.S.; data curation, C.B., M.T.L.C.-B., B.P., B.E.R., S.L.B.R., P.T.S., J.C.M., C.L. and F.T.; formal analysis, C.B., M.T.L.C.-B., B.P., B.E.R., P.T.S. and F.T.; funding, R.C.-S. and H.S.P.d.S.; methodology, C.B., M.T.L.C.-B., B.P., B.E.R., S.L.B.R., P.T.S., J.C.M., C.L. and F.T.; project administration, C.B., R.C.-S. and H.S.P.d.S.; resources, R.C.-S. and H.S.P.d.S.; validation, S.L.B.R., P.T.S., J.C.M., C.L. and F.T.; visualization, M.T.L.C.-B., B.P., B.E.R., S.L.B.R., P.T.S., J.C.M. and C.L.; writing—original draft preparation, C.B., M.T.L.C.-B., S.L.B.R., P.T.S., C.L. and F.T.; writing—review and editing, R.C.-S. and H.S.P.d.S. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by grants from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001, National Council for Scientific and Technological Development (CNPq) (306634/2019-8), and the Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ) (E26/202.781/2017, E-26/202.774/2018, E-26/010.001279/2015 and E26/210.886/2014). Institutional Review Board Statement The institutional animal care committee of the Health Sciences Centre of the Federal University of Rio de Janeiro approved the use and care of the animals and the procedures reported in this study (approval ID: 078/15). Informed Consent Statement Not applicable. Data Availability Statement Materials, such as protocols, analytic methods, and study material, are available upon request to interested researchers. The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher. Data regarding the microbiota sequencing are available through the accession numbers: Submission ID: SUB11172419; BioProject: ID: PRJNA814660. Conflicts of Interest The authors declare no conflict of interest. Figure 1 P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 do not develop full AOM/DSS-induced colitis or CA-CRC. Video colonoscopy associated with 3-D endoluminal ultrasound biomicroscopy imaging was performed after induction at weeks 3, 6, and 8 (A). Values are medians with interquartile ranges of 8–10 animals per group. Significant values are presented (B). The survival curves for the AOM/DSS-induced P2X7R+/+ mice showed a significant increase in mortality compared with that of the other groups at week 8 (C). The AOM/DSS-induced P2X7R+/+ mice presented progressive weight loss compared with the mice in the other groups (D); reduced colon length (E,F); and a smaller number of polyps/tumors per animal (G). The survival curves were analyzed, and the p values were determined by the log-rank test. Values are medians with interquartile ranges of three independent experiments, with 5–7 animals per group. Significant values are presented. Figure 2 P2X7R blockade attenuates colonic injury in the AOM/DSS-treated mice. Histopathological analysis by hematoxylin and eosin (HE) staining of the colon shows the typical inflammatory changes and tissue damage induced by AOM/DSS in P2X7R+/+ mice (A). The P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 developed significantly fewer inflammatory changes (B) and tumors (C,D). Values are medians with interquartile ranges of three independent experiments, with 4–5 animals per group. The scale bars represent 20 μm. The analysis was performed by Brown-Forsythe and Welch ANOVA tests, in which multiple comparisons were carried out using Dunnett’s T3 test. Significant values are presented. Figure 3 P2X7R blockade protects against colonic injury and apoptotic cell loss in the AOM/DSS-treated mice. Proliferating cells were immunohistochemically labeled with anti-Ki67 antibody (A), and apoptotic cells were detected using a TUNEL assay (C), as shown by the representative photomicrographs. In nondysplastic inflamed areas, the P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 did not exhibit a change in the rate of Ki67-positive cells (B) but developed significantly less apoptosis (D). In the tumor areas of the P2X7R+/+ treated mice, the number of Ki67-positive cells was increased, while the number of apoptotic cells was decreased. Values are medians with interquartile ranges of three independent experiments, with 4–5 animals per group. The scale bars represent 20 μm. Significant values are presented. The analysis was performed by Brown-Forsythe and Welch ANOVA tests, in which multiple comparisons were carried out using Dunnett’s T3 test. Significant values are presented. Figure 4 P2X7R blockade modulates proinflammatory cytokine production in colon explants from the AOM/DSS-treated mice. Supernatants from colon explants cultured for 24 h at 37 °C with 5% CO2 were used to measure the concentrations of cytokines by CBA. The P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 developed significantly lower concentrations of TNF-alpha (A), IL-17A (B), and IL-6 (C) and higher concentrations of IL-10 than the P2X7R+/+ controls (D). The results are expressed as pg/mL. Values are medians with interquartile ranges of three independent experiments, with 4–5 animals per group. Significant values are presented. The analysis was performed by Brown-Forsythe and Welch ANOVA tests, in which multiple comparisons were carried out using Dunnett’s T3 test. Significant values are presented. Figure 5 P2X7R blockade modulates the expression of genes related to inflammation and cancer in the colon. The mRNA levels measured by quantitative real-time PCR in colon samples of the P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 were significantly lower than those in the P2X7R+/+-treated animals for the NLRP3 (A), NLRP12 (C), MAPK14 (F), and IL-1beta (G) genes. Other genes analyzed in this study did not show significant changes among the experimental groups (B,D,E). Values are medians with interquartile ranges of three independent experiments, with 3–4 animals per group. The analysis was performed by Brown-Forsythe and Welch ANOVA tests, in which multiple comparisons were carried out using Dunnett’s T3 test. Significant values are presented. Figure 6 P2X7R blockade attenuates the expression of intracellular signaling pathways involved in cytokine production and cell survival triggered by AOM/DSS induction. The P2X7R−/− and P2X7R+/+ mice treated with the P2X7R antagonist A740003 expressed less NF-kappa B (A,B) and phospho-ERK (C,D) than the P2X7R+/+-treated animals. Values are medians with interquartile ranges of three independent experiments, with 4–5 animals per group. The scale bars represent 20 μm. The analysis was performed by Brown-Forsythe and Welch ANOVA tests, in which multiple comparisons were carried out using Dunnett’s T3 test. Significant values are presented. Figure 7 P2X7R blockade is followed by changes in the fecal microbial diversity and composition. Alpha-diversity analysis using the Shannon index shows an upward trend in fecal microbial diversity when P2X7R is blocked (A). Beta-diversity analysis using weighted UniFrac principal coordinate analysis (PCoA) clusters P2X7R−/− away from P2X7R+/+ samples (B). A Venn diagram displays the logical relations among groups (C). Differential abundance analysis of taxonomic profiles depicts the microbial composition at the phylum level (D). Sequencing was performed with samples from two independent experiments, with 2–5 animals per group. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Bye W.A. Nguyen T.M. Parker C.E. Jairath V. East J.E. Strategies for detecting colon cancer in patients with inflammatory bowel disease Cochrane Database Syst. Rev. 2017 9 CD000279 10.1002/14651858.CD000279.pub4 28922695 2. Ullman T. Odze R. Farraye F.A. Diagnosis and management of dysplasia in patients with ulcerative colitis and Crohn’s disease of the colon Inflamm. Bowel Dis. 2009 15 630 638 10.1002/ibd.20766 18942763 3. Kappelman M.D. Farkas D.K. Long M.D. Erichsen R. Sandler R.S. Sorensen H.T. Baron J.A. Risk of cancer in patients with inflammatory bowel diseases: A nationwide population-based cohort study with 30 years of follow-up evaluation Clin. Gastroenterol. Hepatol. 2014 12 265 273.e1 10.1016/j.cgh.2013.03.034 23602821 4. Olen O. Erichsen R. Sachs M.C. Pedersen L. Halfvarson J. Askling J. Ekbom A. Sorensen H.T. Ludvigsson J.F. Colorectal cancer in Crohn’s disease: A Scandinavian population-based cohort study Lancet Gastroenterol. Hepatol. 2020 5 475 484 10.1016/S2468-1253(20)30005-4 32066530 5. Ou B. Zhao J. Guan S. Lu A. Survival of Colorectal Cancer in Patients With or Without Inflammatory Bowel Disease: A Meta-Analysis Dig. Dis. Sci. 2016 61 881 889 10.1007/s10620-015-3940-1 26518415 6. Yaeger R. Shah M.A. Miller V.A. Kelsen J.R. Wang K. Heins Z.J. Ross J.S. He Y. Sanford E. Yantiss R.K. Genomic Alterations Observed in Colitis-Associated Cancers Are Distinct From Those Found in Sporadic Colorectal Cancers and Vary by Type of Inflammatory Bowel Disease Gastroenterology 2016 151 278 287 e276 10.1053/j.gastro.2016.04.001 27063727 7. Porter R.J. Arends M.J. Churchhouse A.M.D. Din S. Inflammatory bowel disease-associated colorectal cancer: Translational risks from mechanisms to medicines J. Crohn’s Colitis 2021 15 2131 2141 10.1093/ecco-jcc/jjab102 34111282 8. Cai X. Yao Y. Teng F. Li Y. Wu L. Yan W. Lin N. The role of P2X7 receptor in infection and metabolism: Based on inflammation and immunity Int. Immunopharmacol. 2021 101 108297 10.1016/j.intimp.2021.108297 34717202 9. Figliuolo V.R. Savio L.E.B. Safya H. Nanini H. Bernardazzi C. Abalo A. de Souza H.S.P. Kanellopoulos J. Bobe P. Coutinho C. P2X7 receptor promotes intestinal inflammation in chemically induced colitis and triggers death of mucosal regulatory T cells Biochim. Biophys. Acta (BBA)-Mol. Basis Dis. 2017 1863 1183 1194 10.1016/j.bbadis.2017.03.004 10. Ferrari D. Pizzirani C. Adinolfi E. Lemoli R.M. Curti A. Idzko M. Panther E. Di Virgilio F. The P2X7 receptor: A key player in IL-1 processing and release J. Immunol. 2006 176 3877 3883 10.4049/jimmunol.176.7.3877 16547218 11. de Campos N.E. Marques-da-Silva C. Correa G. Castelo-Branco M.T. de Souza H.S. Coutinho-Silva R. Characterizing the presence and sensitivity of the P2X7 receptor in different compartments of the gut J. Innate Immun. 2012 4 529 541 10.1159/000336628 22508425 12. Lammas D.A. Stober C. Harvey C.J. Kendrick N. Panchalingam S. Kumararatne D.S. ATP-induced killing of mycobacteria by human macrophages is mediated by purinergic P2Z(P2X7) receptors Immunity 1997 7 433 444 10.1016/S1074-7613(00)80364-7 9324363 13. Coutinho-Silva R. Stahl L. Raymond M.N. Jungas T. Verbeke P. Burnstock G. Darville T. Ojcius D.M. Inhibition of chlamydial infectious activity due to P2X7R-dependent phospholipase D activation Immunity 2003 19 403 412 10.1016/S1074-7613(03)00235-8 14499115 14. Fairbairn I.P. Stober C.B. Kumararatne D.S. Lammas D.A. ATP-mediated killing of intracellular mycobacteria by macrophages is a P2X(7)-dependent process inducing bacterial death by phagosome-lysosome fusion J. Immunol. 2001 167 3300 3307 10.4049/jimmunol.167.6.3300 11544318 15. Mariathasan S. Weiss D.S. Newton K. McBride J. O’Rourke K. Roose-Girma M. Lee W.P. Weinrauch Y. Monack D.M. Dixit V.M. Cryopyrin activates the inflammasome in response to toxins and ATP Nature 2006 440 228 232 10.1038/nature04515 16407890 16. Pelegrin P. Surprenant A. Pannexin-1 mediates large pore formation and interleukin-1beta release by the ATP-gated P2X7 receptor EMBO J. 2006 25 5071 5082 10.1038/sj.emboj.7601378 17036048 17. Chen Y.G. Scheuplein F. Driver J.P. Hewes A.A. Reifsnyder P.C. Leiter E.H. Serreze D.V. Testing the role of P2X7 receptors in the development of type 1 diabetes in nonobese diabetic mice J. Immunol. 2011 186 4278 4284 10.4049/jimmunol.1003733 21357538 18. Kawamura H. Aswad F. Minagawa M. Govindarajan S. Dennert G. P2X7 receptors regulate NKT cells in autoimmune hepatitis J. Immunol. 2006 176 2152 2160 10.4049/jimmunol.176.4.2152 16455971 19. Neves A.R. Castelo-Branco M.T. Figliuolo V.R. Bernardazzi C. Buongusto F. Yoshimoto A. Nanini H.F. Coutinho C.M. Carneiro A.J. Coutinho-Silva R. Overexpression of ATP-activated P2X7 receptors in the intestinal mucosa is implicated in the pathogenesis of Crohn’s disease Inflamm. Bowel Dis. 2014 20 444 457 10.1097/01.MIB.0000441201.10454.06 24412990 20. de Britto M.A. Soletti R.C. Schanaider A. Madi K. de Souza H.S. Machado J.C. Endoluminal ultrasound biomicroscopy as a reliable tool for in vivo assessment of colonic inflammation in rats Int. J. Colorectal. Dis. 2013 28 1613 1620 10.1007/s00384-013-1755-0 23925435 21. Zhang Y. Ding J. Wang L. The role of P2X7 receptor in prognosis and metastasis of colorectal cancer Adv. Med. Sci. 2019 64 388 394 10.1016/j.advms.2019.05.002 31276917 22. Calik I. Calik M. Turken G. Ozercan I.H. A promising independent prognostic biomarker in colorectal cancer: P2X7 receptor Int. J. Clin. Exp. Pathol. 2020 13 107 121 32211091 23. Qian F. Xiao J. Hu B. Sun N. Yin W. Zhu J. High expression of P2X7R is an independent postoperative indicator of poor prognosis in colorectal cancer Hum. Pathol. 2017 64 61 68 10.1016/j.humpath.2017.03.019 28412208 24. Adinolfi E. Capece M. Franceschini A. Falzoni S. Giuliani A.L. Rotondo A. Sarti A.C. Bonora M. Syberg S. Corigliano D. Accelerated tumor progression in mice lacking the ATP receptor P2X7 Cancer Res. 2015 75 635 644 10.1158/0008-5472.CAN-14-1259 25542861 25. Ghiringhelli F. Apetoh L. Tesniere A. Aymeric L. Ma Y. Ortiz C. Vermaelen K. Panaretakis T. Mignot G. Ullrich E. Activation of the NLRP3 inflammasome in dendritic cells induces IL-1beta-dependent adaptive immunity against tumors Nat. Med. 2009 15 1170 1178 10.1038/nm.2028 19767732 26. Sougiannis A.T. VanderVeen B. Chatzistamou I. Kubinak J.L. Nagarkatti M. Fan D. Murphy E.A. Emodin reduces tumor burden by diminishing M2-like macrophages in colorectal cancer Am. J. Physiol.-Gastrointest. Liver Physiol. 2022 322 G383 G395 10.1152/ajpgi.00303.2021 35018819 27. Zhang Y. Pu W. Bousquenaud M. Cattin S. Zaric J. Sun L.K. Ruegg C. Emodin Inhibits Inflammation, Carcinogenesis, and Cancer Progression in the AOM/DSS Model of Colitis-Associated Intestinal Tumorigenesis Front. Oncol. 2020 10 564674 10.3389/fonc.2020.564674 33489875 28. Zhang W.J. Hu C.G. Luo H.L. Zhu Z.M. Activation of P2x7 Receptor Promotes the Invasion and Migration of Colon Cancer Cells via the STAT3 Signaling Front. Cell Dev. Biol. 2020 8 586555 10.3389/fcell.2020.586555 33330466 29. Zhang Y. Li F. Wang L. Lou Y. A438079 affects colorectal cancer cell proliferation, migration, apoptosis, and pyroptosis by inhibiting the P2X7 receptor Biochem. Biophys. Res. Commun. 2021 558 147 153 10.1016/j.bbrc.2021.04.076 33915328 30. Burnstock G. Knight G.E. The potential of P2X7 receptors as a therapeutic target, including inflammation and tumour progression Purinergic Signal. 2018 14 1 18 10.1007/s11302-017-9593-0 29164451 31. Hofman P. Cherfils-Vicini J. Bazin M. Ilie M. Juhel T. Hebuterne X. Gilson E. Schmid-Alliana A. Boyer O. Adriouch S. Genetic and pharmacological inactivation of the purinergic P2RX7 receptor dampens inflammation but increases tumor incidence in a mouse model of colitis-associated cancer Cancer Res. 2015 75 835 845 10.1158/0008-5472.CAN-14-1778 25564520 32. Zhang X. Liu X. Zhou W. Du Q. Yang M. Ding Y. Hu R. Blockade of IDO-Kynurenine-AhR Axis Ameliorated Colitis-Associated Colon Cancer via Inhibiting Immune Tolerance Cell Mol. Gastroenterol. Hepatol. 2021 12 1179 1199 10.1016/j.jcmgh.2021.05.018 34087454 33. Jin B.R. Chung K.S. Hwang S. Hwang S.N. Rhee K.J. Lee M. An H.J. Rosmarinic acid represses colitis-associated colon cancer: A pivotal involvement of the TLR4-mediated NF-kappaB-STAT3 axis Neoplasia 2021 23 561 573 10.1016/j.neo.2021.05.002 34077834 34. Wu X. Ren J. Chen G. Wu L. Song X. Li G. Deng Y. Wang G. Gu G. Li J. Systemic blockade of P2X7 receptor protects against sepsis-induced intestinal barrier disruption Sci. Rep. 2017 7 4364 10.1038/s41598-017-04231-5 28663567 35. Marques C.C. Castelo-Branco M.T. Pacheco R.G. Buongusto F. do Rosario A. Jr. Schanaider A. Coutinho-Silva R. de Souza H.S. Prophylactic systemic P2X7 receptor blockade prevents experimental colitis Biochim. Biophys. Acta 2014 1842 65 78 10.1016/j.bbadis.2013.10.012 24184714 36. Schenk U. Frascoli M. Proietti M. Geffers R. Traggiai E. Buer J. Ricordi C. Westendorf A.M. Grassi F. ATP inhibits the generation and function of regulatory T cells through the activation of purinergic P2X receptors Sci. Signal. 2011 4 ra12 10.1126/scisignal.2001270 21364186 37. Wan P. Liu X. Xiong Y. Ren Y. Chen J. Lu N. Guo Y. Bai A. Extracellular ATP mediates inflammatory responses in colitis via P2 x 7 receptor signaling Sci. Rep. 2016 6 19108 10.1038/srep19108 26739809 38. Monteleone G. Pallone F. Stolfi C. The dual role of inflammation in colon carcinogenesis Int. J. Mol. Sci. 2012 13 11071 11084 10.3390/ijms130911071 23109839 39. Francescone R. Hou V. Grivennikov S.I. Cytokines, IBD, and colitis-associated cancer Inflamm. Bowel Dis. 2015 21 409 418 10.1097/MIB.0000000000000236 25563695 40. Velikova T.V. Miteva L. Stanilov N. Spassova Z. Stanilova S.A. Interleukin-6 compared to the other Th17/Treg related cytokines in inflammatory bowel disease and colorectal cancer World J. Gastroenterol. 2020 26 1912 1925 10.3748/wjg.v26.i16.1912 32390702 41. Landskron G. De la Fuente M. Thuwajit P. Thuwajit C. Hermoso M.A. Chronic inflammation and cytokines in the tumor microenvironment J. Immunol. Res. 2014 2014 149185 10.1155/2014/149185 24901008 42. Caamano J. Hunter C.A. NF-kappaB family of transcription factors: Central regulators of innate and adaptive immune functions Clin. Microbiol. Rev. 2002 15 414 429 10.1128/CMR.15.3.414-429.2002 12097249 43. Luo C. Zhang H. The Role of Proinflammatory Pathways in the Pathogenesis of Colitis-Associated Colorectal Cancer Mediat. Inflamm. 2017 2017 5126048 10.1155/2017/5126048 28852270 44. Greten F.R. Eckmann L. Greten T.F. Park J.M. Li Z.W. Egan L.J. Kagnoff M.F. Karin M. IKKbeta links inflammation and tumorigenesis in a mouse model of colitis-associated cancer Cell 2004 118 285 296 10.1016/j.cell.2004.07.013 15294155 45. Schwitalla S. Fingerle A.A. Cammareri P. Nebelsiek T. Goktuna S.I. Ziegler P.K. Canli O. Heijmans J. Huels D.J. Moreaux G. Intestinal tumorigenesis initiated by dedifferentiation and acquisition of stem-cell-like properties Cell 2013 152 25 38 10.1016/j.cell.2012.12.012 23273993 46. Li K.K. Shen S.S. Deng X. Shiu H.T. Siu W.S. Leung P.C. Ko C.H. Cheng B.H. Dihydrofisetin exerts its anti-inflammatory effects associated with suppressing ERK/p38 MAPK and Heme Oxygenase-1 activation in lipopolysaccharide-stimulated RAW 264.7 macrophages and carrageenan-induced mice paw edema Int. Immunopharmacol. 2018 54 366 374 10.1016/j.intimp.2017.11.034 29202300 47. Shannon S. Jia D. Entersz I. Beelen P. Yu M. Carcione C. Carcione J. Mahtabfar A. Vaca C. Weaver M. Inhibition of glioblastoma dispersal by the MEK inhibitor PD0325901 BMC Cancer 2017 17 121 10.1186/s12885-017-3107-x 28187762 48. Bai Y.P. Shang K. Chen H. Ding F. Wang Z. Liang C. Xu Y. Sun M.H. Li Y.Y. FGF-1/-3/FGFR4 signaling in cancer-associated fibroblasts promotes tumor progression in colon cancer through Erk and MMP-7 Cancer Sci. 2015 106 1278 1287 10.1111/cas.12745 26183471 49. Khatri V. Kalyanasundaram R. Therapeutic implications of inflammasome in inflammatory bowel disease FASEB J. 2021 35 e21439 10.1096/fj.202002622R 33774860 50. Kanneganti T.D. Lamkanfi M. Kim Y.G. Chen G. Park J.H. Franchi L. Vandenabeele P. Nunez G. Pannexin-1-mediated recognition of bacterial molecules activates the cryopyrin inflammasome independent of Toll-like receptor signaling Immunity 2007 26 433 443 10.1016/j.immuni.2007.03.008 17433728 51. Arthur J.C. Lich J.D. Ye Z. Allen I.C. Gris D. Wilson J.E. Schneider M. Roney K.E. O’Connor B.P. Moore C.B. Cutting edge: NLRP12 controls dendritic and myeloid cell migration to affect contact hypersensitivity J. Immunol. 2010 185 4515 4519 10.4049/jimmunol.1002227 20861349 52. Lich J.D. Ting J.P. CATERPILLER (NLR) family members as positive and negative regulators of inflammatory responses Proc. Am. Thorac. Soc. 2007 4 263 266 10.1513/pats.200701-022AW 17607010 53. Allen I.C. Wilson J.E. Schneider M. Lich J.D. Roberts R.A. Arthur J.C. Woodford R.M. Davis B.K. Uronis J.M. Herfarth H.H. NLRP12 suppresses colon inflammation and tumorigenesis through the negative regulation of noncanonical NF-kappaB signaling Immunity 2012 36 742 754 10.1016/j.immuni.2012.03.012 22503542 54. Eichele D.D. Kharbanda K.K. Dextran sodium sulfate colitis murine model: An indispensable tool for advancing our understanding of inflammatory bowel diseases pathogenesis World J. Gastroenterol. 2017 23 6016 6029 10.3748/wjg.v23.i33.6016 28970718 55. Lee J.G. Lee Y.R. Lee A.R. Park C.H. Han D.S. Eun C.S. Role of the global gut microbial community in the development of colitis-associated cancer in a murine model Biomed. Pharmacother. 2021 135 111206 10.1016/j.biopha.2020.111206 33418307 56. Hakansson A. Tormo-Badia N. Baridi A. Xu J. Molin G. Hagslatt M.L. Karlsson C. Jeppsson B. Cilio C.M. Ahrne S. Immunological alteration and changes of gut microbiota after dextran sulfate sodium (DSS) administration in mice Clin. Exp. Med. 2015 15 107 120 10.1007/s10238-013-0270-5 24414342 57. Gobert A.P. Latour Y.L. Asim M. Barry D.P. Allaman M.M. Finley J.L. Smith T.M. McNamara K.M. Singh K. Sierra J.C. Protective Role of Spermidine in Colitis and Colon Carcinogenesis Gastroenterology 2021 162 813 827 10.1053/j.gastro.2021.11.005 34767785 58. Su Q.Q. Tian Y.Y. Liu Z.N. Ci L.L. Lv X.W. Purinergic P2X7 receptor blockade mitigates alcohol-induced steatohepatitis and intestinal injury by regulating MEK1/2-ERK1/2 signaling and egr-1 activity Int. Immunopharmacol. 2019 66 52 61 10.1016/j.intimp.2018.11.012 30445307 59. Yacoub E. Saed Abdul-Wahab O.M. Al-Shyarba M.H. Ben Abdelmoumen Mardassi B. The Relationship between Mycoplasmas and Cancer: Is It Fact or Fiction ? Narrative Review and Update on the Situation J. Oncol. 2021 2021 9986550 10.1155/2021/9986550 34373693 60. Song H. Wang W. Shen B. Jia H. Hou Z. Chen P. Sun Y. Pretreatment with probiotic Bifico ameliorates colitis-associated cancer in mice: Transcriptome and gut flora profiling Cancer Sci. 2018 109 666 677 10.1111/cas.13497 29288512 61. Sirnes S. Honne H. Ahmed D. Danielsen S.A. Rognum T.O. Meling G.I. Leithe E. Rivedal E. Lothe R.A. Lind G.E. DNA methylation analyses of the connexin gene family reveal silencing of GJC1 (Connexin45) by promoter hypermethylation in colorectal cancer Epigenetics 2011 6 602 609 10.4161/epi.6.5.15237 21406965 62. Robles A.I. Traverso G. Zhang M. Roberts N.J. Khan M.A. Joseph C. Lauwers G.Y. Selaru F.M. Popoli M. Pittman M.E. Whole-Exome Sequencing Analyses of Inflammatory Bowel Disease-Associated Colorectal Cancers Gastroenterology 2016 150 931 943 10.1053/j.gastro.2015.12.036 26764183 63. Ma B. Hottiger M.O. Crosstalk between Wnt/beta-Catenin and NF-kappaB Signaling Pathway during Inflammation Front. Immunol. 2016 7 378 10.3389/fimmu.2016.00378 27713747 64. Okayasu I. Ohkusa T. Kajiura K. Kanno J. Sakamoto S. Promotion of colorectal neoplasia in experimental murine ulcerative colitis Gut 1996 39 87 92 10.1136/gut.39.1.87 8881816 65. Laukens D. Brinkman B.M. Raes J. De Vos M. Vandenabeele P. Heterogeneity of the gut microbiome in mice: Guidelines for optimizing experimental design FEMS Microbiol. Rev. 2016 40 117 132 10.1093/femsre/fuv036 26323480 66. Tanaka T. Colorectal carcinogenesis: Review of human and experimental animal studies J. Carcinog 2009 8 5 10.4103/1477-3163.49014 19332896 67. Becker C. Fantini M.C. Neurath M.F. High resolution colonoscopy in live mice Nat. Protoc. 2006 1 2900 2904 10.1038/nprot.2006.446 17406549 68. Lienenluke B. Stojanovic T. Fiebig T. Fayyazi A. Germann T. Hecker M. Thalidomide impairment of trinitrobenzene sulphonic acid-induced colitis in the rat-role of endothelial cell-leukocyte interaction Br. J. Pharmacol. 2001 133 1414 1423 10.1038/sj.bjp.0704193 11498529 69. Borinstein S.C. Conerly M. Dzieciatkowski S. Biswas S. Washington M.K. Trobridge P. Henikoff S. Grady W.M. Aberrant DNA methylation occurs in colon neoplasms arising in the azoxymethane colon cancer model Mol. Carcinog. 2010 49 94 103 10.1002/mc.20581 19777566 70. Faith D.P. Phylogenetic pattern and the quantification of organismal biodiversity Philos. Trans. R. Soc. London. Ser. B Biol. Sci. 1994 345 45 58 10.1098/rstb.1994.0085 7972354 71. Katoh K. Misawa K. Kuma K. Miyata T. MAFFT: A novel method for rapid multiple sequence alignment based on fast Fourier transform Nucleic Acids Res. 2002 30 3059 3066 10.1093/nar/gkf436 12136088 72. Lozupone C.A. Hamady M. Kelley S.T. Knight R. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities Appl. Environ. Microbiol. 2007 73 1576 1585 10.1128/AEM.01996-06 17220268 73. Pruesse E. Quast C. Knittel K. Fuchs B.M. Ludwig W. Peplies J. Glockner F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB Nucleic Acids Res. 2007 35 7188 7196 10.1093/nar/gkm864 17947321 74. Price M.N. Dehal P.S. Arkin A.P. FastTree 2--approximately maximum-likelihood trees for large alignments PLoS ONE 2010 5 e9490 10.1371/journal.pone.0009490 20224823 75. Klindworth A. Pruesse E. Schweer T. Peplies J. Quast C. Horn M. Glockner F.O. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies Nucleic Acids Res. 2013 41 e1 10.1093/nar/gks808 22933715 76. Ewels P. Magnusson M. Lundin S. Kaller M. MultiQC: Summarize analysis results for multiple tools and samples in a single report Bioinformatics 2016 32 3047 3048 10.1093/bioinformatics/btw354 27312411 77. Bolyen E. Rideout J.R. Dillon M.R. Bokulich N.A. Abnet C.C. Al-Ghalith G.A. Alexander H. Alm E.J. Arumugam M. Asnicar F. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 Nat. Biotechnol. 2019 37 852 857 10.1038/s41587-019-0209-9 31341288

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093580 sensors-22-03580 Article Virtual Breathalyzer: Towards the Detection of Intoxication Using Motion Sensors of Commercial Wearable Devices https://orcid.org/0000-0003-3453-2120 Nassi Ben https://orcid.org/0000-0003-2576-0009 Shams Jacob * https://orcid.org/0000-0002-6956-3341 Rokach Lior https://orcid.org/0000-0002-9641-128X Elovici Yuval Iosa Marco Academic Editor Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel; nassib@post.bgu.ac.il (B.N.); liorrk@post.bgu.ac.il (L.R.); elovici@bgu.ac.il (Y.E.) * Correspondence: jacobsh@post.bgu.ac.il 08 5 2022 5 2022 22 9 358019 4 2022 05 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Driving under the influence of alcohol is a widespread phenomenon in the US where it is considered a major cause of fatal accidents. In this research, we present Virtual Breathalyzer, a novel approach for detecting intoxication from the measurements obtained by the sensors of smartphones and wrist-worn devices. We formalize the problem of intoxication detection as the supervised machine learning task of binary classification (drunk or sober). In order to evaluate our approach, we conducted a field experiment and collected 60 free gait samples from 30 patrons of three bars using a Microsoft Band and Samsung Galaxy S4. We validated our results against an admissible breathalyzer used by the police. A system based on this concept successfully detected intoxication and achieved the following results: 0.97 AUC and 0.04 FPR, given a fixed TPR of 1.0. Our approach can be used to analyze the free gait of drinkers when they walk from the car to the bar and vice versa, using wearable devices which are ubiquitous and more widespread than admissible breathalyzers. This approach can be utilized to alert people, or even a connected car, and prevent people from driving under the influence of alcohol. intoxication detection wearable devices This research received no external funding. ==== Body pmc1. Introduction In 2013, a death from a motor vehicle accident caused by an alcohol impaired driver occurred every 51 min, a tragic statistic that represents more than 30% of all US traffic-related deaths that year [1]. The high rate of fatal accidents resulting from “driving under the influence” (DUI) reflects the devastating effects of alcohol consumption on driving (e.g., reduced coordination, difficulty steering, and reduced ability to maintain lane position and brake appropriately). Given the potential consequences of drunk driving, there would be value in an intoxication detection method that provides immediate results and is non-invasive/easy to administer without the need for expensive, specialised equipment. Currently, intoxication can be detected via a blood or breath test, such as the breath alcohol concentration (BrAC) test, which measures the weight of alcohol present within a certain volume of breath [2]. This test is conducted with a breathalyzer device [3] and uses an individual’s breath as a specimen/sample. However, these options are not practical for an individual interested in checking their own level of intoxication, as such tests can only be performed in dedicated labs or require the use of specialized equipment that may require prior calibration and ongoing maintenance. As a result, detecting intoxication based on ubiquitous devices is a scientific gap, and there is a need for a different type of test based on such devices that can be applied by an individual in real time. In this paper, we present Virtual Breathalyzer, a new approach for the detection of intoxication based on motion sensors of smartphones and wrist-worn devices. It is a known fact that alcohol consumption causes changes in people’s movements. We hypothesize that these changes can be measured using the motion sensors of smartphones and wrist-worn devices in order to detect intoxication with a trained machine learning model. In order to assess the performance of our suggested approach, we conducted a field experiment in which we collected 60 free gait samples from patrons of three bars, using a smartphone (Samsung Galaxy S4) and wrist-worn device (Microsoft Band), and labeled the data based on the results of an admissible breathalyzer used by the police. We trained machine learning models to predict if an individual is intoxicated based on their free gait and analyzed the performance of our approach with different BrAC thresholds of intoxication and combinations of features/device sensors. We show that data obtained from a smartphone and wrist-worn device from eight seconds of movement are sufficient to detect intoxication (obtaining an AUC of 0.97). In this paper, we make the following contributions: (1) We show that the motion sensors of smartphones and widely used wrist-worn devices can be used to identify the physiological indicators that imply intoxication (in terms of body movement) based on free gait and may provide an alternative to traditional ad hoc sensors and tests that focus on breath or blood samples. (2) We formalize the task of intoxication detection as a supervised machine learning task based on body movement measurements derived from the sensors of smartphones and wrist-worn devices. We used an actual breathalyzer (as used by police departments) in order to label our data and train our models to evaluate our results. The remainder of this paper is structured as follows: In Section 2, we review related works, and in Section 3, we present the proposed approach. In Section 4, we present the experiment, methodology, and ethics. In Section 5 we describe the data processing method, and we present our evaluation and results in Section 6. Finally, in Section 7 and Section 8, we conclude the paper and present future work directions, respectively. 2. Related Work In this section, we review related work in the fields of gait analysis, context/activity detection using commercial wearable devices, and intoxication detection. 2.1. Gait Analysis Gait analysis has been studied for many years, even before the era of wearable devices. A decade ago, researchers were already using ad hoc sensors specially designed for research purposes. Mantyjarvi et al. [4] analyzed data collected from worn accelerometer devices in order to identify subjects by their gait, Gafurov et al. [5] used a worn accelerometer for authentication and identification based on the subjects’ gait, and Lu et al. [6] showed that authentication from gait is also possible from smartphone sensors. Aminian et al. [7] analyzed accelerometer and gyroscope measurements from ad hoc sensors that they designed to be worn on a shoe in order to explore gait. Xu et al. [8] presented a novel system for gait analysis using smartphones and three sensors located within shoe insoles to provide remote analysis of the user’s gait. 2.2. Context and Activity Detection Using Commercial Wearable Devices In the area of activity detection, Thomaz et al. [9] used smartwatch motion sensors in order to detect eating instances. Ranjan et al. [10] analyzed smartwatch sensors during specific home-based activities (such as turning on a light switch) to identify subjects based on hand gestures. In the field of emotion detection, Hernandez et al. [11] analyzed head movement from Google Glass motion sensors in order to detect stress, fear, and calm. Hernandez et al. [12] analyzed smartwatch motion sensors to estimate heart and breathing rates. Mazilu et al. [13] analyzed wrist movement to detect gait freezing in Parkinson’s disease using the data sensors of smart watches and wristbands, while Gabus et al. [14] and Casilari et al. [15] used a smartwatch in order to detect falls. 2.3. Intoxication Detection Despite the importance of detecting intoxication, there has been a limited amount of research that addresses the domain of intoxication detection using ubiquitous technology. A recent study [16] showed that intoxication can be detected via a dedicated smartphone application that challenges the subject with various tasks, such as typing, sweeping, and other reaction tests. However this method is not passive and can be considered a software alternative to a breathalyzer, since it suffers from another shortcoming of the breathalyzer: its effectiveness is dependent on the cooperativeness of the subject. Kao et al. [17] analyzed the accelerometer data collected from subjects’ smartphones and compared the step times and gait stretch of sober and intoxicated subjects. This research was limited in scope in that it only used three subjects. In addition, it was not aimed at detecting whether a person was intoxicated based on data collected from the device; instead, the study compared differences in the gait of intoxicated and sober subjects. Arnold et al. [18] investigated whether a smartphone user’s alcohol intoxication level (how many drinks they had) can be inferred from their gait. The authors used time and frequency domain features extracted from the device’s accelerometer to classify the number of drinks a subject consumed based on the following ranges: 0–2 drinks (sober), 3–6 drinks (tipsy), or 6+ drinks (drunk). However, their methodology is not admissible, because some people do not become intoxicated from two drinks while others do, as this depends on physiological (e.g., the subject’s weight) and non-physiological factors (e.g., whether the subject has eaten while drinking). Several studies have utilized ubiquitous technology to detect intoxication based on driving patterns. Dai et al. [19] and Goswami et al. [20] used mobile phone sensors and pattern recognition techniques to classify drunk drivers based on driving patterns. Various other approaches for intoxication detection have also been investigated. Thien et al. [21] and Wilson et al. [22] attempted to simulate the HGN (horizontal gaze nystagmus) test [23] in order to detect intoxication using a camera (i.e., smartphone camera) and computer vision methods. Hossain et al. [24] used machine learning algorithms to identify tweets sent under the influence of alcohol (based on text). None of the abovementioned methods were validated against an admissible breathalyzer, and the authors did not test the accuracy of the methods on a large number of subjects. 3. Proposed Approach In this section, we describe Virtual Breathalyzer, an approach for detecting intoxicated users based on free gait data obtained from a smartphone and wrist-worn device. The short-term effects of alcohol consumption on subjects range from a decrease in anxiety and motor skills and euphoria at lower doses to intoxication (drunkenness), stupor, unconsciousness, anterograde amnesia (memory “blackouts”), and central nervous system depression at higher doses [1]. As a result, various field sobriety tests are administered by police officers as a preliminary step before a subject takes a BrAC test using a breathalyzer. One of the most well-known field sobriety tests administered by police departments in order to detect whether a person is intoxicated is the walk and turn test in which a police officer asks a subject to take nine steps, heel-to-toe, along a straight line; turn on one foot; and return by taking nine steps in the opposite direction. During the test, the officer looks for seven indicators of impairment. If the driver exhibits two or more of the indicators during the test, there is a significant likelihood that the subject is intoxicated (according to the US National Highway Traffic Safety Administration/NHTSA [25]). Based on the effectiveness of the walk and turn test, we suggest the following approach: detecting whether a subject is intoxicated by analyzing differences in his/her free gait. We propose identifying the physiological indicators that imply drunkenness (in terms of body movement) based on the difference between two data samples of free gait. Each sample consists of motion sensor data obtained via devices that are carried/worn by an individual. We believe that smartphones and wrist-worn devices can be used for the purpose of intoxication detection based on free gait because (1) smartphones and wrist-worn devices are heavily adopted, with wrist-worn devices being the most commonly used and popular type of wearable device; according to a 2014 survey, one out of every six people owned a wrist-worn device [26], and a 2019 survey showed that their adoption rate increased, with 56% of people owning a wrist-worn device [27]; (2) smartphones and wrist-worn devices contain motion sensors capable of measuring free gait; and (3) most people have their smartphones and wrist-worn devices on them all the time (according to a recent survey [27]). The first data sample consists of a standard free gait sample recorded by an individual during a time period in which they are likely to be sober (e.g., during the morning or afternoon). The second sample is recorded during the time of interest (e.g., the time the individual is believed to be intoxicated). Using a smartphone and wrist-worn device, the free gait of an individual can be recorded both while they are sober and when they are believed to be intoxicated. By identifying features of the individual’s free gait and determining whether the differences between these features when sober and when believed to be intoxicated exceed a predetermined threshold, a trained machine learning model can determine whether the individual is intoxicated. Algorithm 1 presents a high-level solution for detecting intoxication based on the Virtual Breathalyzer approach. It receives four inputs: a trained intoxication detection Model; two samples of free gait: (1) when the user is sober (sSober) and (2) when the user is believed to be intoxicated (sSuspect); and a learned Threshold. First, features are extracted for each sample of free gait for fSuspect and fSober (lines 7–8). Then, the difference between the features fSuspect and fSober is calculated (lines 10–12). The difference is then classified using a trained intoxication detection Model (line 8). Finally, the result is returned according to a learned Threshold. Algorithm 1 Is Intoxicated? 1: Input:Model—Intoxication Detection Model 2: Input:sSober—Gait Measurements while Sober 3: Input:sSuspect—Suspected Gait Measurements 4: Input:Threshold—Confidence threshold 5: Output:Boolean—True/False for intoxication 6: procedure isIntoxicated? 7:     fSober[]=features(sSober) 8:     fSuspect[]=features(sSuspect) 9:     n=length(fSober) 10:     difference[]=newarray[n] 11:     for (i=0;i<n;i++) do 12:         difference[i]=fSuspect[i]−fSober[i] 13:     Probability=Model.classify(difference) 14:     return(Probability>Threshold) 4. The Experiment and Methodology In this section, we describe the experiments we conducted in order to evaluate whether data from a smartphone and a wrist-worn device can be used to detect if the device owner is intoxicated. We present the experimental framework we developed, the ethical considerations we had to take into account, the experimental protocol, and the methodology. 4.1. Experimental Framework Most commercial wrist-worn devices are equipped with motion sensors and include an SDK to allow users to program them easily. We chose to use the Microsoft Band as a wrist-worn device in our experiment, because: (1) its SDK has clear documentation, (2) it is easy to program the device, and (3) the device has both accelerometer and gyroscope sensors, and each sample is provided over three axes (x, y, and z). We paired the Microsoft Band to a smartphone (Samsung Galaxy S4) using Bluetooth communication. We used the Microsoft Band’s SDK to develop a dedicated application for the smartphone that sampled motion sensor data from the wrist-worn device and smartphone. The motion sensor data was sampled from the Samsung Galaxy S4 at 180 Hz and the Microsoft Band at 62 Hz and recorded as a time series in nanoseconds. The application generated a beep sound that was played to the subject (via headphones) and triggered the subject to start walking (while wearing the devices) until the application generated a second beep 16 s later. In order to measure the subject’s gait, the application sampled the sensors for eight seconds, a time period that started on the sixth second of the experiment and continued until the fourteenth second. The stages of the experiment are presented in Figure 1. We decided that using eight seconds of movement was the optimal way to conduct the experiment and obtain the samples for the following reasons: (1) intoxication affects a subject’s gait and balance; (2) the user may be parked a few meters away from the bar so the walk from the bar to the car may be short; (3) gait is probably the best way to ensure that the devices are carried/worn by the user instead of sitting on a desk or table (in the context of a bar); and (4) free gait measurements can be obtained from the user passively by detecting walking instances (from smartphone/wrist-worn device sensors such as the accelerometer, gyroscope, and GPS). In addition, we purchased a Drager Alcotest 5510 breathalyzer (https://www.draeger.com/en_me/Products/Alcotest-5510, accessed on 18 April 2022) in order to obtain BrAC samples. This breathalyzer outputs results in micrograms of alcohol per liter of breath. We chose this type of breathalyzer, because it is a professional breathalyzer used by police departments around the world. 4.2. Ethical Considerations The experiment involved collecting data from intoxicated and sober subjects, which was approved by the institutional review board (IRB), subject to the following precautions:(1) Only individuals that went to a bar in order to drink of their own accord could participate in the experiment; in this way, the onus for any consequences resulting from such drinking would be on the subjects. (2) Only individuals that did not drive to the bar and would not drive back from the bar could participate in the experiment. (3) Anonymization was applied to the data. At the beginning of the experiment, a random user ID number was assigned to each subject, and this user ID number served as the identifier of the subject, rather than his/her actual identifying information. The mapping between the experiment’s user ID numbers and the identity of the subjects was stored in a hard copy document that was kept in a safe box; at the end of the experiment, we destroyed this document. (4) During the experiment, the data collected were stored encrypted in the local storage of the smartphone (which was not connected to the Internet during the experiment). At the end of the experiment, the data was copied to a local server (i.e., within the institutional network), which was not connected to the Internet. Only anonymized information of the subjects was kept for further analysis. (5) Subjects were paid for their participation in the study (each subject received the equivalent of 15 USD in local currency). 4.3. Methodology In order to sample as many people as possible, our experiment took place on three evenings at three bars that offer an ”all you can drink” option (we visited one bar each evening). The Google Maps locations of the bars are provided (https://www.google.com/maps/place/Shlomo+Ibn+Gabirol+St+13,+Tel+Aviv-Yafo/, accessed on 18 April 2022), (https://www.google.com/maps/place/Shlomo+Ibn+Gabirol+St+17,+Tel+Aviv-Yafo/, accessed on 18 April 2022), (https://www.google.com/maps/place/Shlomo+Ibn+Gabirol+St+33,+Tel+Aviv-Yafo/, accessed on 18 April 2022). We waited for people to arrive at the bars, and just before they ordered their first drink, we asked them to participate in our research (participation entailed providing a gait sample during two brief experimental sessions with a smartphone and wrist-worn device, as well as providing two breath samples a few seconds before the sessions started). We explained that they would receive the equivalent of 15 USD in local currency for their participation. We also told the subjects that they would be compensated even if they chose not to drink at all, so drinking was not obligatory. Each subject signed a document stating that he/she came to the bar in order to drink of his/her own accord and that he/she did not drive to the bar and would not drive from the bar (as we were instructed by the IRB). The breathalyzer was calibrated at the beginning of each evening according to the manufacturer’s instructions. The experiment was conducted in two sessions. The first session took place before the subjects had their first drink. The second session took place at least 15 min after the subject’s last drink, just before they intended to leave the bar. We consulted with police authorities regarding the breathalyzer test, and they told us to wait 15 min after the subject had their last drink in order to obtain an accurate BrAC specimen. During each session, our subjects provided us with a gait sample and a BrAC specimen. Their gait was recorded using the application that we developed (described at the beginning of this section). The BrAC specimen was measured with the breathalyzer; the result was used to label each gait sample. Our subjects were outfitted with the devices as follows: they were asked to wear the Microsoft Band on their left or right wrist (at their discretion) and carry a smartphone in a rear pocket (as can be seen in Figure 2). Each subject also wore headphones that were used to hear the beeps used to indicate when they should start/stop walking. Thirty subjects participated in our study, each of whom was instructed to walk (while wearing the devices) in any direction they wished until they heard a beep in the headphones, as can be seen in Figure 1. Each subject provided two free gait samples, one before and one after drinking, resulting in the 60 free gait samples collected in the field experiment. 5. Processing the Data In the following section, we describe the extracted features and the process of creating the dataset. 5.1. Feature Engineering Differences in walking caused by intoxication are expressed as difficulty walking in a straight line and maintaining balance, and swaying. These indicators appear even with the consumption of a small amount of alcohol and can be detected by police officers in the field sobriety test (walk and turn test) without a dedicated device. The walk and turn test is usually performed by officers before a breathalyzer test in order to save the long process of obtaining a breath sample from individuals that are not shown to be intoxicated based on the field sobriety test. Since we used data obtained from motion sensors, we extracted features that can be informative as a means of detecting the abovementioned gait differences. The first type of features that we used are features from the spectrum domain. Previous studies demonstrated the effectiveness of extracting such features from motion sensors [4,12]. We applied a fast Fourier transform (FFT), and extracted features that represent the distribution of the power of the signals across the spectrum domain by taking the average power for four ranges in the spectrum. Such features may indicate physiological changes resulting from alcohol consumption that are associated with reduced frequency of movement as a result of difficulty in maintaining balance while walking. We extracted four features for each axis (x, y, z), each device (smartphone and wrist-worn device), and each device sensor (gyroscope and accelerometer). In total, we extracted 48 such features. The second type of features that we used are statistical features. Previous studies demonstrated the effectiveness of extracting such features from motion sensors [6,9]. We extracted five features that represent high-level information about the signals. Such features may indicate physiological changes associated with intoxication, such as decreased average acceleration as a result of difficulty maintaining balance. We extracted features for each axis, each device, and each device sensor. In total, we extracted 60 such features. The third type of features used were histogram features. We presented the signals as histograms, as done in previous studies [28,29]. We extracted a histogram that represents the distribution of the values of the signals across the time domain between the minimum and maximum values. Such features may indicate differences in the patterns of movement (and specifically, the distribution of the movement) as a result of the abovementioned indicators. We extracted six features for each axis, each device, and each device sensor. In total, we extracted 72 such features. Finally, we extracted known gait features that have been shown to yield good results in previous studies [30,31]. We extracted four features (zero crossing rate, mean crossing rate, median, and RMS). These features may indicate differences in the characteristics of a person’s gait that are the result of difficulty walking. We extracted features for each axis, each device, and each device sensor. In total, we extracted 48 such features. In total, 228 features were extracted and utilized for our method. 5.2. Creating the Dataset As mentioned in Section 4, each subject contributed two breath specimens and gait samples (obtained in two sessions—before and after drinking). Each gait sample is comprised of sensor readings (measurements) obtained from a smartphone and wrist-worn device. The accelerometer and gyroscope were sampled from the smartphone and wrist-worn device. Given person p and his/her two gait samples: s-before (measurement taken before alcohol consumption) and s-after (measurement taken after alcohol consumption), we processed the samples as follows:(1) Feature Extraction—We extracted two feature vectors: the f-before vector (extracted from s-before) and the f-after vector (extracted from s-after). (2) Difference Calculation—We calculated a new feature vector called the f-difference. These features represent the difference (for each feature) between the f-after and f-before values. The difference signifies the effects of alcohol consumption on the subject’s movement and is calculated by subtracting each of the features in f-before from its correlative feature in f-after. (3) Labeling—We labeled the sample of each subject as intoxicated/sober according to the result of the professional breathalyzer for known BrAC thresholds. The dataset creation process resulted in 30 labeled instances extracted from 30 users, representing the differences between the extracted features before and after drinking. We used these data to train supervised machine learning models for intoxication detection. We analyzed the data as a classification task, with the goal of determining whether a person is intoxicated or sober according to known BrAC thresholds as measured using a breathalyzer. More precisely, we aimed to train a model that determines whether a person is intoxicated or not using differences in the subject’s gait features. We chose to classify our instances according to three common BrAC thresholds: 220, 240, and 380. These BrAC thresholds are commonly used by countries around the world (see Table 1). We consider an instance labeled by a breathalyzer result (BrAC) to be sober if its value is less than the threshold and intoxicated if its value exceeds the threshold. The breakdown of the subject’s sober/drunk states according to the common BrAC thresholds 220, 240, and 380 is presented in Figure 3. At the lower BrAC thresholds of alcohol concentration (220, 240), the data is distributed such that 20–33% of the total number of subjects were considered intoxicated. At the highest threshold (380), 10% of the subjects were considered intoxicated. 6. Evaluation In this section, we describe the algorithms used and the evaluation protocol. In addition, we report the performance of the intoxication detection method specified by Algorithm 1 using the models that we trained. 6.1. Algorithms & Evaluation Protocol Five different machine learning models were evaluated to allow for a versatile yet comprehensive representation of the model’s performance. The first model that we evaluated was Naive Bayes which belongs to a family of simple probabilistic classifiers. The second model evaluated was Logistic Regression. This model is able to obtain good results in cases where the two classes can be adequately separated using a linear function. The third model used was Support Vector Machines which is used to identify the maximum margin hyperplane that can separate classes. Finally, we evaluated two ensemble-based classifiers: Gradient Boosting Machine (GBM) and AdaBoost. GBM trains a sequence of trees where each successive tree aims to predict the pseudo-residuals of the preceding trees. This method allowed us to combine a large number of classification trees with a low learning rate. AdaBoost trains a set of weak learners (decision trees) and combines them into a weighted sum that represents the final outcome. Since our data is based on samples from 30 subjects, we could utilize the leave-one-user-out protocol, i.e., the learning process was repeated 30 times, and in each test, 29 subjects were used as a training set, and one subject was used as a test set to evaluate the predictive performance of the method. The leave-one-user-out protocol allowed us to evaluate the performance of the suggested method by utilizing the entire set of instances in the data for training and evaluation. We report the following metrics: area under the receiver operating characteristic curve (AUC), false positive rate (FPR), and true positive rate (TPR). The results that we report in this section are the average of 30 models that were trained and evaluated on the dataset for each task. 6.2. Results We use Algorithm 1 in order to evaluate the following:(1) our method’s performance according to various BrAC thresholds; (2) our method’s performance when using various detection policies; and (3) the importance of each device, sensor, and set of features in terms of the method’s performance. 6.2.1. Performance with Various BrAC Thresholds (220, 240, 380 BrAC) ROC/AUC Results We start by assessing the performance of the intoxication detection method from data obtained from a smartphone and a wrist-worn device. Table 2 presents the AUC results for each of the classification models for BrAC thresholds of 220, 240, and 380. As can be seen, the GBM and AdaBoost classifiers yielded high accuracy rates for these thresholds. Figure 4 and Figure 5 present the ROC curves for the AdaBoost and Gradient Boosting classifiers. Classification Accuracy We also analyzed the classifiers’ decisions. The confusion matrices for the AdaBoost and Gradient Boosting classifiers for BrAC thresholds of 220, 240, and 380 are presented in Table 3 and Table 4. As can be seen, for the threshold of 380 BrAC every subject is classified as sober, demonstrating a difficulty with detecting intoxication for this BrAC threshold. This can be explained by the highly imbalanced dataset, with most subjects (90%) labeled as sober due to the high BrAC threshold. 6.2.2. Performance with Various Detection Policies Here, we set out to evaluate the performance of the intoxication detection method according to two policies. Table 3 and Table 4 present misclassifications (FNR and FPR) for BrAC thresholds of 220, 240, and 380. Each Intoxicated Subject is Classified as Intoxicated (0 FNR) Misclassifying a drunk user as sober would provide false confidence to a user, implying that they are not intoxicated, which could cause them to perform risky behavior, such as driving while unknowingly intoxicated. In order to avoid such incidents, we wanted to test the performance of a model on a policy whereby each intoxicated subject is predicted as intoxicated. In order to do so, we fixed the TPR at 1.0 (the true class is intoxicated) and assessed the impact of this limitation on the FPR, i.e., we looked at the percentage of sober subjects that were misclassified as intoxicated. Table 5 presents the FPR results of the Gradient Boosting and AdaBoost classifiers for BrAC thresholds of 220, 240, and 380. As can be seen from the results, applying a constraint of detecting all intoxicated subjects caused up to 30% of the sober subjects to be misclassified as intoxicated for BrAC thresholds of 220, 240, and 380. Each Subject Classified as Intoxicated is Actually Intoxicated (0 FPR) We also evaluated the performance of the method on another policy whereby each intoxicated subject that is classified as intoxicated by the method is actually intoxicated in reality. In order to do so, we fixed the FPR at zero (the positive class is intoxicated) and assessed the impact of this limitation on the TPR, i.e., we looked at the percentage of intoxicated subjects that were misclassified as sober. Table 6 presents the TPR results of the Gradient Boosting and AdaBoost classifiers for BrAC thresholds of 220, 240, and 380. As can be seen from the results, the impact of applying a constraint of detecting only intoxicated subjects is that this approach is only effective for a BrAC threshold of 220, since 40–55% of the intoxicated subjects are detected (when using a Gradient Boosting classifier as the intoxication detection model). However, for all other BrAC thresholds, all of the intoxicated subjects are misclassified. 6.2.3. Importance of Devices, Features, and Sensors Regarding Performance In this experiment, we aimed to determine the impact of each device, sensor, and set of features on the performance. Importance of Devices We started by evaluating the performance for data that was obtained exclusively from a smartphone or a wrist-worn device. We trained AdaBoost and Gradient Boosting classifiers with data obtained from a single device for BrAC thresholds of 220, 240, and 380. Table 7 presents the results of the AdaBoost and Gradient Boosting classifiers for data obtained from a smartphone, wrist-worn device, and both devices (for comparison). As can be seen from the results, measurements of movements from both devices are required to accurately classify a subject as intoxicated/sober. Importance of Features In the feature extraction process, we extracted four types of features. Since the gait of individuals changes as a result of alcohol consumption, we wanted to identify the best set of indicators to detect intoxication (based on body movement patterns) and determine which of the following is most effective at this task: the distribution of the movement (histogram), frequency of the movement, statistical features, or known gait features. In order to do so, we used the dataset and trained Gradient Boosting and AdaBoost classifiers for BrAC thresholds of 220, 240, and 380. We classified each instance using two methods. The first classification method used a specific set of features among the sets (histogram, known gait features, frequency features (FFT), statistical features). The second classification method used all of the other sets of features (except the set used in the first method). Figure 6 presents the average AUC results for BrAC thresholds of 220, 240, and 380. As can be seen from the results, the models that were trained on only statistical features outperformed the models that were trained without them. All other models that were trained on a certain set of features were unable to obtain higher scores than the models that were trained without them. However, models trained with a combination of features (such as every set except FFT) achieved higher performance. From this, we conclude that a combination of the entire set of features is required to train an effective/accurate intoxication detection model. Importance of Sensors Finally, we examine the impact of data from each sensor on the results. In order to do so, we followed the same protocol used to test the feature robustness: we trained Gradient Boosting and AdaBoost classifiers for BrAC thresholds of 220, 240, and 380. We classified each instance using a model that was only trained on accelerometer features and a model that was only trained on gyroscope features. Figure 7 presents the average AUC results for BrAC thresholds of 220, 240, and 380. As can be seen from the results, a model that was trained only on accelerometer measurements yields nearly the same results as a model trained on measurements from both sensors. Given this, we conclude that subjects’ acceleration when walking is highly informative in the detection of intoxication. 7. Conclusions and Discussion In this paper, we present Virtual Breathalyzer, a novel approach to detect intoxication using data from the motion sensors of commercial wearable devices which may be used as an alternative by users when a breathalyzer is not available. We conducted an experiment involving 30 patrons from three different bars to evaluate our approach. Our experiment demonstrated the proposed approach’s ability to accurately detect intoxication using just a smartphone and wrist-worn device. An AUC of 0.97 was obtained for a BrAC threshold of 240 micrograms of alcohol per one liter of breath. Using two simple gait samples (from a car to a bar and vice versa), a system based on this approach can be used to prevent people from driving under the influence of alcohol and could also be used to trigger the device owner’s connected car to prevent ignition in cases in which the owner is detected as drunk. The significance of the Virtual Breathalyzer approach with respect to the methods proposed in related work is that our approach: (1) requires minimal/no cooperation on the part of the subject (unlike [16]), (2) utilizes ubiquitous, commercial device sensors for detecting intoxication rather than ad hoc sensors (unlike a blood or breath test) (3) is validated against the results of an admissible police breathalyzer (unlike previous methods [19,20,21,22,24]), and (4) can be utilized in real time to prevent a user from driving while intoxicated. Some might argue that intoxication detection via wearable devices provides a welcome opportunity to notify a device owner that they are intoxicated in order to prevent them from driving under the influence of alcohol. Others might argue that intoxication detection via wearable devices threatens people’s privacy, because it could be exploited as a means of learning about the habits of the device owner (e.g., which could lead an employer to fire an employee due to his/her drinking habits) or to prove that a device owner has driven under the influence of alcohol. The main objective of this research was to show that motion sensors can be used as alternative to the traditional blood and breath tests for intoxication detection, rather than taking a particular side in an argument about the advantages and disadvantages of such a method. 8. Future Work There are numerous opportunities to extend this work:(1) Deriving additional insights via alternative virtual, passive methods: additional research is needed to detect intoxication/drug use indirectly via passive and virtual methods. For example, the physiological indicators (e.g., sweat, reduced movement) associated with drug use might also be identified via wearable device sensors (skin conductivity and motion sensors). (2) Deriving insights from aggregated/low resolution data: additional research is also required in order to derive insights from aggregated data. For example, a recent study [30] compared the effectiveness of various statistical features used to detect a subject’s gait from wearable devices. The ability to derive insights from aggregated data can enable virtual intoxication detection methods to be used to make inferences about an individual’s cognitive state. (3) Data quality: additional research is required to understand whether the quality of the data obtained by the sensors of commercial wearable devices can replace dedicated sensors for general health/status inference. For example, cardiovascular data obtained from a dedicated sensor can be used to detect lies [32]; however a recent study revealed that the cardiovascular data obtained from an Apple watch generates false alarms 90% of the time for pulse readings that are associated with a patient’s cardiac condition [33]. We believe that additional research is also required to explore the accuracy and errors of the sensors that are integrated in wearable devices. (4) Dimensionality Reduction and Feature Analysis: additional research on performing dimensionality reduction on extracted features, as well as identifying individual features which contribute most to performance, would be a significant addition to this research in analyzing the impact of extracted features on the performance of our method. (5) General population diversity: additional research is needed in analyzing the diverse medical, geographic, and demographic variations between populations and its effect on the performance of our method, before it can be successfully deployed for general use. Acknowledgments We thank Simon Dzanashvili, Ziv Kaduri, Boris Spektor, and Ron Biton for their help collecting samples from the subjects. We would also like to thank all of the participants in this study. Author Contributions Investigation, B.N. and J.S.; methodology, B.N. and J.S.; project administration, B.N. and J.S.; writing—original draft preparation, B.N. and J.S.; writing—review and editing, B.N. and J.S.; supervision, L.R. and Y.E.; validation, L.R. and Y.E. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Ben-Gurion University of the Negev (date of approval: June 2015). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data are not publicly available due to privacy concerns regarding the subjects involved in the study. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Experimental protocol: a sample of eight seconds of motion sensor data obtained when the subject was walking. Figure 2 A subject outfitted with a Microsoft Band and Samsung Galaxy S4. Figure 3 A breakdown of the subjects’ state (sober/drunk) at various BrAC levels. Figure 4 ROC curve of the Gradient Boosting classifier for BrAC thresholds of 220, 240, and 380 from data that was obtained from a smartphone and wrist-worn device. Figure 5 ROC curve of the AdaBoost classifier for BrAC thresholds of 220, 240, and 380 from data that was obtained from a smartphone and wrist-worn device. Figure 6 Average AUC results of the AdaBoost and Gradient Boosting classifiers based on specific types of features and without them. Figure 7 Average AUC results of the AdaBoost and Gradient Boosting classifiers based on measurements that were obtained from a single sensor and from both sensors. sensors-22-03580-t001_Table 1 Table 1 BrAC thresholds for intoxication around the world. BrAC Threshold Countries 220 Scotland, Finland, Hong Kong 240 Slovenia, South Africa, Israel 380 Malawi, Namibia, Swaziland sensors-22-03580-t002_Table 2 Table 2 AUC of classification algorithms: AdaBoost, Naive Bayes (NB), Linear Regression (LR), Support Vector Machines (SVM), and Gradient Boosting (GB) for BrAC thresholds of 220, 240, and 380. Thresholds 220 240 380 AdaBoost 0.945 0.979 0.500 GB 0.915 0.952 0.926 LR 0.560 0.577 0.457 NB 0.290 0.196 0.414 SVM 0.500 0.500 0.500 sensors-22-03580-t003_Table 3 Table 3 Confusion matrices of the Gradient Boosting classifier for BrAC thresholds of 220, 240, and 380. Predicted 220 240 380 Drunk Sober Drunk Sober Drunk Sober Drunk 6 4 9 0 0 3 Sober 1 19 2 19 0 27 sensors-22-03580-t004_Table 4 Table 4 Confusion matrices of the AdaBoost classifier for BrAC thresholds of 220, 240, and 380. Predicted 220 240 380 Drunk Sober Drunk Sober Drunk Sober Drunk 8 2 9 0 0 3 Sober 3 17 1 20 0 27 sensors-22-03580-t005_Table 5 Table 5 Detecting all intoxicated subjects: FPR (false positive rate) of classifiers with a fixed TPR (true positive rate) of 1.0. Thresholds 220 240 380 GBC 0.3 0.09 0.11 AdaBoost 0.15 0.04 0 sensors-22-03580-t006_Table 6 Table 6 Detecting an intoxicated instance with no errors: TPR (true positive rate) of classifiers with a fixed FPR (false positive rate) of zero. Thresholds 220 240 380 GBC 0.4 0 0 AdaBoost 0.4 0.55 0 sensors-22-03580-t007_Table 7 Table 7 AUC results of the AdaBoost and Gradient Boosting classifiers based on data obtained from a smartphone, wrist-worn device, and both devices. Thresholds 220 240 380 Gradient Boosting Smartphone 0.74 0.38 0.46 Wrist-Worn Device 0.52 0.68 0.92 Both 0.915 0.952 0.926 AdaBoost Smartphone 0.75 0.57 0.59 Wrist-Worn Device 0.33 0.73 0.5 Both 0.945 0.979 0.5 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. CDC Injury Prevention and Control: Motor Vehicle Safety 2016 Available online: http://www.cdc.gov/motorvehiclesafety/impaired_driving/impaired-drv_factsheet.html (accessed on 18 April 2022) 2. WebMD Self-Test for Breath Alcohol 2016 Available online: http://www.webmd.com/mental-health/addiction/self-test-for-breath-alcohol (accessed on 18 April 2022) 3. Wikipedia Breathalyzer 2016 Available online: https://en.wikipedia.org/wiki/Breathalyzer (accessed on 18 April 2022) 4. Mäntyjärvi J. Lindholm M. Vildjiounaite E. Mäkelä S.M. Ailisto H. Identifying users of portable devices from gait pattern with accelerometers Proceedings of the Acoustics, Speech, and Signal Processing, 2005 (ICASSP’05) Philadelphia, PA, USA 23–23 March 2005 IEEE Piscataway, NJ, USA 2005 Volume 2 973 5. Gafurov D. Snekkenes E. Bours P. Gait authentication and identification using wearable accelerometer sensor Proceedings of the Automatic Identification Advanced Technologies Alghero, Italy 7–8 June 2007 IEEE Piscataway, NJ, USA 2007 220 225 6. Lu H. Huang J. Saha T. Nachman L. Unobtrusive gait verification for mobile phones Proceedings of the 2014 ACM International Symposium on Wearable Computers Seattle, WA, USA 13–17 September 2014 ACM New York, NY, USA 2014 91 98 7. Aminian K. Dadashi F. Mariani B. Lenoble-Hoskovec C. Santos-Eggimann B. Büla C.J. Gait analysis using shoe-worn inertial sensors: How is foot clearance related to walking speed? Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing Seattle, WA, USA 13–17 September 2014 ACM New York, NY, USA 2014 481 485 8. Xu W. Huang M.C. Amini N. Liu J.J. He L. Sarrafzadeh M. Smart insole: A wearable system for gait analysis Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments Heraklion Crete, Greece 6–8 June 2012 ACM New York, NY, USA 2012 18 9. Thomaz E. Essa I. Abowd G.D. A practical approach for recognizing eating moments with wrist-mounted inertial sensing Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing Osaka, Japan 7–11 September 2015 ACM New York, NY, USA 2015 1029 1040 10. Ranjan J. Whitehouse K. Object hallmarks: Identifying object users using wearable wrist sensors Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing Osaka, Japan 7–11 September 2015 ACM New York, NY, USA 2015 51 61 11. Hernandez J. Picard R.W. SenseGlass: Using Google Glass to sense daily emotions Proceedings of the Adjunct Publication of the 27th Annual ACM Symposium on User Interface Software and Technology Honolulu, HI, USA 5–8 October 2014 ACM New York, NY, USA 2014 77 78 12. Hernandez J. McDuff D. Picard R.W. BioWatch: Estimation of heart and breathing rates from wrist motions Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare Istanbul, Turkey 20–23 May 2015 ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) Ghent, Belgium 2015 169 176 13. Mazilu S. Blanke U. Troster G. Gait, wrist, and sensors: Detecting freezing of gait in Parkinson’s disease from wrist movement Proceedings of the Pervasive Computing and Communication Workshops (PerCom Workshops) St. Louis, MO, USA 23–27 March 2015 IEEE Piscataway, NJ, USA 2015 579 584 14. Kostopoulos P. Nunes T. Salvi K. Deriaz M. Torrent J. Increased Fall Detection Accuracy in an Accelerometer-Based Algorithm Considering Residual Movement Proceedings of the International Conference on Pattern Recognition Applications and Methods Lisbon, Portugal 10–12 January 2015 15. Casilari E. Oviedo-Jiménez M.A. Automatic fall detection system based on the combined use of a smartphone and a smartwatch PLoS ONE 2015 10 e0140929 10.1371/journal.pone.0140929 26560737 16. Mariakakis A. Parsi S. Patel S.N. Wobbrock J.O. Drunk User Interfaces: Determining Blood Alcohol Level through Everyday Smartphone Tasks Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems Montreal, QC, Canada 21–26 April 2018 ACM New York, NY, USA 2018 234 17. Kao H.L.C. Ho B.J. Lin A.C. Chu H.H. Phone-based gait analysis to detect alcohol usage Proceedings of the 2012 ACM Conference on Ubiquitous Computing Pittsburgh, PA, USA 5–8 September 2012 ACM New York, NY, USA 2012 661 662 18. Arnold Z. Larose D. Agu E. Smartphone Inference of Alcohol Consumption Levels from Gait Proceedings of the Healthcare Informatics (ICHI) Dallas, TX, USA 21–23 October 2015 IEEE Piscataway, NJ, USA 2015 417 426 19. Dai J. Teng J. Bai X. Shen Z. Xuan D. Mobile phone based drunk driving detection Proceedings of the Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS Munich, Germany 22–25 March 2010 IEEE Piscataway, NJ, USA 2010 1 8 20. Goswami T.D. Zanwar S.R. Hasan Z.U. Android Based Rush and Drunk Driver Alerting System Int. J. Eng. Res. Appl. 2014 4 50 53 21. Thien N.H. Venkatesan P. Muntsinger T. Horizontal Gaze Nystagmus Detection in Automotive Vehicles Available online: https://users.ece.cmu.edu/~nht/NystagmusDetectionReport.pdf (accessed on 18 April 2022) 22. Wilson J. Avakov A. Image Processing Methods For Mobile Horizontal Gaze Nystagmus Sobriety Check Available online: https://www.semanticscholar.org/paper/Image-Processing-Methods-For-Mobile-Horizontal-Gaze-Wilson-Avakov/2c7c8763653e36ea518bf35d445c71bc5a95a7ea (accessed on 18 April 2022) 23. Texas District & County Attorneys Association Field-Sobriety-Test-Review 2016 Available online: http://www.tdcaa.com/dwi/field-sobriety-test-review (accessed on 18 April 2022) 24. Hossain N. Hu T. Feizi R. White A.M. Luo J. Kautz H. Inferring fine-grained details on user activities and home location from social media: Detecting drinking-while-tweeting patterns in communities arXiv 2016 1603.03181 25. NHTSA DWI Dection and Standardized Field Sobriety Testing (SFST) Refresher 2015 Available online: https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/sfst_ig_refresher_manual.pdf (accessed on 18 April 2022) 26. Globalwebindex GWI-Device-Summary 2014 Available online: http://cdn2.hubspot.net/hub/304927/file-2301369304-pdf/Reports/GWI_Device_Summary_Q3_2014.pdf?submissionGuid=fb7e899d-fda2-4064-b520-cc77d08df121 (accessed on 18 April 2022) 27. Manifest T. 3 Ways Google Can Compete with Apple in the Wearables Market 2019 Available online: https://themanifest.com/app-development/3-ways-google-compete-apple-wearables-market (accessed on 18 April 2022) 28. Basaran C. Yoon H.J. Ra H.K. Son S.H. Park T. Ko J. Classifying children with 3D depth cameras for enabling children’s safety applications Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing Seattle, WA, USA 13–17 September 2014 ACM New York, NY, USA 2014 343 347 29. Hazan I. Shabtai A. Noise Reduction of Mobile Sensors Data in the Prediction of Demographic Attributes Proceedings of the Second ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft’15 Florence, Italy 16–17 May 2015 IEEE Press Piscataway, NJ, USA 2015 117 120 30. Zhang M. Sawchuk A.A. A feature selection-based framework for human activity recognition using wearable multimodal sensors Proceedings of the 6th International Conference on Body Area Networks Beijing, China 7–8 November 2011 ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) Ghent, Belgium 2011 92 98 31. Zhang M. Sawchuk A.A. Motion primitive-based human activity recognition using a bag-of-features approach Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium Miami, FL, USA 28–30 January 2012 ACM New York, NY, USA 2012 631 640 32. Cook L.G. Mitschow L.C. Beyond the polygraph: Deception detection and the autonomic nervous system Fed. Pract. 2019 36 316 321 31384120 33. Wyatt K.D. Poole L.R. Mullan A.F. Kopecky S.L. Heaton H.A. Clinical evaluation and diagnostic yield following evaluation of abnormal pulse detected using Apple Watch J. Am. Med. Inform. Assoc. 2020 27 1359 1363 Available online: http://xxx.lanl.gov/abs/https://academic.oup.com/jamia/article-pdf/27/9/1359/34153322/ocaa137.pdf (accessed on 18 April 2022) 10.1093/jamia/ocaa137 32979046

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095384 ijerph-19-05384 Review SARS-CoV-2 Circulation in the School Setting: A Systematic Review and Meta-Analysis https://orcid.org/0000-0002-2262-1102 Caini Saverio 1 Martinoli Chiara 2 https://orcid.org/0000-0003-1441-897X La Vecchia Carlo 3 Raimondi Sara 2 Bellerba Federica 2 D’Ecclesiis Oriana 2 https://orcid.org/0000-0002-5163-5837 Sasso Clementina 4 https://orcid.org/0000-0002-2202-6055 Basso Alessandra 5 Cammarata Giulio 2 https://orcid.org/0000-0002-1348-4548 Gandini Sara 2* Tchounwou Paul B. Academic Editor 1 Institute for Cancer Research, Prevention, and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy; s.caini@ispro.toscana.it 2 Department of Experimental Oncology, European Institute of Oncology (IEO), IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy; martinoli.chiara@gmail.com (C.M.); sara.raimondi@ieo.it (S.R.); federica.bellerba@ieo.it (F.B.); oriana.decclesiis@ieo.it (O.D.); giulio.cammarata@ieo.it (G.C.) 3 Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20133 Milan, Italy; carlo.lavecchia@unimi.it 4 The Italian National Institute for Astrophysics (INAF)-Osservatorio Astronomico di Capodimonte, Salita Moiariello 16, 80131 Naples, Italy; clementina.sasso@inaf.it 5 Centre for Philosophy of Social Science (TINT), Unit of Practical Philosophy, Department of Political and Economic Studies, University of Helsinki, P.O. Box 24, 00014 Helsinki, Finland; alessandra.basso@helsinki.fi * Correspondence: sara.gandini@ieo.it 28 4 2022 5 2022 19 9 538413 3 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The contribution of children to viral spread in schools is still debated. We conducted a systematic review and meta-analysis of studies to investigate SARS-CoV-2 transmission in the school setting. Literature searches on 15 May 2021 yielded a total of 1088 publications, including screening, contact tracing, and seroprevalence studies. MOOSE guidelines were followed, and data were analyzed using random-effects models. From screening studies involving more than 120,000 subjects, we estimated 0.31% (95% confidence interval (CI) 0.05–0.81) SARS-CoV-2 point prevalence in schools. Contact tracing studies, involving a total of 112,622 contacts of children and adults, showed that onward viral transmission was limited (2.54%, 95% CI 0.76–5.31). Young index cases were found to be 74% significantly less likely than adults to favor viral spread (odds ratio (OR) 0.26, 95% CI 0.11–0.63) and less susceptible to infection (OR 0.60; 95% CI 0.25–1.47). Lastly, from seroprevalence studies, with a total of 17,879 subjects involved, we estimated that children were 43% significantly less likely than adults to test positive for antibodies (OR 0.57, 95% CI 0.49–0.68). These findings may not applied to the Omicron phase, we further planned a randomized controlled trial to verify these results. SARS-CoV-2 infections schools students teachers susceptibility contract tracing meta-analysis screening uropean Union’s Horizon Europe Research and Innovation Program under Grant Agreement101046016 This research received contributions from the EuCARE Project funded by the European Union’s Horizon Europe Research and Innovation Program under Grant Agreement No 101046016 and the Fondazione Invernizzi and Fondazione CARIPLO, Chance Project. ==== Body pmc1. Introduction The global public health crisis due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has brought distinct challenges to the care of children and adolescents. School closures have been implemented internationally as a common strategy to control the spread of SARS-CoV-2 during the pandemic on the basis of the assumption that children may represent important vectors for viral spread. According to UNESCO, 188 countries have imposed countrywide school closures, affecting more than 1.5 billion children and youth, and schooling has been disrupted for an average of 25 weeks worldwide from the beginning of the pandemic until March 2021, due to complete or partial closures (www.unesco.org (accessed on 12 March 2022)). The consequences of school closures could be dramatic. It has been estimated that over 100 million children will fall below the minimum proficiency level in reading due to the impact of COVID-19 school closures (www.unesco.org, accessed on 12 March 2022), and children with disabilities and special needs or those living in countries or areas with poor digital connectivity are especially hard to serve through remote schooling. Beyond providing instruction, school plays a pivotal role in child education, development, and wellbeing. According to UN reports, over 300 million children rely on school meals for a regular source of daily nutrition, and rising malnutrition is expected among the most vulnerable. Lockdowns and shelter-in-place measures have heightened the risk of children witnessing or suffering domestic violence and abuse. Use of online platforms for distance learning has the increased risk of exposure to inappropriate content and online predators, while risks to child mental health and wellbeing are also considerable (www.un.org, accessed on 12 March 2022). Although data collected from contact tracing and population studies have indicated that children and adolescents are less susceptible to SARS-CoV-2 infection when compared to adults, as shown in a recent meta-analysis [1], the contribution of children to viral spread is still under debate. In fact, given the typically mild clinical course of COVID-19 in younger age [2,3], symptom-based testing may have underestimated infection in children, and unrecognized viral circulation may still occur at school, potentially raising community infection rates. Schools provide a highly regulated environment which is well suited to the investigation of potential COVID-19 exposure [4,5,6,7]. The objective of this study was to carry out a comprehensive review of the literature and a meta-analysis covering the evidence on SARS-CoV-2 transmission in the educational setting, collecting data from publications on the prevalence of SARS-CoV-2 positivity, serosurveys, and contact tracing studies. In particular the aims were to estimate SARS-CoV-2 infections detected in schools comparing positive rates found from screening and contact tracing methods, to compare infectivity and susceptibility of students compared to school staff, and to investigate reasons of between-study heterogeneity. 2. Materials and Methods 2.1. Search Strategy and Selection Criteria We included any original study (article, communication, report), peer-reviewed publication, or pre-print which reported a quantitative estimation of SARS-CoV-2 transmission in the school setting. We excluded reviews, meta-analyses, and modeling studies. Studies performed in special settings were included in the systematic review but excluded from the meta-analysis. We planned and conducted a systematic literature search and review following MOOSE guidelines regarding the meta-analysis of observational studies. We performed a systematic literature review using validated search strategies from the following databases: PUBMED (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi, accessed on 15 May 2021), Ovid MEDLINE database, ISI Web of Science: Science Citation Index Expanded (SCI Expanded), and Living Evidence on COVID database (https://zika.ispm.unibe.ch/assets/data/pub/search_beta/, accessed on 15 May 2021), to identify papers on SARS-CoV-2 transmission in the educational setting (see flowchart in Figure 1). The search was undertaken on 15 May 2021. We used the search terms “screening (or point prevalence)”, “serosurvey (or seroprevalence)”, and “contact tracing” combined with “school (or education), children”. For PUBMED searches, we also limited the search to an age of birth–18 years and added the term “COVID (or COVID-19, or SARS-CoV-2)”. No language restriction was applied. The searches yielded a total of 1088 publications. After screening of titles and abstracts, as well as the removal of duplicates, 35 publications were selected for full-text review. After full-text review, six studies were deemed not eligible for the meta-analysis, and five additional studies were identified after a search of cited references in eligible publications. Finally, seven national and regional reports SARS-CoV-2 transmission in the educational setting fulfilling inclusion criteria were identified and included in the meta-analysis. Data were extracted and cross-checked independently by two investigators. The following information from the published papers was extracted and coded: publication type, country, size of the country, region, study period, study setting, study design, exposure to SARS-CoV-2, test method, test sample, number of subjects tested and testing positive in each category (students or staff), and proportions of positive subjects with 95% confidence interval (CI) and confounders adjusted for. In addition, number, age, and definition of index cases and their contacts were collected for contact tracing studies. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline [8]. Methodological quality of included studies was assessed on the basis of a critical appraisal checklist for prevalence studies (The Joanna Briggs Institute Critical Appraisal tools for use in JBI Systematic Reviews). 2.2. Data Analysis Inclusion criteria were as follows: (1) the study contains the minimum information necessary to obtain the percentages of positive subjects, or data to calculate risk estimates, by type of index case, and corresponding 95% CI (i.e., odds ratios or relative risks and a measure of uncertainty: standard errors, variance, confidence intervals, or exact p-value of the significance of the estimates); (2) the study is based on independent data to avoid giving double weight to a single study. In case of multiple reports of the same study, we considered the estimates from the most recent publications. Pooled estimates of percentages of positivity were obtained through random-effects models after Freeman–Tukey double arcsine transformation. In scenarios with zero cases, Haldane–Anscombe correction was used. All measures of association and the corresponding CI were translated into log relative risk and corresponding variance, using the formula proposed by Greenland et al. [9]. We used random-effects models, taking into account between-study and within-study variability when more than one estimate from a single study was used. The summary odds ratio (SOR) was obtained from the maximum likelihood estimate PROC MIXED in SAS, taking into account the model when more estimates were obtained from a single study. Homogeneity of effects across studies was assessed using the chi-square statistic and quantified by I2, which represents the percentage of total variation across studies that is attributable to heterogeneity rather than chance [10]. We obtained the SOR pooling the study-specific estimates through random-effects models. A funnel-plot-based approach was used for assessing publication bias evaluating regression of log(OR) on the sample size, weighted by the inverse of the variance, as suggested by Macaskill et al. [11]. To assess the influence of possible sources of bias, we considered the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist proposed for observational epidemiologic studies [12]. According to the STROBE checklist, using meta-regression, we evaluated factors influencing between-study heterogeneity. We also examine changes in results after exclusion of specific studies to evaluate the stability of the pooled estimates. Sensitivity analysis was carried out to evaluate whether results were influenced by single studies. All the statistical analyses were performed using SAS software (SAS Institute Inc., Cary, NC, USA; version 9.4) and R software, version 4.0.2 (http://www.r-project.org, accessed on 12 March 2022). Two-sided p-values less than 0.05 were considered statistically significant. 3. Results 3.1. SARS-CoV-2 Positivity Rates in Educational Settings (Screening Studies) We identified 22 studies that reported data on SARS-CoV-2 infections in diverse educational settings, from kindergartens and daycares to primary and high schools (Table S1 in the Supplementary Materials) [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33], involving more than 120,000 subjects. Sixteen studies were from Europe, five were from the US, and one was from Israel. Overall, studies documented SARS-CoV-2 positivity rates from the beginning of the pandemic in March 2020 until May 2021, including periods of low and high community transmission. Screening campaigns were organized by schools as part of mitigation measures to prevent the introduction of SARS-CoV-2 in their premises or by local and national authorities to monitor viral circulation among students, teachers, and nonteaching staff. Testing involved asymptomatic or oligosymptomatic participants, providing an indication of otherwise possibly unrecognized viral spread within educational settings. The vast majority of the studies were judged to be of high quality (80%, Table S4). The summary estimate of positivity rate assessed through implementation of the different screening methods was 0.44% (95% CI 0.13–0.92%), with high heterogeneity (I2 = 97%, Figure 2a). The difference in estimates between cross-sectional and cohort studies was significant (p = 0.03) with a remarkably lower prevalence among cross-sectional studies (0.31%, 95% CI 0.05–0.81%) compared to cohort studies (1.14%, 95% CI 0.01–4.19%) (Table 1). Sixteen studies reported SARS-CoV-2 point prevalence in a total of 112,131 subjects, including one study providing data collected during two rounds of testing within the COVID-19 Schools Infection Survey. A total of 326 coronavirus infections were detected. Overall, the estimated positivity rate was 0.31% (95% CI 0.05–0.81%), with high heterogeneity among studies (I2 = 95%, Table 1). Highest infections rates were reported in the two rounds of testing performed in England in November and December 2020, especially among high school students and staff. Excluding reports not published in peer-reviewed journals by April 2021, the summary estimate of positivity rate was slightly greater, 0.40% (95% CI 0.05–1.07%), but still below 1%. Six cohort studies reported results of multiple testing performed on a total of 12,838 subjects. Multiple testing, especially when intensive schedules over a prolonged period are implemented, may provide indications on the cumulative viral spread within the analyzed educational settings. Overall, estimated positivity rate was 1.14% (95% CI 0.01–4.19%), with high heterogeneity among studies (I2 = 98%, Table 1). The highest number of cases was detected in the study of Crowe and colleagues [28], who identified 46 infections in 773 asymptomatic staff and students (5.6%) from three schools engaged in a pilot program with weekly testing over a 5 week period in November 2020 in Omaha, US. Biweekly testing led to the identification of 25 cases out of 1180 participants (2.1%) over 3 month period in the study by Volpp and colleagues in New Jersey, US (15–22 samples collected on average from each participant, for a total of 21,449 test performed) [20], while only one case out of 5210 participants (0.02%) was detected in a 4 week study performed in Dusseldorf, Germany (34.068 tested samples, up to eight tests per subject) [17]. Two rounds of testing 1 week apart identified one case out of 707 participants in Swiss students and staff participating to Ciao corona study [29], while 16 samples tested positive out of the 3431 collected from 1251 students and staff (1.3% positive subjects) of two schools in Rome, Italy, over a 3 month period [23]. Lastly, Gillespie and colleagues reported the experience of two US schools that implemented strong mitigation measures for reopening [19], including weekly testing for students and staff. Here, nine rounds of universal testing led to the identification of 81 SARS-CoV-2-infected individuals out of the 3720 participants (2.2%), with an additional 23 infections identified through contact tracing and 33 self-reported COVID-19 cases. Nine cross-sectional studies and five cohort studies reported infections detected in children and in adults separately, including one reporting estimates for two rounds of testing (Table S1 in the Supplementary Materials). Children and adults showed comparable SARS-CoV-2 positivity rates in most studies, and the pooled OR estimate was 0.83 (95% CI: 0.53–1.29), with low heterogeneity (I2 = 41%, Figure 2b). We found an indication for publication bias (p = 0.03). Similar results were observed in cross-sectional studies (pooled OR = 0.98; 95% CI 0.74–1.32, I2 = 23%) and cohort studies (pooled OR = 0.62; 95% CI 0.20–1.94, I2 = 4%) (Table 1). 3.2. SARS-CoV-2 Seroprevalence in Educational Settings (Serosurveys) We identified nine studies that reported data on SARS-CoV-2 seroprevalence in educational settings providing in-person activities [14,16,18,27,34,35,36,37,38], with a total of 17,879 subjects involved (Table S2 in the Supplementary Materials). All studies were performed in Europe during 2020. While the above-described point prevalence cross-sectional studies inform on the rates of current infections, cross-sectional serosurveys inform on cumulative exposure to the virus for tested participants. We also identified three cohort studies assessing prevalence of antibodies for SARS-CoV-2 at different timepoints, with participants tested twice to examine longitudinal changes of seroprevalence [27,37,38], and we included the most recent testing in our metanalysis. The majority of the studies were judged to be of high quality (70%, Table S5). The overall seropositive rate was 3.9% (95% CI 1.15–8.19%), with high heterogeneity among studies (I2 = 100%, Figure 3a). The difference in estimates between cross-sectional and cohort studies was statistically significant (p = 0.005), with estimates obtained from cohort studies indicating 10% positivity (10.31%; 95% CI 2.44–22.74%), compared to a lower prevalence of 1.5% from cross-sectional studies (1.49%, 95% CI 0.07–4.69%) (Table 1). Six studies were performed during the first semester of 2020, with antibodies assessed during or shortly after the first wave of the pandemic, including three studies focused on attendance to schools and daycares that remained exceptionally open during national lockdowns. Although the seroprevalence differed among the three studies, authors reported comparable seroprevalence in groups of children not attending school (0.5% versus 1% and 1.4% versus 2.7%, respectively, for children attending in person or staying at home), as well as in adults who did not have occupational contact with children or COVID-19-positive patients (7.7% for daycare staff and 5.5% for the comparator adult group), suggesting that exceptional schooling did not boost SARS-CoV-2 spread in the analyzed settings. In line with these observations, low seroprevalence reported in three additional cross-sectional studies adds up to the indication that schools did not develop into silent hotspots for viral transmission during the first wave of the pandemic [14,18,35], likely due to the successful implementation of extensive preventive measures. In this regard, it is noteworthy to mention two studies reporting seroprevalence in students from a small city in north France and from a large community school in Santiago, Chile [39,40]. In both cases, school-based COVID-19 outbreaks occurred at the very onset of the pandemic and in the absence of preventive measures, leading to 38.1% and 43.4% seropositive pupils and teachers, respectively, in one French high school [39] and 9.9% and 16.6% seropositive students and staff in the Chilean study [40]. In the three cohort studies [27,37,38], increased seroprevalence was recorded during the second study visit, which took place after the summer break or in December 2020. In their study, Ulyte and colleagues reported that SARS-CoV-2 seroprevalence raised from 3% in the summer to 4.5% in late autumn in school children in the canton of Zurich, Switzerland [37]. Interestingly, among the children who participated in both testing rounds, 28/70 (40%) who were initially seropositive became seronegative, while seroconversion (previously seronegative participants who became seropositive) was 5% (109/2153). The estimated rate of ever-positive children was, therefore, 7.8% [37]. Serial blood sampling was also implemented in a secondary school in Dresden, Germany [38]. Here, antibody positivity rates increased from 1.7% to 6.8% during the 6 week study period, and all the participants who tested positive at the initial visit (5/5) remained positive at the second visit. Lastly, data collected within the COVID-19 Schools Infection Survey showed high initial antibody positivity rates, consistent with the study designed to oversample schools in areas of England where coronavirus infection was highest at the start of the academic year (September 2020), with a nonsignificant increase in pupils (7.7% to 9% and 11% to 13.5% for primary and secondary school, respectively) and staff (12.5% to 15%) testing positive for SARS-CoV-2 antibodies between November and December 2020. In this study, 7.3% (20/276) of staff who initially tested positive had no detectable antibodies in the second round. Separate seroprevalence estimates for children and adults were available for six studies (Table S2 in the Supplementary Materials) [16,18,27,34,35,36]. School-aged children had lower antibody positivity rates when compared with adults (parents or school staff) in 4/6 studies (Figure 3b). The pooled OR for children was 0.57 (95% CI 0.49–0.68), significantly lower than adults, with low heterogeneity among studies (I2 = 21%). No indication of publication bias was found (p = 0.42). 3.3. Onward Transmission of SARS-CoV-2 in Educational Settings (Contact Tracing) Studies analyzing onward transmission of SARS-CoV-2 offered the possibility to test more specifically the infectivity and susceptibility to infection of children linked to educational settings. We identified 15 studies that reported data on transmission of SARS-CoV-2 in schools with available information on the number of contacts of index cases (Table S3 in the Supplementary Materials) [16,41,42,43,44,45,46,47,48,49,50,51,52,53,54]. Six studies were from Europe, five were from the USA, and two were from Israel, along with one each from South Korea and Australia. A total of 112,622 contacts of children and adults who were physically present at school while positive for SARS-CoV-2 were identified. Molecular testing for SARS-CoV-2 was normally offered to all contacts exposed to SARS-CoV-2, except for one study [48]. In this study, only symptomatic contacts were tested, so asymptomatic secondary cases were not captured. The majority of the studies were judged to be of high quality (60%, Table S6). When considering any-age index cases and their contacts of any age, the pooled secondary attack rate (SAR) was 2.54% (95% CI 0.76–5.31%), with high heterogeneity among studies (I2 = 100%, Figure 4a). The highest attack rate (13.5%) was recorded within a large outbreak in a high school in Jerusalem, Israel linked to two student index cases and likely promoted by inadequate preventive measures (crowded classes, exemption from facemasks, and continuous air conditioning due to an extreme heatwave) [46]. High attack rates were also recorded in two US-based studies, both reporting transmission with index cases of any age. Doyle and colleagues investigated COVID-19 in primary and secondary schools in Florida during the first semester of school reopening [49]. Of the 63,654 of COVID-19 cases registered between August and December 2020 in school-aged children, 60% were not school-related, and <1% of registered students were identified as having school-related COVID-19. Contact tracing investigations identified 86,832 persons who had a close school contact with these cases; among these, 37,548 received testing and 10,092 received a positive SARS-CoV-2 test result, leading to a 11.6% secondary attack rate. A prospective investigation of SARS-CoV-2 transmission was also performed in a Georgia school district during a period of peak community COVID-19 incidence [55]. Tracing of 86 index cases identified 1005 contacts, of whom 644 were tested and 59 received a positive SARS-CoV-2 test result (SAR = 5.9%). Highest SARs were identified in the setting of indoor sports and staff interactions. On the other hand, extremely low attack rates (<1%) were found in five studies reporting from five nations and two continents and describing transmission of SARS-CoV-2 in a school setting from the early onset of the pandemic (one pediatric case among the first reported cases in France who visited three schools and one ski class while infected generated 172 contacts and one secondary case) until November 2020 [42]. Three studies reported on viral transmission from young (age < 18 years) or adult index cases (Table S3 in the Supplementary Materials) [41,44,52]. In all studies, the proportion of contacts infected by young index cases was lower compared to adult index cases (Figure 4b). The pooled OR was 0.26 (95% CI 0.11–0.63), indicating a significant threefold reduced infectivity for children compared with adults. No indication for publication bias was found (p = 0.59). Six studies reported estimates of viral transmission to young or adult contacts (Table S3 in the Supplementary Materials) [41,44,46,50,51,53]. The pooled OR was 0.60 (95% CI 0.25–1.47), indicating a not statistically significant reduced susceptibility to SARS-CoV-2 infection for children compared to adults (Figure 4c). No indication of publication bias was found (p = 0.65). 4. Discussion The findings of this systematic review and meta-analysis confirm that schools did not develop into hotspots for SARS-CoV-2 transmission, as already emerged from the contact tracing study by Gandini et al. [55], which did not support the hypothesis of school openings as a driver of the second wave of COVID-19 in Italy, a large European country with high incidence of SARS-CoV-2. Likewise, another Italian study analyzed SARS-CoV-2 seroprevalence among school-aged children between September 2020 and January 2021 in Milan. The overall seroconversion rate was 10%, with no differences found between students who attended school compared to those who started remote learning in the first days of November, and most patients (61%) reporting that contact with a confirmed COVID-19 patient occurred within the household. The authors concluded that schools did not amplify SARS-CoV-2 transmission, but rather mirrored the level of the transmission in the community [56]. A Japanese study published in Nature also concluded that there was no causal effect of school closures on the spread of SARS-CoV-2 in spring 2020 [57]. Recent publications are in agreement with results found in this meta-analysis showing that students are less susceptible and less infective, with a large Italian study showing that secondary infections occurred more frequently when the index case was a teacher than a student (37% vs. 10%, p = 0.007) [55]. Bark et al. [58] assessed infections in kindergartens in Canada and found that school-based transmissions of SARS-CoV-2 were rare and clusters were small. Staff members accounted for 53.8% of index cases even if they were 14.3% of the school population. A recent Swedish study confirmed that keeping lower-secondary schools open had a minor impact on the overall spread of SARS-CoV-2 in society despite a twofold increase in infection rate found in teachers compared to students [59]. A study carried out in Australia showed that the majority of events (66%) had no evidence of onward transmission. Furthermore, when outbreaks did occur, they were mostly small (<10 cases) and more common when the first case was an adult (age > 16) [60]. A recent study conducted in USA investigated differences among three waves and among different working places, finding that schools experienced 11% of identified outbreaks, yet involved just 4% of total cases, whereas adult education outbreaks (2%) accounted for disproportionately more cases (9%). The authors concluded that schools were not the key driver of the latest wave in infections [61]. Some studies found an increase in infections with opening of schools, but they are mainly modeling studies [62,63]. Although infection can and does occur in schools, modeling studies have indicated limited viral spread when mitigation measures are adopted [64]. In particular, one modeling study concluded that weekly testing of 75% of unvaccinated students, in addition to symptom-based testing, would reduce cases by about 35% compared with symptom-based testing alone. Regular testing would also reduce student-days lost by up to 80% compared with reactive class closures [65]. Reviewing the experience of different schools showed that health behavioral policies adopted before the vaccination helped in mitigating the risk of viral spread in educational settings. In particular, contact tracing was very useful to promptly isolate infected staff and students. We found fivefold greater frequency of positive tests with contact tracing compared to screening, and these results suggests that we need a randomized clinical trial to verify whether testing all subjects in schools, independently of symptoms, helps in reducing clusters. Engagement of all stakeholders (school staff members, students, and their parents or legal guardians) in the implementation of school-based policies, as well as individual adherence to shared recommendations, is essential for minimizing the COVID-19 transmission chain. Many governments have ordered school closures to prevent contagions. Numerous studies have shown that this decision had a negative impact not only on the learning loss [66] in students but also on their mental health [67,68]. In particular, it appears that the students most affected were those who were younger and from families with low socioeconomic status [69]. Our meta-analysis could be a tool to help balance the pros and cons of school closures and eliminate the inequities that the pandemic has brought. There are some limitations of this study to highlight. Firstly, the risk estimates of each study were calculated from the minimum necessary information in the respective articles included, such that not all possible confounding factors could be taken into account and the risk estimates were not fully adjusted. Secondly, there was significant between-study heterogeneity and publication bias in some scenarios. Thirdly, the majority of the articles analyzed presented data from observational studies with some potential sources of bias. However this is the first meta-analysis investigating all sources of between-study heterogeneity, study designs, countries, methods adopted to investigate infections, and age to be able to have information about causal associations [70]. During the period of conduct of each study, mitigation measures of COVID-19 were put in place, and we cannot exclude that these contributed to the decrease in the spread of the virus in schools. Furthermore, we did not have enough information to quantify the impact of those measures. A recent randomized trial revealed, in line with our findings, low infection rates in school contacts, with a very small number of positive school contacts (around 2%) [71], and daily contact testing of school-based contacts was noninferior to self-isolation for the control of COVID-19 transmission. 5. Conclusions Testing all subjects in schools, independently of symptoms, revealed that students are less likely than adults to favor viral spread, and SARS-CoV-2 circulation in schools was found to be limited. These findings may not apply to the Omicron phase. We are therefore planned a clinical trial to confirm the results of this meta-analysis (https://eucareresearch.eu/activities/school-studies/the-interventional-lolli-study/, accessed on 12 March 2022). This study, while based on observational studies, presents interesting hypotheses to encourage the planning and conduct of randomized controlled experiments. Acknowledgments F.B. is a PhD student within the European School of Molecular Medicine (SEMM). Supplementary Materials The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijerph19095384/s1: Table S1. Studies on screening for SARS-CoV-2 infections; Table S2. Studies on serosurveys for antibodies to SARS-CoV-2; Table S3. Studies on contact tracing; Table S4. Studies on screening for SARS-CoV-2 infections: quality evaluation; Table S5. Studies on serosurveys for antibodies to SARS-CoV-2: quality evaluation; Table S6. Studies on contact tracing: quality evaluation. Click here for additional data file. Author Contributions Conceptualization, S.G. and C.M.; methodology, C.M., S.R., C.L.V. and S.G.; software, O.D.; validation, S.C., S.R., C.L.V. and S.G.; formal analysis, S.G., C.S., G.C. and F.B.; investigation, S.C., G.C., C.M., A.B., O.D. and C.S.; writing—original draft preparation, C.M., O.D. and S.G.; writing—review and editing, S.C., G.C., C.M., A.B., C.S. and S.G.; visualization, F.B. and S.G.; supervision, S.G. and S.R.; funding acquisition S.G. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Not applicable as this is a review and meta-analysis of published data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart of study. Figure 2 Pooled estimates for SARS-CoV-2 screening studies [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33]. (a) Pooled estimate of testing positive for SARS-CoV-2. (b) Summary odds ratio of testing positive for SARS-CoV-2 for children versus adults linked to educational settings. Figure 3 Pooled estimates for SARS-CoV-2 seroprevalence studies [14,16,18,27,34,35,36,37,38]. (a) Pooled estimate of testing positive for antibodies for SARS-CoV-2. (b) Pooled estimate of odds of testing positive for antibodies for SARS-CoV-2 for children versus adults. Figure 4 Pooled estimates for contact tracing studies [16,41,42,43,44,45,46,47,48,49,50,51,52,53,54]. (a) Pooled estimate of testing positive for SARS-CoV-2 after a contact with a case in the school setting. (b) Summary OR of testing positive for SARS-CoV-2 after a contact with a young versus an adult case in the school setting. (c) Summary OR of testing positive for SARS-CoV-2 in young versus adults after a contact with a case. ijerph-19-05384-t001_Table 1 Table 1 Summary estimates. n Summary Low 95% CI Up 95% CI I2 (%) Study Design p-Value % SARS-CoV-2 positivity Contract tracing * 15 2.54 0.76 5.31 100 Screening 22 0.44 0.13 0.92 97 6 1.14 0.01 4.19 98 Cohorts 0.03 16 0.31 0.05 0.81 95 Cross-sectionals Serosurvey 9 3.90 1.15 8.19 100 3 10.31 2.44 22.74 98 Cohorts 0.005 6 1.49 0.07 4.69 88 Cross-sectionals OR for young vs. old Susceptibility in contract tracing 6 0.60 0.25 1.47 63 Infectivity in contract tracing 3 0.26 0.11 0.63 44 Screening 15 0.83 0.53 1.29 41 5 0.62 0.20 1.94 69 Cohorts 0.56 10 0.98 0.74 1.32 23 Cross-sectionals Serosurvey 6 0.57 0.46 0.68 21 * Evaluated considering contacts as denominators instead of screened subjects; p-value from meta-regression for study design. OR: Odd Ratios. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Viner R.M. Mytton O.T. Bonell C. Melendez-Torres G.J. Ward J. Hudson L. Waddington C. Thomas J. Russell S. van der Klis F. Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared with Adults: A Systematic Review and Meta-analysis JAMA Pediatrics 2021 175 143 156 10.1001/jamapediatrics.2020.4573 32975552 2. Ludvigsson J.F. Systematic review of COVID-19 in children shows milder cases and a better prognosis than adults Acta Paediatr. 2020 109 1088 1095 10.1111/apa.15270 32202343 3. Tsankov B.K. Allaire J.M. Irvine M.A. Lopez A.A. Sauvé L.J. Vallance B.A. Jacobson K. Severe COVID-19 Infection and Pediatric Comorbidities: A Systematic Review and Meta-Analysis Int. J. Infect. Dis. 2021 103 246 256 10.1016/j.ijid.2020.11.163 33227520 4. Xu W. Li X. Dozier M. He Y. Kirolos A. Lang Z. Mathews C. Siegfried N. Theodoratou E. What is the evidence for transmission of COVID-19 by children in schools? A living systematic review J. Glob. Health 2020 10 021104 10.7189/jogh.10.021104 33437465 5. Li X. Xu W. Dozier M. He Y. Kirolos A. Lang Z. Song P. Theodoratou E. The role of children in the transmission of SARS-CoV2: Updated rapid review J. Glob. Health 2020 10 021101 10.7189/jogh.10.0201101 33312511 6. Gettings J. Czarnik M. Morris E. Haller E. Thompson-Paul A.M. Rasberry C. Lanzieri T.M. Smith-Grant J. Aholou T.M. Thomas E. Mask Use and Ventilation Improvements to Reduce COVID-19 Incidence in Elementary Schools—Georgia, November 16–December 11, 2020 MMWR Morb. Mortal. Wkly. Rep. 2021 70 779 784 10.15585/mmwr.mm7021e1 34043610 7. van den Berg P. Schechter-Perkins E.M. Jack R.S. Epshtein I. Nelson R. Oster E. Branch-Elliman W. Effectiveness of 3 Versus 6 ft of Physical Distancing for Controlling Spread of Coronavirus Disease 2019 among Primary and Secondary Students and Staff: A Retrospective, Statewide Cohort Study Clin. Infect. Dis. 2021 73 1871 1878 10.1093/cid/ciab230 33704422 8. Moher D. Liberati A. Tetzlaff J. Altman D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement Open Med. 2009 3 e123 e130 21603045 9. Greenland S. Quantitative methods in the review of epidemiologic literature Epidemiol. Rev. 1987 9 1 30 10.1093/oxfordjournals.epirev.a036298 3678409 10. Thompson S.G. Higgins J.P. How should meta-regression analyses be undertaken and interpreted? Stat. Med. 2002 21 1559 1573 10.1002/sim.1187 12111920 11. Macaskill P. Walter S.D. Irwig L. A comparison of methods to detect publication bias in meta-analysis Stat. Med. 2001 20 641 654 10.1002/sim.698 11223905 12. von Elm E. Altman D.G. Egger M. Pocock S.J. Gøtzsche P.C. Vandenbroucke J.P. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies J. Clin. Epidemiol. 2008 61 344 349 10.1016/j.jclinepi.2007.11.008 18313558 13. Desmet S. Ekinci E. Wouters I. Decru B. Beuselinck K. Malhotra-Kumar S. Theeten H. No SARS-CoV-2 carriage observed in children attending daycare centers during the intial weeks of the epidemic in Belgium J. Med. Virol. 2021 93 1828 1831 10.1002/jmv.26689 33230857 14. Szépfalusi Z. Schmidthaler K. Sieber J. Kopanja S. Götzinger F. Schoof A. Hoz J. Willinger B. Makristathis A. Weseslindtner L. Lessons from low seroprevalence of SARS-CoV-2 antibodies in schoolchildren: A cross-sectional study Pediatr. Allergy Immunol. 2021 32 762 770 10.1111/pai.13459 33512035 15. Mossong J. Mombaerts L. Veiber L. Pastore J. Coroller G.L. Schnell M. Masi S. Huiart L. Wilmes P. SARS-CoV-2 transmission in educational settings during an early summer epidemic wave in Luxembourg, 2020 BMC Infect. Dis. 2021 21 417 10.1186/s12879-021-06089-5 33947340 16. Kriger O. Lustig Y. Cohen C. Amit S. Biber A. Barkai G. Talmi L. Gefen-Halevi S. Mechnik B. Regev-Yochay G. The Sheba Medical Center healthcare workers’ children’s school: Can we open schools safely? Clin. Microbiol. Infect. 2021 27 474.e1 474.e3 10.1016/j.cmi.2020.11.030 33309698 17. Lübke N. Schupp A.K. Bredahl R. Kraus U. Hauka S. Andrée M. Ehlkes L. Klein T. Graupner A. Horn J. Screening for SARS-CoV-2 infections in daycare facilities for children in a large city in Germany medRxiv 2021 medRxiv: 2021.02.26.21252510 10.1101/2021.02.26.21252510 18. Hommes F. van Loon W. Thielecke M. Abramovich I. Lieber S. Hammerich R. Gehrke-Beck S. Linzbach E. Schuster A. von dem Busche K. SARS-CoV-2 Infection, Risk Perception, Behaviour and Preventive Measures at Schools in Berlin, Germany, during the Early Post-Lockdown Phase: A Cross-Sectional Study Int. J. Environ. Res. Public Health 2021 18 2739 10.3390/ijerph18052739 33800392 19. Gillespie D.L. Meyers L.A. Lachmann M. Redd S.C. Zenilman J.M. The Experience of 2 Independent Schools with In-Person Learning During the COVID-19 Pandemic J. Sch. Health 2021 91 347 355 10.1111/josh.13008 33768529 20. Volpp K.G. Kraut B.H. Ghosh S. Neatherlin J. Minimal SARS-CoV-2 Transmission After Implementation of a Comprehensive Mitigation Strategy at a School—New Jersey, 20 August–27 November 2020 MMWR Morb. Mortal. Wkly. Rep. 2021 70 377 381 10.15585/mmwr.mm7011a2 33735161 21. Cooper D.M. Zulu M.Z. Jankeel A. Ibraim I.C. Ardo J. Kasper K. Stephens D. Meyer A. Stehli A. Condon C. SARS-CoV-2 acquisition and immune pathogenesis among school-aged learners in four diverse schools Pediatr. Res. 2021 90 1073 1080 10.1038/s41390-021-01660-x 34304252 22. Hoch M. Vogel S. Eberle U. Kolberg L. Gruenthaler V. Fingerle V. Ackermann N. Sing A. Liebl B. Huebner J. Feasibility and Diagnostic Accuracy of Saliva-Based SARS-CoV-2 Screening in Educational Settings and Children Aged <12 Years Diagnostics 2021 11 1797 10.3390/diagnostics11101797 34679495 23. Villani A. Coltella L. Ranno S. Bianchi di Castelbianco F. Murru P.M. Sonnino R. Mazzone T. Piccioni L. Linardos G. Chiavelli S. School in Italy: A safe place for children and adolescents Ital. J. Pediatr. 2021 47 23 10.1186/s13052-021-00978-w 33531046 24. Doron S. Ingalls R.R. Beauchamp A. Boehm J.S. Boucher H.W. Chow L.H. Corridan L. Goehringer K. Golenbock D. Larsen L. Weekly SARS-CoV-2 screening of asymptomatic kindergarten to grade 12 students and staff helps inform strategies for safer in-person learning Cell Rep. Med. 2021 2 100452 10.1016/j.xcrm.2021.100452 34723225 25. Bordi L. Parisi G. Sberna G. Amendola A. Mariani B. Meoni G. Orazi D. Bartoletti P. Lombardozzi L. Barca A. Effective screening strategy against SARS-CoV-2 on self-collected saliva samples in primary school setting: A pilot project J. Infect. 2021 83 e8 e10 10.1016/j.jinf.2021.05.013 34023366 26. Azienda Sanitaria Locale Liguria (ASL3) Report Settimanale Sull’Attività di Screening Nelle Scuole—Aggiornamento al 29 Maggio 2021 Available online: https://www.asl3.liguria.it/components/com_publiccompetitions/includes/download.php?id=16954:dati-screening-scuole-covid-19.pdf (accessed on 30 May 2021) 27. Judd A. COVID-19 Schools Infection Survey, England: Round 4, Antibody Data, March 2021 Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/covid19schoolsinfectionsurveyengland/round4antibodydatamarch2021 (accessed on 28 May 2021) 28. Crowe J. Schnaubelt A.T. SchmidtBonne S. Angell K. Bai J. Eske T. Nicklin M. Pratt C. White B. Crotts-Hannibal B. Assessment of a Program for SARS-CoV-2 Screening and Environmental Monitoring in an Urban Public School District JAMA Netw. Open. 2021 4 e2126447 10.1001/jamanetworkopen.2021.26447 34550382 29. Kriemler S. Ulyte A. Ammann P. Peralta G.P. Berger C. Puhan M.A. Radtke T. Surveillance of Acute SARS-CoV-2 Infections in School Children and Point-Prevalence During a Time of High Community Transmission in Switzerland Front. Pediatr. 2021 9 645577 10.3389/fped.2021.645577 33796490 30. Comune di Pesaro Il Sindaco Scrive alla Regione, «Ora Serve Screening Periodico per Istituti Superiori e Medie. In Caso di Risposta Negativa, Pronti a Ripeterlo» Available online: http://www.comune.pesaro.pu.it/novita-in-comune/dettaglio/news/il-sindaco-scrive-alla-regione-ora-serve-screening-periodico-per-istituti-superiori-e-medie-in-ca/?tx_news_pi1%5Bcontroller%5D=News&tx_news_pi1%5Baction%5D=detail&cHash=4251e47288443964cf5db0ffc41e2303 (accessed on 9 February 2021) 31. Comune dell’Aquila Screening: Oggi 1800 Tamponi, 2 Dubbi Available online: https://www.comune.laquila.it/index.php?id_oggetto=3&id_doc=7725&id_sez_ori=&template_ori=2 (accessed on 21 February 2021) 32. Comune di Pesaro Screening “Scuole sicure” Della Dora e Ceccarelli: «Operazione Necessaria. Tamponi Unica Arma per Evitare altri Contagi» Available online: http://www.comune.pesaro.pu.it/novita-in-comune/dettaglio/news/screening-scuole-sicure-della-dora-e-ceccarelli-operazione-necessaria-tamponi-unica-arma-per-e/?tx_news_pi1%5Bcontroller%5D=News&tx_news_pi1%5Baction%5D=detail&cHash=7d1d874e167ff90dd12b31b58ba7702c (accessed on 9 March 2021) 33. Comune dell’Aquila Coronavirus, screening della popolazione scolastica a Sassa: 299 tamponi tutti negativi Available online: https://www.comune.laquila.it/index.php?id_oggetto=3&id_cat=0&id_doc=7908&id_sez_ori=17&template_ori=3&&gtp=1 (accessed on 19 May 2021) 34. Tönshoff B. Müller B. Elling R. Renk H. Meissner P. Hengel H. Garbade S.F. Kieser M. Jeltsch K. Grulich-Henn J. Prevalence of SARS-CoV-2 Infection in Children and Their Parents in Southwest Germany JAMA Pediatr. 2021 175 586 593 10.1001/jamapediatrics.2021.0001 33480966 35. Kirsten C. Unrath M. Lück C. Dalpke A.H. Berner R. Armann J. SARS-CoV-2 seroprevalence in students and teachers: A longitudinal study from May to October 2020 in German secondary schools BMJ Open 2021 11 e049876 10.1136/bmjopen-2021-049876 36. Lachassinne E. de Pontual L. Caseris M. Lorrot M. Guilluy C. Naud A. Dommergues M.A. Pinquier D. Wannepain E. Hausherr E. SARS-CoV-2 transmission among children and staff in daycare centres during a nationwide lockdown in France: A cross-sectional, multicentre, seroprevalence study Lancet Child Adolesc. Health 2021 5 256 264 10.1016/S2352-4642(21)00024-9 33571450 37. Ulyte A. Radtke T. Abela I.A. Haile S.R. Berger C. Huber M. Schanz M. Schwarzmueller M. Trkola A. Fehr J. Clustering and longitudinal change in SARS-CoV-2 seroprevalence in school children in the canton of Zurich, Switzerland: Prospective cohort study of 55 schools BMJ 2021 372 n616 10.1136/bmj.n616 33731327 38. Armann J.P. Kirsten C. Galow L. Kahre E. Haag L. Dalpke A. Lück C. Berner R. SARS-CoV-2 transmissions in students and teachers: Seroprevalence follow-up study in a German secondary school in November and December 2020 BMJ Paediatr. Open 2021 5 e001036 10.1136/bmjpo-2021-001036 34192197 39. Fontanet A. Tondeur L. Grant R. Temmam S. Madec Y. Bigot T. Grzelak L. Cailleau I. Besombes C. Ungeheuer M.N. SARS-CoV-2 infection in schools in a northern French city: A retrospective serological cohort study in an area of high transmission, France, January to April 2020 Euro. Surveill. 2021 26 2001695 10.2807/1560-7917.ES.2021.26.15.2001695 33860747 40. Torres J.P. Piñera C. De La Maza V. Lagomarcino A.J. Simian D. Torres B. Urquidi C. Valenzuela M.T. O’Ryan M. Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Prevalence in Blood in a Large School Community Subject to a Coronavirus Disease 2019 Outbreak: A Cross-sectional Study Clin. Infect. Dis. 2021 73 e458 e465 10.1093/cid/ciaa955 32649743 41. Macartney K. Quinn H.E. Pillsbury A.J. Koirala A. Deng L. Winkler N. Katelaris A.L. O’Sullivan M.V.N. Dalton C. Wood N. Transmission of SARS-CoV-2 in Australian educational settings: A prospective cohort study Lancet Child Adolesc. Health 2020 4 807 816 10.1016/S2352-4642(20)30251-0 32758454 42. Danis K. Epaulard O. Bénet T. Gaymard A. Campoy S. Botelho-Nevers E. Bouscambert-Duchamp M. Spaccaferri G. Ader F. Mailles A. Cluster of Coronavirus Disease 2019 (COVID-19) in the French Alps, February 2020 Clin. Infect. Dis. 2020 71 825 832 10.1093/cid/ciaa424 32277759 43. Yoon Y. Kim K.R. Park H. Kim S. Kim Y.J. Stepwise School Opening and an Impact on the Epidemiology of COVID-19 in the Children J. Korean Med. Sci. 2020 35 e414 10.3346/jkms.2020.35.e414 33258334 44. Heavey L. Casey G. Kelly C. Kelly D. McDarby G. No evidence of secondary transmission of COVID-19 from children attending school in Ireland, 2020 Eurosurveillance 2020 25 2000903 10.2807/1560-7917.ES.2020.25.21.2000903 45. Ehrhardt J. Ekinci A. Krehl H. Meincke M. Finci I. Klein J. Geisel B. Wagner-Wiening C. Eichner M. Brockmann S.O. Transmission of SARS-CoV-2 in children aged 0 to 19 years in childcare facilities and schools after their reopening in May 2020, Baden-Württemberg, Germany Euro. Surveill. 2020 25 2001587 10.2807/1560-7917.ES.2020.25.36.2001587 46. Stein-Zamir C. Abramson N. Shoob H. Libal E. Bitan M. Cardash T. Cayam R. Miskin I. A large COVID-19 outbreak in a high school 10 days after schools’ reopening, Israel, May 2020 Euro. Surveill. 2020 25 2001352 10.2807/1560-7917.ES.2020.25.29.2001352 47. Jordan I. Fernandez de Sevilla M. Fumado V. Bassat Q. Bonet-Carne E. Fortuny C. Garcia-Miquel A. Jou C. Adroher C. Melé Casas M. Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Children in Summer Schools Applying Stringent Control Measures in Barcelona, Spain Clin. Infect. Dis. 2022 74 66 73 10.1093/cid/ciab227 33709138 48. Nelson E.J. McKune S.L. Ryan K.A. Lednicky J.A. Crowe S.R. Myers P.D. Morris J.G. Jr. SARS-CoV-2 Positivity on or After 9 Days Among Quarantined Student Contacts of Confirmed Cases JAMA 2021 325 1561 1562 10.1001/jama.2021.2392 33605978 49. Doyle T. Kendrick K. Troelstrup T. Gumke M. Edwards J. Chapman S. Propper R. Rivkees S.A. Blackmore C. COVID-19 in Primary and Secondary School Settings During the First Semester of School Reopening—Florida, August–December 2020 MMWR Morb. Mortal. Wkly. Rep. 2021 70 437 441 10.15585/mmwr.mm7012e2 33764962 50. Brandal L.T. Ofitserova T.S. Meijerink H. Rykkvin R. Lund H.M. Hungnes O. Greve-Isdahl M. Bragstad K. Nygård K. Winje B.A. Minimal transmission of SARS-CoV-2 from paediatric COVID-19 cases in primary schools, Norway, August to November 2020 Euro. Surveill. 2021 26 2002011 10.2807/1560-7917.ES.2020.26.1.2002011 51. Larosa E. Djuric O. Cassinadri M. Cilloni S. Bisaccia E. Vicentini M. Venturelli F. Giorgi Rossi P. Pezzotti P. Bedeschi E. Secondary transmission of COVID-19 in preschool and school settings in northern Italy after their reopening in September 2020: A population-based study Euro. Surveill. 2020 25 2001911 10.2807/1560-7917.ES.2020.25.49.2001911 52. Gettings J.R. Gold J.A.W. Kimball A. Forsberg K. Scott C. Uehara A. Tong S. Hast M. Swanson M.R. Morris E. Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Georgia School District-United States, December 2020–January 2021 Clin. Infect. Dis. 2022 74 319 326 10.1093/cid/ciab332 33864375 53. Hershow R.B. Wu K. Lewis N.M. Milne A.T. Currie D. Smith A.R. Lloyd S. Orleans B. Young E.L. Freeman B. Low SARS-CoV-2 Transmission in Elementary Schools—Salt Lake County, Utah, 3 December 2020–31 January 2021 MMWR Morb. Mortal. Wkly. Rep. 2021 70 442 448 10.15585/mmwr.mm7012e3 33764967 54. Dawson P. Worrell M.C. Malone S. Tinker S.C. Fritz S. Maricque B. Junaidi S. Purnell G. Lai A.M. Neidich J.A. Pilot Investigation of SARS-CoV-2 Secondary Transmission in Kindergarten Through Grade 12 Schools Implementing Mitigation Strategies—St. Louis County and City of Springfield, Missouri, December 2020 MMWR Morb. Mortal. Wkly. Rep. 2021 70 449 455 10.15585/mmwr.mm7012e4 33764961 55. Gandini S. Rainisio M. Iannuzzo M.L. Bellerba F. Cecconi F. Scorrano L. A cross-sectional and prospective cohort study of the role of schools in the SARS-CoV-2 second wave in Italy Lancet Reg. Health Eur. 2021 5 100092 10.1016/j.lanepe.2021.100092 34104904 56. Barcellini L. Forlanini F. Sangiorgio A. Gambacorta G. Alberti L. Meta A. Gaia P. Amendola A. Tanzi E. Massa V. Does school reopening affect SARS-CoV-2 seroprevalence among school-age children in Milan? PLoS ONE 2021 16 e0257046 10.1371/journal.pone.0257046 34473776 57. Fukumoto K. McClean C.T. Nakagawa K. No causal effect of school closures in Japan on the spread of COVID-19 in spring 2020 Nat. Med. 2021 27 2111 2119 10.1038/s41591-021-01571-8 34707318 58. Bark D. Dhillon N. St-Jean M. Kinniburgh B. McKee G. Choi A. SARS-CoV-2 transmission in kindergarten to grade 12 schools in the Vancouver Coastal Health region: A descriptive epidemiologic study CMAJ Open 2021 9 E810 E817 10.9778/cmajo.20210106 34429325 59. Vlachos J. Hertegård E. BSvaleryd H. The effects of school closures on SARS-CoV-2 among parents and teachers Proc. Natl. Acad. Sci. USA 2021 118 e2020834118 10.1073/pnas.2020834118 33574041 60. Ryan K. Snow K. Danchin M. Mulholland K. Goldfeld S. Russell F. SARS-CoV-2 infections and public health responses in schools and early childhood education and care centres in Victoria, Australia: An observational study Lancet Reg. Health West Pac. 2022 19 100369 10.1016/j.lanwpc.2021.100369 35098182 61. Lakha F. King A. Swinkels K. Lee A.C.K. Are schools drivers of COVID-19 infections-an analysis of outbreaks in Colorado, USA in 2020 J. Public Health 2022 44 e26 e35 10.1093/pubmed/fdab213 62. Di Domenico L. Pullano G. Sabbatini C.E. Boëlle P.Y. Colizza V. Modelling safe protocols for reopening schools during the COVID-19 pandemic in France Nat. Commun. 2021 12 1073 10.1038/s41467-021-21249-6 33594076 63. Li Y. Campbell H. Kulkarni D. Harpur A. Nundy M. Wang X. Nair H. Usher Network for COVID-19 Evidence Reviews (UNCOVER) group. The temporal association of introducing and lifting non-pharmaceutical interventions with the time-varying reproduction number (R) of SARS-CoV-2: A modelling study across 131 countries Lancet Infect. Dis. 2021 21 193 202 10.1016/S1473-3099(20)30785-4 33729915 64. Lasser J. Sorger J. Richter L. Thurner S. Schmid D. Klimek P. Assessing the impact of SARS-CoV-2 prevention measures in Austrian schools using agent-based simulations and cluster tracing data Nat. Commun. 2022 13 554 10.1038/s41467-022-28170-6 35087051 65. Colosi E. Bassignana G. Contreras D.A. Poirier C. Boëlle P.Y. Cauchemez S. Yazdanpanah Y. Lina B. Fontanet A. Barrat A. Screening and vaccination against COVID-19 to minimise school closure: A modelling study Lancet Infect. Dis. 2022 Online ahead of print 10.1016/S1473-3099(22)00138-4 66. Engzell P. Frey A. Verhagen M.D. Learning loss due to school closures during the COVID-19 pandemic Proc. Natl. Acad. Sci. USA 2021 118 e2022376118 10.1073/pnas.2022376118 33827987 67. Lee J. Mental health effects of school closures during COVID-19 Lancet Child Adolesc. Health 2020 4 421 10.1016/S2352-4642(20)30109-7 32302537 68. Monnier M. Moulin F. Thierry X. Vandentorren S. Côté S. Barbosa S. Falissard B. Plancoulaine S. Charles M.A. Simeon T. Children’s mental and behavioral health, schooling, and socioeconomic characteristics during school closure in France due to COVID-19: The SAPRIS project Sci. Rep. 2021 11 22373 10.1038/s41598-021-01676-7 34789783 69. Hammerstein S. König C. Dreisörner T. Frey A. Effects of COVID-19-Related School Closures on Student Achievement-A Systematic Review Front. Psychol. 2021 12 746289 10.3389/fpsyg.2021.746289 34603162 70. Stuart E.A. Dowdy D.W. Evidence-based COVID-19 policy-making in schools Nat. Med. 2021 27 2078 2079 10.1038/s41591-021-01585-2 34824459 71. Young B.C. Eyre D.W. Kendrick S. White C. Smith S. Beveridge G. Nonnenmacher T. Ichofu F. Hillier J. Oakley S. Daily testing for contacts of individuals with SARS-CoV-2 infection and attendance and SARS-CoV-2 transmission in English secondary schools and colleges: An open-label, cluster-randomised trial Lancet 2021 398 1217 1229 10.1016/S0140-6736(21)01908-5 34534517

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093261 materials-15-03261 Article Research on Low-Frequency Noise Control of Automobiles Based on Acoustic Metamaterial Liao Yi 1† Huang Haibo 2† Chang Guangbao 1 Luo Deyang 1 Xu Chuanlai 34* Wu Yudong 5* Tang Jiyou 2 Matikas Theodore E. Academic Editor 1 SAIC GM WULING Automobile Co., Ltd., Liuzhou 545005, China; yi.liao1@sgmw.com.cn (Y.L.); guangbao.chang1@sgmw.com.cn (G.C.); deyang.luo@sgmw.com.cn (D.L.) 2 School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China; huanghaibo214@my.swjtu.edu.cn (H.H.); jyt@my.swjtu.edu.cn (J.T.) 3 Sichuan Jiuzhou Electric Group Co., Ltd., No. 6 Jiuhua Road, Mianyang 621000, China 4 Sichuan Avionics System Product Lightweight Design and Manufacturing Engineering Laboratory, Mianyang 621000, China 5 National Laboratory of Rail Transit (in Preparation), Chengdu 610031, China * Correspondence: xuchuanlai@163.com (C.X.); wu045043@my.swjtu.edu.cn (Y.W.) † These authors contributed equally to this work. 01 5 2022 5 2022 15 9 326108 3 2022 14 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). With the transformation of the trend of vehicle electrification, the overall noise level in the vehicle is gradually reduced. The problem of low-frequency noise in the vehicle, which was previously ignored, is becoming more and more prominent. To solve the vehicle low-frequency noise problem, a combination of real-vehicle tests and simulation analysis is carried out. During the test, the driver and passengers feel that there is a relatively obvious low-frequency roar noise in the car, which results from the structural radiation noise of the trunk door vibration. Therefore, to solve this problem, we design an acoustic metamaterial with lightweight and miniaturized features based on the local resonance principle of phononic crystals. Firstly, the selection of the resonant unit configuration and the design of the band gap are implemented. Then, the layout planning of the whole vehicle, the layout of the resonance unit and the design of the base frame are implemented. The actual vehicle test results show that: after attaching the designed acoustic metamaterial, the low-frequency noise sound pressure levels in the front and rear of the vehicle were reduced by 2.0 dB (A) and 2.3 dB (A), respectively, meanwhile, the interior noise sound quality was improved. The sound pressure level at the driver’s right ear in the car has an abnormal peak of around 35Hz. In addition, the driver and passengers feel that there is a relatively obvious low-frequency roar noise in the car, and through low-pass filtering of the collected signals, it is confirmed that the peak frequency is the main cause of the low-frequency roar in the car. The low-frequency steady-state noise of the car is generally considered to be the low-frequency vibration of the body panel and the radiation occurs. Through the finite element simulation analysis (Grid Participation Analysis) of the abnormal peak frequency, the results show that the low-frequency roar is caused by the low-frequency vibration of the tailgate sheet metal, and the problem peak frequency is not coupled with the acoustic cavity mode. Facing the problem of the low-frequency roar radiated into the car by the vibration of the tailgate sheet metal parts, based on the local resonance band gap theory, we developed a design to suppress the 35 Hz vibration of the tailgate sheet metal parts and meet the characteristics of lightweight and miniaturization. By attaching the acoustic metamaterial to the tailgate and performing CAE simulation of the whole vehicle, it is determined that the structure can indeed reduce the 35 Hz noise in the car and the peak value of the tailgate sheet metal vibration. acoustic metamaterial local resonance low-frequency roar noise control steady-state noise ==== Body pmc1. Introduction In the field of automotive NVH (Noise, Vibration, Harshness), high-frequency noise and vibration control can achieve ideal results through acoustic packaging or attaching vibration damping, but controlling the radiation caused by the vibration of automotive sheet metal parts low-frequency noise has always been a major and difficult problem in the field of automotive noise and vibration control [1,2,3]. For automobiles, the low-frequency noise and vibration problems radiated into the car caused by the vibration of sheet metal parts will not only seriously affect the ride comfort of the driver and passengers, but also have a great impact on the driving safety and service life of the car [4]. In order to obtain a more comfortable and safe driving and riding environment, and to improve the market competitiveness of vehicles, it is extremely important to control the low-frequency noise radiated into the vehicle by the vibration of the automobile sheet metal parts [5]. The generation path of low-frequency noise radiated by automobile (tailgate) sheet metal parts is shown in Figure 1. The car is driving on rough roads, and the displacement excitation of the road is transmitted to the body sheet metal parts through the tire–suspension system [6]. Excitation generates low-frequency vibration and radiates low-frequency structural noise into the car, causing serious discomfort to passengers and drivers [7,8]. At present, there are three main ways to reduce the vibration of sheet metal parts in response to the problem of low-frequency noise radiated by the vibration of automobile sheet metal parts at home and abroad [9,10]. First, using spring-damping vibration-reducing materials or rubber vibration-reducing materials. With the development of current industrial technology, it is found that the use of spring-damping vibration-reducing materials or rubber damping vibration-reducing materials has a more obvious effect on high-frequency vibration, but it is difficult to achieve an ideal suppression effect of the middle and low-frequency noise [11]. Second, applying reinforcing ribs to the sheet metal parts to increase the natural frequency of the low-frequency band of the sheet metal structure by increasing the rigidity, but the structure of the automobile sheet metal parts is greatly changed which will cause the production cost of the model to increase sharply, and seriously affect the economic benefits of the enterprise [12]. Third, installing the dynamic vibration absorber, but its cost is higher and the mass is higher [13]. In view of the above problems, the local resonance type vibration-damping acoustic metamaterial with negative dynamic equivalent parameter characteristics provides a new idea for noise control of low-frequency vibration radiation of automobile sheet metal parts [14,15,16,17,18,19]. In recent years, studies on the locally resonant phonon crystal formed by the periodic arrangement of elastomers and mass scatterers have been studied with great vigor [20]. Since the band gap produced by it is not limited by the size of the unit cell, it has a broad application market for low-frequency vibration and noise reduction in automobiles. In 2000, when Liu Zhengyou et al. studied the three-dimensional phononic crystal formed by the cubic lattice structure of lead balls coated with viscoelastic silicone rubber soft material and embedded in epoxy resin, they found that the wavelength of the phononic crystal forbidden band is much larger [21]. Due to the size of the lattice, it breaks through the limitation of the Bragg scattering mechanism and can control elastic waves two orders of magnitude lower than the resonant unit. Moreover, the scatterers are not strictly periodic or even randomly distributed, the composite structure also has a band gap effect [22]. This puts forward the local resonance mechanism of the elastic wave band gap, which provides a new theoretical basis for the follow-up automotive low-frequency noise and vibration control field [23]. In 2001, BAZ introduced active control to study the transmission characteristics of elastic waves in periodic beams with two materials alternately arranged, gave the corresponding simplified theoretical analysis model of the spring–mass system, explained the active adjustment method of passband and forbidden band, and proposed the directional design method of local resonance type acoustic metamaterial [24]. In 2008, Hong Kong University of Science and Technology Yang Zhiyu and others proposed a thin-film acoustic metamaterial based on the local resonance theory [25,26,27]. The lightweight structure with a thickness as low as millimeters successfully achieved outstanding sound insulation capabilities in the low-frequency range of 500~800 Hz, which provided a new solution for low-frequency noise reduction. The elastic film needs external tension to propagate the vibration [28]. As the stiffness of the elastic film is very low and the performance is unstable, a small change in tension will cause a frequency shift of tens or even hundreds of hertz. Therefore, no matter from a theoretical or technical point of view, effective control of film tension is very necessary. In 2015, Ma Fuyin and others at Xi’an Jiaotong University proposed a square lattice thin-film acoustic sound insulation metamaterial that requires almost no tension by increasing the thickness of the film [29]. In 2019, Niu Jiamin and others from Xi’an Jiaotong University proposed that under the asymmetric mode, the overall sound absorption performance of the structure has been greatly improved, and the sound absorption bandwidth has been expanded from the original narrow frequency to a wide frequency [30]. In summary, although local resonance acoustic metamaterials seem to be relatively new products now, there are a lot of data on the research of its mechanism, and there are also certain physical samples to verify its vibration suppression effect. However, the current acoustic metamaterials developed by technical institutions have poor stability and the vibration suppression frequency is difficult to reduce to less than 100 Hz. The acoustic metamaterial research is almost limited to simulation design and theoretical research. Focusing on the problem of the low-frequency roar radiated into the car by the vibration of the tailgate sheet metal of a certain vehicle model, based on the theory of local resonance bandgap, a design is designed to suppress the 35 Hz vibration of the tailgate sheet metal with stable and small equivalent stiffness. Through the vehicle finite element simulation, it is verified that the structure can indeed reduce the 35 Hz noise peak in the vehicle and reduce the vibration of the tailgate sheet metal parts, thereby providing a new idea and new solution for the field of vehicle low-frequency noise and vibration control. 2. Basic Theory of Local Resonance Acoustic Metamaterial 2.1. Elastic Wave Equation in Acoustic Metamaterial An acoustic metamaterial is a kind of man-made periodic composite structure material, which is developed from crystals in solid mechanics [31,32]. Therefore, the theory of the energy band of crystals in solid mechanics is also applicable to periodic composite structures. The content of acoustic metamaterial exploration is the propagation of elastic waves in the medium, and the band gap is due to the special effects of elastic waves when they are transmitted in the structure [33]. According to the knowledge of elastic dynamics theory, under the condition of ensuring an ideal elastic medium, small displacement and no initial stress, consider any particle in the homogeneous acoustic metamaterial medium, and use the displacement method used in solving dynamic problems to accurately establish three types of equations describing the relationship between the mass point force, displacement, stress and strain in the acoustic metamaterial are as follows: Differential Equation of Motion:(1) ∂σx∂x+∂τyx∂y+∂τzx∂z+ρx=ρ∂2uαt2 (2) ∂τxy∂x+∂σy∂y+∂τzy∂z+ρy=ρ∂2vαt2 (3) ∂τxz∂x+∂τyz∂y+∂σz∂z+ρz=ρ∂2wαt2 Geometric Equation:(4) εx=∂u∂x  γyz=∂w∂y+∂v∂z (5) εy=∂v∂y  γzx=∂u∂z+∂w∂x (6) εz=∂w∂x  γxy=∂v∂x+∂u∂y Physical Equation:(7) σx=λθt+2μεx τyz=μγy (8) σy=λθt+2μεy τzx=μγz (9) σz=λθt+2μεz τxy=μγx The above equation involves the six components of the stress tensor (σx, σy, σz, τyz, τzx, τxy), six components of strain tensor (γxy,γxz,γyz,εx, εy,εz) and three displacement components (u, v, w), a total of 15 unknowns of spatial coordinates x, y, z and time t. σx is the normal stress, τxy is the shear stress, ρ is mass point density, γx is shear strain, εx is the normal strain, λ,μ are Lame coefficients, θt=εx+εy+εz. Not every equation contains the unknowns in the above equation, by using a displacement method often used to solve the equation of elastic dynamics, considering some of these unknown function hypotheses into the mathematic expression of the “basic unknown functions”, it can be brought into the rest of the equation, and can obtain the expressed in the displacement of stress components, the final three displacements as unknown functions derived the elastic dynamics equation:(10) (λ+2μ)∇(∇∗μ→)−μ∇∗∇u→+ρw2u→=0 In the equation, u→ is the displacement vector; λ, μ are the Lame coefficient; ρ is the density of the medium; ∇ is the Laplace operator; the relation between them and the wave velocity is expressed as: Longitudinal wave velocity: Cl=(λ+2μ)/ρ, Shear wave velocity: Ct=μ/ρ. 2.2. Acoustic Metamaterial Band Gap Mechanism When the vibrational elastic wave propagates in the local resonant phonon crystal, it will be affected by the periodic elastic scatterers, and the elastic wave within a certain intrinsic frequency range cannot continue to propagate through the elastic scatterers, which is called the forbidden band of the acoustic metamaterial. Other eigenfrequency ranges that can pass through these elastic scatterers without obstruction are called passbands. As shown in Figure 2a, it is a typical phonon crystal structure with local resonance. The structure is composed of mass scatterers, an elastic coating layer and matrix. The structure can be simplified to a typical spring–mass system, as shown in Figure 2b. The mass scatterers are composed of a dense metal material, which provides the mass component (expressed as m) for the cell structure. The elastic coating layer is composed of a thin film with certain elasticity, which provides the elastic component of the crystal cell structure (expressed as k). The matrix is rigid material (expressed as M), which is the carrier of vibration elastic wave transmission [34,35,36,37]. Suppose the displacement of matrix M and mass component m is X and x, the matrix excitation is F, and the reaction force of the mass component is F1. By Newton’s second law and Hooke’s law:(11) F−F1=(jw)2MX (12) F1=(jw)2mx (13) k(X−x)=F1 Consider the base body and spring–mass system as a whole:(14) me=M+mw02w02−w2 (15) H(w)=XF=−1mew2 In the equation: me is the system equivalent mass, H(w) is the system displacement frequency response function, ω is the natural circular frequency, w0=km is the natural frequency of the internal spring oscillator. It can be seen from the above formula that: with the change of external excitation frequency, the system shows different characteristics due to its different equivalent mass, as shown in Figure 3. According to Newton’s second law and Hooke’s law theory and the external excitation frequency and displacement frequency response function, the relationship between the dynamic equivalent quality of the system and the excitation frequency can be inferred, as shown in Table 1. In conclusion, the band gap is caused by the resonance of the internal mass component. The band gap range is determined by the natural frequency of the whole structure and internal mass component. The band gap effect occurs when the system is in the negative equivalent mass phase, the excitation frequency is in the range of [w0,w0(M+m)M]. Therefore, the frequency range generated by bandgap can be adjusted directionally by changing the mass or spring of the equivalent simplified model of the cell unit. Based on the above theory, according to the vibration frequency of auto sheet metal parts (equivalent to excitation frequency), an acoustic metamaterial can be designed to suppress the specific frequency. 3. Analysis of Low-Frequency Roaring in Car Aiming at the relatively obvious low-frequency roar (20–100 Hz) generated by a certain hatch car when it is running at a constant speed of 30 km/h on a rough road surface, the LMS equipment is used to collect the sound pressure level at the driver’s right ear and at the middle back passenger seat. Sound pressure sensors are arranged according to relevant national standards GB/T18697-2002, and the location of measuring points is shown in Figure 4. During the signal acquisition process, the adjustable seat is back as far as possible to put it in a vertical position. The test is empty, with only the driver and measurement of personnel in the car. Before the test we ensure that the car is in a closed state, the four-wheel positioning is normal and in the test environment, the influence of background noise is less than the allowable error. When the vehicle speed is adjusted to a constant speed of 30 km/h, LMS onboard equipment is used to collect the sound pressure signal inside the vehicle. The noise test results are shown in Figure 5. The test results show that the car has an obvious peak value at 35 Hz in the frequency range of 20–100 Hz. The peak value at 35 Hz in the right ear of the driver is 50.39 dB (A), and the peak value at 35 Hz in the middle of the passenger rear seat is 50.78 dB (A), as shown in Figure 4 (ordinate of Figure 4a is dB (A) and ordinate of Figure 4b is Pa). In the LMS test software, the collected signals were filtered to filter the peak value at 35 Hz, and the filtered noise signals were listened to by earphones, and it was found that the low-frequency roar had disappeared. Therefore, it can be determined that the low-frequency roar of this vehicle is caused by the peak noise at 35 Hz. As the peak frequency is very low, the continuous steady-state noise of low frequency is generally considered structural noise [38,39]. 3.1. Analysis of Interior Noise Problem Generally speaking, there are two ways to generate structural noise: the sound cavity mode of the whole vehicle and the coupled resonance of the body parts amplify the noise to form a low-frequency roar; the low-frequency vibration of body sheet metal radiates to the car, forming a low-frequency roar. In view of the above two approaches, this paper solves the acoustic cavity mode of the vehicle and analyzes the joint contribution of the panel parts based on the peak noise frequency of 35 Hz in the simulation analysis of road noise. The analysis process is shown in Figure 6. Through CAE simulation analysis, the sound mode of the vehicle has no resonance with the body parts at 35 Hz. Therefore, the peak noise frequency of 35 Hz is mainly caused by the vibration radiation of the automobile panel. 3.1.1. The Establishment of Finite Element Model In order to carry out acoustic cavity modal analysis, road noise simulation and body plate joint contribution analysis of the whole vehicle, it is necessary to establish the sound cavity finite element model and acoustic–solid coupled finite element model. The TB (Trim Body) body is further constructed on the basis of the finite element model of body-in-white that has been constructed and modified through tests, which includes all parts except the engine and chassis system, many of which are replaced by centralized unit mass and one-dimensional unit. Determine the modeling standards and guidelines between the connections of various components: (1) Modeling of spot welding structural adhesives. Spot welding structural adhesives are mainly used in key parts of the car body, which can greatly improve the stiffness of the car body when used in conjunction with welding spots. Modeling of RBE3-hexa-RBE3 for spot welding of structural adhesive. (2) Modeling of shock-absorbing expansion adhesive. Shock-absorbing expansion adhesive mainly connects the outer plate of the top cover with the beam of the top cover, the outer plate of the open and closed parts with the support plate or the inner plate, and mainly plays a shock-absorbing role. (3) Modeling of reinforcement plate and damping plate. A reinforcement glue plate is generally used for side circumference and rear door plates with a thickness of 1.5 mm. It mainly plays the role of stiffness reinforcement and has a certain damping dissipation function. (4) Seal strip modeling. The seal strip is simulated using BUSH (used to define the nominal property values for a generalized spring and damper structural element) or ELAST (used to define the stiffness and stress coefficient of a scalar elastic element) in three translational directions. (5) Limit buffer block modeling. A limit buffer block is mainly used in the engine room cover and back door, to play a shock absorption and support role. The BUSH element is used to simulate and only three translational stiffnesses are set. (6) Connection between car door lock and lock. The BUSH unit can be used to simulate the model car door lock and lock. (7) Hinge modeling for open and closed parts. The hinge needs solid grid modeling, the grid size can be set to 3–5 mm, and the solid grid requires at least three layers of body elements in the direction of thickness. If the hinge is modeled using a solid grid or a shell element, the stiffness of the hinge will be overestimated. Doors generally contain two hinges connected by RBE2 and CBEAM, and the RBE2 center of the two hinges should be set to be collinear to ensure doors can rotate freely around the hinge. The hinge shaft is simulated using three CBEAM units and releases rotational degrees of freedom at both ends. The TB finite element model established is shown in Figure 7. In Hypermesh 2017.01 software, Altair Engineering Inc. (Troy, MI, USA), we extract the inner surface of the body’s internal contact with air, to form a completely closed acoustic cavity model, which defines the spoke boundary as a fully rigid wall. When dividing the finite element mesh, it should be noted that the size of the acoustic element and the structural element should be consistent, and the acoustic element should have at least six elements in each wavelength range. As we are focusing on frequency within 100 Hz, the minimum wavelength λ = c/f = 344/100 = 3.44 m, and the maximum length of the sound cavity grid element is 0.52 m. In this paper, a hexahedral element with a side length of 50 mm is used to automatically divide the cavity mesh. The generated results of the finite element model of the body cavity are shown in Figure 8. The body structure and the sound cavity system are coupled through the vibration of the boundary nodes. In Hypermesh2017.01 software, the coupling between the structure and the sound cavity is realized by using the ACMODF card to search the structure nodes automatically through the nodes on the sound cavity boundary. The acoustic–solid coupling model of the body system is established as shown in Figure 9 (the left door and part of the side circumference are hidden to display the acoustic cavity model). 3.1.2. Simulation Results of Road Noise Based on the acoustic–solid coupled finite element model, the time-domain signals of acceleration measured by engineers on the actual road surface at the steering knuckle of the front and rear suspension are converted into PSD frequency-domain signal files to stimulate the four wheel cores of the vehicle, and the solution response points are the sound pressure level at the driver’s right ear and the middle sound pressure level of the rear passenger’s seat. The solution frequency range is set as 20–100 Hz. The comparison between the test data and the simulation data of road noise is shown in Figure 10 and Figure 11. The results show that the sound pressure level of the driver’s right ear and the middle of the passenger’s rear seat has an obvious peak value at 35 Hz in the low-frequency band, which is corresponding to the peak frequency of the test results of the real car and the overall trend is basically corresponding. The sound pressure level in the right ear of the real car test driver is 50.39 dB (A), and the simulation data is 49.30 dB (A). The test sound pressure level in the middle of the rear passenger row is 50.79 dB (A), and the simulation data is 50.50 dB (A). In the simulation and test, the difference in the sound pressure level between the driver’s right ear and the middle of the rear passenger’s row is relatively small at the peak point, indicating that the previous modified finite element model has high accuracy. In view of this kind of steady-state structural noise, the main contribution of the peak frequency can be effectively determined by analyzing the joint contribution of the body panel. 3.1.3. Analysis of Joint Contribution of Body Parts The control path of vehicle interior noise is generally: excitation source–transfer path–response point. For mass-produced models, it is very difficult to control the excitation source (chassis–suspension system). Modifying the chassis–suspension system will have a great impact on the smoothness, operation stability and safety performance of the whole vehicle, and the modification cost is huge. Therefore, for the noise problem of body vibration radiation, general enterprises tend to consider it from the perspective of transmission path (body sheet metal). The car body and the car sound cavity can be regarded as a closed cavity. The closed cavity sheet metal S low-frequency vibration radiates into the cavity to form the car’s low-frequency roar. Take a point inside the space O as the origin of coordinates, and the rest of the points in the space use it as a reference point. Assume that point J is a point on the closed cavity sheet metal part S, and its radiation sound pressure on a point i in the car is:(16) Pij(r0,w)=Pj(r,w)Qivi(r,w)σSj where Pij(r0,w) is the radiation sound pressure from point J to point I, Qi is the volume sound source at point i, Pj(r,w) is the sound pressure at point j, vi(r,w) is the speed that the sound source j transmits to point i, r0 is the distance from point i to point o, r is the distance from point j to point o, w is the frequency. Many points on the body closed cavity sheet metal parts S radiation noise to point i, and the proportion of point j is:(17) tj(w)=Pij(r0,w)P(r0,w) P(r0,w) is the total sound pressure at point i, and tj(w) is the contribution of point j on the body closed cavity sheet metal part S to the interior noise. When all the point contributions are plotted together, the contribution of each area to the interior acoustic radiation can be determined. Through the analysis of the contribution source of the nodes, the main contribution node area can be found, so as to determine the source of the low-frequency roar contribution. Analysis results of 35 Hz body panel joint contribution were extracted, as shown in Figure 12. The results show that the rear door has the largest contribution to 35 Hz noise. 3.1.4. Simulation Analysis of Vehicle Acoustic Cavity Mode In the process of driving a car, the sheet metal parts of the car body and other sealing components form a closed cavity, and the acoustic cavity mode of the car reflects the inherent properties of the interior air fluid. When the structure resonates with the acoustic cavity mode, the interior noise will be amplified to form the low-frequency roaring sound (20 Hz–100 Hz). By comparing the result of free mode analysis of the sound cavity with the noise in the car, it can be judged whether the 35 Hz noise in the car is caused by the resonance between the sound cavity and the body panel. The modal solution card was set up in the cavity finite element model established earlier, and the modal solution file was imported into Nastran14.0 solver for solving. Through calculation, the modal frequency and mode shape of the acoustic cavity of the structure are obtained in Table 2, Figure 13 and Figure 14: 3.2. Acoustic Metamaterial Design and Simulation Analysis 3.2.1. Establishment of Mathematical Model of Acoustic Metamaterial Through simulation, the front section has determined that the peak noise of 35 Hz in the car is mainly caused by low-frequency vibration radiation of the tail door. Therefore, according to the corresponding size structure of the plate of the tail door, an acoustic metamaterial with specific frequency suppression can be designed. According to the mathematical model of the tailgate, the installation position of the acoustic metamaterial is determined corresponding to the position of the red box shown in Figure 15 (the rectangular shape of the acoustic metamaterial is 60 × 204 × 3 mm, 1 is the inner panel of the tail door, 2 is the reinforced floor of the tail door, 3 is the outer panel of the tail door, 4 is the car tail door lock, and the red dotted box is the attachment position of the acoustic metamaterial of the tail door). The acoustic metamaterial is composed of three parts: Acoustic metamaterial matrix plate 5, adjustable mass block 6 and acoustic metamaterial damping layer 7, as is shown in Figure 16. The designed acoustic metamaterial is directly attached to the sheet metal parts of the tailgate through the magnetic damping layer, eliminating the need for a complicated installation process. The adjustable mass block and the cantilever beam in the acoustic metamaterial layer constitute a typical acoustic metamaterial spring–mass system, which directionally regulates the band gap frequency of the acoustic metamaterial by adjusting the weight of the mass block. 3.2.2. Frequency Design of Acoustic Metamaterial Resonance Element The mathematical model of acoustic metamaterial was imported into Hypermesh2017.01, which was processed by solid cutting and placed in the mapping state. A hexahedral mesh of 1mm was established for each cut entity. The total number of acoustic metamaterials grid is 40,324. Assign material attributes to each component, as shown in Table 3. After designing the modal solution card, it is imported into Nastran solver for solving the calculation. Based on the principle of local resonance of acoustic metamaterial, the resonance element has to produce local resonance with the sheet metal. The natural frequency of the resonant element is calculated as f=12πkm (k is the equivalent stiffness, m is the equivalent mass). By adjusting the thickness of attached mass block 6 (which is equivalent to changing the value of f by changing m in the calculation formula of natural frequency), the first-order natural frequency of each resonance element in the acoustic metamaterial is within the range of 35 ± 0.5 Hz. The adjusted calculation results are shown in Figure 17. The natural frequencies of each resonance unit are, respectively, 34.94 Hz, 34.94 Hz, 34.95 Hz, 34.95 Hz, 35.00 Hz and 35.00 Hz. 4. Results and Discussion After the corresponding acoustic metamaterial is designed, the acoustic metamaterial finite element model is attached to the design part, and the whole vehicle finite element model with the acoustic metamaterial attached to the tailgate is established, as shown in Figure 18 (in order to see the installation position of the acoustic metamaterial, the attached sheet metal parts is displayed transparently). The response points are the sound pressure level in the driver’s right ear, the middle pressure level in the rear passenger’s seat and the vibration acceleration in the middle of the tailgate panel. The same road noise excitation signal and excitation point positions as in Section 3 were used to conduct road noise simulation analysis and vibration response analysis of the plate metal parts of the tailgate before and after the attaching of the acoustic–solid coupled finite element model. The simulation results are shown in Figure 19, Figure 20, Figure 21 and Figure 22. By comparing the data before and after the acoustic metamaterial, the vibration and noise reduction effect of the acoustic metamaterial was verified. In the original state without an acoustic metamaterial attached, the sound pressure level at the driver’s right ear and the middle seat of the rear passenger’s seat has an obvious peak value at 35 Hz; the amplitude of the sound pressure level of the driver’s right ear at 35 Hz is 49.30 dB (A), and the amplitude of the sound pressure level of the passenger’s middle seat at 35 Hz is 50.50 dB (A). Under the condition of attached acoustic metamaterial, the amplitude of the sound pressure level in the driver’s right ear and the middle position of the passenger’s rear row is significantly reduced at 35 Hz. The amplitude of sound pressure level at 35 Hz in the driver’s right ear decreased from 49.30 dB (A) to 47.30 dB (A), and the improvement reached 2.0 dB (A). The amplitude of sound pressure level at 35 Hz in the middle of the passenger rear row decreased from 50.50 dB (A) to 48.20 dB (A), and the improvement reached 2.30 dB (A). In the original condition without attached acoustic metamaterial, the vibration acceleration of the tailgate panel appears at an obvious peak value of 35 Hz. In the vehicle coordinate system, the amplitude of vibration acceleration of the tailgate panel at 35 Hz in the x-direction is 139 m/s2, and the amplitude of vibration acceleration at 35 Hz in the z-direction is 175 m/s2. Under the acoustic metamaterial condition, the amplitude of vibration acceleration of the tailgate panel at 35 Hz was significantly reduced. The amplitude of vibration acceleration at the x-direction of 35 Hz of the tailgate panel is reduced from 139 m/s2 to 108 m/s2, and the improvement reaches 31 m/s2. The amplitude of vibration acceleration at z-direction 35 Hz of the tailgate sheet metal parts decreased from 175 m/s2 to 139 m/s2, and the improvement reached 36 m/s2. By comparing the data verified by the above simulation, it is found that the local resonant acoustic metamaterial has an ideal effect on the control of low-frequency noise radiated from the vibration of sheet metal parts to the vehicle. Regarding the durability of the device, components of acoustic metamaterial: aluminum plate and the damping layer have good durability and have been widely used in the automotive industry, its durability can meet the needs of mass production applications. In addition to that, the three-interval method of random vibration fatigue life calculation based on Gaussian distribution and Miner’s linear cumulative damage criterion shows that the structure can carry out infinite cycles under the random load, which meets the engineering requirements. 5. Conclusions Focusing on the problem of low-frequency noise in a certain car, this paper determines the frequency point of an abnormal peak value of noise in the car through test and simulation analysis. Through CAE simulation analysis, it is concluded that the low-frequency noise is caused by the low-frequency vibration of sheet metal parts of the tailgate. To solve this problem, an acoustic metamaterial is designed based on the band gap theory of local resonant phonon crystal. Through simulation verification, it is judged that the structure can indeed reduce the amplitude of interior noise and vibration acceleration, which verifies the effectiveness of the acoustic metamaterial. It provides a new way of thinking about the problem that the low-frequency noise of vibration and radiation of sheet metal parts is difficult to be controlled. Author Contributions Writing—original draft preparation, Y.L.; writing—review and editing, H.H.; investigation, G.C.; software, D.L.; methodology, C.X.; data curation, Y.W.; software, J.T. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by the Chinese National Science Foundation Grant (No. 51905408, 51775451). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Noise radiation path of rough road structure (tailgate). Figure 2 Typical local resonant acoustic metamaterial crystal cell structure and simplified model. (a) Typical acoustic metamaterial model, (b) Simplified acoustic metamaterial model. Figure 3 Relationship between external excitation frequency and displacement frequency response function. Figure 4 Position of sound pressure sensors. (a) driver’s seat, (b) passenger’s seat. Figure 5 Spectrum diagram of noise in the car. (a) Driver’s seat, (b) Passenger’s seat. Figure 6 CAE diagnostic analysis flow of low-frequency roaring in the car. Figure 7 TB finite element model. Figure 8 Acoustic cavity finite element model. Figure 9 Sound–solid coupling finite element model of the body system. Figure 10 Comparison of test results and simulation results of driver’s right ear noise. Figure 11 Comparison of test results and simulation results of passenger’s right ear noise. Figure 12 A 35 Hz cloud graph of plate joint contribution. Figure 13 Model vibration shape of the first-order acoustic cavity. Figure 14 Model vibration shape of the second-order acoustic cavity. Figure 15 Installation position of acoustic metamaterial (red dotted box). Figure 16 Mathematical model of acoustic metamaterial. (a) The designed local resonance acoustic metamaterial, (b) the local resonance unit. Figure 17 Natural frequency of acoustic metamaterial resonance element. (a) 34.94 Hz, (b) 34.94 Hz, (c) 34.95 Hz, (d) 34.95 Hz, (e) 35.00 Hz, (f) 35.00 Hz. Figure 18 Acoustic metamaterial finite element model attached to the vehicle. Figure 19 Comparison of sound pressure levels in the driver’s right ear. Figure 20 Comparison of sound pressure levels in the middle of rear passenger row. Figure 21 Comparison of x-direction vibration response of sheet metal parts of the tail door. Figure 22 Comparison of z-direction vibration response of sheet metal parts of tail door. materials-15-03261-t001_Table 1 Table 1 The relationship between system dynamic equivalent mass me and excitation frequency w. Excitation Frequency Range Dynamic Equivalent Mass System Movement Status w=0 me=M+m M and m move synchronously 0<w<w0 me>0 M and m move in the same direction w→w0 me→∞ M and m resonate, and the system vibration tends to be static w0<w<w0(M+m)M me<0 The equivalent mass is negative, M and m move in opposite directions w→w0(M+m)M me→0 Equivalent mass tends to 0, system resonance w>w0(M+m)M me>0 M and m move in the same direction w→∞ me→M m tends to stand still materials-15-03261-t002_Table 2 Table 2 Acoustic cavity modes table. Order Time Model Frequency Model Vibration Shape The first-order 49.98 Hz First-order longitudinal The second-order 94.63 Hz First-order lateral materials-15-03261-t003_Table 3 Table 3 Properties of acoustic metamaterial materials. Part Name Modulus of Elasticity (MPa) Density (T/mm3) Poisson’s Ratio Acoustic metamaterial Matrix Plate 5 71,000 2.7 × 10−9 0.3 Adjustable Mass Block 6 210,000 7.9 × 10−9 0.3 Acoustic metamaterial Damping Layer 7 3457 2.1 × 10−9 0.49 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Huang H.B. Wu J.H. Huang X.R. Yang M.L. Ding W.P. The development of a deep neural network and its application to evaluating the interior sound quality of pure electric vehicles Mech. Syst. Signal Process. 2019 120 98 116 10.1016/j.ymssp.2018.09.035 2. Rubino C. Bonet Aracil M. Gisbert-Payá J. Liuzzi S. Stefanizzi P. Zamorano Cantó M. Martellotta F. Composite eco-friendly sound absorbing materials made of recycled textile waste and biopolymers Materials 2019 12 4020 10.3390/ma12234020 31816936 3. Qin Y. Tang X. Jia T. Duan Z. Zhang J. Li Y. Zheng L. Noise and vibration suppression in hybrid electric vehicles: State of the art and challenges Renew. Sustain. Energy Rev. 2020 124 109782 10.1016/j.rser.2020.109782 4. Huang H.B. Wu J.H. Huang X.R. Ding W.P. Yang M.L. A novel interval analysis method to identify and reduce pure electric vehicle structure-borne noise J. Sound Vib. 2020 475 115258 10.1016/j.jsv.2020.115258 5. Wellmann T. Govindswamy K. Tomazic D. Impact of the future fuel economy targets on powertrain, driveline and vehicle NVH development SAE Int. J. Veh. Dyn. Stab. NVH 2017 1 428 438 10.4271/2017-01-1777 6. Wu J. Ma F. Application of acoustic metamaterials in low frequency vibration and noise reduction J. Mech. Eng. 2016 52 68 78 10.3901/JME.2016.13.068 7. Liu Z. Chan C.T. Sheng P. Three-component elastic wave band-gap material Phys. Rev. B 2002 65 165116 10.1103/PhysRevB.65.165116 8. Petrella A. Di Mundo R. Notarnicola M. Recycled expanded polystyrene as lightweight aggregate for environmentally sustainable cement conglomerates Materials 2020 13 988 10.3390/ma13040988 9. Cummer S.A. Christensen J. Alù A. Controlling sound with acoustic metamaterials Nat. Rev. Mater. 2016 1 16001 10.1038/natrevmats.2016.1 10. Yang Z. Mei J. Yang M. Chan N.H. Sheng P. Membrane-type acoustic metamaterial with negative dynamic mas Phys. Rev. Lett. 2008 101 204301 10.1103/PhysRevLett.101.204301 19113343 11. Yang Z. Dai H.M. Chan N.H. Ma G.C. Sheng P. Acoustic metamaterial panels for sound attenuation in the 50–1000 Hz regime Appl. Phys. Lett. 2010 96 41906 10.1063/1.3299007 12. Huang H.B. Wu J.H. Huang X.R. Yang M.L. Ding W.P. A generalized inverse cascade method to identify and optimize vehicle interior noise sources J. Sound Vib. 2020 467 115062 10.1016/j.jsv.2019.115062 13. Qiu C. Liu Z. Acoustic directional radiation and enhancement caused by band-edgestates of two-dimensional phononic crystals Appl. Phys. Lett. 2006 89 063106 10.1063/1.2335975 14. Zhang S. Yin L.L. Fang N. Focusing Ultrasound with an Acoustic Metamaterial Network Phys. Rev. Lett. 2009 102 194301 10.1103/PhysRevLett.102.194301 19518957 15. Deulgaonkar V.R. Kallurkar S.P. Mattani A.G. Review and Diagnostics of noise and vibrations in automobiles Int. J. Mod. Eng. Res. 2011 1 242 246 16. Huo G. Chen Z. Jiao Y. Zhu X. Optimization of Dynamic Vibration Absorbers for Suppressing Sound Radiation of Plate Structures J. Vib. Acoust. 2021 143 021003 10.1115/1.4048168 17. Pochivalov K.V. Shilov A.N. Lebedeva T.N. Ilyasova A.N. Golovanov R.Y. Basko A.V. Kudryavtsev Y.V. Development of vibration damping materials based on butyl rubber: A study of the phase equilibrium, rheological, and dynamic properties of compositions J. Appl. Polym. Sci. 2020 138 50196 10.1002/app.50196 18. Kafesaki M. Sigalas M. García N. Frequency Modulation in the Transmittivity of Wave Guides in Elastic-Wave Band-Gap Materials Phys. Rev. Lett. 2000 85 4044 10.1103/PhysRevLett.85.4044 11056620 19. Goyal D. Mittal S.K. Choudhary A. Dang R.K. Graphene: A two dimensional super material for sensor applications Mater. Today Proc. 2021 43 203 208 20. Zhu X. Liang B. Cheng J. Acoustic unusual material and acoustic invisibility cloak Knowl. Mod. Phys. 2012 24 40 46 21. Wen X. Wen J. Yu D. Phononic Crystals National Defense Industry Press Beijing, China 2009 1 180 22. Chen Y. Li J. Huang T. Zhou M. Calculation of band gap of layered ternary periodic structure Noise Vib. Control 2014 34 19 22 23. Kweun J.M. Lee H.J. Oh J.H. Seung H.M. Kim Y.Y. Transmodal Fabry-Pérot resonance: Theory and realization with elastic metamaterials Phys. Rev. Lett. 2017 118 205901 10.1103/PhysRevLett.118.205901 28581773 24. Liu J. Guo H. Wang T. A review of acoustic metamaterials and phononic crystals Crystals 2020 10 305 10.3390/cryst10040305 25. Qian D. Shi Z. Study on the bandgap characteristics of the simplified model of local resonant periodic double-layer plate. Vibration Test. Diagn. 2019 39 884 891 26. Chen J. Sun C.T. Reducing vibration of sandwich structures using antiresonance frequencies Compos. Struct. 2012 94 2819 2826 10.1016/j.compstruct.2012.03.041 27. Zhang S. Hui Wu J. Hu Z. Low-frequency locally resonant band-gaps in phononic crystalplates with periodic spiral resonators J. Appl. Phys. 2013 113 163511 10.1063/1.4803075 28. Zhou T. Cheng L. A resonant beam damper tailored with acoustic black hole features for broadband vibration reduction J. Sound Vib. 2018 430 174 184 10.1016/j.jsv.2018.05.047 29. Li S. Dou Y. Chen T. Wan Z. Formation mechanism of meso-lf wide band gap in phonon crystal plate J. Xi’an Jiaotong Univ. 2008 52 159 166 30. Zhang X. Takezawa A. Kang Z. A phase-field based robust topology optimization method for phononic crystals design considering uncertain diffuse regions Comput. Mater. Sci. 2019 160 159 172 10.1016/j.commatsci.2018.12.057 31. Huang H.B. Li R.X. Yang M.L. Lim T.C. Ding W.P. Evaluation of vehicle interior sound quality using a continuous restricted Boltzmann machine-based DBN Mech. Syst. Signal Process. 2017 84 245 267 10.1016/j.ymssp.2016.07.014 32. Wang Y. Guo H. Lu J. Wang Y. Liu N. Study on sound insulation characteristics of inhomogeneous local resonant phononic crystals J. Artif. Cryst. 2007 46 1250 1257 33. Zhang J. Yao H. Du J. Zhao J. Dong Y. Qi P. Low-frequency sound insulation characteristics based on local resonant phononic crystals in engine room J. Silic. 2016 44 1440 1445 34. Zhang Y. Yin J. Wen J. Yu D. Low-frequency vibration reduction design based on mass amplification of local resonant phonon crystals Vib. Impact 2016 35 26 32 35. Dong Y. Du J. Yao H. Zhao J. Wu J. Study on the band gap characteristics of double-clad locally resonant phonon crystals J. Artif. Cryst. 2015 44 3676 3680 36. Oudich M. Zhou X. Badreddine Assouar M. General analytical approach for sound transmission loss analysis through a thick metamaterial plate J. Appl. Phys. 2014 116 193509 10.1063/1.4901997 37. Ma F. Wu J. Huang M. Resonant Modal Group Theory of Membrane-Type Acoustical Metamaterials for Low-Frequency Sound Attenuation Eur. Phys. J. Appl. Phys. 2015 71 30504 10.1051/epjap/2015150310 38. Long G. Lim T. A new robust delayless subband adaptive filtering algorithm with variable step sizes for active control of broadband noise Appl. Acoust. 2021 176 107858 10.1016/j.apacoust.2020.107858 39. Huang H. Huang X. Ding W. Yang M. Fan D. Pang J. Uncertainty optimization of pure electric vehicle interior tire/road noise comfort based on data-driven Mech. Syst. Signal Process. 2022 165 108300 10.1016/j.ymssp.2021.108300

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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091104 plants-11-01104 Article Exogenous Copper Application for the Elemental Defense of Rice Plants against Rice Leaffolder (Cnaphalocrocis medinalis) Cheah Boon Huat 1 https://orcid.org/0000-0001-6937-3583 Chuang Wen-Po 1 Lo Jing-Chi 2 Li Yi 1 Cheng Chih-Yun 3 Yang Zhi-Wei 3 Liao Chung-Ta 4 https://orcid.org/0000-0003-0681-4358 Lin Ya-Fen 1* van Munster Manuella Academic Editor Vile Denis Academic Editor 1 Department of Agronomy, National Taiwan University, Taipei 10617, Taiwan; boonhuatcheah@ntu.edu.tw (B.H.C.); wenpo@ntu.edu.tw (W.-P.C.); freebike01@gmail.com (Y.L.) 2 Department of Horticulture and Biotechnology, Chinese Culture University, Taipei 11114, Taiwan; ljq13@ulive.pccu.edu.tw 3 Crop Improvement Division, Taoyuan District Agricultural Research and Extension Station, Taoyuan City 32745, Taiwan; kurama630@tydais.gov.tw (C.-Y.C.); zwyang@tydais.gov.tw (Z.-W.Y.) 4 Crop Environment Division, Taichung District Agricultural Research and Extension Station, Changhua County 51544, Taiwan; liaoct@tdais.gov.tw * Correspondence: yafenlin0725@ntu.edu.tw 19 4 2022 5 2022 11 9 110431 3 2022 14 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Metals that accumulate in plants may confer protection against herbivorous insects, a phenomenon known as elemental defense. However, this strategy has not been widely explored in important crops such as rice (Oryza sativa L.), where it could help to reduce the use of chemical pesticides. Here, we investigated the potential of copper (Cu) and iron (Fe) micronutrient supplements for the protection of rice against a major insect pest, the rice leaffolder (Cnaphalocrocis medinalis). We found that intermediate levels of Cu (20 μM CuSO4) and high concentrations of Fe (742 μM Fe) did not inhibit the growth of C. medinalis larvae but did inhibit rice root growth and reduce grain yield at the reproductive stage. In contrast, high levels of Cu (80 μM CuSO4) inhibited C. medinalis larval growth and pupal development but also adversely affected rice growth at the vegetative stage. Interestingly, treatment with 10 μM CuSO4 had no adverse effects on rice growth or yield components at the reproductive stage. These data suggest that pest management based on the application of Cu may be possible, which would be achieved by a higher effective pesticide dose to prevent or minimize its phytotoxicity effects in plants. micronutrient supplement trace elements Oryza sativa L. rice tolerance insect pest ==== Body pmc1. Introduction The rice leaffolder (Cnaphalocrocis medinalis Guenée; Lepidoptera: Pyralidae) is a major insect pest of rice (Oryza sativa L.) in Asia [1]. In Taiwan, severe infestation usually occurs during the second cropping season from June to October, which is characterized by hot and humid weather that favors the growth and reproduction of this pest, leading to yield losses of 18–24% [2,3]. In the paddy field, C. medinalis larvae instinctively build shelters or feeding chambers by folding a leaf longitudinally using silk strands that attach to the leaf margins [4]. The larvae feed by scraping mesophyll tissue from within the folded leaf, resulting in longitudinal white and transparent streaks [5]. A single larva can damage a number of rice leaves, with cumulative effects that reduce photosynthesis and thus cause yield losses [6,7]. The main strategy to prevent C. medinalis outbreaks in rice fields is the application of topical insecticides, but this causes health issues, as well as environmental and ecological damage [8,9]. Integrated pest management is a holistic solution that includes the use of resistant cultivars, biological control and good field management practices, such as the effective use of fertilizers [10]. The macronutrient content of fertilizers is prioritized over the micronutrient content [11], but optimal micronutrients not only promote plant growth but may also enhance biotic stress tolerance [12,13]. For example, copper (Cu)-deficient plants are more susceptible to pathogens [12], and desert locusts (Schistocerca gregaria) prefer the leaves of Noccaea caerulescens plants deficient in zinc (Zn) compared to plants grown in the presence of intermediate or high concentrations of Zn [14]. The elemental defense hypothesis (also known as the inorganic defense hypothesis) proposes that plants accumulate high levels of inorganic elements as a defensive strategy to protect themselves from pests and pathogens [15]. Inorganic elements may contribute to plant defense directly (by defensive enhancement) or indirectly (by joint effects) [16,17]. In the defensive enhancement hypothesis, metal ions accumulating in plants confer protection once they reach a threshold concentration that is toxic toward pests [16]. For example, artificial diet experiments indicated that plants containing 20–300 mg/kg dry weight (DW) of cobalt (Co) or 140–1000 mg/kg DW of nickel (Ni), both within the so-called accumulator range, as well as 200–400 mg/kg DW of Zn (within the normal physiological range), may directly inhibit the growth and development of beet armyworm (Spodoptera exigua) due to metal toxicity [18]. On the other hand, the joint effects hypothesis proposes that metal ions and organic defense chemicals have additive or synergistic effects against herbivores and pathogens [17,19]. The mechanisms of elemental defense differ according to which elements, plant species and pests are involved [20]. Elemental defense has been investigated mainly in dicotyledonous plants and/or heavy metal hyperaccumulators, focusing on arsenic (As), cadmium (Cd), Ni, selenium (Se) and Zn, but rarely on Cu and iron (Fe) [21,22]. Few studies have considered the feasibility of elemental defense in major crops such as rice, although silicon (Si) fortification has been shown to protect rice against C. medinalis larvae by promoting cell silicification, reducing the soluble protein content, and inducing the biosynthesis of defensive enzymes and metabolites such as jasmonic acid (JA) [9,22,23]. As a rule of thumb, an element that confers protection by elemental defense in plants should reach a certain range of endogenous concentrations that can suppress the growth of pests or pathogens without negative effects on plant growth [24]. We examined whether the elemental defense of a rice cultivar susceptible to C. medinalis (Taoyuan No. 3) can be induced by exogenous micronutrient supplements, focusing on Cu and Fe. We evaluated the effects of different concentrations of Cu and Fe on C. medinalis, rice vegetative growth and rice reproductive growth in an attempt to identify the ideal concentration for elemental defense. 2. Results 2.1. Cu Impedes the Growth and Development of C. medinalis Larvae To test the elemental defense potential of Cu and Fe, we compared the growth of C. medinalis larvae reared on a susceptible rice cultivar (Taoyuan No. 3) grown in substrates containing specific Cu or Fe supplements (Figure 1). The fresh weight (FW) of C. medinalis larvae feeding on rice plants supplied with 80 μM Cu was 17% lower than the control group (0.05 μM Cu) 3 days post-infestation (dpi), but not after 6 days (Figure 1A). The 80 μM Cu treatment decreased the relative growth rate (RGR) of larvae after 3 days (0.38 compared to 0.42 in the control group; Figure 1B), hence fifth-instar larvae were predominant (92%) in the 80 μM Cu treatment group after 6 days in contrast to the predominant prepupae (60%) in the control group (Figure 1C). After 9 days, 38% (5/13) of the larvae in the 80 μM Cu treatment group showed delayed development, remaining in the prepupal stage, while all larvae in the control group had entered the pupal stage (Figure 1D). In contrast to the 80 μM Cu treatment group, we observed no effects on larval FW or RGR in response to either 65 or 265 mg/L Fe (equivalent to 197 and 742 μM Fe, respectively) after 3 and 6 days, compared to the control group (15 mg/L Fe, equivalent to 61 μM Fe) (Figure 1E,F). Similarly, the Fe treatments did not delay C. medinalis development compared to the control group after 6 and 9 days (Figure 1G,H). These results showed that Fe has no potential for elemental defense against the C. medinalis, at least under the conditions we tested, whereas Cu fulfilled the first criterion of elemental defense by delaying C. medinalis growth and development above a certain threshold concentration. 2.2. Vegetative Rice Growth Is Inhibited by Cu in a Dose-Dependent Manner but Is Not Inhibited by Fe Having identified the threshold Cu concentration that inhibits pest growth and development, we next investigated the range compatible with vegetative growth in rice. We therefore grew rice plants in the presence of 20 and 80 μM Cu and examined the effect 15 days after treatment (DAT) (Figure 2). The 80 μM Cu treatment clearly inhibited vegetative shoot growth at 15 DAT compared to the 0.05 μM Cu control group (Figure 2A). We examined several morphological and molecular parameters, and found that the 80 μM Cu treatment reduced the shoot height, relative chlorophyll content and biomass of leaf blades, sheaths and roots compared to the control group (Figure 2B,C and Figure S1). An intermediate treatment (20 μM Cu) caused milder physiological changes at 15 DAT, particularly a reduction in root FW compared to the control group (Figure 2B,C and Figure S1). To ensure that the observed physiological changes were caused by Cu treatment, we measured the micronutrient concentrations of the rice plants. The Cu content of the roots in the 20 μM Cu treatment group was 11.5-fold higher than in the control group (590 vs. 51 mg/kg DW), increasing to 21.7-fold higher (1113 vs. 51 mg/kg DW) in the 80 μM Cu treatment group (Figure 2D). However, the Cu concentration in the shoots increased by a similar amount in both treatment groups, from 23 mg/kg DW in the control group to 58 mg/kg DW in the 20 μM Cu treatment group (2.5-fold higher) and 64 mg/kg DW in the 80 μM treatment group (2.8-fold higher) (Figure 2E). Elemental analysis showed that the concentrations of Mn and Fe were unaffected by either Cu treatment, whereas the shoot Zn concentration was reduced by the 80 μM Cu treatment (Figure S2). The analysis of defense-related phytohormones showed that the concentrations of JA and its bioactive derivative JA-isoleucine in rice leaves increased in the 20 μM Cu treatment group but not in the 80 μM Cu treatment group at 15 DAT (Figure 3A,B). The concentration of salicylic acid (SA) in the rice sheath increased in the 80 μM Cu treatment group (Figure 3C). We also tested the effects of 65 and 265 mg/L Fe on the vegetative growth of rice (Figure S3). Although shoot growth at 15 DAT appeared to be similar in the control group and both treatment groups (Figure S3A), quantitative analysis revealed some changes in response to higher concentrations of Fe (Figure S3B). The plants in both treatment groups were taller (8.1% and 3.5% in the 65 and 265 mg/L Fe groups, respectively), the relative chlorophyll content increased (by 8.3% and 13.1%, respectively), and several tissues accumulated more biomass, particularly the leaf blade DW (+55%) and sheath DW (+121%) in the 265 mg/L Fe treatment group (Figure S3C–I). The Fe treatments did not influence intracellular Fe levels in a predictable manner (Figure S4). For example, the 65 mg/L Fe treatment had no effect on the Fe content of the roots at 15 DAT, whereas the Fe content of the shoots increased 28.5-fold from 53 mg/kg DW in the control group to 1517 mg/kg DW after treatment (Figure S4A,B). This suggests that Fe taken up by rice roots was rapidly and efficiently translocated to the shoots (Figure S4C). In contrast, the 265 mg/L Fe treatment affected the Fe content of neither the roots nor the shoots at 15 DAT, suggesting that a heavy metal exclusion mechanism had been triggered to prevent metal toxicity (Figure S4A,B). Elemental analysis showed that Mn levels were unchanged, Cu levels in the shoot decreased in the 265 mg/L Fe treatment group, and Zn levels in the root increased in both Fe treatment groups (Figure S4D–I). The concentration of defense-related hormones was unaffected by the Fe treatments (Figure S5). In summary, both Cu treatments inhibited the vegetative growth of rice plants with varying levels of severity, whereas both Fe treatments promoted the vegetative growth of rice plants instead. It is therefore clear that vegetative rice plants are more susceptible to metal toxicity caused by Cu than Fe. 2.3. The Growth and Yield Components of Reproductive Rice Plants Are Unaffected by 10 μM Cu Given the severe effects of 80 μM Cu on vegetative rice plants, we evaluated the effect of lower concentrations (10, 20 and 30 μM Cu) for 120 days compared to the 0.05 μM Cu control (Figure 4, Table 1). Morphologically, the three Cu treatments did not affect the growth of aboveground tissues (Figure 4A) but root growth was inhibited by the 20 and 30 μM Cu treatments in a dose-dependent manner (Figure 4B). The treatments had no effect on the shoot height and relative chlorophyll content of rice at the reproductive stage (Figure 4C,D). None of the treatments significantly affected the grain yield, but the 30 μM Cu treatment delayed booting by 7–8 days, presumably due to the inhibition of root growth (Table 1, Figure 4A,B). Notably, the aboveground effect of 265 mg/L Fe on shoots was opposite to that on roots at the reproductive stage (Figure S6). Shoot height was not affected by either Fe treatment, but the relative chlorophyll content of plants exposed to 265 mg/L Fe increased by 27.5% compared to the control group (Figure S6A–C). Conversely, root growth was severely inhibited in the presence of 265 mg/L Fe (Figure S6D) and this probably explained the 29.5% lower grain yield compared to control plants (Table 1). Taken together, root growth and yield components in reproductive rice were negatively affected by exposure to 265 mg/L Fe but not 10 μM Cu. Based on the initial results for the effect of Cu on C. medinalis development, effective pest management would require a treatment option that achieved a dose of 80 μM Cu on the leaf surface, to inhibit feeding by the insect larvae, while ensuring that the concentration in plants remained within 10~30 mg Cu/kg DW. 3. Discussion In an ideal form of elemental defense, the concentration of metal ions in plants is sufficient to inhibit pest growth and development without negative effects on the plant [24]. Elemental defense studies have mainly focused on heavy metal hyperaccumulators and the levels of As, Cd, Ni, Se and Zn, whereas we examined the potential of Cu and Fe to achieve protection against the C. medinalis based on the effects of each element on the growth of C. medinalis and a susceptible rice cultivar, Taoyuan No. 3 (Figure 5). We found that C. medinalis larvae feeding on rice plants treated with 80 μM Cu grew and developed more slowly than the control group and did not gain as much FW (Figure 1A–D). Similarly, maize (Zea mays) plants exposed to 80 μM Cu inhibited fall armyworm (Spodoptera frugiperda) growth due to the priming of herbivore-induced JA and volatile organic compounds in maize leaves by heavy metal stress [25]. Another elemental defense study showed that pepper plants (Capsicum annuum L.) exposed to 50 μM Cu were able to tolerate verticillium wilt better than controls, which was attributed to a Cu-induced defense response resulting in the induction of defensive genes that increased the availability of peroxidases and phenolic compounds [26]. The foliar application of Cu(OH)2 fungicide elicits an SA-dependent defense mechanism in Arabidopsis thaliana that governs the effectiveness of the fungicide against Peronospora parasitica [27]. Cu, therefore, has the potential to protect plants against insect pests and pathogens but only if the effective concentration is compatible with normal plant growth. However, we found that the exogenous application of 80 μM Cu increased the Cu concentration in the shoots to 64 mg/kg DW, severely inhibiting vegetative growth at 15 DAT (Figure 2B–E and Figure S1). The optimal Cu concentration in rice shoots is ~10 mg/kg DW, and anything above ~30 mg/kg DW is harmful, inducing toxicity symptoms such as the loss of chlorophyll, the inhibition of photosynthesis, metabolic disruption and ultimately, stunted growth and low yields [28,29,30]. Furthermore, we also observed the severe inhibition of root growth at the reproductive stage in the presence of 30 μM Cu, which delayed booting and heading (Figure 4A,B). In agreement with our results, a previous pot soil experiment showed that root growth was more severely affected than shoot growth in rice plants at the reproductive stage when the Cu concentration in the soil was 50–150 mg/kg, whereas both shoot and root growth were severely inhibited at concentrations of 300–1000 mg/kg [31]. Rice grain yields decreased in relation to the soil Cu concentration, with ~10% yield losses at 100 mg/kg, ~50% yield losses at 300 mg/kg and up to 90% yield losses at 1000 mg/kg [31]. The minimum lethal (530 mg/kg DW) and sublethal (140 mg/kg DW) concentrations of Cu against beet armyworm neonates were much higher than the aforementioned normal range of Cu concentrations in rice shoots, whereas the equivalent values for C. medinalis larvae remain unknown [19]. Our results indicate that Cu is not ideal as the basis of elemental defense against the C. medinalis, given the absence of a concentration that is both toxic toward the pest and harmless toward the plant. Any gains achieved by the suppression of pest development in the presence of 80 μM Cu would be offset by its negative effects on rice plants at the vegetative and reproductive stages (Figure 5). One potential solution is the use of nanotechnology to increase the effective dose of Cu on the plant surface while preventing the uptake of excess Cu and the resulting inhibition of plant growth, which could be achieved by the exogenous topical application of Cu nanoparticles. For example, a field experiment comparing the antifungal activity of foliar applied Cu-based nanoparticles and other commercial agrochemicals on Phytophthora infestans infected tomato (Solanum lycopersicum) and showed that the nanoparticles exhibited higher activity than the commercial agrochemical at a low concentration without causing any deleterious effect on plants [32]. Another study revealed that the Cu-based nanoparticles inhibited the growth of Xanthomonas axonopodis pv. punicae, a pathogen causing bacterial blight in pomegranate, at 0.2 ppm, i.e., >10,000 times lower than that suggested for Cu-oxychloride fungicide [33]. Recently, an adhesive nanopesticide was reported to show better long-term control efficacies against C. medinalis (Guenée) and Chilo suppressalis (Walker) than the commercial Benevia insecticide and also had no apparent effect on the growth of rice [34]. Nevertheless, it is noteworthy that there is a thin line between plant protection and phytotoxicity, hence a more detailed study of the synthesized nanoparticles is required prior to their applications in agricultural field and presumably, it is more suitable to use Cu-tolerant cultivars. Whereas Cu was toxic toward the C. medinalis larvae at 80 μM, Fe did not affect larval FW, RGR or development at concentrations of 65 mg/L (equivalent to 197 μM) or 265 mg/L (equivalent to 742 μM) compared to larvae feeding on control plants (Figure 1). To explain these observations, we must separately consider the effects of each Fe treatment on intracellular Fe levels and the growth of rice plants. The 65 mg/L Fe treatment increased Fe levels in the shoots to 1517 mg/kg DW at 15 DAT, which exceeds the 700 mg/kg DW critical toxicity threshold in rice, but even so, the vegetative growth of rice plants was temporarily improved under these conditions (Figures S3 and S4B). Similarly, optimal vegetative growth was observed for rice plants in nutrient solutions containing 10 or 50 mg/L Fe, whereas growth inhibition due to Fe toxicity was observed at 250 and 500 mg/L Fe [35]. In contrast to the vegetative growth performance, prolonged exposure to 65 mg/L Fe until the reproductive stage reduced the thousand grain weight by 3.3%, even though we observed no changes in the growth of vegetative tissues (Figure S6, Table 1). The accumulation of Fe in rice shoots may have been insufficient to hamper the growth of C. medinalis larvae, or the robust Fe metabolism in these insects may have prevented Fe accumulation through the coordinated control of Fe absorption, transport, storage and homeostasis [36,37]. The C. medinalis larvae were also unaffected by the highest Fe concentration (265 mg/L) because this treatment surprisingly did not alter the intracellular Fe concentration in the shoots (Figure 1 and Figure S4B). This can be attributed to a strategy I (exclusion/avoidance) mechanism deployed by rice plants to exclude soluble Fe2+ at the root level [38,39]. Rice plants achieve this by releasing oxygen and/or expressing enzymes that promote Fe2+ oxidation, leading to the formation of ferric oxide precipitates on the root surface and preventing the uptake of excess Fe2+ [39]. Although this mechanism has proven effective for vegetative rice growing in Fe-contaminated environments, it is less effective under prolonged exposure that extends to later growth stages because the oxidizing capacity of roots declines with age [40]. Accordingly, we observed the severe impairment of root growth and significant yield losses in the 265 mg/L Fe treatment group at the reproductive stage (Figure S6, Table 1). Given that Fe was unable to inhibit C. medinalis growth or development but still negatively affected rice growth and yield, it is clearly unsuitable as the basis for elemental defense against C. medinalis (Figure 5). 4. Materials and Methods 4.1. Plant Materials The popular Taiwanese rice variety Taoyuan No. 3 was chosen for this study because it is highly susceptible to insect pests [41]. Seeds were surface sterilized with 1.25% NaOCl for 60 min, washed three times in distilled water, soaked in distilled water at 37 °C for 24 h and germinated on water-moistened filter paper in Petri dishes in the dark at 37 °C for 48 h. Germinated seeds of uniform size were transferred to 1 L polyethylene pots containing 700 mL sterile vermiculite soaked with 1× Kimura B nutrient solution (pH 5.0), comprising 0.36 mM (NH4)2SO4, 0.18 mM KNO3, 0.55 mM MgSO4, 0.18 mM KH2PO4, 61.20 µM Fe-citrate, 0.37 mM Ca(NO3)2, 2.51 µM H3BO3, 0.20 µM MnSO4, 0.20 µM ZnSO4, 0.05 µM CuSO4 and 0.05 µM H2MoO4 [7,42]. Each pot contained four germinated seeds. Plants were grown in a growth chamber set at 30/25 °C (day/night) with a 12 h photoperiod. The nutrient solution was renewed every other day. Fourteen days after sowing, each pot was trimmed down to two seedlings with uniform leaf stages and the Cu or Fe treatments were applied for 16 days in different batches of experiments. In the Cu experiment, seedlings were exposed to 0.05 µM CuSO4 (control), or an additional 20 or 80 µM CuSO4. In the Fe experiment, seedlings were exposed to 15 mg/L Fe-citrate (control, equivalent to 61.20 µM Fe), or an additional 50 or 250 mg/L FeNa-EDTA (equivalent to an additional 136 or 681 µM Fe). The growth, elemental composition and phytohormone profiles of vegetative rice plants were examined at 15 DAT, whereas the growth and yield of reproductive rice plants were examined at 120 DAT. The nutrient solutions were renewed every other day. Plants were used for insect experiments 30 days after sowing. 4.2. Insect Experiments We used a C. medinalis colony originally collected from the Taichung District Agricultural Research and Extension Station, COA, Changhua, Taiwan. C. medinalis larvae were reared on White Pearl maize seedlings (Known-You Seed Co., Kaohsiung City, Taiwan) according to a modified maize seedling rearing method [43] and moths were fed on a 10% (w/v) sucrose solution. The insects were kept inside BugDorm-4 mesh cages (MegaView, Taiwan) in a growth chamber set at 30/25 °C (day/night) with 55 ± 5% relative humidity and a 12 h photoperiod. Third-instar C. medinalis larvae were weighed and then placed on the newly expanded leaves of 30-day-old rice plants, one larva per plant. Each experimental group consisted of 16 insects. A plastic cover with mesh cloth was placed over each pot to prevent larvae from escaping. Larval FW was recorded again at 3 and 6 dpi, whereas the developmental stage (instar or pupa) was recorded at 6 and 9 dpi. The RGR of the larvae was calculated using Equations (1) and (2) [44,45]:(1) RGR at 3 dpi= Weight (3dpi)− Weight (0dpi)[( Weight (3dpi)+ Weight (0dpi))÷2] ÷ 3 days (2) RGR at 6 dpi= Weight (6dpi)− Weight (0dpi)[( Weight (6dpi)+ Weight (0dpi))÷2] ÷ 6 days 4.3. Rice Physiological Characteristics We measured the shoot height of 10 plants, the FW and DW of leaf blade, sheath and root tissues in four plants, and the relative chlorophyll content of 10 plants at 15 DAT. The relative chlorophyll content of the leaves was measured using a SPAD 502 Plus chlorophyll meter (Spectrum Technologies, Aurora, IL, USA) and values were calculated based on the mean of three different points on the youngest leaf. To assess the effects of prolonged treatment at the reproductive stage, rice plants were exposed to 0.05 (control) or an additional 10, 20 or 30 µM CuSO4 (Cu experiments), or to 15 mg/L Fe-citrate (control) or an additional 50 or 250 mg/L FeNa-EDTA (Fe experiments) for 120 days, beginning 14 days after sowing. We measured shoot height (eight plants), relative chlorophyll content (four plants), days to booting and heading (eight plants) and yield components (eight plants). The number of days to heading was estimated as previously described [46]. The grain yield (in grams per plant) for potted plants was calculated using Equation (3):(3) Grain yield (g/plant)= Panicle number  Plant × Grain number  Panicle × Total grain weight  Grain number  4.4. Elemental Analysis Root and shoot tissues from vegetative rice plants at 15 DAT were harvested separately for elemental analysis as previously described [47]. The tissues were washed in ice-cold 10 mM CaCl2 and again in Millipore water before drying at 70 °C for 3 days. The dried tissues were cut into fine pieces. Shoot sample (ca. 50 mg) and root sample (ca. 20 mg) from each plant were transferred into a Teflon vessel and digested with 5 mL 69% HNO3 (Suprapur, Merck, Kenilworth, NJ, USA) and 2 mL 37% H2O2 (Suprapur, Merck, Kenilworth, NJ, USA) before multi-element analysis by inductively-coupled plasma-optical emission spectrometry (ICP-OES) (PerkinElmer Optima 5300, Waltham, MA, USA). Tomato leaves (SRM-1573a) from the National Institute of Standards and Technology were used as a reference, giving a recovery of >72% for Cu, Fe, Zn and Mn. Elemental concentrations (mg/kg DW) in rice tissues are presented as means ± standard deviations (SD) based on four biological replicates. 4.5. Phytohormone Analysis Leaf blade, sheath and root tissues from vegetative rice plants at 15 DAT were harvested separately for phytohormone analysis by LC-MS as previously described [2]. The concentrations of SA, JA and JA-isoleucine (ng/g FW) are presented as means ± SD based on three biological replicates. 4.6. Statistical Analysis Statistical analysis was carried out using the lsmeans and multcomp packages in R [48,49]. Statistically significant differences (p < 0.05) were determined using one-way or two-way analysis of variance (ANOVA) followed by Tukey’s post hoc test as appropriate. 5. Conclusions The use of micronutrient supplements to confer elemental defense against pests and pathogens in staple crops such as rice has not been investigated in detail. We found that Fe is unsuitable for this purpose because even high concentrations (265 mg/L Fe) had no effect against C. medinalis larvae. In contrast, 80 µM Cu inhibited C. medinalis growth and development but this concentration was also toxic to the rice plants. Even so, Cu-induced elemental defense in rice may be possible if the efficacy of the pesticide on the leaf surface can be increased without affecting intracellular Cu levels, for example, by the topical application of Cu nanoparticles. Acknowledgments This work was supported by the Council of Agriculture, Executive Yuan, Taiwan, grant number 108AS-1.2.1-ST-aC and the Ministry of Science and Technology, Taiwan, grant number, 109-2313-B-002-030-MY3. We thank Kuo-Chen Yeh and his colleague I-Chien Tang from the Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan for their kind support in the metal concentration experiments. We also thank Yu-Ling Chen for her kind supervision on the digestion of rice materials and Chen-Han Jan from the Department of Agronomy, National Taiwan University, for generously helping to maintain the rice plants. We thank Yet-Ran Chen for the phytohormone analysis, which was supported by the Academia Sinica Metabolomics Core Facility at the Agricultural Biotechnology Research Center of Academia Sinica, supported by Academia Sinica Core Facility and Innovative Instrument Project (AS-CFII-111-218). We also acknowledge support from the Higher Education Sprout Project, National Taiwan University (110L4000, 109L4000 and 107L4000). Supplementary Materials The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/plants11091104/s1, Figure S1: Effects of 20 and 80 µM Cu on the biomass and relative chlorophyll content of vegetative rice plants at 15 DAT. (A) leaf blade fresh weight (FW), (B) leaf blade dry weight (DW), (C) sheath FW, (D) sheath DW, (E) root DW and (F) relative chlorophyll content (SPAD) are shown. Data are means ± SD (tissue FW and DW, n = 4; relative chlorophyll content, n = 10). One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05), Figure S2: Effects of 20 and 80 µM Cu on the Mn, Fe and Zn micronutrient concentrations of vegetative rice plants at 15 DAT. (A) root Mn, (B) shoot Mn, (C) root Fe, (D) shoot Fe, (E) root Zn and (F) shoot Zn concentrations (mg/Kg DW) are shown as means ± SD (n = 4). One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05), Figure S3: Effects of 65 and 265 mg/L Fe on the physiology of vegetative rice plans at 15 DAT. (A) shoot morphology (scale bar = 10 cm), (B) shoot height, (C) root dry weight (DW), (D) leaf blade fresh weight (FW), (E) leaf blade DW, (F) sheath FW, (G) sheath DW, (H) root FW, and (I) relative chlorophyll content (SPAD) are shown. Data are means ± SD (shoot height, n = 10; tissue FW and DW, n = 4; relative chlorophyll content, n = 10). One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05), Figure S4: Effects of 65 and 265 mg/L Fe on the Fe, Mn, Cu and Zn micronutrient concentrations of vegetative rice plants at 15 DAT. (A) root Fe, (B) shoot Fe, (C) Fe translocation efficiency from root to shoot, (D) root Mn, (E) shoot Mn, (F) root Cu, (G) shoot Cu, (H) root Zn and (I) shoot Zn are shown as means ± SD (n = 4). One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05), Figure S5: Effects of 65 and 265 mg/L Fe on defense-related phytohormones in rice tissues at 15 DAT. (A) jasmonic acid (JA), (B) JA-isoleucine (JAIle) and (C) salicylic acid (SA) concentrations are shown in three tissues. Data are means ± SD (n = 3). One-way ANOVA and Tukey’s post hoc test were used for phytohormone measurements in each tissue, with different letters denoting a significant difference (p < 0.05), Figure S6: Effects of 65 and 265 mg/L Fe on the physiology of rice plants at the reproductive stage. (A) shoot morphology during heading (scale bar = 10 cm), (B) shoot height, (C) relative chlorophyll content and (D) root morphology (scale bar = 5 cm) are shown. Data are means ± SD (shoot height, n = 8; relative chlorophyll content, n = 4). One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05). Click here for additional data file. Author Contributions Y.-F.L. and W.-P.C. conceived and designed the experiments; B.H.C., Y.L. and J.-C.L. conducted the experiments and analyzed the data; C.-Y.C. and Z.-W.Y. provided the rice materials; W.-P.C. and C.-T.L. provided the Cnaphalocrocis medinalis larvae; Y.-F.L., W.-P.C., C.-Y.C., Z.-W.Y. and C.-T.L. supervised the research; all authors contributed to the discussion of the results; B.H.C. and Y.-F.L. contributed to manuscript preparation. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Council of Agriculture, Executive Yuan, Taiwan, grant number 108AS-1.2.1-ST-aC and the Ministry of Science and Technology, Taiwan, grant number 109-2313-B-002-030-MY3. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data is contained within the article and Supplementary Material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Effects of Cu and Fe treatments on C. medinalis growth and development at 3, 6 and 9 days post-infestation (dpi): (A) Larval fresh weight (FW) at 0, 3 and 6 dpi; (B) larval relative growth rate (RGR) at 3 and 6 dpi; (C,D) developmental stages of C. medinalis at (C) 6 dpi and (D) 9 dpi (scale bar = 1 cm) under Cu treatments; (E) Larval FW at 0, 3 and 6 dpi; (F) larval RGR at 3 and 6 dpi; developmental stages of C. medinalis at (G) 6 dpi and (H) 9 dpi (scale bar = 1 cm) under Fe treatments. Data are means ± SD (larval FW, n = 12–16; larval RGR, n = 9–16; developmental stages, n = 12–16). Two-way ANOVA and Tukey’s post hoc test were used for FW and RGR measurements, with different letters denoting a significant difference (p < 0.05). Figure 2 Effect of 20 and 80 µM Cu on the physiology of vegetative rice plants at 15 DAT: (A) Shoot morphology (scale bar = 10 cm); (B) shoot height; (C) root fresh weight (FW); (D) root Cu concentration (mg/Kg DW) and (E) shoot Cu concentration (mg/Kg DW) are shown. Data are means ± SD (shoot height, n = 10; root FW, n = 4; tissue Cu concentrations, n = 4). One-way ANOVA and Tukey’s post hoc test were used for each measurement, with different letters denoting a significant difference (p < 0.05). Figure 3 Effect of 20 and 80 µM Cu on defense-related phytohormone concentrations in rice tissues at 15 DAT: (A) Jasmonic acid (JA); (B) JA-isoleucine (JAIle) and (C) salicylic acid (SA) concentrations are shown in three tissues. Data are means ± SD (n = 3). One-way ANOVA and Tukey’s post hoc test were used for phytohormone measurements in each tissue, with different letters denoting a significant difference (p < 0.05). Figure 4 Effects of 10, 20 and 30 µM Cu on the physiology of rice plants at the reproductive stage: (A) Shoot morphology during heading (scale bar = 10 cm); (B) root morphology (scale bar = 5 cm); (C) shoot height and (D) relative chlorophyll content (SPAD) are shown. Data are means ± SD (shoot height, n = 8; relative chlorophyll content, n = 4). Red arrow indicates delayed heading in a plant exposed to 30 µM Cu. One-way ANOVA and Tukey’s post hoc test were used, with different letters denoting a significant difference (p < 0.05). Figure 5 Summary of the elemental defense potential of Cu and Fe against the C. medinalis. High levels of Cu impede the growth and development of C. medinalis but the elemental defense potential is limited because this treatment seriously affects the growth and development of rice plants at the vegetative and reproductive stages. High levels of Fe offer no elemental defense potential because the treatment does not affect the growth of C. medinalis but does inhibit root growth and reduce rice yields at the reproductive stage. plants-11-01104-t001_Table 1 Table 1 Effect of Cu and Fe treatments on the yield components of rice. Grain yield is the product of panicle number per plant, grain number per panicle and the thousand grain weight/1000. For each yield component, the data are means ± SD (n = 8), with significance determined by one-way ANOVA followed by Tukey’s post hoc test (p < 0.05, as denoted by different letters). Treatment Concentration Panicle Number per Plant Grain Number per Panicle Thousand Grain Weight (g) Grain Yield (g/Plant) Cu 0.05 μM (control) 2.75 ± 0.46 a 75.14 ± 23.61 a 28.48 ± 0.34 c 5.89 ± 1.53 a 10 μM 2.63 ± 0.52 a 65.90 ± 24.94 a 29.49 ± 0.44 d 5.10 ± 1.40 a 20 μM 2.13 ± 0.35 a 81.18 ± 25.33 a 27.44 ± 0.12 b 4.73 ± 0.77 a 30 μM 2.25 ± 0.71 a 76.20 ± 21.70 a 26.39 ± 0.21 a 4.76 ± 0.82 a Fe 15 mg/L (control) 3.00 ± 0.53 b 78.88 ± 26.71 a 27.62 ± 0.15 b 6.49 ± 0.40 b 65 mg/L 2.50 ± 0.53 ab 81.65 ± 30.52 a 26.72 ± 0.26 a 5.45 ± 0.93 ab 265 mg/L 2.25 ± 0.46 a 75.33 ± 29.09 a 27.01 ± 0.24 a 4.58 ± 1.23 a Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Nathan S.S. Kalaivani K. Murugan K. Chung P.G. Efficacy of neem limonoids on Cnaphalocrocis medinalis (Guenée) (Lepidoptera: Pyralidae) the rice leaffolder Crop Prot. 2005 24 760 763 10.1016/j.cropro.2005.01.009 2. Guo T.W. Liao C.T. Chuang W.P. Defensive responses of rice cultivars resistant to Cnaphalocrocis medinalis (Lepidoptera: Crambidae) Arthropod Plant Interact. 2019 13 611 620 10.1007/s11829-019-09673-4 3. Cheng C.H. Wu S.C. Population dynamics and forecasting of rice leaffolder, Cnaphalocrocis medinalis (Guenée) in Taiwan Plant Prot. Bull. Taiwan 1999 41 199 213 4. De Jong P.D. Effect of folding and feeding by Cnaphalocrocis medinalis on photosynthesis and transpiration of rice leaves Entomol. Exp. Appl. 1992 63 101 102 10.1111/j.1570-7458.1992.tb02425.x 5. Mahesh P. Srikanth J. Chandran K. Singaravelu B. Salin K.P. Jayabose C. Balan S. Occurrence, damage pattern and status of the rice leaf folder Cnaphalocrocis ruralis Walker (Lepidoptera: Crambidae) in Erianthus spp. in India Exp. Agric. 2019 55 471 483 10.1017/S0014479718000121 6. Padmavathi C. Katti G. Padmakumari A.P. Voleti S.R. Subba Rao L.V. The effect of leaffolder Cnaphalocrocis medinalis (Guenee) [Lepidoptera: Pyralidae] injury on the plant physiology and yield loss in rice J. Appl. Entomol. 2013 137 249 256 10.1111/j.1439-0418.2012.01741.x 7. Cheah B.H. Lin H.H. Chien H.J. Liao C.T. Liu L.Y.D. Lai C.C. Lin Y.F. Chuang W.P. SWATH-MS-based quantitative proteomics reveals a uniquely intricate defense response in Cnaphalocrocis medinalis-resistant rice Sci. Rep. 2020 10 6597 10.1038/s41598-020-63470-1 32759951 8. Yang Y. Xu H. Lu Y. Wang C. Lu Z. Midgut transcriptomal response of the rice leaffolder, Cnaphalocrocis medinalis (Guenée) to Cry1C toxin PLoS ONE 2018 13 e0191686 10.1371/journal.pone.0191686 29360856 9. Han Y. Lei W. Wen L. Hou M. Silicon-mediated resistance in a susceptible rice variety to the rice leaf folder, Cnaphalocrocis medinalis Guenée (Lepidoptera: Pyralidae) PLoS ONE 2015 10 e0120557 10.1371/journal.pone.0120557 25837635 10. Kogan M. Integrated pest management: Historical perspectives and contemporary developments Annu. Rev. Entomol. 1998 43 243 270 10.1146/annurev.ento.43.1.243 9444752 11. Bindraban P.S. Dimkpa C. Nagarajan L. Roy A. Rabbinge R. Revisiting fertilisers and fertilisation strategies for improved nutrient uptake by plants Biol. Fertil. Soils 2015 51 897 911 10.1007/s00374-015-1039-7 12. Datnoff L.E. Mineral Nutrition and Plant Disease American Phytopathological Society St. Paul, MN, USA 2007 1 278 13. Marschner H. Marschner’s Mineral Nutrition of Higher Plants 3rd ed. Academic Press Cambridge, MA, USA 2012 1 672 14. Behmer S.T. Lloyd C.M. Raubenheimer D. Stewart-Clark J. Knight J. Leighton R.S. Harper F.A. Smith J.A.C. Metal hyperaccumulation in plants: Mechanisms of defence against insect herbivores Funct. Ecol. 2005 19 55 66 10.1111/j.0269-8463.2005.00943.x 15. Boyd R.S. Martens S.N. The significance of metal hyperaccumulation for biotic interactions Chemoecology 1998 8 1 7 10.1007/s000490050002 16. Hörger A.C. Fones H.N. Preston G.M. The current status of the elemental defense hypothesis in relation to pathogens Front. Plant Sci. 2013 4 395 10.3389/fpls.2013.00395 24137169 17. Boyd R.S. Plant defense using toxic inorganic ions: Conceptual models of the defensive enhancement and joint effects hypotheses Plant Sci. 2012 195 88 95 10.1016/j.plantsci.2012.06.012 22921002 18. Cheruiyot D.J. Boyd R.S. Moar W.J. Exploring lower limits of plant elemental defense by cobalt, copper, nickel, and zinc J. Chem. Ecol. 2013 39 666 674 10.1007/s10886-013-0279-y 23584612 19. Cheruiyot D.J. Boyd R.S. Moar W. Testing the joint effects hypothesis of elemental defense using Spodoptera exigua J. Chem. Ecol. 2015 41 168 177 10.1007/s10886-015-0553-2 25712748 20. Liu Z. Sun Z. Zeng C. Dong X. Li M. Liu Z. Yan M. The elemental defense effect of cadmium on Alternaria brassicicola in Brassica juncea BMC Plant Biol. 2022 22 17 10.1186/s12870-021-03398-4 34986803 21. Cabot C. Martos S. Llugany M. Gallego B. Tolrà R. Poschenrieder C. A role for zinc in plant defense against pathogens and herbivores Front. Plant Sci. 2019 10 1171 10.3389/fpls.2019.01171 31649687 22. Boyd R. The defense hypothesis of elemental hyperaccumulation: Status, challenges and new directions Plant Soil 2007 293 153 176 10.1007/s11104-007-9240-6 23. Han Y. Li P. Gong S. Yang L. Wen L. Hou M. Defense responses in rice induced by silicon amendment against infestation by the leaf folder Cnaphalocrocis medinalis PLoS ONE 2016 11 e0153918 10.1371/journal.pone.0153918 27124300 24. Martos S. Gallego B. Cabot C. Llugany M. Barceló J. Poschenrieder C. Zinc triggers signaling mechanisms and defense responses promoting resistance to Alternaria brassicicola in Arabidopsis thaliana Plant Sci. 2016 249 13 24 10.1016/j.plantsci.2016.05.001 27297986 25. Winter T.R. Borkowski L. Zeier J. Rostás M. Heavy metal stress can prime for herbivore-induced plant volatile emission Plant Cell Environ. 2012 35 1287 1298 10.1111/j.1365-3040.2012.02489.x 22321129 26. Chmielowska J. Veloso J. Gutiérrez J. Silvar C. Díaz J. Cross-protection of pepper plants stressed by copper against a vascular pathogen is accompanied by the induction of a defence response Plant Sci. 2010 178 176 182 10.1016/j.plantsci.2009.11.007 27. Molina A. Hunt M.D. Ryals J.A. Impaired fungicide activity in plants blocked in disease resistance signal transduction Plant Cell 1998 10 1903 1914 10.1105/tpc.10.11.1903 9811797 28. Cui J.L. Zhao Y.P. Lu Y.J. Chan T.S. Zhang L.L. Tsang D.C.W. Li X.D. Distribution and speciation of copper in rice (Oryza sativa L.) from mining-impacted paddy soil: Implications for copper uptake mechanisms Environ. Int. 2019 126 717 726 10.1016/j.envint.2019.02.045 30878867 29. Mostofa M.G. Fujita M. Salicylic acid alleviates copper toxicity in rice (Oryza sativa L.) seedlings by up-regulating antioxidative and glyoxalase systems Ecotoxicology 2013 22 959 973 10.1007/s10646-013-1073-x 23579392 30. Mostofa M.G. Seraj Z.I. Fujita M. Exogenous sodium nitroprusside and glutathione alleviate copper toxicity by reducing copper uptake and oxidative damage in rice (Oryza sativa L.) seedlings Protoplasma 2014 251 1373 1386 10.1007/s00709-014-0639-7 24752795 31. Xu J. Yang L. Wang Z. Dong G. Huang J. Wang Y. Toxicity of copper on rice growth and accumulation of copper in rice grain in copper contaminated soil Chemosphere 2006 62 602 607 10.1016/j.chemosphere.2005.05.050 16081136 32. Giannousi K. Avramidis I. Dendrinou-Samara C. Synthesis, characterization and evaluation of copper based nanoparticles as agrochemicals against Phytophthora infestans RSC Adv. 2013 3 21743 21752 10.1039/c3ra42118j 33. Mondal K. Mani C. Investigation of the antibacterial properties of nano-copper against Xanthomonas axonopodis pv. punicae, the incident of pomegranate bacterial blight Ann. Microbiol. 2012 62 889 893 10.1007/s13213-011-0382-7 34. Gao Y. Li D. Li D. Xu P. Mao K. Zhang Y. Qin X. Tang T. Wan H. Li J. Efficacy of an adhesive nanopesticide on insect pests of rice in field trials J. Asia-Pac. Entomol. 2020 23 1222 1227 10.1016/j.aspen.2020.08.013 35. Mehraban P. Zadeh A.A. Sadeghipour H.R. Iron toxicity in rice (Oryza sativa L.), under different potassium nutrition Asian J. Plant Sci. 2008 7 251 259 10.3923/ajps.2008.251.259 36. Nichol H. Law J.H. Winzerling J.J. Iron metabolism in insects Annu. Rev. Entomol. 2002 47 535 559 10.1146/annurev.ento.47.091201.145237 11729084 37. Tang X. Zhou B. Iron homeostasis in insects: Insights from Drosophila studies IUBMB Life 2013 65 863 872 10.1002/iub.1211 24078394 38. Onyango D.A. Entila F. Dida M.M. Ismail A.M. Drame K.N. Mechanistic understanding of iron toxicity tolerance in contrasting rice varieties from Africa: 1. Morpho-physiological and biochemical responses Funct. Plant Biol. 2018 46 93 105 10.1071/FP18129 30939261 39. Wu L.B. Shhadi M.Y. Gregorio G. Matthus E. Becker M. Frei M. Genetic and physiological analysis of tolerance to acute iron toxicity in rice Rice 2014 7 8 10.1186/s12284-014-0008-3 24920973 40. Becker M. Asch F. Iron toxicity in rice—Conditions and management concepts J. Plant Nutr. Soil Sci. 2005 168 558 573 10.1002/jpln.200520504 41. Chen L.C. Huang S.H. Cheng C.H. Review of the screening tests for rice varietal resistance to major diseases and insect pests in Taiwan Proceedings of the Symposium on Achievements and Perspectives of Rice Protection in Taiwan Chia-yi Agricultural Experiment Station Chiayi City, Taiwan 2009 83 103 42. Yoshida S. Routine procedure for growing rice plants in culture solution Laboratory Manual for Physiological Studies of Rice Yoshida S. Forno D.A. Cook J.H. Gomez K.A. International Rice Research Institute Los Baños, Philippines 1976 61 66 43. Shono Y. Hirano M. Improved mass-rearing of the rice leaffolder, Cnaphalocrocis medinalis (GUENEE) (Lepidoptera: Pyralidae) using corn seedlings Appl. Entomol. Zool. 1989 24 258 263 10.1303/aez.24.258 44. Farrar R.R. Barbour J.D. Kennedy G.G. Quantifying food consumption and growth in insects Ann. Entomol. Soc. Am. 1989 82 593 598 10.1093/aesa/82.5.593 45. Waldbauer G.P. The consumption and utilization of food by insects Advances in Insect Physiology Beament J.W.L. Treherne J.E. Wigglesworth V.B. Academic Press Cambridge, MA, USA 1968 Volume 5 229 288 46. Matsuzaki A. Rutger J.N. Characteristics relating young panicle development and heading of closely related calrose rice genotypes Jpn. J. Crop Sci. 1991 60 298 305 10.1626/jcs.60.298 47. Lin Y.-F. Liang H.-M. Yang S.-Y. Boch A. Clemens S. Chen C.-C. Wu J.-F. Huang J.-L. Yeh K.-C. Arabidopsis IRT3 is a zinc-regulated and plasma membrane localized zinc/iron transporter New Phytol. 2009 182 392 404 10.1111/j.1469-8137.2009.02766.x 19210716 48. Hothorn T. Bretz F. Westfall P. Simultaneous inference in general parametric models Biom. J. 2008 50 346 363 10.1002/bimj.200810425 18481363 49. Lenth R. Least-squares means: The R package lsmeans J. Stat. Softw. 2016 69 1 33 10.18637/jss.v069.i01

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092420 jcm-11-02420 Article Hemostatic Efficacy of Absorbable Gelatin Sponges for Surgical Nail Matrixectomy after Phenolization—A Blinded Randomized Controlled Trial https://orcid.org/0000-0002-2869-9322 Córdoba-Fernández Antonio * https://orcid.org/0000-0002-3518-2380 Lobo-Martín Adrián Furue Masutaka Academic Editor Departamento de Podología, Universidad de Sevilla, C/Avicena s/n, 41009 Sevilla, Spain; adrlobmar@gmail.com * Correspondence: acordoba@us.es 26 4 2022 5 2022 11 9 242028 3 2022 23 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Background: Some studies have recommended combining germinal matrix excision with phenol ablation in the treatment of onychocryptosis. Matrixectomy after phenolization has been shown to be an effective modification to reduce the drawbacks associated with phenolization alone, although it increases the risk of minor postoperative bleeding. The present study aims to assess the effectiveness and safety of gelatin sponges as hemostatic agents in partial matrixectomy after phenolization. Methods: A comparative clinical trial in parallel groups was designed in 74 halluces (44 patients) with stage I, II, and III onychocryptosis. All participants were randomly assigned to 3 groups: Group A (control group), Group B (conventional gelatin sponge), and Group C (high porosity gelatin sponge). Results: The quantified mean blood loss in the first 48 h after surgery in patients in both experimental groups was significantly lower compared to the control group. The lowest mean blood loss was recorded in Group C (p < 0.001) and followed by Group B (p = 0.005). No adverse effects were recorded in any of the patients included in the experimental groups. Conclusions: Hemostatic gelatin sponges were demonstrated to be effective and safe devices for the control of minor postoperative bleeding associated with matrixectomy after segmental phenolization. ingrown toenail surgery hemostatic gelatin sponges bleeding phenolization ==== Body pmc1. Introduction Currently, segmental phenolization (SP) is the gold standard in the surgical treatment of onychocryptosis due to its low recurrence rate with a favorable adverse effect profile [1]. Studies that have evaluated Wedge resection (WR) matrixectomy combined with posterior SP have been demonstrated to be effective treatments with significantly fewer recurrences than the procedures used SP or WR alone [2,3,4]. However, SP or the combined procedure WR/SP appears to increase the risk of postoperative swelling and discharge with the consequent increased prolonged healing time and risk of infection related to the destruction of cauterized tissue [1,5,6]. The curettage or WR of cauterized tissue after SP has been demonstrated to be an effective modification of combined techniques to reduce the drawbacks associated with SP alone, but with an increased risk of postoperative bleeding and/or pain [7]. Minor postoperative bleeding after partial nail matrixectomy has been an item poorly analyzed as the primary outcome in reported clinical trials. Experimental studies that have compared SP or WR alone versus WR combined with posterior SP have demonstrated that postoperative bleeding was less after SP alone or in combination with WR [7,8,9]. Postoperative toenail wounds involve hemodynamic conditioning originating from the peripheral effect of the heart in a particularly vascularized zone such as the matrix and nail bed. This condition is exacerbated after surgery by reactive hyperemia produced on the toe after removal of the tourniquet, which increases in the standing position. Thus, achieving postoperative hemostasis after nail surgery is crucial due to the rich vascular supply of the nail bed and matrix. Platelet-rich fibrin has been shown to be effective in controlling postoperative bleeding and recovery time after SP or partial WR [10,11]. However, this turns out to be less cost-effective than other approved hemostatic agents, as the preparation of autologous blood products is complex and time-consuming with an increase in operative durations. Most mechanical hemostats are based on animal-derived products, such as collagen and gelatin, especially purified gelatin derived from porcine skin. The advantage of these hemostatic devices is that they act not only by mechanical pressure but also by their physiological action mechanism, i.e., absorb blood cells and activate platelet aggregation, release coagulation factors, and activate endogenous hemostasis [12]. The most commonly used absorbable gelatin hemostatic agents are presented in sponge forms and have been demonstrated to be useful in different surgical specialties. In dermatologic surgery, gelatin sponges have been used to control postoperative hemostasis from capillary, venous, and low-pressure arteriolar bleeding [13]. Most collagen-derived products, such as gelatin sponges (GS), possess remarkable coagulation functions due to their good porous structure and hygroscopic properties. These properties have attracted the attention of most biomedical researchers, and include excellent biocompatibility, good biodegradability, cell interactivity, non-immunogenicity, and excellent processability, availability, and cost-effectiveness. Their high swelling capacity and rapid hemostatic ability make them suitable for preventing exudate accumulation and protecting the wound bed from bacterial invasion [14]. Due to its pH neutrality, GS work as an ideal drug carrier and can be very useful in combination with antifibronolitics or other hemostatic agents [15]. Absorbable GS soaked in tamponed aluminum chloride has been used successfully to achieve hemostasis after nail biopsy [16]. GS are flexible materials with well-interconnected micropore structures, with a pore size between 10 and 100 μm in diameter and interconnected channels. High-porosity gelatin sponges (HPGS) are characterized by high pore density, reduced linking, and high nanoscale with roughness of the lamella surfaces that have shown rapid hemostasis in vitro and in vivo models versus conventional gelatin sponges (CGS) [17]. Some animal model and clinical studies have demonstrated faster re-absorption of HPGS and a less inflammatory response than CGS, which produces less overall mass, resulting in a reduced risk of aberrant fibrosis, in addition, making it unnecessary to remove the dressingdue to its rapid biodegradation [18,19,20]. Currently, there are no studies that have analyzed the efficacy and safety of absorbable GS in nail surgery. We consider that SP and subsequent WR using GS can reduce these drawbacks, maintaining the advantage of combining procedures. Consequently, the objective of this experimental study is to evaluate the clinical efficacy and safety of two different types of GS after combining SP with the posterior WR matrixectomy. 2. Materials and Methods 2.1. Study Design and Sample A prospective single-center, parallel groups, randomized, double-blind study was designed. We recruited patients with ingrown toenails in hallux treated in the surgical section of the Podiatric Clinical Area of the University of Sevilla (Spain). The study was developed in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines. The inclusion criteria were hallux nail onychocryptosis stage I, II, or III according to the Kline classification [21] which indicated surgical treatment. Patients with erythema, drainage, and acute pain received conservative treatment prior to enrollment in the study. Patients with severe medical comorbidities (anemia, cardiovascular disease, uncontrolled diabetes, coagulation disorders, or patients with abnormal platelet count or taking antiplatelet aggregates or other oral anticoagulants) were excluded. The participants gave their written consent according to the Declaration of Helsinkiand the research protocol was approved by the Research Ethic Committee of the University hospitals Virgen Macarena and Virgen del Rocío (ID: 1206-N-15). The study was registered in the ClinicalTrials.gov PRS Registry (ID: NCT05140161). All participants were randomly assigned to 3 groups using a simple equal-probability randomization scheme: Group A (control group), Group B (CGS group), and Group C (HPGS group). The final sample consisted of 44 participants with hallux-nail onychocryptosis (74 toes; 148 nail folds). The same researcher generated the random allocation sequence, enrolled participants, and assigned interventions. The investigator blinded each patient to the surgical procedure. The flow chart of the patients throughout the course of the study can be observed in Figure 1. 2.2. Surgical Procedure For the three groups, the surgical procedure consisted of a partial nail avulsion associated with SP and posterior WR, as described by Winograd [22]. After a hallux nerve block with approximately 3–4 mL of 2% mepivacaine without vasoconstrictor, hallux blood was exsanguinated with a small Esmarch-type bandage and a soft rubber tourniquet was applied at the base of the toe. All procedures were performed on the medial and lateral nail folds of one or both halluces. A partial plate nail avulsion and posterior SP were performed using a 90% phenol solution that was applied for one minute with sterile gauze. After this, remnant phenol was dissolved in the area using 70% alcohol irrigation and then physiological saline solution. Subsequently, the cauterized tissue with a whitish appearance and granulation tissue, if present, was carefully removed using a scalpel and curette. The excised area included approximately 3–4 mm of the adjacent nail and nail bed down to the periosteum (Figure 2). The patients in each group were subjected to three different experimental conditions. The subjects of the control group (Group A) did not receive any treatment, while the patients in the two experimental groups received CGS (Octocolagen®, Clarben SA, Madrid, Spain) or HPGS (Gelita-Spon Standard®, Gelita Medical, Eberbach, Germany), respectively. Gelatin sponges were previously soaked in saline solution and prepared for their application by a different researcher from the one who performed the procedure. CGS was applied to the subjects of Group B and HPGS was applied to the subjects of Group C. Both types of sponges came in cubes of 10 × 10 × 10 mm size and were easily packed into the operated nail grooves covering the subeponychial space and the injured nail bed previously soaked with saline solution (Figure 3). All surgical wounds were covered with a non-adherent 6 × 4 cm sterile polypropylene dressing size (Apodrex®, Vectem SA, Barcelona, Spain) and five hydrophilic cotton gauzes (Tegosa SA, Toledo, Spain) were placed around the hallux and partially covered with a cohesive conforming bandage of size 400 × 4 cm (Peha-haft®, Hartmann, Heidenheim, Germany). The tourniquet was then removed and the bandage was finalized while the patient remained with the foot elevated (tremdelemburg position) for ten minutes before standing up. 2.3. Outcome Measurement The patients were blinded for the treatment applied and the surgeon for the treatment applied to the patients in the experimental groups. The halluces of the control group received standard treatment with only non-adherent dressing, gauzes, and a compressive bandage while in the toes of the experimental groups in every operated groove a wet cube of the selected gelatin sponge of size 10 × 10 × 10 mm was also applied. Non-adherent dressings and five gauzes were previously weighed using a precision electronic balance (Nahitaserie 5152, d = 0.01 g), obtaining an exact of 4.29 g. For the analysis of postoperative inflammation, digital circumference (in cm) was measured using a flexible rule at the level of the proximal fold of the nail. The healing of the spontaneous wound closure was monitored by clinical evaluations and digital photographs. After 48 h, all participants returned for regulated and standardized dressing changes. Participants were reviewed 48 h after the surgical procedure patients and the elastic compressive bandage was removed. Non-adherent dressings and five gauzes were carefully removed together and subsequently weighed (Figure 4), and the digital circumference was again measured. In the control and experimental groups, the wounds were cleaned with a saline solution and 10% povidone iodine antiseptic solution was applied. In the experimental groups, when necessary, excess amorphous fibrin and gelatin sponge was partially removed with Adson forceps and the digital circumference (in cm) was measured again. The toe was covered with the same non-adhesive dressing, gauze, and elastic bandage. From the fifth day, patients were seen approximately every 48–72 h until the recovery period was complete. To limit subjectivity in the assessment of complete recovery time, clinical indicators of recovery time were considered when there was no drainage (no exudate evident), when the granulation tissue was covered by a scab (no evidence of granuloma or encapsulation), when there were no signs of erythematous tissue without evidence of infection, and the patient was able to use normal footwear and perform activities/work. All criteria had to be met before recovery time was reached. On day 5, when participants presented for redress, an experienced blinded clinician in nail wound care evaluated the wound. The recovery time was the interval between the application of the first dressing (at the time of surgery) and the clinical indicators were completely achieved. To measure postoperative pain, an analog visual scale for the self-evaluation of pain on a 10 cm scale (0 = absence of pain to 10 = unbearable pain) was used. Postoperative analgesia was administered with 500 mg of acetaminophen per os every 6 to 8 h (no more than 4 g/day) when pain measured with the chromatic scale was less than 5 and 1000 mg when it was more than 5. The same clinician performed all surgical procedures, and all parties involved in the postoperative period were blinded, including resident podiatrists, who collected the pain questionnaires. After a minimum follow-up of 8 months, an attempt was made to contact all patients for a telephone interview to assess satisfaction with the procedure. An independent and blinded evaluator conducted the telephone interviews. Recurrence was based on the presence of recurrent nail spicules or an ingrowing toenail with a minimum follow-up period of 8 months. Satisfaction with the procedure was analyzed on a 0–10-point scale. 2.4. Sample Size Calculation The sample size calculation was performed with GPower 3.1.9 software (Universität Kiel, Kiel, Germany) based on a previous pilot study that investigated the postsurgical bleeding difference between partial matrixectomy after phenolization with or without the GS used in Group B. According to this pilot study, the percentage of abundant bleeding observed was 91.2% in the toes of the control group. Taking into account a clinically important reduction of 50% for this percentage, an error of 0.05 with a desired power of 80% (β = 20%) and a minimum sample size of 20 halluces per group, was considered. Taking into to account potential protocol violations, the research included additional toes in each of the experimental groups (5 in Group B and 9 in Group C). 2.5. Statistical Analysis Quantitative data were described as mean, standard deviation (SD), and 95% confidence interval (CI; lower and upper limits). For the analysis of the qualitative data, the Chi-square test was used to analyze the dependency relationship between the variables through cross tables. For the analysis between a categorical and a quantitative variable, normality tests were performed using the Shapiro–Wilk test to determine the most appropriate test based on the behavior of the data. To compare independent samples when the variables’ values met the normality criteria, the T test was used for two groups or ANOVA for three groups. When the variable to be analyzed did not meet the normality criteria, the Mann–Whitney U-test was used for two groups or the Kruskal–Wallis test for three groups. For related samples where the values of the variables were in accordance with normality, the t-test was used. To compare more than two related groups when the variable to be studied did not meet the normality criteria, Friedman’s two-dimensional analysis of variance by ranges was used.IBM SPSS Statistic software (v25, SPSS Inc., Chicago, IL, USA) was used for the data analysis and statistically significant differences were established at p < 0.05 with 95% CI. 3. Results 3.1. Descriptive Dates A total of 52 patients (80 halluces) were included in the study conducted between March 2017 and November 2021. The final study sample consisted of 44 patients (74 halluces), of whom 19 were male and 25 were female. All participants were randomly assigned to three groups. The distribution of the three groups was homogeneous (p > 0.05), with respect to age variables (p = 0.94), sex (p = 0.60), nail morphology (p = 0.38), and stage of onychocryptosis (p = 0.35). The comparison between the laterality of the affected toes (right and left) used for the comparison between the groups demonstrated statistically significant differences (p < 0.05). The descriptive characteristics of the study sample are represented in Table 1. 3.2. Outcome Measurements The outcome measures for each of the treatment groups are shown in Table 2. Regarding the main variable (blood loss), the Kruskal–Wallis test for independent samples demonstrated significant differences with respect to mean blood loss 48 h after surgery in patients from both experimental groups with respect to the control group. The most significant difference from the control group was recorded with respect to mean blood loss in Group C (p < 0.001) and followed by Group B (p < 0.005). No significant differences were found between the experimental groups (p > 0.999). The average difference in recovery time and the number of postoperative cures required between the control group and the experimental groups was not significant (Table 3 and Table 4). The evolution of pain measurements observed on the VAS scale during the first 3 days after surgery was similar in the three groups (Figure 4). The t-test for the related samples did not show significant differences in mean pain at 3 days postoperatively (Figure 5). The two-dimensional Friedman variance estimate by rank for related samples showed that the mean differences in pain at 3 days postoperatively did not differ significantly between groups. The T-test for related simples demonstrated that in the three groups there was a significant increase (p < 0.001) in their mean values between the mean digital circumference before and after surgery. The ANOVA test for independent samples did not show significant differences between the average digital circumference between the groups for recovery time and the number of postoperative cures required (Table 3 and Table 4). Out of 44 patients, 38 (86.36%) responded to the telephone interview. One hundred and thirty-four procedures (67 hallux) were analyzed, observing 10 recurrences, 4 asymptomatic (spicules), and 6 symptomatic, of which only three patients required a second operation. The satisfaction rate was 92.10%. The Mann–Whitney U-test for independent samples showed significant differences in the degree of satisfaction measured on a scale of 0–10 between the group of patients with or without recurrence (Table 5). In any of the groups, complications were recorded with respect to the rate of postoperative infection, hypergranulation, encapsulation, or tissue reaction. 4. Discussion In the standard surgical approach for the management of ingrown toenails, matrix excision should be selective to minimize damage to the surrounding normal structures, but at the same time must be complete and reliable to prevent recurrences. Phenol is an effective protein denaturant that exhibits its cauterizing effect by producing a necrosis of coagulation in soft tissue with a higher incidence of postoperative discharge, hemorrhage, and risk of infection [1]. On the other hand, in chemical matrixectomy, regulation of the level of tissue destruction is uncontrolled and can result in bone injury [23]. The results of our study demonstrate that SP and subsequent WR using GS can reduce these drawbacks, maintaining the advantage of combining procedures. We used the original WR described by Winograd in 1929, and the wounds were left open for secondary healing. In most studies that have combined both procedures, WR was performed prior to SP and the authors claim to use the technique described by Winograd, but the truth is that in most of them, the nail folds were constructed with the help of sutures [2,3,9]. In the original Winograd procedure, the author describes a small incision in the soft tissue of the nail fold and the eponychium in line with the toenail incision; the nail is cut, the ingrown portion is removed, and the matrix and nail bed are destroyed using a curette to prevent recurrence. The author noted that it was unnecessary to excise hypertrophic folds. The wound is left open for secondary healing and dressing changes are performed until the incision heals [22]. In our experience, the main associated drawback of WR alone or after SP is postoperative bleeding, which causes discomfort to the patient and sometimes requires more postoperative monitoring. Postoperative bleeding after nail surgery has been poorly studied in clinical trials, most often as a categorical variable [7,10,11]. Most nail surgery procedures, including SP, are usually performed with strict surgical ischemia using a tourniquet, as the accumulation of blood pooling in the nail bed is undesirable, makes the excision technically more difficult, and can dilute phenol below its optimal concentration. Although SP can reduce postoperative bleeding, when the tourniquet is removed, reactive hyperemia is produced in the hallux, which increases in the standing position with the consequent risk of postoperative bleeding and rapidly decreases the anesthetic effect, which can compromise patient welfare during the postoperative period. The results of our study demonstrate that both CGS and HPGS are effective in reducing bleeding after combining SP/WR. Quantified mean blood loss in the first 48 h after surgery in the patients in the control group was significantly higher compared to both experimental groups. Four clinical trials have analyzed the combined efficacy of both techniques versus SP alone [2,3,7,9]. In two of them, greater bleeding was observed in the groups where both techniques were combined [7,9]. However, the results of these studies cannot be objectively compared with ours since bleeding was analyzed as a categorical variable and in the two of them in the combined procedure groups, nail folds were constructed with the help of sutures [3,9]. Some in vivo studies demonstrate that GS can act as a scaffold to support short-term cell survival and high-level growth factor production, exhibiting good clinical potential to improve wound healing [24]. The results of the present study with respect to healing time demonstrate that the use of GS after the combined procedures does not affect recovery time or the number of dressing changes necessary between any of the groups. The recovery time observed in our study was similar to that reported in other studies with WR alone or combined WR/SP [4,9,25,26,27]. As in previous studies, secondary intention healing using GS has been associated with excellent cosmetic appearance and a high level of patient satisfaction [13]. In any of the experimental groups, complications were not recorded with respect to postoperative infection rate, risk of encapsulation, or tissue reaction. The available evidence demonstrates that the addition of phenol when performing a partial nail avulsion dramatically reduces symptomatic recurrence, but at the cost of increased postoperative infection [5,28]. As in previous studies, we have observed that the removal of cauterized tissue after SP reduces the risk of infection [7]. In our study, no postoperative infections were observed in either group. In the experimental groups, both types of absorbable gelatin sponges demonstrated a high swelling capacity and a rapid hemostatic capacity to prevent exudate accumulation, which may have reduced the risk of infection. In relation to the rest of the secondary outcomes analyzed in the postoperative period, we have not found significant differences between any of the groups. Pain recorded between groups on the first three postoperative days was very similar, close to 5 on the scale on the first day, mild on the second day, and minimal on the third day. Although the pain recorded on the first and second days in experimental Group B was slightly higher than that reported in the control group and in experimental Group C (see Figure 5). Issa et al. found that the intensity and duration of pain was similar, without statistically significant differences between the SP and WR/SP groups, although it was significantly less in the WR/SP group combined treatment than in the WR alone group [3]. In the same way, other studies demonstrate that postoperative pain intensity was similar with SP alone or combined procedures [3,7,9]. With the same HPGS used in our experimental group C, some in vitro and vivo studies carried out in the animal model have demonstrated faster re-absorption and a lower inflammatory response than demonstrated by other CGS [18]. However, we have not found significant differences between the experimental groups regarding the average digital circumference before and after the operation, and the same way as in similar studies performed with the same procedure, no significant differences between the groups in postoperative swelling were recorded [25]. Arista et al. found greater inflammation in individuals in the SP group and in those who combined WR/SP with suture application [9]. In our study, wound closure occurred with secondary intention without the use of sutures or approximation strips, and the average inflammation in the control group was very similar to that recorded in the experimental groups. The recovery time recorded in our study was not conditioned by the use of gelatin sponges. No significant differences were observed with respect to the variable between any of the groups. The number of cures and recovery time was similar (approximately two weeks) to that reported in other studies with WR alone or combined WR/SP [25,26,27,28]. We consider that performing combined SP/WR with gelatin sponges can avoid the delayed healing associated with the cauterized effect on soft tissues and bone of SP alone or combined WR/SP, maintaining the efficacy reported with the combination of both procedures. The gelatin matrix of sponges has the additional advantage of being biocompatible and was demonstrated to be completely resorbed within two weeks. The mean satisfaction reported on a scale of 0–10 by 85% of patients without signs of recurrence was 9.4 ± 0.9 with favorable secondary intention healing, excellent cosmesis, and a high level of patient satisfaction. Our results indicate a recurrence rate of 7.4% after a mean follow-up of 40.8 months (range, 34–51), of which only 4.4% were symptomatic. These results are similar to those reported by Fulton et al. with combined WR/SP treatment and other studies with SP alone [3,8]; however, they are higher than those recorded in other studies with combined procedures with a recurrence rate of 0.6%, although with a significantly shorter follow-up period than our study [3,4]. In any of the experimental groups, no adverse reactions were reported during the course of the application. Only one patient in experimental group B was excluded because he had a tissue reaction because he did not attend the first treatment appointment at 48 h. Despite its biodegradation, we recommend that when necessary, excess amorphous fibrin and gelatin sponge is partially removed at 48 h, especially when using CGS. The combined procedure of WR associated with posterior SP using gelatin sponges is a quick and very effective mode of therapy in the surgical treatment of onychocryptosis and is simple, safe, and easy to perform with minimal postoperative morbidity. On the other hand, GS are hemostatic devices that can be of great benefit for patients with acute bleeding, such as that that can occur in nail surgery after the removal of the tourniquet. Gelatin sponges have a neutral pH that makes them suitable for acting as an ideal carrier for drugs and can be very useful combined with antifibronolitic agents in patients undergoing nail surgery with pharmacological drugs that inhibit blood coagulation. 5. Conclusions Absorbable gelatin sponges proved to be effective and safe devices for the control of minor postoperative bleeding associated with combined SP/WR with favorable secondary intention healing, excellent cosmesis, and a high level of patient satisfaction. The local application of gelatin sponges in ingrown nail surgery may result in a slight increase in the acute inflammatory response without significantly affecting healing time, recovery time, or postoperative pain and swelling. Acknowledgments We thank Sylvia Wild Marcos resident of Área Clínica de Podologíafor her assistance with the data collection and Antonia Sáez Díaz for her assistance with the statistical analysis. The authors give special thanks to the Área Clínica de Podología of the Universidad de Sevilla for its logistic support. Author Contributions Conceptualization, A.C.-F.; methodology, A.C.-F. and A.L.-M.; investigation, A.C.-F. and A.L.-M.; data curation, A.C.-F. and A.L.-M.; writing—original draft preparation, A.C.-F.; writing—review and editing, A.C.-F. and A.L.-M.; visualization, A.C.-F. and A.L.-M.; supervision, A.C.-F. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and the research protocol was approved by the Research Ethic Committee of the University hospitals Virgen Macarena and Virgen del Rocío (ID: 1206-N-15). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Please contact acordoba@us.es with any data requests. Conflicts of Interest The authors declare no conflict of interest. The authors report no involvement in the research by the sponsor that could have influenced the outcome of this work. Figure 1 Flow chart of the patients. Figure 2 Stage III onychocryptosis in the lateral fold (left image). Aspect of the hallux after the Winograd procedure (right image). Figure 3 Immediate postoperative aspect (left) and 48 h after (right) application of gelatin sponges. Figure 4 The image shows one of the weighing performed on a bandage of one of the experimental groups. Figure 5 Evolution of the mean pain measured in 3 postoperative days for three groups of treatment. Abbreviations: VAS, visual analog scale; GS, conventional gelatin sponge; HPGS, high porosity gelatin sponge. jcm-11-02420-t001_Table 1 Table 1 Descriptive characteristics of the study sample. Characteristics Group A (Control) Group B (CGS) Group C (HPGS) Total Average age ± SD (years) 27.4 ± 18.1 30.3 ± 18.3 28.2 ± 18.7 28.7 ± 18.2 Halluces of male 6 (30%) 11 (44%) 10 (34.5%) 27 Halluces of female 14 (70%) 14 (56%) 19 (65.5%) 47 Nail morphology: Normal 2 (10%) 4 (16%) 2 (6.9%) 8 (10.8%) Abnormal 17 (90%) 21 (84%) 27 (93.1%) 66 (89.1%) Laterality: Right 5 (25%) 14 (56%) 20 (69%) 39 (52.7%) Left 15 (75%) 11 (44%) 9 (31%) 35 (47.2%) ONC Stage: Stage 1 2 (10%) 2 (8%) 2 (6.9%) 6 (8.1%) Stage 2 1 (5%) 6 (24%) 1 (3.4%) 8 (10.8%) Stage 3 17 (85%) 17(68%) 26 (89.7%) 60 (81.0%) Abbreviations: SD, standard deviation; CGS, conventional gelatin sponge; HPGS, high porosity gelatin sponge; ONC, onychocryptosis. jcm-11-02420-t002_Table 2 Table 2 Outcome measurements in the three treatment groups. Outcome Measurements Control (n = 20) Mean ± SD (95% CI) Median (IR) Group CGS (n = 25) Mean ± SD (95% CI) Median (IR) Group HPGS (n = 29) Mean ± SD (95% CI) Median (IR) Post-surgical blood loss (g) 3.5 ± 0.8 1.9 ± 0.8 1.9 ± 0.8 2.8 (2.3–4.0) 2.1 (1.5–2.6) 1.8 (1.2–2.2) Digital circumference, pre-operative and at 48 h (cm) 8.3 ± 0.7 8.4 ± 0.7 8.3 ± 0.7 8.8 (7.9–9.0) 8.1 (8.0–9.1) 8.1 (7.8–8.9) 8.8 ± 0.6 8.8 ± 0.7 8.8 ± 0.6 8.9 (8.3–9.2) 8.8 (8.4–9.4) 8.7 (8.3–9.4) Pain day 1 4.2 ± 1.9 5.0 ± 2.3 4.2 ± 2.5 4.1 (3.1–5.8) 5.0 (3.0–7.1) 4 (2–6) 2.4 ± 2.1 3.6 ± 2.7 2.3 ± 2.4 Pain day 2 2.0 (0.3–4.0) 4 (1–6) 0 (0–1.5) 0.6 ± 1.1 1.0 ± 1.6 0.9 ± 2.0 Pain day 3 0 (0–1.0) 0 (0–1.5) 0 (0–1) Recovery time (days) 15.1 ± 4.2 15.3 ± 3.6 16.0 ± 4.0 14 (13–15) 15 (14–20) 14 (14–17.3) Number of cures 3.0 ± 1.1 3.4 ± 1.0 3.5 ± 1.1 3 (2–3) 3 (3–4) 3 (3–4) Abbreviations: SD, standard deviation; CI, confidence interval; IR, interquartile range; CGS, conventional gelatin sponge; HPGS, high porosity gelatin sponge. jcm-11-02420-t003_Table 3 Table 3 Comparison of the outcome between the control group and the experimental Group B. Outcome Measurements Control (n = 20) Mean ± SD (95% CI) Group CGS (n = 25) Mean ± SD (95% CI) p-Value Post-surgical blood loss (g) 3.5 ± 2.3 1.9 ± 0.8 0.005 * Circumference, pre-operative and at 48 h (cm) 8.3 ± 0.7 8.4 ± 0.7 0.616 ** 8.8 ± 0.6 8.8 ± 0.7 0.979 ** Recovery time (days) 15.1 ± 4.2 16.3 ± 3.6 0.144 * Number of cures 3.0 ± 1.1 3.4 ± 1.0 0.051 * Abbreviations: SD, standard deviation; CI, confidence interval; IR, interquartile range; CGS, conventional gelatin sponge. * Kruskal–Wallis test for independent samples. ** One-way ANOVA for independent samples. jcm-11-02420-t004_Table 4 Table 4 Comparison of the outcome between the control group and the experimental Group C. Outcome Measurements Control (n = 20) Mean ± SD (95% CI) Group HPGS (n = 29) Mean ± SD (95% CI) p-Value Post-surgical blood loss (g) 3.5 ± 2.3 1.9 ± 0.8 0.001 * Circumference, pre-operative and at 48 h (cm) 8.3 ± 0.7 8.3 ± 0.7 0.860 ** 8.8 ± 0.6 8.8 ± 0.6 0.970 ** Recovery time (days) 15.1 ± 4.2 16.0 ± 4.0 0.258 * Number of cures 3.0 ± 1.1 3.5 ± 1.1 0.094 * Abbreviations: SD, standard deviation; CI, confidence interval; IR, interquartile range;HPGS, high porosity gelatin sponge. * Kruskal–Wallis test for independent samples. ** One-way ANOVA for independent samples. jcm-11-02420-t005_Table 5 Table 5 Recurrencein relation to the number of procedures performed. Recurrence: No Median (IR) Recurrence: Yes Median (IR) p-Value Number of nail folds evaluated (%) 114 (85.07%) 10 (7.4%) Follow-up (months) 28.0 ± 20.3 40.8 ± 9.5 0.071 * 26 (8–50) 39 (34–51) Satisfaction scale score (0–10) 9.4 ± 0.9 6.8 ± 3.9 0.004 * 10 (9–10) 9 (4.5–9.3) * Mann–Whitney U-test for independent samples. Abbreviations: SD, standard deviation; CI, confidence interval; IR, interquartile range. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Vinay K. Narayan Ravivarma V. Thakur V. Choudhary R. Narang T. Dogra S. Varthya S.B. Efficacy and safety of phenol-based partial matricectomy in treatment of onychocryptosis: A systematic review and meta-analysis J. Eur. Acad. Dermatol. Venereol. 2022 36 526 535 10.1111/jdv.17871 34913204 2. Fulton G.F. O’Donohoe M.K. Reynolds J.V. Keane F.B. Tanner W.A. Wedge resection alone or combined with segmental phenolization for the treatment of ingrowing toenail Br. J. Surg. 1994 81 1074 1075 10.1002/bjs.1800810751 7922070 3. Issa M.M. Tanner W.A. Approach to ingrowing toenails: The wedge resection/segmental phenolization combination treatment Br. J. Surg. 1988 75 181 183 10.1002/bjs.1800750232 3349312 4. Shaikh F.M. Jafri M. Giri S.K. Keane R. Efficacy of wedge resection with phenolization in the treatment of ingrowing toenails J. Am. Podiatr. Med. Assoc. 2008 98 118 122 10.7547/0980118 18347120 5. Rounding C. Bloomfield S. Surgical treatments for ingrowing toenails Cochrane Database Syst. Rev. 2005 2 CD001541 6. Eekhof J.A. Van Wijk B. Knuistingh Neven A. van der Wouden J.C. Interventions for ingrowing toenails Cochrane Database Syst. Rev. 2012 18 CD001541 10.1002/14651858.CD001541.pub3 22513901 7. Álvarez-Jiménez J. Córdoba-Fernández A. Munuera P.V. Effect of curettage after segmental phenolization in the treatment of onychocryptosis: A randomized double-blind clinical trial Dermatol. Surg. 2012 38 454 461 10.1111/j.1524-4725.2011.02232.x 22122781 8. Morkane A.J. Robertson R.W. Inglis G.S. Segmental phenolization of ingrowing toenails: A randomized controlled study Br. J. Surg. 1984 71 526 527 10.1002/bjs.1800710718 6375800 9. Arista G.F. Merino J.E. Onicocriptosis: Estudio comparativo del periodo posoperatorio de una matricectomía parcial lateral con el de una matricectomía parcial lateral con fenolización Dermatol. Rev. Mex. 2006 50 87 93 10. Córdoba-Fernandez A. Rayo-Rosado R. Juarez-Jiménez J.M. Platelet gel for the surgical treatment of onychocryptosis J. Am. Podiatr. Med. Assoc. 2008 98 296 301 10.7547/0980296 18685050 11. Garrido-Castells X. Becerro-de-Bengoa-Vallejo R. Calvo-Lobo C. Losa-Iglesias M.E. Palomo-López P. Navarro-Flores E. López-López D. Effectiveness of Leukocyte and Platelet-Rich Fibrin versus Nitrofurazone on Nail Post-Surgery Bleeding and Wound Cicatrization Period Reductions: A Randomized Single Blinded Clinical Trial J. Clin. Med. 2019 27 1552 10.3390/jcm8101552 12. Tompeck A.J. Gajdhar A.U.R. Dowling M. Johnson S.B. Barie P.S. Winchell R.J. King D. Scalea T.M. Britt L.D. Narayan M. A comprehensive review of topical hemostatic agents: The good, the bad, and the novel J. Trauma Acute Care Surg. 2020 88 e1 e21 10.1097/TA.0000000000002508 31626024 13. Rullan P.P. Vallbona C. Rullan J.M. Mansbridge J.N. Morhenn V.B. Use of gelatin sponges in Mohs micrographic surgery defects and staged melanoma excisions: A novel approach to secondary wound healing J. Drugs Dermatol. 2011 10 68 73 21197526 14. Ndlovu S.P. Ngece K. Alven S. Aderibigbe B.A. Gelatin-Based Hybrid Scaffolds: Promising Wound Dressings Polymers 2021 13 2959 10.3390/polym13172959 34502997 15. Liang J. Liu H. Huang X. Xiong W. Zhao H. Chua S. Li Z. Using tranexamic acidsoaked absorbable gelatin sponge following complex posterior lumbar spine surgery: A randomized control trial Clin. Neurol. Neurosurg. 2016 147 110 114 10.1016/j.clineuro.2016.06.001 27343711 16. Hwa C. Kovich O.I. Stein J.A. Achieving hemostasis after nail biopsy using absorbable gelatin sponge saturated in aluminum chloride Dermatol. Surg. 2011 37 368 369 10.1111/j.1524-4725.2011.01889.x 21342315 17. Hajosch R. Suckfuell M. Oesser S. Ahlers M. Flechsenhar K. Schlosshauer B. A novel gelatin sponge for accelerated hemostasis J. Biomed. Mater. Res. B Appl. Biomater. 2010 94 372 379 10.1002/jbm.b.31663 20578223 18. Goncalves S. Chiossone-Kerdel J.A. Bianco A.S. Ercolino J.M. Hernandez-Rojas J. Effect of absorbable gelatin sponge in the middle ear: In vitro and in vivo animal model Acta Otolaryngol. 2015 135 14 25 10.3109/00016489.2014.951455 25496177 19. Hildenbrand T. A new gelatine-based hemostat for sinonasal surgery: A clinical survey In Vivo 2013 27 523 526 23812224 20. Sielaff M. Hermanns M. Uhlig R. Abou-Ghazalé T. Steinmüller T. Early experience with a novel gelatine-based sponge for local haemostasis in thyroid surgery In Vivo 2014 28 255 258 24632982 21. Kline A. Onychocryptosis: A simple classification system Foot Ankle J. 2008 1 6 13 22. Winograd A.M. A modification in the technic of operation for ingrown toenail. 1929 J. Am. Podiatrc. Med. Assoc. 2007 97 274 277 10.7547/0970274 17660367 23. Caprioli R. Bilotti M.A. Surgical nail procedures Clin. Podiatr. Med. Surg. 1989 6 431 451 2650852 24. Ye D. Wu S. Zhang B. Hong C. Yang L. Characteristics and clinical potential of a cellularly modified gelatin sponge J. Appl. Biomater. Funct. Mater. 2021 19 22808000211035061 10.1177/22808000211035061 34519565 25. Córdoba-Fernández A. Rayo-Rosado R. Juárez-Jiménez J.M. The use of autologous platelet gel in toenail surgery: A within-patient clinical trial J. Foot Ankle Surg. 2010 49 385 389 10.1053/j.jfas.2010.04.019 20605484 26. van der Ham A.C. Hackeng C.A. Yo T.I. The treatment of ingrowing toenails. A randomised comparison of wedge excision and phenol cauterisation J. Bone Jt. Surg. Br. 1990 72 507 509 10.1302/0301-620X.72B3.2341458 27. Herold N. Houshian S. Riegels-Nielsen P. A prospective comparison of wedge matrix resection with nail matrix phenolization for the treatment of ingrown toenail J. Foot Ankle Surg. 2001 40 390 395 10.1016/S1067-2516(01)80006-5 11777234 28. Grieg J.D. Anderson J.H. Ireland A.J. Anderson J.R. The surgical treatment of ingrowing toenails J. Bone Jt. Surg. Br. Vol. 1991 73 131 133 10.1302/0301-620X.73B1.1991748

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091156 animals-12-01156 Article Physiological Changes in Chicken Embryos Inoculated with Drugs and Viruses Highlight the Need for More Standardization of this Animal Model https://orcid.org/0000-0003-1882-4158 Sommerfeld Simone 1* Mundim Antonio Vicente 1 Silva Rogério Reis 1 Queiroz Jéssica Santos 1 Rios Maisa Paschoal 1 Notário Fabiana Oliveira 1 Medeiros Ronchi Alessandra Aparecida 1 https://orcid.org/0000-0001-9320-7278 Beletti Marcelo Emílio 2 https://orcid.org/0000-0002-9138-311X Franco Rodrigo Rodrigues 3 https://orcid.org/0000-0002-6937-1411 Espindola Foued Salmen 3 https://orcid.org/0000-0002-1803-4861 Goulart Luiz Ricardo 3† https://orcid.org/0000-0001-8485-078X Fonseca Belchiolina Beatriz 13 Gonzalez John Michael Academic Editor Owens Casey M. Academic Editor Ravindran Velmurugu Academic Editor 1 School of Veterinary Medicine, Federal University of Uberlândia, Uberlândia 38402-018, Brazil; antoniomundim@ufu.br (A.V.M.); rogerioreissilva98@gmail.com (R.R.S.); jesk.queiroz@hotmail.com (J.S.Q.); maisapaschoal@hotmail.com (M.P.R.); fabiana.notario@hotmail.com (F.O.N.); alessandra.medeiros@ufu.br (A.A.M.R.); biafonseca@ufu.br (B.B.F.) 2 Institute of Biomedical Sciences, Federal University of Uberlândia, Uberlândia 38405-319, Brazil; mebeletti@ufu.br 3 Institute of Biotechnology, Federal University of Uberlândia, Uberlândia 38405-319, Brazil; rodrigorfr@yahoo.com.br (R.R.F.); foued@ufu.br (F.S.E.); lrgoulart@ufu.br (L.R.G.) * Correspondence: simone.sommerfeld@ufu.br; Tel.: +55-34-3225-8656 † In memorian. 29 4 2022 5 2022 12 9 115603 3 2022 22 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary Over the years, the chicken embryo (CE) has been a widely used animal model, which is essential to decrease the number of born animals in experiments. Thus, we intended to know if there is a lack of standardization in using embryos in research. Therefore, the objective of this study was to verify whether alterations in CE of different ages are specific to the model, having as reference a virus and two drugs that cause known alterations in adults and other species. The response of embryos to challenges with viruses and drugs did not always occur as expected compared with adult animals. Although macroscopic and microscopic changes were visible in the infected group, other laboratory analyses did not show significant changes. Our results showed that some drugs and viruses can generate laboratory results that seem to be inherent to the model studied and depend on the CE’s developmental stage. Abstract Several studies have been developed using the Gallus gallus embryo as an experimental model to study the toxicity of drugs and infections. Studies that seek to standardize the evaluated parameters are needed to better understand and identify the viability of CEs as an experimental model. Therefore, we sought to verify whether macroscopic, histopathological, blood count, metabolites and/or enzymes changes and oxidative stress in CE of different ages are specific to the model. To achieve this goal, in ovo assays were performed by injecting a virus (Gammacoronavirus) and two drugs (filgrastim and dexamethasone) that cause known changes in adult animals. Although congestion and inflammatory infiltrate were visible in the case of viral infections, the white blood cell count and inflammation biomarkers did not change. Filgrastim (FG) testing did not increase granulocytes as we expected. On the other hand, CE weight and red blood cell count were lower with dexamethasone (DX), whereas white blood cell count and biomarkers varied depended on the stage of CE development. Our work reinforces the importance of standardization and correct use of the model so that the results of infection, toxicity and pharmacokinetics are reproducible. in ovo chorioallantoic membrane Gammacoronavirus toxicity oxidative stress Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES#88887.336865/2019-00 National Institute of Science and Technology in Theranostics and Nanobiotechnology—INCT-Teranano (CNPq/CAPES/FAPEMIG)# CNPq-465669/2014-0 The authors would like to thanks to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES—(#88887.336865/2019-00), National Institute of Science and Technology in Theranostics and Nanobiotechnology—INCT-Teranano (CNPq/CAPES/FAPEMIG, Grant # CNPq-465669/2014-0) for financial support. FSE is scholarship recipient from Fapemig and CNPq. ==== Body pmc1. Introduction The embryonated egg is self-sufficient, and its natural development at 37 °C and 60% humidity guarantees the maintenance of these animals without more complex means of support. Furthermore, within the egg, the embryo is a highly controlled, accessible and relatively transparent model in which normal physiology, disease pathology and the consequences of experimental manipulation can be easily visualized [1], allowing high reproducibility and simplified and economical experiments [2]. Numerous studies have been carried out using the Gallus gallus embryo as an experimental model for evaluating the toxic effects of drugs and infections. These studies usually evaluated blood, allantoic and amniotic fluid biochemical parameters, erythrocyte morphology, oxidative stress and histopathological lesions [3,4,5,6,7]. As well as in the evaluation methods and collected materials, there is much variation in the ages and inoculation routes, among which the shell membrane (SM), the allantoid fluid (AF), the chorioallantoic membrane (CAM), the yolk sac and the amnion are widely used [7,8,9,10,11]. Chicken embryo (CE) development is completed in just 21 days, being the fastest among the most used animal models and equal only to the mouse embryo [12]. Thus, on each day of incubation age, many physiological changes can significantly influence the studies and responses being evaluated, making the definition of the day of inoculation and collection crucial for realizing an excellent experimental study. The standardization of parameters, such as the day of inoculation and collection, the inoculation route used, the biological materials collected, and the types of analyses performed are crucial for an experiment’s success. Studies that seek the standardization of such parameters are needed to better understand and identify the viability of CE and in ovo studies as models for preclinical tests. Thus, this study aims to verify if the results of viability, weight, pathological and histopathological changes, blood count, dosage of metabolites and/or enzymes and oxidative stress in CE of different ages are specific to the model, proposing and discussing the need for standardization for embryos, using as reference a virus that causes known changes in adult chickens and two drugs, DX which is a glucocorticoid widely used in animals and humans and can cause immunosuppressive effects and FG which is a stimulator of granulocyte precursors widely used in humans in treatment of cancer. 2. Materials and Methods This research was performed in the following laboratories of the Uberlândia Federal University: Poultry Egg Incubation, Nanobiotechnology, Biochemistry, Molecular Biology, Animal Pathology, Veterinary Clinical, and Rodent Vivarium Network. The studies were divided into different phases. The project was evaluated and approved by the Ethics and Research with Animals Committee of the Universidade Federal de Uberlândia (certificate A011/20 and n° 008/21). All methods were performed in accordance with the CONCEA (Conselho Nacional de Controle de Experimentação Animal) guidelines and regulations, and the study is reported in accordance with ARRIVE guidelines. 2.1. Challenge of CE with Gammacoronavirus The first part of the experiment was carried out in specific pathogen-free (SPF) eggs of Gallus gallus challenged with a Gammacoronavirus, the infectious bronchitis virus (IBV) that causes embryonic chicken lesions. The CE were incubated in an artificial incubator (Premium Ecológica®, Belo Horizonte, Brazil) at 37 °C, 58% humidity, with the eggs being turned at a two-hour interval. The eggs were weighed and inoculated at 10 embryonic incubation days (EID). This age was used as between 9–10 EID, lesions in CE can be distinguished [13]. A total of 4.35 log viral particles/CE/of IBV (strain Massachusetts, H52), diluted in sterile Phosphate-buffered saline (PBS), were inoculated in AF from 10 CE. In parallel, four embryos were inoculated as negative controls (NC) with sterile PBS (diluent of the virus). After 24 h of incubation, the CE were evaluated to remove the non-specific mortalities. At 17 EID, 0.5 mL of AF was collected. Blood was collected by sectioning the umbilical vessels and divided into two microtubes: one with EDTA K3 for blood cell analysis and the other with clot activator for serum analysis. In the AF and serum, the minerals, metabolites, and enzymes were quantified. After collecting the blood, the CE were immediately euthanized by decapitation, weighed and evaluated for macroscopic changes. The livers were collected, stored in formalin for histopathological tests and in liquid nitrogen for oxidative stress evaluation. 2.2. Inoculation with DX and FG 2.2.1. Drug Dosages: Pilot Test Prior to commencing the study, we carried out a pilot test to determine the dose of each drug. In this part of the experiment, we used a commercial line of CE, Hy-Line W36, as SPF birds only are mandatory for research with viruses. The eggs were incubated from zero EID in conditions identical to those mentioned in item 2.1. There is no standardized allometric extrapolation calculation for CE. Therefore, we usually test the adult chicken dose in 10 EID CE with an average weight of 20 g (CE and embryonic annexes). The intention was to determine the dose that would not kill the embryo. In the pilot test, we tested two routes: SM and CAM. We used an approximate dose for a hatched animal as the basis. The 2–4 mg/kg doses were used for DX [14]. According to the drug manufacturer, there is no indication of FG for birds, so we based it on human doses (5 mg/kg). Therefore, the following doses were tested: 4, 0.4 and 0.08 µg/CE of DX and 150, 15 and 1.5 µg/CE of FG, with three CE per dose via SM and CAM plus the NC for each route, totaling 42 embryos. After seven days, at 17 EID, the CE were evaluated for macroscopic changes. The dose chosen was based on the group with no expressive mortality or severe lesions in the embryos. For DX, the dose of 0.08 µg/CE did not cause gross lesions in any CE, but the 0.4 and 4 µg/CE resulted in green AF in CE inoculated via SM and CAM. Doses of 1.5, 15 and 150 µg/CE of FG did not alter the CE. Therefore, the used dose of DX was 0.08 µg/CE (~4 µg/kg) and FG was 150 µg/CE (~7.5 µg/kg). As the results for embryos inoculated via CAM and SM were identical, in the first moment, the SM route was used as it was the easiest, with a lower risk of death or lesions, and is an essential route for young or old embryos (which were used in this work). 2.2.2. Drug Tests in CE We started the experiment using CE at 12 EID (Hy-Line W36), as they are older CE and their organs and physiologies more mature than those of younger CE. The egg incubation conditions were identical to those mentioned in item 2.1. A total of 18 CE was used with six CE in the following groups inoculated via SM: (i) treated with 0.08 µg/CE of DX; (ii) treated with 150 µg/CE of FG; and (iii) NC, inoculated with water (diluent of drugs) only. The CE were treated at intervals of 24 h for three days. At 12 EID, the eggs were weighed. After seven days post-inoculation (pi), at 19 EID, we carried out blood and liver collection. We evaluated the weight and macroscopic lesions similar to those described in item 2.1, except for AF, as the amount of this fluid was very low at this age. We also performed inoculations with FG (150 µg/CE) and DX (0.08 µg/CE) and a NC group at intervals of 24 h for three days, with six or eight eggs per group, at ages zero, three and seven EID via SM. After nine, 11 and 10 days of incubation, the CE inoculated at zero, three and seven EID, respectively, were euthanized by decapitation, weighed and evaluated regarding mortality and macroscopic lesions. We did not conduct blood, metabolites or microscopy analysis of the CE inoculated at zero, three and seven EID. Another assay was performed in CE at 10 EID. In this part of the experiment, the route of inoculation for DX was SM. As there were no changes, as expected, in blood granulocyte counts in CE inoculated at 12 EID with FG, and there were no changes in young CE, the CAM route was used for FG in CE of 10 EID. As the FG pathway in humans is subcutaneous and the CAM pathway in CE has direct access to the vessels, we hypothesized that this could be an alternative to test this drug. Thus, it could be possible to assess whether the route could interfere with the results for FG. This part of the experiment was carried out twice, with a total of 18 CE each time, totaling 36 CE. The groups were divided as follows: (i) CE inoculated with 0.08 µg/CE of DX via SM; (ii) NC of DX–CE inoculated with water via SM; (iii) CE inoculated with 150 µg/CE via CAM; (iv) NC of FG–CE inoculated with water via CAM. The CE were treated at intervals of 24 h for 3 days. After seven days pi, at 17 EID, blood, AF, liver weight and macroscopic lesions were collected, similar to that described in item 2.1. The experiment was repeated at an interval of 15 days, identical to the previous experiment. 2.3. Weight of the CE and Annexes During the experiments, the eggs were numbered and weighed on the first day of inoculation and their weights recorded. Then, the embryo and yolk were weighed immediately after collecting blood and AF on the day of collection. As the embryo weight is related to the initial egg weight, we performed an adjustment for an initial egg weight of 50 g, according to Ribeiro et al. (2020) [7]. 2.4. Macroscopic Evaluations We checked and counted the CE that died and identified the death date based on embryo development degree. For live animals, we observed their annexes for the presence of circulatory changes, malformation and colour changes. We also checked the embryos by external evaluation and evaluated the internal organs for circulatory changes, malformation and colour changes and compared the treated groups with the animals in their respective control group. 2.5. Blood Cell Count, Hematocrit, Hemoglobin and Erythrocyte Indices To determine the hematocrit value (Ht), we filled capillary tubes up to 2/3 with a blood sample. We centrifuged them at 12,000× g for 5 min for later reading on a microhematocrit scale. Hemoglobin (Hb) concentration was measured using the cyanmethemoglobin method based in Collier (1944) [15] with modifications using Drabkin’s solution and reading by spectrophotometry at an absorbance of 540 nm. The resulting colour is of an intensity proportional to the hemoglobin content in the blood. In parallel, we measured the hemoglobin by calculating 1/3 of the hematocrit value. The total red blood cell (RBC) count was obtained using the Natt and Herrick (1952) [16] solution. Therefore, we performed a manual count in a Neubauer chamber for the hemacytometer method using blood dilution of 1:200. Counting was performed in the five diagonal squares of the central reticulum of the chamber. The result was multiplied by 10,000 to obtain the value of erythrocytes per microliter of blood [17]. The total white blood cell count and thrombocytes were also determined using the hemacytometer method by diluting the blood with the Natt and Herrick (1952) [16] solution. The leucocytes and thrombocytes were counted simultaneously in the four external reticula of the Neubauer chamber. The result was multiplied by 500 to obtain the value of leucocytes and thrombocytes per microliter of blood [17]. Two different people counted the cells to confirm the precision of the result. The characteristics of the cells (thrombocytes and eosinophils) were confirmed by cytochemistry. We calculated the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) using the formulas [18]:MCV =(Hc ×10) RBCMCH =(Hb ×10)RBCMCHC =(Hb ×100)Hc 2.6. Characterisation of Blood Cells The blood smear slides were prepared for staining with fast panoptic dye for differential leucocyte counts under an optical microscope (Olympus CX31, 100× immersion oil). Slides were also stained using the Periodic Acid Schiff (PAS) cytochemical technique for identifying thrombocytes and Sudan Black B (SBB) for identifying eosinophils [18]. Finally, the cells were counted twice at different moments under an optical microscope. Knowing that serotonin binds to gaseous formaldehyde, we carried out the marking of thrombocytes. We based this on Swayne et al. (1986) [19] with some modifications. First, blood smear slides were placed in a box containing formalin and kept for 24 h at 50 °C. Next, we read the slides under a UV light microscope (EVOS FL Cell Imaging System, Life Technologies Corporation, Waltham, MA, USA). Thrombocyte diameter was measured using the ImageJ morphometry program. Slides from healthy and adult chickens (24 weeks of age) of the same line were prepared in parallel as a positive control. 2.7. Biochemical Analyses of the Serum and AF As the collection of blood from the embryo is not simple and some researchers perform analysis of metabolites and enzymes in allantois, we performed the analysis in blood and allantois to determine if the results were similar. Biochemical analysis of serum and AF was performed in an automatic biochemical analyser (ChemWell® 2910, Awareness Technology). The analytes aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), creatinine (Creat), uric acid (UA), calcium (Ca), phosphorus (P) and c-reactive protein (CRP) (Bioclin®, Minas Gerais, Brazil) were measured in both serum and AF. 2.8. Oxidative Stress Immediately after euthanasia by decapitation, the livers of the CE were removed and stored at −80 °C. The samples were homogenized with 10 mM sodium phosphate buffer (pH 7.4) and centrifuged at 800× g, at 4 °C for 10 min. The supernatant was used to quantify the biomarkers of oxidative stress. 2.8.1. Reactive Oxygen Species (ROS) The samples were incubated with dichloro-dihydro fluorescein diacetate (10 µM) and 5 mM Tris-HCl buffer (pH 7.4) for 3 min. Subsequently, the fluorescence was measured at 530 nm (excitation in 474 nm). 2.8.2. Lipid Peroxidation The liver homogenates were incubated with 0.67% thiobarbituric acid (TBA) and 10% trichloroacetic acid (TCA), for 120 min. Then, n-butanol was added to the samples to remove the organic phase and the fluorescence was measured at 553 nm, after excitation at 515 nm. Lipid peroxidation was determined using the malondialdehyde (MDA) analytical curve [20]. 2.8.3. Sulfhydryl Group The sulfhydryl group was detected using ditionitrobenzoic acid (DTNB) diluted in 0.2 mM potassium phosphate buffer (pH 8.0). The liver homogenates were incubated for 30 min with 1 mM phosphate buffer (pH 7.4) and 10 mM DTNB solution. The presence of sulfhydryl groups was spectrophotometrically detected at 412 nm [21]. 2.8.4. Total Antioxidant Capacity The liver homogenates were incubated with 300 mM sodium acetate buffer (pH 3.6), 10 mM 2,4,6-tri (2pyridyl)-striazine (TPTZ) and 20 mM ferric chloride at 37 °C for 6 min, at 593 nm. A trolox analytical curve determined the antioxidant capacity and sodium acetate buffer was used as a blank [22]. 2.9. Histopathology The fragments of liver fixed in 10% buffered formalin were processed for the preparation of histological slides stained with Hematoxylin and Eosin (HE) [23]. Histopathologic morphology was qualitatively assessed and classified for the presence of inflammation, degeneration, necrosis and circulatory change. Intracellular fat deposits (lipidosis) were evaluated semiquantitatively and classified by assigning a score relative to the level of lipid deposits in the sample, according to the histological classification of Brunt et al. (1999) [24] modified by Angulo (2009) [25] with adaptations. According to Fáncsi (1982) [26], the cytoplasm of hepatocytes from CE has drops of lipids, and the amount of lipid inclusions increases mainly around the twenty-seventh day. Thus, the presence of small vacuoles in the cytoplasm of hepatocytes was considered physiological in the assessment of lipidosis. The scores were evaluated according to the NC and divided into: 0 corresponding to normal, with discrete lipid deposits; 1 with slight lipid deposits; 2 with moderate lipid deposits; 3 with a marked level of lipid deposition. In the analysis of the inflammatory process, the number of inflammatory foci and the number of inflammatory cells in the foci were microscopically evaluated in all the livers of the embryos according to the NC. The inflammatory process was classified as: 0 corresponding to normal, with no inflammatory process; 1—mild, when the number of inflammatory foci was less than three with mild inflammatory infiltrate; 2—moderate, when the number of inflammatory foci ranged from three to five with moderate inflammatory infiltrate; and 3—marked, when the number of inflammatory foci was greater than five with marked inflammatory infiltrate. Regarding circulatory alterations, hemorrhage and congestion, they were evaluated semiquantitatively in relation to the NC as: 0 corresponding to normal, with no circulatory alterations; 1—light; 2—moderate; 3—accentuated. 2.10. Angiogenesis Although no injury was observed in CE treated with FG at any dose or route and we noticed an increase in blood vessels in some eggs treated with FG. Therefore, we performed another experiment adding five and 25 times the dose of FG used in the previous investigation. The dose increase was to assess whether doses higher than those used in humans were capable of causing visible damage to embryos and test the hypothesis that FG induces angiogenesis. We tested 34 CE (Hy-Line W36) at three EID and divided them into the following groups: (i) treated with 0.08 µg/CE of DX; (ii) treated with 150 µg/CE of FG; (iii) treated with 750 µg/CE of FG; (iv) treated with 3.75 mg/CE of FG; (v) NC, inoculated with water (diluent of drugs) only, all by the SM route. The CE was treated at intervals of 24 h for days. At 12 EID, we evaluated the viability and macroscopic lesions. We evaluated the angiogenesis in CAM using ImageJ software with the Vessels Analysis [27] plugin. 2.11. Statistical Analysis We assessed whether the data followed normality. For parametric data, we used Analysis of variance (ANOVA) followed by Tukey’s test and for non-parametric data, we used the Kruskal–Wallis test. For evaluation of two groups, we used the t test for parametric data and Kruskal–Wallis or Wilcoxon tests for non-parametric data. A Pearson correlation test was performed. We considered a 95% confidence interval using the program GraphPad Prism 9.2. 3. Results 3.1. The Virus Can Change Blood Cell Count, Calcium and Lipid Peroxidation in the Liver Of the ten CE inoculated with Gammacoronavirus, three died, six had lesions and one survived without lesions. The injuries, as expected, were dwarf or curled embryos with a green liver in one CE, five tiny embryos (being 2 CE with a hemorrhagic or enlarged liver, and 1 CE with milky AF). The presence of the virus led to a change in the weight of live embryos, as expected. Embryos inoculated with the virus had an average weight of 13.41 g (±2.86), whereas the NC weighed 18.17 g (±1.62) with p = 0.0173. We could not weigh the yolk sac of embryos inoculated with the virus because they disintegrated during manipulation. We performed a blood cell count, quantification of metabolites, minerals and enzymes and the results are described in Table 1 and Table 2. Figure 1 shows the levels of ROS, ferric reducing antioxidant power (FRAP), lipid peroxidation and sulfhydryl groups in the liver of CE infected with Gammacoronavirus. In comparison with the NC, the virus decreased the lipid peroxidation levels (p < 0.05) of the embryos. In the histopathological analysis of the liver, congestion and hemorrhage were observed in CE infected with the virus. There was also a moderate inflammatory process predominantly composed of heterophils (Table 3 and Figure 2). 3.2. The Age of Inoculation and Type of Drug Result in Different Effects on Injury, Mortality or Embryo Viability The CE were inoculated with the same dose of drugs at 0, 3, 7, 10 and 12 EID for three days. After inoculation, the CE were evaluated daily by light candling, and the dead CE necropsied and removed. Between 7–12 days of inoculation, the eggs were opened and necropsied (Table 4). Of the dead embryos inoculated at zero EID with DX, two were hemorrhagic and died between three to four EID; two died at nine EID and had malformed heads, and two survived but had malformed heads. The only dead CE treated with FG died at nine EID without a specific injury. At three EID, the CE inoculated with DX had the CAM not wholly formed around the CE, and the yolk sac leaked very quickly. Dead CE inoculated at seven EID with DX presented a smaller size, gelatinous albumen, irregular warping and a green liver, and died between 14–15 EID. Injured live CE showed decreased size and curling, plus petechiae on top of the head. The injured CE in NC and FG inoculated at 10 EID showed a delicate increase in the liver. The injured CE inoculated at 10 EID treated with DX had an enlarged liver which was dark or light green. The lesions observed in live injured CE inoculated at 12 EID with DX were white material over the heart (with UA aspect) and beige material within the allantois. This material was different in appearance and colour from the UA commonly found in the allantois in normal embryos. 3.3. The Weight of CE Can Be a Drug Analysis Tool Depending on Age As shown above, most CE inoculated with DX at zero EID did not survive; thus, the weights of the embryos from the control group and the FG-treated group were evaluated, and there was no difference in weights. CE inoculated with DX at three EID showed decreased weight compared with NC and FG groups. The same occurred in CE inoculated at seven EID. The yolk of embryos inoculated with DX presented a lower weight in relation to the NC and FG groups inoculated at three and seven EID. In CE inoculated at 10 EID and 12 EID, a lower weight of embryos treated with DX compared with embryos from NC and FG groups was observed, but this difference was not observed in the yolk weights of these animals (Figure 3). 3.4. The Blood Cell Count Can Change According to the Age of Inoculation The blood samples collected from CE treated with FG did not show a statistical difference compared with the NC group for inoculations made at 10 EID and 12 EID, but the same did not occur for CE treated with DX. Compared with the NC group, the samples from embryos inoculated with DX at 10 EID had a smaller number of erythrocytes, lower values of hematocrit and hemoglobin, and a smaller number of thrombocytes (Table 5). No statistically relevant differences were observed in the amounts of total leucocytes. In CE inoculated at 12 EID, embryos treated with DX showed a lower number of erythrocytes. The number of thrombocytes was more significant than the NC group, contrary to the CE treated at 10 EID. In the group inoculated at 12 EID, there was a statistical difference for the amounts of total leucocytes, which was higher for the group treated with DX, heterophiles which was higher, and lymphocytes which were lower compared with the NC group (Table 6). 3.5. Not All Metabolites, Enzymes and/or Minerals Change Even in Liver-Damaged Embryos Among the serum and AF samples analyzed only AST from serum samples of CE treated with DX at 10 EID showed a statistical difference compared with the NC group (Table 7, Table 8 and Table 9). 3.6. The Amount of Metabolites, Enzymes and Minerals in Serum and Allantois Are Not Always Identical The UA, Creat, ALP, GGT, ALT, AST, Ca and P of serum and AF samples from embryos treated with FG and DX at 10 EID were evaluated. Only AST and calcium in CE treated with FG and Crea, ALP and P in CE treated with DX showed similar values for the two analyzed samples (Table 7 and Table 8). Although the values of the metabolites and enzymes were not equivalent in all analyses, the results were identical since there were no statistical differences except for AST, which increased in the group treated with DX at 10 EID in serum but not in the AF. 3.7. The Age of Inoculation Is an Essential Factor for Changing Oxidative Stress Parameters Figure 4 shows the levels of sulfhydryl groups, FRAP, lipid peroxidation and ROS in the liver of CE inoculated with FG and DX at 10 and 12 EID. In comparison to the NC, FG increased the levels of sulfhydryl groups (p < 0.05) of CE treated at 10 EID. At the same EID, embryos treated with DX had increased levels of ROS production. In CE treated at 12 EID with FG, there was no difference between the NC group, but the CE treated with DX showed a decrease in the sulfhydryl group and FRAP levels and an increase in the levels of lipid peroxidation and ROS production. 3.8. There Is a Correlation between the Results for Haemoglobin Using a Drabkin Solution or Performing the Calculation of One Third of the Haematocrit There was a correlation between the assessment of hemoglobin by calculating one third of the hematocrit and the method using the Drabkin solution. The r value in the group of CE inoculated at 12 EID was 0.61, representing a moderate correlation. In the groups treated at 10 EID with FG, DX and virus, the r value was 0.86, 0.85 and 0.86, respectively, showing a strong correlation. 3.9. Characterisation of Granulocytes and Thrombocytes by Cytochemistry Thrombocytes were labelled by the formaldehyde method (Figure 5) and the analysis showed that the thrombocytes’ diameters in CE were lower than in adult animals. Moreover, the FG and DX increased the diameter of the thrombocytes. Blood smear slides were stained by PAS cytochemical methods for identification of thrombocytes by staining of cytoplasmic glycogen granules and SBB for identification of eosinophils by staining of cytoplasmic granules. These two methods were used to differentiate lymphocytes that were negative for PAS and heterophils that were negative for SBB (Figure 6). 3.10. Unidentified Granulocytes Were Found in Several Groups Despite the various methods of analysis used to identify the cells, some cells with a rounded nucleus and basophilic round cytoplasmic granules were found on some slides in groups NC, FG, DX, and in the group infected with the virus (Figure 7). These cells were not positive by cytochemistry used in our work. 3.11. Liver Histopathological Analysis The degenerative change observed in the CE livers was lipidosis. The hepatocytes were vacuolated, ranging from few and small light vacuoles to large light vacuoles, shifting the nucleus to the periphery, with the hepatocyte resembling an adipocyte. As in virus-infected embryos, the inflammatory process had a periportal distribution and was predominantly composed of heterophils (Figure 8). The animals inoculated with FG at 10 EID showed an inflammatory process with infiltration of heterophils. Embryos inoculated with DX at 10 EID showed a mild inflammatory process and circulatory alteration and animals inoculated at 12 EID showed a mild inflammatory process and degeneration (lipidosis) (Table 10). 3.12. FG in High Doses Does Not Cause Injury to Angiogenesis in CE We tested the hypothesis that FG could cause angiogenesis in CE using several doses. Unlike that believed, FG did not induce angiogenesis (measured by vascular density and vessel length density), just as DX did not change the number of vessels (Supplementary Figure S1). As already reported in the previous experiment, DX led to incomplete CAM formation. The high dose of FG also did not cause visible changes in the embryo. 4. Discussion CE provide an ideal model for investigating the development of pathogens such as viruses and testing drug effects, evaluating both toxicity and pharmacokinetics. Thus, CE as an animal model can be an important ally for carrying out experiments that require quick and less complex execution and with limited resources. The CE and its annexes constitute a favorable environment for replicating several viruses, being widely used for the isolation or production of vaccines [9]. IBV causes dwarfism, hemorrhage and death when inoculated into embryonated eggs. Some strains of the Gammacoronavirus can cause nephropathies and others hemagglutination [28]. However, IBV has a minimal agglutination capacity for erythrocytes in chickens [29]. Our study showed a decrease in hemoglobin concentration, hematocrit value and the number of erythrocytes in infected embryos compared with the NC group, indicating anemia. Hematimetric indices did not differ in relation to the NC group. Thus, we can classify anemia as normocytic and normochromic. This means that the cells were of standard size and hemoglobin concentration, thus there was a decrease in RBC, but there was no response from the bone marrow to release cells into the bloodstream. Normocytic and normochromic anemia can indicate decreased erythrocyte production, which can develop rapidly in birds with diseases involving infectious agents [18]. Although there was no statistical difference in the number of leucocytes in the infected animals compared with embryos in the NC group, some animals had a high leucocyte count (>30,000/mm3). In contrast, others had a low count (<4000/mm3) (Supplementary Table S1). These results contributed to the increase in the standard deviation in this analysis. During an infection the response of the white blood cell count can vary. In the initial of disease, leucocytosis may occur as a response by the body. However, as the leucocytes are consumed, leucopenia may occur when the demand for leucocytes is above the production capacity of these cells by the bone marrow [18]. From 12 EID, the hematopoiesis in CE is more active and occurs mainly in bone marrow [30]. Therefore, in this work, hematopoiesis in the CE was intense since we used animals between 10–17 EID. However, although the CE used in this work were from the same flock and the mother had high consanguinity, there may be an inherent variation in the model itself. There was no change in the Creat and UA levels in serum and allantois samples from infected CE compared with the NC group, and macroscopic kidney lesions were not observed either. On the other hand, the liver of infected animals was macroscopically altered, with an increase in volume and a greenish colour. In addition, we observed a moderate inflammatory reaction by histopathologic analyses (Figure 2), although liver enzymes were not increased in the serum or allantois compared with the control group [31]. There was also a decrease in lipid peroxidation rather than an increase. The absence of a rise in GGT, ALT, AST and the reduction in lipid peroxidation indicate that the stress was very intense, reducing liver responsiveness. Serum calcium levels from virus-infected CE decreased compared with the NC group. Possibly the viruses can hijack the host cell’s machinery and utilize the host cell’s calcium to create an environment adapted to meet their own demands for replication [32]. This hypothesis is supported in the work of Cao et al. (2011) [33]. These authors observed that the expression levels of some calcium-binding proteins were increased after in ovo IBV infection. These proteins facilitate the transcellular transport of calcium, suggesting that IBV may disrupt cellular Ca2+ homeostasis for its own benefit. In addition to virus experiments, drug studies using CE as a model provide a technically simple way to study complex biological systems for in vivo drug toxicity and pharmacokinetic assessment. For example, DX is a widely used glucocorticoid. Its administration in CE can cause immunosuppressive effects increasing embryonic catecholamines that alter development and cause death [34]. There was high macroscopic lesion and mortality rate after the DX inoculation, similar to other studies [34,35,36]. As expected, the mortality was age-dependent. In addition, in our study, CE treated with DX reduced the weight in all CE that lived. The reduced weight in CE treated with DX can be related to muscle and bone development inhibition [35,36]. Furthermore, high doses of glucocorticoids can generate suppression of growth hormone activity in the pituitary gland which is fully established at the beginning of the last week of the embryonic development of CE [36]. Thus, we can suggest that DX promotes a delay in embryonic development, negatively influencing embryo weight gain, which may explain the delay in the complete formation of CAM found by us. Unlike DX, FG did not cause significant changes and deaths. The only death observed in an embryo inoculated at zero EID was not accompanied by changes and occurred in an embryo from the NC group, probably caused by a natural process. Similarly, the injury in the CE inoculated via CAM possibly resulted from the inoculation process since hemorrhage may occur using this route. CE treated with DX at 10 and 12 EID were anemic. The CE treated with DX showed a decreased erythrocyte count and decreased hematocrit and at 10 EID, hemoglobin concentration compared with CE in the NC group. There were also decreases in hematocrit, hemoglobin and erythrocyte values in animals treated with DX at 12 EID, but only erythrocytes showed a statistical difference for the NC group. Despite that, there was a high correlation between hemoglobin and hematocrit (r value = 0.78), hematocrit and erythrocyte (r value = 0.77) and hemoglobin and erythrocytes (r value = 0.81). Therefore, the erythrocyte reduction accompanied the reduction in hemoglobin and hematocrit. Although the CE treated with DX had anemia, the hematimetric indices were not statistically different between the groups treated and the NC, defining anemia as normocytic and normochromic. Chickens treated with corticosteroids show increased energy expenditure [37]. Embryos treated with DX at 10 EID had higher yolk consumption, indicated by the lower yolk weight of these embryos compared with animals in the NC group. The nutritional deficit associated with liver damage caused by the drug may have impaired the production of erythrocytes, causing normocytic normochromic anemia. In CE inoculated with DX at 10 EID, there was a decrease in the number of thrombocytes compared with embryos from the NC group. Perhaps the production of thrombocytes in CE treated with DX at 10 EID was impaired by the damage caused in the liver. Thrombopoietin (TPO) is the regulator of megakaryocyte development and thrombocyte production and its expression in chickens occurs mainly in the liver [38]. Hemopoietic activity in the liver starts at seven EID with a peak at 14 EID [39], but is more active from 12 EID [30]. In animals treated with DX at 12 EID, the opposite was observed. There was an increase in the number of thrombocytes compared with CE from the NC group. Thrombocytosis may reflect a rebound response after recovery from other conditions associated with excessive use of thrombocytes. Considering that CE from 12 EID had a more mature liver, active bone marrow and hemopoietic activity [30], thrombocytosis can be explained in CE treated at 12 EID. Additionally, it should also be considered that in birds, thrombocytes have a phagocytic function and the influence of glucocorticoids on these cells is unknown [40]. In embryos treated with DX at 12 EID, there was an increase in the number of leucocytes, different to that observed in CE inoculated at 10 EID. This can be explained by the onset of lymphoid activity in the Bursa of Fabricius at 12 EID [41], with a greater capacity to respond to the stimulus caused by the drug. In mammals treated with DX, an initial leucocytosis may occur, mainly due to neutrophilia [29]. In fact, CE inoculated at 12 EID showed an increase in H/L ratio due to the increase in heterophils and a decrease in lymphocytes. This corroborates several studies in born animals [42,43,44]. During CE development, granulopoiesis is more predominant; however, at hatching, the granulocytes begin to be replaced by lymphocytes within first three days [18]. Taken together, the results show that embryos with a small difference in embryo development stage can completely alter the cell count response. We do not know if this occurs with other drugs. However, knowing that the embryo is an ascending animal model, further work must be carried out to consider the best age for using the model depending on the expected objective. As a granulocyte colony-stimulating factor (G-CSF), FG is used in human medicine to increase levels of neutrophils in the bloodstream. Therefore, we expected that the same effect would be observed in the CE in this experiment, increasing heterophils that have characteristics and performance corresponding to human neutrophils. However, no increase in granulocytes were observed in animals treated with FG at 10 EID or 12 EID either by inoculation in CAM or SM. Perhaps this did not occur because FG is a synthetic compound for human use and may not have the same results in other species. The analysis of biochemical parameters provides essential data for the assessment of the clinical status of the animal. However, blood samples collected in research with CE do not always allow this analysis because it is not easy and takes time. Therefore, alternatives samples have been used to assess these parameters, such as amniotic fluid and AF [5,7,45]. In this work, we compared the biochemical analyses of serum and AF and observed that the values found for the two samples were not always similar. However, the differences observed between groups in serum samples were also observed in AF samples, except for AST, which may indicate that this enzyme does not have a good analysis from allantois. It is known that proteins found in serum have different physical and biochemical properties and change in various physiological and pathological conditions. One of the problems with enzymatic analysis methods is that the reagents were designed to provide the substrate and its optimal concentrations for human plasma, but these variables can change depending on the species. For example, birds have deficient levels of activity of the enzyme ALT in the liver tissue, so in cases of severe liver damage, this enzyme may present normal values. AST activity occurs in multiple tissues, but the main ones are liver and muscle, being considered sensitive but not very specific in cases of liver problems. GGT activity is increased in all conditions in which hepatocellular damage is present. ALP is associated with the regulation of bird growth, participating in chondrogenic and osteoblastic activities. Thus, physiological variations can be observed, with higher activity levels resulting from bone growth in young birds. Elevations in ALP may be associated with liver disease even if its activity in this organ is minimal [26]. In our study, only the AST enzyme of CE treated with DX at 10 EID showed a statistical difference compared with the CN group. However, histopathological findings and results of oxidative stress biomarkers indicate that there was liver damage. At 12 EID, there was no increase in AST in CE treated with DX. At this age, just 50% of the CE had a macroscopic injury (Table 3) and maybe because of this, the AST level did not increase. However, the AST maximum value of the group treated of DX at 19 EID was greater than the NC (Supplementary Table S2). Thus, AST may be the best parameter for analysis of liver function in embryo serum. High concentrations (up to five times) of UA in plasma can lead to precipitation of this acid in the form of crystals, which accumulate in tissues. Situations of hypouricemia are rare and may be related to severe liver damage with a consequent decrease in UA production [46]. The excretion of Crea occurs via the kidneys, but in birds, most creatine is excreted before being converted to creatinine [18]. Thus, increased Crea concentrations are rare and may occur in severe renal impairment, significantly if filtration is affected [46]. In our study, no changes in urea or Creat were observed in any of the treatments. Macroscopic lesions were also not observed. This can mean that there was no damage to the CE kidneys. However, as we did not perform histopathological analysis of the kidneys, we cannot rule out the possibility that the high damage caused by the treatment does not lead to changes in biochemical parameters. Drugs can cause increased production of oxidants and the formation of free radicals, which, by exceeding the body’s ability to neutralise and scavenge these radicals, can cause organ damage [47]. Our study showed an increase in oxidative stress biomarkers ROS in the livers of embryos treated with DX at 10 EID and 12 EID and an increase in lipid peroxidation in embryos treated at 12 EID. In adult animals, corticosteroids can increase oxidative stress [48], but a similar approach was never studied in CE. The increased energy expenditure triggered by high circulating corticosteroid levels may be responsible for the increased of ROS as reflected by increased lipid peroxidation [48]. The body uses enzymatic and non-enzymatic antioxidants to neutralize damage caused by free radicals and minimize excessive oxidative stress. Sulfhydryl groups are an example of essential antioxidants status, suggesting how this process is controlled and protected from oxidative damage. Embryos that were treated at 12 EID showed decreased sulfhydryl groups and FRAP values, indicating that these embryos had difficulty matching the damage caused by free radicals in the induction of oxidative stress by DX. Embryos treated with FG at 12 EID did not show changes in oxidative stress biomarkers compared with CE from the NC group. However, in CE inoculated at 10 EID via CAM, FG increase the sulfhydryl group content. Filgrastim is a granulocytic colony-stimulating factor (G-CSF). It has biological activity identical to that of endogenous human G-CSF with a free cysteine at position 17 with an ionized sulfhydryl group that is very reactive to free radical oxidation [49]. From this, we can conclude that FG may have shown an antioxidant effect, with possible protection of the embryo against ROS. To measure hemoglobin in this experiment, we used Drabkin’s solution and compared it with the values obtained using the 3Hb/Hc ratio. Our study showed a moderate correlation in embryos treated at 12 EID and a strong correlation in embryos treated at 10 EID [50]. Thus, we can conclude that the calculation based on hematocrit can be used to approximate the hemoglobin value in situations where measurement by spectrophotometry is not possible. However, this replacement is only possible if there is no suspicion of hemolysis, since hemolysis due to collection or pathological problems, promotes a decrease in hematocrit without a proportional reduction in hemoglobin. To perform the differential count of leucocytes in birds, there is a great difficulty is differentiating between thrombocytes and lymphocytes. Though not identical, the nuclei of thrombocytes and small lymphocytes are too similar to serve as a basis for distinguishing between these two cell types. In the present study, cells in fast panoptic stained CE blood smears with small, round or oval nuclei with dense chromatin clumps were categorized as thrombocytes if they had cytoplasmic vacuoles and colourless cytoplasm. Cells classified as small lymphocytes had similar nuclei but scant amounts of blue or dark blue cytoplasm without vacuoles. To establish a basis for the categorization of these cells, some cytochemical properties of these cells were compared. The typical thrombocytes were visualized by UV after being exposed to gaseous formaldehyde. Swayne et al. (1986) [19] observed that most of the thrombocytes (99%) had been fluorescent after gaseous formaldehyde treatment and all of the small lymphocytes had been non-fluorescent. This fluorescence resulted from serotonin condensation products. We measured the thrombocytes found in the slides of animals inoculated in this study and compared them with cells found in the blood smear slides of adult chickens. Thrombocytes from adult chickens had a larger size compared with the NC group, which averaged 8.5 µm. We could not determine why FG increased the size of thrombocytes. Using the PAS, we characterized the thrombocytes as PAS positive, whereas lymphocytes and erythroblasts were PAS negative (Figure 6). The eosinophils were SBB positive, whereas the heterophils were SBB negative (Figure 6). The use of PAS and SBB is important for better cell classification. Despite the different forms of differentiation used to identify cells in the blood smears of embryos in this experiment, some cells remained without conclusive identification. The authors identified these cells as being a type of granulocyte, but they could be confused with eosinophils, basophils or granulocyte precursors [17,18,51]. These cells were found in samples from embryos treated with FG (20%) and DX (25%) inoculated at 10 EID, animals infected with virus (100%), and in animals from the NC group (23.07%) inoculated at 10 EID. Another response observed in the use of FG in humans is the stimulation of endothelial cells with consequent angiogenesis [52,53,54]. In this study, we analyzed the blood vessels of the CAM of animals inoculated with FG to identify a possible increase in vessel density characterizing the occurrence of angiogenesis. However, there was no statistical difference between CE inoculated with FG and the NC group. 5. Conclusions Overall, the results of this work provide vital information on the use of CE as an experimental model. The response of CE to challenges from viruses and drugs does not always go as expected. Although macro and microscopic damage were visible in viruses, white blood cell counts and inflammation biomarkers such as CRP did not change. It is important to mention that some drugs can be innocuous and not result in expected effects on CE, which was the case with FG. In the case of DX, changes in blood parameters and biomarkers seem to be inherent to the model and are highly dependent on the developmental stage of the CE. This article reiterates the wonderful value of the CE as an animal model. However, our work sheds light on the importance of standardization and the correct use of the model (considering the laboratory analysis, drug, age, route) so that the infection, toxicity and pharmacokinetic results are reliable. Acknowledgments To Felipe Cesar Gonçalves and Igor Paula de Castro who support us with technical experience. To Hy Line Companie that support us with eggs in our research. The authors thank Luiz Ricardo Goulart Filho, who passed away in 2021. His departure left us with a vast sadness, but his brilliance and generosity reached all who had the honor to learn from him. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani12091156/s1, Figure S1: Angiogenesis was measured by vascular density and vessel length density using the software ImageJ with the plugin Vessels Analysis 58. The CE was inoculated at 3 EID and evaluated at 12 EID. (A) vascular density, (B) vessel length density, (C) Photos CAM (NC), (D) Photo CAM treated with DX, (E) Photo CAM treated with FG (150 µg/CE), (F) Photo CAM treated with FG (750 µg/CE), (G) Photo CAM treated with FG (3.75 mg/CE); Table S1: Maximum and minimum values and median of hematological analysis from CE infected with Gammacoronavirus and NC; Table S2: Maximum and minimum values and median of metabolites and minerals from the serum and AF of CE from CE infected with Gammacoronavirus and NC; Table S3: Maximum and minimum values and median of hematological analysis from CE treated with DX at 10 EID and their respective NC; Table S4: Maximum and minimum values and median of hematological analysis from CE treated with FG at 10 EID and their respective NC; Table S5: Maximum and minimum values and median of metabolites and minerals from the serum and AF of CE treated with FG and DX inoculated at 10 EID and their respective NC; Table S6: Maximum and minimum values and median of metabolites and minerals from the serum of CE treated with FG and DX inoculated at 12 EID and NC; Table S7: Maximum and minimum values and median of hematological analysis from CE treated with FG and DX at 12 EID and NC. Click here for additional data file. Author Contributions B.B.F. idealized and coordinated the project. S.S., B.B.F., A.V.M. and L.R.G. designed all the experiments. S.S., R.R.S. and B.B.F. carried out drugs and virus inoculation in chicken embryos. S.S., B.B.F., R.R.S., M.P.R., J.S.Q. and F.O.N., collected the biological material and macroscopic analysis. F.S.E. and R.R.F. performed the biochemical studies of the liver chicken embryos. F.O.N. and A.A.M.R. performed the histopathological analyses of the liver chicken embryos. S.S., M.P.R., J.S.Q. and M.E.B. performed the blood analyses of the chicken embryos. S.S., A.V.M. and B.B.F. wrote the manuscript. All the authors revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The project was evaluated and approved by the Ethics and Research with Animals Committee of the Universidade Federal de Uberlândia (certificate A011/20 and n 008/21). All methods were performed in accordance with the relevant guidelines and regulations. Data Availability Statement Data are contained within the article or supplementary material. Full data will be made available if the publisher requests it. Conflicts of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationship that could be construed as a potential conflict of interest. Figure 1 Levels of oxidative stress biomarkers in terms of ROS production (A), FRAP (B), lipid peroxidation (C) and sulfhydryl groups (D) in liver of CE after infection with Gammacoronavirus. The asterisk symbol indicates a statistical difference between the groups (** = p ≤ 0.01). FRAP: ferric reducing antioxidant power. ROS: reactive oxygen species. NC: Negative control. Figure 2 Histopathological analysis of CE liver infected with Gammacoronavirus at 10 EID. (A) NC sample showing sinusoids with a minimal number of erythrocytes (arrow). (B) NC sample without perivascular inflammatory infiltrates (arrow). (C) Liver of virus-infected CE with congestion characterised by erythrocyte-filled sinusoids (arrows). (D) Liver of virus-infected CE with inflammatory infiltrate (arrow). The bars in images (A,C) represent 200 µm and the bars in images (B,D) represent 60 µm. Figure 3 Adjusted embryo and yolk weight in grams at different ages and treatments. Embryo weight inoculated at 0 EID (A), 3 EID (B), 7 EID (C) inoculated via SM, 10 EID inoculated with FG via CAM (E), 10 EID inoculated with DX via SM (G), 12 EID inoculated at SH (I). Yolk sac weight at 7 EID (D), 10 EID inoculated with FG via CAM (F), 10 EID inoculated with DX (H) via SM, 12 EID (J) inoculated at SH. In CE inoculated at 0 EID, the CE of the DX group died. We could not weigh the yolk sac of embryos inoculated with the DX at 0 and 3 EID because they disintegrated during manipulation. The asterisks symbols indicate a statistical difference between the groups (* = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001; **** = p ≤ 0.0001). NC: Negative control. FG: Filgrastim. DX: Dexamethasone. Figure 4 Levels of oxidative stress biomarkers in terms of sulfhydryl groups (A), FRAP (B), lipid peroxidation (C) and ROS production (D) in chicken embryos’ livers after inoculation with FG via CAM at 10 EID; sulfhydryl groups (E), FRAP (F), lipid peroxidation (G) and ROS production (H) in chicken embryos’ livers after inoculation with DX via SM at 10 EID; sulfhydryl groups (I), FRAP (J), lipid peroxidation (K) and ROS production (L) in chicken embryos’ livers after inoculation with FG and DX via SM in 12 EID. The asterisks symbols indicate a statistical difference between the groups (* = p ≤ 0.05; *** = p ≤ 0.001; **** = p ≤ 0.0001). FRAP: ferric reducing antioxidant power. ROS: Reactive oxygen species. NC: Negative control. FG: Filgrastim. DX: Dexamethasone. Figure 5 Diameter of formalin-labelled thrombocytes evaluated. (A) diameter of thrombocytes in SPF CE inoculated with Gammacoronavirus. (A1) thrombocytes stained in group treated with virus. (B) Diameter of thrombocytes in CE treated with filgrastim at 10 EID. (B1) thrombocytes stained in group treated with FG inoculated at 10 EID via CAM. (C) Diameter of thrombocytes in CE treated with DX inoculated at 10 EID via SM. (C1) thrombocytes stained in the group treated with DX. (D) Diameter of thrombocytes in CE treated with FG and DX inoculated at 12 EID via SM. (D1) thrombocytes stained in the group treated with FG. (D2) thrombocytes stained in the group treated with DX. (E) Thrombocytes stained in the NC group in CE inoculated at 10 EID. (E1) trans, (E2) UV, (E3) over. The asterisks symbols indicate a statistical difference between the groups (* = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001; **** = p ≤ 0.0001). NC: Negative control. Scale bar = 100 µm. Figure 6 Blood smear slides stained by cytochemical methods. (A) Sudan Black B (SBB) positive eosinophils (arrow) and SBB negative heterophils (arrowhead). (B) Periodic Acid Schiff (PAS) positive thrombocytes (arrow) and PAS negative lymphocytes (arrowhead). Figure 7 Unidentified granulocytes in blood smear stained with fast Panotico® (arrow 100×). Figure 8 Histopathological analysis of the livers of CE treated with DX and FG at 10 EID. (A) CE liver sample from NC with a small amount of lipids in vacuoles in hepatocytes considered normal for comparison with the other groups (arrow). (B) Sample from the NC without inflammatory infiltrate (arrow). (C) DX-treated CE sample showing large cytoplasmic vacuoles in hepatocytes containing lipid characterizing lipid degeneration (arrow). (D) DX-treated CE sample with sinusoids filled with erythrocytes characterizing congestion (arrows). (E) FG-treated CE sample with perivascular inflammatory infiltrate (white arrow) and congestion (black arrows). The bars in images (A–C) represent 60 µm and the bars in images (D,E) represent 200 µm. animals-12-01156-t001_Table 1 Table 1 Blood cell counts in CE treated with Gammacoronavirus inoculated at 10 EID. NC Virus Ht (%) 21.00 (±1.63) a 15.60 (±2.30) b Hg (g/dL) (1/3 Ht) 7.00 (±0.55) a 5.20 (±0.77) b Hg (g/dL) (Cyanmethemoglobin) 8.05 (±0.16) a 6.23 (±0.99) b Erythrocytes × 106/mm3 2.05 (±0.15) a 1.59 (±0.23) b MCH (pg) 35.15 (±3.47) a 40.08 (±9.95) a MCV (fL) 38.15 (±3.47) a 40.08 (±9.95) a MCHC (g/dL) 96.96 (±17.07) a 100.6 (±27.12) a Thrombocytes × 104/mm3 2.21 (±0.51) a 2.75 (±2.05) a Leucocytes × 103/mm3 8 (±2.67) a 20.4(±22.5) a Monocytes/mm3 28 (±55) a 254 (±465.5) a Lymphocytes/mm3 650 (±730) a 2170 (±2943) a Heterophiles × 103/mm3 7.29 (±2.27) a 17.6 (±18.8) a Heterophile/lymphocyte 24.09 (±18.53) a 28.32 (±20.51) a Eosinophils/mm3 0.00 (±0.00) a 0.00 (±0.00) a Unidentified granulocytes/mm3 23.75(±47.5) a 259 (±459.1) a Basophils/mm3 0.00 (±0.00) a 0.00 (±0.00) a The value in parentheses is the standard deviation. Different letters on the same line show statistical difference (p < 0.05). Monocytes, MCV: non-parametric test. Unidentified granulocytes: cells not tagged in Sudan Black B or PAS but not having a standard format. NC: Negative control. Ht: Hematocrit. Hg: Hemoglobin. MCH: corpuscular volume. MCH: mean corpuscular hemoglobin. MCHC: mean corpuscular hemoglobin concentration. animals-12-01156-t002_Table 2 Table 2 Quantification of metabolites, minerals and enzymes in CE treated with Gammacoronavirus inoculated at 10 EID. NC (Serum) Virus (Serum) NC (AF) Virus (AF) UA (mg/dL) 21.76 (±23.13) a 22.63 (±15.17) a 18.53 (±21.53) a 54.30 (±29.89) a Creat (mg/dL) 1.42 (±1.21) ab 0.50 (±0.35) a 3.21 (±1.41) b 1.55 (±1.11) ab ALP (U/L) 1857 (±1108) a 2258 (±1540) a 80.40 (±26.37) b 55.74 (±49.27) b GGT (U/L) 81.53 (±55.34) a 252.4 (±121.5) a 210.00 (±172.2) a 184.00 (±119.40) a AST (U/L) 264.00 (±40.84) a 451.00 (±281.1) a 200.00 (±123.3) a 592.00 (±283.10) a ALT (U/L) 57.50 (±233.6) a 92.00 (±85.73) a 63.00 (±38.1) a 48.00 (±22.80) a CRP (mg/L) 24.55 (±10.31) a 24.75 (±9.91) a 59.50 (±32.55) a 84.00 (±45.72) a Ca (mg/dL) 95.23 (±66.18) a 10.23 (±8.08) b 16.05 (±10.48) b 16.60 (±13.77) b P (mg/dL) 6.82 (±3.70) a 5.50 (±2.96) a 19.19 (±8.57) b 10.76 (±6.32) ab The value in parentheses is the standard deviation. Different letters on the same line show statistical difference (p < 0.05). NC: Negative control. AF: Allantoic fluid. UA: Uric Acid. Creat: Creatinine. ALP: Alkaline Phosphatase. GGT: gamma-glutamyl transferase AST: aspartate aminotransferase. ALT: alanine aminotransferase. Ca: calcium. P: phosphorus and CRP: c-reactive protein. animals-12-01156-t003_Table 3 Table 3 Histopathological analysis of liver from CE infected with Gammacoronavirus. NC Virus Inflammation 0.00 a (Mi: 0.00; Ma: 0.00) 2.00 b (Mi: 0.00; Ma: 2.00) Degeneration 0.00 a (Mi: 0.00; Ma: 0.00) 0.00 a (Mi: 0.00; Ma: 0.00) Necrosis 0.00 a (Mi: 0.00; Ma: 0.00) 0.00 a (Mi: 0.00; Ma: 3.00) Circulatory change 0.00 a (Mi: 0.00; Ma: 0.00) 1.00 b (Mi: 0.00; Ma: 3.00) Different letters on the same line show statistical difference (p < 0.05). Mi: Minimum; Ma: Maximum. NC: Negative Control. animals-12-01156-t004_Table 4 Table 4 Evaluation of CE’s viability, lesions and embryonic mortality when treated with FG and DX at different ages. Alive (Normal) Injured Dead Total Zero EID NC 6 0 1 6 FG 5 0 1 6 DX 0 2 4 6 3 EID NC 6 0 0 6 FG 6 0 0 6 DX 1 5 0 6 7 EID NC 6 0 0 6 FG 6 0 0 6 DX 0 3 3 6 10 EID CAM NC 5 1 0 6 FG 6 1 0 7 10 EID SM CN 6 0 0 6 DX 3 6 0 9 12 EID NC 6 0 0 6 FG 6 0 0 6 DX 3 3 0 6 Note: eggs broken or killed by the inoculation process were removed from the analysis. CE inoculated at 0, 3, 7, 10 and 12 EID were evaluated at 9, 11, 10, 17 and 19 EID, respectively. EID: Embryonic incubation days. CAM: Chorioallantoic membrane. SM: Shell membrane. NC: Negative control. FG: Filgrastim. DX: Dexamethasone. animals-12-01156-t005_Table 5 Table 5 Blood cell count in CE treated with FG and DX at 10 EID. 10 EID NC (CAM) FG (CAM) NC (SM) DX (SM) Ht (%) 21.64 (±3.38) # 18.43 (±3.60) # 20.33 (±1.86) a 17.13 (±2.35) b Hg (g/dL) (1/3 ht) 7.20 (±1.13) # 6.14 (±1.20) # 6.78 (±0.62) a 5.71 (±0.78) b Hg (g/dL) (Cyanmethemoglobin) 8.12 (±0.66) # 7.52 (±1.29) # 7.83 (±0.65) a 7.22 (±1.12) b Erythrocytes × 106/mm3 1.76 (±0.53) # 1.73 (±0.28) # 2.05 (±0.27) a 1.58 (±0.26) b MCH (pg) 50.34 (±14.07) # 47.35 (±4.95) # 38.35 (±2.04) a 45.58 (±6.69) b MCV (fL) 107.1 (±13.82) # 135.0 (±43.47) # 99.73 (±8.53) a 109.10 (±13.39) a MCHC (g/dL) 38.33 (±3.3) # 41.00 (±3.48) # 38.56 (±1.85) a 42.12 (±2.65) b Thrombocytes × 103/mm3 15.8 (±0.97) # 13.3 (±13.1) # 16.3 (±5.1) a 8.75 (±5.75) b Leucocytes × 103/mm3 3.68 (±2.06) # 4.25 (±2.85) # 4.15 (±0.74) a 3.37 (±2.58) a Monocytes/mm3 0.00 (±0.00) # 14.17 (±33.09) # 0.00 (±0.00) a 0.00 (±0.00) a Lymphocytes/mm3 159.01 (±97.72) # 220.80 (±216.80) # 318.5 (±326.3) a 357 (±396.6) a Heterophiles/mm3 3523 (±2020) # 3973 (±2565) # 3104 (±1251) a 2453 (±1695) a Heterophile/lymphocyte 26.26 (±34.75) # 32.85 (±31.77) # 38.51 (±38.11) a 36.80 (±43.29) a Eosinophils/mm3 5.00 (±15.00) # 25.53 (±69.48) # 0.00 (±0.00) a 1.18 (±6.03) a Basophils/mm3 0.00 (±0.00) # 0.00 (±0.00) # 0.00 (±0.00) a 0.00 (±0.00) a Statistical comparisons are between FG CAM and NC CAM (test t) or DX SM and NC SM (test t). Different symbols on the same line indicate a statistical difference between FG and NC inoculated via CAM. Different lowercase letters on the same line indicate a statistical difference between DX and NC at inoculated via SM (p < 0.05). MCH, eosinophils, monocytes; via CAM: non-parametric test. Ht: Hematocrit. Hg: Hemoglobin. MCH: corpuscular volume. MCH: mean corpuscular hemoglobin. MCHC: mean corpuscular hemoglobin concentration. animals-12-01156-t006_Table 6 Table 6 Blood cell count in CE treated with FG and DX at 12 EID. 12 EID CN (SM) FG (SM) DX (SM) Ht (%) 27.80 (±3.56) A 28.67 (±3.50) A 23.40 (±3.71) A Hg (g/dL) (1/3 ht) 8.93 (±1.03) A 9.55 (±1.17) A 9.26 (±1.48) A Hg (g/dL) (Cyanmethemoglobin) 10.61 (±3.04) A 10.55 (±1.48) A 7.90 (±1.13) A Erythrocytes × 106/mm3 2.59 (±0.48) A 2.66 (±0.38) A 1.90 (±0.26) B MCH (pg) 41.13 (±9.12) A 39.65 (±2.12) A 41.09 (±1.39) A MCV (fL) 102.8 (±25.82) A 108.4 (±10.98) A 128.6 (±10.29) A MCHC (g/dL) 37.75 (±7.09) A 36.92 (±4.40) A 33.28 (±3.18) A Thrombocytes × 103/mm3 5.30 (±1.35) A 5.66 (±1.08) A 14.5 (±7.32) B Leucocytes × 103/mm3 4.00 (±1.05) A 4.96 (±1.78) A 16.3 (±8.30) B Monocytes/mm3 45.83 (±40.79) AB 61.67 (±34.86) A 40.00 (±132.70) B Lymphocytes/mm3 457.60 (±114.80) A 516.70 (±139.00) A 271.90 (±139.80) B Heterophiles/mm3 3498 (±940.50) A 4132 (±1549) A 16,900 (±8200) B Heterophile/lymphocyte 8.00 (±1.55) A 7.00 (±3.30) A 65.77 (±29.40) B Eosinophils/mm3 0.00 (±0.00) A 0.00 (±0.00) A 0.00 (±0.00) A Basophils/mm3 0.00 (±0.00) A 0.00 (±0.00) A 0.00 (±0.00) A Statistical comparisons are between NC, FG, DX inoculated via SM (ANOVA). Different uppercase letters on the same line indicate a statistical difference (p < 0.05). Leucocytes, lymphocytes and monocytes FG via CAM: non-parametric test. Ht: Hematocrit. Hg: Hemoglobin. MCH: corpuscular volume. MCH: mean corpuscular hemoglobin. MCHC: mean corpuscular hemoglobin concentration. animals-12-01156-t007_Table 7 Table 7 Quantification of metabolites, minerals and enzymes in serum and AF in CE treated with FG and DX at 10EID inoculated via CAM. 10 EID CAM NC (Serum) FG (Serum) NC (AF) FG (AF) UA (mg/dL) 11.00 (±7.60) # 16.49 (±14.55) # 97.57 (±31.16) * 87.88 (±51.40) * Creat (mg/dL) 1.31 (±0.68) # 0.80 (±0.63) # 2.49 (±0.85) * 3.19 (±0.77) * APL (U/L) 1836 (±815.30) # 2380 (±298.40) # 47.05 (±32.58) * 61.26 (±53.26) * GGT (U/L) 63.17 (±85.13) # 67.00 (±81.56) # 14.53 (±5.50) # 12.49 (±6.98) # AST (U/L) 48.12 (±29.53) # 49.18 (±15.01) # 15.14 (±11.55) * 9.33 (±6.02) * ALT (U/L) 54.02 (±51.67) #* 158.00 (±150.10) # 8.28 (±4.07) * 11.71 (±8.51) * Ca (mg/dL) 18.80 (±17.03) # 21.80 (±21.75) # 12.50 (±7.05) # 8.34 (±4.62) # P (mg/dL) 7.48 (±4.52) # 4.52 (±2.58) # 15.37 (±9.04) #* 22.13 (±9.63) * Statistical comparisons are between FG CAM and NC CAM (t test) serum and AF inoculated at 10 EID. Different symbols on the same line indicate a statistical difference between FG and NC inoculated at 10 EID via CAM. Creat in FG group inoculated at 10 EID: non-parametric test. UA: Uric Acid. Creat: Creatinine. ALP: Alkaline Phosphatase. GGT: gamma-glutamyl transferase AST: aspartate aminotransferase. ALT: alanine aminotransferase. Ca: calcium. P: phosphorus and CRP: c-reactive protein. animals-12-01156-t008_Table 8 Table 8 Quantification of metabolites, minerals and enzymes in serum and AF in CE treated with FG and DX at 10EID inoculated via SM. 10 EID SM NC (Serum) DX (Serum) NC (AF) DX (AF) UA (mg/dL) 13.86 (±10.37) ab 12.04 (±9.84) a 60.00 (±38.63) ab 70.30 (±45.93) b Creat (mg/dL) 0.53 (±0.35) a 1.12 (±1.03) a 3.57 (±0.53) b 2.62 (±1.29) b APL (U/L) 2125 (±1365) a 4233 (±5830) a 45.94 (±39.65) b 77.81 (±54.46) b GGT (U/L) 81.20 (±94.30) a 49.41 (±82.50) a 12.72 (±11.31) a 19.51 (±9.54) a AST (U/L) 37.55 (±20.84) a 99.89 (±68.10) b 39.87 (±55.81) a 13.27 (±4.25) a ALT (U/L) 142.6 (±161.3) a 142.8 (±138.7) a 8.00 (±1.58) a 13.00 (±8.69) a Ca (mg/dL) 9.15 (±10.65) a 30.53 (±30.50) a 6.50 (±2.80) a 15.91 (±13.46) a P (mg/dL) 4.68 (±3.33) a 5.80 (±4.21) a 23.65 (±6.32) b 26.90 (±11.91) b Statistical comparisons are between DX SM and NC SM (t test) inoculated at 10 EID (t test) serum and AF. Different lowercase letters on the same line indicate a statistical difference between DX and NC inoculated at 10 EID via SM. GGT in DX group inoculated at 10 EID via SM: non-parametric test. GGT and ALP in DX group inoculated at 10 EID via SM; Creat in FG group inoculated at 10 EID: non-parametric test. UA: Uric Acid. Creat: Creatinine. ALP: Alkaline Phosphatase. GGT: gamma-glutamyl transferase AST: aspartate aminotransferase. ALT: alanine aminotransferase. Ca: calcium. P: phosphorus and CRP: c-reactive protein. animals-12-01156-t009_Table 9 Table 9 Quantification of metabolites, minerals and enzymes in serum and AF in CE treated with FG and DX at 12 EID inoculated via SM. 12 EID SM CN (Serum) FG (Serum) DX (Serum) UA (mg/dL) 8.28 (±1.88) A 12.53 (±10.17) A 9.50 (±10.82) A Creat (mg/dL) 1.37 (±1.04) A 0.70 (±0.53) A 1.39 (±0.53) A APL (U/L) 2194 (±322.90) A 2439 (±437.70) A 1928 (±356.40) A GGT (U/L) 47.25 (±40.85) A 59.84 (±64.05) A 69.08 (±47.69) A AST (U/L) 123.1 (±81.82) A 108.2 (±19.21) A 556.1 (±27.61) A ALT (U/L) 56.68 (±59.33) A 130.5 (±226.9) A 73.70 (±25.15) A Ca (mg/dL) 17.98 (±9.35) A 17.70 (±12.28) A 13.63 (±10.32) A P (mg/dL) 5.22 (±3.89) A 4.76 (±2.85) A 9.52 (±3.28) A Statistical comparisons are between NC, FG, DX inoculated at 12 EID via SM (ANOVA) in serum because at 19 EID (age at colect) there are not AF. Different uppercase letters on the same line indicate a statistical difference in CE inoculated at 12 EID. UA, ALT, group inoculated at 12 EID: non-parametric test. UA: Uric Acid. Creat: Creatinine. ALP: Alkaline Phosphatase. GGT: gamma-glutamyl transferase AST: aspartate aminotransferase. ALT: alanine aminotransferase. Ca: calcium. P: phosphorus and CRP: c-reactive protein. animals-12-01156-t010_Table 10 Table 10 Histopathological analysis of liver from embryos inoculated with FG and DX at 10 and 12 EID. 10 EID 12 EID NC (CAM) FG (CAM) NC (SM) DX (SM) NC FG DX Inflammation 0 (Mi: 0; Ma: 0) # 1 (Mi: 0; Ma: 2) * 0 (Mi: 0; Ma: 0) a 0 (Mi: 0; Ma: 2) b 0 (Mi: 0; Ma: 0) A 0 (Mi: 0; Ma: 1) AB 1 (Mi: 0; Ma: 2) B Degeneration 0 (Mi: 0; Ma: 0) # 0 (Mi: 0; Ma: 0) # 0 (Mi: 0; Ma: 0) a 0 (Mi: 0; Ma: 3) a 0 (Mi: 0; Ma: 0) A 0 (Mi: 1; Ma: 1) AB 1 (Mi: 1; Ma: 3) B Necrosis 0 (Mi: 0; Ma: 0) # 0 (Mi: 0; Ma: 0) # 0 (Mi: 0; Ma: 0) a 0 (Mi: 0; Ma: 2) a 0 (Mi: 0; Ma: 0) A 0 (Mi: 0; Ma: 0) A 0 (Mi: 0; Ma: 0) A Circulatory change 0 (Mi: 0; Ma: 0) # 0 (Mi: 0; Ma: 1) # 0 (Mi: 0; Ma: 0) a 1 (Mi: 0; Ma: 3) b 0 (Mi: 0; Ma: 0) A 0 (Mi: 0; Ma: 1) A 0 (Mi: 0; Ma: 0) A Different symbols on the same line indicate a statistical difference between FG and NC inoculated via CAM. Different lowercase letters on the same line indicate a statistical difference between DX and NC at inoculated via SM. Different uppercase letters on the same line indicate a statistical difference in CE inoculated at 12 EID (p < 0.05). Mi: Minimum, Ma: Maximum. NC: Negative control. CAM: Chorioallantoic membrane. FG: Filgrastim. SM: Shell Membrane. DX: Dexamethasone. EID: Embryonated incubation days. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kain K.H. Miller J.W.I. Jones-Paris C.R. Thomason R.T. Lewis J.D. Bader D.M. Barnett J.V. Zijlstra A. The chick embryo as an expanding experimental model for cancer and cardiovascular research Dev. Dyn. 2014 243 216 228 10.1002/dvdy.24093 24357262 2. Lokman N.A. Elder A.S.F. Ricciardelli C. Oehler M.K. Chick chorioallantoic membrane (CAM) assay as an in vivo model to study the effect of newly identified molecules on ovarian cancer invasion and metastasis Int. J. Mol. Sci. 2012 13 9959 9970 10.3390/ijms13089959 22949841 3. Halik G. Strojny B. Hotowy A. Grodzik M. Piast R. Toxicity studies of six types of carbon nanoparticles in a chicken-embryo model Int. J. Nanomed. 2017 12 2887 2898 4. Hruba H. Abdelsalam E.E.E. Anisimov N. Bandouchova H. Havelkova B. Heger T. Kanova M. Kovacova V. Nemcova M. Piacek V. Reproductive toxicity of fluoroquinolones in birds BMC Vet. Res. 2019 15 209 10.1186/s12917-019-1957-y 31226987 5. Khosravi A. Sharifi I. Tavakkoli H. Derakhshanfar A. Keyhani A.R. Salari Z. Mosallanejad S.S. Bamorovat M. Embryonic toxico-pathological effects of meglumine antimoniate using a chick embryo model PLoS ONE 2018 13 e0196424 10.1371/journal.pone.0196424 29799841 6. Liu P. Deng G. Guo X.Q. Kuang J. Zhang C. Cao H. Hu G. Clinicopathology of Gout in Growing Layers Induced by Avian Nephrotrophic Strains of Infectious Bronchitis Virus Pak. Vet. J. 2015 35 8318 7. de Morais Ribeiro L.N. de Paula E. Rossi D.A. Monteiro G.P. Junior E.C.V. Silva R.R. Franco R.R. Espindola F.S. Goulart L.R. Fonseca B.B. Hybrid Pectin-Liposome Formulation against Multi-Resistant Bacterial Strains Pharmaceutics 2020 12 769 10.3390/pharmaceutics12080769 32823823 8. Haselgrübler R. Stübl F. Stadlbauer V. Lanzerstorfer P. Weghuber J. An In Ovo Model for Testing Insulin-mimetic Compounds J. Vis. Exp. 2018 134 e57237 10.3791/57237 9. Guy J.S. Isolation and Propagation of Coronaviruses in Embryonated Eggs Methods Mol. Biol. 2015 454 109 117 10. Fauzia E. Barbhuyan T.K. Shrivastava A.K. Kumar M. Garg P. Khan M.A. Robertson A.A.B. Raza S.S. Chick Embryo: A Preclinical Model for Understanding Ischemia-Reperfusion Mechanism Front. Pharmacol. 2018 9 1034 10.3389/fphar.2018.01034 30298003 11. Shi L. Ko M.L. Huang C.C.Y. Park S.Y. Hong M.P. Wo C. Ko G.Y.P. Chicken Embryos as a Potential New Model for Early Onset Type I Diabetes J. Diabetes Res. 2014 2014 354094 10.1155/2014/354094 25133191 12. Bronner-Fraser M. Methods in Cell Biology: Avian Embryology 2nd ed. Elsevier New York, NY, USA 2017 1 432 13. Maier H.J. Bickerton E. Britton P. Coronaviruses: Methods and protocols Coronaviruses Methods Protoc. 2015 1282 1 282 14. Viana F.A.B. Guia Terapêutico Veterinário 3rd ed. CEM Lagoa Santa, Brazil 2019 1 528 15. Collier H.B. Standardization of Blood Haemoglobin Determinations Can. Med. Assoc. J. 1944 50 550 20323122 16. Natt M.P. Herrick C.A. A New Blood Diluent for Counting the Erythrocytes and Leucocytes of the Chicken Poult. Sci. 1952 31 735 738 10.3382/ps.0310735 17. Campbell T.W. Hematology Avian Medicine: Principles and Application Wingers Publishing Lake Worth, FL, USA 1997 810 18. Thrall M.A. Veterinary Hematology and Clinical Chemistry 2nd ed. Wiley Hoboken, New Jersey, USA 2012 784 19. Swayne D.E. Stockham S.L. Johnson G.S. Cytochemical Properties of Chicken Blood Cells Resembling Both Thrombocytes and Lymphocytes Vet. Clin. Pathol. 1986 15 17 24 10.1111/j.1939-165X.1986.tb00639.x 15221711 20. Justino A.B. Pereira M.N. Peixoto L.G. Vilela D.D. Caixeta D.C. Souza A.V. Teixeira R.R. Silva H.C.G. Moura F.B.R. Moraes I.B. Hepatoprotective Properties of a Polyphenol-Enriched Fraction from Annona crassiflora Mart. Fruit Peel against Diabetes-Induced Oxidative and Nitrosative Stress J. Agric. Food Chem. 2017 65 4428 4438 10.1021/acs.jafc.7b01355 28514152 21. Aksenov M.Y. Markesbery W.R. Changes in thiol content and expression of glutathione redox system genes in the hippocampus and cerebellum in Alzheimer’s disease Neurosci. Lett. 2001 302 141 145 10.1016/S0304-3940(01)01636-6 11290407 22. Franco R.R. Justino A.B. Martins M.M. Silva C.G. Campana P.R.V. Lopes J.C.D. Almeida V.L. Espindola F.S. Phytoscreening of Vochysiaceae species: Molecular identification by HPLC-ESI-MS/MS and evaluating of their antioxidant activity and inhibitory potential against human α-amylase and protein glycation Bioorg. Chem. 2019 91 103122 10.1016/j.bioorg.2019.103122 31357074 23. Tolosa E.M.C. Rodrigues C.J. Behmer O.A. Freitas-Neto A.G. Manual de Técnicas Para Histologia Normal e Patológica 2nd ed. Manole São Paulo, Brazil 2003 331 24. Brunt E.M. Janney C.G. Di Bisceglie A.M. Neuschwander-tetri B.A. Bacon B.R. Nonalcoholic steatohepatitis: A proposal for grading and staging the histological lesions Am. J. Gastroenterol. Suppl. 1999 94 2467 2474 10.1111/j.1572-0241.1999.01377.x 25. Angulo P. Nonalcoholic fatty liver disease Encycl. Mol. Mech. Dis. 2009 346 1429 26. Fáncsi T. Ultrastructural Studies of the Goose Embryo Liver Anat. Histol. Embryol. 1982 11 138 146 10.1111/j.1439-0264.1982.tb00929.x 6214969 27. Elfarnawany M.H. Signal Processing Methods for Quantitative Power Doppler Microvascular Angiography Ph.D. Thesis The University of Western Ontario London, ON, Canada 2015 28. Decaro N. Gammacoronavirus: Coronaviridae The Springer Index of Viruses Springer New York, NY, USA 2011 Volume 100 403 29. Schultze B. Cavanagh D. Herrler G. Neuraminidase treatment of avian infectious bronchitis coronavirus reveals a hemagglutinating activity that is dependent on sialic acid-containing receptors on erythrocytes Virology 1992 189 792 794 10.1016/0042-6822(92)90608-R 1322604 30. Sheng G. Primitive and definitive erythropoiesis in the yolk sac: A bird’s eye view Int. J. Dev. Biol. 2010 54 1033 1043 10.1387/ijdb.103105gs 20563984 31. Zhang Z. Sun M. Deng J. Yu J. Yang X. Zhao W. Chen G. Wang P. Zika virus induced more severe inflammatory response than dengue virus in chicken embryonic livers Front. Microbiol. 2019 10 1 9 10.3389/fmicb.2019.01127 30728808 32. Zhou Y. Frey T.K. Yang J.J. Viral calciomics: Interplays between Ca2+ and virus Cell Calcium 2009 46 1 17 10.1016/j.ceca.2009.05.005 19535138 33. Cao Z. Han Z. Shao Y. Geng H. Kong X. Liu S. Proteomic analysis of chicken embryonic trachea and kidney tissues after infection in ovo by avian infectious bronchitis coronavirus Proteome Sci. 2011 9 11 10.1186/1477-5956-9-11 21385394 34. Heiblum R. Arnon E. Chazan G. Robinzon B. Gvaryahu G. Snapir N. Glucocorticoid Administration During Incubation: Embryo Mortality and Posthatch Growth in Chickens Poult. Sci. 2001 80 1357 1363 10.1093/ps/80.9.1357 11558923 35. Eriksen M.S. Haug A. Torjesen P.A. Bakken M. Prenatal exposure to corticosterone impairs embryonic development and increases fluctuating asymmetry in chickens (Gallus gallus domesticus) Br. Poult. Sci. 2003 44 690 697 10.1080/00071660310001643660 14965089 36. Mashaly M.M. Effect of Exogenous Corticosterone on Chicken Embryonic Development Poult. Sci. 1990 70 371 374 10.3382/ps.0700371 37. Lin H. Decuypere E. Buyse J. Oxidative stress induced by corticosterone administration in broiler chickens (Gallus gallus domesticus): 2. Short-term effect Comp. Biochem. Physiol.-B Biochem. Mol. Biol. 2004 139 745 751 10.1016/j.cbpc.2004.09.014 15581807 38. Bartunek P. Karafiat V. Bartunkova J. Pajer P. Dvarakova M. Kralova J. Zenke M. Dvorak M. Impact of chicken thrombopoietin and its receptor c-Mpl on hematopoietic cell development Exp. Hematol. 2008 36 495 505 10.1016/j.exphem.2007.12.001 18243490 39. Wong G.K. Cavey M.J. Development of the liver in the chicken embryo. I. Hepatic cords and sinusoids Anat. Rec. 1992 234 555 567 10.1002/ar.1092340411 1456458 40. Maxwell M.H. Avian blood leucocyte responses to stress Worlds. Poult. Sci. J. 1993 49 34 43 10.1079/WPS19930004 41. Bellairs R. Osmond M. The Atlas of Chick Development 3rd ed. Academic Press Cambridge, MA, USA 2014 42. Vicuña E.A. Kuttappan V.A. Galarza-Seeber R. Latorre J.D. Faulkner O.B. Hargis B.M. Tellez G. Bielke L.R. Effect of dexamethasone in feed on intestinal permeability, differential white blood cell counts, and immune organs in broiler chicks Poult. Sci. 2012 94 2075 2080 10.3382/ps/pev211 26195804 43. Jain N.C. Essentials of Veterinary Hematology 1st ed. Wiley-Blackwell Hoboken, NJ, USA 1993 44. Aengwanich W. Effects of dexamethasone on physiological changes and productive performance in broilers Asian J. Anim. Vet. Adv. 2007 32 157 161 10.3923/ajava.2007.157.161 45. Elsayed M. Mohamed N. Hatab M. Elaroussi M. Oxidative Stress of in-Ovo Ochratoxin A Administered during Chick Embryonic Development Braz. J. Poult. Sci. 2019 21 eRBCA-2019-0637 10.1590/1806-9061-2017-0637 46. Ritchie B.W. Harrison J.G. Harrison L.R. Avian Medicine: Principles and Application Wingers Publishing Lake Worth, FL, USA 2009 1384 47. Mandelker L. Vajdovich P. Oxidative stress in applied basic research and clinical practice-Studies on experimental models Eur. J. Histochem. 2012 56 ejh.2012.br9 48. Lin H. Decuypere E. Buyse J. Oxidative stress induced by corticosterone administration in broiler chickens (Gallus gallus domesticus): 1. Chronic exposure Comp. Biochem. Physiol.-B Biochem. Mol. Biol. 2004 139 737 744 10.1016/j.cbpc.2004.09.013 15581806 49. Hasegawa M. A thermodynamic model for denaturation of granulocyte colony-stimulating factor: O-linked sugar chain suppresses not the triggering deprotonation but the succeeding denaturation Biochim. Biophys. Acta Protein Struct. Mol. 1993 1203 295 297 10.1016/0167-4838(93)90097-B 50. Mukaka M.M. Statistics corner: A guide to appropriate use of correlation coefficient in medical research Malawi Med. J. 2012 24 69 71 23638278 51. Weiss D.J. Wardrop K.J. Schalm’s Veterinary Hematology John Wiley & Sons Ames, IA, USA 2010 1206 52. Bussolino F. Ziche M. Wang J.M. Alessi D. Morbidelli L. Cremona O. Bosia A. Marchisio P.C. Mantovani A. In Vitro and In Vivo Activation of Endothelial Cells by Colony-stimulating Factors J. Clin. Investig. 1991 87 986 995 10.1172/JCI115107 1705569 53. Bussolino F. Wang J.M. Defilippi P. Turrini F. Sanavio F. Edgell C.-J.S. Aglietta M. Arese P. Mantovani A. Granulocyte and granulocyte-macrophage colony stimulating factors induce human endothelial cells to migrate and proliferate Nature 1989 337 471 473 10.1038/337471a0 2464767 54. Bocchietto E. Guglielmetti A. Silvagno F. Taraboletti G. Pescarmona G.P. Mantovani A. Bussolino F. Proliferative and Migratory Responses of Murine Microvascular Endothelial Cells to Granulocyte-Colony-Stimulating Factor J. Cell. Physiol. 1993 95 89 95 10.1002/jcp.1041550112 7682223

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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091192 plants-11-01192 Article Germacrene A Synthases for Sesquiterpene Lactone Biosynthesis Are Expressed in Vascular Parenchyma Cells Neighboring Laticifers in Lettuce https://orcid.org/0000-0003-0862-2149 Kwon Moonhyuk 12† https://orcid.org/0000-0003-2778-3685 Hodgins Connor L. 1† https://orcid.org/0000-0002-4849-7330 Haslam Tegan M. 1‡ Roth Susan A. 1 Nguyen Trinh-Don 1§ Yeung Edward C. 1 https://orcid.org/0000-0003-1288-5347 Ro Dae-Kyun 1* Jerković Igor Academic Editor 1 Department of Biological Sciences, University of Calgary, Calgary, AL T2N 1N4, Canada; mkwon@gnu.ac.kr (M.K.); clhodgin@ucalgary.ca (C.L.H.); tegan.haslam@biologie.uni-goettingen.de (T.M.H.); susan.roth1@ucalgary.ca (S.A.R.); don.nguyen@ubc.ca (T.-D.N.); yeung@ucalgary.ca (E.C.Y.) 2 Division of Applied Life Sciences (BK21 Plus), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju 660-701, Korea * Correspondence: daekyun.ro@ucalgary.ca † These authors contributed equally to this work. ‡ Present address: Department of Plant Biochemistry, University of Göttingen, Justus-von-Liebig-Weg 11 Göttingen, D-37077 Göttingen, Germany. § Present address: Department of Chemistry, Irving K. Barber Faculty of Science, University of British Columbia, Kelowna, BC V1V 1V7, Canada. 28 4 2022 5 2022 11 9 119224 2 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Sesquiterpene lactone (STL) and natural rubber (NR) are characteristic isoprenoids in lettuce (Lactuca sativa). Both STL and NR co-accumulate in laticifers, pipe-like structures located along the vasculature. NR-biosynthetic genes are exclusively expressed in laticifers, but cell-type specific expression of STL-biosynthetic genes has not been studied. Here, we examined the expression pattern of germacrene A synthase (LsGAS), which catalyzes the first step in STL biosynthesis in lettuce. Quantitative PCR and Illumina read mapping revealed that the transcripts of two GAS isoforms (LsGAS1/LsGAS2) are expressed two orders of magnitude (~100–200) higher in stems than laticifers. This result implies that the cellular site for LsGAS1/2 expression is not in laticifers. To gain more insights, promoters of LsGAS1/2 were cloned and fused to β-glucuronidase (GUS), followed by transformations of lettuce with these promoter-GUS constructs. In in situ GUS assays, the GUS expression driven by the LsGAS1/2 promoters was tightly associated with vascular bundles. High-resolution microsections showed that GUS signals are not present in laticifers but are detected in the vascular parenchyma cells neighboring the laticifers. These results suggest that expression of LsGAS1/2 occurs in the parenchyma cells neighboring laticifers, while the resulting STL metabolites accumulate in laticifers. It can be inferred that active metabolite-trafficking occurs from the parenchyma cells to laticifers in lettuce. lettuce laticifers isoprenoid sesquiterpene lactone natural rubber Natural Sciences and Engineering Research Council of Canada (NSERC)PJ01566401 National Research Foundation of Korea (NRF)2021R1A5A8029490 Ministry of Trade, Industry and Energy (MOTIE, Korea)20014582 This work was supported by Natural Sciences and Engineering Research Council of Canada (NSERC); Cooperative Research Program for Agriculture Science and Technology Development (PJ01566401), Rural Development Administration, Republic of Korea; the National Research Foundation of Korea (NRF) grant (2021R1A5A8029490); the Technology Development Program (20014582) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea). ==== Body pmc1. Introduction Lettuce (Lactuca sativa) is a major leafy vegetable crop from the Asteraceae family with an annual production of ~27 million tonnes [1]. Aside from its agricultural value, lettuce has attracted attention for two specialized metabolites—natural rubber (NR; cis-1,4-polyisoprene) and sesquiterpene lactones (STLs), a group of fifteen carbon isoprenoids with a characteristic α-methylene γ-lactone moiety [2,3]. NR is a commodity with which hundreds of industrial products are manufactured, including tyres [4]. STLs exhibit diverse bioactivities, such as parthenolide as an anti-inflammatory agent known to inhibit NF-κB activation [5]. Both NR and STLs are isoprenoid natural products derived from isopentenyl diphosphate (IPP) and co-accumulate in laticifer cells [2,3]. Laticifers are a group of cells linearly fused with one another through perforated cell walls to form a network of multicellular structures along the vasculature [6]. Latex, the cytoplasmic content of laticifers, is metabolically active to synthesize diverse specialized metabolites. In lettuce, NR and STLs are released presumably as defensive chemicals when laticifers are ruptured by physical damage during herbivory. Among the hundreds of natural products in laticifers, the most notable example is NR from the Para rubber tree (Hevea brasiliensis) [7]. The metabolic competency of laticifers can be shown by the massive production of NR in Para rubber tree (~13 million tonnes per year by the International Rubber Study Group’s report). However, in-depth molecular studies of laticifers in plants, including Para rubber tree, are difficult due to recalcitrance to transformation, the perennial nature of woody plants, and/or obligate outcrossing. Several model plants (i.e., Arabidopsis, poplar, rice, alfalfa) are not suitable for these studies, as they do not develop laticifers. To overcome these problems, we have initiated molecular studies of lettuce laticifers since lettuce is a transformable, annual, diploid, and self-pollinating plant [8,9]. Furthermore, the recent release of lettuce genomic data further supports molecular genetic studies of lettuce laticifers [10]. Although NR biosynthesis remains to be fully understood, it was reported that a protein complex is formed by cis-prenyltransferase isoform 3 (LsCPT3) and CPT-Like protein isoform 2 (LsCPTL2) on the cytosolic side of the endoplasmic reticulum (ER) in lettuce (Figure 1A) [8], and its related species dandelion also has orthologous proteins that form a protein complex on the ER [11]. The original gene name LsCPTL2 has been renamed LsCBP2 (Lactuca sativa CPT-binding protein 2) [12], and hereafter, we will use LsCBP2 to refer to LsCPTL2. RNAi-silencing showed that the protein complex formed by LsCPT3 and LsCBP2 is required for NR biosynthesis in lettuce [8], and qPCR data and LsCPT3/LsCBP2 promoter analysis by reporter gene fusion showed that these two genes are highly and exclusively expressed in lettuce laticifers [8,13]. Based on phylogenetic analysis, LsCPT3/LsCBP2 for NR biosynthesis seems to have diverged from the primary metabolic genes, LsCPT1/LsCBP1 [8]. The protein pair, LsCPT1/LsCBP1, also forms a protein complex on the ER and synthesizes dehydrodolichyl diphosphate (DHDD), which is transformed into a group of oligomeric isoprene polymers, dolichol [8,14,15,16] (Figure 1A). Dolichol serves as a carrier molecule of sugars for protein glycosylation in eukaryotes [17] and for peptidoglycan cell walls in prokaryotes [18], making it an indispensable metabolite in both domains of life. Therefore, lettuce has evolved to produce two types of cis-1,4-polyisoprenes, dolichol and NR. STLs also accumulate in lettuce latex, and their biosynthesis in lettuce is characterized down to costunolide (Figure 1A) [19,20,21]. The first reaction is catalyzed by germacrene A synthase (LsGAS), which synthesizes germacrene A from farnesyl diphosphate (FPP). Sequential oxygenations of germacrene A by two cytochrome P450s (germacrene A oxidase and costunolide synthase) yield a core STL precursor, costunolide. Despite our advanced understanding of STL biosynthesis, cell-type specific expression of STL-biosynthetic genes has not been studied in lettuce. Since both NR and STLs co-accumulate in high quantities in laticifers, it has been assumed that both of their biosynthetic genes are simultaneously expressed in lettuce laticifers. Here, the occurrence of LsGAS transcripts was analyzed by quantitative PCR (qPCR) and targeted Illumina read mapping in different tissues. We further examined LsGAS promoter activities by β-glucuronidase (GUS)-fusion using a transgenic approach. Unexpectedly, no evidence for the laticifer-specific expression of LsGAS was obtained. In situ GUS staining patterns showed that the LsGAS promoter drives gene expression in the parenchyma cells neighboring the laticifers. NR and STLs co-accumulate in laticifers, but their respective genes for biosynthesis are expressed in distinct cells, highlighting the importance of cellular compartmentalization in isoprenoid (STL and NR) metabolism in lettuce and possibly other plants. 2. Results 2.1. Assessing Relative LsGAS Transcripts by qPCR Analysis Although previously reported [2,3], we cultivated lettuce in a phytochamber and confirmed the presence of STLs and NR in lettuce latex by LC-quadruple time-of-flight (qTOF) and HPLC (high performance liquid chromatography)-GPC (gel permeation column)-ELSD (evaporative light scattering detector), respectively. Three major STLs with mass accuracy of less than 5 Δppm, and NR with an average Mw of 2.3 million Da, were detected in lettuce latex (Figure 1B,C). The first reaction for STL biosynthesis is catalyzed by germacrene A synthase (GAS). In lettuce and its related species chicory, three GAS isoforms have been biochemically characterized [22,23]. These GAS isoforms are referred to as LsGAS1-3. Genomic analysis of lettuce with Phytozome (phytozome-next.jgi.doe.gov, accessed on 14 April 2022) identified the three genes in three genomic loci (LsGAS1 in Lsat_1_v5_gn_8_116421.1; LsGAS2 in Lsat_1_v5_gn_8_116340.1, and LsGAS3 in Lsat_1_v5_gn_2_29221.1). LsGAS1 and LsGAS2 are clustered into linkage group #8 with a distance of 10.9 kb (Figure 2A), while LsGAS3 is located in linkage group #2. LsGAO1 is also linked with LsGAS1/2, occurring 226 kb upstream of LsGAS2 (Figure 2A). Two gene models were identified between the LsGAO1 and LsGAS1/2 loci; one has no annotation (Lsat_1_v5_gn_8_116301.1) and the other was annotated as an Arabidopsis broad-spectrum mildew resistance protein RPW8 (Lsat_1_v5_gn_8_115321.1). Both have no functional relation to STL biosynthesis. We further examined 220 kb upstream of LsGAO1 and 650 kb downstream of LsGAS1 in the lettuce genome. However, no gene model with a possible role in STL biosynthesis could be identified. Therefore, we concluded that LsGAS1/2 and their immediate downstream metabolic gene, LsGAO1, form a gene cluster in linkage group #8 in lettuce, but no evidence for extensive gene clustering involving other downstream genes was obtained. To evaluate the expression of LsGAS1-3 in lettuce, we first examined their relative transcripts in latex and other tissues with qPCR. Relatively pure liquid latex was isolated by making an incision in the lettuce stem. In the qPCR analysis, LsGAS1/2 displayed co-relating expression patterns in six different tissues, but the expression of LsGAS3 differed from those of LsGAS1/2. Unexpectedly, relative transcripts of LsGAS1/2 in stems were >200-fold higher than those in latex (Figure 2B). Among all the tissues examined, transcripts of LsGAS1/2 were the lowest in the latex where their metabolic end-products accumulate. In contrast, LsGAS3 showed ~2.5-fold higher expression in stems, relative to latex (Figure 2C). These results suggested that laticifers might not be the cellular sites for LsGAS expression. 2.2. Assessing LsGAS Transcription with Targeted RNA-Seq Analysis The transcript levels of LsGAS1-3 were independently analyzed by targeted Illumina read mapping analysis. Four individual lettuce plants were used to generate four replicates of Illumina-sequencing libraries either from the stem or latex. Using the libraries, 100 bp paired-end reads were carried out to obtain eight sequencing data sets, each of which had read numbers ranging between 55 to 69 million reads per library. Previously characterized biosynthetic genes for STLs (LsGAS1/2/3, LsGAO1/2, LsCOS), NR (LsCPT3, LsCBP2), and DHDD (LaCPT1, LsCBP1) [8,19,20,21] were used as reference templates to count read numbers mapped to these genes. Two isoforms of FPS (farnesyl diphosphate synthase), which provide a precursor for LsGAS, were also identified from the lettuce genome, and their expression in stem and latex was examined alongside LsGAS1-3. Consistent with the qPCR data, LsGAS1 and LsGAS2 showed two orders of magnitude higher levels (100–120-fold higher) of transcripts in stems than in latex (Table 1). The abundance of LsGAS3 transcripts was significantly lower (40–70-fold lower) than those of LsGAS1/2 with an almost negligible level of transcripts in stems. LsGAS3 still showed higher expression in stems, but the difference between latex and stems was not statistically significant. Of the two LsFPS transcripts examined, LsFPS2 showed negligible expression in latex and a 95-fold higher expression in stems, mirroring the expression pattern of LsGAS1/2. This suggests that LsFPS2 could be a major contributor for the substrate in STL biosynthesis, although more investigation is required. Similar to LsGAS1/2, the downstream biosynthetic genes, LsGAO1 and LsCOS, also showed predominant expression in stems, closely resembling those of LsGAS1/2. However, the second isoform of LsGAO (LsGAO2) exhibited a 9.7-fold higher level of transcripts in latex than in stems. In contrast to the expression of LsGAS1/2, the expression levels of NR-biosynthetic genes (LsCPT3/LsCBP2) were several folds higher in latex, relative to stems. These results are consistent with previously reported qPCR data and promoter-GUS analysis [8,13]. The transcripts for DHDD biosynthesis (LsCPT1/LsCBP1) were overall much less abundant than those for STL- and NR-biosynthesis and were present at comparable levels in latex and stems. Based on these results, we concluded that LsGAS1 and LsGAS2, the first enzymes committed to STL biosynthesis in lettuce, do not show any significant expression in latex where their metabolic end-products accumulate. These results are in sharp contrast to NR biosynthesis in lettuce. We previously showed that transcripts for NR-biosynthetic genes were mainly found in latex where NR accumulates [8,13]. 2.3. Characterizing GAS1/2 Promoters with GUS-Fusion Constructs Cell-type specific expression of LsGAS1/2 was more precisely analyzed by characterizing their promoter activities. The LsGAS1/2 promoters, each consisting of a ~1 kb fragment upstream of their ATG start codons, were identified from the lettuce genome. These promoters are hereafter referred to as pLsGAS1 and pLsGAS2. The promoter fragments were transcriptionally fused to the reporter gene, β-glucuronidase (GUS). The promoter-GUS constructs and vector controls were individually transformed to lettuce, and a total of eight and twelve independent T1 lines were generated using the pLsGAS1-GUS and pLsGAS2-GUS constructs, respectively. Leaves from T1 lines were infiltrated with X-Gluc, and two lines for each construct that showed particularly strong GUS signals were selected to propagate the T2 generation for further analysis. In in situ GUS staining of T2 plants, the vector-transformed control showed no sign of GUS staining (Figure 3A), but both pLsGAS1-GUS- and pLsGAS2-GUS-transformed lettuces showed clear GUS activities along the vascular bundles (Figure 3B,C). However, as the GUS-staining patterns in the vascular bundles do not reveal the identity of specific cell-types in vascular bundles, the transgenic lettuces were fixed and microsectioned to precisely visualize the cells stained with GUS activity. In the microsections of vector control lettuce, laticifers were recognized by blue pigments (proteins stained by amido black 10B) and by characteristic cell fusions through degraded cell walls (yellow rectangles, Figure 3D). In contrast, microsections of pLsGAS1-GUS or pLsGAS2-GUS transgenic lettuces showed no evidence of GUS stains in the laticifers. Instead, negative laticifer images were observed over GUS-stained blue backgrounds in surrounding parenchyma cells (Figure 3E,F). The observed negative images of laticifers were in stark contrast to the intense GUS stains of laticifers in lettuce transformed with LsCBP2 promoter GUS-fusions (LsCBP2-GUS) in our previous work [13]. To further confirm the lack of GUS activity in laticifers, latex samples were collected from vector control lettuce and from lettuces transformed with pLsGAS1-GUS, pLsGAS2-GUS, or pLsCBP2-GUS (a positive control for GUS expression in laticifers [13]). The in vitro latex assays showed no GUS activity in latex samples collected from the vector control and pGAS1/2-GUS-transformed lettuce (Figure 3G–I). However, intense GUS activity was detected in the latex collected from the pLsCBP2-GUS-transformed lettuce (Figure 3J). Taken together, we concluded that LsGAS1/2 are not expressed in laticifers but are expressed in vascular parenchyma cells neighboring laticifers. 3. Discussion This work’s key finding is that LsGAS1/2 do not express in laticifers but in vascular parenchyma cells neighboring laticifers in lettuce. The plausible explanation for LsGAS1/2 not being expressed in laticifers is to avoid precursor competition with NR-biosynthetic enzymes in laticifers. LsGAS1/2 and LsCPT3/LsCBP2 share a central precursor, IPP, for STL and NR biosynthesis, respectively. IPP is a building block for NR, and the molecular weight of NR in lettuce is known to reach 1.5–2.0 million g/mol [3,8,24], which implies that up to 30,000 IPP monomers are condensed to formulate a NR molecule in laticifers. Aside from NR, lettuce accumulates a copious amount of STLs in laticifers [2], and thus it would be a great challenge to consistently synthesize both NR and STLs in laticifers. One metabolic strategy to resolve this conflict is to express STL biosynthetic genes in the parenchyma cells connected to laticifers and transfer STL metabolites to laticifers after synthesis. Initially, qPCR data intrigued us to examine the cellular compartmentalization of STL- and NR-biosynthesis, but targeted RNA-Seq analysis provided more quantitative details of transcript levels of STL biosynthetic genes (Table 1). LsGAS1/2 showed a markedly strong expression in stems with negligible levels of LsGAS1/2 transcripts in laticifers. Considering that some non-laticifer cytosolic components could contaminate the latex samples when incisions were made in stems during sample collection, the transcript levels of LsGAS1/2 could be even lower in laticifers. Similarly, two subsequent biosynthetic genes, LsGAO1 and LsCOS, showed strong expression in stems. The simplistic view of early STL biosynthesis is that the sequential catalysis by LsGAS1/2, LsGAO1, and LsCOS funnels carbon flux from FPP to various STLs in the parenchyma cells. Although downstream enzymes remain uncharacterized, it is possible that the complete biosynthesis of STLs happens in the parenchyma cells adjacent to laticifers, followed by transport of the STLs to laticifers. The second isoform of LsGAO (LsGAO2) showed the opposite expression pattern, and significantly more LsCOS transcripts could be detected in laticifers in comparison to LsGAS1/2 transcript levels in laticifers (Table 1). It appears that the expression of STL-biosynthetic genes becomes progressively stronger in laticifers after LsGAS1/2. However, to avoid precursor competition, only LsGAS1/2 needs to be expressed in non-laticifer cells. Expression of the downstream biosynthetic genes, LsGAO and LsCOS, in non-laticifer cells is not necessary to avoid precursor competition, as their substrates are not IPP. Once the backbone of STLs, germacrene A, is synthesized from a unique IPP pool in the parenchyma cells, germacrene A and its downstream intermediates could be transported to laticifers for further transformation. In situ RNA hybridization and immunolocalization were previously performed in Euphorbia tirucalli and opium poppy, respectively, which found transcripts or enzymes in the parenchyma cells adjacent to laticifers [25,26]. However, those plants are not amenable for genetic transformation, limiting the uses of simple yet accurate promoter-GUS analysis through a transgenic approach. Present studies used the pGAS-GUS-transformed lettuce to provide a technically independent view of the contribution of vascular parenchyma cells to specialized metabolism in plants. Although we have not investigated the localization of LsGAS1/2 enzymes in this work, the complete lack of GUS activity in latex from the pLsGAS1/2-GUS transgenic lettuce suggests that protein transportation between cells is limited. Therefore, our model predicts that active metabolite trafficking operates from parenchyma cells to laticifers. We are currently working on identifying transporters responsible for STL movement in lettuce. 4. Materials and Methods 4.1. Plant Growth and DNA Isolation Lettuce (cv. Ninja) was grown in a phytochamber at 22 °C for 16 h of light and 20 °C for 8 h of dark. Genomic DNA was isolated from leaves using the DNeasy Plant Mini Kit (Qiagen) and was used to amplify LsGAS1/2 promoters. 4.2. Quantitative Real-Time PCR Total RNA was extracted from various tissues using Trizol. Lettuce latex was isolated by making a small incision in stems with a razor blade. First strand cDNA was synthesized from total RNA using oligo(dT)12–18 and Superscript III reversed transcriptase (Invitrogen). qPCR was performed using the Step One Real-Time PCR System (Applied Biosystems) with primer sets 1/2, 3/4, 5/6 or 7/8 for LsGAS1-3 and Actin, respectively. All primer sequences are listed in Supplementary Table S1. The PCR mixture (total 10 μL) was prepared by mixing cDNA (1 ng), primers (5 μM), and 5 μL of Power SYBR Green PCR Master Mix (Applied Biosystems). The qPCR program was set for 1 cycle of 95 °C for 10 min and 40 cycles of 95 °C for 15 s and 58 °C for 1 min. The relative transcript abundances were determined from the ΔCT values calculated using the reference gene (actin). 4.3. RNA-Seq Analysis Lettuce latex and whole stem (including latex) samples were collected from four individual lettuce plants (2 months old). Total RNA was extracted using Trizol and additionally purified with the Illustra RNAspin Mini RNA Isolation kit (Fisher Scientific, Carlsbad, USA). Quality control of total RNA, library generation, and NovaSeq 6000 system (100 bp paired-end reads) Illumina sequencing were performed at Genome Quebec, McGill University, Canada. A total of eight sequencing data sets with a sequencing depth between 57.9 and 68.3 million reads per library were generated. The Map Reads to Contig function in CLC Genomics Workbench (version 21.0.4, Qiagen, Aarhus, Denmark) with a similarity fraction of 0.95 was used to count reads mapped to the reference genes listed in Table 1. 4.4. Plasmid Construction The promoter sequences of LsGAS1/2 were obtained from the Phytozome lettuce genome database. DNA fragments about 1 kb upstream of the LsGAS1/2 start codon were amplified using primer sets of 9/10 or 11/12 (hybrid primers designed to include gene-specific sequences and common sequences for subsequent Gateway cloning), respectively, were cloned into the pGEMT-Easy vector (Promega, Madison, USA), and were sequenced. The GAS promoters were re-amplified with primer sets 13/14 (common primers for Gateway cloning) and cloned into pDONR221 (Invitrogen, Carlsbad, USA) using the Gateway BP Clonase II Enzyme mixture (Invitrogen). They were then cloned into the destination vector pKGWFS7 [27] with the Gateway LR Clonase II Enzyme mixture (Invitrogen). 4.5. Generating Transgenic Plants, Histochemical GUS Staining, and Microsections Transgenic lettuce plants were generated as described [13]. GUS activity in T2 transgenic lettuce was detected according to the methods previously described [13,28]. Leaves of 1–2 week old transgenic plants were submerged and infiltrated with a GUS staining solution (10 mM EDTA, 0.1% Triton–X 100, 1 mM K3Fe(CN)6, 2 mM X-Gluc substrate, and 0.1 M Na3PO4, pH 7) under vacuum for 2–3 h. The leaves were then incubated at 37 °C for 16–18 h. Leaves were cleared using an ethanol series beginning with 50% ethanol and increasing in increments of 5% every 12 h. Leaf staining patterns were observed using an Olympus SZX2-ILLT light microscope. Plants with strong expression were grown to an early bolting stage (3 weeks), and 1 mm thick longitudinal hand sections were prepared from their stems. GUS staining in stems was performed as described for leaves. After staining, the stems were fixed using a fixative solution (1.6% paraformaldehyde, 2.5% glutaraldehyde, and 0.05 M phosphate buffer, pH 6.8). The samples were fixed for 1–2 weeks. After fixing, the samples were dehydrated in 100% ethanol and embedded with Technovit 7100 (Electron Microscopy Sciences, Hatfield, USA). The samples were sectioned using Ralph knives and a Leica Reichert-Jung 2040 Autocut rotary microtome to a thickness of 3 µm. Slides were examined using a Leitz Aristoplan microscope (Leitz). Images were generated using a Nikon Digital Sight, DS-Fi2 camera (Nikon). 4.6. Metabolite Analyses STLs and NR from lettuce latex were measured, according to the published methods [8,21]. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants11091192/s1, Table S1: The list of primers used in this study. Click here for additional data file. Author Contributions Conceptualization, M.K., C.L.H., E.C.Y. and D.-K.R.; methodology, M.K., C.L.H. and T.M.H.; formal analysis, S.A.R.; investigation, M.K., C.L.H., T.M.H., S.A.R. and T.-D.N.; data curation, S.A.R.; writing—original draft preparation, M.K., C.L.H. and D.-K.R.; writing—review and editing, T.M.H., S.A.R., T.-D.N. and E.C.Y.; visualization, M.K., C.L.H. and D.-K.R.; supervision, M.K. and D.-K.R.; project administration, D.-K.R.; funding acquisition, M.K. and D.-K.R. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not Applicable. Informed Consent Statement Not Applicable. Data Availability Statement The genome sequences of lettuce GAS isoforms used in our study were downloaded from the Phytozome (Available online: http//www.phytozome-next.jgi.doe.gov, accessed on 14 April 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Biosynthetic pathways and metabolite analysis of NR and STLs in lettuce latex. (A) Biosynthetic routes of diverse secondary isoprenoids in lettuce latex. (B) STL detection in lettuce latex by LC-qTOF. [M+H]+ ions were detected in positive ion mode. (C) NR detection in lettuce latex by HPLC-GPC (gel permeation column)-ELSD (evaporative light scattering detector). Abbreviations used are: DHDD, dehydrodolichyl diphosphate; STL, sesquiterpene lactone; NR, natural rubber; IPP, isopentenyl diphosphate; FPP, farnesyl diphosphate; PDI, polydispersity index. The key enzymes for each biosynthetic pathway are labeled in red. Representative STL products are shown. Schemes follow the same formatting. Figure 2 Genomic cluster and expression analysis of LsGAS. (A). Schematic representation of LsGAS1, LsGAS2, and LsGAO1, retrieved from Phytozome. (B,C). qPCR analyses of LsGAS1/2 (B) and LsGAS3 (C) in various lettuce tissues. Young rosette leaves were collected 10–14 days after germination; old rosette leaves were collected 4–6 weeks after germination. The transcript level in floral buds was set to one, and all other values were relative to the floral bud transcript level. Stem samples used whole stem tissues including latex. Data are means ± S.D. (n = 4). **** indicates a p value of < 0.0001; n.s. indicates no statistical significance, p value >0.05. Figure 3 LsGAS1 and LsGAS2 promoter analyses in transgenic lettuce. (A–C). In situ GUS-staining patterns in leaves of transgenic lettuce. Scale bars are 5 mm. (A) Vector control (Con); (B) pLsGAS1-GUS-transformed lettuce; (C) pLsGAS2-GUS-transformed lettuce. (D–F) Microsections of stems at early bolting stage from wild-type control (Con) and transgenic lettuce (pLsGAS1/2-GUS constructs). Scale bars are 20 µm. (D) The high density of proteins in laticifers were stained with amido black 10B, and total carbohydrates were stained with periodic acid-Schiff’s (PAS) stain in vector control lettuce. Yellow rectangles show characteristic features of cell fusions in laticifers. (E,F) GUS activities are visualized by blue pigment. Laticifers with cell-fusions (indicated by yellow rectangles) are shown as negative images in blue backgrounds. (G–J) GUS activity assays using isolated latex. Previously reported transgenic lettuce (pLsCBP2-GUS) was used as a positive control [13], and vector control was used as a negative control (Con). Scale bars are 5 mm. plants-11-01192-t001_Table 1 Table 1 Quantitative read maps for transcripts in STL-, NR-, and DHDD-biosynthesis in lettuce latex and whole stems, including latex. Target Genes 1 Metabolic Products Stem— 2 Mapped Read Number Latex— Mapped Read Number 4 Fold (Stem/ Latex) LsGAS1 STL 5 311.5 ± 95.5 2.6 ± 1.1 ** 119.81 LsGAS2 STL 521.7 ± 176.6 5.0 ± 1.3 * 104.34 LsGAS3 STL 7.5 ± 8.9 0.1 ± 0.2 75.00 LsGAO1 STL 1375.1 ± 343.3 8.5 ± 2.4 ** 161.78 LsGAO2 STL 9.5 ± 4.1 92.5 ± 23.4 ** 0.10 LsCOS STL 746.9 ± 124.4 72.2 ± 29.4 * 10.34 LsCPT3 NR 312.4 ± 38.7 2251.7 ± 259.3 ** 0.14 LsCBP2 NR 337.8 ± 51.5 2664.2 ± 423.0 ** 0.13 LsCPT1 DHDD 17.7 ± 1.1 12.6 ± 1.1 ** 1.40 LsCBP1 DHDD 9.3 ± 0.8 9.7 ± 0.6 0.96 3 LsFPS1 FPP 528.8 ± 122.0 1537.1 ± 164.4 ** 0.34 3 LsFPS2 FPP 95.7 ± 25.7 1.0 ± 0.4 ** 95.70 1 The abbreviations are as follows: STL, sesquiterpene lactone; NR, natural rubber, DHDD, dehydrodolichyl diphosphate; FPP, farnesyl diphosphate. 2 The number of the reads mapped to a targeted transcript per million reads. 3 LsFPS1 and LsFPS2 are Lsat_1_v5_gn_5_2060.1 and Lsat_1_v5_gn_7_114941.1, respectively, in the lettuce genome. 4 * indicates a p value of < 0.05 and ** indicates a p value of < 0.01. 5 Data are average ± SD (n = 4). Each data set is from independently prepared Illumina libraries from different lettuce plants. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. United Nations, Food and Agriculture Organization of the United Nations 2020 Available online: http://www.fao.org/faostat/en/#data/QCL (accessed on 10 February 2021) 2. Sessa R.A. Metabolite profiling of sesquiterpene lactones from Lactuca species: Major latexcomponents are novel oxalate and sulfate conjugates of lactucin and its derivatives J. Biol. Chem. 2000 275 26877 26884 10.1016/S0021-9258(19)61456-0 10858433 3. Bushman B.S. Scholte A.A. Cornish K. Scott D.J. Brichta J.L. Vederas J.C. Ochoa O. Michelmore R.W. Shintani D.K. Knapp S.J. Identification and comparison of natural rubber from two Lactuca species Phytochemistry 2006 67 2590 2596 10.1016/j.phytochem.2006.09.012 17055543 4. Beilen J.B.V. Poirier Y. Establishment of new crops for the production of natural rubber Trends Biotechnol. 2007 25 522 529 10.1016/j.tibtech.2007.08.009 17936926 5. Hehner S.P. Hofmann T.G. Dröge W. Schmitz M.L. The antiinflammatory sesquiterpene lactone parthenolide inhibits NF-kappa B by targeting the I kappa B kinase complex J. Immunol. 1999 163 5617 5623 10553091 6. Hagel J.M. Yeung E.C. Facchini P.J. Got milk? The secret life of laticifers Trends Plant Sci. 2008 13 631 639 10.1016/j.tplants.2008.09.005 18977166 7. Cornish K. Alternative Natural Rubber Crops: Why Should We Care? Technol. Innov. 2017 18 244 255 10.21300/18.4.2017.245 8. Qu Y. Chakrabarty R. Tran H.T. Kwon E.-J.G. Kwon M. Nguyen T.-D. Ro D.-K. A lettuce (Lactuca sativa) homolog of human Nogo-B receptor interacts with cis-prenyltransferase and is necessary for natural rubber biosynthesis J. Biol. Chem. 2015 290 1898 1914 10.1074/jbc.M114.616920 25477521 9. Chakrabarty R. Qu Y. Ro D.-K. Silencing the lettuce homologs of small rubber particle protein does not influence natural rubber biosynthesis in lettuce (Lactuca sativa) This contribution is in honor of Professor Vincenzo de Luca’s 60th birthday Phytochemistry 2015 113 121 129 10.1016/j.phytochem.2014.12.003 25553584 10. Reyes-Chin-Wo S. Wang Z. Yang X. Kozik A. Arikit S. Song C. Xia L. Froenicke L. Lavelle D.O. Truco M.-J. Genome assembly with in vitro proximity ligation data and whole-genome triplication in lettuce Nat. Commun. 2017 8 14953 10.1038/ncomms14953 28401891 11. Epping J. Deenen N.V. Niephaus E. Stolze A. Fricke J. Huber C. Eisenreich W. Twyman R.M. Prüfer D. Schulze C. Gronover, A rubber transferase activator is necessary for natural rubber biosynthesis in dandelion Nat. Plants 2015 1 15048 10.1038/nplants.2015.48 12. Lakusta A.M. Kwon M. Kwon E.-J.G. Stonebloom S. Scheller H.V. Ro D.-K. Molecular studies of the protein complexes involving cis-prenyltransferase in guayule (Parthenium argentatum), an alternative rubber-producing plant Front. Plant Sci. 2019 10 165 10.3389/fpls.2019.00165 30858856 13. Barnes E.K. Kwon M. Hodgins C.L. Qu Y. Kim S.-W. Yeung E.C. Ro D.-K. The promoter sequences of lettuce cis-prenyltransferase and its binding protein specify gene expression in laticifers Planta 2021 253 51 10.1007/s00425-021-03566-8 33507397 14. Harrison K.D. Park E.J. Gao N. Kuo A. Rush J.S. Waechter C.J. Lehrman M.A. Sessa W.C. Nogo-B receptor is necessary for cellular dolichol biosynthesis and protein N-glycosylation EMBO J. 2011 30 2490 2500 10.1038/emboj.2011.147 21572394 15. Brasher M.I. Surmacz L. Leong B. Pitcher J. Swiezewska E. Pichersky E. Akhtar T.A. A two-component enzyme complex is required for dolichol biosynthesis in tomato Plant J. 2015 82 903 914 10.1111/tpj.12859 25899081 16. Kwon M. Kwon E.-J.G. Ro D.-K. cis-Prenyltransferase Polymer Analysis from a Natural Rubber Perspective Methods Enzymol. 2016 576 121 145 27480685 17. Sato M. Fujisaki S. Sato K. Nishimura Y. Nakano A. Yeast Saccharomyces cerevisiae has two cis-prenyltransferases with different properties and localizations. Implication for their distinct physiological roles in dolichol synthesis Genes Cells 2001 6 495 506 10.1046/j.1365-2443.2001.00438.x 11442630 18. Kato J.J. Fujisaki S. Nakajima K. Nishimura Y. Sato M. Nakano A. The Escherichia coli homologue of yeast RER2, a key enzyme of dolichol synthesis, is essential for carrier lipid formation in bacterial cell wall synthesis J. Bacteriol. 1999 181 2733 2738 10.1128/JB.181.9.2733-2738.1999 10217761 19. Nguyen D.T. Göpfert J.C. Ikezawa N. MacNevin G. Kathiresan M. Conrad J. Spring O. Ro D.-K. Biochemical conservation and evolution of germacrene A oxidase in Asteraceae J. Biol. Chem. 2010 285 16588 16598 10.1074/jbc.M110.111757 20351109 20. Ikezawa N. Göpfert J.C. Nguyen D.T. Kim S.-U. O’Maille P.E. Spring O. Ro D.-K. Lettuce costunolide synthase (CYP71BL2) and its homolog (CYP71BL1) from sunflower catalyze distinct regio- and stereoselective hydroxylations in sesquiterpene lactone metabolism J. Biol. Chem. 2011 286 21601 21611 10.1074/jbc.M110.216804 21515683 21. Nguyen D.T. Kwon M. Kim S.-U. Fischer C. Ro D.-K. Catalytic Plasticity of Germacrene A Oxidase Underlies Sesquiterpene Lactone Diversification Plant Physiol. 2019 181 945 960 10.1104/pp.19.00629 31534022 22. Karimi M. Inzé D. Depicker A. GATEWAYTM vectors for Agrobacterium-mediated plant transformation Trends Plant Sci. 2002 7 193 195 10.1016/S1360-1385(02)02251-3 11992820 23. Yeung E.C. Chan C.K.W. Glycol methacrylate: The art of embedding and serial sectioning Botany 2015 93 1 8 10.1139/cjb-2014-0177 24. Bennett M.H. Mansfield J.W. Lewis M.J. Beale M.H. Cloning and expression of sesquiterpene synthase genes from lettuce (Lactuca sativa L.) Phytochemistry 2002 60 255 261 10.1016/S0031-9422(02)00103-6 12031443 25. Bouwmeester H.J. Kodde J. Verstappen F.W.A. Altug I.G. Kraker J.-W.D. Wallaart T.E. Isolation and characterization of two germacrene A synthase cDNA clones from chicory Plant Physiol. 2002 129 134 144 10.1104/pp.001024 12011345 26. Bell J.L. Burke I.C. Neff M.M. Genetic and biochemical evaluation of natural rubber from Eastern Washington prickly lettuce (Lactuca serriola L.) J. Agric. Food Chem. 2015 63 593 602 10.1021/jf503934v 25513853 27. Weid M. Ziegler J. Kutchan T.M. The roles of latex and the vascular bundle in morphine biosynthesis in the opium poppy, Papaver somniferum Proc. Natl. Acad. Sci. USA 2004 101 13957 13962 10.1073/pnas.0405704101 15353584 28. Uchida H. Yamashita H. Kajikawa M. Ohyama K. Nakayachi O. Sugiyama R. Yamato K.T. Muranaka T. Fukuzawa H. Takemura M. Cloning and characterization of a squalene synthase gene from a petroleum plant, Euphorbia tirucalli L. Planta 2009 229 1243 1252 10.1007/s00425-009-0906-6 19283408

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095081 ijerph-19-05081 Article Mother’s Loneliness: Involuntary Separation of Pregnant Women in Maternity Care Settings and Its Effects on the Experience of Mothers during the COVID-19 Pandemic Malarkiewicz Paulina 1* https://orcid.org/0000-0002-6606-9575 Maksymowicz Stanisław 2 Libura Maria 3 1 Department of Obstetrics and Gynaecology, School of Medicine, Collegium Medicum of the University of Warmia and Mazury, al. Warszawska 30, 10-082 Olsztyn, Poland 2 Department of Psychology and Sociology of Health and Public Health, School of Public Health, Collegium Medicum of the University of Warmia and Mazury, al. Warszawska 30, 10-082 Olsztyn, Poland; stanislaw.maksymowicz@uwm.edu.pl 3 Medical Education and Simulation Department, School of Medicine, Collegium Medicum of the University of Warmia and Mazury, al. Warszawska 30, 10-082 Olsztyn, Poland; maria.libura@uwm.edu.pl * Correspondence: paulina.malarkiewicz@uwm.edu.pl 21 4 2022 5 2022 19 9 508127 2 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The aim of the study was to investigate the challenges of involuntary separation experienced by women during pregnancy and childbirth in the time of the COVID-19 pandemic. The study was conducted by the means of a self-administered questionnaire. One thousand and eleven women (1011) from Poland took part in the study, with an average age of approximately 30 years. The study was approved by the Research Ethics Committee of Warmia and Mazury University in Olsztyn, Poland. The results show that the majority of the surveyed women experienced involuntary separation from their partners during pregnancy and childbirth: 66.27% had no choice but to give birth alone and 84.37% had not been able to attend medical appointments with their partners. Solitary encounters with healthcare were associated with the feeling of fear (36.4%), anger (41%), a sense of injustice (52.2%), acute sadness (36.6%) and a sense of loss (42.6%), with all the reported levels higher in younger women. Over 74% of respondents were afraid of childbirth without a partner present. Almost 70% felt depressed because of a lonely delivery experience. Nearly a quarter of the mothers surveyed declared that if they could go back in time, they would not have made the decision to become pregnant during the pandemic. Based on our study, we found that adjustments to prenatal and neonatal care arrangements under COVID-19-related regimens are needed. Our proposal is to implement at least three fundamental actions: (1) risk calculations for pandemic-related cautionary measures should take into account the benefits of the accompanied medical appointments and births, which should be restored and maintained if plausible; (2) medical personnel should be pre-trained to recognise and respond to the needs of patients as a part of crisis preparedness. If the situation does not allow the patient to stay with her family during important moments of maternity care, other forms of contact, including new technologies, should be used; (3) psychological consultation should be available to all patients and their partners. These solutions should be included in the care plan for pregnant women, taking into account a risk-benefit assessment. pregnancy separation anxiety COVID-19 quality of life maternity care ==== Body pmc1. Introduction Pregnancy is a time of radical changes in the lives of expecting mothers, involving biological, physiological and social functioning spheres. This time is also marked by evolving relationships, especially those with the closest partner/father of the child, beginning with the predominantly mutually agreed decision to become pregnant, throughout the duration of pregnancy itself, to childbirth and postpartum experience. At each of these stages, stress, anxiety and other mental health challenges or even psychiatric disorders may appear. Thus, preparing for the role of a mother and undergoing pregnancy-associated transitions is a possible trigger of psychological disorders, such as antenatal anxiety and depression [1,2]. Often, fears for the success of the pregnancy, the proper development of the fetus and the course of delivery, are also present. One can experience a wide range of emotions during pregnancy, which may often be quite extreme [3]. Mental health disorders become particularly challenging when life and/or health threatening situations occur on a wider social plane, which is undoubtedly the case with the COVID-19 (coronavirus) pandemic that started worldwide in 2020 [4]. Currently, women of a reproductive age do not remember the earlier pandemics of the twentieth centuries, while the more recent ones had a limited impact in terms of social reception in most countries. The global pandemic of severe acute respiratory syndrome (SARS) in 2002–2003 was the first in the 21st century [4]. Yet, since it contained only residents of the threatened areas who were faced with accompanying mental health challenges, the rest of the world were mostly observers. Additionally, the SARS pandemic did not cause as much fear and did not record as many deaths as the COVID-19 pandemic. The swine flu virus epidemic effects were more directly felt in the European region. In the spring of 2009, a new influenza A virus (H1N1) emerged [5]. At first, it was detected in the United States, but soon it spread across the world. H1N1 turned out to be dangerous for pregnant women [6]. It is unofficially estimated that it caused the deaths of approximately 200,000 people [7]. The Ebola epidemic in 2013–2016 did not directly affect European residents [8]. The COVID-19 pandemic can be considered a new and uncertain situation for most of society. No government or healthcare system was prepared for such a crisis. Undoubtedly, the threat to life and/or health associated with a novel infectious disease is a major stress factor. The measures aimed at mitigating the risk of infection themselves may also pose an additional burden on patients. The pandemic also significantly impacted the functioning of the healthcare system, maternity care included. At the beginning of the pandemic in 2020, health officials in Poland suggested that it was advisable to postpone any plans of family enlargement because of potential negative effects of COVID-19 on pregnancy, as well as the limitations in the functioning of hospitals and gynecology clinics. PTGiP (Polish Society of Obstetricians and Gynecologists), following the international guidelines [9], recommended to suspend family births on 20 March 2020. The possibility of accompanying the partner during the ultrasound examination of the pregnant woman was also suspended [10]. However, some pregnancies were already underway, not to mention the fact that it is impossible to suspend reproduction in the entire population. Therefore, the prenatal care had to function in reality of shifting guidelines and changing pandemic restrictions. The aim of our study was to analyze how the COVID-19 pandemic influenced the quality of life of pregnant women, how it affected their, and their partners, well-being and whether it translates into their future procreative plans. The pivotal theme of the study is loneliness, resulting from lonely doctor visits and childbirth. Cacioppo et al. defines loneliness as “subjective distress resulting from a discrepancy between desired and perceived social relationships” [11]. Jeste et al. in JAMA Psychiatry suggests that loneliness is a modern epidemic, resulting in serious health disorders [12]. In our study, loneliness turned out to be the dominant emotion during the initial conversations with both pregnant women and women who gave birth to a child under sanitary restrictions, which one of the authors of this study conducted in her medical practice. Medical interviews, which practically piloted the main study, were filled with patients’ complaints about exactly this issue, showing how important this problem was to women and that it requires systematic scientific investigation. We also wanted to present recommendations aimed at improved focus on mental well-being in maternity care for possible subsequent waves of COVID-19 or future pandemics. The main hypothesis of the present study is the following: pregnant women experienced elevated levels of loneliness linked to the coronavirus pandemic and related sanitary measures, which had a significant impact on their quality of life [13] and procreative plans (planned family expansion). 2. Materials and Methods The study, approved by the Research Ethics Committee of Warmia and Mazury University in Olsztyn, Poland (No. 6/2021), was carried out from January to February 2021, during the second wave of the coronavirus pandemic in Poland. The conditions for participation in the study were: adult age, ongoing pregnancy or delivery during the COVID-19 pandemic and informed consent to participate in the study. The study was conducted using a self-report questionnaire (on-line and paper), consisting of 44 questions: 42 closed, single-choice and single-choice Likert scale questions and 2 open-questions, divided into 5 domains: (1) demographic data (6 questions), (2) patient’s health status (9 questions), (3) patient’s social standing during pregnancy and childbirth (6 questions), (4) patient’s emotions (17 questions) and (5) the impact of the health care system functioning during a pandemic on the patient’s experiences of pregnancy and childbirth (6 questions). The questionnaires were disseminated via the Internet and at one maternity hospital in Olsztyn, Poland. The online survey tool was created using a commonly utilized platform, https://docs.google.com/ (accessed on 19 April 2022), which allows respondents to anonymously complete a survey on both mobile devices and standard computers. Investigators used the snowball sampling method to deliver the survey invitation letter with the survey URL to potential participants via the Instagram account, Facebook and email. Participants were invited to forward the survey invitation letter with the survey link to their friends and relatives. All individuals were freely participating in the study and had the option to discontinue at any moment. The survey was anonymous and confidential, and it took about 10 min to complete. One thousand and eleven women (1011) took part in the study, aged from 17 to 50. A total of 899 participants filled the online form, while one hundred twelve (112) completed the pen and paper version. The average age was 29.5 years. The participants had a higher education degree equivalent to the Master’s level (59.1%, n = 597), secondary education (21.8%, n = 235) or a Bachelor’s degree (16.5%, n = 166). A total of 82.3% (n = 832) of the respondents indicated that they were currently employed, 14.8% (n = 150) were unemployed and 2.9% (n = 29) were studying. The distribution of the place of residence variable was relatively equal, with a slight predominance of villages and large cities. Most of the respondents remained in a permanent formal relationship (77.7%, n = 786), with 20.7% (n = 209) declaring an informal relationship status. A total of 49.9% (n = 504) of respondents gave birth during the pandemic, before participating in the survey. The remaining women (50.1%, n = 507) were pregnant during the pandemic (they were awaiting delivery at the time of filling in the questionnaire). The structure of the study group is presented in Table 1. Statistical Analysis and Variable Measurement Microsoft Excel and IBM SPSS Statistics 27 (Armonk, NY, USA: IBM Corp) were used to perform the analysis. To present the overall characteristics of the data, descriptive statistics for all study variables were calculated. Then, the Pearson’s correlation coefficients and multivariate linear regression analysis were calculated to determine covariates. A two-tailed significance level of 0.05 was used in all statistical tests. The odds ratio was calculated with MedCalc (https://www.medcalc.org/calc/odds_ratio.php (accessed on 5 April 2022). The internal consistency of the scales was computed using Cronbach’s alpha coefficient. The internal consistency of the items in this study are the following: for the Likert scale questions about emotions related to separation, Cronbach’s alpha is 0.904 (excellent); for the Likert scale questions about women’s emotions, Cronbach’s alpha is 0.804 for pregnant women (acceptable); while for those who gave birth, Cronbach’s alpha is 0.764 (acceptable) [14]. The problem of involuntary separation was measured through independent variables: medical visits and delivery status (single or not). The effect of the involuntary separation on quality of life and well-being was measured through dependent variables: (1) increased anxiety, anger, a sense of injustice, acute sadness, a sense of loss (one scale); reduced joy of pregnancy; (2) fear of giving birth alone, low mood regarding the vision of a solo childbirth, fear of lonely hospitalization, fear of isolation from the baby and concern for the health of the baby (one scale—pregnant); (3) influence of solo childbirth on the joy of pregnancy, anxiety during a solo childbirth, fear of lonely hospitalization, fear of isolation from the baby and concern for the health of the baby (one scale—gave birth) (see Figure 1). 3. Results 3.1. Separation and Emotions The main hypothesis of the present study is that pregnant women would experience elevated levels of loneliness linked to the coronavirus pandemic and related sanitary measures, which would have a significant impact on their quality of life, was confirmed. The most important limitation for pregnant women was the inability of the partner to participate in prenatal care appointments and be present during delivery. We called this phenomenon, involuntary separation. This term means that the separation of the patient from her closest social circle is imposed rather than chosen. The way in which the problem was measured and its impact on the quality of life, well-being, procreative plans as well as the resulting recommendations, are shown in Figure 1. Among all the women surveyed, 84.37% (n = 853) admitted that during pregnancy, they had not been able to attend medical appointments with their partners. Respondents who gave birth during the pandemic, in 66.27% (n = 334) of cases, had to do it alone due to pandemic-related measures. Only for 7.34% (n = 37), it was a chosen option. Furthermore, 26.39% (n = 133) were allowed to have a husband/partner by their side at the time of delivery. As a result of multiple regression analysis with Age, Education, Occupational status, Place of residence size and Marital status as independent variables and Partner’s participation in medical appointments as a dependent variable, one can conclude that there were no significant differences in any of the variables. Respondents indicated that due to lonely doctor appointments, they experienced increased anxiety (36.4%, n = 368), anger (41%, n = 415), a sense of injustice (52.2%, n = 527), acute sadness (36.6%, n = 369) and a sense of loss (42.6%, n = 431). This problem affected both groups of respondents (pregnant women and those who had already given birth at the time of questionnaire completion) equally, as both were limited by the systemic restrictions. The impact of separation shown as a series of negative emotions proved to be strongly associated with some demographic variables. The age of the patient was significantly negatively associated with all negative experiences. This means that the younger the women, the higher the index of negative emotions accompanying the separation. Another age-related variable was the level of education, which again was strongly associated with the experience of anger, a sense of injustice and overwhelming sadness. Marital status was not as strongly associated with the emotions of anger and an overwhelming sadness. The other measured demographic variables, such as occupational status and place of residence size, were not statistically significantly associated with negative emotions (Table 2A). The multivariate linear regression analysis of independent variables (demographic: Age, Education, Occupational status, Place of residence and Marital status) and dependent variables (Increased anxiety, Anger, Feeling of injustice, Overwhelming sadness and a Sense of loss) confirmed that there is a strong association between dependent variables and a younger age (Beta for Increased anxiety is −0.126, for Anger is −0.176, for Feeling of injustice is −0.171, for Overwhelming sadness is −0.147 and for a Sense of loss is −0.166; all variables are significantly associated). Anger was also significantly associated with Education (Beta is −0.102). Multivariate linear regression analysis and odds ratio are shown in Table 2B. The detailed results of the regression analysis are in the Supplement file: Table S1–S5. The odds ratio for independent variable, Age, and Increased anxiety is 1.54 (1.7 to 2.04, p = 0.0021), Anger is 1.8 (1.4 to 2.4, p < 0.0001), Feeling of injustice is 1.6 (1.2 to 2.2, p = 0.0009), Overwhelming sadness is 1.8 (1.4 to 2.4, p < 0.0001) and a Sense of loss is 1.18 (0.9 to 1.5, p = 0.023, insignificant). The odds ratio was also significant for Education and Anger, and is 1.77 (1.28 to 2.45, p = 0.0005). Thus, it was confirmed that the problems related to separation concern young women to a greater extent. Other variables are not significantly associated (Table 2B). For the further part of the analysis, our sample was divided into two groups: (1) women who were pregnant during the pandemic (at the time they completed the questionnaire) and (2) women who gave birth during the pandemic (before they completed the questionnaire). Our assumption was that the experiences of these groups, although similar, will differ on selected planes. Both groups indicated that the loneliness they experienced in maternity care affected their overall well-being, and might also have far-reaching effects. 3.1.1. Women Who Were Pregnant during the Pandemic The majority of women in this group admitted that they were afraid of a lonely childbirth (74.1%, n = 376, of which 55.4%, n = 281 were definitely afraid of such a situation). For 69.6% (n = 353), this perspective was a cause of a lowered mood, and this applied to all women regardless of demographic characteristics or other tested variables. Even more pregnant women were afraid of a lonely hospital stay (76.6%, n = 388). This worry was statistically significantly (Pearson correlation) associated with a younger age (p < 0.002), but also with the lower level of education (p < 0.023) and occupational status (p < 0.047). A total of 84.8% (n = 430) of women in this group were also concerned with the prospect of isolation from their child after childbirth (without significant demographic differences). Slightly less, 78.7% (n = 399), were anxious about their child’s health (variable significantly related to marital status, p < 0.022). The above data are illustrated in Figure 2. 3.1.2. Women Who Gave Birth during the Pandemic Such fears of pregnant woman were mirrored by the experiences of those who gave birth during the pandemic. First of all, a large proportion of respondents in this group (62.9%, n = 317) declared that the absence of a partner during childbirth negatively impacted their level of happiness. This reduction was statistically significantly (Pearson correlation) associated with occupational status (p < 0.008), the course of childbirth (i.e., giving birth alone, p < 0.015) and partner’s participation in earlier medical appointments (associating with lonely medical appointments, p < 0.016). A higher level of anxiety (reported by 68.7% of participants, n = 346) was statistically significantly (Pearson correlation) associated with a lower age (p < 0.002) and a lack of partner’s participation in medical appointments (p < 0.030). Women giving birth during the pandemic also admitted that they were afraid of loneliness during hospitalization, resulting from visiting policies (64.5%, n = 325); this variable was significantly associated with a lower age (p < 0.002). Many women experienced the fear of being separated from their child (80%, n = 403), another variable significantly associated with a lower age at the p level of <0.011 (even though only about 5% were actually separated from the child), as well as fears concerning their infant’s health (77.5%, n = 391, without any statistically significant association with demographic and other variables). The above data are illustrated in Figure 3. 3.2. Restrictions and Healthcare System We also examined how the pandemic restrictions influenced the experiences related to pregnancy in general, and the encounters with the healthcare system’s services in particular. Almost a third of the women surveyed admitted that the pandemic restrictions reduced their happiness during pregnancy (29%, n = 293 of the respondents indicated “definitely yes” or “probably yes”; 50.5%, n = 511 indicated “probably not” and “definitely not”; 20.5%, n = 207 do “not know”; a statistically significant association with demographic variables was found only with the place of residence variable (p < 0.005, Pearson correlation), and it was stronger in smaller towns and villages). One of the limitations mentioned in the questionnaire was related to the availability of maternity care services, especially the restricted access to medical examinations. A total of 18% (n = 182) of the respondents indicated that due to the pandemic, they missed some prenatal care appointments, between two or three on average. Due to the restrictions, 17% (n = 172) experienced a limited access to health services, including tests and vaccinations. Among the most frequently indicated were: vaccinations, OGTT 75 g (Oral Glucose Tolerance Test), 11 to 13 + 6 scan (first trimester screening), second trimester anomaly scan and amniocentesis. In extreme cases, as some women wrote in the survey, no tests were performed other than one ultrasound. Access to basic tests such as blood count and urinalysis was also difficult. One of the respondents wrote in a comment that some of the appointments took the form of teleconsultations (one may suspect that these were relatively frequent, but we did not ask the respondents directly). Respondents were asked if their pregnancy care was altered by the pandemic: 18% (n = 182) indicated that the care quality worsened, 49.2% (n = 497) declared it did not change, while for 1.6% (n = 16), it improved, with 31.3% (n = 316) expressing no opinion. Thus, taking into account both restricted access and perceived care quality, nearly 1/5 of respondents experienced lower care quality and/or accessibility due to the pandemic, regardless of demographic characteristics. As many as a quarter of the respondents (23.9%, n = 242) declared that they would have waited until the end of the pandemic before getting pregnant if they had known what was awaiting them. However, when asked whether the pandemic influenced their decision to get pregnant, the majority of women (78.3%, n = 792) admitted that it did not influence their decision (Table 3). Moreover, participants in our study suffered from restricted access to information related to childbirth since the onset of pandemic. A total of 40.4% (n = 408) of the women said that they did not receive any information. A total of 24.8% (n = 251) said that the information they received was insufficient. Relations with healthcare personnel were also affected, with more than 1/5 of the respondents (21.2%, n = 214) declaring deterioration in this respect. Detailed results of the measurement of the effect of epidemic restrictions are presented in Table 3. 4. Discussion Pregnancy involves a complex psychological process [15]. The fertility of a woman, her age, socioeconomic status and family situation are important factors [16]. The course of pregnancy involving complications also increases the incidence of depression in pregnant women. The context of the pandemic had a significant impact on the mental well-being of our respondents, which is in line with other research; in the systematic review of the prevalence of anxiety during the COVID-19 pandemic, it proved to be significantly higher among females, especially in Europe [17]. Anxiety is the most common mental health issue present during pregnancy. Rauf et al. found that during the pandemic, women experienced increased perinatal anxiety, and a lower availability of appropriate obstetric healthcare, which we also observed in our study. Moreover, in Rauf et al.’s study, women experienced increased levels of fear for their own health, as well as that of their baby’s, which was also an important aspect in our study [18]. Dunkel Shetter et al. emphasized that anxiety and stress during pregnancy are risk factors for negative outcomes for both mothers and children. Depression and post-traumatic stress disorder most often concern the perinatal period, i.e., 4–6 weeks after delivery [19]. As shown in a recent study, increased levels of anxiety scores were strongly associated with SARS-CoV-2 infection during pregnancy [20]. Due to the forced separation from the father of the child, some needs and expectations of women during pregnancy and childbirth were compromised. The patients mainly regretted limited participation of their partners in maternity care appointments and their absence during delivery. Before the outbreak of the pandemic, patients were able to freely use medical care in the company of a life partner. As showed by Cheng et al., the role of a partner in the care for a pregnant woman is crucial. Among others, low partner support was associated with higher pregnancy-related anxiety [21]. However, in our study, the lack of partner’s support was not intended but forced by sanitary restrictions (involuntary separation). Perhaps, for this reason, the absence of a partner during antenatal care generated the sense of injustice and anger among our responders. The systematic review of Antoniou et al. established that a correlation between the support from the partner and prenatal mental disorders and anxiety in women was common [22]. This is in concord with a previous study, showing that the presence of a partner during labor increases positive birth experiences. The partner provides support and assistance to the pregnant woman during childbirth, reducing her anxiety. The presence of a known and trusted person in the delivery room is essential for most first-time delivery patients [23]. Finally, research shows that when crises are affecting society at large, support and planning are needed for pregnant women, who are a particularly vulnerable [24]. What we propose as the conclusions of our study, is a list of recommendations to such effect. 5. Conclusions The pandemic turned out to have a significant impact on the quality of life and experiences of pregnant women who participated in our study, especially those of a younger age. During pregnancy, higher levels of anxiety and stress are observed. Among our respondents, the pandemic significantly influenced both, especially due to the perspective of a lonely childbirth and the risk of separation from an infant and its father/partner. It was a new and unpredictable situation that markedly influenced the well-being of pregnant women in all its dimensions: psychological, sociological and even physical. Being pregnant and giving birth to a child is a pivotal life event. Contrary to expectations, pregnant patients were denied access to prenatal care in the partner’s company, and family births and appointments were often suspended. Perinatal loneliness was not a choice, but a necessity. Involuntary separation that occurs widely [25] is a new sociological phenomenon, not only for pregnant women, but also for all patients at the time of the current pandemic. Despite many restrictions, 50.5% (n = 511) of the respondents declared that it did not diminish their joy of pregnancy. In quite important moments, such as the obstetric appointment or delivery, the partner could not take part. As the role of the partner appears to be very important during pregnancy, this forced absence significantly increased the feeling of anxiety. Pregnant women also struggled with a high sense of injustice. However, the decision to get pregnant was seemingly not influenced by the pandemic, with only 8.4% (n = 85) of the respondents declaring it had an impact on their decision. However, this artefact can be explained by the fact that half of the respondents gave birth during the early stage of the pandemic (49.9%, n = 504); thus, the decision to conceive must have preceded its onset. The fear of contracting COVID-19 during pregnancy (61%, n = 617) and the importance of having a partner present during medical appointments and delivery were highlighted as main challenges. The experiences of the patients we examined have shown that there is still no answer to the loneliness problem in the health care system. Unfortunately, these experiences may have a significant impact on subsequent procreation plans. While writing this article, we are currently in the middle of the fifth wave of the COVID-19 pandemic. Appointments with a partner are still banned in many places, but more and more people have already been vaccinated against COVID-19. The situation of pregnant women is improving. However, it does not change the fact that patients who have already given birth feel a sense of loss. We hope that with more knowledge about the new SARS-CoV-2 virus and the increasing number of vaccinated people, we will be able to gradually return to the standards of perinatal care from before the outbreak of the pandemic. Recommendations Based on our research, we would like to present recommendations that can contribute to better prenatal care for pregnant women and their partners in the current and future pandemics: Firstly, restriction-related risk calculations should take into account the benefits of accompanied medical appointments and births, which, if possible, should be restored and maintained. These actions can reduce the burden of stress during pregnancy and its consequences. The presence of a partner during pregnancy and childbirth is often paramount for a woman. Additionally, although the partner’s participation may pose an additional risk of infection, available verification methods, e.g., by rapid antigen tests or PCR tests, should be used instead of a top-down ban on joint visits. Secondly, as shown by research and clinical experience, special situations require special preparation of personnel. It can be achieved through training in response to the specific needs of patients in unusual times. If the situation does not actually allow the patient to contact her family, other forms of contact and new technologies should be used, e.g., video calls, remote or hybrid participation. Thirdly, psychological care should be provided to all patients and their carers/partners. Psychological consultation should be offered to each patient and her partner. This is especially true of young pregnant women and those giving birth for the first time, and women who are less well-off. This could help identify patients requiring therapy or psychiatric treatment. Moreover, offering patients as much support and empathy as possible is crucial. Most of the respondents indicated insufficient access to information about labor and hospitalization during the pandemic. It is important to improve communication among health professionals and patients. All the regulations related to the necessary restrictions should be presented in simple terms and explained to patients. All the described solutions should be incorporated into the maternity care plan, which should take into account different possible scenarios in case of an emergency situation. 6. Limitations Due to epidemic restrictions, the study was largely conducted via the Internet. Only a small number of respondents completed the questionnaire at the clinic (n = 112). Additionally, the selection of the sample was not random, but based on the snowball method. Even though a relatively heterogeneous group was obtained, a large overrepresentation of women with a higher education was observed. Moreover, the study was not preceded by extensive qualitative piloting (only by the doctor’s conversations with patients and desk-research). We also have not collected data on the exact time since the birth. However, the questionnaire was administered at the turn of January and February 2021, so all respondents had given birth up to 12 months prior (the pandemic started in Poland in March 2020). Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095081/s1, Table S1. Multivariate linear regression analysis: increased anxiety, Table S2. Multivariate linear regression analysis: anger, Table S3. Multivariate linear regression analysis: feeling of injustice, Table S4. Multivariate linear regression analysis: overwhelming sadness, Table S5. Multivariate linear regression analysis: a sense of loss. Click here for additional data file. Author Contributions Conceptualization, P.M. and S.M.; methodology, S.M.; software, S.M.; validation, P.M., S.M.; formal analysis, S.M.; investigation, P.M. and S.M.; resources, P.M. and S.M.; data curation, S.M.; writing—original draft preparation, P.M. and S.M.; writing—review and editing, P.M., S.M. and M.L.; visualization, S.M.; supervision, S.M.; project administration, P.M. and S.M. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted according to the Declaration of Helsinki guidelines and was approved by the Research Ethics Committee of Warmia and Mazury University in Olsztyn, Poland. No 6/2021. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The datasets are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Involuntary separation-measured variables, income and outcome. Figure 2 Emotions related with pregnancy (n = 507). Figure 3 Emotions related with childbirth (n = 504). ijerph-19-05081-t001_Table 1 Table 1 Characteristics of the studied group. Count Column N % (N = 1011) Age 17–24 110 10.9% 25–29 423 41.8% 30–34 347 34.3% 35–39 114 11.3% 40–44 15 1.5% 45–50 2 0.2% Education Primary education 13 1.3% Secondary education 235 23.2% Higher education—Bachelor’s degree 166 16.4% Higher education—Master’s degree 597 59.1% Occupational status Employed 832 82.3% Studying 29 2.9% Unemployed 150 14.8% Place of residence (the number of residents) Countryside 237 23.4% City up to 50,000 208 20.6% City 50,000–150,000 131 13.0% City 150,000–500,000 196 19.4% City over 500,000 239 23.6% Single 10 1.0% In an informal relationship 209 20.7% Marital status Married 786 77.7% Divorced 4 0.4% Widowed 2 0.2% Health status (pregnancy and childbirth) Pregnant during the pandemic (responded before giving birth) 507 50.1% Gave birth during the pandemic 504 49.9% Involuntary separation Solo medical appointments during pregnancy (among all studied women) 853 84.37% Solo childbirth (among women who gave birth) 334 66.27% ijerph-19-05081-t002_Table 2 Table 2 (A) Pearson correlation between demographic variables and perceived emotions related to separation. (B) Multivariate linear regression analysis and odds ratio. (A) Age Education Occupational Status Place of Residence Size Marital Status Increased anxiety Pearson correlation −0.125 ** −0.061 −0.002 0.048 −0.047 Sig. (two-tailed) <0.000 0.081 0.963 0.168 0.174 N 822 822 822 822 822 Anger Pearson correlation −0.202 ** −0.149 ** 0.013 −0.043 −0.075 * Sig. (two-tailed) <0.000 <0.000 0.719 0.211 0.031 N 829 829 829 829 829 Feeling of injustice Pearson correlation −0.181 ** −0.098 ** 0.006 −0.027 −0.049 Sig. (two-tailed) <0.000 <0.005 0.854 0.439 0.155 N 832 832 832 832 832 Overwhelming sadness Pearson correlation −0.177 ** −0.138 ** 0.034 −0.026 −0.087 * Sig. (two-tailed) <0.000 <0.000 0.335 0.465 0.013 N 823 823 823 823 823 A sense of loss Pearson correlation −0.111 ** −0.056 −0.034 0.056 −0.039 Sig. (two-tailed) <0.001 0.106 0.326 0.107 0.258 N 826 826 826 826 826 (B) Age Education Occupational Status Place of Residence Size Marital Status Increased anxiety Standardized Coefficients Beta −0.126 −0.038 −0.028 0.070 −0.019 Sig. <0.001 0.334 0.445 0.051 0.591 OR (CI and p-value) 1.54 (1.17 to 2.04, p = 0.0021) 1.33 (0.97 to 1.84, p = 0.0781) 0.92 (0.64 to 1.32, p = 0.6646) 0.8 (0.60 to 1.06, p = 0.1204) 1.44 (1.03 to 2.03, p = 0.0327) Anger Standardized Coefficients Beta −0.176 −0.102 −0.058 −0.002 −0.026 Sig. <0.001 0.008 0.108 0.958 0.459 OR (CI and p-value) 1.80 (1.36 to 2.37, p < 0.0001) 1.77 (1.28 to 2.45, p = 0.0005) 0.83 (0.58 to 1.19, p = 0.3200) 1.14 (0.86 to 1.50, p = 0.3458) 1.5 (1.07 to 2.12, p = 0.0172) Feeling of injustice Standardized Coefficients Beta −0.171 −0.052 −0.045 0.002 −0.012 Sig. <0.001 0.172 0.215 0.950 0.734 OR (CI and p-value) 1.62 (1.22 to 2.15, p = 0.0009) 1.43 (1.02 to 1.02, p = 0.0386) 0.97 (0.66 to 1.41, p = 0.8808) 1.07 (0.8 to 1.42, p = 0.6278) 1.46 (1.01 to 2.10, p = 0.0402) Overwhelming sadness Standardized Coefficients Beta −0.147 −0.090 −0.027 0.013 −0.044 Sig. <0.001 0.020 0.467 0.722 0.216 OR (CI and p-value) 1.82 (1.38 to 2.4, p < 0.0001) 1.63 (1.18 to 2.24, p = 0.0029) 0.83 (0.057 to 1.19, p = 0.3229) 1.12 (0.85 to 1.48, p = 0.4095) 1.42 (1.0 to 1.98, p = 0.0438) A sense of loss Standardized Coefficients Beta −0.116 −0.048 −0.059 0.074 −0.013 Sig. 0.002 0.218 0.108 0.040 0.723 OR (CI and p-value) 1.18 (0.9 to 1.55, p = 0.023) 1.16 (0.84 to 1.6, p = 0.3538) 1.16 (0.81 to 1.68, p = 0.3975) 0.76 (0.58 to 1.01, p = 0.0617) 1.22 (0.87 to 1.71, p = 0.2446) ** Correlation is significant at the 0.01 level (two-tailed). * Correlation is significant at the 0.05 level (two-tailed). ijerph-19-05081-t003_Table 3 Table 3 Effects of epidemic restrictions. Count Column N % (N = 1011) Impact of pandemic restrictions on happiness during pregnancy: reduced happiness Definitely and probably yes 293 29% Definitely and probably not 511 50.5% Do not know 207 20.5% Healthcare availability during pandemic (% does not accumulate—affirmative answers from different questions) Missed prenatal care appointments 182 18% Limited access to health services 172 17% Limited access to main doctor 170 16.8% Limited access to the hospital emergency ward 275 27.2% Healthcare quality during pandemic Worsened 182 18% Did not changed 497 49.2% Improved 16 1.6% Hard to say 316 31.3% Access to information related to childbirth since the onset of pandemic Did not received all sufficient information 408 40.4% Received, but lacked sufficient information 251 24.8% Received all sufficient information 352 34.8% Worsened 214 21.2% Relations with healthcare personnel Did not changed 709 70.1% Improved 88 8.7% Decision to get pregnant I would do the same 769 76.1% I would not decide to get pregnant 242 23.9% No 792 78.3% Did the pandemic influence the decision to get pregnant? Yes 85 8.4% Hard to say 134 13.3% Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Biaggi A. Conroy S. Pawlby S. Pariante C.M. Identifying the women at risk of antenatal anxiety and depression: A systematic review J. Affect. Disord. 2015 191 62 77 10.1016/j.jad.2015.11.014 26650969 2. Orsolini L. Latini R. Pompili M. Serafini G. Volpe U. Vellante F. Fornaro M. Valchera A. Tomasetti C. Fraticelli S. Understanding the Complex of Suicide in Depression: From Research to Clinics Psychiatry Investig. 2020 17 207 221 10.30773/pi.2019.0171 3. Wilska A. Rantanen A. Botha E. Joronen K. Parenting Fears and Concerns during Pregnancy: A Qualitative Survey Nurs. Rep. 2021 11 82 10.3390/nursrep11040082 4. Platto S. Wang Y. Zhou J. Carafoli E. History of the COVID-19 pandemic: Origin, explosion, worldwide spreading Biochem. Biophys. Res. Commun. 2020 538 14 23 10.1016/j.bbrc.2020.10.087 33199023 5. Dandagi G.L. Byahatti S.M. An insight into the swine-influenza A (H1N1) virus infection in humans Lung India 2011 28 34 38 10.4103/0970-2113.76299 21654984 6. Siston A.M. Pandemic 2009 Influenza A(H1N1) Virus Illness Among Pregnant Women in the United States JAMA 2010 303 1517 1525 10.1001/jama.2010.479 20407061 7. Carlson A. Thung S.F. Norwitz E.R. H1N1 Influenza in Pregnancy: What All Obstetric Care Providers Ought to Know Rev. Obstet. Gynecol. 2009 2 139 145 19826571 8. Saeed S. Hasan S. Ahmad S.A. Masood R. Ebola virus: A global public health menace: A narrative review J. Fam. Med. Prim. Care 2019 8 2189 2201 10.4103/jfmpc.jfmpc_297_19 9. Benski C. Di Filippo D. Taraschi G. Reich M.R. Guidelines for Pregnancy Management During the COVID-19 Pandemic: A Public Health Conundrum Int. J. Environ. Res. Public Health 2020 17 8277 10.3390/ijerph17218277 10. Stanowisko Prezydium PTGiP Odnośnie Interpretacji Zarządzenia NFZ Dotyczącego Porodów Rodzinnych Available online: https://www.ptgin.pl/aktualnosc/stanowisko-prezydium-ptgip-odnosnie-interpretacji-zarzadzenia-nfz-dotyczacego-porodow (accessed on 1 April 2022) 11. Cacioppo J.T. Cacioppo S. Boomsma D.I. Evolutionary mechanisms for loneliness Cogn. Emot. 2014 28 3 21 10.1080/02699931.2013.837379 24067110 12. Jeste D.V. Lee E.E. Cacioppo S. Battling the Modern Behavioral Epidemic of Loneliness: Suggestions for Research and Interventions JAMA Psychiatry 2020 77 553 554 10.1001/jamapsychiatry.2020.0027 32129811 13. WHO WHOQOL: Measuring Quality of Life Available online: https://www.who.int/tools/whoqol (accessed on 1 April 2022) 14. George D. Mallery P. SPSS for Windows Step by Step: A Simple Guide and Reference. 11.0 Update 4th ed. Allyn & Bacon Boston, MA, USA 2003 15. Bjelica A. Cetkovic N. Trninic-Pjevic A. Mladenović-Segedi L. The phenomenon of pregnancy—A psychological view Ginekol. Pol. 2018 89 102 106 10.5603/GP.a2018.0017 29512815 16. Kim M.K. Lee S.M. Bae S.-H. Kim H.J. Lim N.G. Yoon S.-J. Lee J.Y. Jo M.-W. Socioeconomic status can affect pregnancy outcomes and complications, even with a universal healthcare system Int. J. Equity Health 2018 17 2 10.1186/s12939-017-0715-7 29304810 17. Kan F.P. Raoofi S. Rafiei S. Khani S. Hosseinifard H. Tajik F. Raoofi N. Ahmadi S. Aghalou S. Torabi F. A Systematic Review of the Prevalence of Anxiety among the General Population during the COVID-19 Pandemic J. Affect. Disord. 2021 293 391 398 34246947 18. Rauf N. Zulfiqar S. Mumtaz S. Maryam H. Shoukat R. Malik A. Rowther A. Rahman A. Surkan P. Atif N. The Impact of the COVID-19 Pandemic on Pregnant Women with Perinatal Anxiety Symptoms in Pakistan: A Qualitative Study Int. J. Environ. Res. Public Health 2021 18 8237 10.3390/ijerph18168237 34443987 19. Dikmen-Yildiz P. Ayers S. Phillips L. Depression, anxiety, PTSD and comorbidity in perinatal women in Turkey: A longitudinal population-based study Midwifery 2017 55 29 37 10.1016/j.midw.2017.09.001 28917088 20. Nowacka U. Kozlowski S. Januszewski M. Sierdzinski J. Jakimiuk A. Issat T. COVID-19 Pandemic-Related Anxiety in Pregnant Women Int. J. Environ. Res. Public Health 2021 18 7221 10.3390/ijerph18147221 34299673 21. Cheng E.R. Rifas-Shiman S.L. Perkins M.E. Rich-Edwards J.W. Gillman M.W. Wright R. Taveras E.M. The Influence of Antenatal Partner Support on Pregnancy Outcomes J. Women’s Health 2016 25 672 679 10.1089/jwh.2015.5462 22. Antoniou E. Stamoulou P. Tzanoulinou M.-D. Orovou E. Perinatal Mental Health; The Role and the Effect of the Partner: A Systematic Review Healthcare 2021 9 1572 10.3390/healthcare9111572 34828618 23. Karlström A. Nystedt A. Hildingsson I. The meaning of a very positive birth experience: Focus groups discussions with women BMC Pregnancy Childbirth 2015 15 251 10.1186/s12884-015-0683-0 26453022 24. Silva-Suarez G. Rabionet S.E. Zorrilla C.D. Perez-Menendez H. Rivera-Leon S. Pregnant Women’s Experiences during Hurricane Maria: Impact, Personal Meaning, and Health Care Needs Int. J. Environ. Res. Public Health 2021 18 8541 10.3390/ijerph18168541 34444290 25. Glasier M.W.C. Arbeau K.J. Caregiving Spouses and the Experience of Involuntary Separation Gerontologist 2017 59 465 473 10.1093/geront/gnx163 29045635

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095506 ijerph-19-05506 Article Investigation of Antimicrobial Resistance Genes in Listeria monocytogenes from 2010 through to 2021 Hanes Robert M. Huang Zuyi * Regal Patricia Academic Editor Lamas Alexandre Academic Editor Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA; rhanes01@villanova.edu * Correspondence: zuyi.huang@villanova.edu; Tel.: +1-610-519-4848 01 5 2022 5 2022 19 9 550628 2 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Antimicrobial resistance (AMR) is a serious public health issue. Due to resistance to current antibiotics and a low rate of development of new classes of antimicrobials, AMR is a leading cause of death worldwide. Listeria monocytogenes is a deadly foodborne pathogen that causes listeriosis for the immunocompromised, the elderly, and pregnant women. Unfortunately, antimicrobial resistance has been reported in L. monocytogenes. This study conducted the first comprehensive statistical analysis of L. monocytogenes isolate data from the National Pathogen Detection Isolate Browser (NPDIB) to identify the trends for AMR genes in L. monocytogenes. Principal component analysis was firstly used to project the multi-dimensional data into two dimensions. Hierarchical clustering was then used to identify the significant AMR genes found in L. monocytogenes samples and to assess changes during the period from 2010 through to 2021. Statistical analysis of the data identified fosX, lin, abc-f, and tet(M) as the four most common AMR genes found in L. monocytogenes. It was determined that there was no increase in AMR genes during the studied time period. It was also observed that the number of isolates decreased from 2016 to 2020. This study establishes a baseline for the ongoing monitoring of L. monocytogenes for AMR genes. antimicrobial resistance Listeria monocytogenes listeriosis principal component analysis hierarchical clustering This research received no external funding. ==== Body pmc1. Introduction Antimicrobial resistance (AMR) has been a general concern since antibiotics have been in use. Sulfa drugs, discovered in 1935, were the first widely used antibiotics and today there is widespread resistance to them [1]. Fleming was concerned about the development of penicillin resistance, and it was first observed in 1940 before penicillin was in widespread use. Tetracycline was introduced in 1950 and resistance was first observed in 1959, while vancomycin was introduced in 1959 and resistance was first observed in 1979 [2]. From the 1960s to the 1980s, AMR was not a significant concern due to the development of new antimicrobials and the discovery of new classes of antibiotics [2]. Today there are more than 20 classes of antibiotics available [3], and AMR is a serious public health issue due to increasing resistance and the low rate of development of new classes of antimicrobials. It is estimated that AMR is a leading cause of death worldwide after stroke and heart disease [4]. AMR not only increases the risk of infectious diseases, but it also negatively impacts other healthcare advances due to the risk of infection during treatments. In 2019, the CDC reported nearly 3 million infections and more than 35,000 deaths due to resistant microorganisms [5]. In Europe, such infections were responsible for more than 426,000 illnesses and 33,000 deaths in 2019 [6]. The CDC estimates that there are approximately 48 million cases of foodborne illnesses per year in the United States. Listeriosis, while not common, is one of the leading causes of death from foodborne illnesses [7]. In the U.S., there are approximately 1600 infections per year that result in about 260 deaths, corresponding to a hospitalization rate of 94% and a mortality rate of 16% [8]. The fatality rate can be as high as 30% in immunocompromised people, the elderly, and pregnant women [9]. Listeria monocytogenes, the pathogen that causes listeriosis, has the third highest mortality of foodborne pathogens in the U.S. [10]. It is part of the genus Listeria, which contains seven species; however, it is the only species pathogenic to animals and humans. L. monocytogenes has been found to be a highly occurring pathogen in several countries, including the United States, United Kingdom, Australia, Canada, and Mexico [11]. It is found in the environment and is carried by animals [12]. Humans are infected with the bacteria primarily by eating or handling contaminated food or touching contaminated surfaces [12]. It can also be transmitted from mother to child in utero or at birth [12]. L. monocytogenes is susceptible to a wide range of antibiotics active against Gram-positive bacteria, except cephalosporins and fosfomycin, for which it has inherent resistance [13]. The most common treatment for listeriosis is ampicillin used alone or in conjunction with gentamicin [13]. The first resistant strains of L. monocytogenes were isolated in France in 1988, including the first multidrug resistant strain [13]. Up through 1999, only sporadic resistance had been observed in antibiotics, including tetracycline, chloramphenicol, erythromycin, and streptomycin [13]. A foodborne strain was found to be resistant to trimethoprim, part of a secondary treatment for listeriosis for patients who are allergic to penicillins [13]. Notably, resistance to penicillins and gentamicin was not observed [13]. Similar trends were observed in a study of AMR in L. monocytogenes strains isolated in France between 1926 and 2007. That study also confirmed the presence of resistance genes and compared the minimum inhibitory concentrations (MICs) for various antibiotics. It was found that MICs from 1989–2007 increased compared to 1926–1988 [14]. In a study published in 2001, antimicrobial susceptibility testing (AST) was performed on Listeria isolates from retail foods purchased in the greater Dublin area. Resistance to penicillin and ampicillin was observed in 3.73% and 1.98% of 1001 isolates, respectively [15]. These were the second and third highest percentages of resistance observed, after tetracycline resistance, which was observed in 6.3% of isolates [15]. AST of 317 L. monocytogenes isolates collected from food, humans, and the environment in Italy between 1998 and 2009 found resistance to ampicillin, penicillin, gentamicin, and trimethoprim-sulfamethoxazole in 100% of the isolates [16]. That study also found that there was an increase in resistance in isolates from 2007–2009 compared to isolates analyzed from 1998–2006 [16]. In a 2014 study of L. monocytogenes from meat products and processing environments, resistance was observed in 34.5% of 206 isolates. The highest resistance was to oxacillin. There was low resistance to tetracycline and no resistance to penicillin [17]. Additionally, in a recent study in Uruguay, 50 L. monocytogenes isolates from various sources were subject to AST and analyzed for AMR genes. All of the samples were determined to be fully susceptible to penicillin, gentamicin, and trimethoprim-sulfamethoxazole [18]. This study also found that all L. monocytogenes isolates contained the resistance genes fosX and lin [18]. In a review published in 2021 and focused on foodborne pathogens isolated from dairy cattle and poultry manure in Northeastern Ohio, L. monocytogenes was the second highest pathogen found in the isolates. All the isolates were resistant to at least one of the antibiotics tested. Significantly, 89.5% of the 67 L. monocytogenes isolates were found to have ampicillin resistance and 47% were found to have penicillin resistance [19]. These studies show a trend of increasing AMR observed in L. monocytogenes. While resistance to antibiotics used in the first-line treatment used for listeriosis has not yet been widely reported in humans, resistance has been reported in animals, as discussed in the studies cited above. This is concerning because resistance in animals could eventually be transferred to humans. These observations demonstrate the importance of continued surveillance of AMR in L. monocytogenes and the need for the development of other therapeutic options. A potential method for monitoring the development of AMR is to monitor the occurrence of AMR genes. An active surveillance program is critical to monitoring the development of AMR among pathogens. In the United States, the National Center for Biotechnology Information (NCBI) (Bethesda, MD, USA) maintains the National Database of Antibiotic Resistant Organisms (NDARO) to aid surveillance of pathogens [20]. As part of this effort, the NCBI Pathogen Detection Isolate Browser (NPDIB) was developed to identify AMR genes observed in pathogen bacterial genomic sequences [21]. The NPDIB consists of the Reference Gene Catalog and AMRFinderPlus. The Reference Gene Catalog includes sequences from food, the environment, and patients received from public health agencies around the world. AMRFinderPlus is a program that identifies the AMR genes in both protein and nucleotide sequences that have been submitted to the Reference Gene Catalog. AMRFinderPlus has been validated against two different datasets [22]. While the data from the NPDIB data have been used to determine common AMR genes for general pathogens as a whole, few studies have been conducted for the deadly L. monocytogenes. In this work, a statistical analysis of isolate data from the NPDIB was thus performed to: (1) identify the major AMR genes found in L. monocytogenes samples; (2) assess changes over time to study the occurrence and development of AMR genes in L. monocytogenes; and (3) establish a baseline for ongoing monitoring. The collection date and location were determined from previous work in which it was found that the NPDIB was more widely used from 2010 onwards. In this previous work, it was also found that the locations in which the L. monocytogenes is highly occurring are United States, United Kingdom, Australia, Canada, and Mexico [11]. Therefore, this study is focused on the NPDIB data from 2010 to 2021 for several regions in the world with data available. These regions include: Australia/New Zealand, Asia, Europe, North America, South Africa, and United Kingdom/Ireland. 2. Materials and Methods 2.1. Antimicrobial Resistance Data from the NCBI Pathogen Detection Isolate Browser The NCBI Pathogen Detection Isolate Browser (NPDIB) currently contains almost a million total isolates covering 34 organism groups [21]. The data for this analysis were downloaded from the NPDIB on 24 February 2022, using the following search criteria:Organism group = Listeria monocytogenes; Collection date = from: 31 December 2009, to: 31 December 2021. For this analysis, the NPDIB data were downloaded into a Microsoft Excel worksheet. The data were then organized into a matrix where each row corresponded to a L. monocytogenes sample with the columns including the following: scientific name, collection date, location, isolation type, serovar, and AMR genotype. As for the isolation type, the clinical category represents samples isolated from human sources, while the environmental/other category represents samples isolated from all other sources including the environment, animals, and food. Table 1 shows a detailed description of each column category. After the data were downloaded from the NPDIB, they were formatted for subsequent analysis. A MATLAB program was written to extract the AMR genotype data from a single column into multiple columns. As downloaded from NPDIB, the AMR genotype data are in the following format: “aac(6′)-I = COMPLETE, abc-f = COMPLETE, fosX = COMPLETE, lin = COMPLETE, msr(C) = COMPLETE”. These data were processed to create one column per gene, populated with a 1 if the gene was found in the sample and 0 if the gene was not found. The data in the other columns were manipulated to align the formats and to replace text entries with numerical entries. Table 2 summarizes the data in the final spreadsheet that was used for analysis. 2.2. Principal Component Analysis and Hierarchical Clustering The data from the NPDIB were downloaded as described above. The data matrix contains a total of 35,753 rows, each of which corresponds to an isolate sample of L. monocytogenes entered from January 2010 through December 2021. These samples were further analyzed to obtain a matrix in which each row represents one gene while each column represents one year with the detection occurrence of the gene in the corresponding year recorded in the matrix cell. The data contained a total of 65 AMR genes for 2010 to 2021 resulting in a matrix that contains 65 rows and 12 columns. Due to the number of dimensions, these data were analyzed using principal component analysis (PCA) and hierarchical clustering (HC) to identify the highly occurring AMR genes by region and setting. PCA allows the visualization of multi-dimensional data in two dimensions. The data are expressed in terms of new variables that are linear combinations of the existing variables. The principal components PC1 and PC2 are those that retain the most variation from the original data [23]. In this work, PCA is used to project AMR genes into the PC1~PC2 two-dimensional space so that the outlier genes, which typically show higher occurrence over years, are identified for further investigation. While AMR genes can be visualized in PCA, certain genes are lumped together. PCA does not directly provide the correlation relationship between individual AMR genes. Therefore, hierarchical clustering is further used to group the genes projected onto the PC1~PC2 space into clusters that are similar to each other in the format of dendrograms. PCA and HC were performed, and graphs were generated using the free statistical software package R, version 1.4.1106, implemented in RStudio (Boston, MA, USA) [24]. 3. Results 3.1. Occurrence of Listeria monocytogenes The data matrix generated from the NPDIB data included 35,753 Listeria monocytogenes isolates from the six regions identified above: Australia/New Zealand, Asia, Europe, North America, South Africa, and UK/Ireland. In Figure 1A, the total number of samples peaked in 2016 and then declined during the subsequent years. Figure 1B shows this trend is driven by North America, consisting of USA, Canada, and Mexico, where L. monocytogenes is most prevalent. In UK/Ireland, the occurrence of L. monocytogenes increased modestly over the time period. In the other four regions, the occurrence of L. monocytogenes was relatively constant over the time period. In all cases, the number of samples declined in 2020 and 2021. Lower numbers of samples were expected in 2020 and 2021, likely a result of public health measures enacted due to the COVID-19 pandemic. The decline in the number of samples from 2016 through 2019 could potentially be due to an actual decrease in the occurrence of L. monocytogenes or simply due to fewer samples being submitted to the NPDIB. The decline in the number of samples of L. monocytogenes from 2016 through 2019 was further investigated by determining the total number of samples submitted to NPDIB per year from North America for all pathogens. Figure 2A indicates that the total number of samples submitted per year from North America for all pathogens shows a similar trend as L. monocytogenes samples. However, Figure 2B shows the percentage of L. monocytogenes samples declined over the time period starting in 2013. This suggests that the decrease in L. monocytogenes samples is due to a lower prevalence of the pathogen in North America and not simply due to an overall lower number of samples being collected and submitted to the NPDIB. 3.2. Presence of Antimicrobial Resistance Genes A comprehensive analysis of Listeria monocytogenes isolates was performed to determine the highly occurring AMR genes and to determine if AMR genes increased over time. For the time period 2010 to 2021, there are 35,753 samples for which the organism group is identified as L. monocytogenes. There were a total of 65 AMR genes found in these samples. Multivariate statistical analysis, mainly PCA and hierarchical clustering, was performed and the highly occurring genes were identified by region and isolation type. Upon initial review of the data, it was found that the genes fosX and lin are present in nearly every sample. The gene fosX is present in 99.98% of the samples and lin is present in 97.8% of the samples. The following analysis was performed using samples that contained at least one AMR gene other than fosX or lin. This resulted in a modified data matrix of 10,039 samples, in which reach row represented a L. monocytogenes sample, each column represented a gene, and the entries represented if the gene was detected in the sample. PCA was performed to determine the highly occurring genes. Figure 3 shows that fosX, lin, and abc-f are the most frequently occurring genes, followed by tet(M) and vanC, vanR, vanS, vanT, and vanXY-C, which occur at a greater frequency than the remaining 56 AMR genes. Hierarchical clustering (HC) was also performed to identify clusters of genes that occurred with similar frequencies. Figure 4 shows that fosX, abc-f, and lin are clustered together, followed by tet(M) and the vancomycin resistance genes vanC, vanR, vanS, vanT, and vanXY-C. The gene dfrG was also clustered with the vancomycin resistance genes. PCA and hierarchical clustering were also performed to compare regions based on the occurrence of AMR genes. For this analysis, a data matrix was generated in which each column represented the region from which the sample was collected and there was one column per gene in which the entries represented if the gene was detected in the region for each row. This resulted in a modified data matrix of 32,509 samples as there were a number of samples for which the location was not identified. The PCA and HC results are shown in Figure 5, which indicate that similar resistance genes were observed in the following clusters: (1) North America, (2) Europe and UK/Ireland, and (3) Asia, Australia/New Zealand, and South Africa. These results are not unexpected because the regions are clustered by geographical proximity. Table 3 lists the highly occurring genes found in each region. In all cases except Asia and North America, fosX, lin, and abc-f represent greater than or equal to 97% of the AMR genes observed. For North America, they represent 93% of the observed genes and for Asia, they represent 72% of the observed genes. Table 4 lists the highly occurring genes by isolation type. In both cases, the genes listed represent 99.5% of the genes observed in each setting. It is expected to find more variety in AMR genes in the environmental/other category because these represent a wider variety of sources and typically AMR genes originate in these sources before being transferred to humans. 3.3. Investigation of Highly Occurring AMR Genes Figure 6A shows the number of samples of Listeria monocytogenes with genes fosX, lin, abc-f, and tet(M) and the second chart (b) shows the number of samples with vanC, vanR, vanS, vanT, and vanXY-C. The genes fosX and lin show the same trend as the number of samples because they are present in nearly all the samples. The gene abc-f is relatively constant from 2013 through to 2019, suggesting that the frequency of this gene is increasing since the number of samples is declining over the time period. The gene tet(M) shows a similar trend to the number of samples suggesting the frequency of this gene remained constant over the time period. The five vancomycin resistance genes (vanC, vanR, vanS, vanT, and vanXY-C) spiked in 2014 and 2016 but have not been observed in recent years. Figure 7 confirms that the percentages of samples containing genes fosX, lin, and tet(M) fluctuated around the same values for samples from 2010 through to 2021. However, there was an increase in the frequency of abc-f from 2017 through to 2020. 3.4. The Biological Functions of the Highly Occurring Genes The four highest occurring genes were fosX, lin, abc-f, and tet(M). The fosX and lin AMR genes are present in nearly all samples. These genes impart antimicrobial resistance to fosfomycin, quinolones, and expanded-spectrum cephalosporins [18]. The abc-f gene is a lincomycin resistance gene [25] and the tet(M) gene is a tetracycline resistance gene [26]. Table 5 summarizes the biological functions of all the highly occurring AMR genes. 4. Discussion The results presented in Section 3.1 indicate that the frequency of L. monocytogenes has been declining in North America since 2015. To corroborate this result, the number of Listeria infections in the United States was reviewed from two other sources: the Foodborne Diseases Active Surveillance Network (FoodNet) and NORS. These two sources support the conclusion from the NPDIB data that L. monocytogenes did not increase from 2010 through to 2021. FoodNet tracks infections commonly transmitted through food since 1996. FoodNet’s surveillance area includes 15% of the US population across 10 states [39]. Table 6 shows the results for Listeria from the pathogen surveillance tool from 2010 through to 2020 [39]. These results show a more consistent rate of Listeria infections with a small peak in 2017. However, it is noted that the FoodNet data are smaller datasets over a small segment of the United States and the results support the general observation that Listeria infections are not increasing over time. The National Outbreak Reporting System (NORS) reports outbreaks for foodborne disease per year. Table 7 shows the results reported by NORS for Listeria from 2010 through to 2018 [40]. Similar to the FoodNet data, the NORS data do not align exactly with the trend seen in the NPDIB results, but they also support the general observation that Listeria infections are not increasing over time. From the results in Section 3.2, it is noted that a diversity of AMR genes was not observed in L. monocytogenes during the time period. There are two AMR genes, fosX and lin, that were present in nearly all samples. The fosX gene has been demonstrated to be part of the core genome of L. monocytogenes [41]. There are two additional AMR genes, abc-f and tet(M), that occurred at higher frequency. The frequency of occurrence of the gene tet(M) did not change over time and is consistent with observations of tetracycline resistance in the works cited in Section 1. The frequency of occurrence of the gene abc-f increased from 2017 through to 2020 but decreased in 2021. Based on the information included in Table 5, this gene does not confer resistance to the primary antibiotics used to treat listeriosis. There are five AMR genes, vanC, vanR, vanS, vanT, and vanXY-C, that occurred at a lower frequency. These were observed in the period 2014 to 2016 and have not been observed since. It is interesting to note that these genes were present only in environmental/other isolates and only in the years that L. monocytogenes had the highest frequency of occurrence. Going forward, isolates in the NPDIB should be monitored closely to see if these AMR genes occur again as that could potentially be an indicator of increased AMR and a rise in frequency of L. monocytogenes. The current treatment regimen for serious cases of listeriosis is ampicillin either used alone or in conjunction with gentamicin. The findings in this analysis are important because they demonstrate that AMR genes that confer resistance against ampicillin and gentamicin are not widely present in L. monocytogenes at this time. For example, the AMR gene ampR, which confers ampicillin resistance, and the AMR genes aac(6′) and aph(2″), which confer gentamicin resistance, were not found in any of the L. monocytogenes isolates. This indicates that the current treatment regimen will continue to be medically relevant. However, the results from NPDIB are in contrast with more recent studies cited in Section 1 in which resistance to penicillin, ampicillin, and gentamicin has been observed, e.g., [15,16,19]. As a result, ongoing monitoring of AMR genes in L. monocytogenes in the environment, animals, and humans is important because tracking the occurrence of genes that impart resistance to the first-line antibiotics will improve understanding of the future risks of the effectiveness of these treatments. In addition, the highly occurring genes can guide research for new treatments against L. monocytogenes. These AMR genes serve as potential drug targets for new and alternative treatments, for example, new antibiotics or compounds that will work synergistically with current antibiotics to treat resistant L. monocytogenes infections. Overall, these results demonstrate that the AMR genes present in L. monocytogenes samples from six regions are not changing over time and AMR resistance genes that impact the current treatment regimen were not observed in the NPDIB data. Although the observations from the NPDIB data are conclusive and generally supported by other sources, there are a couple of questions regarding the NPDIB data. First, the database is incomplete in several ways. For example, metadata are either missing or not consistently formatted, and there are very little data for antibiotic susceptibility testing. Second, the total number of samples reported in the NPDIB for all countries, all organisms declined from 2018 to 2019 and declined in the United States from 2017 to 2019. It is not clear if these declines are due to lower frequencies of isolates or due to lower compliance in submitting samples. Lower compliance in submitting samples to the NPDIB could potentially impact the validity of conclusions made from analysis of NPDIB data. For example, it may affect how representative the data are if not all health agencies in the USA or internationally are not uniformly collecting and sequencing samples and submitting to NCBI for analysis and inclusion in the NPDIB. 5. Conclusions It is concluded from the NPDIB data that there was no increase in antimicrobial resistance genes in L. monocytogenes during the time period from 2010 through to 2021. This is supported by the fact that AMR genes, with the exception of fosX and lin, are not observed in a significant number of samples over the time period and by the fact that L. monocytogenes isolates are observed to be decreasing over time. It would be expected that an increase in antimicrobial resistance in L. monocytogenes would also result in an increase in the number of reported isolates. Going forward, efforts should focus to ensure samples are submitted to NCBI and to improve the consistency in metadata because, as shown in this work, the database can be used for the surveillance of antimicrobial resistance for the 34 pathogens included in the database. L. monocytogenes isolates should be monitored closely for any changes in AMR genes, as well as for the appearance of ampicillin or gentamicin resistance genes. It would be critical to track and trace these cases closely as they could potentially be indicators of a rise in the frequency of L. monocytogenes. Author Contributions Conceptualization, Z.H.; methodology, Z.H.; formal analysis, R.M.H.; data curation, R.M.H.; writing—original draft preparation, R.M.H.; writing—review and editing, Z.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A) Total number of L. monocytogenes samples per year; (B) L. monocytogenes samples per region per year. Figure 2 (A) Total number of samples from all pathogens and L. monocytogenes per year; (B) L. monocytogenes samples as a percentage of total pathogens per year. Figure 3 PCA to identify the most frequently occurring AMR genes in L. monocytogenes samples. Figure 4 Hierarchical clustering to identify the AMR genes that occurred with similar frequency in L. monocytogenes samples. Figure 5 PCA (A) of regions on the basis of AMR genes; HC (B) of regions on the basis of AMR genes. Figure 6 (A) Number of L. monocytogenes samples per year with genes fosX, lin, and abc-f and tet(M). (B) Number of L. monocytogenes samples per year with genes vanC, vanR, vanS, vanT, and vanXY-C. Figure 7 Percentage of L. monocytogenes samples per year with genes fosX, lin, abc-f, and tet(M). ijerph-19-05506-t001_Table 1 Table 1 Description of data downloaded from NPDIB. Category Description Scientific name Listeria monocytogenes Collection date Date the sample was collected Location Location from which the sample was collected Isolation type Clinical or environmental/other Serovar Serovar AMR genotype List of the AMR genotypes identified in sample ijerph-19-05506-t002_Table 2 Table 2 Description of processed NPDIB data matrix used for analysis. Category Abbreviated Name Entries Comments Scientific name Sci_name 1 = Listeria monocytogenes Collection date Year 2010 through to 2021 Location Region 1 = Australia/New Zealand 2 = Asia 3 = Europe 4 = North America 5 = South Africa 6 = United Kingdom/Ireland Isolation type Epi_type 1 = clinical 2 = environmental Serovar Serovar 1 = 1/2a 2 = 1/2b 3 = 4b AMR gene Gene name, e.g., fosX 0 = not found in sample 1 = found in sample There is 1 column for each gene ijerph-19-05506-t003_Table 3 Table 3 Highly occurring AMR genes by region. Aus/NZ Asia Europe N. America S. Africa UK/Ireland fosX fosX fosX fosX fosX fosX abc-f lin abc-f abc-f lin abc-f lin abc-f lin lin abc-f lin erm(G) tet(M) tet(M) tet(M) fexA tet(M) tet(M) dfrG vanC tet(M) tet(S) vanR dfrG ant(6)-Ia vanXY-C tet(S) erm(B) vanT aph(3′)-IIIa vanS lnu(B) tet(S) spw catA1 catA catA1 mef(A) msr(D) erm(C) fexA lnu(A) ijerph-19-05506-t004_Table 4 Table 4 Highly occurring AMR genes by isolation type. Clinical Environmental/Other fosX fosX lin abc-f abc-f lin tet(M) tet(M) catA1 vanC catA vanR mef(A) vanXY-C msr(D) vanT dfrG vanS fexA tet(S) dfrE fexA dfrG erm(B) lnu(G) blaTEM-116 erm(C) lsa(A) mph(B) tet(L) ijerph-19-05506-t005_Table 5 Table 5 Biological functions of highly occurring AMR genes. AMR Gene Biological Function References fosX Catalyzes hydration of fosfomycin breaking the oxirane ring [18] abc-f ATP-binding cassette protein that mediates resistance to a broad array of antibiotic classes that target the ribosome of Gram-positive pathogens [25] lin Ribosomal protection protein, lincomycin [18] tet(M) Tetracycline resistance (ribosome protection), class M [27,28] vanC Glycopeptide resistance gene; vancomycin, class C [29] vanR Glycopeptide resistance gene; vancomycin, class R [30] vanXY-C Glycopeptide resistance gene; vancomycin [31] vanT Glycopeptide resistance gene; vancomycin, class T [32] vanS Glycopeptide resistance gene; vancomycin, class S [30] tet(S) Tetracycline resistance (ribosome protection), class S [27,28] dfrE Trimethoprim resistance [33] fexA Active efflux, phenicols [28] dfrG Trimethoprim resistance [34] erm(B) Ribosome modification-mediated resistance; macrolide, lincosamide, and streptogramin B [27] lnu(G) Enzymatic inactivation by nucleotidylation, lincomycin [35] blaTEM-116 Β-lactamase, broad-spectrum cephalosporin [36] erm(C) Ribosome modification-mediated resistance; macrolide, lincosamide, and streptogramin B [28] lsa(A) Lincosamide and streptogramin A resistance [37] mph(B) Encode phosphotransferases conferring macrolide resistance [38] tet(L) Tetracycline resistance (active efflux), class L [27,28] ijerph-19-05506-t006_Table 6 Table 6 FoodNet data for Listeria infections by year. Year Infections (Incidence Per 100,000 Population) 2010 0.26 2011 0.28 2012 0.26 2013 0.25 2014 0.24 2015 0.25 2016 0.26 2017 0.32 2018 0.26 2019 0.27 2020 0.2 ijerph-19-05506-t007_Table 7 Table 7 NORS outbreak data for Listeria per year. Year Outbreaks Illnesses Hospitalizations Deaths 2009 4 35 18 0 2010 5 32 29 9 2011 6 209 184 39 2012 5 41 38 6 2013 10 86 77 16 2014 14 84 79 20 2015 6 75 61 7 2016 6 77 69 10 2017 11 54 47 7 2018 4 43 38 4 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Aminov R.I. A brief history of the antibiotic era: Lessons learned and challenges for the future Front. Microbiol. 2010 12 305 312 10.3389/fmicb.2010.00134 21687759 2. Christaki E. Marcou M. Tofarides A. Antimicrobial resistance in bacteria: Mechanisms, evolution, and persistence J. Mol. Evol. 2020 88 26 40 10.1007/s00239-019-09914-3 31659373 3. Mühlberg E. Umstätter F. Kleist C. Domhan C. Mier W. Uhl P. Renaissance of vancomycin: Approaches for breaking antibiotic resistance in multidrug-resistant bacteria Can. J. Microbiol. 2020 66 11 16 10.1139/cjm-2019-0309 31545906 4. Bowler J. The 3rd Leading Global Cause of Death Is Likely Not What You Think, New Study Reveals Available online: https://www.sciencealert.com/the-third-leading-cause-of-death-globally-in-2019-was-antibiotic-resistant-bacterial-infection (accessed on 24 February 2022) 5. CDC Antibiotic Resistance Threats in the United States U.S Department of Health and Human Services Washington, DC, USA 2019 1 113 10.15620/cdc:82532 6. Friedrich A.W. Control of hospital acquired infections and antimicrobial resistance in Europe: The way to go Wien. Med. Wochenschr. 2019 169 25 30 10.1007/s10354-018-0676-5 30623278 7. FDA Common Foodborne Disease Causes Available online: https://www.fda.gov/files/food/published/Most-Common-Foodborne-Illnesses-%28PDF%29.pdf (accessed on 13 February 2022) 8. CDC National Enteric Disease Surveillance: The Listeria Initiative National Center for Emerging and Zoonotic Infectious Diseases Atlanta, GA, USA 2016 1 2 9. Lotfollahi L. Prevalence and antimicrobial resistance profiles of Listeria monocytogenes in spontaneous abortions in humans Afr. J. Microbiol. Res. 2011 5 1990 1993 10.5897/AJMR11.498 10. Hurley D. Luque-Sastre L. Parker C.T. Huynh S. Eshwar A.K. Nguyen S.V. Andrews N. Moura A. Fox E.M. Jordan K. Whole-genome sequencing-based characterization of 100 Listeria monocytogenes isolates collected from food processing environments over a four-year period Appl. Environ. Sci. 2019 4 e00252-19 10.1128/mSphere.00252-19 31391275 11. Yang K. Wang A. Fu M. Wang A. Chen K. Jia Q. Huang Z. Investigation of incidents and trends of antimicrobial resistance in foodborne pathogens in eight countries from historical sample data Int. J. Environ. Res. Public Health 2020 17 472 10.3390/ijerph17020472 12. Abd Al-Mayahi F.S. Jaber S.M. Multiple drug resistance of Listeria monocytogenes isolated from aborted women by using serological and molecular techniques in Diwaniyah city/Iraq Iran. J. Microbiol. 2020 12 305 312 10.18502/ijm.v12i4.3933 32994901 13. Charpentier E. Courvalin P. Antibiotic resistance in Listeria spp. Antimicrob. Agents Chem. 1999 43 2103 2108 10.1128/AAC.43.9.2103 14. Morvan A. Moubareck C. Leclercq A. Hervé-Bazin M. Bremont S. Lecuit M. Courvalin P. Le Monnier A. Antimicrobial resistance of Listeria monocytogenes strains isolated from humans in France Antimicrob. Agents Chem. 2010 54 2728 2731 10.1128/AAC.01557-09 15. Walsh D. Duffy G. Sheridan J.J. Blair I.S. McDowell D.A. Antibiotic resistance among Listeria, including Listeria monocytogenes, in retail foods J. Appl. Microbiol. 2001 90 517 522 10.1046/j.1365-2672.2001.01273.x 11309061 16. Caruso M. Fraccalvieri R. Pasquali F. Santagada G. Latorre L.M. Difato L.M. Miccolupo A. Normanno G. Parisi A. Antimicrobial susceptibility and multilocus sequence typing of Listeria monocytogenes isolated over 11 years from food, humans, and the environment in Italy Foodborne Pathog. Dis. 2020 17 284 294 10.1089/fpd.2019.2723 31718307 17. Gómez D. Azón E. Marco N. Carramiñana J.J. Rota C. Ariño A. Yangüela J. Antimicrobial resistance of Listeria monocytogenes and Listeria innocua from meat products and meat-processing environment Food Microbiol. 2014 42 61 65 10.1016/j.fm.2014.02.017 24929718 18. Mota M.I. Vázquez S. Cornejo C. D’Alessandro B. Braga V. Caetano A. Betancor L. Varela G. Does shiga toxin-producing Escherichia coli and Listeria monocytogenes contribute significantly to the burden of antimicrobial resistance in Uruguay? Front. Vet. Sci. 2020 7 903 10.3389/fvets.2020.583930 33240959 19. Hailu W. Helmy Y.A. Carney-Knisely G. Kauffman M. Fraga D. Rajashekara G. Prevalence and antimicrobial resistance profiles of foodborne pathogens isolated from dairy cattle and poultry manure amended farms in northeastern Ohio, the United States Antibiotics 2021 10 1450 10.3390/antibiotics10121450 34943663 20. National Database of Antibiotic Resistant Organisms Available online: https://www.ncbi.nlm.nih.gov/pathogens/antimicrobial-resistance/ (accessed on 13 February 2022) 21. Pathogen Detection Available online: https://www.ncbi.nlm.nih.gov/pathogens/ (accessed on 16 January 2022) 22. Feldgarden M. Brover V. Gonzalez-Escalona N. Frye J.G. Haendiges J. Haft D.H. Hoffmann M. Pettengill J.B. Prasad A.B. Tillman G.E. AMRFinderPlus and the reference gene catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence Sci. Rep. 2021 11 12728 10.1038/s41598-021-91456-0 34135355 23. Jollife I.T. Cadima J. Principal component analysis: A review and recent developments Philos. Trans. R. Soc. A 2016 374 20150202 10.1098/rsta.2015.0202 24. Stogios P.J. R: The R Project for Statistical Computing Available online: https://www.r-project.org/ (accessed on 20 February 2022) 25. Sharkey L.K.R. Edwards T.A. O’Neill A.J. ABC-F proteins mediate antibiotic resistance through ribosomal protection mBio 2016 7 e01975-15 10.1128/mBio.01975-15 27006457 26. Haubert L. Mendonça M. Lopes G.V. de Itapema Cardoso M.R. da Silva W.P. Listeria monocytogenes isolates from food and food environment harbouring tetM and ermB resistance genes Lett. Appl. Microbiol. 2016 62 23 29 10.1111/lam.12516 26518475 27. Brenciani A. Bacciaglia A. Vecchi M. Vitali L.A. Varaldo P.E. Giovanetti E. Genetic elements carrying erm(B) in Streptococcus pyogenes and association with tet(M) tetracycline resistance gene Antimicrob. Agents Chem. 2007 51 1209 1216 10.1128/AAC.01484-06 28. Hua M. Huang W. Chen A. Rehmet M. Jin C. Huang Z. Comparison of antimicrobial resistance detected in environmental and clinical isolates from historical data for the US BioMed Res. Int. 2020 51 1209 1216 10.1155/2020/4254530 32351993 29. Almahdawy O. Shalal O.S. Najee H. Description of vancomycin resistance genes in enterococcus sp. clinical strains isolated from Bucharest, Romania Rom. Biotechnol. Lett. 2019 24 395 399 10.25083/rbl/24.3/395.399 30. Evers S. Courvalin P. Regulation of VanB-type vancomycin resistance gene expression by the VanSB-VanRB two-component regulatory system in enterococcus faecalis V583 J. Bacteriol. 1996 178 1302 1309 10.1128/jb.178.5.1302-1309.1996 8631706 31. Reynolds P.E. Arias C.A. Courvalin P. Gene vanXY C encodes D,D-dipeptidase (VanX) and D,D-carboxypeptidase (VanY) activities in vancomycin-resistant Enterococcus gallinarum BM4174 Mol. Microbiol. 2002 34 341 349 10.1046/j.1365-2958.1999.01604.x 10564477 32. Stogios P.J. Savchenko A. Molecular mechanisms of vancomycin resistance Protein Sci. 2020 29 654 669 10.1002/pro.3819 31899563 33. Gómez-Sanz E. Haro-Moreno J.M. Jensen S.O. Roda-García J.J. López-Pérez M. The resistome and mobilome of multidrug-resistant Staphylococcus sciuri C2865 unveil a transferable trimethoprim resistance gene, designated dfrE, spread unnoticed mSystems 2021 6 e00511-21 10.1128/mSystems.00511-21 34. Zankari E. Hasman H. Cosentino S. Vestergaard M. Rasmussen S. Lund O. Aarestrup F.M. Larsen M.V. Identification of acquired antimicrobial resistance genes J. Antimicrob. Chem. 2012 67 2640 2644 10.1093/jac/dks261 35. Zhu X.Q. Wang X.M. Li H. Shang Y.H. Pan Y.S. Wu C.M. Wang Y. Du X.D. Shen J.Z. Novel lnu(G) gene conferring resistance to lincomycin by nucleotidylation, located on Tn6260 from enterococcus faecalis E531 J. Antimicrob. Chem. 2017 72 993 997 10.1093/jac/dkw549 36. Bokaeian M. Zahedani S.S. Bajgiran M.S. Moghaddam A.A. Frequency of PER, VEB, SHV, TEM and CTX-M genes in resistant strains of Pseudomonas aeruginosa producing extended spectrum β-Lactamases Jundishapur J. Microbiol. 2015 8 13783 10.5812/jjm.13783 37. Fernández-Fuentes M.A. Abriouel H. Ortega Morente E. Pérez Pulido R. Gálvez A. Genetic determinants of antimicrobial resistance in gram positive bacteria from organic foods Int. J. Food Microbiol. 2014 172 49 56 10.1016/j.ijfoodmicro.2013.11.032 24361832 38. Nair S. Ashton P. Doumith M. Connell S. Painset A. Mwaigwisya S. Langridge G. De Pinna E. Godbole G. Day M. WGS for surveillance of antimicrobial resistance: A pilot study to detect the prevalence and mechanism of resistance to azithromycin in a UK population of non-typhoidal Salmonella J. Antimicrob. Chem. 2016 71 3400 3408 10.1093/jac/dkw318 27585964 39. FoodNet Fast Available online: https://wwwn.cdc.gov/foodnetfast/ (accessed on 13 February 2022) 40. National Outbreak Reporting System Available online: https://wwwn.cdc.gov/norsdashboard/ (accessed on 13 February 2022) 41. Scortti M. Han L. Alvarez S. Leclercq A. Moura A. Lecuit M. Vazquez-Boland J. Epistatic control of intrinsic resistance by virulence genes in Listeria PLoS Genet. 2018 14 e1007525 10.1371/journal.pgen.1007525 30180166

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093289 materials-15-03289 Article The Effect of Ca and Mg on the Microstructure and Tribological Properties of YPbSn10 Antifriction Alloy Avram Vasile 1 Csaki Ioana 1* Mates Ileana 1 https://orcid.org/0000-0001-7033-6528 Stoica Nicolae Alexandru 2 Stoica Alina-Maria 2 https://orcid.org/0000-0001-6864-3297 Semenescu Augustin 13 Green Itzhak Academic Editor 1 Faculty of Materials Science and Engineering, University POLITEHNICA Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania; avram.vasile@upb.ro (V.A.); ileana_mariana.mates@upb.ro (I.M.); augustin.semenescu@upb.ro (A.S.) 2 Faculty of Mechanical Engineering and Mechatronics, University POLITEHNICA Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania; nicolae.stoica@upb.ro (N.A.S.); am.stoica@upb.ro (A.-M.S.) 3 Academy of Romanian Scientists, 3 Ilfov, 050044 Bucharest, Romania * Correspondence: ioana.apostolescu@upb.ro; Tel.: +40-749-504-540 04 5 2022 5 2022 15 9 328915 3 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). An alloy YPbSn10 used for antifriction applications was synthetized in a furnace and the structure was improved by a microalloying technique. The elements chosen for microalloying were Ca 2%wt and Mg 2%wt. The microalloying technique proved to have good results in producing alloys with homogeneous composition, with a good distribution of the hard phase. The alloys were produced in a furnace and samples were collected and investigated. The structural properties were investigated using an SEM technique with EDS analyses and XRD to identify the compounds formed during alloying. The tribological properties were investigated to see the improvement obtained in this area. The results revealed a homogeneous composition for both samples, alloyed with Ca or with Mg, and the friction coefficient was reduced after the microalloying with almost 20%. microalloying friction coefficient homogeneous microstructure University Politehnica of Bucharest-PubArt Programme supporting scientific articles and communications publicationThis research was funded by University Politehnica of Bucharest-PubArt Programme supporting scientific articles and communications publication. ==== Body pmc1. Introduction The antifriction alloys are a group of alloys with a soft matrix with hard inclusions. The representative alloys have more tin (Sn) and lead (Pb). For this study, an alloy easily found in Romania, with Pb as the main constituent, was studied. A quaternary alloy, YPbSn10, consisting in four elements: Pb, Sb, Sn and Cu, was chosen. An efficient method of improving the properties of antifriction alloys was proved to be microalloying with different elements such as Cd, Ni, As or P [1,2,3,4]. The chemical and physical characteristics determining the lubricant adsorption, chemical affinity towards the conjugated friction surface, dilation, conductivity and thermal fatigue coefficient are linked to the material’s nature. For antifriction alloys we formulated two basic requirements [1,3]: favorable behavior in sliding conditions in a semifluid friction regime and high wear resistance in exploitation. From the mechanical resistance point of view, the constituent phases are prone to be harder, thus the abrasive wear is reduced [4]. Other materials used in tribological applications are particulate reinforced aluminum hybrid metal matrix composites that have increased in automotive applications due to their distinct properties. In the present study, an effort has been made to synthesize Al7075 aluminum alloy with reinforcement of B4C and MoS2 as lubricant under weight percentages of 4%, 8% and 12% using a stir casting process. A significant improvement of wear resistance and coefficient of friction of aluminum hybrid composites has been achieved owing to inclusion of solid lubricant (MoS2) along with hard ceramic reinforcement particles (B4C) in the matrix alloy, proved by Shoufa Liu et al. [5]. The material hardness is also influenced by the presence of hard phases. To avoid hard phase agglomeration, a harmful process that might occur during alloy processing, microalloying could represent a good solution [6,7]. In this study, structural and tribological properties of YPbSn10 alloy microalloyed with Ca 2%wt and other samples microalloyed with Mg 2%wt were investigated. The reason for choosing Ca and Mg was that they produce in the structure hard phases that could be uniformly distributed in the structure and they are environmentally friendly elements. The compound CaPb3 has low toxicity and is the hard compound formed when the microalloying is carried out with Ca 2%wt. In the case of Mg microalloying, the hard compound formed is MgPb2 and it presents low toxicity. The novelty of this paper is to use an appropriate amount of Ca and Mg as nontoxic elements to obtain at least a 15% decrease in friction coefficient. Determining the friction coefficient is essential for the tribological evaluation of antifriction alloys. Such materials, including those described in this paper, have been analyzed by a series of researchers. They determined the friction coefficient of the materials using different types of tribological tests. For example, Nedolini et al. performed pin-on-disk tests on YSn83 [8], CuSn12, CuAl10Fe3 and AlSi12 [9]. Block-on-ring tests were performed by Wang et al. [10] on a ZCuSn10Pb10 alloy, by Amonov et al. on a Sn-based Babbitt metal [11] and Leszczynska-Madej et al. [11] on two different Sn alloys (SnSb12Cu6Pb and SnSb9Cu4). Zeren et al. [12] used for their studies journal bearing test equipment, where the bearings were made from two tin-based bearing alloys (SAE 12 and a Sn–Sb–Cu alloy). 2. Materials and Methods 2.1. Materials The alloys produced for the present paper were prepared as follows: two master alloys for YPbSn10 alloy, CuSb50 and PbSb50, Sn and Sb were used. The load was melted at 550 °C and overheated at 600–700 °C. Then, the slag and the coal layer from the metal surface were removed and the rest of the tin was introduced to the mixture. The alloy was maintained for 10–15 min at 500–550 °C, after mixing. For microalloying the YPbSn10 alloy, adding an extra step to the alloying process was considered. The material was developed as described and the rest of the tin was introduced into the metallic bath. The introduced elements were Ca and Mg, respectively, for the second set of samples. After introducing the tin, the melt was mixed and maintained for 10–15 min at 550–600 °C. The master alloys CuSnCa and CuSnMg were added, respectively, mixed for 1–2 min, then the slag was removed at a temperature of 425–450 °C and poured into a metallic shell. After introducing the master alloy to the metallic bath, for additional protection of the molten metal bath, an Ar stream was blown into the furnace, which was dried and purified by a CRS purifying cartridge. Ar flow rate: 1–1.5 L/min. Chemical composition of the starting alloy is shown in Table 1. The chemical composition for the alloy produced in this research was realized by inductive plasma emission spectroscopy (ICP-OES Spectroflame P, Germany) for Sn, Sb, Cu and Pb and with optical emission spectroscopy with continuum current. For ease of understanding the experiments, the samples were denoted as: Alloy       Sample YPbSn10Ca0.2       YP1 YPbSn10Mg0.2       YP2 For the study, the samples were embedded in Bakelite-type resin and then prepared by grinding with abrasive paper and polished with Lecloth-type cloth soaked with a suspension of α-alumina in water. The attack solution used was C2H6O + HNO3. For the microstructural investigation, an FEI Quanta 250 with high vacuum CBS, ESD and BSE microscope was used. The software used was XTMicroscope server for SEM ELEMENT EDS Analysis Software Suite for EDS. For XRD analyses, the data acquisition was realized by using a BRUKER D8 ADVANCE diffractometer with the aid of the DIFFRACplusXRD Commender (Bruker AXZ) software, using the Bragg–Brentano diffraction method, coupling Θ-Θ in a vertical configuration. Data processing was realized with the aid of DIFFRAC.EVA VER.5 2019 in the DIFFRAC.SUITE.EVA program package and the ICDD PDF4+2021 database. 2.2. Tribological Tests Tribological tests were carried out with a UMT II BRUKER (former CETR) tribometer. This testing method consists in the use of a cylindrical pin, mounted in the upper part of the tribometer, that applies a constant load on the flat specimen mounted on the lower module that has a translational movement. For these tests, the tribometer was equipped with a dual force sensor model DFH-20 (2 ÷ 200 N range, 25 mN resolution), used to measure the friction force between the upper and lower specimen, as well as to measure and control the normal loading force. In order to maintain a constant loading force during the tests, a suspension system was mounted between the force sensor and the pin holder. The pin has a diameter of 6.35 mm (nominal contact area 31.67 mm2) and length of 28 mm and is made of bronze, a material often used in friction couples because of its tribological properties. The materials of the lower specimen are the experimental alloys under study. The tests were performed in dry conditions at room temperature. The tribometer allows real-time monitoring of the normal load force (Fz), the friction force (Ff) and the friction coefficient (COF). 3. Results and Discussions 3.1. Structural Characterization The produced samples’ microstructure analysis results were investigated to observe the influence of Ca on the structure of the alloy. The influence of the mischmetal microalloying on YPbSn10 alloy was present and the beneficial effect of the mischmetal was noticed at 1%wt of mischmetal [13,14]. Figure 1 reveals the compounds formed during microalloying of the base YPbSn10 alloy with Ca 2%wt (YP1 sample). The compounds formed were subjected to mapping to investigate the elements present in the compound. Mapping analyses revealed that the compound is formed from Sb, Sn and Cu, suggesting that the compound present here is based on these three elements. In the needle-like compound present in Figure 2, it was observed that copper is present in small quantities. EDS analysis was performed on the sample and the results are presented in the next section and in Figure 3. The EDS analyses revealed that the cuboidal compound contains Sb, Sn and Cu, as the mapping shows in Figure 3, and the dark gray needle-like compounds contain more Cu and the light gray mass contains Pb and Ca. Ca is uniformly distributed in the matrix. The compound containing calcium is present in the highest peak in Figure 4. The XRD patterns confirm the EDS investigation and reveal the Ca distributed evenly in the sample. Other compounds identified in the XRD pattern were Sb and SnSb. The small blue peaks belong to copper stibium compounds. The XRD analyses revealed that the Ca was efficiently microalloyed for the YPbSn10 alloy. For sample YP2, we investigated the microstructure, and the result is presented in Figure 5. Figure 5 reveals the cuboidal and needle-like compounds formed during microalloying with Mg 2%wt. The sample YP2 microstructure reveals a series of gray cuboidal compounds evenly distributed in the alloys. Additionally, needle-like compounds with a dark gray color were observed. The bulk alloy is light gray. Mapping analyses were performed on the cuboidal compound and the results are presented in Figure 6. For sample YP1, the elements present in the cuboidal compound were Sb and Sn. The needle-like compounds contain Cu and the bulk mass of the alloy contains Pb and MgPb evenly distributed in the bulk alloy. The EDS analyses results identifying the elements in the microalloyed sample are presented in Figure 7. In this figure, it was observed that the main compounds in the gray cuboidal compounds were Sb and Sn and, in the needle-like shape, more Cu and also Sb and Sn were found. Figure 8 shows the XRD pattern shows that the red peaks contain Pb and MgPb2 compound and the blue peaks contain mainly Sn and Sb. The MgPb2 compound is a high peak near Pb so the Mg was efficiently introduced in the alloy. 3.2. Tribological Tests In order to determine the friction coefficient (COF) between the three materials and the bronze pin, tribological “pin-on-flat” tests were performed over a length of 5 mm at three different sliding speeds (0.1 mm/s, 0.5 mm/s and 1 mm/s), using three different normal loads (5 N, 10 N and 15 N). Given that the nominal contact area between the pin and the six samples was a circular area determined by the diameter of the pin, the contact pressure corresponding to the three loading forces was 0.16 MPa (5 N), 0.32 MPa (10 N) and 0.48 MPa (15 N). Figure 9 presents the variation in the friction coefficient for the tests performed on the alloys at 1 mm/s sliding speed and under a normal load of 10 N (0.32 MPa contact pressure). For all the tests, the friction coefficient was relatively constant, indicating a smooth sliding. The average value of the friction coefficient was determined for all the tests performed and the results are presented in Table 2. It is observed that the relative sliding speed has no significant influence on the average COF. On the other hand, increasing the load leads, in most cases, to a slight increase in the average COF. The average values of the friction coefficient are graphically analyzed and compared in Figure 10. The analysis results reveal that the lowest values of the friction coefficient were obtained for the sample YP1, with a minimum value of 0.0871. This alloy had a significantly reduced COF compared to the base material (YP3). Comparing the results obtained for samples YP1 and YP2 with those obtained for standard sample YP3, we noticed that the introduction of the alloying materials (Ca and Mg) reduces the friction coefficient considerably, thus improving their tribological behavior. The good distribution of the hard phase in the alloy mass resulted in decreasing the friction coefficient. It was observed that for a sliding speed of 0.1 m/s, the Ca 2%wt alloyed sample (YP1) had the lowest friction coefficient. It was also observed that for the high sliding speeds employed in the experiments, the sample alloyed with 2% Ca (YP1) had an improved behavior, but also presented the lowest friction coefficient. The Ca added to this alloy was more beneficial than Mg. The CaPb compounds were well distributed in the alloy and the tribological results revealed a decrease with almost 20% of the friction coefficient in comparison with the base alloy YPbSn10. The improvement in the structure, by adding calcium or magnesium is proved by the improvement obtained in the tribological properties. The decrease in the friction coefficient value is a good measure for tribological properties. 4. Conclusions Two novel compositions of YPBSn10 alloy, microalloyed with 2%wt Ca or 2%wt Mg, were produced. The alloy characterization was performed from a structural and a tribological point of view. The investigated structure was homogeneous, and the hard phase was well distributed in the alloy matrix. The XRD analyses underlined the compounds formed during alloy production. Based on the tribological tests, it was determined that microalloying the YPBSn10 alloy with 2%wt Ca and 2%wt Mg, respectively, leads to an improved friction coefficient. However, by comparing the two alloys, the one containing Ca as the microalloying element had an improved behavior during tribological tests, exhibiting the lowest friction coefficient for different testing conditions. Thus, for an improved sliding behavior it is recommended to use the Ca 2%wt for microalloying of the YPbSn10 alloy for different tribological applications. Author Contributions Conceptualization, I.C. and V.A.; methodology, I.M.; software, N.A.S.; validation, A.-M.S. and N.A.S.; formal analysis, V.A.; investigation, A.S.; writing—original draft preparation, V.A.; writing—review and editing, I.C. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 SEM image of YP1 sample at 100 µm and 20 µm. Figure 2 Mapping analyses of the compounds formed during Ca microalloying. Figure 3 EDS analysis in points 1, 2 and 3 for the sample YP1. Figure 4 XRD pattern of the YP1 sample. Figure 5 SEM image of YP2 sample at 100 µm and 20 µm. Figure 6 Mapping for the cuboidal compound found in sample YP2. Figure 7 EDS analyses results for YP2 sample. Figure 8 XRD pattern for the sample YP2. Figure 9 Variation in the COF during the 10 N, 1 mm/s tests. Figure 10 Average values of the friction coefficient: (a) Comparison for the 0.1 mm/s sliding speed; (b) comparison for the 0.5 mm/s sliding speed; (c) comparison for the 1 mm/s sliding speed. materials-15-03289-t001_Table 1 Table 1 Chemical composition of alloys produced. Sample Pb Cu Sb Sn Zn Fe Al Ni Mo Ca Mg Others * YP1 bal 1.03 13.5 8.7 <0.02 <0.02 <0.02 <0.02 <0.02 0.23 - <0.01 YP2 bal 1.19 13.9 7.1 <0.02 <0.02 <0.02 <0.02 <0.02 - 0.21 <0.01 * Others: impurities that could be found in this alloy as S, Mo, Al, As, aso. materials-15-03289-t002_Table 2 Table 2 Average value of the friction coefficient. Sample Loading Force Fz Relative Sliding Speed 0.1 mm/s 0.5 mm/s 1 mm/s YP1: YPbSn10-Ca-2 5 N 0.0871 0.1015 0.0916 10 N 0.0989 0.1021 0.1074 15 N 0.1033 0.1126 0.1097 YP2: YPbSn10-Mg-2 5 N 0.1007 0.1159 0.1286 10 N 0.0975 0.1153 0.1190 15 N 0.1013 0.1008 0.1410 YP3: YPbSn10 5 N 0.1198 0.1255 0.1310 10 N 0.1144 0.1252 0.1254 15 N 0.1242 0.1243 0.1344 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Guruswamy S. Engineering Properties and Applications of Lead Alloys Marcel Dekker Inc. New York, NY, USA 2000 2. Majdanczuk T.B. Iljuszenko W.M. Bondarenko A.N. Effect of modifying and alloying elements on the structure and properties of surfaced layers made of high-tin bronze Biul. Inst. Spaw. 2017 61 39 43 10.17729/ebis.2017.1/5 3. Roik T.A. Kholyavko V.V. Vitsuk Y.Y. Influence of mechanism tribosynthesis of secondary structures for properties of antifriction composites materials based on nickel J. Met. Phys. Nov. Technol. 2009 31 1001 1016 4. Roik T.A. Gavrish A.P. Kirichok P.A. Vitsyuk Y. Effect of secondary structures on the functional properties of high-speed sintered bearings for printing machines Powder Metall. Met. Ceram. 2015 54 119 127 10.1007/s11106-015-9688-5 5. Liu S. Wang Y. Muthuramalingam T. Anbuchezhiyan G. Effect of B4C and MOS2 reinforcement on micro structure and wear properties of aluminum hybrid composite for automotive applications Compos. Part B Eng. 2019 176 107329 10.1016/j.compositesb.2019.107329 6. Jamroziak K. Roik T. Gavrish O. Vitsiuk I. Lesiuk G. Correia J.A. De Jesus A. Improved manufacturing performance of a new antifriction composite parts based on copper Eng. Fail. Anal. 2018 91 225 233 10.1016/j.engfailanal.2018.04.034 7. Deng J. Cao T. Self-lubricating mechanisms via the in situ formed tribofilm of sintered ceramics with CaF2 additions when sliding against hardened steel Int. J. Refract. Met. Hard Mater. 2007 25 189 197 10.1016/j.ijrmhm.2006.04.010 8. Nedeloni M.D. Nedeloni L. Cîndea L. Iancu V. Petrica A.V. Budai A.M. Conciatu I.L. Aspects concerning the cavitation erosion and dry sliding wear behavior of the YSn83 antifriction alloy and EN-GJS-400-15 spheroidal cast iron IOP Conf. Ser. Mater. Sci. Eng. 2019 477 012060 10.1088/1757-899X/477/1/012060 9. Nedeloni L. Korka Z.-I. Nedeloni M.-D. Conciatu I.L. Dry Sliding Wear behavior of some Cu and Al Alloys Ann. Eftimie Murgu Univ. Resita 2018 25 69 80 10. Wang Z. Zhang G. Kang Y. Liu Y. Ren X. The Effect of Y on the Microstructure, Mechanical and Wear Properties of ZCuSn10Pb10 Alloy Materials 2022 15 1047 10.3390/ma15031047 35160992 11. Amanov A. Ahn B. Lee M.G. Jeon Y. Pyun Y.S. Friction and Wear Reduction of Eccentric Journal Bearing Made of Sn-Based Babbitt for Ore Cone Crusher Materials 2016 9 950 10.3390/ma9110950 28774070 12. Leszczyńska-Madej B. Madej M. Hrabia-Wisnios J. Effect of Chemical Composition on the Microstructure and Tribological Properties of Sn-Based Alloys J. Mater. Eng. Perform 2019 28 4065 4073 10.1007/s11665-019-04154-4 13. Zeren A. Feyzullahoglu E. Zeren M. A study on tribological behavior of tin-based bearing material in dry sliding Mater. Des. 2007 28 318 323 10.1016/j.matdes.2005.05.016 14. Avram V. Semenescu A. Csáki I. Y-PbSn10 antifriction alloys microalloyed with mischmetal U.P.B. Sci. Bull. Ser. B 2021 83 307 312

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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091359 foods-11-01359 Article Consumers’ Understanding of Ultra-Processed Foods https://orcid.org/0000-0002-9807-2752 Sarmiento-Santos Juliana 1 Souza Melissa B. N. 1 Araujo Lydia S. 1 Pion Juliana M. V. 2 https://orcid.org/0000-0002-4284-0994 Carvalho Rosemary A. 3 https://orcid.org/0000-0001-5583-7092 Vanin Fernanda M. 1* Saletti Rosaria Academic Editor 1 Laboratory of Bread and Dough Process (LAPROPAMA), Food Engineering Department, Faculty of Animal Science and Food Engineering (USP/FZEA), University of São Paulo, Av. Duque de Caxias Norte 225, Pirassununga 13635-900, SP, Brazil; julianasarmiento@usp.br (J.S.-S.); nascimentomelissabs@usp.br (M.B.N.S.); lydia.araujo@usp.br (L.S.A.) 2 NOZ Pesquisa e Inteligência, Rua Cauowaá, 1575-92, São Paulo 01258-011, SP, Brazil; juvanin@nozinteligencia.com.br 3 Food Engineering Department, Macromolecules Functionality Multi-User Center (CEMFUM), Faculty of Animal Science and Food Engineering (USP/FZEA), University of São Paulo, Av. Duque de Caxias Norte 225, Pirassununga 13635-900, SP, Brazil; rosecarvalho@usp.br * Correspondence: fernanda.vanin@usp.br; Tel.: +55-19-3565-6866 07 5 2022 5 2022 11 9 135906 4 2022 04 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Food classification systems have been proposed to improve food quality criteria. Among these systems, “processing level” has been used as a criterion. NOVA classification, as the denotation “ultra-processed” food (UPF), has been widely used in different countries. However, even though some studies have pointed out some controversial aspects, no study has evaluated its comprehension by the population where it is used as reference. Therefore, this study explored the understanding of the term UPF for Brazilian consumers, where this denotation has been used in the last 8 years. A questionnaire was used, with questions referring to different aspects of self-assessment of knowledge about UPF. Altogether, 939 valid participants completed the questionnaire, and 81.9% of them declared to know the term UPF. For 78.2%, a better definition for UPF should be “foods that have gone through many processes in industry”. Finally, it was concluded that the term UPF is still confusing for most Brazilians, indicating the risk of use and the urgent necessity to improve the classifications systems and consequently consumer understanding. Only when all parties interested in healthy food work together could this problem be solved. offer intention NOVA classification baby food consumer knowledge food processing level “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil” (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2021/12270-9 This study was financed in part by the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil” (CAPES)—Finance Code 001. This research was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grant number 2021/12270-9. ==== Body pmc1. Introduction Changes in consumer diets have been observed in recent years. In general, there is an increase in the consumption of processed foods, a reduction in the intake of fresh products and an increase in the number of people who eat outside the home [1,2,3]. The diversity and increased supply of processed foods can influence the population’s eating patterns, especially children, as the first years of life stand out as an especially important period for establishing eating habits [4,5,6,7]. Parents identified time as a key difficulty preparing home-cooked meals with fresh ingredients [6]. Sadler et al. [8] consider that the increase in the number of working women, together with the need to save time, may be related to increasing development in the processed food market. Accordingly, it can be said that processed foods have been preferred due to their characteristics such as practicality and convenience. However, the healthiness of these products has been increasingly questioned. Food classification arrangements that categorize foods considering their “processing level” have resorted to predict diet-related quality criteria and their outcome on consumer health. Particularly, the NOVA classification presented the denotation “ultra-processed” food (UPF), and later, the dietary guidelines of many countries have used this classification system, including in Latin America, such as Brazil [9], Ecuador [10], Peru [11] and Uruguay [12], as well as Belgium [13] and France [14], in addition to the Food and Agriculture Organization of United Nations [15]. Basically, the NOVA classification groups foods into four major groups: (1) in natura or minimally processed foods, (2) processed culinary ingredients, (3) processed and (4) ultra-processed [16]. As claimed by NOVA, UPF are those that have five or more ingredients in their composition, mainly those with names unknown to the consumer, which are subjected to industrial processing that cannot be reproduced at home and that do not have an appearance or texture of a traditional food [9,16]. However, according to the authors themselves, this system does not consider the nutritional aspects of foods nor the techniques applied in the preparation of foods. Some studies have demonstrated the risks and concerns that the application of these definitions can bring to consumer health [17,18], in addition to highlighting inconsistencies and flaws, since their definitions are broad and ambiguous and often not supported by scientific evidence [19,20]. Jones [18] considered that consumers are confused by the definitions put forward by NOVA and, for example, they are avoiding some foods considered as UPF, such as cereals and wholegrain/fortified breads, which can result in reduced intake of folate, calcium and fiber. Similarly, even though breastfeeding is considered as ideal, secure choices are indispensable when this is not possible. Jones [18] mentions that avoiding the consumption of infant formulas, food supplements and gluten- or lactose-free foods, as they are UPFs, may not contribute to improved health, in addition to being foods that are not considered in preventing the increase in obesity. Furthermore, confirmation of the relationship between processed foods and healthiness is imprecise. It appears that classification systems were established to produce suggestions about larger groups of processed foods to draw generalized conclusions about the industrialized process. According to Poti et al. [21], although there is “very consistent” indication that UPF consumption and the levels of obesity and cardiometabolic health, it remains unclear whether this is process-dependent and not related to the nutritional content. The authors themselves conclude that more longitudinal studies are needed to control this confusion [21]. As previously mentioned, the Food Guide for the Brazilian Population (FGBP) was established considering the NOVA classification, and consequently, the guidelines use the theory of UPF. However, to be successful, healthcare statements must deliver easily comprehensible messages in order to be used by consumers and construct efficient assessments [22]. Thus, despite the considerable increase in studies on the NOVA classification, according to the authors’ knowledge, no study has been published in the literature exploring the understanding of the classification and the term “ultra-processed” in the Brazilian population. Therefore, this study aimed to explore how consumers conceptualize the UPF definition and assess the level of agreement between foods considered as UPF and those included in the NOVA classification. Based on the results obtained by the present survey, it is expected to provide subsidies to improve the knowledge in the light of the demystification of issues that have been gaining increasing social visibility, which in turn could impute better communication with the general population and all parties interested in food aspects, such as food industry, consumers and nutritional and health professionals. 2. Materials and Methods 2.1. Research Participants The understanding of the term UPF was explored through the dissemination of an online questionnaire. The questionnaire was previously evaluated by the Research Ethics Committee of the University of São Paulo for further data collection (Certificate of Ethical Appreciation number 36600620.9.0000.5422). Subsequently, the questionnaire was disseminated via email and social networks between October 2020 and July 2021, using convenience sampling (snowball technique), a method that has become popular for recruiting participants by taking advantage of social media, by assuming that a qualified participant shares an invite with other participants. This process assumes that there is a link between the initial sample and the others, allowing a series of references to be made within a circle of acquaintances [23,24]. In total, 1195 participants answered the questionnaire, representing a fixed percentage (0.0005%) of the total population in Brazil [25]. Table 1 presents the socioeconomic and other characteristics of the participants. No information about the study objectives was provided to the participants. After detailed analysis of all responses, eliminating the incomplete ones, 939 valid responses were considered, and the final sample was non-stratified. Supplementary Table S1 details the valid responses, preserving the participant’s privacy according to the Free and Informed Consent Term (TCLE). 2.2. Data Acquisition The questionnaire was divided into 6 steps: (1) affirmation of self-knowledge about UPF; (2) identification of UPF with images; (3) confirmation of knowledge about UPF based on the guidelines of the Food Guide for Brazilian Population (FGBP) [9]; (4) intention to offer some foods to children; (5) presentation of the definition of UPF according to the FGBP and verification of agreement or not; and (6) socioeconomic data. In the first step, the participants showed their self-knowledge about the subject by answering two questions: (1) “Do you know what UPF is?”, being able to answer “Yes” or “No”, and later indicating (2) “What do you think is the best definition of UPF?”, with two possible answers (a) “Foods with many processes performed by the food industry” or (b) “Foods with many ingredients in their formulation”. The second step consisted of visual assessment, through images, of different foods. Participants answered if they consider the samples as UPFs or not. Six images were used: potato chips with salt; baby food—identified as industrialized organic; infant formula; apple—presented in packaged fruit format; soft drink; and loaf bread. Four affirmations were presented, in the third step, to assess the participant’s knowledge about the concept of UPFs, and the participants questioned if they consider the information true or false. Then, the intention to offer certain foods to children under two years of age was evaluated (fourth step). Finally, in the fifth step, the participant was presented to the definition of UPF as detailed in the FGBP [9]. Then, participants answered if they already knew these definitions, if they agree with it or do not agree and, finally, explained why they agree or not with the definition. In the sixth step, the participants provided data with multiple-choice questions aimed at ratings on socioeconomic issues such as gender, year of birth, education, income and place of residence. Participants were also asked about the presence of children in the family. The study included supplementary questions related to food habits; however, they were not analyzed in the present study. 2.3. Data Analysis Results were analyzed by four researchers independently, and a consensus was reached for subjective differences. In data analysis, Spearman correlation rank coefficient was initially used to evaluate the correlation of the knowledge of the participant with their characteristics (normality of data sets was assessed using the Anderson–Darling test with p-values below 0.005). Then, Pearson’s correlation was used to evaluate the correlation between the declaration of self-knowledge and the correct answers, as the normality of both data sets was assessed using the Anderson–Darling test with p-values of 0.05 and 0.95, respectively. In relation to the number of correct answers and the participants’ professions, the normality of both data with the same test had p-values below 0.005; therefore, as the data set does not follow a normal distribution, Spearman correlation rank coefficient was used [26]. Data were verified with Minitab software version 17.1.0 (Minitab, LLC; State College, PA, USA). 3. Results The data presented in this research have a margin of error of 2.8%, with 95% confidence. In this study, the participants were sampled in a convenience sampling method, and 80% of participants were women. Therefore, the sample does not represent the Brazilian population. It could be suggested that the participants may reflect part of Brazilian consumers, especially women, and the results obtained may guide future studies with a representative sample of the Brazilian population. The higher number of responses from female participants (80.6%), as well as with children (63.3%), may be related to concerns about health and food, resulting in a high interest in the questionnaire. Furthermore, in relation to socioeconomic distribution, most of the participants, 87.4%, reside in the Southeast region, with an income between 1 and 3 (32.5%) or 4 and 6 (21.1%) minimum wages. These aspects, residence region and income, underlined that the results of the survey are most representative for the portion of the population in the region with the highest purchasing power and technology development in Brazil. In relation to the highest averages of correct answers, it could be observed that women participants and residents of the Northern regions were those who had the highest number of correct answers (Table 1). The higher education of the participants and the presence of children in the family showed a very weak correlation with the increase in correct answers in the questionnaire. However, none of the characteristics of participants presented a strong correlation with the knowledge about UPF, through Spearman correlation. As all p-values were greater than the significance level of 0.05, no correlation was statistically significant could be proposed. 3.1. Participants’ Understanding Regarding the Term UPF Most of the participants, 81.9%, declared to know the term UPF. Regardless of declaring whether they knew the term UPF or not, 78.2% of participants indicated that the best definition for UPF should be foods that have many processes performed on them by the food industry (Figure 1). 3.2. Checking Food Classified as UPF Figure 2 shows the distribution of participants’ answers regarding the classification as UPF or non-UPF. Among the different foods presented, soft drinks and packaged fruits showed a clear convergence of opinion for UPF (92.3%) and non-UPF (94.8%), respectively, as the NOVA classification proposal. The participants also classified infant formula as UPF (80%). For the other foods presented, such as baby food, loaf bread and potato chips with salt, it was observed that, in general, consumers are confused about the UPF classification, as 65.6%, 55.6% and 62.3% of the participants, respectively, classified them as UPFs (Figure 2). Thus, no clear evidence of classification was verified, as the numbers are close to half of the participants, not indicating a clear trend. According to NOVA classification, industrialized organic baby food, loaf bread and potato chips with salt are classified as UPF, UPF and processed, respectively. In the FGBP, potato chips with salt are also classified as processed [9]. Packaged fruits were classified as UPF by 5.2% of the participants (Figure 2). Table 2 presents the distributions of participants’ answers related to the affirmations presented in the questionnaire. Among the four affirmations presented (Table 2), only affirmations 2 and 4 had a significant percentage of correct answers (87.7% and 63.9%, respectively), showing that the consumers’ perceptions about UPFs are related to products with many ingredients in their formulation, with high levels of sugar, fat, salt and additives, in addition to low nutritional quality. On the other hand, the affirmations that presented examples of foods (1 and 3) showed significant errors, reinforcing the difficulty related to the classification of food as proposed by NOVA (Table 2). Yogurts and cereal bars are foods cited as examples of UPF by NOVA classification [9,16], and only 55.6% of the participants got the statement right. In relation to the affirmation “Foods pre-processed by the industry with frying or cooking, such as frozen potatoes and broccoli, for example, are UPF” (Table 2), 73.9% of the participants considered this affirmation as true. However, according to NOVA classification, those products are UPFs and minimally processed foods, respectively. 3.3. Knowledge and Perception of Participants about UPF Finally, the relationship between the participants who answered knowing the term UPF and the number of correct answers were, therefore, correlated by Pearson’s correlation, obtaining a medium level of correlation, 0.533 (p-value = 0.092) (Table 3). These results may indicate that even the participants believe to know UPF, in fact they do not have real knowledge about the subject. The classification difficulty was also reported by the participants of the present questionnaire when they were asked to explain if they agree or not with the definition of UPF. Among the participants who answered 80% or more of the questions presented in the questionnaire correctly, that is, who demonstrated that they actually know what UPF is, some statements requesting a more understandable definition mention that “to reach the greatest number of people, so that it is understandable and more easily absorbed, such a definition lacks clarity” and also “should be written in a more accessible/understandable way for the general population”. There were also participants who mentioned that “they are foods with low nutritional quality” and that the definition “is not related to the amount of processes involved in food preparation”, in addition to “uses the term processed in the name but the definition refers to others characteristics” and “is not related to the processing but to the composition of the food” with information such as “the quantity of ingredients is not related to the processing of the product” and also that “a food could have many ingredients and not be UPF”. Many participants mentioned not understanding the subject clearly, writing that “it is not clear” even after reading the definition. 3.4. Intention to Offer Food for Children When the participants were asked about the intention to offer certain foods to children, they chose only foods that were previously correctly classified (fruits and soft drinks), presenting results according to FGBC [27] (Figure 3). In other words, 91.9% of participants said they never offer a soft drink to a child under 2 years old, and 93.6% said they offer fruit without restriction. Even so, it is alarming to find that 1.0% of the participants answered that they never offer a fruit to a child under 2 years old; after all, fruits and vegetables are the basis of infant feeding, especially in the introduction of food [27,28,29,30]. A considerable number of participants considered never offering strawberry yogurt (36.5%), corn starch biscuits (33.6%) and tapioca flour biscuits (25.6%) to a child under 2 years old, which are classified as UPFs according to NOVA classification. This thought may be related to guidelines received by pediatricians. In relation to infant formula and industrialized baby food, most of the participants considered offering those products “sometimes”, 84.7% and 60.1%, respectively. The results showed that most of the participants that classified infant formula (80.7%) and baby food (53.8%) as UPF (Figure 2) [9], they also intended to offer these foods to children. Such acceptance may be related to the consumer’s perception that the nutritional contribution of food is important, and not how this food is processed [18]. On this subject, the participants declared that “I would not stop giving my son the (infant) formula because it was UPF”, “the (infant) formula, I had to offer because he has APLV (cow’s milk protein allergy)”, and “I think the issue of recommendation is a bit delicate, that infant formula should be avoided”. There were also manifestations questioning the different classification when “not considering UHT (ultra-high temperature) milk as UPF and considering infant formula”. Furthermore, an important point was raised when considering that “the fact of not having exclusive breastfeeding can already be considered a stressful factor for a puerperal woman and she feels bad knowing that she is feeding her child with UPF, I think it’s unnecessary”. 3.5. Relation between UPF Understanding and the Participants Qualification Considering the 10 questions presented related to the NOVA classification, the average of the correct answers for all valid participants was 6.2. The highest number of correct answers was observed among Gastronomy and Nutrition professionals. However, the correlation between the number of correct answers and the participants’ professions, through Spearman’s correlation, showed a very weak correlation value, 0.072 (p-value = 0.017). Therefore, regardless of the academic background, the participants’ knowledge about UPF is unsatisfactory, even for food or health professionals. Furthermore, even after reading the definition of ultra-processed products, the participants in the present research mentioned that it was confusing to understand and that the language is not “accessible to all audiences”. 4. Discussion The definitions of UPF found in the literature show variability [18,19] and can open different interpretations [19], in addition to demonstrating a lack of agreement between the studies related to NOVA [18]. The present study gives substantial contribution in the research area on the lack of understanding about the NOVA classification, especially in relation to UPF. It is important to underline that it was expected to find higher knowledge about the term UPF, since most participants had at least completed higher education (78.4%). It is also important to highlight that most of the participants reside in the richest region of Brazil (Southeast). This aspect could be related to the use of the snowball technique and the fact that the questionnaire was launched by residents of the Southeast [24]. A similar result, as reported in Section 3.1 (Figure 1), was found with consumers in Uruguay, where 91.2% of the participants declared to know the term UPF and described it as highly processed products [31]. In addition to Uruguay, consumers in Argentina (n = 120) and Ecuador (n = 61) also related the term UPF to processing (92.0%), and not to the list of ingredients (21.2%) [32]. According to Sadler [8], divergences about the “degree of processing” probably stem from singular perceptions and intents once most of the classifications were proposed by epidemiologists. Derbyshire [17] analyzed 50 foods that meet the definition of UPF by NOVA and found that they are classified as healthy according to the parameters of the Nutrient Profile Model in the United Kingdom. Furthermore, for the same foods, there was no correlation between the number of ingredients and nutritional quality when compared to the nutritional profile of European Regulation No. 1924/2006 [33]. As detailed in Section 3.2, some products are very difficult to be classified in the NOVA classification. Ares et al. [31] reported that breads, French fries, fried foods and packaged foods, in general, were not clearly classified and may depend on specific product characteristics such as ingredients and nutritional composition. Aguirre et al. [32] also considered the classification of bread as non-obvious, and only 3.9% of the participants considered bread as UPF. This difficulty was also reported for bread by nutrition students and professionals, and only 11% of them classified it correctly [34]. In the case of packaged foods, Ares et al. [31] showed that 4.0% of participants considered packaged foods as UPF, corroborating with this study. Similarly, frozen fruits and vegetables were also considered highly processed by low-income parents [35]. The disagreement about frozen vegetables underlined again the food classification difficulty by consumers when trying to use the NOVA classification. Furthermore, the definition of UPF has been updated over the years [36,37]. The FGBP published in 2014 explained that “the processing techniques used in the manufacture of UPF include pre-processing with frying or cooking” [9]. Thus, it can be understood that pre-processing with bleaching, in the case of frozen broccoli, results in considering this food as a UPF. Later, publications indicated that only pre-processing with frying must classify food as UPF [38]. The classification of frozen foods was also considered unclear by Ares et al. [31]. Another product that deserves special attention is infant formulas. There is no doubt that breast milk is the best option [9,39]; however, experts believe that the second-best option is infant formula [39]. In Brazil, the recommendation of the Food Guide for Children Under 2 years old, published in 2019, to offer cow’s milk when breastfeeding is not possible due to the classification of infant formulas as UPF [9,27] was questioned by the Brazilian Society of Pediatrics. Finally, in 2021 an abbreviated and revised version of the Food Guide for Children Under 2 years old was published, indicating that infant formula in Brazil can be used when necessary [40]. In addition to not recommending cow’s milk to infants before 12 months of age, due to difficulty in digestion, infant formulas are recommended as the safest option in the United States [39] and in Europe [41] when breastfeeding is not possible. It is also important to highlight the danger in the search for homemade infant formulas to replace industrialized infant formulas [18,41] by saying that homemade preparations are healthier than industrial ones. In this regard, the Food and Drug Administration warns of profoundly serious problems when preparing and offering homemade infant formulas to babies, the consequences of which range from severe nutritional imbalances to foodborne illnesses, which can be fatal [42]. Unfortunately, baby food was intended to be offered without restriction for only 11.1% of the participants, less than strawberry yogurt (13.0%), corn starch (12.7%) and tapioca flour biscuits (16.7%). Most industrialized baby foods sold in Brazil do not contain salt in their composition, only vegetables, meats, legumes, cereals and fruits, among others [43,44,45]. The FGBC recommends that children’s meals should have one food from each group: (1) beans; (2) cereals or roots or tubers; (3) meat or eggs; (4) legumes and (5) vegetables [29]. Following the recommendation of the FGBC [27], if an industrialized baby food has rice, beans, Basella alba, pumpkin and egg in its formulation, sauteed with oil, onion and garlic, it is already classified as UPF because it has more than five ingredients, even without any additives such as dyes, preservatives, antioxidants, flavorings, flavor enhancers and sweeteners, among others. Commercial baby food appears to be equally safe and healthy as homemade baby food [46]. Brembeck and Fuentes [47] studied 19 mothers in Sweden and concluded that there is no contradiction between care and convenience, as good motherhood is no longer unilaterally associated with home cooking. These mothers reported that convenience is when the husband takes on the responsibility of cooking, having good baby food on hand, having a child who feeds himself using cutlery or having the whole family eat the same food at the same time [47]. For mothers, convenience food is not necessarily processed food. In addition, there are few types of food available in the Brazilian market for children in early childhood. The supply of foods not suitable for age is a concern [48,49] and not necessarily the quality of baby food, as these foods follow strict regulations. The suspicion mentioned in Section 3.4 about guidelines received by pediatricians was also observed in a survey carried out in Uruguay that investigated whether the 212 pediatricians’ recommendations to parents during the introduction of food were in accordance with current guidelines. This study showed that UPFs considered less obvious and judged to be frequently consumed by children, such as yogurt, dairy desserts and biscuits, were not mentioned by pediatricians when listing foods that must be avoided [50]. Additionally, a survey conducted in Italy with 509 children and adolescents showed that sweet biscuits (13.2%) and processed beverages (9.3%) are among the main UPFs consumed [51]. It is also worrying that 34.3% of the participants considered offering processed juice to a child under 2 years old, knowing that processed juices are among the products with the highest levels of added sugar [52]. Following the difficulties and confusing about NOVA classification, the intention to correlate knowledge about UPF with the participants’ professional training (Section 3.5) has already been addressed by recent research showing the lack of credibility of data generated by researchers and the possibility of incorrect guidance to the population. Studies carried out with students and nutrition professionals in a Brazilian higher education institution in 2015 (n = 72) [53] and 2016 (n = 69) [34] showed that these students and professionals had unsatisfactory knowledge about the NOVA classification, concluding as a critical point, as it should be easily understood by everyone, regardless of their background. Similar results were found in France [54], with 150 specialists in human nutrition and/or food technology. In this regard, NOVA classification has been questioned by several studies due to its complexity [30,32], inconsistencies [54,55] and broad and ambiguous definitions [8,17,19]. Although classification systems have been used and considered in public health policies, this study explored that its implementation by national or international organizations does not, therefore, mean that no additional studies or criticism is needed. In general, it is observed that there is no clear consensus in classifications about which characteristics make a food more or less processed. From the nutritional point of view, some studies have reported that the higher levels of sugar intake in the diet are associated with homemade products such as tea and coffee [52]. Additionally, Derbyshire [17] showed that many foods that are classified as UPF by NOVA are not considered “less healthy” according to the United Kingdom nutrient profile model. These types of approaches allow reflecting on targeted public health strategies, suitable for different groups of people. All of this underlined that the use of claims such as “homemade”, among other marketing tools, has been growing in products that could be less healthful than industrialized ones [56]. From the point of view of technology and food science, the industrial process must always be improved, aiming to maximize the positive effects and minimize the negative ones, which in turn can be much better measured and controlled in the food industry than at the domestic level. Focusing only on the promotion of cuisine negates the need for the food safety, food security, convenience and practicality that is necessary for the evolution of contemporary social systems. Re-analyzing our understanding about processed foods and their relationship with the social needs of contemporary life represents a path to be built together by food engineers, nutritionists and epidemiologists in order to avoid biased traps that indicate a faster but more dangerous path. 5. Conclusions For the first time, the comprehension about UPF definition was evaluated with the Brazilian population, although it has been used in Brazil over the last 8 years in the Food Guide for the Brazilian Population. The term UPF is still confusing for most participants. Furthermore, considering the socioeconomic characteristic of participants, it could be concluded that the definition of UPF is not clear for those who had at least completed higher education or reside in regions with higher levels of development. This confusion seems to be related to the definitions associated with the term, as this is not logical and therefore not easily understandable and may induce the consumer to make mistakes when making a purchase decision. Consumers are avoiding some foods considered as UPF, even products which could contribute to improved health, which in turn could be related to the increase in some food phobia. All of this underlined the risk of consuming UPF to consumer health. Healthier choices could ensue with the development of new products, however, the manner in which processed foods have been classified does not motivate innovation in the food industry. A food classified as UPF, even if reformulated for health aspects, would still be classified as UPF simply because it was industrially produced. Care is needed to balance naïve and heuristic messages with scientific rigor and avoid unwanted consequences. All parties interested in adequate food should improve the classification system and, consequently, the understanding of the consumer; after all, innovation with healthy, sustainable, safe and convenient foods could greatly benefit the population. Acknowledgments We would like to thank two anonymous reviewers for their valuable contributions. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods11091359/s1, Table S1: Quiz Summary. Click here for additional data file. Author Contributions Conceptualization, J.S.-S., J.M.V.P. and F.M.V.; methodology, J.S.-S. and F.M.V.; software, J.M.V.P.; validation, J.M.V.P.; formal analysis, J.S.-S. and F.M.V.; investigation, M.B.N.S. and L.S.A.; resources, M.B.N.S. and L.S.A.; data curation, J.S.-S. and F.M.V.; writing—original draft preparation, J.S.-S.; writing—review and editing, J.S.-S., R.A.C. and F.M.V.; visualization, F.M.V.; supervision, F.M.V.; project administration, J.S.-S. and F.M.V.; funding acquisition, F.M.V. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of UNIVERSITY OF SÃO PAULO (protocol code 36600620.9.0000.5422 on 28 October 2020. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data is contained within the article and Supplementary Material. Conflicts of Interest The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Distribution of answers from valid participants (n = 939) to the question “Do you know what is an ultra-processed food?”, with further indication of the best definition for ultra-processed food (UPF) by the participants. Figure 2 Distribution of food classification presented to research participants as UPFs (blue) or not (red). Figure 3 Distribution of intention to offer food to children under two years old. foods-11-01359-t001_Table 1 Table 1 Socioeconomic and characterization of participants. Characteristics Absolute Frequency Relative Frequency Average Correct Answers Spearman Correlation p-Value Gender −0.072 0.031    Female 756 80.6% 6.6    Male 181 19.2% 6.4    Other 2 0.2% 4.0 Age 0.000 0.994    Under 18 0 0.0% -    18 to 24 178 19.0% 6.5    25 to 34 367 39.1% 6.6    35 to 44 282 30.0% 6.6    45 to 54 76 8.1% 6.1    55 to 64 27 2.9% 7.1    >65 9 1.0% 6.1 Children in the family 0.018 0.583    No child 345 36.7% 6.6    With child (<17 years old) 594 63.3% 6.8 Education 0.011 0.745    Complete/incomplete elementary school 40 4.3% 6.5    Complete high school 163 17.3% 6.5    Complete higher education 736 78.4% 6.7 Income −0.076 0.021    Without own income (now) 112 11.9% 6.6    Below minimum wage 34 3.6% 6.2    From 1 to 3 minimum wages 305 32.5% 6.8    From 4 to 6 minimum wages 198 21.1% 6.6    From 7 to 9 minimum wages 109 11.6% 6.5    Above 10 minimum wages 139 14.8% 6.3    I prefer not to inform 42 4.5% 6.5 Region of residence −0.042 0.208    North 27 2.8% 7.8    Northeast 20 2.2% 6.2    Southeast 820 87.4% 6.5    Midwest 14 1.5% 6.5    South 58 6.1% 6.1 foods-11-01359-t002_Table 2 Table 2 Percentage of correct answers and errors related to the affirmations presented in the questionnaire. Affirmation True (T) or False (F) Correct Error Examples of UPF are: yogurts and cereal bars. (1) T 55.6% 44.4% UPFs are nutritionally rich and low in calories, sugar, fat, salt and chemical additives, with enhanced flavor and longer shelf life. (2) F 87.7% 12.3% Food pre-processed by the industry with frying or cooking, such as frozen potatoes and broccoli, for example, are UPFs. (3) F 26.1% 73.9% Products with industrial formulations consisting of five or more ingredients are UPFs. (4) T 63.9% 36.1% foods-11-01359-t003_Table 3 Table 3 Relation between participants who answered knowing or not ultra-processed foods (UPFs) and the number of correct answers presented (identification of UPFs by images and statements to identify true or false). Do You Know What Is an UPF? Number of Correct Answers in the Questionnaire Total Yes No (Images and Affirmations) 1 0 1 1 5 0 2 5 23 2 3 25 41 21 4 62 114 30 5 144 159 36 6 195 174 31 7 205 170 35 8 205 73 12 9 85 9 3 10 11 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Bezerra I.N. Vasconcelos T.M. Cavalcante J.B. Yokoo E.M. Pereira R.A. Sichieri R. Evolution of Out-of-Home Food Consumption in Brazil in 2008–2009 and 2017–2018 Rev. Saude Pública 2021 55 1 11 10.11606/s1518-8787.2021055003221 2. Rodrigues R.M. Souza A.D. Bezerra I.N. Pereira R.A. Yokoo E.M. Sichieri R. Most Consumed Foods in Brazil: Evolution between 2008–2009 and 2017–2018 Rev. Saúde Pública 2021 55 4s 10.11606/s1518-8787.2021055003406 34852162 3. Soares M.M. Juvanhol L.L. Ribeiro S.A.V. Franceschini S.D.C.C. Araújo R.M.A. Prevalence of Processed and Ultra-Processed Food Intake in Brazilian Children (6–24 Months) Is Associated with Maternal Consumption and Breastfeeding Practices J. Food Sci. Nutr. 2021 72 978 988 10.1080/09637486.2021.1885016 33645412 4. Dutra-de-Oliveira J.E. Marchini J.S. Ciências Nutricionais Savier São Paulo, Brazil 1998 5. Lessa A.D.C. Fonseca L.B. Nobre L.N. Assis A.M.D.O. Lessa A.D.C. Fonseca L.B. Nobre L.N. Assis A.M.D.O. Dietary Patterns of Children during the First Year of Life: A Cohort Study—Dietary Patterns of Children Food Nutr. Sci. 2017 8 1001 1011 10.4236/FNS.2017.811072 6. McCloat A. Mooney E. Hollywood L.E. Have Irish Parents Put Cooking on the Back Burner? An Island of Ireland Study of the Food Skills, Cooking Confidence and Practices of Parents Br. Food J. 2017 119 992 1002 10.1108/BFJ-09-2016-0440 7. Navarro P. Mehegan J. Murrin C.M. Kelleher C.C. Phillips C.M. Adherence to the Healthy Eating Index-2015 across Generations Is Associated with Birth Outcomes and Weight Status at Age 5 in the Lifeways Cross-Generation Cohort Study Nutrients 2019 11 928 10.3390/nu11040928 8. Sadler C.R. Grassby T. Hart K. Raats M. Sokolović M. Timotijevic L. Trends in Food Science and Technology Elsevier Ltd. Amsterdam, The Netherlands 2021 149 162 9. Ministério da Saúde Guia Alimentar Para a População Brasileira 2nd ed. Ministério da Saúde Brasília, Brazil 2014 9788561091699 10. Ministry of Public Health of Ecuador Documento técnico de Las Guías Alimentarias Basadas En Alimentos (GABA) Del Ecuador [Technical Document of the Food Based Food Guidelines (GABA) of Ecuador] Available online: https://lodijeron.files.wordpress.com/2018/10/guias-alimentarias-ecuador-2018.pdf (accessed on 28 June 2021) 11. Serrano L. Luis M. Guías Alimentarias Para La Población Peruana Instituto Nacional de Salud Bogotá, Colombia 2019 55 12. Ministerio de Desarrollo Social Guía Alimentaria Para La Población Uruguaya | Ministerio de Desarrollo Social Available online: https://www.gub.uy/ministerio-desarrollo-social/comunicacion/publicaciones/guia-alimentaria-para-la-poblacion-uruguaya (accessed on 28 June 2021) 13. Flemish Institute of Healthy Living Voedingsdriehoek|Gezond Leven Available online: https://www.gezondleven.be/themas/voeding/voedingsdriehoek (accessed on 28 June 2021) 14. HCSP Pour Une Politique Nutritionnelle de Santé Publique En France. PNNS 2017–2021 Available online: https://www.hcsp.fr/explore.cgi/avisrapportsdomaine?clefr=657 (accessed on 28 June 2021) 15. FAO Food-Based Dietary Guidelines | Food and Agriculture Organization of United Nations Available online: http://www.fao.org/nutrition/education/food-dietary-guidelines/en/ (accessed on 28 June 2021) 16. Monteiro C.A. Cannon G. Levy R. Moubarac J.-C. Jaime P. Paula Martins A. Canella D. Louzada M. Camila Ricardo D. Calixto G. The Food System World Nutrition Peacehaven, UK 2016 Volume 7 17. Derbyshire E. Trends in Food Science and Technology Elsevier Ltd. Amsterdam, The Netherlands 2019 98 104 18. Jones J.M. Food Processing: Criteria for Dietary Guidance and Public Health? Proc. Nutr. Soc. 2019 78 4 18 10.1017/S0029665118002513 30249309 19. Gibney M. Ultra-Processed Foods: Definitions and Policy Issues Curr. Dev. Nutr. 2019 3 nzy077 10.1093/cdn/nzy077 30820487 20. Gibney M.J. Forde C.G. Mullally D. Gibney E.R. Ultra-Processed Foods in Human Health: A Critical Appraisal Am. J. Clin. Nutr. 2017 106 717 724 10.3945/ajcn.117.160440 28793996 21. Poti J.M. Braga B. Qin B. Ultra-Processed Food Intake and Obesity: What Really Matters for Health-Processing or Nutrient Content? Curr. Obes. Rep. 2017 6 420 431 10.1007/s13679-017-0285-4 29071481 22. National Center for Health Statistics Health, United States, 2009 with Special Feature on Medical Technology National Center for Health Statistics Hyattsville, MD, USA 2009 23. Atkinson R. Flint J. Accessing Hidden and Hard-to-Reach Populations: Snowball Research Strategies Social Research Update Department of Sociology, University of Surrey Guildford, UK 2001 Volume 33 24. Fiori I.C. Consiglio Kasemodel M.G. Makishi F. Nunes R. Valentin D. Favaro-Trindade C.S. Silva V.L. Brazilian Consumers’ Understanding and Recognition Ability on Organic Processed Food J. Food Prod. Mark. 2019 25 829 848 10.1080/10454446.2019.1683784 25. IBGE IBGE | Projeção Da População Available online: https://www.ibge.gov.br/apps/populacao/projecao/box_popclock.php (accessed on 27 May 2021) 26. Granato D. de Araújo Calado V.Ô.M. Jarvis B. Observations on the Use of Statistical Methods in Food Science and Technology Food Res. Int. 2014 55 137 149 10.1016/j.foodres.2013.10.024 27. Ministério da Saúde Guia Alimentar Para Crianças Menores De 2 AnosI 1st ed. Departamento de Promoção da Saúde, Ministério da Saúde Brasília, Brazil 2019 8533403445 28. Lopes W.C. Marques F.K.S. de Oliveira C.F. Rodrigues J.A. Silveira M.F. Caldeira A.P. de Pinho L. Infant Feeding in the First Two Years of Life Rev. Paul. Pediatr. 2018 36 164 170 10.1590/1984-0462/;2018;36;2;00004 29947724 29. Savage J.S. Fisher J.O. Birch L.L. Parental Influence on Eating Behavior: Conception to Adolescence J. Law Med. Ethics 2007 35 22 34 10.1111/j.1748-720X.2007.00111.x 17341215 30. Vidal L. Brunet G. Bove I. Girona A. Fuletti D. Ares G. Parents’ Mental Associations with Ultra-Processed Products for Their Infant Children: Insights to Improve Complementary Feeding Practices Food Qual. Prefer. 2021 94 104335 10.1016/j.foodqual.2021.104335 31. Ares G. Vidal L. Allegue G. Giménez A. Bandeira E. Moratorio X. Molina V. Curutchet M.R. Consumers’ Conceptualization of Ultra-Processed Foods Appetite 2016 105 611 617 10.1016/j.appet.2016.06.028 27349706 32. Aguirre A. Borneo M.T. El Khori S. Borneo R. Exploring the Understanding of the Term “Ultra-Processed Foods” by Young Consumers Food Res. Int. 2019 115 535 540 10.1016/j.foodres.2018.09.059 30599975 33. European Union Regulation (EC) No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on Nutrition and Health Claims Made on Foods Available online: https://eur-lex.europa.eu/legal-content/PT/TXT/PDF/?uri=CELEX:32006R1924&from=GA (accessed on 14 June 2021) 34. Menegassi B. de Almeida J.B. Olimpio M.Y.M. Brunharo M.S.M. Langa F.R. The New Food Classification: Theory, Practice and Difficult Cienc. E Saude Coletiva 2018 23 4165 4176 10.1590/1413-812320182312.30872016 35. Bleiweiss-Sande R. Goldberg J. Evans E.W. Chui K. Sacheck J. Perceptions of Processed Foods Among Low-Income and Immigrant Parents Health Educ. Behav. 2019 47 101 110 10.1177/1090198119885419 31661981 36. Araújo C. Ribeiro K.D. Padrão P. Moreira P. Industrialized Foods in Early Infancy: A Growing Need of Nutritional Research Porto Biomed. J. 2019 4 e47 10.1097/j.pbj.0000000000000047 31930180 37. Angelovičová M. Zeleňáková L. Zajác P. Čapla J. The NOVA System and Ultra-Processed Foods in Relation to Consumer Decision-Making in Foods Choice Potravin. Slovak J. Food Sci. 2020 14 914 920 10.5219/1358 38. Monteiro C.A. Cannon G. Levy R.B. Moubarac J.-C. Louzada M.L. Rauber F. Khandpur N. Cediel G. Neri D. Martinez-Steele E. Commentary Ultra-Processed Foods: What They Are and How to Identify Them Public Health Nutr. 2019 22 936 941 10.1017/S1368980018003762 30744710 39. AAP Why Formula Instead of Cow’s Milk?-HealthyChildren.Org Available online: https://www.healthychildren.org/english/ages-stages/baby/formula-feeding/pages/why-formula-instead-of-cows-milk.aspx?_ga=2.205173207.631741452.1625228397-1125699201.1625228397&_gl=1*2rqndc*_ga*mteynty5otiwms4xnji1mji4mzk3*_ga_fd9d3xzvqq*mtyyntiyodq0mi4xlj (accessed on 1 July 2021) 40. Ministério da Saúde Guia Alimentar Para Crianças Brasileiras Menores De 2 Anos-Versão Resumida Ministério da Saúde Brasília, Brazil 2021 41. Livsmedelsverket Good Food for Babies—Swedish Food Agency Available online: https://www.livsmedelsverket.se/en/food-habits-health-and-environment/dietary-guidelines/babies-and-children/spadbarn (accessed on 6 July 2021) 42. FDA FDA Advises Parents and Caregivers to Not Make or Feed Homemade Infant Formula to Infants | FDA Available online: https://www.fda.gov/food/alerts-advisories-safety-information/fda-advises-parents-and-caregivers-not-make-or-feed-homemade-infant-formula-infants (accessed on 1 July 2021) 43. Empório da Papinha Empório Da Papinha-Papinhas e Comidinhas Orgânicas e Saborosas Para Toda a Infância Available online: https://emporiodapapinha.com.br/ (accessed on 1 July 2021) 44. Gourmetzinho Institucional–Gourmetzinho Available online: https://www.gourmetzinho.com.br/institucional/sobre (accessed on 1 July 2021) 45. Nestlé Nestlé NaturNes Available online: https://www.nestle.com.br/marcas/nestle-naturnes (accessed on 1 July 2021) 46. Fuentes M. Brembeck H. Best for Baby? Framing Weaning Practice and Motherhood in Web-Mediated Marketing Consum. Mark. Cult. 2016 20 153 175 10.1080/10253866.2016.1205493 47. Brembeck H. Fuentes M. Convenient Food for Baby: A Study of Weaning as a Social Practice Food Cult. Soc. 2017 20 569 586 10.1080/15528014.2017.1357950 48. Cainelli E.C. Gondinho B.V.C. Palacio D.D.C. de Oliveira D.B. Reis R.A. Cortellazzi K.L. Guerra L.M. Cavalcante D.d.B. Pereira A.C. Bulgareli J.V. Ultra-Processed Foods Consumption among Children and Associated Socioeconomic and Demographic Factors Einstein (São Paulo) 2021 19 1 8 10.31744/einstein_journal/2021AO5554 34495084 49. Longo-Silva G. Silveira J.A.C. Menezes R.C.E.D. Toloni M.H.D.A. Idade de Introdução de Alimentos Ultraprocessados Entre Pré-Escolares Frequentadores de Centros de Educação Infantil J. Pediatr. 2017 93 508 516 10.1016/j.jped.2016.11.015 50. Vidal L. Bove I. Brunet G. Girona A. Alcaire F. Antúnez L. Ares G. Are the Recommendations of Pediatricians about Complementary Feeding Aligned with Current Guidelines in Uruguay? Public Health Nutr. 2021 24 641 650 10.1017/S1368980020005352 51. Ruggiero E. Esposito S. Costanzo S. di Castelnuovo A. Cerletti C. Donati M.B. de Gaetano G. Iacoviello L. Bonaccio M. Ultra-Processed Food Consumption and Its Correlates among Italian Children, Adolescents and Adults from the INHES Cohort Study Public Health Nutr. 2021 24 6258 6271 10.1017/S1368980021002767 34289922 52. Bailey R.L. Fulgoni V.L. Cowan A.E. Gaine P.C. Sources of Added Sugars in Young Children, Adolescents, and Adults with Low and High Intakes of Added Sugars Nutrients 2018 10 102 10.3390/nu10010102 53. Menegassi B. Cardozo C.M.L. Langa F.R. Moreira C.C. Luz V.G. Classificação de Alimentos NOVA: Comparação Do Conhecimento de Estudantes Ingressantes e Concluintes de Um Curso de Nutrição Demetra Aliment. Nutr. Saúde 2020 15 e48711 10.12957/demetra.2020.48711 54. Braesco V. Souchon I. Sauvant P. Haurogné T. Maillot M. Féart C. Darmon N. Ultra-Processed Foods: How Functional Is the NOVA System? Eur. J. Clin. Nutr. 2022 1 9 10.1038/s41430-022-01099-1 33199852 55. Petrus R.R. do Amaral Sobral P.J. Tadini C.C. Gonçalves C.B. The NOVA Classification System: A Critical Perspective in Food Science Trends Food Sci. Technol. 2021 116 603 608 10.1016/j.tifs.2021.08.010 56. Kanematsu L.R.A. Müller J. Scapin T. Fabri R.K. Colussi C.F. Bernardo G.L. Fernandes A.C. Pacheco Da Costa Proenca R. Uggioni P.L. Do Foods Products Labeled “Home-Made” Contain Fewer Additives? A Brazilian Survey J. Food Prod. Mark. 2020 26 486 498 10.1080/10454446.2020.1811185

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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092116 cancers-14-02116 Correction Correction: Bishayee et al. Lotus (Nelumbo nucifera Gaertn.) and Its Bioactive Phytocompounds: A Tribute to Cancer Prevention and Intervention. Cancers 2022, 14, 529 https://orcid.org/0000-0001-9159-960X Bishayee Anupam 1* Patel Palak A. 1 https://orcid.org/0000-0003-4290-3251 Sharma Priya 1 Thoutireddy Shivani 1 https://orcid.org/0000-0001-6213-1207 Das Niranjan 2 1 College of Osteopathic Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, FL 34211, USA; ppatel24886@med.lecom.edu (P.A.P.); PSharma44656@med.lecom.edu (P.S.); SThoutired89922@med.lecom.edu (S.T.) 2 Department of Chemistry, Iswar Chandra Vidyasagar College, Belonia 799155, Tripura, India; ndnsmu@gmail.com * Correspondence: abishayee@lecom.edu or abishayee@gmail.com 24 4 2022 5 2022 24 4 2022 14 9 211606 4 2022 06 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). ==== Body pmcTable Legend In the original article, there was a mistake in the legend for Table 2 [1]. In the table legend (page 24), “in vivo” appears incorrectly which should be replaced by “in vitro”. The correct legend appears below. Table 2. Potential anticancer effects and mechanisms of action of N. nucifera-derived constituents based on in vitro studies. Error in Table In the original article, there were mistakes in Table 3 as published. In the table legend (page 32), “in vitro” appears incorrectly which should be replaced by “in vivo”. Additionally, the content of the table is same as Table 2, which should be replaced by a correct table. The corrected Table 3 along with the title appear below. cancers-14-02116-t003_Table 3 Table 3 Potential anticancer effects and mechanisms of action of N. nucifera-derived constituents based on in vivo studies. Materials Tested Animal Tumor Models Anticancer Effects Mechanisms Dose (Route) Duration References Breast cancer Flavonoid-rich leaf extract BALB/c athymic nude mice injected with MCF-7 cells Reduced tumor volume and weight ↓HER2; p-HER2; ↓Fas 0.5 & 1% (diet) 28 days Yang et al., 2011 [79] Aqueous leaf extract MDA-MB-231 cells injected in female C57BL/6 nude mice Inhibited tumor growth Not reported 0.5–2 % (s.c.) 14 days Chang et al., 2016 [80] Liensinine + doxorubicin Female nude mice injected with MDA-MB-231 cells Reduced tumor growth ↑Apoptosis; ↑cleaved caspase-3; ↓autophagy/mitophagy; ↑auto-phagosome /mitophagosome; ↑colocalization of DNM1L and TOMM20 60 mg/kg (i.p.); 2 mg/kg (i.p.) 30 days Zhou et al., 2015 [90] Colon cancer Nuciferine CT29 cells subcutaneously implanted in nude mice Reduced tumor weight Not reported 9.5 mg/kg (i.p.) 3 times a week for 3 weeks Qi et al., 2016 [96] Liensinine HT29 cells injected in female BALB/c nude mice Suppressed colorectal tumorigenesis, reduced tumor size ↓Ki-67 30 mg/kg (oral) Every other day for 15 days Wang et al., 2018 [97] Eye cancer Neferine WERI-Rb-1 cells injected in female athymic nude mice Reduced tumor volume and weight ↓Ki-67; ↓VEGF; ↓SOD; ↑MDA 0.5–2 mg/kg (i.p) Every 3 days for 30 days Wang et al., 2020 [100] Gallbladder cancer Liensinine NOZ cells injected in BALB/c nude mice Reduced tumor volume and weight ↓Ki-67 2 mg/kg (i.p) Every 2 days Shen et al., 2019 [101] Gastric cancer Liensinine from seeds SGC7901 cells injected in BALB/c homozygous (nu/nu) nude mice Reduced tumor size ↓Ki-67 10 µM (i.p.) Every 2 days for a month Yang et al., 2019 [106] Head and neck cancers Neferine CAL27 cells injected in male BALB/c nude mice Reduced tumor volume ↑Apoptosis; ↑autophagy, ↑cleaved caspase-3, ↑cleaved PARP1, ↑LC3; ↑p62 10 mg/kg (i.p) Not reported Zhu et al., 2021 [107] Liver cancer Water-soluble polysaccharides from seeds H22 cells injected in female Kunming mice Reduced tumor weight ↑TNF-ɑ; ↑IL-2; ↑SOD; ↓MDA 50–200 mg/kg (oral) 14 days Zheng et al., 2016 [102] Leaf extract DEN fed male Sprague-Dawley rats Reduced tumor size ↓AST; ↓ALT; ↓albumin; ↓total triglyceride; ↓total cholesterol; ↓lipid peroxidation; ↑GSH; ↑GSHPx; ↑SOD; ↑CAT; ↑GST; ↓Rac1; ↓PKCɑ; ↓TNF-ɑ; ↓IL-6 0.5–2.0% (p.o.) 12 weeks Horng et al., 2017 [119] Leaf extract 2-AAF-induced male Wistar rats Inhibited hepatic fibrosis and hepatocarcinogenesis ↓Triglycerides; ↓total cholesterol; ↓AFP; ↓IL-6; ↓TNF-ɑ; ↓AST; ↓ALT; ↓γGT; ↓GST-Pi; ↓lipid peroxidation; ↓8-OHdG; ↑Nrf2; ↑CAT; ↑GPx; ↑SOD-1 0.5–2% in the diet (p.o.) 6 months Yang et al., 2019 [120] Neferine+oxaliplatin HepG2 and Bel-7402 cells injected in male BALB/c mice Increased tumor volume reducing the effect of oxaliplatin ↑E-cadherin; ↓Vimentin; ↓Ki-67; 20 mg/kg/d (i.p.) 3 weeks Deng et al., 2017 [116] Isoliensinine Huh-7 cells injected in male athymic nude mice and H22 cells injected in Kunming mice Reduced tumor volume ↑caspase-3; ↓Bcl-2; ↓Bcl-xL; ↓MMP-9; ↓p65 phosphorylation 3 and 10 mg/kg/d (i.p. and gavage) 10 days; 3 weeks Shu et al., 2015 [117] Isoliensinine Huh-7 cells transfectants injected in male athymic nude mice Reduced tumor growth ↑Caspase-3 activity 10 mg/kg/d (gavage) 20 days Shu et al., 2016 [118] Lung cancer Leaf extract and leaf polyphenol extract 4T-1 metastatic tumor in the lung of BALB/c mice Reduced metastasis and tumor weight ↓PKCɑ activation 0.25, 1% (p.o.) 19 days Wu et al., 2017 [81] Nuciferine A549 cells injected in BALB/c mice Reduced tumor size and weight ↑Apoptosis; ↓Bcl-2; ↑Bax; ↓Wnt/β-catenin; ↑Axin 50 mg/kg (i.p.) 3 times a week for 20 days Liu et al., 2015 [126] Neferine DEN-induced lung carcinogenesis in albino male Wistar rats Suppressed tumor growth ↓ROS; ↓lipid peroxidation; ↓protein carbonyl; ↑GSH; ↑SOD; ↑GPx; ↑GST; ↑CAT; ↓glycoprotein components; ↑ATPase; ↑p53; ↑Bax; ↑caspase-9; ↑caspase-3; ↓Bcl-2; ↓COX-2; ↓NF-κB; ↓CYP2E1; ↓VEGF; ↓PI3K; ↓Akt; ↓mTOR 10–20 mg/kg (oral) 20 alternate days Sivalingam et al., 2019 [127] Neural cancer Nuciferine SY5Y cells subcutaneously implanted in nude mice Reduced tumor weight Not reported 9.5 mg/kg (i.p.) 3 times a week for 3 weeks Qi et al., 2016 [96] Nuciferine U251 cells subcutaneously inoculated in BALB/c nude mice Suppressed tumor weight and size ↓Ki-67; ↓CDC2; ↓Bcl-2; ↓HIF1A; ↓N-cadherin; ↓VEGFA 15 mg/kg (i.p.) Once a day for 2 weeks Li et al., 2019 [130] Skin cancer Procyanidin extract from seedpod B16 cells inoculated into syngeneic C57BL/6 J mice Suppressed tumor volume and weight ↓lipid peroxidation levels; ↑SOD; ↑CAT; ↑GSPx; ↑spleen and thymus index 60–120 mg/kg (i.g.) Every 2–3 days for 15 days Duan et al., 2010 [137] Leaf extract UV-radiation exposed female guinea pigs Reversed UVB-induced epidermal hyperplasia and hyperpigmentation ↓MITF; ↓tyrosinase; ↓TRP-1; ↓PKA; ↓ERK; ↓melanin 1–2% (topical) 2 weeks Lai et al., 2020 [138] 7-Hydroxy-dehydronuciferine A375.S2 cells injected in BALB/c nu/nu female mice Reduced tumor volume Not reported 20 mg/kg (i.p.) Every 7 days for 28 days Wu et al., 2015 [139] The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs Reference 1. Bishayee A. Patel P.A. Sharma P. Thoutireddy S. Das N. Lotus (Nelumbo nucifera Gaertn.) and Its Bioactive Phytocompounds: A Tribute to Cancer Prevention and Intervention Cancers 2022 14 529 10.3390/cancers14030529 35158798

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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092296 cancers-14-02296 Review Glioma Stem Cells in Pediatric High-Grade Gliomas: From Current Knowledge to Future Perspectives Da-Veiga Marc-Antoine 1 https://orcid.org/0000-0003-1754-6002 Rogister Bernard 12 https://orcid.org/0000-0002-7789-0801 Lombard Arnaud 13 Neirinckx Virginie 1† Piette Caroline 14*† Wong David Academic Editor 1 Laboratory of Nervous System Disorders and Therapy, GIGA Institute, University of Liège, 4000 Liège, Belgium; madaveiga@uliege.be (M.-A.D.-V.); bernard.rogister@uliege.be (B.R.); alombard@chuliege.be (A.L.); virginie.neirinckx@uliege.be (V.N.) 2 Department of Neurology, CHU of Liège, 4000 Liège, Belgium 3 Department of Neurosurgery, CHU of Liège, 4000 Liège, Belgium 4 Department of Pediatrics, Division of Hematology-Oncology, CHU Liège, 4000 Liège, Belgium * Correspondence: caroline.piette@chuliege.be † These authors contributed equally to this work. 04 5 2022 5 2022 14 9 229621 2 2022 02 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary Pediatric high-grade glioma (pHGG) has a dismal prognosis in which the younger the patient, the more restricted the treatments are, in regard to the incurred risks. Current therapies destroy many tumor cells but fail to target the highly malignant glioma stem cells (GSCs) that adapt quickly to give rise to recurring, treatment-resistant cancers. Despite a lack of consensus around an efficient detection, GSCs are well described in adult brain tumors but remain poorly investigated in pediatric cases, mostly due to their rarity. An improved knowledge about GSC roles in pediatric tumors would provide a key leverage towards the elimination of this sub-population, based on targeted treatments. The aim of this review is to sum up the state of art about GSCs in pHGG. Abstract In children, high-grade gliomas (HGG) and diffuse midline gliomas (DMG) account for a high proportion of death due to cancer. Glioma stem cells (GSCs) are tumor cells in a specific state defined by a tumor-initiating capacity following serial transplantation, self-renewal, and an ability to recapitulate tumor heterogeneity. Their presence was demonstrated several decades ago in adult glioblastoma (GBM), and more recently in pediatric HGG and DMG. In adults, we and others have previously suggested that GSCs nest into the subventricular zone (SVZ), a neurogenic niche, where, among others, they find shelter from therapy. Both bench and bedside evidence strongly indicate a role for the GSCs and the SVZ in GBM progression, fostering the development of innovative targeting treatments. Such new therapeutic approaches are of particular interest in infants, in whom standard therapies are often limited due to the risk of late effects. The aim of this review is to describe current knowledge about GSCs in pediatric HGG and DMG, i.e., their characterization, the models that apply to their development and maintenance, the specific signaling pathways that may underlie their activity, and their specific interactions with neurogenic niches. Finally, we will discuss the clinical relevance of these observations and the therapeutic advantages of targeting the SVZ and/or the GSCs in infants. pediatric high-grade glioma diffuse midline glioma glioblastoma diffuse intrinsic pontine glioma cancer stem cell glioma stem cell glioma initiating cell subventricular zone TELEVIE-FNRSEUROMA fundsM.-A.D.-V. is a Ph.D. student funded by the TELEVIE-FNRS and the EUROMA funds (Fondation Léon Frédéricq, University of Liège); AL received the Clinical Researcher of the FNRS-Belgium; BR research group is supported by the FNRS, the TELEVIE, the University of Liège and the Fondation Léon Frédéricq. ==== Body pmc1. Pediatric High-Grade Gliomas: From Histologic to Histomolecular Classification Brain and other central nervous system (CNS) tumors represent the most frequent solid malignant neoplasms in people aged 0–19 years [1]. Among them, gliomas form the most frequent subgroup and account for 51.6% and 31.1% of CNS tumors in children (0–14 years) and adolescents (15–19 years), respectively [1]. As a group, high-grade gliomas (HGG) constitute the most common pediatric malignant tumor of the CNS, with an incidence of 0.87 per 100,000 children in the United States [2]. For years, pediatric gliomas were grouped with their adult counterparts, despite known differences in various aspects. More recently, however, the identification of specific genetic abnormalities underlying pediatric gliomas has progressively allowed the recognition of prognostically and biologically distinct entities primarily occurring in children (but sometimes also in adults). The recent fifth edition of the WHO Classification of Tumors of the CNS (WHO CNS5) divided the “Gliomas, Glioneuronal Tumors, and Neuronal Tumors” entity into six families, including two pediatric types: (1) the “Pediatric-type diffuse low-grade gliomas” (pLGG), expected to have good prognosis and (2) the “Pediatric-type diffuse high-grade gliomas” (pHGG), predicted as more aggressive [3]. Noteworthy, the term glioblastoma (GBM) is no longer used in children and adolescents. Among the pHGG, the WHO CNS5 classification distinguishes four subtypes, based on histopathological and molecular characteristics [4] (Figure 1): (a) the “Diffuse midline glioma (DMG), H3 K27-altered” subgroup was first defined in the 2016 CNS WHO classification [4], based on the existence of a diffuse growth pattern, a midline location (e.g., thalamus, brain stem, or spinal cord) and a K27M mutation (lysine 27 is replaced by methionine) in the histone H3 (H3) genes H3F3A or HIST1H3B [5], leading to epigenetic changes [5,6,7,8,9,10]. In 2021, other alterations (e.g., EZHIP protein overexpression) were recognized as defining the same entity [11]. DMG, H3 K27-altered includes tumors previously called diffuse intrinsic pontine glioma (DIPG). (b) the “Diffuse hemispheric glioma, H3 G34-mutant” entity is depicted by the presence of an arginine or valine residue (less frequent) at codon 34 instead of a glycine residue in the H3F3A and represents approximately 18% of the cortical pHGG in children [12]. Patients in this subgroup are mainly adolescents and young adults and have better overall survival (OS), compared to patients with K27 mutation [5]. (c) the “Diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype” requires a molecular characterization and the integration of histopathological and molecular data for diagnostic purposes [13]. (d) the “Infant-type hemispheric glioma” occurs in newborns and infants and has a distinct molecular profile, with gene fusions involving ALK, ROS1, NTRK1/2/3, or MET [14]. Most of the epidemiologic data, as well as basic science and clinical studies, were reported before this recent WHO CNS5 classification and classically divided the pHGG between DIPG and non-DIPG tumors. DIPG represents the major cause of death in children with CNS tumors. Male and female patients are equally affected and the median age at diagnosis is 7 years [15]. Outside clinical trials, the current standard of care is limited to focal radiotherapy (RT) [16]. Despite innovative therapeutic strategies [17], the prognosis remains poor with a median OS of 11.2 months [18]. Non-DIPG pHGG are equally distributed between male and female patients. The mean age at diagnosis is 8.7 years [19]. The current standard of care consists of surgical resection followed by RT and concomitant adjuvant chemotherapy. Despite a significant number of clinical trials for children with HGG [20], their prognosis did not improve over the last decades, with a median OS of 17 months [19]. For the purpose of the present review, we will adopt the recent histomolecular WHO CNS5 classification wherever possible. In case molecular data is not available, we will distinguish DMG from non-DMG pHGG wherever feasible, based on the location of the tumor. In case the location is not specified, we will use the broader category “pHGG” (Figure 1). In conclusion, pHGG are now individualized from their adult counterpart, to reflect their specificities in terms of pathogenesis and prognosis. As a group, they represent the most common pediatric cancer of the CNS. Despite numerous innovative treatments, they remain the major cause of death in children with CNS tumors, requiring new lines of research [21,22]. 2. From Stem Cells to Glioma Stem Cells Adult stem cells are defined as unspecialized cells that own the property to self-renew and to differentiate into diverse specialized cell types [21]. Stem cells ensure the production of tissue-specific short-lived cells in the intestinal epithelium, the skin or the hematological system, while allowing these tissues to constantly self-renew [22,23]. In the adult CNS, neural stem cells (NSCs) are found in neurogenic niches where they were shown to differentiate into committed neural subtypes, such as neurons, astrocytes or oligodendrocytes [24]. Cells with stem-like properties are also found within cancerous tissues, where they are called cancer stem cells (CSCs). Generally, less than 5% of the malignant cells of a tumor mass are known to preserve a self-renewal potential through multiple generations and can proliferate and reproduce a complex new tumor [25]. The basis of the CSC theory appeared for the first time in 1937, when the injection of a single leukemia cell into mice produced a quickly lethal leukemia [26]. Over 50 years later, Dick and coworkers identified a subset of patient-derived leukemia cells that could traffic to the bone marrow of immunodeficient mice, to actively proliferate and maintain the original leukemic cell phenotype [27]. They further characterized leukemia-initiating cells and showed that they could differentiate in vivo and self-renew [28]. While there has never been any clear consensus regarding their definition, CSCs were classically associated with four major in vitro properties [29]: (1) formation of spherical colonies in suspension cultures [30,31,32,33], (2) expression of different levels and patterns of surface and intracellular markers [34], (3) ability to differentiate towards multiple lineages [30,35] and (4) higher resistance to radiation and/or chemotherapy than the non-CSCs tumoral cells [36,37,38,39]. Importantly, in vivo, CSCs have been described as able to initiate the development of new tumors in serial xenotransplantation experiments [30]. So far, CSCs have thus been defined by the combination of multiple operational criteria. Since their initial description, CSCs were identified in several cancers, including breast cancer [25], prostate cancer [40], colorectal cancer [37,41,42] and pancreatic cancer [43]. In GBM, CSCs were first evidenced in 2002 in adults by Ignatova et al., who identified neural stem-like cells expressing astroglial and neuronal markers [44]. They were then demonstrated in pediatric pHGG by Hemmati et al., who identified some tumor cells expressing NSC and other stem cell-associated proteins, including CD133 [45] (see below). In 2004, Singh and collaborators reported the ability of adult GBM and pHGG CD133-positive cells to generate tumors that recapitulated the patient’s tumor histology in serial xenotransplantation [30]. Finally, in 2006, Bao et al. showed that CD133-positive glioma cells confer radioresistance and could be responsible for tumor recurrence after RT. They were the first to use the term “glioma stem cells” (GSCs) [46]. Since then, it has been estimated that approximately one GSC for 1000 tumor cells is present in adult GBM [47]. Gimple et al. proposed a GSC definition based on multiple functional criteria that assess the cell capacity to self-renew, initiate tumor through serial transplantation, and recapitulate tumor cell heterogeneity [48]. 3. From Adult to Pediatric Glioma Stem Cells Despite their initial description in pHGG as early as in 2004 [30], GSCs have been poorly characterized and their role has been under-researched in children as compared to adults. This can partly be explained by the low incidence of pHGG and the rarity of the pHGG tissue available for investigations. Here, we will review and summarize the literature that supports GSC identification in pHGG based on the putative stem cell protein markers (3.1) and illustrates the capacity of GSCs to recapitulate the initial patient tumor at the molecular or phenotypic levels (3.2). We will also discuss the more recent insight into GSC generation and maintenance in pHGG (3.3) (Figure 2). Although beyond the scope of the present review, note that CSCs have also been described in other childhood brain cancers, especially in embryonal tumors [30,35,49,50,51] and ependymomas [52,53,54,55]. In these tumors, many of the following molecular markers and phenotypic features were also used for CSC identification and characterization. 3.1. Putative Markers for GSCs in pHGG As described above, adult GSCs have been defined based on their capacity to self-renew, differentiate, and form tumors. Several proteins and transcription factors were proposed as putative markers, although it is nowadays well-accepted that their expression lacks specificity and consistency, and does not allow the accurate isolation of GSCs from other tumor cells [57]. Nonetheless, the many studies that harnessed such markers to support the existence of GSCs in pediatric HGG definitely contributed to the current knowledge on pediatric GSCs, and these findings are described in the following section (Figure 2A). 3.1.1. CD133 Prominin-1, also called CD133, is a pentaspan transmembrane glycoprotein, which functional roles in both normal and pathological conditions are yet unclear: it could be involved in membrane organization, act as a scaffolding protein, maintain stem cell-like properties and determine cellular fate (reviewed in Glumac et al. [58]). CD133 has been used to detect and isolate NSCs, and was suggested as an important contributor to their self-renewal and differentiation potential [59], although further research has demonstrated that CD133-negative NSCs were highly clonogenic and multipotent [60]. CD133 has been the most common cell surface antigen used to detect and isolate supposed CSCs in various types of solid tumors, including in gliomas (reviewed in Glumac et al. [58]). In pHGG, CD133 was first proposed in 2003 as an important protein for GSC discrimination [35,45]. Then, Singh et al. showed that only 100 CD133-positive pHGG cells were necessary to initiate a tumor upon intracranial transplantation into adult immunodeficient mice, while 100,000 CD133-negative cells failed [30]. Since then, numerous studies have related the expression of CD133 with stem-like properties in pHGG [61,62] and in DMG [63,64,65]. However, contrasting results obtained with adult GBM samples have shown CD133-positive and negative cells as able to convert into each other [66,67] and equally endowed with tumor initiation capacity [66,68], which dramatically requestioned the relevance of CD133 as an accurate marker of adult GSCs. Whether CD133 more soundly correlates with the GSC phenotype in pHGG compared to adult HGG remains to be addressed. 3.1.2. Bmi-1 CD133 is usually co-expressed with other proteins, including the B cell-specific Moloney murine leukemia virus integration site 1 (Bmi-1). Bmi-1 is a member of the Polycomb repressor complex (PRC) 1, which mediates gene silencing by regulating the chromatin structure, and which is required for the self-renewal of both normal and cancer stem cells [69]. High expression levels of Bmi-1 have been reported in pHGG [45,62] and in DMG [63,64,70]. The silencing of Bmi1 expression in a pHGG patient-derived orthotopic xenograft (PDOX) model decreased cell proliferation in vitro and inhibited tumor formation of both CD133-positive and CD133-negative subpopulations in vivo. However, gene expression profiling revealed a downregulation of different molecular targets of Bmi1 in CD133-positive compared to CD133-negative cells, which consisted of a novel set of core genes whose modulation impaired tumor initiation [62]. The Bmi1 inhibitor PTC-209 [71] reduced DMG cell proliferation, auto-renewal, migration, cell cycle, and telomerase activity. PTC-209 treatment affected the Rb pathway (which initiates DNA replication during the cell cycle) and increased tumor cell sensitivity to DNA damages caused by radiomimetic drugs [64]. 3.1.3. ALDH Over the past decade, high expression of aldehyde dehydrogenase (ALDH) has been used as a marker for normal stem cells and CSCs in many types of tissues. ALDH is a superfamily of enzymes that detoxify a variety of endogenous and exogenous aldehydes and are involved in resistance to drugs and radiation. In addition, ALDH is required for the biosynthesis of retinoic acid, which participates in both self-renewal and cell differentiation in various stem cells [72]. A recent study identified heterogeneous ALDH expression in different patient-derived DMG H3 K27-altered cell lines [65]. ALDH-positive cells were highly proliferative, demonstrated a capacity to form neurospheres and led to a decreased survival in mice upon orthotopic xenograft, in contrast to ALDH-negative cells. A transcriptomic characterization revealed high mRNA levels of MYC, E2F, DNA damage repair (DDR), glycolytic metabolism, and mTOR signaling genes in ALDH-positive compared to negative cell lines, which supports a stem-like phenotype. The targeting of MAPK/PI3K/mTOR recapitulated the downregulation of MYC, E2F, and DDR genes, diminished glycolytic metabolism in vitro, and inhibited tumor growth in vivo, likely by reducing cancer stemness [65]. 3.1.4. L1CAM The L1 Cell Adhesion Molecule (L1CAM) regulates neural cell growth, survival, migration, axonal outgrowth, and neurite extension during CNS development [73]. The targeting of L1CAM in vitro using shRNA interference in CD133-positive glioma cells (including pHGG) strongly disrupted neurosphere formation, induced apoptosis, and inhibited cell growth. In vivo, silencing of L1CAM expression suppressed tumor growth and increased the survival of tumor-bearing animals [74]. 3.1.5. Mushashi-1 Musashi-1 (Msi1) is an RNA-binding protein. It is highly expressed in the normal CNS, where it is an important marker of NSCs or progenitor cells [75]. Msi1 modulates Notch signaling and has multiple functions, including maintenance of the NSC state and self-renewal ability, differentiation, and tumorigenesis [75]. Interestingly, Msi1 expression was described in pHGG samples [45,76,77], where it was shown to enhance resistance to chemotherapy [77]. In vitro study of pHGG demonstrated that Msi1 promoted the expression of CD44 (see below), therefore co-expressed with MSI1 within recurrence-promoting cells at the migrating front of primary GBM samples. Mechanistically, Msi1 impaired CD44 downregulation in a 3′UTR- and miRNA-dependent manner, by controlling mRNA turnover [76]. 3.1.6. Nestin The neuroepithelial stem cell protein Nestin (NEural STem proteIN) was initially described in NSCs of the developing and adult brain, but is now known to be expressed in a variety of normal and malignant tissues. Physiologically, Nestin is a class VI intermediate filament component of the cytoskeleton, required for cell survival, self-renewal, and mitogen-stimulated proliferation of neural progenitor cells [78]. Often co-expressed with other stem cell markers, such as CD133 and/or Sox2 (see hereunder), high Nestin expression was found in pHGG [30,45,62] and DMG [63,64,70,79,80]. 3.1.7. Sox2 In recent years, the aberrant expression of sex-determining region Y (SRY)-box 2 (Sox2) has been detected in a wide diversity of cancers. Sox2 is considered as one of the key founding members of core pluripotency-associated transcription factors. Indeed, it plays a main role in the differentiation of pluripotent stem cells to neural progenitors and in sustaining the properties of neural progenitor cells [81]. As described above, Sox2 is generally co-expressed with other stem cell markers such as CD133 and Nestin in pHGG [45] and DMG [63,70,79,80,82]. 3.1.8. Olig2 The oligodendrocyte transcription factor 2 (Olig2) is present, to various extents, in all grades of pediatric and adult diffuse gliomas [83]. Olig2 expression is restricted to CNS, where it influences the proliferation of glial progenitors, the specification of oligodendrocyte progenitor cells (OPC) from neural progenitors or their primitive progenitors (pri-OPC) and the fate switch of OPC-astrocyte by inhibiting astrocytic differentiation in the developing brain [84]. A high expression of Olig2 was co-expressed with other stem cell proteins such as CD133, Nestin, and Sox2 in DMG [63,64,70,79,80,82]. 3.1.9. Nanog Nanog is a transcription factor that includes a DNA-binding domain, and is part of the core regulatory network that suppresses differentiation and maintains pluripotency [85]. Furthermore, Nanog expression closely correlates with stem-like traits in some malignant conditions, including adult GBM [86]. Nanog expression was evaluated in 24 post-mortem DMG tumors, together with other putative GSC protein expression. Whereas Sox2 and Olig2 were expressed in almost all samples, all cases were negative for Nanog [70] 3.1.10. CD44 CD44 is a membrane glycoprotein, known as a receptor for hyaluronic acid and is involved in diverse cellular processes including cell motility, proliferation, apoptosis, and angiogenesis. CD44 has been associated with a stem-like phenotype in adult GBM [87], although disrupting CD44 has later been proposed to increase stem-like phenotype [88,89]. Many studies have investigated its intricate role(s) in tumor cell invasion, proliferation, and resistance to chemoradiation therapy [90]. In pHGG, postmortem analysis of DMG K27M-altered tumors with supratentorial dissemination revealed an upregulation of CD44 correlated with c-SRC activation in multiple foci, which most likely contributed to invasiveness [91]. CD44 also has been shown highly expressed in patient-derived DMG cell cultures [92,93]. 3.1.11. CD15 CD15 is a trisaccharide 3-fucosyl-N-acetyllactosamine, also known as stage-specific embryonic antigen 1 (SSEA1). It has been confirmed to be prominently upregulated in normal cells such as neutrophils, macrophages but also NSCs, as well as in several cancers including adult GBM [94]. Studies have revealed high expression of CD15 in patient-derived DMG H3 K27-altered cells [92] and in pHGG [95] models, without deeply investigating its functional role(s). 3.2. Recapitulation of Patient Tumor Features Among a large majority of non-stem tumor cells, GSCs have long been described as essential for forming a tumor that is molecularly and phenotypically close to the original tissue (Figure 2A). It was demonstrated for the first time in 2004, when the xenograft of CD133-positive pHGG recapitulated the histopathological features of the patient’s initial tumor after serial transplantation [30]. In vitro, the establishment of patient-derived GSC cultures in a serum-free medium promotes enrichment in stem-like cells, and has long been demonstrated as the most reliable culture procedure for retaining initial patient tumor features [96,97]. In that sense, GSC cultures from pHGG and DMG H3 K27 altered tumors were shown to be proliferative, positive for several stem cell markers, able to differentiate, and endowed with a tumorigenic potential. Importantly, these cell lines accurately reflected the tumor patient in terms of methylation pattern, copy number alterations, and DNA mutations [98]. A paper showed that patient-derived orthotopic xenograft models of pHGG closely resembled their respective GSC line at the molecular level, and recapitulated patient tumor methylation profile and clinical outcome [99]. Another recent paper reports the establishment of 21 PDOX models as well as 8 matched cell lines from various pHGG groups (including DMG H3 K27-altered, diffuse hemispheric glioma H3 G34-mutant and diffuse pHGG, H3-wildtype and IDH-wildtype). The histology, DNA methylation signature, DNA mutations, and gene expression pattern of the patient tumors from which these models were derived were replicated in great majority [100]. However, it has to be reminded that neither GSC cultures nor PDOX models allow to precisely address whether GSCs in situ are the only cells that are responsible for tumor recapitulation. 3.3. Models for GSC Generation and Maintenance in pHGG In adult GBM, the generation of tumors has first been suggested to follow a hierarchical model where a GSC population is at the source of mainly unidirectional state changes towards a more differentiated progeny with a more restrictive profile [101]. Recently, genetic barcoding of freshly isolated adult GBM cells transplanted into PDOX mouse models further provided evidence for a conserved proliferative hierarchy, in which slow-cycling tumor stem-like cells give birth to a quick cycling, self-renewing, progenitor-like population [102]. Such a hierarchical model has been challenged in the last decade, where a model for stochastic evolution of tumors has progressively been introduced. Recent studies have shed light on the strong plasticity of adult GBM cells that dynamically transit from one cellular state to another [56, 103], in response to microenvironmental cues, cell–cell interactions, or therapeutic pressure. Enriched expression of several GSC markers (e.g., CD44, CD133, Nestin) has been associated with distinct cellular states, confirming their specificity to a transitory cell status rather than to a cell entity [104,105]. Importantly, this extensive plasticity of adult GBM cells appears more restricted in adult low-grade (IDH mutant) gliomas [103] and DMG H3 K27-altered [56]. Indeed, scRNA-seq analysis of primary DMG H3 K27-altered described that tumor cells are mostly constituted of cells that resemble oligodendrocyte precursor cells (OPC-like), which display an enhanced proliferative and tumor-propagating capacity compared to the minority of more differentiated cells (astrocyte-like and oligodendrocyte-like) [56] (Figure 2B). This H3K27M hierarchy suggests a more narrowed tumor evolution compared to adult GBM (reviewed in Suva et Tirosh [104]), and also provides clues about the putative cell of origin in these tumors (see below). Consistently, a longitudinal study of pHGG genomic profiles revealed a proliferative hierarchy of tumor cells, with slow-cycling cells giving rise to more “proliferating” then “differentiated” cells [106]. 4. The Subventricular Zone as a Key Actor in pHGG: In the adult brain, two well-described neurogenic zones host both NSCs and GSCs: the SVZ, located in the walls of the lateral ventricles, and the subgranular zone (SGZ) of the hippocampal dentate gyrus. A limited but sustained neurogenesis is ongoing within those two areas, even in adults [107]. Furthermore, the SVZ has been shown to offer to GSCs a particular microenvironment participating in their resistance to chemo- and RT [108,109]. These observations have raised the question of the cell of origin of HGG, on the one hand, and of the role of GSCs in HGG recurrence, on the other hand. These questions are particularly important in children, in whom the absolute numbers of proliferating cells vastly outnumber those in the adult brain (for a review, see Baker et al. [110]). Here, we will present data dealing with the cell of origin in pHGG. We will then discuss the potential role of the SVZ in pHGG recurrence. Finally, we will summarize data evaluating how it could impact the survival of patients with pHGG. 4.1. The Cell of Origin in pHGG Identifying the cell-of-origin responsible for glioma development has been a challenge for several years. In that attempt, Parada and collaborators have modeled GBM development in genetically-engineered murine models based on the deletion of p53, Nf1, and Pten tumor suppressors in restricted cell populations (under lineage-specific transcriptional control). Such studies allowed to point out NSCs located in the SVZ as usual suspects for HGG initiation [111], which was recently based on the genetic analysis of tumor material with matched SVZ samples that carry low-driver mutations [112]. Further investigations introduced the concept of a non-unique origin, and showed that lineage-specific gliomas could respectively arise from mutations in the NSCs from the SVZ or OPCs. Both types of gliomas have a distinct transcriptomic profile, methylation profile and functional properties [113], and were shown as differentially sensitive to chemotherapeutic drugs, supporting the consideration of different treatment opportunities based on the tumor profile. With regard to pHGG, a subset of Nestin/SOX2-positive cells also expressing the OPC-related protein Olig2 have been proposed as the tumor-forming population in DMG H3 K27-altered. These cells were detected in the pons of children, and their abundance correlated with the location and timeframe of glioma development [114]. Such finding is corroborated with the recent single-cell transcriptomic data provided by Filbin et al., suggesting DMG H3 K27-altered as enriched in OPC-like cells with great tumor-propagating potential [56]. On the other hand, diffuse hemispheric glioma, H3 G34-mutant were recently demonstrated as developing from GSX2+ interneuron progenitor-like cells (IPC-like) from the SVZ [115]. Altogether, it seems that diverse cell types may give rise to tumors with high genomic and phenotypic diversity, which stresses the importance of developmental programs in determining glioma subtype (for reviews, see Baker et al. [110], Alcantara Llaguno & Parada [111]). 4.2. The Potential Role of GSCs and SVZ in pHGG Recurrence In adult GBM, both experimental and clinical data suggest that GSCs could migrate from the tumor mass towards the SVZ, where they could escape therapies and be involved in GBM recurrences (for a review, see Lombard et al. [116]). In children, the cellular and molecular mechanisms mediating a possible migration of glioma cells towards the SVZ are largely unexplored. In 2014, Caretti et al. evaluated the SVZ spread of DMG, based on an autopsy series of 16 patients. They found that, in 10 of the 16 patients, there was contact or invasion of the SVZ during the disease, raising the question of the tropism of DMG cells for the SVZ neurogenic niche [117,118]. More recently, Qin and collaborators established two cultures of a pontine DMG at the time of early postmortem autopsy: one from the tumor in the pons and one from the tumor in the SVZ. Using an orthotopic mice model, they showed that SVZ-derived DMG cells injected in the pons migrated towards the SVZ in response to chemoattractant signals secreted by SVZ-hosted neural precursor cells. They identified pleiotrophin (PTN), and its three binding partners—secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1 (SPARCL1) and heat shock protein 90B (HSP90B)—as key mediators of this chemoattractant effect [79] (Figure 2C). 4.3. The Prognostic Impact of an SVZ Involvement in pHGG As described above, the specific environment offered by the SVZ to the NSC and GSC could be involved in both the genesis and the recurrence of the pHGG. The clinical significance of a contact between the tumor and the SVZ at diagnosis or at recurrence has been widely studied in adults (for a review, see Lombard et al. [116]). To the best of our knowledge, only one study evaluated the impact of a SVZ involvement by the tumor at diagnosis on the survival of children with pHGG [118]. In this study, SVZ involvement (SVZ+) was defined by a contact of the contrast-enhancing part of the tumor with the lateral wall of the lateral ventricle on preoperative post-gadolinium T1-weighted magnetic resonance imaging. A total of 63 children and adolescents with pHGG (excluding DIPG) were included (29 SVZ- and 34 SVZ+). Clinical features were similar in both study groups except for more midline location and a higher tumor volume in SZV+ tumors. In the univariable analysis, near- or gross-total resection and seizure presentation were correlated with increased overall survival, while SVZ+ tumors were associated with decreased overall survival (508 days in SVZ+ vs. 981 in SVZ −, HR = 1.94, 95% CI 1.03–3.64, p = 0.04). In a multivariate analysis considering the tumor volume and the degree of resection, SVZ+ tumors remained significantly associated with decreased survival (HR = 1.94, 95% CI 1.03–3.64, p = 0.04) [118]. These results suggest that tumor contact with the SVZ is a general negative prognosis marker in non-DIPG pHGG and invites biological investigations to better consider, study, and understand the role of SVZ in glioma pathobiology. 5. From the Concept of Pediatric GSC to Targeted Therapies Standard treatments, such as surgery and RT, have been used to specifically target the SVZ in adult GBM and several studies have evaluated their impact on survival (for a review, see Lombard et al. [116]). In pHGG, it is unknown whether irradiating the SVZ in complement to the tumor mass could improve the survival. However, when administered at a young age, RT could lead to possible neurocognitive deficits related to NSC alterations [119,120]. More recently, innovative strategies specifically targeting the GSCs have been developed in adult HGG [121]. In children as well, different methods of GSC targeting have been evaluated. Here we review the various opportunities for targeting GSCs in pHGG via the targeted inhibition of specific signaling pathways (5.1) and the use of oncolytic viruses (5.2). 5.1. Targeting of the GSC Signaling Pathways and Metabolism Several signaling pathways are shared between NSCs and GSCs (Figure 2D) and could play the main role in GSC maintenance. The Hedgehog (Hh) signaling pathway is highly conserved during evolution and is a key regulator of embryonic development processes, including cell differentiation, proliferation, and tissue patterning [122]. Using an in vitro model derived from early postmortem DMG tissues, Monje et al. showed that the Hh signaling was active in DMG cells and could be involved in the transformation of a potential cell of origin located in the ventral pons [115]. Exposure of DMG cells to the Hh pathway antagonist KAAD-cyclopamine significantly reduced their ability to generate neurospheres [114]. The NOTCH signaling is involved in NSC proliferation, survival, self-renewal, and differentiation [123]. It plays multiple roles in both CNS development and brain tumor biology [124]. High levels of NOTCH receptors, ligands, and downstream effectors are expressed in DMGs, where its inhibition reduces DMG growth, induces apoptosis, and increases sensitivity to RT [125]. The MAPK and the PI3K-Akt signaling pathways play a role in cell proliferation and differentiation, survival, and gene expression [126]. Both pathways are implicated in many cancers [127,128], including pHGG and DMG [129,130]. Inhibition of MAPK/PI3K/mTOR reduced the stem-like phenotype of ALDH-positive DMG cells [65]. Preclinical single-agent targeting of PI3K/mTOR pathway in DMG has seemed promising [131] and dual inhibition of MAPK and PI3K/mTOR pathway in DMG has shown to induce synergistic antitumor effects [130,132]. Long-term survivors have been reported with personalized therapy targeting the PI3K pathway [133]. Finally, specific therapies can also be oriented against metabolic vulnerabilities. Using single-cell RNA sequencing, it was recently shown that DMG H3 K27-altered contains different cell subtypes (namely OPC-like and astrocyte-like cells) with distinct metabolic profiles that can be selectively targeted [134]. 5.2. Oncolytic Virotherapy Oncolytic virotherapy has demonstrated a strong efficiency for the treatment of solid cancers, and the first FDA-approved oncolytic virus has recently been introduced for the treatment of melanoma [135]. OVs can be engineered and designed to selectively enter and replicate into cancer cells, e.g., through the presence of a specific receptor on the tumor surface, leading to cell lysis. Friedman et al. investigated the capacity of a genetically-modified oncolytic Herpes Simplex Virus (HSV) (G207) to infect and kill glioma cells. G207 contains deletions in the γ34.5 and ICP6/UL39 genes that prevent virus killing of normal brain cells. This virus has previously been proven safe in adult GBM patients, with a modest clinical response [136]. They have shown in vitro that CD133-positive and CD133-negative glioma cell subpopulations were similarly responsive to G207-induced cell death, claiming that putative stem-like cells were not resistant to the virus [137]. Another oncolytic HSV (G47Delta, with deletions in the γ34.5, ICP6/UL39, and additional deletion of the immediate-early alpha47 promoter) has been shown to reduce self-renewal of GSC cultures in vitro, and reduced their tumorigenicity. However again, both CD133-positive and CD133-negative cells were equally infected by the virus, stressing the complexity of CD133 in the stem-cell phenotype [138]. Other viruses have been considered for the treatment of pHGG. In 2016, Josupeit and collaborators evaluated the potential of parvovirus H1 (H-1PV). H1-PV is a non-pathogenic small single-stranded rodent DNA virus able to infect and replicate into human cells. They showed that H-1PV efficiently replicated in pHGG neurospheres and induced cytotoxicity in vitro. Nonetheless, H-1PV was able to target both stem-like and differentiated cell subpopulations in neurosphere cultures [139]. Overall, both studies showed that OVs allow the targeting of all glioma cells, including GSCs. Delta-24-RGD (DNX-2401) is a replication-competent oncolytic adenovirus genetically modified capable of infecting and killing glioma cells, and stimulating an anti-tumor immune response. To enhance potency, an RGD-motif was engineered into the fiber H-loop, enabling the virus to use αvβ3 or αvβ5 integrins to enter cells. These integrins are typically enriched at the surface of tumor cells, including adult GSCs [140] but also in DMG cells [141,142]. The administration of DNX-2401 in mice was proven safe and resulted in a significant increase in survival in immunodeficient and immunocompetent models of pHGG and DMG [142]. Beyond their oncolytic capacity, OVs may elicit an immune response [143] that raises great interest in the treatment of immunologically “cold” tumors such as pHGGs [144]. Very recently, Friedman et al. investigated whether G207 injection triggered a clinical response in pHGG patients [145]. Friedman et al. showed that G207 injection converted “cold” pHGG to immunologically “hot”, which provides great hopes for patient treatment. Moreover, using mesenchymal stem cells (MSC) as OV carriers improved OV delivery at the tumor site and offered protection from the clearance of the virus by the immune system [146], as recently demonstrated in DMG H3 K27-altered brainstem xenografts in mice. They showed that OV-loaded MSCs could reach the tumor and release the OV. They also reported that the concomitant administration of RT resulted in improved survival compared to OV-loaded MSCs alone [146]. 6. Conclusions Despite numerous innovative treatments, the survival of infants and children with pHGG remains poor and did not improve over the last decades. This can be explained by the rarity of pHGG and the low availability of tumor tissues for research purposes, the limited therapeutic approaches due to high risk of neurologic sequelae at young ages, and the absence of recognition of a specific and well-described pediatric entity. In this regard, the recent publication of the WHO CNS5 represents a major advance in the management of pHGG and has backed more than ever the importance to consider them as complete distinct entities, isolated from their adult counterparts. For decades, GSCs were studied in adult GBM, providing novel insight into GSC biology that continuously requires further understanding. The study of GSCs was later translated to pHGG, and warrants specific interest. Although the knowledge about their characterization and function is still incomplete, functional and in situ evidence about GSC presence in pHGG is increasingly brought to light. Proteins were identified in pHGG cells as important players in the retention of a stemness state, proliferation, and resistance to therapy. Several studies also show that pediatric GSCs recapitulate the patient tumor phenotype upon xenotransplantation. Recent application of new cutting-edge technologies in pHGG allowed in-depth GSC characterization in situ, depicting a hierarchical model of pediatric GSCs in their native environment. It remains to be seen whether future studies will challenge or consolidate this model. The SVZ has been suggested as a hideout for GSCs, thanks to a peculiar environment that promotes their maintenance in a stem-like state. These findings encourage us to consider these hidden cells as possibly responsible for the origin and the recurrence in future treatment strategies, and further reflect on SVZ targeted therapy. Finally, different signaling pathways have been evidenced in pHGG, and specific targeted therapies are under evaluation. Altogether, the last years have provided an enriched understanding and remodeling of the concept of GSCs in pediatric-type tumors. In parallel, the important molecular differences that characterize pediatric (vs. adult) HGG have led to the development of novel targeted therapeutic approaches for children (e.g., epigenetic modulation or immunotherapy) (reviewed in [17]). However, the establishment of such children-oriented therapies based on GSC targeting and/or modulation is less advanced. How the recent insight on GSCs could finally translate towards the establishment of therapeutic approaches in pHGG remains to be determined. Future perspectives will only be possible through close collaboration between the basic science and the clinics, on the one hand, and between the pediatric and the adult fields of expertise, on the other hand, while keeping in mind the specificities of pHGG occurring in infancy and childhood. Author Contributions Writing—Original Draft Preparation: M.-A.D.-V., V.N., C.P.; Writing—Review & Editing: M.-A.D.-V., B.R., A.L., C.P., V.N. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Clinical and molecular characteristics of the four pHGG subtypes according to the WHO CNS5 classification.The recent Fifth edition of the WHO Classification of Tumors of the Central Nervous System has defined, among the dedicated Pediatric-type high-grade gliomas (pHGG) entity, four histomolecular subtypes: (a) the Diffuse midline glioma H3 K27-altered (blue), (b) the Diffuse hemispheric glioma, H3 G34-mutant (red), (c) the Diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype (yellow) and (d) the Infant-type hemispheric glioma (grey). Most of the published data were reported before this recent classification and classically divided the pHGG between diffuse intrinsic pontine glioma (DIPG) and non-DIPG tumors, based on their location. The correspondence between the former, location-based, and the current, histomolecular-based classification is represented on the sagittal brain section using a color code. Abbreviations: ALK: anaplastic lymphoma kinase; DIPG: diffuse intrinsic pontine glioma; DMG: diffuse midline glioma; EZHIP: EZH inhibitory protein; H3: histone H3; H3F3A: gene encoding H3.3; HIST1H3B: gene encoding H3.1; IDH: isocitrate dehydrogenase; MET: MET proto-oncogene, receptor tyrosine kinase; NA: non-applicable; NTRK1/2/3: neurotrophic receptor tyrosine kinase 1/2/3; OS: overall survival; pHGG: pediatric-type high-grade glioma; ROS1: ROS Proto-Oncogene 1, receptor tyrosine kinase; WHO CNS5: fifth edition of the WHO Classification of Tumors of the Central Nervous System; WT: wildtype. The schematic art pieces used in this figure were provided by Servier Medical art (https://smart.servier.com), 25 April 2022. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License. Figure 2 Graphical summary illustrating the functional evidences of GSCs existence in pHGG (A), their generation and maintenance in pHGG (B), the role of the SVZ (C), and the signaling pathways involved in GSC-features (D). While there is no clear consensus, glioma stem cells (GSC) are classically defined based on multiple functional criteria, including the expression of different levels and patterns of surface and intracellular markers, the formation of spherical colonies in suspension cultures, a higher resistance to radiation and/or chemotherapy compared to the non-GSCs tumoral cells and the potential to recapitulate the initial tumor heterogeneity (A). scRNA-seq analysis of primary Diffuse Midline Glioma (DMG) H3 K27-altered showed that tumor cells are mostly constituted of cells that resemble oligodendrocyte precursor cells, which display an enhanced proliferative and tumor-propagating capacity compared to the minority of more differentiated cells (astrocyte-like and oligodendrocyte-like) (B). The subventricular zone (SVZ) is a key actor in pediatric high-grade gliomas (pHGG), as suggested by the recent in vivo demonstration that DMG cells injected in the pons migrate towards the SVZ in response to chemoattractant signals secreted by SVZ-hosted neural precursor cell. This chemoattractant effect depends on the pleiotrophin (PTN) and its three binding partners and is mediated by the PTN receptor protein tyrosine phosphate receptor type Z and the activation of the Rho/Rho kinase pathway (C). Several signaling pathways are shared between neural stem cells and pediatric GSC and are involved in gliogenesis, resistance to radiotherapy, and stem-like phenotype of pHGG (D). Abbreviations: AC: astrocyte; ALDH: aldehyde dehydrogenase; Bmi-1: B cell-specific moloney murine leukemia virus integration site 1; DMG: diffuse midline glioma; Hh: hedgehog; HSP90B: heat shock protein 90B; L1CAM: L1 cell adhesion molecule; MAPK: mitogen-activated protein kinase; MSI1: mushashi-1; mTOR: mammalian target of rapamycin; Nes: nestin; NPC: neural precursor cell; OC: oligodendrocyte; Olig2: oligodendrocyte transcription factor 2; OPC: oligodendrocyte progenitor cell; pGSC: pediatric glioma stem cell; PI3K: phosphatidylinositol 3′–kinase; PTN: pleiotrophin; ROCK: Rho-associated protein kinase; Sox2: SRY-Box transcription factor 2; SPARC: secreted protein acidic and rich in cysteine; SPARCL1: SPARC-like protein 1; SVZ: subventricular zone. The schematic art pieces used in this figure were provided by Servier Medical art (https://smart.servier.com), 25 April 2022. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License. Figure 2B is adapted from Filbin et al. [56]. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ostrom Q.T. Patil N. Cioffi G. Waite K. Kruchko C. Barnholtz-Sloan J.S. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2013–2017 Neuro-Oncology 2020 22 IV1 IV96 10.1093/neuonc/noaa200 33123732 2. Ostrom Q.T. de Blank P.M. Kruchko C. Petersen C.M. Liao P. Finlay J.L. Stearns D.S. Wolff J.E. Wolinsky Y. Letterio J.J. Alex’s Lemonade Stand Foundation Infant and Childhood Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2007-2011 Neuro-Oncology 2015 16 (Suppl. 10) x1 x35 10.1093/neuonc/nou327 25542864 3. Louis D.N. Perry A. Wesseling P. Brat D.J. Cree I.A. Figarella-Branger D. Hawkins C. Ng H.K. Pfister S.M. Reifenberger G. The 2021 WHO Classification of Tumors of the Central Nervous System: A Summary Neuro-Oncology 2021 23 1231 1251 10.1093/neuonc/noab106 34185076 4. Louis D.N. Perry A. Reifenberger G. von Deimling A. Figarella-Branger D. Cavenee W.K. Ohgaki H. Wiestler O.D. Kleihues P. Ellison D.W. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: A Summary Acta Neuropathol. 2016 131 803 820 10.1007/s00401-016-1545-1 27157931 5. Sturm D. Witt H. Hovestadt V. Khuong-Quang D.A. Jones D.T.W. Konermann C. Pfaff E. Tönjes M. Sill M. Bender S. Hotspot Mutations in H3F3A and IDH1 Define Distinct Epigenetic and Biological Subgroups of Glioblastoma Cancer Cell 2012 22 425 437 10.1016/j.ccr.2012.08.024 23079654 6. Bender S. Tang Y. Lindroth A.M. Hovestadt V. Jones D.T.W. Kool M. Zapatka M. Northcott P.A. Sturm D. Wang W. Reduced H3K27me3 and DNA Hypomethylation Are Major Drivers of Gene Expression in K27M Mutant Pediatric High-Grade Gliomas Cancer Cell 2013 24 660 672 10.1016/j.ccr.2013.10.006 24183680 7. Lewis P.W. Müller M.M. Koletsky M.S. Cordero F. Lin S. Banaszynski L.A. Garcia B.A. Muir T.W. Becher O.J. Allis C.D. Inhibition of PRC2 Activity by a Gain-of-Function H3 Mutation Found in Pediatric Glioblastoma Science 2013 340 857 861 10.1126/science.1232245 23539183 8. Chan K.M. Fang D. Gan H. Hashizume R. Yu C. Schroeder M. Gupta N. Mueller S. David James C. Jenkins R. The Histone H3.3K27M Mutation in Pediatric Glioma Reprograms H3K27 Methylation and Gene Expression Genes Dev. 2013 27 985 10.1101/gad.217778.113 23603901 9. Herz H.M. Morgan M. Gao X. Jackson J. Rickels R. Swanson S.K. Florens L. Washburn M.P. Eissenberg J.C. Shilatifard A. Histone H3 Lysine-to-Methionine Mutants as a Paradigm to Study Chromatin Signaling Science 2014 345 1065 1070 10.1126/science.1255104 25170156 10. Lee J. Solomon D.A. Tihan T. The Role of Histone Modifications and Telomere Alterations in the Pathogenesis of Diffuse Gliomas in Adults and Children J. Neurooncol. 2017 132 1 11 10.1007/s11060-016-2349-9 28064387 11. Castel D. Kergrohen T. Tauziède-Espariat A. Mackay A. Ghermaoui S. Lechapt E. Pfister S.M. Kramm C.M. Boddaert N. Blauwblomme T. Histone H3 Wild-Type DIPG/DMG Overexpressing EZHIP Extend the Spectrum Diffuse Midline Gliomas with PRC2 Inhibition beyond H3-K27M Mutation Acta Neuropathol. 2020 139 1109 1113 10.1007/s00401-020-02142-w 32193787 12. Lowe B.R. Maxham L.A. Hamey J.J. Wilkins M.R. Partridge J.F. Histone H3 Mutations: An Updated View of Their Role in Chromatin Deregulation and Cancer Cancers 2019 11 660 10.3390/cancers11050660 31086012 13. Korshunov A. Schrimpf D. Ryzhova M. Sturm D. Chavez L. Hovestadt V. Sharma T. Habel A. Burford A. Jones C. H3-/IDH-Wild Type Pediatric Glioblastoma Is Comprised of Molecularly and Prognostically Distinct Subtypes with Associated Oncogenic Drivers Acta Neuropathol. 2017 134 507 516 10.1007/s00401-017-1710-1 28401334 14. Clarke M. Mackay A. Ismer B. Pickles J.C. Tatevossian R.G. Newman S. Bale T.A. Stoler I. Izquierdo E. Temelso S. Infant High-Grade Gliomas Comprise Multiple Subgroups Characterized by Novel Targetable Gene Fusions and Favorable Outcomes Cancer Discov. 2020 10 942 963 10.1158/2159-8290.CD-19-1030 32238360 15. van Zanten S.E.M.V. Jansen M.H. Sanchez Aliaga E. van Vuurden D.G. Vandertop W.P. Kaspers G.J. A Twenty-Year Review of Diagnosing and Treating Children with Diffuse Intrinsic Pontine Glioma in The Netherlands Expert Rev. Anticancer Ther. 2015 15 157 164 10.1586/14737140.2015.974563 25435089 16. Hall M.D. Odia Y. Allen J.E. Tarapore R. Khatib Z. Niazi T.N. Daghistani D. Schalop L. Chi A.S. Oster W. First Clinical Experience with DRD2/3 Antagonist ONC201 in H3 K27M–Mutant Pediatric Diffuse Intrinsic Pontine Glioma: A Case Report J. Neurosurg. Pediatrics 2019 23 719 725 10.3171/2019.2.PEDS18480 17. Aziz-Bose R. Monje M. Diffuse Intrinsic Pontine Glioma: Molecular Landscape and Emerging Therapeutic Targets Curr. Opin. Oncol. 2019 31 522 530 10.1097/CCO.0000000000000577 31464759 18. Cooney T. Lane A. Bartels U. Bouffet E. Goldman S. Leary S.E.S. Foreman N.K. Packer R.J. Broniscer A. Minturn J.E. Contemporary Survival Endpoints: An International Diffuse Intrinsic Pontine Glioma Registry Study Neuro-Oncology 2017 19 1279 1280 10.1093/neuonc/nox107 28821206 19. da Costa M.D.S. Camargo N.C. Dastoli P.A. Nicácio J.M. Benevides Silva F.A. Sucharski Figueiredo M.L. Chen M.J. Cappellano A.M. da Silva N.S. Cavalheiro S. High-Grade Gliomas in Children and Adolescents: Is There a Role for Reoperation? J. Neurosurg. Pediatr. 2020 27 160 169 10.3171/2020.7.PEDS20389 33307529 20. Jones C. Karajannis M.A. Jones D.T.W. Kieran M.W. Monje M. Baker S.J. Becher O.J. Cho Y.J. Gupta N. Hawkins C. Pediatric High-Grade Glioma: Biologically and Clinically in Need of New Thinking Neuro-Oncology 2017 19 153 161 10.1093/neuonc/now101 27282398 21. Zakrzewski W. Dobrzyński M. Szymonowicz M. Rybak Z. Stem Cells: Past, Present, and Future Stem Cell Res. Ther. 2019 10 68 10.1186/s13287-019-1165-5 30808416 22. Doulatov S. Notta F. Laurenti E. Dick J.E. Hematopoiesis: A Human Perspective Cell Stem Cell 2012 10 120 136 10.1016/j.stem.2012.01.006 22305562 23. Clevers H. The Intestinal Crypt, a Prototype Stem Cell Compartment Cell 2013 154 274 10.1016/j.cell.2013.07.004 23870119 24. Temple S. The Development of Neural Stem Cells Nature 2001 414 112 117 10.1038/35102174 11689956 25. Al-Hajj M. Wicha M.S. Benito-Hernandez A. Morrison S.J. Clarke M.F. Prospective Identification of Tumorigenic Breast Cancer Cells Proc. Natl. Acad. Sci. USA 2003 100 3983 3988 10.1073/pnas.0530291100 12629218 26. Furth J. Kahn M.C. The Transmission of Leukemia of Mice with a Single Cell Am. J. Cancer 1937 31 276 282 10.1158/AJC.1937.276 27. Lapidot T. Sirard C. Vormoor J. Murdoch B. Hoang T. Caceres-Cortes J. Minden M. Paterson B. Caligiuri M.A. Dick J.E. A Cell Initiating Human Acute Myeloid Leukaemia after Transplantation into SCID Mice Nature 1994 367 645 648 10.1038/367645a0 7509044 28. Bonnet D. Dick J.E. Human Acute Myeloid Leukemia Is Organized as a Hierarchy That Originates from a Primitive Hematopoietic Cell Nat. Med. 1997 3 730 737 10.1038/nm0797-730 9212098 29. Clevers H. The Cancer Stem Cell: Premises, Promises and Challenges Nat. Med. 2011 17 313 319 10.1038/nm.2304 21386835 30. Singh S.K. Hawkins C. Clarke I.D. Squire J.A. Bayani J. Hide T. Henkelman R.M. Cusimano M.D. Dirks P.B. Identification of Human Brain Tumour Initiating Cells Nature 2004 432 396 401 10.1038/nature03128 15549107 31. Galli R. Binda E. Orfanelli U. Cipelletti B. Gritti A. de Vitis S. Fiocco R. Foroni C. Dimeco F. Vescovi A. Isolation and Characterization of Tumorigenic, Stem-like Neural Precursors from Human Glioblastoma Cancer Res. 2004 64 7011 7021 10.1158/0008-5472.CAN-04-1364 15466194 32. Reynolds B.A. Weiss S. Generation of Neurons and Astrocytes from Isolated Cells of the Adult Mammalian Central Nervous System Science 1992 255 1707 1710 10.1126/science.1553558 1553558 33. Yuan X. Curtin J. Xiong Y. Liu G. Waschsmann-Hogiu S. Farkas D.L. Black K.L. Yu J.S. Isolation of Cancer Stem Cells from Adult Glioblastoma Multiforme Oncogene 2004 23 9392 9400 10.1038/sj.onc.1208311 15558011 34. Walcher L. Kistenmacher A.K. Suo H. Kitte R. Dluczek S. Strauß A. Blaudszun A.R. Yevsa T. Fricke S. Kossatz-Boehlert U. Cancer Stem Cells-Origins and Biomarkers: Perspectives for Targeted Personalized Therapies Front. Immunol. 2020 11 1280 10.3389/fimmu.2020.01280 32849491 35. Singh S.K. Clarke I.D. Terasaki M. Bonn V.E. Hawkins C. Squire J. Dirks P.B. Identification of a Cancer Stem Cell in Human Brain Tumors Cancer Res. 2003 63 5821 5828 14522905 36. Clarke M.F. Dick J.E. Dirks P.B. Eaves C.J. Jamieson C.H.M. Jones D.L. Visvader J. Weissman I.L. Wahl G.M. Cancer Stem Cells—Perspectives on Current Status and Future Directions: AACR Workshop on Cancer Stem Cells Cancer Res. 2006 66 9339 9344 10.1158/0008-5472.CAN-06-3126 16990346 37. Hanahan D. Weinberg R.A. The Hallmarks of Cancer Cell 2000 100 57 70 10.1016/S0092-8674(00)81683-9 10647931 38. Ricci-Vitiani L. Lombardi D.G. Pilozzi E. Biffoni M. Todaro M. Peschle C. de Maria R. Identification and Expansion of Human Colon-Cancer-Initiating Cells Nature 2007 445 111 115 10.1038/nature05384 17122771 39. Rahmathulla G. Toms S.A. Weil R.J. The Molecular Biology of Brain Metastasis J. Oncol. 2012 2012 723541 10.1155/2012/723541 22481931 40. Collins A.T. Berry P.A. Hyde C. Stower M.J. Maitland N.J. Prospective Identification of Tumorigenic Prostate Cancer Stem Cells Cancer Res. 2005 65 10946 10951 10.1158/0008-5472.CAN-05-2018 16322242 41. Dalerba P. Dylla S.J. Park I.K. Liu R. Wang X. Cho R.W. Hoey T. Gurney A. Huang E.H. Simeone D.M. Phenotypic Characterization of Human Colorectal Cancer Stem Cells Proc. Natl. Acad. Sci. USA 2007 104 10158 10163 10.1073/pnas.0703478104 17548814 42. O’Brien C.A. Pollett A. Gallinger S. Dick J.E. A Human Colon Cancer Cell Capable of Initiating Tumour Growth in Immunodeficient Mice Nature 2007 445 106 110 10.1038/nature05372 17122772 43. Li C. Heidt D.G. Dalerba P. Burant C.F. Zhang L. Adsay V. Wicha M. Clarke M.F. Simeone D.M. Identification of Pancreatic Cancer Stem Cells Cancer Res. 2007 67 1030 1037 10.1158/0008-5472.CAN-06-2030 17283135 44. Ignatova T.N. Kukekov V.G. Laywell E.D. Suslov O.N. Vrionis F.D. Steindler D.A. Human Cortical Glial Tumors Contain Neural Stem-like Cells Expressing Astroglial and Neuronal Markers in vitro Glia 2002 39 193 206 10.1002/glia.10094 12203386 45. Hemmati H.D. Nakano I. Lazareff J.A. Masterman-Smith M. Geschwind D.H. Bronner-Fraser M. Kornblum H.I. Cancerous Stem Cells Can Arise from Pediatric Brain Tumors Proc. Natl. Acad. Sci. USA 2003 100 15178 15183 10.1073/pnas.2036535100 14645703 46. Bao S. Wu Q. McLendon R.E. Hao Y. Shi Q. Hjelmeland A.B. Dewhirst M.W. Bigner D.D. Rich J.N. Glioma Stem Cells Promote Radioresistance by Preferential Activation of the DNA Damage Response Nature 2006 444 756 760 10.1038/nature05236 17051156 47. Vermeulen L. de Sousa e Melo F. Richel D.J. Medema J.P. The Developing Cancer Stem-Cell Model: Clinical Challenges and Opportunities Lancet Oncol. 2012 13 e83 e89 10.1016/S1470-2045(11)70257-1 22300863 48. Gimple R.C. Bhargava S. Dixit D. Rich J.N. Glioblastoma Stem Cells: Lessons from the Tumor Hierarchy in a Lethal Cancer Genes Dev. 2019 33 591 609 10.1101/gad.324301.119 31160393 49. Ahmad Z. Jasnos L. Gil V. Howell L. Hallsworth A. Petrie K. Sawado T. Chesler L. Molecular and In Vivo Characterization of Cancer-Propagating Cells Derived from MYCN-Dependent Medulloblastoma PLoS ONE 2015 10 e0119834 10.1371/journal.pone.0119834 25785590 50. Huang G.H. Xu Q.F. Cui Y.H. Li N. Bian X.W. Lv S.Q. Medulloblastoma Stem Cells: Promising Targets in Medulloblastoma Therapy Cancer Sci. 2016 107 583 589 10.1111/cas.12925 27171351 51. Bahmad H.F. Poppiti R.J. Medulloblastoma Cancer Stem Cells: Molecular Signatures and Therapeutic Targets J. Clin. Pathol. 2020 73 243 249 10.1136/jclinpath-2019-206246 32034059 52. Meco D. Servidei T. Lamorte G. Binda E. Arena V. Riccardi R. Ependymoma Stem Cells Are Highly Sensitive to Temozolomide in Vitro and in Orthotopic Models Neuro-Oncology 2014 16 1067 1077 10.1093/neuonc/nou008 24526307 53. Taylor M.D. Poppleton H. Fuller C. Su X. Liu Y. Jensen P. Magdaleno S. Dalton J. Calabrese C. Board J. Radial Glia Cells Are Candidate Stem Cells of Ependymoma Cancer Cell 2005 8 323 335 10.1016/j.ccr.2005.09.001 16226707 54. Milde T. Kleber S. Korshunov A. Witt H. Hielscher T. Koch P. Kopp H.G. Jugold M. Deubzer H.E. Oehme I. A Novel Human High-Risk Ependymoma Stem Cell Model Reveals the Differentiation-Inducing Potential of the Histone Deacetylase Inhibitor Vorinostat Acta Neuropathol. 2011 122 637 650 10.1007/s00401-011-0866-3 21863243 55. Servidei T. Lucchetti D. Navarra P. Sgambato A. Riccardi R. Ruggiero A. Cell-of-Origin and Genetic, Epigenetic, and Microenvironmental Factors Contribute to the Intra-Tumoral Heterogeneity of Pediatric Intracranial Ependymoma Cancers 2021 13 6100 10.3390/cancers13236100 34885210 56. Filbin M.G. Tirosh I. Hovestadt V. Shaw M.L. Escalante L.E. Mathewson N.D. Neftel C. Frank N. Pelton K. Hebert C.M. Developmental and Oncogenic Programs in H3K27M Gliomas Dissected by Single-Cell RNA-Seq Science 2018 360 331 335 10.1126/science.aao4750 29674595 57. Lathia J.D. Mack S.C. Mulkearns-Hubert E.E. Valentim C.L.L. Rich J.N. Cancer Stem Cells in Glioblastoma Genes Dev. 2015 29 1203 1217 10.1101/gad.261982.115 26109046 58. Glumac P.M. LeBeau A.M. The Role of CD133 in Cancer: A Concise Review Clin. Transl. Med. 2018 7 18 10.1186/s40169-018-0198-1 29984391 59. Uchida N. Buck D.W. He D. Reitsma M.J. Masek M. Phan T.V. Tsukamoto A.S. Gage F.H. Weissman I.L. Direct Isolation of Human Central Nervous System Stem Cells Proc. Natl. Acad. Sci. USA 2000 97 14720 14725 10.1073/pnas.97.26.14720 11121071 60. Sun Y. Kong W. Falk A. Hu J. Zhou L. Pollard S. Smith A. CD133 (Prominin) Negative Human Neural Stem Cells Are Clonogenic and Tripotent PLoS ONE 2009 4 e5498 10.1371/journal.pone.0005498 19430532 61. Shu Q. Wong K.K. Su J.M. Adesina A.M. Yu L.T. Tsang Y.T.M. Antalffy B.C. Baxter P. Perlaky L. Yang J. Direct Orthotopic Transplantation of Fresh Surgical Specimen Preserves CD133+ Tumor Cells in Clinically Relevant Mouse Models of Medulloblastoma and Glioma Stem Cells 2008 26 1414 1424 10.1634/stemcells.2007-1009 18403755 62. Baxter P.A. Lin Q. Mao H. Kogiso M. Zhao X. Liu Z. Huang Y. Voicu H. Gurusiddappa S. Su J.M. Silencing BMI1 Eliminates Tumor Formation of Pediatric Glioma CD133+ Cells Not by Affecting Known Targets but by Down-Regulating a Novel Set of Core Genes Acta Neuropathol. Commun. 2014 2 160 10.1186/s40478-014-0160-4 25526772 63. Thirant C. Bessette B. Varlet P. Puget S. Cadusseau J. Tavares S.d.R. Studler J.M. Silvestre D.C. Susini A. Villa C. Clinical Relevance of Tumor Cells with Stem-Like Properties in Pediatric Brain Tumors PLoS ONE 2011 6 e16375 10.1371/journal.pone.0016375 21297991 64. Kumar S.S. Sengupta S. Lee K. Hura N. Fuller C. DeWire M. Stevenson C.B. Fouladi M. Drissi R. BMI-1 Is a Potential Therapeutic Target in Diffuse Intrinsic Pontine Glioma Oncotarget 2017 8 62962 62975 10.18632/oncotarget.18002 28968963 65. Surowiec R.K. Ferris S.F. Apfelbaum A. Espinoza C. Mehta R.K. Monchamp K. Sirihorachai V.R. Bedi K. Ljungman M. Galban S. Transcriptomic Analysis of Diffuse Intrinsic Pontine Glioma (DIPG) Identifies a Targetable ALDH-Positive Subset of Highly Tumorigenic Cancer Stem-like Cells Mol. Cancer Res. 2021 19 223 239 10.1158/1541-7786.MCR-20-0464 33106374 66. Chen R. Nishimura M.C. Bumbaca S.M. Kharbanda S. Forrest W.F. Kasman I.M. Greve J.M. Soriano R.H. Gilmour L.L. Rivers C.S. A Hierarchy of Self-Renewing Tumor-Initiating Cell Types in Glioblastoma Cancer Cell 2010 17 362 375 10.1016/j.ccr.2009.12.049 20385361 67. Wang J. Sakariassen P. Tsinkalovsky O. Immervoll H. Bøe S.O. Svendsen A. Prestegarden L. Røsland G. Thorsen F. Stuhr L. CD133 Negative Glioma Cells Form Tumors in Nude Rats and Give Rise to CD133 Positive Cells Int. J. Cancer 2008 122 761 768 10.1002/ijc.23130 17955491 68. Beier D. Hau P. Proescholdt M. Lohmeier A. Wischhusen J. Oefner P.J. Aigner L. Brawanski A. Bogdahn U. Beier C.P. CD133(+) and CD133(−) Glioblastoma-Derived Cancer Stem Cells Show Differential Growth Characteristics and Molecular Profiles Cancer Res. 2007 67 4010 4015 10.1158/0008-5472.CAN-06-4180 17483311 69. Bhattacharya R. Banerjee Mustafi S. Street M. Dey A. Dwivedi S.K.D. Bmi-1: At the Crossroads of Physiological and Pathological Biology Genes Dis. 2015 2 225 239 10.1016/j.gendis.2015.04.001 26448339 70. Ballester L.Y. Wang Z. Shandilya S. Miettinen M. Burger P.C. Eberhart C.G. Rodriguez F.J. Raabe E. Nazarian J. Warren K. Morphologic Characteristics and Immunohistochemical Profile of Diffuse Intrinsic Pontine Gliomas Am. J. Surg. Pathol. 2013 37 1357 1364 10.1097/PAS.0b013e318294e817 24076776 71. Kreso A. van Galen P. Pedley N.M. Lima-Fernandes E. Frelin C. Davis T. Cao L. Baiazitov R. Du W. Sydorenko N. Self-Renewal as a Therapeutic Target in Human Colorectal Cancer Nat. Med. 2014 20 29 36 10.1038/nm.3418 24292392 72. Vassalli G. Aldehyde Dehydrogenases: Not Just Markers, but Functional Regulators of Stem Cells Stem Cells Int. 2019 2019 3904645 10.1155/2019/3904645 30733805 73. Altevogt P. Doberstein K. Fogel M. L1CAM in Human Cancer Int. J. Cancer 2016 138 1565 1576 10.1002/ijc.29658 26111503 74. Bao S. Wu Q. Li Z. Sathornsumetee S. Wang H. McLendon R.E. Hjelmeland A.B. Rich J.N. Targeting Cancer Stem Cells through L1CAM Suppresses Glioma Growth Cancer Res. 2008 68 6043 10.1158/0008-5472.CAN-08-1079 18676824 75. Glazer R.I. Wang X.Y. Yuan H. Yin Y. Musashi1: A Stem Cell Marker No Longer in Search of a Function Cell Cycle 2008 7 2635 2639 10.4161/cc.7.17.6522 18719393 76. Pötschke R. Haase J. Glaß M. Simmermacher S. Misiak C. Penalva L.O.F. Kühnöl C.D. Hüttelmaier S. MSI1 Promotes the Expression of the GBM Stem Cell Marker CD44 by Impairing MiRNA-Dependent Degradation Cancers 2020 12 3654 10.3390/cancers12123654 77. Pötschke R. Gielen G. Pietsch T. Kramm C. Klusmann J.H. Hüttelmaier S. Kühnöl C.D. Musashi1 Enhances Chemotherapy Resistance of Pediatric Glioblastoma Cells in vitro Pediatric Res. 2020 87 669 676 10.1038/s41390-019-0628-9 78. Bernal A. Arranz L. Nestin-Expressing Progenitor Cells: Function, Identity and Therapeutic Implications Cell. Mol. Life Sci. 2018 75 2177 2195 10.1007/s00018-018-2794-z 29541793 79. Qin E.Y. Cooper D.D. Abbott K.L. Vogel H. Jackson P.K. Correspondence M.M. Neural Precursor-Derived Pleiotrophin Mediates Subventricular Zone Invasion by Glioma Cell 2017 170 845 849.e19 10.1016/j.cell.2017.07.016 28823557 80. Xu C. Liu X. Geng Y. Bai Q. Pan C. Sun Y. Chen X. Yu H. Wu Y. Zhang P. Patient-Derived DIPG Cells Preserve Stem-like Characteristics and Generate Orthotopic Tumors Oncotarget 2017 8 76644 76655 10.18632/oncotarget.19656 29100338 81. Mamun M.A. Mannoor K. Cao J. Qadri F. Song X. SOX2 in Cancer Stemness: Tumor Malignancy and Therapeutic Potentials J. Mol. Cell Biol. 2020 12 85 98 10.1093/jmcb/mjy080 30517668 82. Finlay J. Hallou C. Dewari P. Pollard S. Pathania M. Bulstrode H. Rowitch D. Characterising a SOX2+ OLIG2+ Glioma Stem Cell Using Crispr-Engineered Fluorescent Reporters in Primary Patient-Derived GBM and DIPG Cells Neuro-Oncology 2019 21 iv9 10.1093/neuonc/noz167.039 83. Otero J.J. Rowitch D. Vandenberg S. OLIG2 Is Differentially Expressed in Pediatric Astrocytic and in Ependymal Neoplasms J. Neuro-Oncol. 2011 104 423 438 10.1007/s11060-010-0509-x 84. Kosty J. Lu F. Kupp R. Mehta S. Lu Q.R. Harnessing OLIG2 Function in Tumorigenicity and Plasticity to Target Malignant Gliomas Cell Cycle 2017 16 1654 1660 10.1080/15384101.2017.1361062 28806136 85. Theunissen T.W. Silva J.C.R. Switching on Pluripotency: A Perspective on the Biological Requirement of Nanog Philos. Trans. R. Soc. B: Biol. Sci. 2011 366 2222 2229 10.1098/rstb.2011.0003 86. Ye Y. Zhang M. Yan G. Ma Q. Yan Z. Wang L. Yang K. Guo D. Nanog Promotes Stem-like Traits of Glioblastoma Cells Front. Biosci.-Landmark 2021 26 552 565 10.2741/4907 87. Anido J. Sáez-Borderías A. Gonzàlez-Juncà A. Rodón L. Folch G. Carmona M.A. Prieto-Sánchez R.M. Barba I. Martínez-Sáez E. Prudkin L. TGF-β Receptor Inhibitors Target the CD44(High)/Id1(High) Glioma-Initiating Cell Population in Human Glioblastoma Cancer Cell 2010 18 655 668 10.1016/j.ccr.2010.10.023 21156287 88. Hartheimer J.S. Park S. Rao S.S. Kim Y. Targeting Hyaluronan Interactions for Glioblastoma Stem Cell Therapy Cancer Microenviron. 2019 12 47 56 10.1007/s12307-019-00224-2 31079324 89. Wang H.H. Liao C.C. Chow N.H. Huang L.L.H. Chuang J.I. Wei K.C. Shin J.W. Whether CD44 Is an Applicable Marker for Glioma Stem Cells Am. J. Transl. Res. 2017 9 4785 29218080 90. Mooney K.L. Choy W. Sidhu S. Pelargos P. Bui T.T. Voth B. Barnette N. Yang I. The Role of CD44 in Glioblastoma Multiforme J. Clin. Neurosci. 2016 34 1 5 10.1016/j.jocn.2016.05.012 27578526 91. Georgescu M.M. Islam M.Z. Li Y. Circu M.L. Traylor J. Notarianni C.M. Kline C.N. Burns D.K. Global Activation of Oncogenic Pathways Underlies Therapy Resistance in Diffuse Midline Glioma Acta Neuropathol. Commun. 2020 8 111 10.1186/s40478-020-00992-9 32680567 92. Mount C.W. Majzner R.G. Sundaresh S. Arnold E.P. Kadapakkam M. Haile S. Labanieh L. Hulleman E. Woo P.J. Rietberg S.P. Potent Antitumor Efficacy of Anti-GD2 CAR T Cells in H3-K27M+ Diffuse Midline Gliomas Letter Nat. Med. 2018 24 572 579 10.1038/s41591-018-0006-x 29662203 93. Hoeman C.M. Cordero F.J. Hu G. Misuraca K. Romero M.M. Cardona H.J. Nazarian J. Hashizume R. McLendon R. Yu P. ACVR1 R206H Cooperates with H3.1K27M in Promoting Diffuse Intrinsic Pontine Glioma Pathogenesis Nat. Commun. 2019 10 1023 10.1038/s41467-019-08823-9 30833574 94. Hassn Mesrati M. Behrooz A.B. Abuhamad A.Y. Syahir A. Understanding Glioblastoma Biomarkers: Knocking a Mountain with a Hammer Cells 2020 9 1236 10.3390/cells9051236 95. Donovan L.K. Potter N.E. Warr T. Pilkington G.J. A Prominin-1-Rich Pediatric Glioblastoma: Biologic Behavior Is Determined by Oxygen Tension-Modulated CD133 Expression but Not Accompanied by Underlying Molecular Profiles Transl. Oncol. 2012 5 141 154 10.1593/tlo.11337 22741033 96. De P.C. Hamer W. van Tilborg A. Eijk P.P. Sminia P. Troost D. van Noorden C. Ylstra B. Leenstra S. The Genomic Profile of Human Malignant Glioma Is Altered Early in Primary Cell Culture and Preserved in Spheroids Oncogene 2008 27 2091 2096 10.1038/sj.onc.1210850 17934519 97. Lee J. Kotliarova S. Kotliarov Y. Li A. Su Q. Donin N.M. Pastorino S. Purow B.W. Christopher N. Zhang W. Tumor Stem Cells Derived from Glioblastomas Cultured in BFGF and EGF More Closely Mirror the Phenotype and Genotype of Primary Tumors than Do Serum-Cultured Cell Lines Cancer Cell 2006 9 391 403 10.1016/j.ccr.2006.03.030 16697959 98. Wenger A. Larsson S. Danielsson A. Elbæk K.J. Kettunen P. Tisell M. Sabel M. Lannering B. Nordborg C. Schepke E. Stem Cell Cultures Derived from Pediatric Brain Tumors Accurately Model the Originating Tumors Oncotarget 2017 8 18626 18639 10.18632/oncotarget.14826 28148893 99. Larsson S. Wenger A. Dósa S. Sabel M. Kling T. Carén H. Cell Line-Based Xenograft Mouse Model of Paediatric Glioma Stem Cells Mirrors the Clinical Course of the Patient Carcinogenesis 2018 39 1304 1309 10.1093/carcin/bgy091 29982329 100. He C. Xu K. Zhu X. Dunphy P.S. Gudenas B. Lin W. Twarog N. Hover L.D. Kwon C.H. Kasper L.H. Patient-Derived Models Recapitulate Heterogeneity of Molecular Signatures and Drug Response in Pediatric High-Grade Glioma Nat. Commun. 2021 12 4089 10.1038/s41467-021-24168-8 34215733 101. Furusawa C. Kaneko K. Chaotic Expression Dynamics Implies Pluripotency: When Theory and Experiment Meet Biol. Direct 2009 4 17 10.1186/1745-6150-4-17 19445676 102. Lan X. Jörg D.J. Cavalli F.M.G. Richards L.M. Nguyen L.V. Vanner R.J. Guilhamon P. Lee L. Kushida M.M. Pellacani D. Fate Mapping of Human Glioblastoma Reveals an Invariant Stem Cell Hierarchy Nature 2017 549 227 232 10.1038/nature23666 28854171 103. Tirosh I. Venteicher A.S. Hebert C. Escalante L.E. Patel A.P. Yizhak K. Fisher J.M. Rodman C. Mount C. Filbin M.G. Single-Cell RNA-Seq Supports a Developmental Hierarchy in Human Oligodendroglioma Nature 2016 539 309 313 10.1038/nature20123 27806376 104. Suvà M.L. Tirosh I. The Glioma Stem Cell Model in the Era of Single-Cell Genomics Cancer Cell 2020 37 630 636 10.1016/j.ccell.2020.04.001 32396858 105. Dirkse A. Golebiewska A. Buder T. Nazarov P.V. Muller A. Poovathingal S. Brons N.H.C. Leite S. Sauvageot N. Sarkisjan D. Stem Cell-Associated Heterogeneity in Glioblastoma Results from Intrinsic Tumor Plasticity Shaped by the Microenvironment Nat. Commun. 2019 10 1787 10.1038/s41467-019-09853-z 30992437 106. Hoffman M. Gillmor A.H. Kunz D.J. Johnston M.J. Nikolic A. Narta K. Zarrei M. King J. Ellestad K. Dang N.H. Intratumoral Genetic and Functional Heterogeneity in Pediatric Glioblastoma Cancer Res. 2019 79 2111 2123 10.1158/0008-5472.CAN-18-3441 30877103 107. Franjic D. Skarica M. Ma S. Arellano J.I. Tebbenkamp A.T.N. Choi J. Xu C. Li Q. Morozov Y.M. Andrijevic D. Transcriptomic Taxonomy and Neurogenic Trajectories of Adult Human, Macaque, and Pig Hippocampal and Entorhinal Cells Neuron 2022 110 452 469.e14 10.1016/j.neuron.2021.10.036 34798047 108. Goffart N. Lombard A. Lallemand F. Kroonen J. Nassen J. di Valentin E. Berendsen S. Dedobbeleer M. Willems E. Robe P. CXCL12 Mediates Glioblastoma Resistance to Radiotherapy in the Subventricular Zone Neuro-Oncology 2017 19 66 77 10.1093/neuonc/now136 27370398 109. Piccirillo S.G.M. Spiteri I. Sottoriva A. Touloumis A. Ber S. Price S.J. Heywood R. Francis N.J. Howarth K.D. Collins V.P. Contributions to Drug Resistance in Glioblastoma Derived from Malignant Cells in the Sub-Ependymal Zone Cancer Res. 2015 75 194 202 10.1158/0008-5472.CAN-13-3131 25406193 110. Baker S.J. Ellison D.W. Gutmann D.H. Pediatric Gliomas as Neurodevelopmental Disorders Glia 2016 64 879 10.1002/glia.22945 26638183 111. Alcantara Llaguno S. Chen J. Kwon C.H. Jackson E.L. Li Y. Burns D.K. Alvarez-Buylla A. Parada L.F. Malignant Astrocytomas Originate from Neural Stem/Progenitor Cells in a Somatic Tumor Suppressor Mouse Model Cancer Cell 2009 15 45 56 10.1016/j.ccr.2008.12.006 19111880 112. Lee J.H. Lee J.E. Kahng J.Y. Kim S.H. Park J.S. Yoon S.J. Um J.-Y. Kim W.K. Lee J.-K. Park J. Human Glioblastoma Arises from Subventricular Zone Cells with Low-Level Driver Mutations Nature 2018 560 243 247 10.1038/s41586-018-0389-3 30069053 113. Wang Z. Sun D. Chen Y.J. Xie X. Shi Y. Tabar V. Brennan C.W. Bale T.A. Jayewickreme C.D. Laks D.R. Cell Lineage-Based Stratification for Glioblastoma Cancer Cell 2020 38 366 379.e8 10.1016/j.ccell.2020.06.003 32649888 114. Monje M. Mitra S.S. Freret M.E. Raveh T.B. Kim J. Masek M. Attema J.L. Li G. Haddix T. Edwards M.S.B. Hedgehog-Responsive Candidate Cell of Origin for Diffuse Intrinsic Pontine Glioma Proc. Natl. Acad. Sci. USA 2011 108 4453 4458 10.1073/pnas.1101657108 21368213 115. Chen C.C.L. Deshmukh S. Jessa S. Hadjadj D. Lisi V. Andrade A.F. Faury D. Jawhar W. Dali R. Suzuki H. Histone H3.3G34-Mutant Interneuron Progenitors Co-Opt PDGFRA for Gliomagenesis Cell 2020 183 1617 1633.e22 10.1016/j.cell.2020.11.012 33259802 116. Lombard A. Digregorio M. Delcamp C. Rogister B. Piette C. Coppieters N. The Subventricular Zone, a Hideout for Adult and Pediatric High-Grade Glioma Stem Cells Front. Oncol. 2021 10 3197 10.3389/fonc.2020.614930 117. Caretti V. Bugiani M. Freret M. Schellen P. Jansen M. van Vuurden D. Kaspers G. Fisher P.G. Hulleman E. Wesseling P. Subventricular Spread of Diffuse Intrinsic Pontine Glioma Acta Neuropathol. 2014 128 605 607 10.1007/s00401-014-1307-x 24929912 118. Mistry A.M. Mummareddy N. CreveCoeur T.S. Lillard J.C. Vaughn B.N. Gallant J.-N. Hale A.T. Griffin N. Wellons J.C. Limbrick D.D. Association between Supratentorial Pediatric High-Grade Gliomas Involved with the Subventricular Zone and Decreased Survival: A Multi-Institutional Retrospective Study J. Neurosurg. Pediatrics 2020 26 288 294 10.3171/2020.3.PEDS19593 119. Jalali R. Mallick I. Dutta D. Goswami S. Gupta T. Munshi A. Deshpande D. Sarin R. Factors Influencing Neurocognitive Outcomes in Young Patients With Benign and Low-Grade Brain Tumors Treated With Stereotactic Conformal Radiotherapy Int. J. Radiat. Oncol. Biol. Phys. 2010 77 974 979 10.1016/j.ijrobp.2009.06.025 19864079 120. Khatua S. Dhall G. O’Neil S. Jubran R. Villablanca J.G. Marachelian A. Nastia A. Lavey R. Olch A.J. Gonzalez I. Treatment of Primary CNS Germinomatous Germ Cell Tumors with Chemotherapy Prior to Reduced Dose Whole Ventricular and Local Boost Irradiation Pediatric Blood Cancer 2010 55 42 46 10.1002/pbc.22468 20222020 121. Biserova K. Jakovlevs A. Uljanovs R. Strumfa I. Cancer Stem Cells: Significance in Origin, Pathogenesis and Treatment of Glioblastoma Cells 2021 10 621 10.3390/cells10030621 33799798 122. Skoda A.M. Simovic D. Karin V. Kardum V. Vranic S. Serman L. The Role of the Hedgehog Signaling Pathway in Cancer: A Comprehensive Review Bosn. J. Basic Med. Sci. 2018 18 8 20 10.17305/bjbms.2018.2756 29274272 123. Lathia J.D. Mattson M.P. Cheng A. Notch: From Neural Development to Neurological Disorders J. Neurochem. 2008 107 1471 1481 10.1111/j.1471-4159.2008.05715.x 19094054 124. Pierfelice T.J. Schreck K.C. Eberhart C.G. Gaiano N. Notch, Neural Stem Cells, and Brain Tumors Cold Spring Harb. Symp. Quant. Biol. 2008 73 367 375 10.1101/sqb.2008.73.013 19022772 125. Taylor I.C. Hütt-Cabezas M. Brandt W.D. Kambhampati M. Nazarian J. Chang H.T. Warren K.E. Eberhart C.G. Raabe E.H. Disrupting NOTCH Slows Diffuse Intrinsic Pontine Glioma Growth, Enhances Radiation Sensitivity, and Shows Combinatorial Efficacy With Bromodomain Inhibition J. Neuropathol. Exp. Neurol. 2015 74 778 790 10.1097/NEN.0000000000000216 26115193 126. Madhunapantula S.V. Mosca P.J. Robertson G.P. The Akt Signaling Pathway Cancer Biol. Ther. 2011 12 1032 1049 10.4161/cbt.12.12.18442 22157148 127. Faury D. Nantel A. Dunn S.E. Guiot M.-C. Haque T. Hauser P. Garami M. Bognár L. Hanzély Z. Liberski P.P. Molecular Profiling Identifies Prognostic Subgroups of Pediatric Glioblastoma and Shows Increased YB-1 Expression in Tumors J. Clin. Oncol. 2007 25 1196 1208 10.1200/JCO.2006.07.8626 17401009 128. Holland E.C. Celestino J. Dai C. Schaefer L. Sawaya R.E. Fuller G.N. Combined Activation of Ras and Akt in Neural Progenitors Induces Glioblastoma Formation in Mice Nat. Genet. 2000 25 55 57 10.1038/75596 10802656 129. Mackay A. Burford A. Carvalho D. Izquierdo E. Fazal-Salom J. Taylor K.R. Bjerke L. Clarke M. Vinci M. Nandhabalan M. Integrated Molecular Meta-Analysis of 1,000 Pediatric High-Grade and Diffuse Intrinsic Pontine Glioma Cancer Cell 2017 32 520 537.e5 10.1016/j.ccell.2017.08.017 28966033 130. Wu Y.L. Maachani U.B. Schweitzer M. Singh R. Wang M. Chang R. Souweidane M.M. Dual Inhibition of PI3K/AKT and MEK/ERK Pathways Induces Synergistic Antitumor Effects in Diffuse Intrinsic Pontine Glioma Cells Transl. Oncol. 2017 10 221 228 10.1016/j.tranon.2016.12.008 28189993 131. Duchatel R. Jackson E. Patabendige A. Cain J. Tsoli M. Monje M. Alvaro F. Ziegler D. Dun M. Dipg-03. Targeting pi3k using the blood brain barrier penetrable inhibitor, gdc-0084, for the treatment of diffuse intrinsic pontine glioma (dipg) Neuro-Oncology 2019 21 ii68 10.1093/neuonc/noz036.024 132. Chang R. Tosi U. Voronina J. Adeuyan O. Wu L.Y. Schweitzer M.E. Pisapia D.J. Becher O.J. Souweidane M.M. Maachani U.B. Combined Targeting of PI3K and MEK Effector Pathways via CED for DIPG Therapy Neurooncol. Adv. 2019 1 vdz004 10.1093/noajnl/vdz004 32642647 133. Gojo J. Pavelka Z. Zapletalova D. Schmook M.T. Mayr L. Madlener S. Kyr M. Vejmelkova K. Smrcka M. Czech T. Personalized Treatment of H3K27M-Mutant Pediatric Diffuse Gliomas Provides Improved Therapeutic Opportunities Front. Oncol. 2020 9 1436 10.3389/fonc.2019.01436 31998633 134. Mbah N.E. Myers A.L. Chung C. Thompson J.K. Hong H.S. Sajjakulnukit P. Nwosu Z.C. Shan M. Sweha S.R. Maydan D.D. Therapeutic Targeting of Differentiation State-Dependent Metabolic Vulnerabilities in DIPG bioRxiv 2022 15 482555 10.1101/2022.03.01.482555 135. Andtbacka R.H. Collichio F.A. Amatruda T. Senzer N. Chesney J. Delman K. Spitler L. Puzanov I. Agarwala S. Milhem M. Final Planned Overall Survival (OS) from OPTiM, a Randomized Phase III Trial of Talimogene Laherparepvec (T-VEC) versus GM-CSF for the Treatment of Unresected Stage IIIB/C/IV Melanoma (NCT00769704) J. ImmunoTherapy Cancer 2014 2 P263 10.1186/2051-1426-2-S3-P263 136. Markert J.M. Razdan S.N. Kuo H.C. Cantor A. Knoll A. Karrasch M. Nabors L.B. Markiewicz M. Agee B.S. Coleman J.M. A Phase 1 Trial of Oncolytic HSV-1, G207, given in Combination with Radiation for Recurrent GBM Demonstrates Safety and Radiographic Responses Mol. Ther. 2014 22 1048 1055 10.1038/mt.2014.22 24572293 137. Friedman G.K. Langford C.P. Coleman J.M. Cassady K.A. Parker J.N. Markert J.M. Yancey Gillespie G. Engineered Herpes Simplex Viruses Efficiently Infect and Kill CD133+ Human Glioma Xenograft Cells That Express CD111 J. Neuro-Oncol. 2009 95 199 209 10.1007/s11060-009-9926-0 138. Wakimoto H. Kesari S. Farrell C.J. Curry W.T. Zaupa C. Aghi M. Kuroda T. Stemmer-Rachamimov A. Shah K. Liu T.C. Human Glioblastoma-Derived Cancer Stem Cells: Establishment of Invasive Glioma Models and Treatment with Oncolytic Herpes Simplex Virus Vectors Cancer Res. 2009 69 3472 3481 10.1158/0008-5472.CAN-08-3886 19351838 139. Josupeit R. Bender S. Kern S. Leuchs B. Hielscher T. Herold-Mende C. Schlehofer J. Dinsart C. Witt O. Rommelaere J. Pediatric and Adult High-Grade Glioma Stem Cell Culture Models Are Permissive to Lytic Infection with Parvovirus H-1 Viruses 2016 8 138 10.3390/v8050138 140. Lang F.F. Conrad C. Gomez-Manzano C. Alfred Yung W.K. Sawaya R. Weinberg J.S. Prabhu S.S. Rao G. Fuller G.N. Aldape K.D. Phase I Study of DNX-2401 (Delta-24-RGD) Oncolytic Adenovirus: Replication and Immunotherapeutic Effects in Recurrent Malignant Glioma J. Clin. Oncol. 2018 36 1419 10.1200/JCO.2017.75.8219 29432077 141. Cobb D.A. de Rossi J. Liu L. An E. Lee D.W. Targeting of the Alpha v Beta 3 Integrin Complex by CAR-T Cells Leads to Rapid Regression of Diffuse Intrinsic Pontine Glioma and Glioblastoma J. ImmunoTherapy Cancer 2022 10 e003816 10.1136/jitc-2021-003816 35210306 142. Martínez-Vélez N. Garcia-Moure M. Marigil M. González-Huarriz M. Puigdelloses M. Gallego Pérez-Larraya J. Zalacaín M. Marrodán L. Varela-Guruceaga M. Laspidea V. The Oncolytic Virus Delta-24-RGD Elicits an Antitumor Effect in Pediatric Glioma and DIPG Mouse Models Nat. Commun. 2019 10 2235 10.1038/s41467-019-10043-0 31138805 143. Li J. Meng Q. Zhou X. Zhao H. Wang K. Niu H. Wang Y. Gospel of Malignant Glioma: Oncolytic Virus Therapy Gene 2022 818 146217 10.1016/j.gene.2022.146217 35093451 144. Wang Z. Guo X. Gao L. Wang Y. Guo Y. Xing B. Ma W. Classification of Pediatric Gliomas Based on Immunological Profiling: Implications for Immunotherapy Strategies Mol. Ther. Oncolytics 2021 20 34 10.1016/j.omto.2020.12.012 33575469 145. Friedman G.K. Johnston J.M. Bag A.K. Bernstock J.D. Li R. Aban I. Kachurak K. Nan L. Kang K.-D. Totsch S. Oncolytic HSV-1 G207 Immunovirotherapy for Pediatric High-Grade Gliomas N. Engl. J. Med. 2021 384 1613 1622 10.1056/NEJMoa2024947 33838625 146. Chastkofsky M.I. Pituch K.C. Katagi H. Zannikou M. Ilut L. Xiao T. Han Y. Sonabend A.M. Curiel D.T. Bonner E.R. Mesenchymal Stem Cells Successfully Deliver Oncolytic Virotherapy to Diffuse Intrinsic Pontine Glioma Clin. Cancer Res. 2021 27 1766 1777 10.1158/1078-0432.CCR-20-1499 33272983

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092425 jcm-11-02425 Article Comparing the Time-Dependent Evolution of Microcirculation in Gracilis vs. ALT Flaps Using Laser-Doppler Flowmetry and Tissue-Spectrometry Moellhoff Nicholas 1† https://orcid.org/0000-0002-4656-3808 Heidekrueger Paul I. 2† Frank Konstantin 1 Pistek Svenja 1 Alt Verena 1 Giunta Riccardo E. 1 Ehrl Denis 1* Innocenti Marco Academic Editor 1 Division of Hand, Plastic and Aesthetic Surgery, University Hospital, Ludwig Maximilian University of Munich, 81377 Munich, Germany; nicholas.moellhoff@med.uni-muenchen.de (N.M.); konstantin.frank@med.uni-muenchen.de (K.F.); svenja.pistek@campus.lmu.de (S.P.); verena.alt@med.uni-muenchen.de (V.A.); riccardo.giunta@med.uni-muenchen.de (R.E.G.) 2 Centre of Plastic, Aesthetic, Hand and Reconstructive Surgery, University of Regensburg, 93053 Regensburg, Germany; paul@heidekrueger.net * Correspondence: denis.ehrl@med.uni-muenchen.de; Tel.: +49-4400-73502 † These authors contributed equally to this work. 26 4 2022 5 2022 11 9 242512 3 2022 24 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Postoperative free flap monitoring is considered a key component of care after microsurgical reconstruction. To achieve successful flap salvage after surgical revision, early recognition of vascular compromise is required. The aim of this study was to assess and compare the time-dependent evolution of microcirculation in gracilis muscle (GM) and anterolateral thigh (ALT) flaps. This study included continuous measurements of blood flow (flow), hemoglobin oxygenation (SO2) and the relative amount of hemoglobin (rHb) using laser-doppler flowmetry and tissue-spectrometry (O2C, LEA Medizintechnik, Gießen, Germany) over a time-period of 72 h. Microcirculation was assessed in a total of 66 viable free flaps (GM n = 40; ALT n = 26). A statistically significant positive correlation between time post-anastomosis and microvascular flow was found for both GM and ALT flaps with rs = 0.384 (p < 0.001) and rs = 0.178 (p = 0.015), respectively. No significant positive or negative correlations between time post-anastomosis and SO2 were found for both GM and ALT flaps with rs = 0.052 (p = 0.387) and rs = −0.018 (p = 0.805), respectively. Overall, a significant negative correlation between time post-anastomosis and rHb was found for GM flaps with rs = −0.140 (p = 0.019). For ALT flaps, no significant positive or negative correlation was found with rs = −0.011 (p = 0.887). Microcirculation differs in different flap entities, and surgeons should be aware of these differences in order to correctly evaluate and classify the values of flow, SO2 and rHb obtained when using the O2C device for postoperative monitoring. microvascular flow O2C anastomosis free flap microsurgery ==== Body pmc1. Introduction Postoperative free flap monitoring is considered a key component of postoperative care after microsurgical reconstruction performed by both plastic surgeons and surgical nurses. Early recognition of vascular compromise is essential, in order to achieve successful flap salvage after surgical revision [1]. In addition to clinical monitoring of color, capillary refill time, turgor and temperature, technical devices exist to reduce human error and to objectify the status of free flap perfusion by measuring microvascular flow (flow), hemoglobin oxygenation (SO2) or the relative amount of hemoglobin (rHb) in the capillary bed [2,3,4]. Previously, our study group investigated the microcirculation of viable free flaps using laser-doppler flowmetry and tissue-spectrometry [5]. Continuous measurements over a time period of 72 h post-anastomosis revealed distinct perfusion dynamics, which can be related to the physicochemical mechanisms such as vasodilatation, hyperemia and increased oxygen consumption encountered during ischemia and reperfusion [3,4,6]. It was shown that overall, mean values of flow increased significantly over time, while SO2 showed a decreasing trend line and rHB remained constant throughout the study period. However, a main limitation of the study was the heterogeneity of free flaps investigated, including fasciocutaneous, musculocutaneous and muscle flaps. Importantly, it was acknowledged that each flap entity might have an individual hemodynamic profile. This can be related to rheologic effects of different tissue composition, as well as differences in vascular supply patterns and variability in vessel calibers [7,8,9,10,11,12,13]. Exemplary, according to Mathes and Nahai, free muscle, musculocutaneous and fasciocutaneous flaps can be categorized into different groups depending on their vascular supply [14]. The gracilis muscle (GM) flap is considered a type II flap, as it is supplied by a dominant, and one (or more) minor pedicles [14]. The anterolateral thigh (ALT) flap is considered a type B or type C flap, with a septocutaneous or musculocutaneous perforator [15]. Following these different categorizations, there might also be differences in the parameters of microcirculation measured between different free flap entities. Hence, the aim of this study was to assess and compare the time-dependent evolution of microcirculation of two frequently utilized free flaps, namely GM and ALT flaps, using continuous measurements of laser-doppler flowmetry and tissue-spectrometry over a time-period of 72 h post-anastomosis. 2. Materials and Methods 2.1. Study Design This study was designed as a prospective single-center study to compare the evolution of microcirculation in two different flap types, gracilis muscle (GM) flaps and anterolateral thigh (ALT) flaps. The study was conducted at a level 1 hospital in Germany (University Hospital, LMU Munich) between 2020 and 2022. All free flap surgeries were performed by the senior author (D.E.). Ethical approval was granted by the local institutional review board (IRB protocol number: 20-549). 2.2. Sample Upon availability of the O2C device (LEA Medizintechnik, Gießen, Germany), all patients requiring GM or ALT free flap reconstruction—irrespective of defect etiology and localization—treated at the Division of Hand, Plastic and Aesthetic Surgery of the University Hospital, LMU Munich were included in the study. Patients’ incapable of understanding the aims and scope of the study and/or under the age of 18 were excluded from the study. No further exclusion criteria were defined. As this study investigated microcirculation in viable flaps only, flaps with major complications (defined as total flap loss or partial flap loss of >10%), and flaps requiring emergent revision surgery (i.e., arterial or venous thrombosis or hematoma) were excluded from data analysis. In order to compare a muscle flap (GM) with a fasciocutaneous flap (ALT) only, ALT flaps incorporating vastus lateralis muscle (myocutaneous vastus lateralis flaps) were also excluded from analysis. 2.3. Assessments and Outcomes Microcirculation was continuously measured using the O2C device and the LFx37 probe (both LEA Medizintechnik, Gießen, Germany) according to a previously described protocol [5]. Briefly, the O2C device measures blood flow (flow), hemoglobin oxygenation (SO2) and the relative amount of hemoglobin (rHb) within the capillary-venous compartment of the vascular tree using a laser-doppler flowmetry and a tissue-spectrometry-unit [16]. For GM flaps, the probe was sutured directly on to the muscle, while for ALT flaps it was attached to the skin island using medical device proofed double-sided tape. The probe was placed as far distally from the vascular pedicle as possible. The time of microvascular anastomosis was noted, and measurements commenced immediately postoperatively for a period of 72 h post-anastomosis. Measurements were performed continuously and were only interrupted occasionally for patient transportation, probe dislocation, or to correct signal interferences due to blood or wound exudate collecting underneath the measuring probe. 2.4. Data Extraction and Statistical Analysis For each free flap, mean values of microvascular flow, SO2 and rHb were extracted in hourly intervals over a period of 72 h post-anastomosis, using the O2CevaTime Software (Version No. 28.3, LEA Medizintechnik, Gießen, Germany). The time-dependent course of the variables was analyzed based on the following reference times: 1, 3, 6, 12, 24, 36, 48, 60, and 72 h post-anastomosis. Data are presented as means with respective standard deviation (1 SD). Data were tested for normal distribution using the Shapiro–Wilk test and by visual inspection of normal Q-Q plots. Data were normally distributed, and differences between the two groups (GM vs. ALT) at the respective time intervals were assessed using the unpaired Student’s t-test. A Spearman’s rank-order correlation was run to assess the relationship between the time post-anastomosis at the respective reference times and the three parameters of microcirculation (flow, SO2, rHb). For all analyses, the level of statistical significance was set at p < 0.05 to guide conclusions. All statistical analysis was conducted in SPSS Statistics 28 (IBM, Armonk, NY, USA). 3. Results Data of a total of 161 free flaps were extracted using the O2C device and appropriate software. This study then included continuous measurements of a total of 66 viable free flaps (GM n = 40; ALT n = 26) performed in 66 patients (43 male, 23 female) with a mean age of 60.94 ± 17.19 years (GM: 58.78 ± 17.34 years vs. ALT: 64.27 ± 16.74 years). 3.1. Microvascular Flow For both GM and ALT flaps, mean values of microvascular flow showed a strong increase over time after anastomosis (Figure 1). For GM flaps, values increased from 86.31 ± 24.98 A.U. to 145.77 ± 43.26 A.U., as measured from 1 to 72 h post-anastomosis. Within the same time period, flow increased from 106.67 ± 50.71 A.U. to 140.41 ± 48.64 A.U. in the ALT group. Peak measurements for flow were reached at 72 h post-anastomosis in the GM group (145.77 ± 43.26 A.U.), whereas they were reached after 48 h in the ALT group (149.84 ± 58.40 A.U.). Overall, microvascular flow in GM and ALT flaps evolved similarly over time, with no significant differences between mean values of flow at any of the investigated time intervals (Table 1). A statistically significant positive correlation between time post-anastomosis and microvascular flow was found for both GM and ALT flaps with rs = 0.384 (p< 0.001) and rs = 0.178 (p = 0.015), respectively. 3.2. Hemoglobin Oxygenation (SO2) In the GM group, mean values of SO2 remained fairly constant over time. SO2 values evolved from 52.69 ± 25.70 A.U. at 1 h post-anastomosis to 54.46 ± 21.45 A.U. at 72 h post-anastomosis. A decreasing trend was found for SO2 values in the ALT group, as mean measurements at 1 h post-anastomosis were 45.83 ± 35.47 A.U. and decreased down to 34.41 ± 19.35 A.U. However, no significant positive or negative correlations between time post-anastomosis and SO2 were found for both GM and ALT flaps with rs = 0.052 (p = 0.387) and rs = −0.018 (p = 0.805), respectively. Overall, SO2 values in GM flaps were higher as compared to ALT flaps, with results differing significantly at 3, 12, 18, 24, 36, 48, 60, and 72 h post-anastomosis (all p < 0.05) (Table 2, Figure 2). 3.3. Relative Amount of Hemoglobin (rHb) Values for rHb remained stable for GM flaps post-anastomosis. At 1 h post-anastomosis, values were as high as 48.44 ± 22.08 A.U., reaching 48.15 ± 16.30 A.U. at 72 h post-anastomosis. Values for ALT flaps increased from 32.67 ± 7.26 A.U. to 38.94 ± 20.98 A.U. over the investigated study period. Overall, a small but significant negative correlation between time post-anastomosis and rHb was found for GM flaps with rs = −0.140 (p = 0.019). For ALT flaps, no significant positive or negative correlation was found with rs = −0.011 (p = 0.887). Similar to the results presented for SO2, overall rHb values in GM flaps were higher as compared to ALT flaps, reaching significance at 3, 24, 36 and 60 h post-anastomosis (all p < 0.05) (Table 3, Figure 3). 4. Discussion This study assessed and compared the physiological perfusion dynamics in a patient cohort receiving two different types of free flaps using laser-doppler flowmetry and tissue-spectrometry measurements provided by the O2C monitoring device (LEA Medizintechnik, Gießen, Germany). For the first time, the data show parallels and differences in microvascular flow, SO2 and rHb between GM and ALT flaps in the first 72 h post-anastomosis. The results of this study thus add further information regarding the time-dependent course of physiological microcirculation after re-anastomosis, and provide guidance to surgeons using the O2C device for postoperative flap monitoring as to what to expect in the early postoperative period. To summarize, the data show that microvascular flow developed comparably in GM and ALT flaps, both increasing over the study period with a statistically significant positive correlation between time post-anastomosis and microvascular flow. This is in line with pooled data of various flap types presented by our study group previously, which revealed that flow significantly increased up to 18 h post-anastomosis, after which peak formation occurred [5]. Interestingly, in GM and ALT flaps the peak measurements for flow were reached at 72 h post-anastomosis, whereas they were reached after 48 h in the ALT group. Increases of microvascular flow post-anastomosis have been attributed to ischemia and reperfusion, which induce hyperemia, vasodilatation, and a decrease of vascular resistance based on physical (sympathectomy) and chemical (accumulation of anaerobic metabolites, inflammatory proteins, reactive oxygen species) effects [11,17,18,19,20,21,22]. Free flap vascular territories (angiosomes) are three-dimensional tissue units supplied by a distinct source artery [23]. Adjacent vascular territories are connected via choke vessels. This is of significant relevance in free flap surgery, as the axial arterial supply of angiosomes located in proximity to the territory supplied by the main (perforator-) pedicle might be cut or ligated during flap harvesting. Adequate tissue perfusion is then dependent on blood inflow via connecting choke vessels [24,25]. The impact of choke vessel dilation on the parameters of microcirculation remains to be established. Studies have determined that choke vessel dilation is not an immediate consequence of perforator ligation, but occurs between 24 and 72 h after flap elevation [24,26]. Dilation is connected to arterial inflow, with increased blood flow supporting choke vessel dilation [24]. The increase of microvascular flow observed in both flap entities in this study over 72 h might therefore enable choke vessel dilation, thereby decreasing vascular resistance and promoting free flap viability. Differences between the two investigated groups were found with regard to SO2 and rHb values, as both were significantly higher in GM flaps during the investigated time periods. Over time, a decreasing trend was found for SO2 values, together with an increasing trend for rHb values in the ALT group, without, however, showing a statistically significant correlation over time. In the GM group, overall values for SO2 and rHb remained constant, with a small but significant negative correlation between time post-anastomosis and rHb. Hölzle et al. investigated microcirculation in radial forearm flaps, which—similar to the ALT flap—is a fasciocutaneous flap [3]. Different from our approach, they performed interrupted measurements of flow, SO2 and rHb at 1, 3, 7 and 14 days postoperatively. In line with the presented data, they found an increase of flow post-anastomosis, attributed to a hyperemic response to tissue hypoxia. In addition, they described stable values for SO2 after anastomosis, which decreased by the third postoperative day, while hemoglobin concentration remained stable [3]. Similarly, while Spearman´s correlation showed no significant negative trend between time post-anastomosis and SO2, the absolute values of SO2 in the ALT group decreased from 45.83 ± 35.47 A.U. to 34.41 ± 19.35 A.U in our study population. Contrary, absolute values of rHb increased from 32.67 ± 7.26 A.U. to 38.94 ± 20.98 A.U. over the 72 h follow-up in ALT flaps, although once more Spearman´s Rho showed no significant correlation. In a follow-up study, Hölzle et al. compared radial forearm flaps with fibular, perforator and ALT flaps, and found significantly higher SO2 and flow values in forearm flaps [4]. They attributed this to the fact that the radial forearm is supplied by many closely meshed fasciocutaneous vessels, while the lateral leg is supplied by single septocutaneous or myocutaneous vessels [4]. From our experience, probe placement has a strong impact on the measurement parameters. Placing the probe at a different location, and with altered pressure, can largely affect values for flow, SO2 and rHb. It is hard to believe that in the aforementioned studies the probe was placed at the exact same location at every measuring time point of the interrupted measurements. Therefore, the values might have differed between the investigated time points solely due to inconsistent probe placement. Hence, we consider the standardized and continuous probe placement that we performed as a significant strength of our study. There is a scarcity of studies comparing fasciocutaneous with muscle flaps with regard to the time-dependent evolution of the parameters relevant for microcirculation with the O2C device. Rahmanian-Schwarz et al. demonstrated superior thermoregulation in LDM flaps compared to ALT flaps in the postoperative course when exposed to hot and cold water, as assessed by measuring microvascular flow and velocity using the O2C device [27]. While not entirely relevant to our study, the data underline differences in postoperative microcirculation with regard to the type of free flap transplanted and show significant differences depending on the type of tissue incorporated in the flap. The authors speculate that the presence of the muscle in the LDM flap improves neural and vascular regeneration, thus offering better conditions for thermoregulation [27]. For both flaps, measurements were however performed on the skin island, as the LDM flap was harvested as a myocutaneous flap. Therefore, it remains unanswered what measurements directly on the muscle, such as those performed in GM flaps in our study, would have revealed. The results presented in our study demonstrate higher SO2 and rHb values in GM flaps, compared to ALT flaps, while no significant differences were found for microvascular flow. In our opinion, this could be the result of higher oxygen consumption in ALT flaps or greater capillary oxygen supply in GM flaps. Potentially, tissue hypoxia is more pronounced in fasciocutaneous compared to muscle flaps. This could result in higher post-anastomosis tissue oxygen consumption in ALT flaps, as compared to GM flaps, potentially explaining the differences in SO2. However, it is known that muscle tissue is less resistant to ischemia, compared to skin and fascia [28,29,30]. Therefore, it may be speculated that due to unspecified local regulatory mechanisms, intracapillary hemoglobin oxygenation could be increased in GM flaps. Thus, further studies investigating the ischemia tolerance of different flap entities are warranted and could potentially provide an explanation for the findings of this study. From a clinical perspective, we observe higher levels of postoperative edema in patients receiving GM flaps, compared to ALT flaps. This is in line with literature, where postoperative swelling in muscle flaps is frequently described, resolving only after several months postoperatively in many cases [31,32,33]. This, in turn, could explain the higher levels of rHb found in GM flaps, as outflow in the capillary tree could be affected by the increased swelling. Ischemia-reperfusion injury causes leukocyte infiltration, inflammation, and an increase in interstitial edema and apoptosis [22,34]. Thus, postoperative swelling in muscular tissue is likely to be elevated, as it is more prone to ischemia in the first place [28,29,30]. Future studies should investigate the level of postoperative edema using standardized measuring devices such as three-dimensional imaging, to further elucidate the impact of postoperative edema on the parameters of microcirculation in different flap types. This study marks the beginning of our effort in defining hemodynamic profiles in different flap entities. Next, given sufficient case numbers, investigation of further flap entities will follow. In addition, the question remains whether an understanding of physiological perfusion dynamics in different free flaps using the O2C device can ultimately change clinical outcomes and optimize clinical decision making with regard to emergent revision surgery upon vascular compromise. This remains to be elucidated in due course and can be considered a major shortcoming of this study. In addition, the impact of individual patient characteristics and co-morbidities on the parameters of microcirculation still remains elusive and needs to be addressed in the future. A further limitation is the lack of long-term data acquisition. It would be interesting to investigate the evolution of microcirculation in different flap entities also over an extended time-period, i.e., 3, 6 and 12 months postoperatively, to evaluate the impact of neovascularization and neoangiogenesis, making blood supply independent of the vascular pedicle. Lastly, the method of probe fixation (suture vs. tape) might influence the measurements obtained. However, we do believe that firm contact of the probe with the tissue is essential for reliable read-outs and the impact of the type of fixation is likely to be negligible if firm contact is achieved. 5. Conclusions This study provides data to further define the hemodynamic profile and time-dependent perfusion dynamics in GM and ALT flaps post-anastomosis. Microcirculation differs in different flap entities and surgeons should be aware of these differences, in order to correctly evaluate and classify the values of flow, SO2 and rHb obtained when using the O2C device for postoperative monitoring. Author Contributions Conceptualization, N.M. and D.E.; methodology, D.E. and N.M.; software, N.M. and S.P.; validation, D.E., N.M.; formal analysis, N.M., K.F., V.A., S.P.; investigation, D.E., N.M.; resources, R.E.G.; data curation, N.M., V.A., S.P.; writing—original draft preparation, N.M., D.E., P.I.H.; writing—review and editing, P.I.H., R.E.G., V.A., S.P., K.F.; visualization, N.M.; supervision, D.E.; project administration, D.E. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the medical faculty of LMU Munich (protocol number: 20-549, 26/08/2020). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Restrictions apply to the availability of these data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Line graph comparing microvascular blood flow (flow) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. Figure 2 Line graph comparing hemoglobin oxygenation (SO2) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. Figure 3 Line graph comparing relative amount of hemoglobin (rHb) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. jcm-11-02425-t001_Table 1 Table 1 Detailed analysis of the evolution of microvascular blood flow (flow) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. Time Post-Anastomosis (Hours) Gracilis Muscle ALT p-Value Mean Flow (A.U.) Standard Deviation Mean Flow (A.U.) Standard Deviation 1 86.31 24.98 106.67 50.71 0.217 3 109.3 41.93 116.12 39.92 0.583 6 113.36 38.85 118.65 45.86 0.644 12 120.74 40.38 132.92 44.70 0.275 18 139.24 41.02 134.70 36.98 0.672 24 137.34 39.39 132.22 41.60 0.667 36 142.35 36.74 132.75 38.33 0.365 48 138.41 32.11 149.84 58.40 0.398 60 139.88 38.06 138.22 50.70 0.904 72 145.77 43.26 140.41 48.64 0.756 jcm-11-02425-t002_Table 2 Table 2 Detailed analysis of the evolution of hemoglobin oxygenation (SO2) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. Time Post-Anastomosis (hours) Gracilis Muscle ALT p-Value Mean SO2 (A.U.) Standard Deviation Mean SO2 (A.U.) Standard Deviation 1 52.69 25.70 45.83 35.47 0.62 3 58.73 16.62 41.41 27.56 0.008 6 47.91 21.34 35.26 27.03 0.056 12 56.00 17.05 33.36 24.52 <0.001 18 60.32 18.86 34.43 24.71 <0.001 24 60.94 17.95 31.78 18.84 <0.001 36 59.53 17.14 37.70 21.41 <0.001 48 56.59 17.39 35.53 20.10 <0.001 60 54.58 17.58 33.17 23.15 0.001 72 54.46 21.45 34.41 19.35 0.012 jcm-11-02425-t003_Table 3 Table 3 Detailed analysis of the evolution of relative amount of hemoglobin (rHb) in gracilis muscle and ALT free flaps over a period of 72 h post-anastomosis. Time Post-Anastomosis (Hours) Gracilis Muscle ALT p-Value Mean rHb (A.U.) Standard Deviation Mean rHb (A.U.) Standard Deviation 1 48.44 22.08 32.67 7.26 0.106 3 54.03 17.03 34.47 15.19 <0.001 6 48.91 16.47 40.35 23.70 0.116 12 48.51 15.99 38.24 24.03 0.051 18 47.18 14.93 38.83 24.10 0.112 24 48.72 13.69 36.39 14.02 0.004 36 47.91 13.22 33.65 15.21 0.001 48 45.44 13.80 38.68 14.82 0.12 60 43.88 13.31 34.61 15.91 0.047 72 48.15 16.30 38.94 20.98 0.201 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Smit J.M. Acosta R. Zeebregts C.J. Liss A.G. Anniko M. Hartman E.H.M. Early reintervention of compromised free flaps improves success rate Microsurgery 2007 27 612 616 10.1002/micr.20412 17868141 2. Rothenberger J. Amr A. Schaller H.-E. Rahmanian-Schwarz A. Evaluation of a non-invasive monitoring method for free flap breast reconstruction using laser doppler flowmetrie and tissue spectrophotometry Microsurgery 2013 33 350 357 10.1002/micr.22096 23436443 3. Hölzle F. Loeffelbein D.J. Nolte D. Wolff K.-D. Free flap monitoring using simultaneous non-invasive laser Doppler flowmetry and tissue spectrophotometry J. Cranio-Maxillofac. Surg. 2006 34 25 33 10.1016/j.jcms.2005.07.010 4. Hölzle F. Rau A. Loeffelbein D. Mücke T. Kesting M. Wolff K.-D. Results of monitoring fasciocutaneous, myocutaneous, osteocutaneous and perforator flaps: 4-year experience with 166 cases Int. J. Oral Maxillofac. Surg. 2010 39 21 28 10.1016/j.ijom.2009.10.012 19944567 5. Moellhoff N. Gernert C. Frank K. Giunta R.E. Ehrl D. The 72-Hour Microcirculation Dynamics in Viable Free Flap Reconstructions J. Reconstr. Microsurg. 2022 10.1055/s-0042-1742733 6. Cai Z.G. Zhang J. Zhang J.G. Zhao F.Y. Yu G.Y. Li Y. Ding H.S. Evaluation of near infrared spectroscopy in monitoring postoperative regional tissue oxygen saturation for fibular flaps J. Plast. Reconstr. Aesthetic Surg. 2008 61 289 296 10.1016/j.bjps.2007.10.047 18060850 7. Lorenzetti F. Suominen S. Tukiainen E. Kuokkanen H. Suominen E. Vuola J. Asko-Seljavaara S. Evaluation of Blood Flow in Free Microvascular Flaps J. Reconstr. Microsurg. 2001 17 163 168 10.1055/s-2001-14347 11336147 8. Begue T. Masquelet A.C. Nordin J.Y. Anatomical basis of the anterolateral thigh flap (25.05.1990) Surg. Radiol. Anat. 1990 12 311 313 10.1007/BF01623713 1982906 9. Yamada S. Okamoto H. Sekiya I. Wada I. Kobayashi M. Goto H. Mizutani J. Nozaki M. Hayashi K. Murakami S. Anatomical basis of distally based anterolateral thigh flap J. Plast. Surg. Hand Surg. 2013 48 197 200 10.3109/2000656X.2013.859146 24256309 10. Deng C. Nie K. Jin W. Li H. Li S. Wu B. Wang D. Wei Z. Is the Oblique Branch a Preferable Vascular Pedicle for Anterolateral Thigh Free Flaps? J. Reconstr. Microsurg. 2018 34 478 484 10.1055/s-0038-1639370 29605952 11. Lorenzetti F. Salmi A. Ahovuo J. Tukiainen E. Asko-Seljavaara S. Postoperative changes in blood flow in free muscle flaps: A prospective study Microsurgery 1999 19 196 199 10.1002/(SICI)1098-2752(1999)19:4<196::AID-MICR6>3.0.CO;2-5 10336249 12. Mücke T. Rau A. Merezas A. Kanatas A. Mitchell D. Wagenpfeil S. Wolff K.-D. Steiner T. Changes of perfusion of microvascular free flaps in the head and neck: A prospective clinical study Br. J. Oral Maxillofac. Surg. 2014 52 810 815 10.1016/j.bjoms.2014.07.001 25149324 13. Figus A. Ramakrishnan V. Rubino C. Hemodynamic Changes in the Microcirculation of DIEP Flaps Ann. Plast. Surg. 2008 60 644 648 10.1097/SAP.0b013e318145be31 18520200 14. Mathes S.J. Nahai F. Classification of the vascular anatomy of muscles: Experimental and clinical correlation Plast. Reconstr. Surg. 1981 67 177 187 10.1097/00006534-198167020-00007 7465666 15. Mathes S.J. Nahai F. Reconstructive Surgery: Principles, Anatomy & Technique Churchill Livingstone London, UK 1997 16. Available online: http://www.lea.de/eng/indexe.html (accessed on 20 February 2022) 17. Siemionow M. Andreasen T. Chick L. Lister G. Effect of muscle flap denervation on flow hemodynamics: A new model for chronic in vivo studies Microsurgery 1994 15 891 894 10.1002/micr.1920151213 7707932 18. Chen L.-E. Seaber A.V. Bossen E. Urbaniak J.R. The effect of acute denervation on the microcirculation of skeletal muscle: Rat cremaster model J. Orthop. Res. 1991 9 266 274 10.1002/jor.1100090215 1992076 19. Rosenberry R. Chung S. Nelson M.D. Skeletal Muscle Neurovascular Coupling, Oxidative Capacity, and Microvascular Function with ‘One Stop Shop’ Near-infrared Spectroscopy J. Vis. Exp. 2018 20 e57317 10.3791/57317 20. Nasir S. Baykal B. Altuntaş S. Aydin M.A. Hemodynamic Differences in Blood Flow between Free Skin and Muscles Flaps: Prospective Study J. Reconstr. Microsurg. 2009 25 355 360 10.1055/s-0029-1215522 19396745 21. Hanasono M. Ogunleye O. Yang J. Hartley C. Miller M. Changes in Blood Velocity Following Microvascular Free Tissue Transfer J. Reconstr. Microsurg. 2009 25 417 424 10.1055/s-0029-1223850 19593731 22. Eisenhardt S.U. Schmidt Y. Karaxha G. Iblher N. Penna V. Torio-Padron N. Stark G.B. Bannasch H. Monitoring molecular changes induced by ischemia/reperfusion in human free muscle flap tissue samples Ann. Plast. Surg. 2012 68 202 208 10.1097/SAP.0b013e3181f77ba5 21508818 23. Taylor G.I. Palmer J.H. The vascular territories (angiosomes) of the body: Experimental study and clinical applications Br. J. Plast. Surg. 1987 40 113 141 10.1016/0007-1226(87)90185-8 3567445 24. Miyamoto S. Minabe T. Harii K. Effect of Recipient Arterial Blood Inflow on Free Flap Survival Area Plast. Reconstr. Surg. 2008 121 505 513 10.1097/01.prs.0000299185.32881.55 18300969 25. Rozen W.M. Ashton M.W. Le Roux C.M. Pan W.-R. Corlett R.J. The perforator angiosome: A new concept in the design of deep inferior epigastric artery perforator flaps for breast reconstruction Microsurgery 2010 30 615 622 10.1002/micr.20684 19582823 26. Dhar S.C. Taylor G.I. The Delay Phenomenon: The Story Unfolds Plast. Reconstr. Surg. 1999 104 2079 2091 10.1097/00006534-199912000-00021 11149772 27. Rahmanian-Schwarz A. Schiefer J.L. Amr A. Rothenberger J. Schaller H.-E. Hirt B. Thermoregulatory response of anterolateral thigh flap compared with latissimus dorsi myocutaneous flap: An evaluation of flaps cutaneous flow and velocity due to thermal stress Microsurgery 2011 31 650 654 10.1002/micr.20950 22009691 28. Oksman D. de Almeida O.M. de Arruda R.G. de Almeida M.L.M. Do Carmo F.S. Comparative study between fasciocutaneous and myocutaneous flaps in the surgical treatment of pressure ulcers of the sacral region JPRAS Open 2018 16 50 60 10.1016/j.jpra.2017.12.001 32158810 29. Wolff K.D. Stiller D. Ischemia tolerance of free-muscle flaps: An NMR-spectroscopic study in the rat Plast. Reconstr. Surg. 1993 91 485 491 10.1097/00006534-199303000-00015 8438020 30. Wang W. Ong A. Vincent A.G. Shokri T. Scott B. Ducic Y. Flap Failure and Salvage in Head and Neck Reconstruction Semin. Plast. Surg. 2020 34 314 320 10.1055/s-0040-1721766 33380919 31. Chim H. Zoghbi Y. Nugent A.G. Kassira W. Askari M. Salgado C.J. Immediate application of vacuum assisted closure dressing over free muscle flaps in the lower extremity does not compromise flap survival and results in decreased flap thickness Arch. Plast. Surg. 2018 45 45 50 10.5999/aps.2016.01977 29316773 32. Sakamoto Y. Takahara T. Ota Y. Aoki T. Yamazaki H. Otsuru M. Takahashi M. Aoyama K.-I. Kaneko A. Kawada S. MRI analysis of chronological changes in free-flap volume in head and neck reconstruction by volumetry Tokai J. Exp. Clin. Med. 2014 39 44 50 24733597 33. Eisenhardt S.U. Schmidt Y. Thiele J.R. Iblher N. Penna V. Torio-Padron N. Stark G.B. Bannasch H. Negative pressure wound therapy reduces the ischaemia/reperfusion-associated inflammatory response in free muscle flaps J. Plast. Reconstr. Aesthet. Surg. 2012 65 640 649 10.1016/j.bjps.2011.11.037 22137686 34. Eisenhardt S.U. Momeni A. Iblher N. Penna V. Schmidt Y. Torio N. Stark G.B. Bannasch H. The use of the vacuum-assisted closure in microsurgical reconstruction revisited: Application in the reconstruction of the posttraumatic lower extremity J. Reconstr. Microsurg. 2010 26 615 622 10.1055/s-0030-1267378 20922656

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095241 ijms-23-05241 Article One AP2/ERF Transcription Factor Positively Regulates Pi Uptake and Drought Tolerance in Poplar Chen Ningning † Qin Jiajia † Tong Shaofei † Wang Weiwei † https://orcid.org/0000-0002-2955-6155 Jiang Yuanzhong * Miura Kenji Academic Editor Shabala Sergey Academic Editor Key Laboratory for Bio-Resources and Eco-Environment of Ministry of Education, College of Life Science, Sichuan University, Chengdu 610065, China; chenn130@foxmail.com (N.C.); qjj19980808@163.com (J.Q.); tongshaofei@foxmail.com (S.T.); wangww_infor@163.com (W.W.) * Correspondence: jyz88623@126.com † These authors contributed equally to this work. 08 5 2022 5 2022 23 9 524105 4 2022 03 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Drought decreases the inorganic phosphate (Pi) supply of soil, resulting in Pi starvation of plants, but the molecular mechanism of how plants, especially the perennial trees, are tolerant to drought stress and Pi starvation, is still elusive. In this study, we identified an AP2/ERF transcription factor gene, PalERF2, from Populus alba var. pyramidalis, and it was induced by both mannitol treatment and Pi starvation. Overexpressing and knocking-down of PalERF2 both enhanced and attenuated tolerance to drought stress and Pi deficiency compared to WT, respectively. Moreover, the overexpression of PalERF2 up-regulated the expression levels of Pi starvation-induced (PSI) genes and increased Pi uptake under drought conditions; however, its RNAi poplar showed the opposite phenotypes. Subsequent analysis indicated that PalERF2 directly modulated expressions of drought-responsive genes PalRD20 and PalSAG113, as well as PSI genes PalPHL2 and PalPHT1;4, through binding to the DRE motifs on their promoters. These results clearly indicate that poplars can recruit PalERF2 to increase the tolerance to drought and also elevate Pi uptake under drought stress. PalERF2 transcriptional regulation drought stress inorganic phosphate starvation Populus National Natural Science Foundation of China32071732 and 31700528 National Key Research and Development Program of China2016YFD0600101 Postdoctoral Science Foundation2017M623037 Fundamental Research Funds for the Central UniversitiesSCU2019D013 This work was supported by National Natural Science Foundation of China (32071732 and 31700528) and the National Key Research and Development Program of China (2016YFD0600101). The project funded was by Postdoctoral Science Foundation (2017M623037) and Fundamental Research Funds for the Central Universities (SCU2019D013). ==== Body pmc1. Introduction The inorganic phosphate (Pi) deficiency impairs plant growth and development [1]. This deficiency compels plants to evolve a series of morphological, physiological, and metabolic adaptations in order to improve Pi mobilization and uptake under low Pi circumstances, including increasing the activity of high-affinity Pi transporters, the induction of acid phosphatases (APases), and accumulation of anthocyanins [2,3]. In addition, the phosphorus cycling in woody plants may be different from herbaceous plants, because they experience seasonal change and the cycling growth may affect the dynamic changes of the total phosphorus content [4,5,6]. Drought stress leads to decreasing water uptake by roots, reducing leaf expansion and down-regulating stomatal conductance and causing a decrease in photosynthesis-mediated carbon assimilation [7,8]; it also decreases Pi supply through mineralization and by reducing Pi diffusion and mass flow in the soil [9,10,11]. This drought stress may reduce Pi uptake by influencing the nutrient uptake kinetics by roots [7,8,12] and therefore decrease Pi uptake from the soil and the concentration of phosphorus in plant tissue [13,14,15,16,17]. Pi starvation responses (PSR) of plants involve hundreds of Pi-starvation-induced (PSI) genes like PURPLE ACID PHOSPHATASES (PAPs), PHOSPHATE TRANSPORTERS (PHTs), PHOSPHATE (PHO), PHOSPHATE RESPONSES (PHRs), and PHR-LIKES (PHLs). Among them, PAPs can hydrolyze various phosphorus monoesters and release phosphorus under suitable pH conditions; PHTs can absorb phosphate from soil and redistribute Pi in plants [18,19,20,21,22]. Some PSI transcription factors also respond to dehydration. For instance, PHRs and PHLs belonging to the MYB-CC family have key and redundant functions in regulating plant transcriptional response to Pi starvation [23,24,25]; the ectopic expression of their homolog, TaMYBsm3 of wheat, in Arabidopsis enhances drought tolerance [26]. AtWRKY75 is a positive regulator of Pi absorption through up-regulating the expression levels of AtPHT1;1 and AtPHT1;4 [27]; however, this gene has a negative function in osmotic tolerance [28]. AtMYB2 involves salinity and drought responses [29,30,31] and is a transcriptional activator of the miR399f, which plays a crucial role in Pi homeostasis by repressing PHO2 expression [32,33,34]. In poplars, there were more than 4000 and 9000 genes that showed differentiated expressions upon Pi starvation in roots and leaves under drought stress [35]. Moreover, the phosphate transporter (PHT) genes showed similar differentiated expressions upon drought stress [36,37]. Therefore, there is likely a crosstalk between PSR and dehydration responses. The AP2/ERF superfamily is one of the biggest transcription factor families in plants [38]. The members of this family regulate target genes by binding to the GCC-box and some also can bind to dehydration-response element (DRE) motif [39,40]. The AP2/ERF genes are involved in various biotic and abiotic stress response, including wounding, pathogens, drought, and PSR. For example, AtORA59 integrates JA and ethylene signals to directly enhance the expression of PDF1.2 and increase resistance against the fungus Botrytis cinerea in Arabidopsis [41]. AtTINY regulates brassinosteroid-mediated plant growth and drought responses [42], while NtERF172 confers tobacco more drought tolerance by scavenging H2O2 [43]. In addition, around 22 ERF genes increase expressions in response to Pi starvation in Jatropha curcas [44], and the down-regulation of ERF035 in this plant leads to changed root architecture and biosynthesis of anthocyanins under low Pi conditions [45]. In Arabidopsis, three ERF genes, ERF1, ERF2 and ERF5, were suggested to be likely PHR1 targets [46]. In this study, we identified that PalERF2, an AP2/ERF gene from P. alba var. pyramidalis, was induced by drought stress and Pi starvation. Overexpression of PalERF2 in poplars conferred more tolerance to drought stress and Pi deficiency, whereas knocking-down PalERF2 by RNA interference (RNAi) attenuated tolerance to these two stresses. In addition, we found that the expression levels of PSI genes were up-regulated in the PalERF2 overexpression lines, which resulted in an increase of Pi contents under drought condition, whereas the opposite phenotypes were observed in the PalERF2 RNAi poplars. Moreover, PalERF2 bound to the DRE motifs of the promoters of PalRD20, PalSAG113, PalPHL2, and PalPHT1;4, and, therefore, directly regulated their expressions. Therefore, these findings together suggest that PalERF2 positively regulates the tolerance of poplar to Pi starvation and drought stress. 2. Results 2.1. Identification of a Drought and Low Pi Induced AP2/ERF Gene in P. alba var. pyramidalis A 948bp length DNA fragment was simultaneously isolated from the cDNA pools of P. alba var. pyramidalis treated by both drought and low Pi, respectively. This transcript belongs to an AP2/ERF gene (PAYT003289.1), which is a homolog of AtERF2 (AT5G47220.1) from Arabidopsis. Hence, we termed it as PalERF2. In P. alba var. pyramidalis, PalERF2 protein shares 71% sequence similarity with its closest paralog PAYT035246.1. PalERF2 is a member of the ERF subfamily B3 cluster [47] and contains a typical AP2 DNA-binding domain composed of an α-helix and three β-sheet regions (Figure 1A). Notably, PalERF2 and its homologs share the high identity only of the domain region (Figure 1A). To determine the expression pattern of PalERF2, the expression level of PalERF2 in various tissues of P. alba var. pyramidalis was examined by qRT-PCR. PalERF2 expressed dominantly in the stem, and it had a similar level in young leaf, petiole, and root, but scarcely so in mature leaf (Figure 1B). In addition, we further determined the spatio-temporal expression pattern of PalERF2. Interestingly, both drought and low Pi induced PalERF2 rapidly, and the maximum expression level was 2 days after treatments. However, low Pi treatment mainly induced PalERF2 in root (Figure 1C), while drought-induced PalERF2 was dominant in the shoot (Figure 1D). There are 23 ERF members of B3 cluster in poplar [47]. We chose the seven closest paralogs of PalERF2 and analyzed their expression patterns under drought stress and low Pi condition (Figure S1A). These genes displayed various expression patterns, but no one was similar to PalERF2 (Figure 1C,D and Figure S1B,C). To verify the subcellular localization of PalERF2, we constructed a 35S:PalERF2-GFP expression vector and transiently expressed it in mesophyll protoplasts of poplar. The results showed that the GFP protein as the control was distributed in both the cytoplasm and nucleus, while PalERF2 fused with GFP was only in the nucleus (Figure 1E). 2.2. PalERF2 Is a Positive Regulator of Poplar PSR To determine the function of PalERF2 in tolerance to low Pi condition (10 μM Pi) in poplar, the overexpression lines (PalERF2-OE2 and PalERF2-OE4) and RNAi-mediated gene knock-down lines (PalERF2-RNAi6 and PalERF2-RNAi12) of PalERF2 were obtained (Figure S2A–D), and the transgenic poplars show no significant difference in normal Pi condition (1.25 mM Pi) compared to the wild type (WT) (Figure S2C,D). However, after 4 weeks of growth in liquid MS containing 10 μM Pi, the PalERF2-OE transgenic poplars showed a stronger root system and higher shoot, but the PalERF2-RNAi lines showed attenuated growth in the plant height, leaf, and root system (Figure 2A and Figure S3). Moreover, the Pi contents in the root and shoot of the PalERF2-OE lines were obviously highest, and the PalERF2-RNAi cuttings had the lowest Pi contents in the whole plants. The anthocyanin accumulation is an indicator of low Pi stress degree. Compared to WT, the overexpression of PalERF2 significantly reduced anthocyanin accumulation under Pi starvation, but PalERF2-RNAi poplars accumulated the most anthocyanins (Figure 2B,C). These results indicated that PalERF2 is a positive regulator involved in tolerance to Pi starvation in poplar. To investigate whether overexpression or knocking-down of PalERF2 affects the expression of PSI genes, we analyzed the expression level of these genes in the transgenic and WT plants by qRT-PCR. As shown in Figure 2D, PalPHT1;4, a Pi transporter [20], was up-regulated in overexpression lines. PHL1, PHL2, and PHR1 are considered to be key and function-redundant transcription factors in response to Pi starvation in plants [25], and PalPHL1;1, PalPHL1;2, PalPHR1, and PalPHL2 were strongly upregulated in PalERF2-OE poplars. In addition, the PHO1s [48], such as PalPHO1;H1, PalPHO1;H2, and PalPHO1;H4, which are responsible for transferring Pi to the xylem and ultimately into the stem, were also up-regulated in transgenic plants. However, the above PSI genes are down-regulated in PalERF2-RNAi poplars. SPX3, which encoded a repressor of PSR by interacting with OsPHR2 in rice [49], was up-regulated in overexpressing PalERF2 poplars and down-regulated in PalERF2-RNAi lines. A purple acid phosphatase gene PalPAP17 [50] and a type B monogalactosyldiacylglycerol synthase gene PalMGDG2 [51], showed opposite expression patterns in overexpressing and knocking-down poplars. These results indicated that PalERF2 directly or indirectly regulate some PSI genes. 2.3. PalERF2 Directly Regulated Expression of PalPHT1;4 and PalPHL2 through Binding to the DRE Element in Their Promoters ERF subfamily members can bind to GCC box (5′ AGCCGCC 3′) or dehydration-responsive element (DRE) (5′ A/GCCGAC 3′) [39,40,52,53]. We analyzed the promoters of PSI genes whose expression had been up-regulated in the PalERF2 overexpressing poplars, however, there was no GCC box in these promoters. We found that some of these genes contained DRE or core DRE sequence on their promoters (Figure S4). For example, one and two DRE elements were found in the PalPHR1 and PalMGDG2 promoters, respectively. All promoters of PalPHT1;4, PalPHL2, and PalMGDG2 contain a core DRE sequence (5′ CCGAC 3′). To confirm whether PalERF2 could bind to the DRE elements of these promoters, we chose PalPHT1;4 and PalPHL2 for further confirmation. We determined again that PalERF2 could significantly up-regulate the transcription of their promoters by a dual-luciferase assay (Figure 3A,B). Further ChIP-qPCR indicated that PalERF2 could bind to the promoter regions, harboring DRE elements of the PalPHT1;4 and PalPHL2 in vivo (Figure 3C,D). Subsequent EMSA indicated that PalERF2 bound to DRE element of PalPHT1;4 and PalPHL2 in vitro; such a binding could be impaired by competitors (Figure 3F). Together, these findings suggest that PalERF2 directly and positively regulated PalPHT1;4 and PalPHL2. 2.4. PalERF2 Positively Regulates Drought Stress of Poplar Cuttings To determine the function of PalERF2 in poplar tolerant to drought stress, the cuttings of PalERF2 overexpressing and knocking-down lines were transplanted to and cultivated in the soil. After 3 weeks, these plantlets were withdrawing water for drought treatment. After 5 days of drought treatment, the leaves of PalERF2-RNAi poplars showed more severe dehydration than WT, whereas the leaves of overexpressing poplars had slightly dropped (Figure 4A). Moreover, RNAi plants contained the highest levels of MDA and the least total chlorophyll among three genotypic poplars, in contrast, PalERF2-OE lines had the lowest MDA contents and the highest total chlorophyll contents (Figure 4B,C). These results indicate that the RNAi poplars were most stressed and overexpression lines were most tolerant. Therefore, PalERF2 had a positive function in tolerance of poplars to drought stress. To reveal the influence of PalERF2 on the expression of drought stress-related genes, the qRT-PCR was used for detecting the expression differences of drought stress-related genes in PalERF2 transgenic lines and WT plants. As shown in Figure 4D, the expression level of PalERD5 was down-regulated in PalERF2-OE2 and PalERF-OE4 but up-regulated in PalERF2-RNAi lines compared with WT. Its homolog AtERD5 encodes a mitochondrial proline dehydrogenase and its transcription is repressed by dehydration in Arabidopsis [54]. In addition, four transcription factor genes, PalMYB2, PalMYB96, PalNAC3, and PalNAC19, whose homologs show positive responses to drought and ABA signaling in other plants [55,56,57,58], were also expressed higher in overexpressing plants and lower in RNAi lines compared to WT. PalSAG113 was down-regulated in PalERF2-OE plants and its homolog was found to be a negative regulator of ABA signaling [59]. We also found that a likely gene with the E3 ubiquitin ligase homolog [60], PalPUB23, also decreased expression levels in overexpressing cuttings and up-regulated expression in RNAi poplars. In addition, the expression of PalCPK6 and PalCOR47, whose homologs respond to drought stress [61,62,63], were also up-regulated in overexpression lines and down-regulated in the RNAi lines respectively. We found that the expression of PalRD20 was significantly enhanced in overexpression lines but decreased in the RNAi lines. The homolog of this gene, AtRD20, is a stress-inducible caleosin and participates in drought tolerance in Arabidopsis [64]. These results indicate that PalERF2 up-regulated the expression of the drought-responsive genes and down-regulated the genes that negatively modulate drought response. 2.5. PalERF2 Regulated Expression of PalRD20 and PalSAG113 through Binding to the DRE Motif of Its Promoter To investigate whether PalERF2 directly regulated these drought-related genes, we analyzed promoters of the genes with differential expressions in PalERF2 transgenic lines compared to WT. We found that there was no GCC box, but at least one DRE element or one core DRE motif in promoters of these genes (Figure S5). For instance, the promoters of PalCOR47, PalPUB23, and PalSAG113 had one DRE element, respectively, while the PalRD20 and PalNAC19 promoters contained a core DRE motif, respectively. We hypothesized that PalERF2 could directly regulate the genes containing DRE elements in the promoters. We firstly determined PalERF2 could increase the transcription activity of PalRD20 and PalSAG113 promoters by a dual-luciferase assay. The results showed that PalERF2 significantly enhanced the fluorescence intensity of PalRD20 promoter driven by LUC compared to the control. However, it repressed the expression of LUC driven by PalSAG113 promoter (Figure 5A,B). ChIP-qPCR assay showed that PalERF2 binds to the promoter regions containing DRE elements in PalRD20 and PalSAG113 overexpression lines in vivo (Figure 5C,D). The EMSA assay showed that the DRE element in the promoters of PalRD20 and PalSAG113 could be bound by MBP-PalERF2 fusion protein, and this binding could be taken apart by cold probes in vitro (Figure 5F). Therefore, PalERF2 directly regulates the expression of PalRD20 and PalSAG113 through the DRE element in their promoters. 2.6. Overexpressing PalERF2 Improved Pi Uptake of Poplars and Expression Level of PSI Genes during Drought Stress Because drought stress leads to reducing Pi diffusion and mass flow in the soil, we wondered whether PalERF2 could increase the tolerance to Pi starvation that resulted from drought stress. Therefore, we measured the Pi contents of PalERF2 transgenic poplars before and after drought treatment. Before the drought treatment, overexpressing plants had more abundant Pi contents both in the shoot and root compared to WT, whereas the Pi contents of RNAi lines were lower than that of WT (Figure 6A). Although drought stress decreased Pi contents in all lines and tissues, the PalERF2 overexpression lines contained much more and knocking-down lines had less Pi contents compared to the WT (Figure 6B). In addition, we used qRT-PCR to detect the expression levels of PSI genes after drought treatment, and these genes showed significantly enhanced expression levels in the overexpression lines and decreased expression levels in RNAi lines compared to the WT (Figure 6C). These results indicated that drought stress impairs the Pi uptake capacity of poplar, but up-regulated expression of PalERF2 can rescue Pi absorption when drought stress occurs. 3. Discussion The occurrence of one abiotic stress is usually accompanied by several secondary stresses in plants. For example, water deficiency not only leads to osmotic stress but also reduces Pi uptake in plants [13,14,15,16,17]. The responses of plants to drought stress involve the transcriptional rearrangements of associated genes including a series of PSI genes [65]. For example, the micro-RNA, miR399f modulates plants response to drought, ABA, and salt stresses, and also plays a crucial role in Pi homeostasis by repressing PHO2 expression in Arabidopsis [32,33,34]. The transcriptional activator of the miR399f, AtMYB2 is involved in salinity and drought response [29,30,31]. Therefore, the enhancement of Pi uptake is one of the strategies for plants to adapt to drought-caused Pi starvation. Herein, we revealed that PalERF2 from P. alba var. pyramidalis was induced by mannitol treatment and low Pi condition (Figure 1C,D) and demonstrated it was a positive regulator of tolerance to drought and Pi starvation in poplar (Figure 2 and Figure 4). Stomatal closure indicates a response to drought stress in plants, and thus many genes regulating stomatal movements change the expression in leaf under drought stress [66]. Mannitol treatment simulates drought stress but it does not affect Pi diffusion and mass flow. Our mannitol treatment rapidly induced PalERF2 expression in the shoot of poplar, and overexpression of PalERF2 resulted in more tolerance to drought stress compared to the WT plants (Figure 1D and Figure 4A). PalERF2 directly up-regulated the expression of PalRD20 (Figure 5). In Arabidopsis, RD20 is mainly expressed in leaves, guard cells. and flowers, and positively regulates stomatal closure [64]. This also strengthened ABA signaling through decreasing the transcription of PalSAG113 (Figure 5), a repressor of the ABA pathway [67]. Therefore, PalERF2 was induced rapidly in the shoot in order to close stomata under drought conditions. In addition, the root system is mainly responsible for Pi uptake; thereby, the associated genes prefer to express in the root. For example, a total of 42 PHT genes were identified in another P. trichocarpa, of which 25 PHTs were highly expressed in roots [37]. After Pi starvation treatment, PalERF2 was mainly induced in poplar roots (Figure 1C), and PalERF2 directly and positively regulated the expression of two PSI genes, PalPHL2 and PalPHT1;4, to improve the Pi uptake in poplar (Figure 2 and Figure 3). In Arabidopsis, AtPHL2 functions redundantly with AtPHR1 to control transcriptional responses to Pi starvation and can directly bind to the P1BS elements of PHT1s promoters to regulate expression [25]; the homolog of PalPHT1;4 in Arabidopsis, AtPHT1;4, is the main high-affinity Pi transporter in roots [20]. Therefore, the overexpression of PalERF2 improved the Pi uptake of poplars and enhanced the growth in the Pi starvation environment. These results suggest that the double functions of PalERF2 rely on its induced expressions in specific tissues. Although PalERF2 expression was mainly induced in shoots after 150 mM Mannitol treatment, it was also upregulated in roots (Figure 1D). This implies that PalERF2 can enhance Pi uptake in poplar to some extent under drought condition. Our results of the Pi contents determination of PalERF2 transgenic poplars before and after drought treatment support this conclusion, and some PSI genes like PalPHT1;4 and PalPHL2 showed significantly enhanced expression in PalERF2-OE poplars but decreased expression in the PalERF2-RNAi lines after drought treatment (Figure 6). These results indicate that PalERF2 participates in the drought and Pi starvation stress responses of poplar through tissue-specific transcription networks, but at the same time can enhance the Pi uptake of poplar under drought stress. DRE is bound by the DREB proteins, such as DREB1, DREB2, and CBF1, which belong to a subfamily of the AP2/ERF family [40]. In addition, another subfamily of AP2/ERF members, ERFs, can bind to DRE and GCC box. For instance, AtERF1, AtERF4, and AtEBP exhibit similar binding activities to the DRE and GCC boxes in Arabidopsis [54]. AtERF1B binds to the DRE of RD29B, RD20, and ERD7 promoters to regulate the expressions of these genes under drought and salinity stress [68]. PalERF2 is a member of the ERF subfamily, and overexpressing or knocking-down this gene thus influences the expression levels of drought-responsive gene PalRD20 through the DRE element but not GCC box (Figure 5). PalERF2 targets PSI genes, like PalPHL2 and PalPHT1;4, also through the DRE box (Figure 3). Therefore, the PalERF2 modulates target genes depending on the DRE element. Although DRE is an element of the promoters of many ABA-independent drought-responsive genes [68,69,70], overexpressing or knocking-down of PalERF2 therefore also regulated the expression level of ABA-dependent drought-responsive genes, including PalNAC19, PalNAC3, PalMYB96, and PalSAG113 (Figure 4D). Moreover, PalSAG113 is a negative regulator of the ABA pathway [64]. These results indicate that PalERF2 may orchestrate ABA-dependent and -independent pathways. Remarkably, PalERF2 displays bifunction to the target genes, because it activates the transcription of PalRD20, PalPHL2, and PalPHT1;4, but represses the expression of PalSAG113 (Figure 5B). This suggests that PalERF2 may combine with other transcription regulatory proteins to modulate the transcription of all of these target genes. Our results together indicate a model for PalERF2 to mediate PSI genes and increase tolerance to drought stress in poplar (Figure 7). When drought stress and Pi starvation occur, PalERF2 is induced. PalERF2 is recruited to up-regulate the transcription of PalRD20 and down-regulate PalSAG113 expression, resulting in enhanced tolerance to drought. In addition, PalERF2 also positively regulates the expression level of PalPHL2 and PalPHT1;4 to increase Pi uptake, hence increasing tolerance to Pi deficiency. Our results therefore provide new insights into molecular crosstalk between drought and Pi starvation in woody plants. 4. Materials and Methods 4.1. Plant Materials and Growth Conditions The plantlets of P. alba var. pyramidalis and P. tomentosa were propagated in woody plant medium (WPM, Hopebio, Qindao, China) with 30 g·L−1 sucrose and 500 μL·L−1 PPM (Plant Cell Technology, Washington, DC, USA). The growth chamber provided a 16 h of light/8 h of dark cycle and 100 μmol·m−2·s−1 light intensity at a constant temperature of 25 °C. For the Pi starvation treatment, poplar shoots of the same length were selected for rooting culture in WPM medium containing 0.1 mg/L NAA until each line took root, and then they were transferred to sterile tubes with 5 mL MS Pi-deficient liquid medium and went on growing for 4 weeks. In the MS Pi-deficient medium, KH2PO4 was replaced by equimolar amounts of KCl2 and another 10 μM KH2PO4 was added. For the detected expression levels of AP2/ERF genes, P. alba var. pyramidalis were cultured in 5 mL MS Pi-deficient (10 μM) liquid medium or MS liquid medium with 150 mM mannitol, then shoots and roots were collected every other day, respectively. RNA from shoots and roots were extracted and reverse transcription performed. In order to perform drought treatment, the poplar plantlets with similar growth status and scale were transferred to the soil for 3 weeks, then watering was cut off until the phenotype appeared. 4.2. Nucleic Acid Extraction and qRT-PCR Analysis The genome DNA (gDNA) of poplar were extracted by CTAB method [71]. Total RNA from poplar were extracted by Biopin Plant Total RNA Extraction Kit (Bioflux, Beijing, China) and gDNA was removed by RNAase-free DNase I (TaKaRa, Dalian, China). Following, reverse transcription of 2 μg of RNA was carried out to obtain complementary DNA (cDNA) using a PrimeScriptTM RT Reagent Kit (Takara, Dalian, China). The quantitative RT-PCR assay was performed with Real Time PCR EastTM-SYBR Green II (Foregene, Chengdu, China), and ubiquitin (UBQ) gene was used as an internal reference. All gene-specific primers are listed in Table S1. 4.3. Gene Cloning The coding sequence (CDS) of PalERF2 was obtained by PCR, and the parameters are as follows: 95 °C initial denaturation for 5 min, 34 cycles of 95 °C for 30 s, 55 °C for 30 s and 72 °C for 30 s, and final extension at 72 °C for 5 min. The Phanta Max Super-Fidelity DNA polymerase (Vazyme, Nanjing, China) was used for the PCR reaction. The CDS of PalERF2 was ligated onto the pCX-DG vector by Seamless Cloning Mix Kit (Biomed, Beijing, China) and the construct was introduced into the Agrobacterium strain GV3101 by freeze-thaw method [72]. 4.4. Generation of Transgenic Poplars PalERF2 transgenic poplars (overexpression and RNAi) obtained by Agrobacterium mediated the leaf discs transformation method [73]. The key points of the method are as follows: The transgenic Agrobacterium was cultured to OD600 0.4–0.6, then centrifuged to remove the supernatant and resuspended in WPM liquid medium containing 100 μmol/L acetosyringone (AS); healthy poplar leaves were selected and cut along the main leaf vein to grow 1.5 cm square and placed in the resuspended Agrobacterium for 10 min; the excess bacteria on the leaves were removed and placed on solid WPM containing 100 μmol/L AS for co-cultivation for 2 days. After selective cultivation, budding, and rooting cultivation, a complete poplar tree was finally obtained. The positive transformants were determined by PCR and the overexpression lines with the highest expression levels and RNAi lines with the lowest expression levels were analyzed by qRT-PCR. The primers are shown in the Table S1. 4.5. Subcellular Localization of PalERF2 PalERF2 CDS fragment was ligated onto the pBI221 vector. Then the recombinant vector was introduced into poplar mesophyll protoplasts and the cell nucleus was stained by 4’,6-diamidino-2-phenylindole (DAPI). The protocol isolated poplar mesophyll protoplasts according to the previous description [74]. Healthy poplar leaves were selected and cut into 0.2 mm diameter filaments, and placed in 50 mL enzymatic hydrolysis solution containing 0.75 g Cellulase R10 and 0.2 g Macerozyme R10 (YAKULT, Kyoto, Japan). Enzymatic digestion was carried out in the dark for 3 h. Then, a 50 mL W5 solution (154 mM NaCl, 125 mM CaCl2, 5 mM KCl and 2 mM MES) was added to stop the enzymatic hydrolysis, and the protoplasts were collected by centrifugation at 100× g. MMG solution (0.4 M Mannitol, 15 mM MaCl2 and 4 mM MES) was used to resuspend the protoplasts, 200 μL protoplast/MMG solution was taken, a 1 μg vector was added, and then 220 μL of 40% PEG solution was added to the mix; 800 μL of W5 solution was added and 100 g centrifugation was carried out to collect the protoplasts; then protoplasts were resuspended in 1 mL W5 solution and cultured for 10 h at 22 °C under low light. Green fluorescence was observed by confocal laser microscope (Leica TCS SP5 II system, Solms, Germany). 4.6. Dual-Luciferase Assay The promoters of PalPHL2, PalPHT1;4, PalRD20, and PalSAG113 were obtained by PCR using sequence-specific primers, and the PCR products were ligated onto pGreen II 0800-LUC vector as the reporters using a Seamless Cloning Mix Kit (Biomed, Beijing, China). The construct pCX-DG-PalERF2 was set as the effector. All vectors were introduced into Agrobacterium strain GV3101 by freeze-thaw method. The Agrobacterium was cultured in YEP medium to OD600 0.6–0.8, and the cells were collected by centrifugation at 5000× g and resuspended in an infection buffer (10 mM MgCl2, 10 mM MES, and 100 μmol/L AS, pH 5.7), cultured at 200 rpm at 28 °C for 2 h. Then the reporter and effector were co-injected into leaves of Nicotiana benthamiana. After 2 days of dark treatment and 1 day of normal growth, the LUC and REN luciferase signals were detected by Dual-luciferase Reporter System (Synergy H1, BioTek, Winooski, VT, USA) using a Luciferase Reporter Assay Kit (Biovision, San Francisco, CA, USA). 4.7. Measurement of Anthocyanin Content The weighed leaves of the WT and transgenic poplars were homogenized with 1 mL hydrochloric acid/methanol (v/v, 1/99) to extract anthocyanin at 4 °C until the leaves turned white. The values of OD530 and OD657 for each sample were measured by a spectrophotometer (AOE, Shanghai, China). The anthocyanin calculation formula is (A530 − 0.25·A657)/fresh weight [75]. 4.8. Measurement of Phosphate Content The phosphorus content was measured as described previously with some modifications [76]. The weighed fresh or dry poplar root and shoot were shattered with a high-throughput grinder (SCIENTZ-48, Ningbo, China) and mixed with 100 μL of phosphorus extract buffer (0.2922 g of EDTA, 1.21 g of Tris, 5.844 g of NaCl, 700 μL β-mercaptoethanol, and 100 mM PMSF constant volume to 1 L by ddH2O) and 900 μL 1% acetic acid; then they were incubated at 42 °C for 30 min. After centrifugating the suspension at 12,000× g for 5 min, 150 μL of the supernatant was transferred into a new tube with 350 μL color-developing solution (0.35 g ammonium molybdate, 2.339 mL concentrated sulfuric acid, and 1.4 g ascorbic acid constant volume to 100 mL by ddH2O) and incubated at 42 °C for 30 min. Finally, the absorbance at the wavelength of 820 nm was determined, and the calculation of the phosphorus content was according to the standard curve. 4.9. Measurement of MDA and Total Chlorophyll Content For the MDA content measurement, The weighed leaves of WT and transgenic poplars were homogenized with 1 mL 5% trichloroacetic acid (TCA) by a high-throughput grinder (SCIENTZ-48, Ningbo, China). After centrifugation at 3000× g for 10 min, 200 μL of the supernatant was mixed with an equal volume of 0.67% thiobarbituric acid (TBA). Then it was incubated at 100 °C for 30 min, and centrifuged again to remove the precipitate, and the supernatant was measured with absorbances at 450 nm, 532 nm, and 600 nm by an ultraviolet spectrophotometer (AOE, Shanghai, China), respectively. The MDA calculation formula is [6.45·(A532 − A600) − 0.56·A450]/fresh weight [77]. For the total chlorophyll content measurement, 1 mL of 80% acetone was used to extracted chlorophyll until the leaves turned white, then the absorbance was measured at 663 nm and 645 nm, respectively. The chlorophyll content calculation formula is (8.02·A663 + 20.21·A645)/(1000*fresh weight) [78]. 4.10. Electrophoresis Mobility Shift Assay (EMSA) The CDS of PalERF2 was ligated onto the pMAL-c2x vector and introduced into the Escherichia coli strain Rosetta. Positive transformants were cultured at 37 °C until OD600 reached 0.6, then 1% IPTG (m/v) was added for 16 h at 16 °C. The MBP-PalERF2 fusion protein was purified by Amylose Resin (NEB Inc., Ipswich, MA, USA). Then, 45 bp-length probes containing a DRE element from promoters of PalPHL2, PalPHT1;4, PalRD20, and PalSAG113 were labelled by biotin. The EMSA was according to the protocol of the LightShift®® Chemiluminescent EMSA Kit (Thermo Scientific, Waltham, MA, USA). The probes and primers are listed in Table S1. 4.11. Chromatin Immunoprecipitation-qPCR (ChIP-qPCR) Transgenic poplar of PalERF2 tagged with GFP were transplanted into nutritional soil for 1 month, and then 3 g fresh leaves were used for CHIP-qPCR assay according to the previous description [79]. After formaldehyde cross-linking, nucleoprotein extraction, sonication of DNA, addition of Anti-GFP, protein A beads binding protein, protein digestion, DNA extraction, and other steps, the DNA was finally obtained, and qPCR was used to detect whether the specific DNA fragment was enriched. The primers are listed in Table S1. 4.12. Phylogenetic Analysis The sequence data of AP2/ERF genes were downloaded from the NCBI database (www.ncbi.nlm.nih.gov, accessed on 17 April 2020). The amino acid sequences were aligned and generated a phylogenetic tree using Neighbor-Joining (NJ) method by the MEGA6 software. The bootstrap value was 1000. 4.13. Statistical Method Numerical values were calculated as means ± SD. For multiple sets of data, one-way ANOVA were used for significance analysis, and different letters such as a, b, and c indicate significant differences (p < 0.05). The comparison of the two sets of data used Student’s t-test followed by Duncan’s multiple range test in the SPSS statistics 17 (SPSS Inc., Chicago, IL, USA). 5. Conclusions PalERF2 directly modulated the expressions of phosphorus starvation-responsive genes PalPHL2 and PalPHT1;4 to enhance the phosphorus starvation resistance and regulate drought response in poplar by binding to DRE motifs on the promoters of drought-responsive genes PalRD20 and PalSAG113. Under drought stress, poplar recruits PalERF2 to elevate its phosphorus uptake capacity. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23095241/s1. Click here for additional data file. Author Contributions Y.J. designed the experiments. N.C. performed the experiments, with the help of J.Q. and S.T., Y.J. and W.W. analyzed the data. N.C. and Y.J. wrote the manuscript. Y.J. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Characteristics of PalERF2 of Populus alba var. Pyramidalis. (A) Multiple sequence alignment of ERFs and the accession numbers are derived from different species (NM_001325036.1 from Nicotiana tabacum, XP_015636763.1 from rice, AT5G47220.1 from Arabidopsis thaliana, KAB5574006.1 from Salix brachista, and XP_003538752.2 from Glycine max). (B) The qRT-PCR analysis of PalERF2 expression in root (R), stem (S), mature leaves (ML), young leaves (YL), and petiole (P) in the mediums of MS. (C,D) The temporal expression pattern of PalERF2 under low Pi treatment (10 μM Pi) and 150 mM mannitol treatment in shoot and root, respectively. Error bars indicate SD values from three biological replicates. (E) Subcellular localization of PalERF2 in the mesophyll protoplasts of P. alba var. pyramidalis. The empty vector pBI221-expressing GFP is used as control (upper row) and the PalERF2-GFP fusion proteins are localized in the nucleus only (lower row). DAPI staining indicates the nucleus. Figure 2 The PalERF2 transgenic poplars under low Pi condition. (A) Phenotypes of transgenic and WT poplars grew in liquid medium with 10 μM Pi for 4 weeks. (B) The Pi contents of transgenic and WT poplars in root and shoot after low Pi treatment. (C) Anthocyanin contents of WT and transgenic poplar after low Pi treatment. Error bars indicate SD values from five biological replicates. Significant differences were analyzed by Duncan’s test (p < 0.05, n = 5). Different letters indicate statistically significant differences. (D) The qRT-PCR analysis of Pi starvation response (PSR) genes in PalERF2-OE, PalERF2-RNAi, and WT poplars. Error bars indicate SD values from three biological replicates. Figure 3 PalERF2 regulates PalPHL2 and PalPHT1;4 expression. (A) Structures of effector and reporters employed in dual-luciferase assay. (B) Transient co-expression of effector and reporter vectors in Nicotiana benthamiana leaves for dual-luciferase assay. Error bars indicate SD values (n = 3). Asterisks indicate significant differences compared to control by Student’s t-test, ***, p < 0.01. (C) Distribution of core DRE motifs in the promoters of PalPHL2 and PalPHT1;4. (D,E) ChIP-qPCR determined the binding of PalERF2 to the PalPHL2 and PalPHT1;4 promoter regions containing DRE, respectively. Error values represent means ± SD (n = 3). Significant differences were analyzed by Duncan’s test (p < 0.05, n = 5). Different letters indicate statistically significant differences. (F) EMSA tested the binding activity of PalERF2 to the DRE in PalPHL2 and PalPHT1;4 promoters. The unlabeled cold probes were added to compete with labeled probes. + means the cold probe is 20 times the labeled probe, ++ means 50 times. The arrows mark the binding probe and free probe. Figure 4 The phenotypes of PalERF2 transgenic poplars under drought stress. (A) The phenotypes of transgenic and WT poplars after 5 days of drought treatment. (B) The MDA contents were measured after drought treatment. (C) The total chlorophyll contents were measured after drought treatment. (B,C) values represents means ± SD (n = 5). Significance of differences was analyzed by Duncan’s test (p < 0.05, n = 5). Different letters indicate statistically significant difference. (D) The relative expression of drought-associated genes in PalERF2-OE, PalERF2-RNAi, and WT poplars. Error bars indicate SD values from three biological replicates. Figure 5 PalERF2 directly regulated the expression of PalRD20 and PalSAG113. (A) Structures of effector and reporters employed in Dual-luciferase assay. (B) Transient co-expression of effector and reporter vectors in N. benthamiana leaves. Data shown as mean ± SD (n = 3). Asterisks indicate significant differences compared to control by Student’s t-test, ***, p < 0.01. (C) Distribution of DRE and core DRE motifs in the promoter of PalRD20 and PalSAG113. (D,E) ChIP-qPCR demonstrated that PalERF2 bound to the promoter region of PalRD20 and PalSAG113 containing DRE in vivo. Significant differences were analyzed by Duncan’s test (p < 0.05, n = 5). Different letters indicate statistically significant differences. (F) EMSA demonstrated that PalERF2 bound to the DRE in the PalRD20 and PalSAG113 promoters. Unlabeled cold probes as a competitor to compete with labeled probes. + means the cold probe is 20 times the labeled probe, ++ means 50 times. The arrows mark the binding probe and free probe. Figure 6 The Pi contents and the expression of PSR genes in PalERF2 transgenic and WT poplars. (A) The Pi contents in WT and transgenic plants before drought treatment. (B) The Pi contents in WT and transgenic poplars after drought treatment. (A,B) Error bars indicate SD values from three biological replicates. Significant difference was analyzed by Duncan’s test (p < 0.05, n = 5). Different letters indicate statistically significant differences. (C) The qRT-PCR analyzed the relative expression of PSR genes in WT and transgenic poplars after drought treatment. Error bars indicate SD values from three biological replicates. Figure 7 The proposed model for the PalERF2 mediated drought stress and low Pi responses in poplars. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. López-Bucio J. Hernández-Abreu E. Sánchez-Calderón L. Nieto-Jacobo M.F. Simpson J. Herrera-Estrella L. Phosphate availability alters architecture and causes changes in hormone sensitivity in the Arabidopsis root system Plant Physiol. 2002 129 244 256 10.1104/pp.010934 12011355 2. Franco-Zorrilla J.M. Martin A.C. Leyva A. Par-Ares J.P. Interaction between phosphate-starvation, sugar and cytokinin signaling in and the roles of cytokinin receptors CRE1/AHK4 and AHK3 Plant Physiol. 2005 138 847 857 10.1104/pp.105.060517 15923327 3. Jain A. Nagarajan V.K. Raghothama K.G. Transcriptional regulation of phosphate acquisition by higher plants Cell Mol. Life Sci. 2012 69 3207 3224 10.1007/s00018-012-1090-6 22899310 4. Rennenberg H. Herschbach C. Phosphorus nutrition of woody plants: Many questions-few answers Plant Biol. 2013 15 785 788 10.1111/plb.12078 23902300 5. Staaf H. Plant nutrient changes in beech leaves during senescence as influenced by site characteristics Acta. Oecol. Oec. Plant 1982 3 161 170 6. Eschrich W. Fromm J. Essiamah S. Mineral partitioning in the phloem during autumn senescence of beech leaves Trees 1988 2 73 83 10.1007/BF00196752 7. Lange O.L. Nobel P.S. Osmond C.B. Ziegler H. Physiological Plant Ecology II Physiological Responses to Moderate Water Stress Springer Berlin/Heidelberg, Germany 1982 263 324 8. Christophe S. Jean-Christophe A. Annabelle L. Alain O. Anne-Sophie V. Plant N fluxes and modulation by nitrogen, heat and water stresses: A review based on comparison of legumes and non legume plants Abiotic Stress in Plants-Mechanisms and Adaptations Shanker A. Venkateswarlu B. Intech Open Access Publisher Rijeka, Croatia 2011 79 118 9. Fierer N. Schimel J.P. Effects of drying-rewetting frequency on soil carbon and nitrogen transformations Soil Biol. Biochem. 2002 34 777 787 10.1016/S0038-0717(02)00007-X 10. Schimel J. Balser T.C. Wallenstein M. Microbial stress-response physiology and its implications for ecosystem function Ecology 2007 88 1386 1394 10.1890/06-0219 17601131 11. Sanaullah M. Rumpel C. Charrier X. Chabbi A. How does drought stress influence the decomposition of plant litter with contrasting quality in a grassland ecosystem? Plant Soil 2012 352 277 288 10.1007/s11104-011-0995-4 12. Bassirirad H. Kinetics of nutrient uptake by roots: Responses to global change New Phytol. 2000 147 155 169 10.1046/j.1469-8137.2000.00682.x 13. Cramer M.D. Hawkins H.J. Verboom G.A. The importance of nutritional regulation of plant water flux Oecologia 2009 161 15 24 10.1007/s00442-009-1364-3 19449035 14. Waraich E.A. Ahmad R. Ashraf M.Y. Role of mineral nutrition in alleviation of drought stress in plants Aust. J. Crop Sci. 2011 5 764 777 15. Ge T.D. Sun N.B. Bai L.P. Tong C.L. Sui F.G. Effects of drought stress on phosphorus and potassium uptake dynamics in summer maize (Zea mays) throughout the growth cycle Acta Physiol. Plant 2012 34 2179 2186 10.1007/s11738-012-1018-7 16. Sardans J. Penuelas J. The role of plants in the effects of global change on nutrient availability and stoichiometry in the plant-soil system Plant Physiol. 2012 160 1741 1761 10.1104/pp.112.208785 23115250 17. He M.Z. Dijkstra F.A. Drought effect on plant nitrogen and phosphorus: A meta analysis New Phytol. 2014 204 924 931 10.1111/nph.12952 25130263 18. Raghothama K.G. Karthikeyan A.S. Phosphate acquisition Plant Soil 2005 274 37 49 10.1007/s11104-004-2005-6 19. Mitsukawa N. Okumura S. Shirano Y. Sato S. Kato T. Harashima S. Shibata D. Overexpression of an Arabidopsis thaliana high-affinity phosphate transporter gene in tobacco cultured cells enhances cell growth under phosphate-limited conditions Proc. Natl. Acad. Sci. USA 1997 94 7098 7102 10.1073/pnas.94.13.7098 9192698 20. Shin H. Shin H.S. Dewbre G.R. Harrison M.J. Phosphate transport in Arabidopsis: Pht1;1 and Pht1;4 play a major role in phosphate acquisition from both low- and high-phosphate environments Plant J. 2004 39 629 642 10.1111/j.1365-313X.2004.02161.x 15272879 21. Nussaume L. Kanno S. Javot H. Marin E. Pochon N. Ayadi A. Nakanishi T.M. Thibaud M.C. Phosphate import in plants: Focus on the PHT1 transporters Front. Plant Sci. 2011 2 83 10.3389/fpls.2011.00083 22645553 22. Richardson A.E. Regulating the phosphorus nutrition of plants: Molecular biology meeting agronomic needs Plant Soil 2009 322 17 24 10.1007/s11104-009-0071-5 23. Rubio V. Linhares F. Solano R. Martín A.C. Iglesias J. Leyva A. Paz-Ares J. A conserved MYB transcription factor involved in phosphate starvation signaling both in vascular plants and in unicellular algae Gene Dev. 2001 15 2122 2133 10.1101/gad.204401 11511543 24. Bustos R. Castrillo G. Linhares F. Puga M.I. Rubio V. Pérez-Pérez J. Solano R. Leyva A. Paz-Ares J. A central regulatory system largely controls transcriptional activation and repression responses to phosphate starvation in Arabidopsis PLoS Genet. 2010 6 e1001102 10.1371/journal.pgen.1001102 20838596 25. Sun L.C. Song L. Zhang Y. Zheng Z. Liu D. Arabidopsis PHL2 and PHR1 act redundantly as the key components of the central regulatory system controlling transcriptional responses to phosphate starvation Plant Physiol. 2016 170 499 514 10.1104/pp.15.01336 26586833 26. Li Y. Zhang S. Zhang N. Zhang W. Li M. Liu B. Shi Z. MYB-CC transcription factor, TaMYBsm3, cloned from wheat is involved in drought tolerance BMC Plant Biol. 2019 19 143 10.1186/s12870-019-1751-9 30987595 27. Devaiah B.N. Karthikeyan A.S. Raghothama K.G. WRKY75 transcription factor is a modulator of phosphate acquisition and root development in Arabidopsis Plant Physiol. 2007 143 1789 1801 10.1104/pp.106.093971 17322336 28. Zhao K. Zhang D. Lv K. Zhang X. Cheng Z. Li R. Zhou B. Jiang T. Functional characterization of poplar WRKY75 in salt and osmotic tolerance Plant Sci. 2019 289 110259 10.1016/j.plantsci.2019.110259 31623781 29. Abe H. Yamaguchi-Shinozaki K. Urao T. Iwasaki T. Hosokawa D. Shinozaki K. Role of Arabidopsis MYC and MYB homologs in drought- and abscisic acid-regulated gene expression Plant Cell 1997 9 1859 1868 9368419 30. Guo Y.F. Gan S.S. AtMYB2 regulates whole plant senescence by inhibiting cytokinin-mediated branching at late stages of development in Arabidopsis Plant Physiol. 2011 156 1612 1619 10.1104/pp.111.177022 21543729 31. Yoo J.H. Park C.Y. Kim J.C. Do Heo W. Cheong M.S. Park H.C. Kim M.C. Moon B.C. Choi M.S. Kang Y.H. Direct interaction of a divergent CaM isoform and the transcription factor, MYB2, enhances salt tolerance in Arabidopsis J. Biol. Chem. 2005 280 3697 3706 10.1074/jbc.M408237200 15569682 32. Baek D. Chun H.J. Kang S. Shin G. Park S.J. Hong H. Kim C. Kim D.H. Lee S.Y. Kim M.C. A role for Arabidopsis miR399f in salt, drought, and ABA signaling Mol. Cells 2016 39 111 118 26674968 33. Bari R. Pant B.D. Stitt M. Scheible W.R. PHO2, microRNA399, and PHR1 define a phosphate-signaling pathway in plants Plant Physiol. 2006 141 988 999 10.1104/pp.106.079707 16679424 34. Lin S.I. Chiang S.F. Lin W.Y. Chen J.W. Tseng C.Y. Wu P.C. Chiou T.J. Regulatory network of microRNA399 and PHO2 by systemic signaling Plant Physiol. 2008 147 732 746 10.1104/pp.108.116269 18390805 35. Kavka M. Polle A. Dissecting nutrient-related co-expression networks in phosphate starved poplars PLoS ONE 2017 12 e0171958 10.1371/journal.pone.0171958 28222153 36. Loth-Pereda V. Orsini E. Courty P.E. Lota F. Kohler A. Diss L. Blsudez D. Chalot M. Nehls U. Bucher M. Structure and expression profile of the phosphate Pht1 transporter gene family in mycorrhizal Populus trichocarpa Plant Physiol. 2011 156 2141 2154 10.1104/pp.111.180646 21705655 37. Zhang C.X. Meng S. Li M.J. Zhao Z. Genomic identification and expression analysis of the phosphate transporter gene family in poplar Front. Plant Sci. 2016 7 1398 10.3389/fpls.2016.01398 27695473 38. Nakano T. Suzuki K. Fujimura T. Shinshi H. Genome-wide analysis of the ERF gene family in Arabidopsis and rice Plant Physiol. 2006 140 411 432 10.1104/pp.105.073783 16407444 39. Ohmetakagi M. Shinshi H. Ethylene-inducible DNA-binding proteins that interact with an ethylene-responsive element Plant Cell 1995 7 173 182 7756828 40. Hao D.Y. Ohme-Takagi M. Sarai A. Unique mode of GCC box recognition by the DNA-binding domain of ethylene-responsive element-binding factor (ERF domain) in plant J. Biol. Chem. 1998 273 26857 26861 10.1074/jbc.273.41.26857 9756931 41. Pré M. Atallah M. Champion A. Vos M.D. Pieterse C.M.J. Memelink J. The AP2/ERF domain transcription factor ORA59 integrates jasmonic acid and ethylene signals in plant defense Plant Physiol. 2008 147 1347 1357 10.1104/pp.108.117523 18467450 42. Xie Z. Nolan T. Jiang H. Tang B. Zhang M. Li Z. Yin Y. The AP2/ERF transcription factor TINY modulates brassinosteroid-regulated plant growth and drought responses in Arabidopsis Plant Cell 2019 31 1788 1806 10.1105/tpc.18.00918 31126980 43. Zhao Q. Hu R.S. Liu D. Liu X. Wang J. Xiang X.H. Li Y.Y. The AP2 transcription factor NtERF172 confers drought resistance by modifying NtCAT Plant Biotechnol. J. 2020 18 2444 2455 10.1111/pbi.13419 32445603 44. Tang Y. Qin S. Guo Y. Chen Y. Wu P. Chen Y. Wu P. Chen Y. Li M. Jiang H. Genome-wide analysis of the AP2/ERF gene family in Physic Nut and overexpression of the JcERF011 gene in rice increased its sensitivity to salinity stress PLoS ONE 2016 11 e0150879 10.1371/journal.pone.0150879 26943337 45. Chen Y. Wu P. Zhao Q. Tang Y. Chen Y. Li M. Jiang H. Wu G. Overexpression of a phosphate starvation response AP2/ERF gene from Physic Nut in Arabidopsis alters root morphological traits and phosphate starvation-induced anthocyanin accumulation Front. Plant. Sci. 2018 9 1186 10.3389/fpls.2018.01186 30177937 46. Crombez H. Motte H. Beeckman T. Tackling plant phosphate starvation by the roots Dev. Cell 2019 48 599 615 10.1016/j.devcel.2019.01.002 30861374 47. Chen N. Tong S. Tang H. Zhang Z. Liu B. Lou S. Liu J. Liu H. Ma T. Jiang Y. The PalERF109 transcription factor positively regulates salt tolerance via PalHKT1;2 in Populus alba var pyramidalis. Tree Physiol. 2020 40 717 730 10.1093/treephys/tpaa018 32083670 48. Khan G.A. Bouraine S. Wege S. Li Y. de Carbonnel M. Berthomieu P. Poirier Y. Rouached H. Coordination between zinc and phosphate homeostasis involves the transcription factor PHR1, the phosphate exporter PHO1, and its homologue PHO1;H3 in Arabidopsis J. Exp. Bot. 2014 65 871 884 10.1093/jxb/ert444 24420568 49. Shi J. Hu H. Zhang K. Zhang W. Yu Y. Wu Z. Wu P. The paralogous SPX3 and SPX5 genes redundantly modulate Pi homeostasis in rice J. Exp. Bot. 2014 65 859 870 10.1093/jxb/ert424 24368504 50. Abbasi-Vineh M.A. Sabet M.S. Karimzadeh G. Identification and functional analysis of two purple acid phosphatases AtPAP17 and AtPAP26 involved in salt tolerance in Arabidopsis thaliana plant Front. Plant Sci. 2021 11 2326 10.3389/fpls.2020.618716 51. Kobayashi K. Awai K. Takamiya K. Ohta H. Arabidopsis type B monogalactosyldiacylglycerol synthase genes are expressed during pollen tube growth and induced by phosphate starvation Plant Physiol. 2004 134 640 648 10.1104/pp.103.032656 14730084 52. Yang S. Wang S. Liu X. Yu Y. Yue L. Wang X. Hao D. Four divergent Arabidopsis ethylene-responsive element-binding factor domains bind to a target DNA motif with a universal CG step core recognition and different flanking bases preference FEBS J. 2009 276 7177 7186 10.1111/j.1742-4658.2009.07428.x 19878300 53. Zarei A. Körbes A.P. Younessi P. Montiel G. Champion A. Memelink J. Two GCC boxes and AP2/ERF-domain transcription factor ORA59 in jasmonate/ethylene-mediated activation of the PDF1.2 promoter in Arabidopsis Plant Mol. Biol. 2011 75 321 331 10.1007/s11103-010-9728-y 21246258 54. Kiyosue T. Yoshiba Y. Yamaguchi-Shinozaki K. Shinozaki K. A nuclear gene encoding mitochondrial proline dehydrogenase, an enzyme involved in proline metabolism, is upregulated by proline but downregulated by dehydration in Arabidopsis Plant Cell 1996 8 1323 1335 8776899 55. Abe H. Urao T. Ito T. Seki M. Shinozaki K. Yamaguchi-Shinozaki K. Arabidopsis AtMYC2 (bHLH) and AtMYB2 (MYB) function as transcriptional activators in abscisic acid signaling Plant Cell 2003 15 63 78 10.1105/tpc.006130 12509522 56. Seo P.J. Xiang F. Qiao M. Park J.Y. Lee Y.N. Kim S.G. Lee Y.J. Park W.J. Park C.M. The MYB96 transcription factor mediates abscisic acid signaling during drought stress response in Arabidopsis Plant Physiol. 2009 151 275 289 10.1104/pp.109.144220 19625633 57. Liu X. Liu S. Wu J. Zhang B. Li X. Yan Y. Li L. Overexpression of Arachis hypogaea NAC3 in tobacco enhances dehydration and drought tolerance by increasing superoxide scavenging Plant Physiol. Biochem. 2013 70 354 359 10.1016/j.plaphy.2013.05.018 23816928 58. Takasaki H. Maruyama K. Takahashi F. Fujita M. Yoshida T. Nakashima K. Myouga F. Toyooka K. Yamaguchi-Shinozaki K. Shinozaki K. SNAC-As, stress-responsive NAC transcription factors, mediate ABA-inducible leaf senescence Plant J. 2015 84 1114 1123 10.1111/tpj.13067 26518251 59. Zhang K.W. Gan S.S. An Abscisic acid-AtNAP transcription factor-SAG113 protein phosphatase 2C regulatory chain for controlling dehydration in senescing Arabidopsis leaves Plant Physiol. 2012 158 961 969 10.1104/pp.111.190876 22184656 60. Cho S.K. Ryu M.Y. Song C. Kwak J.M. Kim W.T. Arabidopsis PUB22 and PUB23 are homologous U-box E3 ubiquitin ligases that play combinatory roles in response to drought stress Plant Cell 2008 20 1899 1914 10.1105/tpc.108.060699 18664614 61. Zhang H. Liu D. Yang B. Liu W.Z. Mu B. Song H. Chen B. Li Y. Ren D. Deng H. Arabidopsis CPK6 positively regulates ABA signaling and drought tolerance through phosphorylating ABA-responsive element-binding factors J. Exp. Bot. 2020 71 188 203 10.1093/jxb/erz432 31563949 62. Puhakainen T. Hess M.W. Mäkelä P. Svensson J. Heino P. Palva E.T. Overexpression of multiple dehydrin genes enhances tolerance to freezing stress in Arabidopsis Plant Mol. Biol. 2004 54 743 753 10.1023/B:PLAN.0000040903.66496.a4 15356392 63. Kiyosue T. Abe H. Yamaguchi-Shinozaki K. Shinozaki K. ERD6, a cDNA clone for an early dehydration-induced gene of Arabidopsis, encodes a putative sugar transporter Biochim. Biophys. Acta (BBA)-Biomembr. 1998 1370 187 191 10.1016/S0005-2736(98)00007-8 64. Aubert Y. Vile D. Pervent M. Aldon D. Ranty B. Simonneau T. Vavasseur A. Galaud J.P. RD20, a stress-inducible caleosin, participates in stomatal control, transpiration and drought tolerance in Arabidopsis thaliana Plant Cell Physiol. 2010 51 1975 1987 10.1093/pcp/pcq155 20952421 65. Jia J. Zhou J. Shi W. Cao X. Luo J. Polle A. Luo Z.B. Comparative transcriptomic analysis reveals the roles of overlapping heat-/drought-responsive genes in poplars exposed to high temperature and drought Sci. Rep. 2017 7 43215 10.1038/srep43215 28233854 66. Becker D. Hoth S. Ache P. Wenkel S. Roelfsema M.R.G. Meyerhoff O. Hartung W. Hedrich R. Regulation of the ABA-sensitive Arabidopsis potassium channel gene GORK in response to water stress FEBS Lett. 2003 554 119 126 10.1016/S0014-5793(03)01118-9 14596925 67. Guo X.H. Deng K.Q. Wang J. Yu D.S. Zhao Q. Liu X.M. Mutational analysis of Arabidopsis PP2CA2 involved in abscisic acid signal transduction Mol. Biol. Rep. 2010 37 763 769 10.1007/s11033-009-9601-8 19579056 68. Cheng M.C. Liao P.M. Kuo W.W. Lin T.P. The Arabidopsis ETHYLENE RESPONSE FACTOR1 regulates abiotic stress-responsive gene expression by binding to different cis-acting elements in response to different stress signals Plant Physiol. 2013 162 1566 1582 10.1104/pp.113.221911 23719892 69. Liu S.W. Lv Z.Y. Liu Y.H. Li L. Zhang L.D. Network analysis of ABA-dependent and ABA-independent drought responsive genes in Arabidopsis thaliana Genet. Mol. Biol. 2018 41 624 637 10.1590/1678-4685-gmb-2017-0229 30044467 70. Chaves M.M. Maroco J.P. Pereira J.S. Understanding plant responses to drought-from genes to the whole plant Funct. Plant Biol. 2003 30 239 264 10.1071/FP02076 32689007 71. Logemann J. Schell J. Willmitzer L. Improved method for the isolation of RNA from plant-tissues Anal. Biochem. 1987 163 16 20 10.1016/0003-2697(87)90086-8 2441623 72. Jyothishwaran G. Kotresha D. Selvaraj T. Srideshikan S.M. Rajvanshi P.K. Jayabaskaran C. A modified freeze–thaw method for efficient transformation of Agrobacterium tumefaciens Curr. Sci. 2007 93 770 772 73. Jia Z. Gou J. Sun Y. Yuan L. Tang Q. Yang X. Pei Y. Luo K. Enhanced resistance to fungal pathogens in transgenic Populus tomentosa Carr. by overexpression of an nsLTP-like antimicrobial protein gene from motherwort (Leonurus japonicus) Tree Physiol. 2010 30 1599 1605 10.1093/treephys/tpq093 21084346 74. Guo J. Morrell-Falvey J.L. Labbé J.L. Muchero W. Kalluri U.C. Tuskan G.A. Chen J.G. Highly efficient isolation of Populus mesophyll protoplasts and its application in transient expression assays PLoS ONE 2012 7 e44908 10.1371/journal.pone.0044908 23028673 75. Rabino I. Mancinelli A.L. Light, temperature and anthocyanin production Plant Physiol. 1986 81 922 924 10.1104/pp.81.3.922 16664926 76. Ames B.N. Assay of inorganic phosphate, total phosphate and phosphatases Methods Enzymol. 1966 8 115 118 77. Heath R. Photoperoxidation in isolated chloroplasts. I. Kinetics and stoichiometry of fatty acid peroxidation Arch. Biochem. Biophys. 1968 125 189 198 10.1016/0003-9861(68)90654-1 5655425 78. Gitelson A.A. Merzlyak M.N. Remote estimation of chlorophyll content in higher plant leaves Int. J. Remote Sens. 1997 18 2691 2697 10.1080/014311697217558 79. Chen Y.F. Li L.Q. Xu Q. Kong Y.H. Wang H. Wu W.H. The WRKY6 transcription factor modulates PHOSPHATE1 expression in response to low Pi stress in Arabidopsis Plant Cell 2009 21 3554 3566 10.1105/tpc.108.064980 19934380

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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091269 foods-11-01269 Article Research on the Cross-Chain Model of Rice Supply Chain Supervision Based on Parallel Blockchain and Smart Contracts Peng Xiangzhen 12 https://orcid.org/0000-0003-0475-9746 Zhang Xin 12* Wang Xiaoyi 123 Li Haisheng 1 Xu Jiping 12 https://orcid.org/0000-0001-8565-4430 Zhao Zhiyao 12 Wang Yanhong 4 Ramon Jeronimo Juan Manuel Academic Editor Flórez López Raquel Academic Editor 1 Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China; 2030602060@st.btbu.edu.cn (X.P.); wangxy@btbu.edu.cn (X.W.); lihsh@btbu.edu.cn (H.L.); xujiping@btbu.edu.cn (J.X.); zhaozy@btbu.edu.cn (Z.Z.) 2 Key Laboratory of Industrial Internet and Big Data, China National Light Industry, Beijing Technology and Business University, Beijing 100048, China 3 Beijing Institute of Fashion Technology, Beijing 100048, China 4 China Academy of Information and Communications Technology, Beijing 100048, China; wangyanhong1@caict.ac.cn * Correspondence: zhangxin@btbu.edu.cn 27 4 2022 5 2022 11 9 126923 3 2022 24 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Rice is one of the three major staple foods in the world, and the quality and safety of rice are related to the development of human beings. The new crown epidemic, pesticide residues, insect pests, and heavy metal pollution have a certain security impact on the food supply chain. The rice supply chain is characterized by a long life cycle; complex roles in the main links; many types of hazards; and multidimensional, multisource, and heterogeneous information. To strengthen the rice supply chain’s supervision ability under the epidemic situation, a supervision cross-chain model suitable for the complicated data of the rice supply chain based on parallel blockchain theory and smart contract technology was built. Firstly, the data collected in the rice supply chain and different types of data stored in different parallel blockchains were analyzed. Secondly, based on data analysis, a collection/supervision cross-chain mechanism based on “hash lock + smart contract + relay chain”, a concurrency mechanism based on the K-means algorithm and a Bloom filter, and a consensus mechanism suitable for multichain consensus named the Supervision Practical Byzantine Fault Tolerance (SPBFT) were proposed. Furthermore, a cross-chain model of rice supply chain supervision was constructed. Finally, theoretical verification and simulation experiments were used to analyze the operation process, safety, cross-chain efficiency, and scalability of the model. The results showed that the application of parallel blockchains and smart contracts to supervision of rice supply chain information improved the convenience and security of information interaction between various links in the rice supply chain, the storage cost of supply chain data and the high latency of interaction was reduced, and the refined management of the rice supply chain data and personnel was realized. This research applied new information technology to the coordination and resource sharing of the food supply chain, and provides ideas for the digital transformation of the food industry. rice supply chain cross-chain supervision smart contracts blockchain food safety National Key Research and Development Program of China2019YFC1605306 Beijing Natural Science Foundation4222042 Beijing Technology and Business University 2022 Research Capacity Enhancement ProgramTC200A00L-3/2020 This work was supported in part by the National Key Research and Development Program of China (No. 2019YFC1605306), the Beijing Natural Science Foundation (4222042), and the Industrial Internet Innovation and Development Project: Novel connection platform for large-scale industrial Internet identification-PLM(TC200A00L-3/2020), Beijing Technology and Business University 2022 Research Capacity Enhancement Program (corresponding author: X.Z.) ==== Body pmc1. Introduction Since 2020, COVID-19 has continued to spread [1]. In addition, global food crops have been affected by extreme weather such as droughts and floods, and pests such as locusts and Spodoptera frugiperda [2,3]. The quality and safety of food crops have been seriously threatened. The three major United Nations food and agriculture agencies—the FAO (Food and Agriculture Organization), WFP (World Food Program), and IFAD (International Fund for Agricultural Development)—as well as international organizations such as the WTO (World Trade Organization) and the G20 (Group of Twenty) have called for global cooperation in regional governance to reduce the impact of the epidemic on food security. Rice is one of the world’s three major foods [4]. The global rice output in 2021/22 is expected to exceed 9.5 billion tons. Under the influence of COVID-19, ensuring the quality and safety of rice is an important measure to protect human health. Therefore, since the outbreak of COVID-19, the rice supply chain has been managed more accurately by the relevant rice regulatory authorities and enterprises. Products that do not meet the food safety standards are penalized more severely. To strengthen the supervision of rice quality and safety [5], it ensures the quality and safety of rice under COVID-19. Agricultural technological innovation is an effective means to strengthen the supervision of the agricultural and food supply chain. The supervision level of the agricultural and food supply chain is improved by using new technologies. It can also promote the digital transformation of agricultural products and food, and the agricultural products and food quality and safety can be realized [6,7]. The parallel blockchain is an organic combination of parallel intelligent theoretical methods and blockchain technology. It is committed to adding computational experiments to the current blockchain technology through the parallel interaction and coevolution of the actual/artificial blockchain system [8]. It realizes the management of and decision making by the blockchain system by combining description, prediction, and guidance [9]. Agricultural and food supply chain data is complex, and frequently interacts. By referring to the parallel blockchain idea, the storage pressure of the blockchain is reduced, the transaction volume of the blockchain system is increased, and the storage cost of agricultural and food supply chain data is reduced. The application of a parallel blockchain can help the efficient management of complex information in the whole life cycle of the agricultural and food supply chain. A smart contract is a computer program with a status and a conditional response running on a distributed ledger. The contract completes the encapsulation, verification, and execution of the complex behaviors of distributed nodes through preset rules, and it achieves the functions of information exchange, value transfer, and asset management [10,11,12]. In recent years, the combination of blockchain technology with artificial intelligence, big data, 5G, and the industrial internet have been explored by researchers to strengthen regulatory capabilities, which has been mainly reflected in the following aspects [13,14,15]. Firstly, artificial intelligence (AI) and smart contracts were combined to solve the problem of redundancy of blockchain information and improved supervision efficiency [16,17]. Secondly, blockchain technology and big data technology were combined to unify different data sources and realize unified data supervision [18,19]. Thirdly, blockchain technology and 5G technology were combined to solve the problem of slow real-time data transmission [20,21]. Fourthly, the blockchain was combined with the industrial internet, and the precise traceability of regulatory information was achieved through identification analysis [22]. Compared with the traditional agricultural and food supply chain supervision model, the “blockchain+” model can ensure the safety and credibility of the data in the agricultural and food supply chain. The credible traceability and precise accountability of the agricultural products and food data can be realized, thereby improving the supervision of the agricultural and food supply chain efficiency and authenticity. The rice supply chain is characterized by complex links, diverse data types, and long life cycles. The application of the blockchain and smart contracts has promoted the digitization and intelligence of the rice supply chain, and the supervision of the rice supply chain by the regulatory authorities has been improved to a certain extent. However, as the amount of data has increased, the application of a blockchain and smart contracts in the supervision of the rice supply chain has encountered the following shortcomings. The research on blockchains in the rice supply chain is mostly on single-link blockchains such as the “production blockchain”, “processing blockchain”, and “storage blockchain” [23,24,25]. Blockchain research in the rice supply chain is mostly the in the mode of “blockchain + local database” or “blockchain + cloud database” [26]. It is difficult for data to be interconnected in a timely and effective manner between all links of the rice supply chain. There are security risks in the data interaction between the blockchain and the local database. Due to the numerous links in the rice supply chain and the huge actual circulation of rice, the amount of data generated by the rice supply chain is huge [27,28]. The blockchain itself has limited storage space, and the single-chain architecture cannot afford the huge amount of data in the rice supply chain [29]. The single-chain architecture has problems such as high latency and high storage costs [30]. The data storage for the rice supply chain is decentralized, and the basic information, harmful substance information, and personnel identity information of each link are weakly correlated [31,32,33,34]. The management of rice supply chain data is sloppy, and regulators can only supervise rice data, so it is difficult to effectively supervise related fraudulent activities of enterprises [35,36,37]. To solve the weak availability of the blockchain and smart contracts in the rice supply chain in view of the unique architecture and data flow characteristics of the rice supply chain, this paper builds a cross-chain supervision model of the rice supply chain based on parallel blockchains and smart contracts. The main contributions of this paper are listed below. It is difficult to effectively interconnect each link of the rice supply chain, and the data interaction between the blockchain and the off-chain database is characterized by security risks [38,39]. We designed a multichain model of “main chain + parallel chain “suitable for rice supply chain supervision based on parallel blockchains and smart contracts. This model allowed the whole life cycle data of the rice supply chain to be stored on the blockchain, and the convenience and security of data interaction between various links were improved. In view of the many links in the rice supply chain, the participants are complex, and the rice circulation is huge [40,41,42]. A cross-chain mechanism based on a hash locking mechanism, smart contract technology, and relay chain architecture was designed. A concurrency mechanism based on the K-means algorithm and a Bloom filter was designed. An SPBFT consensus mechanism based on the PBFT consensus mechanism was designed. These mechanisms effectively reduced the delay in complex data interaction in the rice supply chain, and greatly reduced the cost of data storage. In view of the characteristics of scattered data storage in the rice supply chain, and since it is difficult for regulators to supervise corporate behavior, four types of smart contracts were customized. The design of these smart contracts strengthened the coupling between rice supply chain data, basic information, harmful substance information, and personnel identity information, and a refined management of rice supply chain data and personnel was realized. Faced with the unique link structure and complex flow data of the rice supply chain, the existing blockchain research has strengthened the management capability of rice supply chain information to a certain extent. However, the application of and research on the existing blockchain and smart contracts in the rice supply chain are still immature, with low security of data interaction, poor performance of comprehensive management of the whole supply chain, and weak performance of all types of data management, making it difficult to manage the rice supply chain efficiently and precisely. Based on parallel blockchain theory and smart contract technology, this paper designed and used a new “parallel chain + main chain” architecture in the rice supply chain. The cross-chain mechanism, concurrency mechanism, and SPBFT consensus mechanism were also designed to serve in the operation of the rice supply chain supervision model. This paper solved some limitations of the blockchain in rice supply chain information management, and realized the precise management of rice supply chain information. The rest of the paper is organized as follows. Section 2 is a literature review. Section 3 analyzes the supervision information of the rice supply chain and divides the parallel chains. Section 4 designs the cross-chain mode of rice supply chain supervision, including the design of the cross-chain framework of rice supply chain supervision and the cross-chain mechanism, concurrency mechanism, and consensus mechanism. Section 5 shows the results, and through analysis of the model operation process, safety, efficiency, and extensibility, shows the supervision effect of the model on the rice supply chain. Section 6 contains the conclusion and suggestions for future work. 2. Literature Review The cross-chain regulatory model of the rice supply chain based on parallel blockchains and smart contracts requires higher requirements for latency, privacy, security, convenience, and granularity of data management for cross-chain data interaction in the rice supply chain. In this section, we have compiled some of the latest research on the use of the blockchain for agricultural products, as well as for food in recent years, as shown in Table 1. In a theoretical study of blockchain-based frameworks or models for agricultural products and food management, [19] noted that the use of the blockchain in food and beverage supply chains may offer benefits by improving food safety, supplier reputation, visibility of small farmers, efficiency in tracing food contamination sources, transparency, and accountability. Ref. [20] explored the challenges faced by typical management systems, such as food safety, food fraud, and inefficient processes, as well as ethical aspects such as fair trade, animal welfare, and the environmental impact of food production. The authors pointed out that the use of blockchain-based systems to manage supply chains offers significant benefits, such as faster and more reliable traceability. Ref. [25] pointed out that digital transformation of agricultural and food supply chains promises a traceable, transparent, trustworthy, and intelligent ecosystem through blockchain-based smart contract technology. Ref. [29] pointed out that the blockchain has great potential to improve the performance of food supply chain traceability by providing security and full transparency. The aforementioned studies explored the advantages of blockchain applications in agricultural and food management frameworks or models, but the ability of the blockchain to handle the huge volume of data in agricultural and food supply chains has not been explored. In research on the blockchain and smart-contract-based agricultural products and food information management, [1] proposed a blockchain and an approach based on a deep-learning model for food market regulation: stacked autoencoders. The authors provided a basis for market regulation by predicting consumers’ emotional tendencies. Ref. [24] proposed a blockchain-based solution to manage a country’s strategic grain reserves using Hyperledger Fabric software. Ref. [32] combined a cryptographic algorithm, timestamp technology, consensus algorithm, and sidechain technology of the blockchain with the rice supply chain. A federated chain was built between upstream and downstream companies in the supply chain, including producers, suppliers, and vendors, to create secure and efficient supply chain information management. Ref. [35] pointed out that the use of the blockchain in the food supply chain was beneficial to reducing management costs, as well as improving management efficiency. Ref. [38] proposed a hierarchical multidomain blockchain network structure and secondary verification mechanism for food supply chain supervision, combining the characteristics of the blockchain such as distribution, transparency, collegiality, and the practical need for regional autonomy. The above research focused on changing the traditional centralized management model through the decentralized feature of the blockchain, which was used to enhance the information-control capability of agricultural products and food. However, the granularity of information management for agricultural products and the food supply chain has high requirements, and the ability of the blockchain to manage complex data interaction requests is still a problem to be solved. In research on the blockchain and smart-contract-based agricultural products and food information traceability, [21] proposed a blockchain-based traceability system for agricultural products to monitor data on the blockchain, as well as to improve security and traceability of agri-food businesses. Ref. [22] proposed a complete blockchain-based agricultural and food supply chain solution to ensure traceability, trust, and delivery mechanisms in the agricultural and food supply chain. Ref. [33] proposed a blockchain-based traceability architecture for minimizing the risk of COVID-19 and bacteria, fungi, and parasites in the frozen meat supply chain. The aforementioned study utilized the characteristics of the blockchain such as nontamperability and transparency to improve the information traceability of agricultural products and foods, but the efficiency of this information traceability still needs to be improved. In the area of blockchain-based applications for the integration of agricultural products and food with the Internet of Things, Ref. [17] developed a supply chain traceability system framework based on the blockchain and radio frequency identification technology for tracing food products in the supply chain. Ref. [28] proposed a new approach to apply blockchain and IoT technologies to support the traceability of farm produce sources by collecting data through sensors to be stored in the blockchain and by using smart contracts for bookkeeping. Ref. [30] proposed an agricultural supply chain management architecture using the blockchain and IoT to address the storage and scalability optimization, interoperability, security, and privacy issues, as well as personal data privacy and storage issues in current single-chain agricultural supply chain systems. The above study integrated technologies such as IoT with the blockchain for application, which were then used to improve the information traceability and management of agricultural products and food, which provided an application idea for future blockchain applications. In this paper, we built a cross-chain supervision model for the rice supply chain based on a parallel blockchain and smart contract, and adopted a new architecture of “main chain + parallel chain” to extend the performance of the blockchain. We designed a cross-chain collection mechanism and a cross-chain supervision mechanism for the rice supply chain to ensure the privacy and security of the cross-chain data. A concurrency mechanism based on the K-means algorithm and a Bloom filter was designed to cope with the high frequency of data interaction in the rice supply chain and reduce the latency of the model. An SPBFT consensus mechanism was also designed to serve the consensus requests between the nodes of the new architecture. This study can improve the information supervision capability of the rice supply chain and ensure the food quality and safety of rice. 3. Analysis of Supervision Information on the Rice Supply Chain and Division of Parallel Chains To strengthen the supervision of the rice supply chain and reduce the flow of problematic rice into the market, a cross-chain supervision model of the rice supply chain based on the blockchain and smart contracts was designed. Firstly, we divided the rice supply chain into six typical links: planting, receiving and storing, processing, storage, transportation, and sales. The receiving and storing link included four subnodes: acquisition, drying, edulcoration, and warehousing. The processing node had five subnodes: ridge valley, rice milling, color selection, polishing, and packaging. Figure 1 shows the classification of the rice supply chain links. Secondly, the rice supply chain supervision cross-chain model architecture was divided into three different types: main chain, parallel blockchain, and relay chain. Among them, the main chain nodes were various regulatory agencies, on-chain companies, and consumers; the parallel blockchain was the data storage chain; and the relay chain was the data cross-chain transfer chain. Finally, we sorted the different data generated during the entire life cycle of the rice supply chain and preliminarily divided it into nine parallel chains for storage. Regarding the different types of data stored in different parallel blockchains, nine parallel blockchains were stipulated that corresponded to hazardous substance information, corporate information, consumer information, regulatory agency information, transaction records, cost information, data interaction records, health records, etc. (Table 2). More than 200 types of key data were compiled based on relevant national/local/industry standards and actual data generated in each link of the rice supply chain. The data covered the entire process for rice, from planting to edible circulation. The data in this paper was collected from IoT devices such as RFID, NFC, mobile phones, computers, and GPS. After the rice data were stored in the blockchain through the collection cross-chain mechanism designed in this paper, the rice supply chain information supervision model established based on parallel blockchain and smart contract technology managed the collected data. The model in turn enabled trusted supervision of the data. Based on the analysis of key data in the rice supply chain, we organized the data privacy issues arising from the rice supply chain. Data owners fell into three categories: businesses, regulators, and consumers. For enterprises there were six blockchains: parallel blockchains I, II, V, VI, VIII, and IX. Among them, the data contained in the four parallel blockchains II, V, VIII, and IX were shared data, and the related harmful substance information and cost information in the parallel blockchains I and VI were nonpublic data. For regulators, they owned data stored on parallel blockchains IV and VII. The data contained in parallel blockchain IV were shared data, and the data contained in parallel blockchain VII were private data. For consumers, their own data were in parallel blockchain III. The blockchain data is shared data. In terms of access rights, enterprises and consumers can access all shared data after verifying their identities. When the supervisory authority exercises supervisory powers, the corresponding data is accessed according to the authority it has. Based on the key data for the supervision of the entire rice supply chain, the authority of the relevant supervisory authorities of the rice supply chain (Table 3) were classified. Given the different nature of each regulatory department, we regulated the parallel blockchains that each department had the right to supervise and access to ensure the privacy and security of data at the application level. The links in the rice supply chain are complex, and the amount of rice data is huge. Different data types produced by the rice supply chain into different parallel chains were categorized and stored to improve the efficiency of data supervision by the supervisory authority. Since the chain nodes of various regulatory agencies were distributed in the main chain, a rice supervision framework was designed to solve the problem of cross-chain interaction between the main chain and the parallel blockchain. This framework could realize cross-chain intercommunication between the main chain and the parallel blockchain. Based on this, credible data interaction, credible data collection, and credible data supervision in the rice supply chain were solved by this framework. 4. Design of the Cross-Chain Model 4.1. Cross-Chain Framework of Rice Supply Chain Supervision The quality and safety of rice are closely related to human health. Strengthening the supervision of the entire rice supply chain is one of the important measures to ensure the quality and safety of rice. At present, most of the research on food quality supervision based on the blockchain is on the single-chain mode, in which a storage mode of “blockchain + cloud database” is adopted to store the supervised data. However, the rice supply chain is characterized by complex links, long life cycles, and a large variety of data. The traditional single-chain model cannot achieve complete decentralization of the data; therefore, it cannot guarantee the absolute security of data storage. In addition, with increases in time and rice business, the data generated by the rice supply chain will steadily increase, which will lead to a continuous increase in the computing resources required for supervision. We proposed a cross-chain framework for rice supply chain supervision to solve the above problems. Figure 2 shows the cross-chain framework of rice supply chain supervision. In the cross-chain framework of rice supervision we designed, three groups of people are served; namely, regulatory authorities, enterprises, and consumers. An organic combination of hash lock, cross-chain contract, and relay chain was adopted in the cross-chain mechanism. Among these, the cross-chain contracts were divided into CCSC-A (collection cross-chain smart contract A), CCSC-B (collection cross-chain smart contract B), SCSC-A (supervision cross-chain smart contract A), and SCSC-B (supervision cross-chain smart contract B). At the same time, the K-means algorithm and Bloom filter were used to facilitate the data transmission between the main chain and the parallel blockchain, and the SPBFT consensus mechanism was designed to reach a consensus between the main chain and the parallel blockchain. At the bottom of the frame is the parallel blockchain group, which mainly realized the branched storage of data. We divided the data throughout the entire framework into four categories according to types, namely collecting cross-chain data, supervising cross-chain data, consensus data, and cross-chain processing data. A cross-chain mechanism combining a hash lock, smart contract, and relay chain was designed to resist cross-chain attacks in the cross-chain process and ensure the credible transmission of data; a concurrency mechanism based on the K-means algorithm and a Bloom filter was designed to avoid data in the cross-chain process being blocked and to improve the efficiency of the data cross-chain; while the SPBFT consensus mechanism was designed to reach a consensus for each node between the main chain and parallel blockchain. 4.2. Mechanism 4.2.1. Cross-Chain Mechanism Based on Hash Lock, Smart Contract, and Relay Chain (1) Collection cross-chain mechanism Participating companies, regulatory authorities, and consumers involved in each batch of the rice supply chain are involved in the data interaction of multiple chains when collecting data in real-time. To ensure data security in the process of the data cross-chain, we designed a collection cross-chain mechanism, as shown in Figure 3. First, various companies, regulatory agencies, and consumers must be certified in the supply chain. When data needs to be stored on the chain, the user sends a request to CCSC-A. After CCSC-A is authenticated, storage permissions will be opened to users. The data collected by the collection equipment is standardized and processed to form D (all data) and Ds (data digest). CCSC-A encrypts D with a hash lock to form a ciphertext Dn. Hash lock is described as N (random number) and is randomly generated, and then H(N) (a unique hash value of N) is generated, where N is the decryption key of D, and H(N) is the dongle of D. CCSC-A obtains pkp (user’s public key), and it uses pkp to encrypt Dn. Ds and H(N) to form DATA (data packet). CCSC-A transmits the DATA fragments to the relay chain; that is, each node only owns a part of the DATA. Then, T (time lock) is designed. Within the range of T, each node of the relay chain reaches a consensus and randomly selects a node to restore DATA through the game. In the restoration process, each node endorses the DATA slice. When time T ends, each node will automatically encrypt DATA, and the encryption result is returned to CCSC-A for verification. When CCSC-A receives the results returned by more than 51% of the nodes in the relay chain, it can be determined that the DATA slice in the relay chain has been processed. After the endorsement of each node in the relay chain is completed, CCSC-B obtains skp (user’s private key) for decryption, and Ds, Dn, and H(N) are obtained. CCSC-B calls the concurrency mechanism to process Ds, then prestores Ds and returns the address AD. After that, CCSC-B uses H(N) to encrypt AD. CCSC-A calls CCSC-B, the contract enters N, decrypts to obtain AD, and stores it on the main chain. After CCSC-B obtains N, it decrypts Dn, and obtains D. The same operation is performed on D to obtain the data digest, which matches with Ds to verify whether D has been tampered with. Finally, the data is stored on the chain according to AD. The above data interaction needs to be done within T time and only once, otherwise CCSC-A will terminate this data upload. Regarding the security of the relay chain, the endorsement of each relay chain in the cross-chain data can be used to monitor and review problem nodes. Algorithms 1 and 2 shows the pseudo-code design of the CCSC-A and the CCSC-B mentioned in the cross-chain collection process. The detailed logic design of Algorithms 1 and 2 is provided in Appendix A. Among them, H (user) is the user’s only hash, Y is the storage success certificate, and F is the storage failure notification. There is a mutual calling relationship between CCSC-A and CCSC-B. This mechanism guarantees storage security during the data storage process through relay chains, hash locks, and cross-chain smart contracts. It can respond to attacks promptly and realize the trusted data storage of this model. Algorithm 1 Collect cross-chain smart contract A(CCSC-A) Input: H(user); D; Dn; DATA; Ds; T; AD; CCSC-B; pkp; Y; F; 1:func Certification(H(user)) (D) // Data acquisition module 2:func Hash lock(D)// Data encryption module 3:func Slice(DATA)// Data fragmentation module 4:func Game(Relay chain (node))// Game module 5:func Get(AD)// Storage module Algorithm 2 Collect cross-chain smart contract B(CCSC-B) Input: DATA; CCSC- A; N; skp func Get-Crack (DATA,skp)// Obtain DATA and use user skp to decrypt to obtain Ds, etc. func Pre-stored(Ds)// Pre-storage based on data summary, get AD func Get(N)// Obtain N through data interaction, and generate Y/F to CCSC-A func Storage(D)// Store according to the pre-stored address (2) Regulatory cross-chain mechanism When the main chain supervisory authority needs to supervise the data, the supervisory data may involve data interaction between multiple chains. To ensure that the data is not tampered with or misappropriated during the transmission process, a supervision cross-chain mechanism was designed to ensure the safety of supervision data transmission. Figure 4 shows this supervision cross-chain mechanism. The supervisory authority node on the main chain sends a supervisory request to SCSC-A and submits the required supervisory cross-chain data request to SCSC-A. SCSC-A verifies its unique hash value, and if the permissions match, the request is passed. The supervision of cross-chain data requests is standardized by SCSC-A. The required data may exist in multiple subchains. Therefore, SCSC-A uses a concurrent mechanism to preprocess the data to be viewed by the regulatory agency. SCSC-A supervises the location of the cross-chain data stored in parallel blockchains and puts the request into the cross-chain waiting queue of each parallel blockchain. Each parallel blockchain sends data to SCSC-A, and the contract integrates it to form Data (supervised cross-chain data). A random number N is formed, and a unique hash value H(N) is generated. H(N) encrypts Data to form Dn. At the same time, the time lock T is set by SCSC-A. SCSC-A calls the pkp of the main chain supervision department to encrypt Dn and H(N) to form DATA. Then the fragments are saved into the relay chain. Each node of the relay chain endorses the slice data. Then, the sorting node through the SPBFT consensus mechanism is selected randomly. The DATA is restored, and it is transmitted to SCSC-B. When the time interval T arrives, each node of the relay chain randomly encrypts and locks the data in the chain, and returns the encrypted hash value to SCSC-A. When SCSC-A receives feedback from more than 51% of the nodes in the relay chain, it can be determined that the cross-chain data in the relay chain has been destroyed. SCSC-B obtains skp and S (proof of authority) from the regulatory authority. Dn is obtained after SCSC-B uses skp to decrypt DATA. SCSC-B uses the same H(N) to encrypt S. After calling SCSC-B, SCSC-A decrypts with N to obtain S and uploads it to the parallel blockchain to record this data interaction. Finally, SCSC-B obtains the random number N at the same time. After the contract decrypts Dn, Data is obtained, and is sent to the supervisory authority. At the same time, the data slice in the relay chain is automatically destroyed. After SCSC-B decrypts, it sends a decryption success message to SCSC-A, and the data cross-chain is completed this time. If SCSC-A does not receive a message within the time range T, the cross-chain fails this time, and SCSC-A initiates emergency measures to encrypt and block all designed cross-chain data. The supervisory cross-chain mechanism relies on the mutual calls between SCSC-A and SCSC-B to realize the safe transmission of data and ensure the security of the supervisory data. To this end, we designed the smart contract pseudo code, where H(S) is the hash of the regulatory authority, V is the notification of successful decryption, and IR is the data interaction record. Algorithm 3 shows the pseudo-code of SCSC-A, and Algorithm 4 shows the pseudo-code of SCSC-B. The detailed logic design of Algorithms 3 and 4 is given in Appendix A. Algorithm 3 Supervise cross-chain smart contract A(SCSC-A) Input H(S); Ds; PA; SCSC-B; V; IR 1: func Certification(H(S))//Verify Permissions 2: func Pretreatment(D)//Cross-chain request preprocessing 3: func Integration(Data)//Form a supervised cross-chain data Data 4: func Slice(DATA)//DATA slices are stored in the relay chain 5: func Storage(IR)//Interactive record storage 6: func Destroy(S)//Call SCSC-B, decrypt, and get S 7: func Determine(V)//Time lock trigger design, including trigger conditions and trigger results Algorithm 4 Supervise cross-chain smart contract B(SCSC-B) Input Data; N; SCSC-A; skp; T; DATA func Decrypt(DATA)//Decrypt DATA with skp func Get(N)//Get N, pass S func Get(Data)//Decrypt to get Data func Transport(Data) func Self-defense(T, SCSC-A)//Anti-attack design 4.2.2. Concurrency Mechanism Based on K-Means Algorithm and Bloom Filter A data cross-chain is prone to high concurrency problems. First of all, when the main chain node needs to cross-chain storage and the number of cross-chain invocations is too large at the same time, the amount of data that the smart contract needs to process far exceeds the designed amount of data, which is likely to cause data cross-chain blockage, which can seriously cause cross-chain “paralysis”. At this time, a “traffic policeman” is needed to command the data and realize the orderly cross-chain of data. To deal with the problem of high concurrency of cross-chain data, the K-means clustering algorithm was used to preprocess the cross-chain data to achieve orderly cross-chain data. In addition, each time the cross-chain data was required to involve multiple parallel chains. As time increased, as well as the expansion and subdivision of cross-chain data types, it would cause the amount of calculations needed to confirm the storage location of cross-chain data to increase linearly. We applied a Bloom filter for processing, thereby greatly reducing the amount of calculations needed. Through the organic combination of the K-means clustering algorithm and the Bloom filter, the problem of data cross-chain concurrency was solved. Figure 5 shows the concurrency mechanism. First, the required cross-chain data packet Data is defined, with each packet containing multiple cross-chain data, as shown in Equation (1):(1) Data=Applicant(121,5,123)Applicant(151,1,1523)Applicant(11,9,13)……Applicant(i,j,m) Each piece of the data in the formula is associated with the applicant’s hash. Data are in a three-dimensional representation, where i is the rice batch, j is the link, and m is the specific number of rows in the database. We separately specified these three variables, where j corresponds to a total of 13 links in the rice supply chain, and the value of m corresponds to the specific position of the required cross-chain data in the nine parallel chains. The K-means algorithm is an unsupervised learning algorithm that automatically clusters sample data based on the measurement standard of the correlation between data samples. Its objective function is shown in Equation (2):(2) argmin∑i=1k∑t=1nipt−ui2 In the formula, k is the number of clusters; ni is the number of sample points in cluster i; pt is the t-th data sample; and ui is the centroid of cluster i. We clustered the sample data based on the Euclidean distance between the sample data and the centroid, as shown in Equation (3):(3) d(t,i)=∑pt−ui2 We designed a secondary clustering method to preprocess the concurrency of cross-chain data. The K-means algorithm design was as follows:(1) Initial clustering. First, initialize the k value according to the preset nine parallel blockchain data storage ranges. The k value is the number of m across the parallel blockchain in the data packet, which is determined by the maximum and minimum values of m. In addition, we determined the corresponding initial test centroid according to the value of m, as shown in Equation (4):(4) c=m1+m2+m3+m4+……+mnn The c value is the mean value of each part after sorting the values from small to large and dividing them into k parts, and clustering the cross-chain data on the value of m. The purpose was to form the distribution form of I as shown in Figure 5 for the cross-chain data packet (Data) in preparation for the secondary clustering. Different colors in I represent different data requests. (2) Secondary clustering. According to the similarity of the values of i and j, two clusters were performed based on the first clustering to form the distribution state of II shown in Figure 5. The different colors in II represent the data classified into different categories after the secondary clustering. The method of secondary clustering was used to make the data in Data clustered when the storage locations of the same or similar batches and links were similar, thereby reducing the number of search calculations. A Bloom filter is a binary data structure used to determine whether an element is in a set. After the Data were clustered by the K-means algorithm, k data blocks were formed. At this time, it was only necessary to verify a random piece of data in each data block to determine the names of the parallel blockchains of all elements in the data block. Specifically, a Bloom filter was designed for each parallel blockchain, and the hash of the data contained in each parallel blockchain was mapped to the Bloom filter in advance. When verification was required, only nine parallel-chain Bloom filters were required to judge the data to be determined, and then specific classifications could be carried out. When a large amount of data needs to be cross-chained, a time level “T” was designed to control the data of each cross-chain. We used the organic combination of the K-means algorithm and Bloom filter to quickly determine the parallel chain where the data were located within T time, thereby improving the efficiency of the data cross-chain, and the problem of high concurrency of cross-chain data was resolved. 4.2.3. SPBFT Consensus Mechanism SPBFT Consensus Algorithm The consensus mechanism is an important component of blockchain technology. The cross-chain supervision model of the rice supply chain involved the main chain, relay chain, and multiple parallel chains. Reaching a consensus among the main chain, relay chain, and parallel blockchain was the basis for the implementation of the cross-chain supervision of each node in the rice supply chain. PBFT is an election consensus algorithm for a single-chain structure. It is not suitable for multichain consensus. We designed the SPBFT consensus algorithm based on the voting consensus algorithm PBFT. Figure 6 shows the SPBFT consensus algorithm. We adopted the consensus method of “Chain link Chain” to achieve a consensus among the main chain, parallel blockchain, and relay chain. For the main chain, each supervisory node, enterprise node, and consumer node processed messages through the node status (consistency) of each stage to achieve a complete message-processing state, thereby achieving consensus. For parallel blockchains and relay chains, the SPBFT consensus algorithm was used to realize the migration of the information state from the parallel blockchain to the main chain, and the consistency of the states of the parallel blockchain nodes and the main chain nodes was realized. Finally, “Chain link Chain” → “Node link Node” was realized. SPBFT Consensus Process The SPBFT consensus process of the main chain, parallel blockchain, and relay chain selected different consensus steps according to different types of blockchains. Figure 7 shows the SPBFT consensus sequence diagram. The SPBFT had six steps. Compared with the PBFT consensus mechanism, a competition step was added to adapt to multichain consensus. For steps I–VI, the specific descriptions are as follows. Request: Client C sends a request to the master node. Preprepare: The master node assigned a unique number n to the request, and formed a preprepare message with the request. After signing, the preprepare message was delivered to all member nodes. The unique number n consisted of the type, the parallel blockchain number, and the request number. The parallel blockchain number here was only assigned when the parallel blockchain consensus was reached, and the rest were preset to 0, which aimed to solve the multichain consensus concurrency problem. Prepare: When the member node received the preprepare message, it relied on the signature to judge the correctness of the message, and it judged whether to accept it or not. After confirming that it was correct, the signature of this section and n were combined to form a prepared message, and the message was broadcasted to all other member nodes. Commit: After receiving the prepare message, all nodes verified the correctness by signing. If the number of prepared messages received by each node exceeded two-thirds of the total number of nodes, it broadcasted a commit message to all nodes, indicating that the node could perform the requested service. Competition: The competition stage was dedicated to the consensus of the relay chain. Our initial definition was that all nodes in the relay chain were trusted nodes. After all nodes received the commit message, every two nodes played a free game. All nodes broadcasted game information, game rounds, and signatures to other nodes, where the signatures were the signature verifications performed by the node that failed the game. After receiving the message, other nodes confirmed the winning node by verifying the signature and the number of signatures. The winning node performed the second round of the game and sent game messages until the only winning node was selected after N rounds. The winning node sent the game information and signatures of N other nodes to all nodes to form a game message competition. Reply: All nodes, if they received a commit message, verified the correctness of the message. If the number of commit messages exceeded one-third of all nodes, the business of the request was completed, and a reply message was constructed to reply to the client. The client judged whether the system had completed the request based on whether it had received the correct reply from more than one-third of the nodes. For the relay chain consensus, all nodes received the competition message and verified the correctness of the message. The winning node completed the business requested by the request. Then, it constructed a reply message, and it directly replied to the client. The client judged whether the system had completed the request based on whether it had received the correct reply from more than one-third of the nodes. For the main chain consensus, we assumed that the total number of main chain nodes was n, the number of error nodes was f, and the number of malicious nodes was f. To ensure the security of the consensus, the number of secure nodes needed to be controlled above f + 1 nodes. According to Equation (5), the number of nonsecure nodes that the main chain could tolerate was (n − 1)/3. The process of the main chain consensus was the traditional PBFT consensus step. The nodes only involved the nodes of the main chain, and did not involve the relay chain and parallel blockchains. (5) f+f+f+1=n→f=(n−1)/3 For the parallel blockchain consensus, the consensus reached involved each node of the parallel blockchain and each node of the main chain. The specific consensus process was: the client initiated a request message on the main chain, and the main chain broadcasted the message to each node of the parallel blockchain. Each node of the parallel blockchain completed steps I–IV independently, and cross-chains to each node of the main chain after the reply message were constructed in step VI. The reply message was used as the request for the second round of consensus on the main chain, and each node of the main chain would directly reply to the client after reaching a reply-1 message. Regarding the consensus of the relay chain, the achievement of the consensus involved each node of the relay chain and each node of the main chain. Specifically, the client initiated a request message on the main chain, and the main chain broadcasted the message to each node of the relay chain. Each node of the relay chain completed step IV independently, and after constructing the reply message in step VI, it broadcasted to each node of the main chain. The reply message was used as the request for the second round of consensus on the main chain, and each node of the main chain reached a reply-2 to the client after the message. 5. Results and Analysis 5.1. Operation Process Analysis The cross-chain model of rice supply chain supervision based on the blockchain and smart contracts fundamentally solved the serious problem of supply chain centralization, and achieved complete decentralization of data. Figure 8 shows the mode flow chart. We analyzed the operation process, and the results showed that the multichain model could effectively realize the supervision of the entire life cycle of the rice supply chain by the supervisory authority. The cross-chain model of the rice supply chain was divided into cross-chain collection of data and cross-chain supervision of data, and they respectively corresponded to trusted cross-chain storage of data and trusted cross-chain supervision. For a cross-chain collection of data, the participating enterprise nodes of the main chain used data-collection equipment to collect data. The identity of the request initiator was verified by CCSC-A, and hash locking and asymmetric encryption were used to encrypt the data. The fragments were stored in the relay chain. Each node of the relay chain realized the distribution of reorganization rights through the game method. The data summary by CCSC-B was used to prestore the data, and the corresponding storage address was obtained. The address was encrypted by the same hash lock, and mutual decryption of encrypted data was realized through mutual calls between CCSC-A and CCSC-B. Finally, the safe storage of data was realized within the specified time. For the cross-chain supervised data, the main chain supervising node initiated a data call view request, and used SCSC-A to verify its identity. After that, the requested data were preprocessed, and the request was sent to the parallel blockchain. Through SPBFT, the parallel blockchain transmitted the data to SCSC-A, which was hash locked and asymmetrically encrypted by SCSC-A, and then it was fragmented into the relay chain. The winning node of the relay chain game sorted the data and sent it to SCSC-B, which then used the same hash lock to encrypt the identity certification document of the regulatory authority. Then, SCSC-B realized the decryption of the data through mutual calls with SCSC-A. Finally, SCSC-B sent the data to the supervisory department, and SCSC-A stored the invocation information of the supervisory department on the parallel blockchain to realize the on-chain storage of the data interaction records. This mode could realize the safe storage and call of data between the main chain and the parallel blockchain. It was a completely feasible and credible mode. The model could realize the trusted cross-chain transmission of data among the main chain’s various regulatory department nodes, enterprise nodes, and consumer nodes. Given the complex links, the long life cycle, and the diversity of participants in the rice supply chain, this multichain model could achieve safe, effective, and completely credible supervision of rice quality. 5.2. Security Analysis In the process of data cross-chain transmission, it is easy to encounter malicious attacks, and it is easy to cause cross-chain data to be attacked by Sybil attacks, data tampering, data leakage, data theft, etc. (Table 4). The cross-chain supervision model of the rice supply chain based on blockchain and smart contracts can effectively resist the attacks mentioned in the table. Regarding the challenge of the consensus mechanism, the SPBFT consensus mechanism was used to achieve a secure consensus on the main chain, parallel blockchain, and relay chain. The parallel blockchain is a storage chain; its purpose is only to share the storage pressure on the main chain. The relay chain itself is a trusted chain, and a notary exists in the form of a blockchain. Therefore, the SPBFT consensus mechanism adopts the “chain link”. It can tolerate less than one-third of invalid or malicious nodes. For a Sybil attack, during the cross-chain process, a cross-chain smart contract is customized. The contract can verify the identity of the main chain node and upload the node’s identity certificate to the parallel blockchain storage, which can effectively prevent the cross-chain process from being attacked. To counter the risk of data leakage, tampering, and loss, a four-fold guarantee mechanism was designed to ensure data security. The first guarantee mechanism was the hash lock mechanism, which encrypted the data by generating a unique hash value through a number generated randomly. Through the time lock and the hash lock, the “counterparty risk” in data transmission was prevented. The second guarantee mechanism was an asymmetric encryption mechanism, which encrypted the data locked by the hash and the hash value through the public key of the applicant, preventing other nodes from using the hash value to “steal” the random number to decrypt the data. The third guarantee was the relay chain mechanism. After the data were encrypted, slices were stored in the relay chain. Each node contained only part of the encrypted data, and the time T was set. After the transmission was completed, the data were automatically encrypted and locked. In addition, each node of the relay chain obtained the right to reorganize through the game, which increased the predictable complexity of the position of the reorganized node, thereby ensuring data security. The fourth guarantee was the smart contract mechanism. Through the automatic inspection and nontamperability of the smart contract, the smart contract was customized to verify the identity of the personnel and assist in the credible cross-chain transmission of data. We conducted experimental simulations on the multichain supervision model of the rice supply chain and adopted a cloud server, which was configured with a four-core CPU, 8 GB of RAM, and a 50 GB high-performance cloud hard drive. The cloud server had 32 nodes, of which 8 were used as main chain nodes, corresponding to the representative enterprises in the six main links of the rice supply chain and two supervisory departments. Among them, six were arranged as relay chain nodes, and the relay chain game adopted CFR (the Virtual Regret Minimization Algorithm). The remaining 18 nodes built three parallel blockchains, and each parallel blockchain deployed six nodes, corresponding to stored corporate information, supervisor information, and cost information. Different malicious nodes and wrong nodes were set up to test the correctness of the cross-chain transmission in the multichain supervision model of the rice supply chain. The test set was divided into three groups, and the number of error nodes in each group was 0, 1, and 3, respectively. Each test set performed 500 cross-chains for data collection and cross-chains for supervision data. Since the parallel blockchain and relay chain nodes were trustworthy, the faulty nodes were deployed to the main chain node for testing. The SPBFT consensus mechanism could effectively tolerate failures below 30% (only for the main chain nodes), and the cross-chain success rate reached 100%, which could fully guarantee the security of data cross-chain transmission. 5.3. Efficiency Analysis The performance of the multichain architecture was tested and analyzed, mainly for cross-chain concurrency issues. For the concurrency problem, this study adopted secondary clustering, and equipped each parallel blockchain with a Bloom filter to solve the cross-chain concurrency. This study used experimental simulation to transmit 50,000 sets of data at the same time to test the concurrent processing capabilities of the rice supply chain. First of all, the concurrency mechanism performed the first clustering. Figure 9a shows the first clustering situation. The abscissa shows the cluster center of the data, and the ordinate is the number of data. After the clustering was successful, each cluster randomly selected a piece of data to match with the Bloom filter in the parallel blockchain. Screening was performed to determine the parallel blockchain represented by each cluster. The first clustering took 0.60823 s and was iterated six times in total. The results showed that the data could match the corresponding parallel blockchain position after a hash conversion. Secondary clustering of the 12,695 sets of the first chain’s data was performed to facilitate the data search. Figure 9b shows the second clustering situation. The abscissa shows the cluster center of the data, and the ordinate is the number of data. The second clustering took 1.32542 s in total and was iterated 22 times. The results showed that the test data set stored in the first chain were concentrated in the 63rd and 101st batches. Through a simulation analysis, the mechanism could effectively prevent the occurrence of concurrency. The data filtered by the K-means algorithm and Bloom filter clustering could increase the cross-chain speed and quickly determine the specific location of its storage. 5.4. Scalable Analysis The research on the cross-chain model of rice supply chain supervision based on the blockchain and smart contracts showed that the model has good scalability. It is not only suitable for the supervision of the rice supply chain, but also has universality in the fields of the supply chain, medical care, and finance. Specifically, the cross-chain mechanism based on “hash lock + relay chain + cross-chain smart contract” adds data to cross-chain transmission mechanisms such as the notary mechanism, relay/side chain mechanism, and hash lock mechanism, and the complexity is cracked. It also adds a cross-chain attacked emergency locking mechanism. It is safe and realizes the safe storage and transmission of data, which expands the multichain from the initial asset exchange to other industries. The concurrency mechanism based on the K-means algorithm and Bloom filter can play a good role in improving big data and multirequest situations, and it can effectively deal with the occurrence of concurrency problems. The SPBFT consensus mechanism we designed can achieve consensus among multiple chains, and in a true sense realize the interconnection of multiple chains. This makes SPBFT not only applicable to the rice supply chain, but the consensus can also be extended to other supply chain applications, to better ensure product quality and safety. 5.5. Discussion Since entering the era of blockchain 2.0, researchers have begun to study the application of cross-chain technology in all walks of life. They have studied the use of multichain systems to replace the existing single-chain systems to improve the performance and efficiency of the blockchain. In [10], Bhaskara et al. proposed a novel blockchain-based architecture, Fortified-Chain. They introduced a hybrid computing paradigm of blockchain-based distributed data-storage systems. Their research overcomes the shortcomings of blockchain-based cloud-centric healthcare systems, such as high latency, high storage costs, and a single point of failure. In [13], Peng et al. designed a two-tier blockchain structure for vaccine production regulation that was used to address the shortcomings of traditional centralized management. In [14], Laavanya et al. proposed a blockchain-integrated, privacy-assured IOMT framework for stress management while considering sleeping habits, in which every user was assigned their own private permissioned blockchain to ensure data storage and privacy. We compared and analyzed the information supervision models of the rice supply chain based on parallel blockchains and smart contracts designed in this study, as shown in Table 5. In terms of security, the authors of [10] designed a three-layer fortified-chain architecture, as well as a patient-anonymization mechanism. The authors used a selective ring-based access-control mechanism, which had a good performance in terms of fault tolerance, attack diversity, security recoverability, attack cost, and efficiency, but its application scenario was limited to the healthcare domain, its scalability was insufficient, and its latency was high. Ref. [13] designed a two-layer blockchain structure, as well as a multinode cooperative consensus mechanism. It had a better performance in terms of fault tolerance, attack diversity, security recovery, attack cost, and efficiency, but its application scenario was limited to vaccine production, its scalability was insufficient, and there were no major improvements in throughput or latency. The authors of [14] designed a multichain storage architecture and RSA encryption mechanism with a POW consensus mechanism, which had a better performance in terms of fault tolerance and efficiency. However, it performed poorly in terms of attack diversity, security recovery, and attack cost; was insufficiently scalable; and had high latency. In this paper, we designed a four-fold guarantee mechanism including hash locking, asymmetric encryption, a relay chain, and a smart contract to resist various attacks, and we designed the SPBFT consensus mechanism, which had a better performance in terms of fault tolerance, attack diversity, security recovery, and attack cost. The model we designed used concurrent mechanisms based on K-means clustering and a Bloom filter, which were more efficient in combination and more scalable. However, the resource consumption of the model designed in this paper was still high compared to the traditional single-chain architecture. 6. Conclusions and Future Work To strengthen the capabilities of rice supply chain supervision under an epidemic, a rice supply chain supervision cross-chain model based on blockchain theory and smart contract technology was designed. Firstly, this study constructed an overall analysis of the rice supply chain, and we abstracted the main links of the entire supply chain. Then, the supply chain data were divided into parallel chains. Secondly, a cross-chain model of rice supply chain supervision was designed. The model included a cross-chain framework for rice supply chain supervision, a cross-chain mechanism based on “hash lock + smart contract + relay chain”, a concurrency mechanism based on K-means clustering and a Bloom filter, and an SPBFT consensus mechanism. Finally, the operation process, safety, efficiency, and scalability of the model were analyzed in this study. The results showed that this model research was an innovative practice in rice regulation by applying the multichain model to rice supervision. In terms of the entire rice supply chain industry, this model strengthened the exchange of information between different links of rice, and realized point-to-point real-time data exchange between different types of enterprises in the rice supply chain. In terms of credible supervision of the rice supply chain, it improved the cohesion of supervisors with the data of the entire rice supply chain. The model strengthened the coupling between rice supply chain data, basic information, harmful substance information, and personnel identity information, and realized the refined management of rice supply chain data and personnel. In terms of the model technology of the entire rice supply chain, the convenience and security of cross-chain data interaction between each link of the rice supply chain was improved, and the storage cost of supply chain data and the high latency of interaction were reduced. We realized the credible supervision of rice data with better distributed ledger technology, ensuring the quality and safety of rice. A comparison of our proposed model with the traditional centralized management model and other popular blockchain-based methods for managing agricultural and food information is shown in Table 6. In the comparison, it can be seen that our proposed system had a high level of security and a relatively low cost due to the use of parallel chains for data storage and the customized design of smart contracts. The model could automatically and efficiently interact with the data, with less reliance on manual and storage devices. Since the SPBFT consensus mechanism was established based on the PBFT consensus mechanism, its fault node tolerance was one-third. To solve this problem, we will try to improve the SPBFT consensus mechanism to increase its fault tolerance. In addition, we will explore the combination of the cross-chain model with the identification analysis technology in the industrial internet and the Internet of Things. Applying the cross-chain model to the entire category of grain and oil supply chain supervision and other products’ supply chain supervision will be a direction of our future efforts. The cross-chain supervision model based on the rice supply chain was designed in this paper to apply to the unique links and information flow characteristics of the rice supply chain. After qualitative modifications of the supply chain architecture and information flow characteristics for other categories of cereals, the novel architecture, cross-chain mechanism, and concurrency mechanism proposed in this paper can be applied to the supply chain information management of all categories of cereals. This provides an idea for the information management of the whole grain oil category. This research provided a feasible and practical solution for accelerating the digital transformation of the food industry that can enhance the ability to supervise food crops and ensure food security. Author Contributions Conceptualization, X.Z. and X.P.; methodology, X.P.; software, X.W.; validation, J.X. and Z.Z.; formal analysis, J.X. and H.L.; investigation, X.W., J.X. and H.L.; data curation, X.Z. and X.P.; writing—original draft preparation, X.P.; writing—review and editing, X.P., X.Z., X.W. and J.X.; supervision, X.P., X.Z., X.W., J.X., Z.Z. and Y.W.; project administration, J.X. and Z.Z.; funding acquisition, X.P., X.Z., X.W., H.L, J.X., Z.Z. and Y.W. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The authors declare that the data supporting the findings of this study are available from the authors. Conflicts of Interest The authors declare no competing financial or nonfinancial interests. Appendix A Algorithm A1: Collect cross-chain smart contract A(CCSC-A) Input: H(user); D; Dn; DATA; Ds; T; AD; CCSC-B; pkp; Y; F; 1: func Certification(H(user)) (D) // Data acquisition module {  For t in range (m) If H(user) permissions match   Matching collection information:{Hazardous Material Information or corporate information or consumer information or regulatory agency information or transaction records or cost information or data interaction records or health records or other information} If Data validation after data standardization  Return Step 2 } 2: func Hash lock(D)// Data encryption module { For t in range (m) If D standards compliant   Get data summaries Ds D→N→H(N)// D takes a random number N and generates the corresponding hash value H(N) Dn←Encrypt H(N)(D)// Encrypt D using H(N) to generate ciphertext Dn DATA←Encryptpkp(Dn, H(N), Ds)// Use the user’s public key to integrate and encrypt Dn, H(N), and Ds to generate data packets DATA If Ds, H (N), Dn, DATA generate  Return true Return false } 3:func Slice(DATA)// Data Fragmentation Module{  For t in range (m) If Step 2 returns true Slice(DATA)//DATA Fragmentation Send(DATA)→Relay chain (node)// Data shards are stored in each node of the relay chain Return true      Return false } 4:func Game(Relay chain (node))// Game module { For t in range (m) If Step 3 returns true Game(node)// The game of each node of the relay chain obtains the right of reorganization Return Relay chain (node)←DATA// Data normalization      Each node encrypts data shards and returns H(DATA) to the contract      If Judgment complete: Set(T)// Set time lock T Verify(H(DATA)>51%)// The amount of H (DATA) returned within T time is greater than 50% Return true Return exit } 5: func Get(AD)// storage module { If Step 4 returns true Transfer(CCSC-B) Return CCSC-A→N; AD→CCSC-A// N and AD exchange to obtain Store AD to the blockchain If   Store successfully verified: Verify(Decrypt (D)) →Y/F// Verification of CCSC-B decryption result notification Y/F Return Storage(AD) and true Return Exit and false //main chain, exit is interrupt cross-chain transmission in time } Algorithm A2: Collect cross-chain smart contract B(CCSC-B) Input: DATA; CCSC- A; N; skp 1:func Get-Crack (DATA, skp)// Obtain DATA and use user skp to decrypt to obtain Ds, etc. { For t in range (m) If Preliminary decryption of DATA:   Get user private key skp   Decrypt DATA   Return Dn, H(N), Ds and true } 2: func Pre-stored(Ds)// Pre-storage based on data summary, get AD { For t in range (m) If data pre-storage: Data preprocessing based on data summaries Return AD Return false } 3:func Get(N)// Obtain N through data interaction { For t in range (m) If Get random number N: Transfer(CCSC-A) Return CCSC-A→N; AD→CCSC-A// N and AD exchange to obtain If decrypt DATA:   Decrypt with N to get D   Get H(D) for D hash, verify whether D has been tampered with } 4: func Storage(D)// Store according to the pre-stored address { For t in range (m) If Data storage to parallel blockchain:   Store D to the corresponding parallel blockchain   Return Send Y/F to CCSC-A } Algorithm A3: Supervise cross-chain smart contract A(SCSC-A) Input H(S); Ds; S; SCSC-B; V; IR;DATA 1: func Certification(H(S))// Verify Permissions { For t in range (m) If HS permissions comply with  Return Accept cross-chain requests      Return false } 2: func Pretreatment(D)// Cross-chain request preprocessing { If  Data request preprocessing:    Request preprocessing based on concurrency mechanism based on K-means algorithm and Bloom filter   Return The location of the parachain where the requested data resides } 3: func Integration(Data)// Form a supervised cross-chain data Data { For t in range (m)      If Cross-chain supervision data processing:       Extract each parachain data to form Data       Generate a random number N, take the hash H(N), use H(N) to encrypt the Data, and get Dn       Get user pkp, encrypt H(N), Dn, get DATA       Return true Return false } 4: func Slice(DATA)// DATA slices are stored in the relay chain { For t in range (m)    If   Relay chain data processing:        Set the hash lock T        Data slices are stored to relay chain nodes        Each node of the relay chain plays a game, sorts the DATA, and transmits it to SCSC-B        If T ends         Return The DATA fragments of each node in the relay chain are automatically encrypted, and H(D) is sent to SCSC-A         If H(D)>=51%         Return true        Return false      Return false } 5: func Storage(IR)// Interactive record storage {   If  IR deal with:    IR: {Initiate the request related person information, request information, data transmission process information} Stored in the blockchain main chain    Return ture  else    Return false } Algorithm A4: Supervise cross-chain smart contract B(SCSC-B) InputData; N; SCSC-A; skp; T; DATA 1: func Decrypt(DATA)// Decrypt DATA with skp { For t in range (m)   If DATA processing:      Get user private key skp     Decrypt DATA, get Dn, H(N) } 2: func Get(N)// Get N, pass S { For t in range (m)     If   S processing:         Use the same H(N) for data encryption If      data exchange: Transfer(SCSC-B) Return SCSC-A→S; N→SCSC-B// Exchange N and S to obtain Return   false } 3: func Get(Data)// Decrypt to get Data { For t in range (m) If  Dn processing:    Decrypt Dn to get Data    Hash Ds to verify whether it has been tampered with    Return ture Return false } 4: func Transport(Data) { For t in range (m) If Data verification without tampering    Return Regulatory Authority and ture Return false } 5: func Self-defense(T, SCSC-A)// Anti-attack design { For t in range (m) If   Step 4 Back ture     Send (V)→SCSC-A If Attack handling:    Received the attack information of SCSC-A    Return Data is automatically encrypted } Figure 1 Schematic diagram of the classification of rice supply chain links. Figure 2 The cross-chain framework of rice supply chain supervision. Figure 3 Schematic diagram of collection cross-chain mechanism. Figure 4 Schematic diagram of supervision cross-chain mechanism. Figure 5 Schematic diagram of concurrency mechanism. Figure 6 Schematic diagram of SPBFT consensus algorithm. Figure 7 Schematic diagram of SPBFT consensus sequence diagram. Figure 8 Schematic diagram of mode flow. Figure 9 Concurrent simulation. (a) First clustering result graph; (b) Second clustering results graph. foods-11-01269-t001_Table 1 Table 1 Literature review classification table. Category Main Content References A theoretical study on the framework or model of agricultural products and food management based on the blockchain and smart contracts Exploring the advantages of blockchain applications in agricultural products and food management frameworks or models [19,20,25,29] Research on information management of agricultural products and food based on the blockchain and smart contracts Focus on changing the traditional centralized management model through the decentralized nature of the blockchain, which is used to strengthen the information control ability of agricultural products and food [1,24,32,35,38] Research on traceability of agricultural products and food information based on the blockchain and smart contracts Improve information traceability of agricultural and food products by using the characteristics of the blockchain such as nontamperability and transparency [21,22,33] Blockchain-based applications for the integration of agricultural products and food with the Internet of Things, etc. The integration of technologies such as the Internet of Things and the blockchain is used to improve the information traceability and management of agricultural products and food. [17,28,30,34] foods-11-01269-t002_Table 2 Table 2 Parallel blockchain data division. Batch: Parallel Blockchain Key Data I Hazard information Mycotoxins, heavy metals, pesticide residues, pests, fumigants and herbicide residues, abnormal temperature and humidity, mildew, generated fungi, and toxins. II Corporate information Company name, company address, company contact information, business license, main business, legal representative, legal person contact information, registered capital, and enterprise nature. III Consumer information Identity information, contact information, home address, the purpose of the purchase, time of purchase, place of purchase, goods purchased, and product shelf life. IV Regulatory information Institution name, department, supervision link, link standard description, rules and regulations, prevention and control strategies, supervision data, supervision progress, information of responsible personnel, problem product records, qualified product records, supervision time, and supervision methods. V Transaction record Purchase price, purchase source, purchase time, purchase amount of fertilizers, seeds, pesticides, films, etc.; use of planting equipment, purchaser information, seller information, real-time purchase price, purchase time, etc., drying equipment purchase information record, drying staff salary record, plant expense records, etc., impurity removal equipment, drug purchase information records, site expense records, etc., storage time, expense information records, rice batches, ridge equipment purchase information records, equipment maintenance costs, parts purchase records, rice milling equipment purchases information record, color sorting equipment purchase information record, polishing equipment purchase information record, impurity removal equipment purchase information record, worker salary record, storage time, expense record; management record, transportation distance record, driver salary record, distance cost record, sales batch second, sales records, and venue rental records. VI Cost information Seed price, fertilizer price, labor cost, total cost, sales price, labor cost, drying (equipment, etc.) cost, cleaning (medicine, equipment, etc.) cost, storage (warehouse, tools, etc.) cost, storage price, ridged valley (equipment, etc.) cost, rice milling (equipment, etc.) cost, color sorting (equipment, etc.) cost, polishing (equipment) cost, packaging cost, primary product price, warehousing cost, outgoing price, transportation cost, driver’s salary, high-speed fee, purchase price, sales price, venue cost, sales staff salary, and publicity expenses. VII Data interaction record Supervision, query data records, traceability records, and access records. VIII Health record Site hygiene conditions, daily dressing records, daily disinfection records, and cleaning records. IX Information Seed source, production site, planting/harvesting time, rice yield rate, fertilizer/pesticide use information, purchase batch, purchase inspection report, drying record report, pharmaceutical use record, impurity content, impurity removal rate, inventory number, product batch, product source, quality inspection report, product category, product quantity, ridged grain method, equipment inspection record, ridged grain time, roughness removal/husking rate, rice milling method, equipment inspection record, entire rice/broken rice rate, color selection accuracy, carry-out ratio, polishing method, polishing rate, packaging material source, packaging material qualification certificate, product quality information, temperature and humidity record report, storage time, storage time, transportation vehicle information, vehicle disinfection report, departure place, route, arrival time, driver information, product name, product integrity rate, purchase time, sales time, sales address, and product quantity. foods-11-01269-t003_Table 3 Table 3 Permission data table. Batch: Node Function Permissions I II III IV V VI VII VIII IX Regulatory Authority National Grain Administration √ √ √ √ √ √ √ √ √ Ministry of Finance √ √ √ √ √ √ √ √ Ministry of Health √ √ √ √ √ √ √ State Administration for Industry and Commerce √ √ √ √ √ √ General Administration of Quality Supervision, Inspection and Quarantine √ √ √ √ √ √ √ √ Ministry of Agriculture √ √ √ √ √ √ √ foods-11-01269-t004_Table 4 Table 4 Attack descriptions. Attack Type Description Consensus mechanism challenge Whether the consensus algorithm between the parallel blockchain and the main chain can achieve real security. Witch attack A malicious node illegally presents multiple identities to the outside world and conducts malicious behaviors after mastering multiple nodes. Data leakage risk When data is transmitted between the parallel blockchain and the main chain, malicious nodes attack, resulting in the leakage of data information. Data tampering risk In the cross-chain process, malicious nodes attack and tamper with the data during data transmission, resulting in untrustworthy data. Data loss risk In the cross-chain process, data is “dropped out”, resulting in data loss. foods-11-01269-t005_Table 5 Table 5 Comparative analysis table. Performance Index Ref. [10] Ref. [13] Ref. [14] Our Study Security Fault Tolerance Middle High High Middle Attack Diversity High High Low High Security Recovery High High Middle High Attack Cost High High Middle High Model Efficiency Throughout Capacity High Middle Middle High Delay Middle Middle High low Scalability Resource Consumption High High High High Application Scalability Middle Low Low High foods-11-01269-t006_Table 6 Table 6 Comparison of different blockchain application models in agricultural products and food information management. Category Information Regulation Method Labor Cost Equipment Cost Security Level Traditional centralized management model Manual processing High High Low Blockchain + InterPlanetary File System (IPFS) Machine processing Low High Middle Blockchain + local database Machine processing Low High Middle Blockchain + cloud database Machine processing Low High Middle This study Machine processing Low Low High Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hao Z. Wang G. Mao D. Zhang B. Li H. Zuo M. Zhao Z. Yen J. A novel method for food market regulation by emotional tendencies predictions from food reviews based on blockchain and saes Foods 2021 10 1398 10.3390/foods10061398 34204245 2. Wu Q. Wu J. Ren M. Zhang X. Wang L. Modification of insoluble dietary fiber from rice bran with dynamic high pressure microfluidization: Cd(II) adsorption capacity and behavior Innov. Food Sci. Emerg. Technol. 2021 73 102765 10.1016/j.ifset.2021.102765 3. Wei L. Zhang J. Wang C. Liao W. Recent progress in the knowledge on the alleviating effect of nitric oxide on heavy metal stress in plants Plant Physiol. Biochem. 2020 147 161 171 10.1016/j.plaphy.2019.12.021 31865162 4. Li Y. Li Y. Chen Z. Bu L. Shi F. Huang J. High-temperature air fluidization improves cooking and eating quality and storage stability of brown rice Innov. Food Sci. Emerg. Technol. 2020 67 102536 10.1016/j.ifset.2020.102536 5. Zhou Z. Wang B. Dong M. Ota K. Secure and Efficient Vehicle-to-Grid Energy Trading in Cyber Physical Systems: Integration of Blockchain and Edge Computing IEEE Trans. Syst. Man Cybern. Syst. 2019 50 43 57 10.1109/TSMC.2019.2896323 6. Saad M. Qin Z. Ren K. Nyang D. Mohaisen D. e-PoS: Making Proof-of-Stake Decentralized and Fair IEEE Trans. Parallel Distrib. Syst. 2021 32 1961 1973 10.1109/TPDS.2020.3048853 7. Shayan M. Fung C. Yoon C.J.M. Beschastnikh I. Biscotti: A Blockchain System for Private and Secure Federated Learning IEEE Trans. Parallel Distrib. Syst. 2020 32 1513 1525 10.1109/TPDS.2020.3044223 8. Yuan Y. Wang F.Y. Towards blockchain-based intelligent transportation systems Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) Rio de Janeiro, Brazil 1–4 November 2016 2663 2668 9. Yu W. Luo K. Ding Y. You G. Hu K. A Parallel Smart Contract Model Proceedings of the 2018 International Conference on Machine Learning and Machine Intelligence Ha Noi, Vietnam 28–30 September 2018 Association for Computing Machinery New York, NY, USA 2018 72 77 10.1145/3278312.3278321 10. Egala B.S. Pradhan A.K. Badarla V. Mohanty S.P. Fortified-Chain: A Blockchain-Based Framework for Security and Privacy-Assured Internet of Medical Things with Effective Access Control IEEE Internet Things J. 2021 8 11717 11731 10.1109/JIOT.2021.3058946 11. Li W. Feng C. Zhang L. Xu H. Cao B. Imran M.A. A Scalable Multi-Layer PBFT Consensus for Blockchain IEEE Trans. Parallel Distrib. Syst. 2020 32 1146 1160 10.1109/TPDS.2020.3042392 12. Agyekum K.O.-B.O. Xia Q. Sifah E.B. Cobblah C.N.A. Xia H. Gao J. A Proxy Re-Encryption Approach to Secure Data Sharing in the Internet of Things Based on Blockchain IEEE Syst. J. 2021 16 1685 1696 10.1109/JSYST.2021.3076759 13. Peng S. Hu X. Zhang J. Xie X. Long C. Tian Z. Jiang H. An Efficient Double-Layer Blockchain Method for Vaccine Production Supervision IEEE Trans. NanoBioscience 2020 19 579 587 10.1109/TNB.2020.2999637 32603300 14. Rachakonda L. Bapatla A.K. Mohanty S.P. Kougianos E. SaYoPillow: Blockchain-Integrated Privacy-Assured IoMT Framework for Stress Management Considering Sleeping Habits IEEE Trans. Consum. Electron. 2020 67 20 29 10.1109/TCE.2020.3043683 15. Yanez W. Mahmud R. Bahsoon R. Zhang Y. Buyya R. Data Allocation Mechanism for Internet-of-Things Systems with Blockchain IEEE Internet Things J. 2020 7 3509 3522 10.1109/JIOT.2020.2972776 16. Huang C. Wang Z. Chen H. Hu Q. Zhang Q. Wang W. Guan X. RepChain: A Reputation-Based Secure, Fast, and High Incentive Blockchain System via Sharding IEEE Internet Things J. 2021 8 4291 4304 10.1109/JIOT.2020.3028449 17. Wang L. He Y. Wu Z. Design of a Blockchain-Enabled Traceability System Framework for Food Supply Chains Foods 2022 11 744 10.3390/foods11050744 35267377 18. Giraldo F.D. Barbosa Milton C. Gamboa C.E. Electronic Voting Using Blockchain and Smart Contracts: Proof of Concept IEEE Lat. Am. Trans. 2020 18 1743 1751 10.1109/TLA.2020.9387645 19. Kshetri N. DeFranco J. The Economics Behind Food Supply Blockchains Computer 2020 53 106 110 10.1109/MC.2020.3021549 20. Katsikouli P. Wilde A.S. Dragoni N. Høgh-Jensen H. On the benefits and challenges of blockchains for managing food supply chains J. Sci. Food Agric. 2020 101 2175 2181 10.1002/jsfa.10883 33063342 21. Li X. Huang D. Research on Value Integration Mode of Agricultural E-Commerce Industry Chain Based on Internet of Things and Blockchain Technology Wirel. Commun. Mob. Comput. 2020 2020 8889148 10.1155/2020/8889148 22. Shahid A. Almogren A. Javaid N. Al-Zahrani F.A. Zuair M. Alam M. Blockchain-Based Agri-Food Supply Chain: A Complete Solution IEEE Access 2020 8 69230 69243 10.1109/ACCESS.2020.2986257 23. Lin C. He D. Huang X. Xie X. Choo K.-K.R. PPChain: A Privacy-Preserving Permissioned Blockchain Architecture for Cryptocurrency and Other Regulated Applications IEEE Syst. J. 2020 15 4367 4378 10.1109/JSYST.2020.3019923 24. Iftekhar A. Cui X. Yang Y. Blockchain Technology for Trustworthy Operations in the Management of Strategic Grain Reserves Foods 2021 10 2323 10.3390/foods10102323 34681372 25. Liu Y. Ma X. Shu L. Hancke G.P. Abu-Mahfouz A.M. From Industry 4.0 to Agriculture 4.0: Current Status, Enabling Technologies, and Research Challenges IEEE Trans. Ind. Inform. 2020 17 4322 4334 10.1109/TII.2020.3003910 26. Ferrag M.A. Derdour M. Mukherjee M. Derhab A. Maglaras L. Janicke H. Blockchain Technologies for the Internet of Things: Research Issues and Challenges IEEE Internet Things J. 2019 6 2188 2204 10.1109/JIOT.2018.2882794 27. Li H. Han D. Tang M. A Privacy-Preserving Charging Scheme for Electric Vehicles Using Blockchain and Fog Computing IEEE Syst. J. 2020 15 3189 3200 10.1109/JSYST.2020.3009447 28. Son N.M. Nguyen T.-L. Huong P.T. Hien L.T. Novel System Using Blockchain for Origin Traceability of Agricultural Products Sens. Mater. 2021 33 601 10.18494/SAM.2021.2490 29. Feng H. Wang X. Duan Y. Zhang J. Zhang X. Applying blockchain technology to improve agri-food traceability: A review of development methods, benefits and challenges J. Clean. Prod. 2020 260 121031 10.1016/j.jclepro.2020.121031 30. Bhat S.A. Huang N.-F. Sofi I.B. Sultan M. Agriculture-Food Supply Chain Management Based on Blockchain and IoT: A Narrative on Enterprise Blockchain Interoperability Agriculture 2021 12 40 10.3390/agriculture12010040 31. Ray P.P. Dash D. Salah K. Kumar N. Blockchain for IoT-Based Healthcare: Background, Consensus, Platforms, and Use Cases IEEE Syst. J. 2020 15 85 94 10.1109/JSYST.2020.2963840 32. Xue Y. Liang X. Zhao D. A blockchain-based rice supply chain system MATEC Web Conf. 2021 336 09003 10.1051/matecconf/202133609003 33. Iftekhar A. Cui X. Blockchain-Based Traceability System That Ensures Food Safety Measures to Protect Consumer Safety and COVID-19 Free Supply Chains Foods 2021 10 1289 10.3390/foods10061289 34199825 34. Mondal S. Wijewardena K.P. Karuppuswami S. Kriti N. Kumar D. Chahal P. Blockchain Inspired RFID-Based Information Architecture for Food Supply Chain IEEE Internet Things J. 2019 6 5803 5813 10.1109/JIOT.2019.2907658 35. Zhang X. Sun P. Xu J. Wang X. Yu J. Zhao Z. Dong Y. Blockchain-Based Safety Management System for the Grain Supply Chain IEEE Access 2020 8 36398 36410 10.1109/ACCESS.2020.2975415 36. He W. Da Xu L. Integration of Distributed Enterprise Applications: A Survey IEEE Trans. Ind. Inform. 2012 10 35 42 10.1109/TII.2012.2189221 37. Vu N. Ghadge A. Bourlakis M. Blockchain adoption in food supply chains: A review and implementation framework Prod. Plan. Control 2021 2021 1 18 10.1080/09537287.2021.1939902 38. Tao Q. Cui X. Huang X. Leigh A.M. Gu H. Food Safety Supervision System Based on Hierarchical Multi-Domain Blockchain Network IEEE Access 2019 7 51817 51826 10.1109/ACCESS.2019.2911265 39. He Y. Zhang C. Wu B. Yang Y. Xiao K. Li H. A cross-chain trusted reputation scheme for a shared charging platform based on blockchain IEEE Internet Things J. 2021 1 10.1109/JIOT.2021.3099898 40. Zhu S. Cai Z. Hu H. Li Y. Li W. zkCrowd: A Hybrid Blockchain-Based Crowdsourcing Platform IEEE Trans. Ind. Inform. 2019 16 4196 4205 10.1109/TII.2019.2941735 41. Wang J. Zhang X. Xu J. Wang X. Li H. Zhao Z. Kong J. Blockchain-Based Information Supervision Model for Rice Supply Chains Comput. Intell. Neurosci. 2022 2022 2914571 10.1155/2022/2914571 35392045 42. Chen Q. Zhao Z. Wang X. Xiong K. Shi C. Microbiological predictive modeling and risk analysis based on the one-step kinetic integrated Wiener process Innov. Food Sci. Emerg. Technol. 2022 75 102912 10.1016/j.ifset.2021.102912

PMC009xxxxxx/PMC9099568.txt

==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094725 ijms-23-04725 Article Exploring Diverse Coagulation Factor XIII Subunit Expression Datasets: A Bioinformatic Analysis Jamil Muhammad Ahmer † Singh Sneha † El-Maarri Osman https://orcid.org/0000-0002-1585-4100 Oldenburg Johannes https://orcid.org/0000-0002-4103-5854 Biswas Arijit * Wautier Jean-Luc Academic Editor Institute of Experimental Hematology and Transfusion Medicine, University Hospital of Bonn, Building 043, Venusberg Campus 1, 53127 Bonn, Germany; muhammad.jamil@ukbonn.de (M.A.J.); sneha.gupta@ukbonn.de (S.S.); osman.elmaarri@ukb.uni-bonn.de (O.E.-M.); johannes.oldenburg@ukbonn.de (J.O.) * Correspondence: arijit.biswas@ukbonn.de; Tel.: +49-228-287-19428 † These authors contributed equally to this work. 25 4 2022 5 2022 23 9 472531 3 2022 18 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Coagulation factor XIII (FXIII) circulates in plasma as a pro-transglutaminase heterotetrameric complex (FXIIIA2B2), which upon activation by thrombin and calcium covalently crosslinks preformed fibrin polymers. The heterotetrameric complex is composed of a catalytic FXIIIA2 subunit and a protective/regulatory FXIII-B2 subunit coded by F13A1 and F13B genes, respectively. The catalytic FXIIIA2 subunit is encoded by the F13A1 gene, expressed primarily in cells of mesenchymal origin, whereas the FXIIIB subunit encoded by the F13B gene is expressed and secreted from hepatocytes. The plasma FXIIIA2 subunit, which earlier was believed to be secreted from cells of megakaryocytic lineage, is now understood to result primarily from resident macrophages. The regulation of the FXIII subunits at the genetic level is still poorly understood. The current study adopts a purely bioinformatic approach to analyze the temporal, time-specific expression array-data corresponding to both the subunits in specific cell lineages, with respect to the gene promoters. We analyze the differentially expressed genes correlated with F13A1 and F13B expression levels in an array of cell types, utilizing publicly available microarray data. We attempt to understand the regulatory mechanism underlying the variable expression of FXIIIA2 subunit in macrophages (M0, M1, M2 and aortic resident macrophages). Similarly, the FXIIIB2 subunit expression data from adult, fetal hepatocytes and embryonic stem cells derived hepatoblasts (hESC-hepatoblast) was analyzed. The results suggest regulatory dependence between the two FXIII subunits at the transcript level. Our analysis also predicts the involvement of the FXIIIA2 subunit in macrophage polarization, plaque stability, and inflammation. FXIII expression profiling micro-array RNA-Seq differential gene expression TRANSFAC gene ontology ingenuity pathway analysis DFGSI 2767-1/1 DFG for work on FXIII researchBI 1645/3-1 The position of S.S. is funded by DFG (SI 2767-1/1) under the individual research grant program awarded to S.S. The work in the lab of O.E.M. is partially supported by an investigator-initiated grant from TAKEDA (IIR-DE-002694). A.B has received funding from DFG for work on FXIII research (BI 1645/3-1). ==== Body pmc1. Introduction To prevent hemorrhagic trauma upon injury, activated fibrin molecules assemble to form strong mesh-like structures known as fibrin clot. Although the generation of fibrin clot marks the end of the blood coagulation cascade, the resulting soluble clot is still susceptible to premature fibrinolysis. The conversion of this soluble clot to an insoluble one resistant to premature fibrinolysis is ensured by the crosslinking of pre-formed fibrin polymers by coagulation Factor XIII (FXIII), by virtue of its transglutaminase activity. In plasma, FXIII exists with the heterotetramer zymogenic complex with dimeric catalytic FXIIIA subunits, and dimeric protective FXIIIB subunits bind non-covalently to each other. In plasma, the overall abundance of this pro-transglutaminase complex (FXIIIA2B2) is ≈68 nM, with the two subunits bound with high affinity (Kd 1.5 nM) [1]. Upon activation by thrombin and sequential calcium-binding, this complex dissociates, releasing the catalytically active monomeric FXIIIA subunit for cross-linking fibrin [2]. Only an insignificant amount of free FXIIIA is present in plasma, although there are almost two times the amount of FXIIIB in plasma compared to FXIIIA subunit, thereby resulting in a significant amount of free the FXIIIB subunit. Plasma FXIIIA is now understood to be contributed to by cells of myeloid lineage derived from the bone marrow, although it is expressed in several other cell types such as monocytes, monocyte-derived macrophages, and platelets. The FXIIIB subunit is expressed in hepatocytes [3]. The zymogenic FXIII circulates in plasma bound to fibrinogen (Kd 10 nM) [4]. Other than covalently crosslinking fibrin molecules to itself, FXIII crosslinks other fibrin stabilizers such as (α 2-PI, PAI, TAFI, etc.) to the growing fibrin clot as well [5,6]. The deficiency of FXIII, inherited or acquired, is known to cause bleeding predispositions, where congenital FXIII deficiency is due to defects either of the F13A1 (at genetic locus 6p24-25) or F13B genes (at genetic locus 1q32-32.1). The global prevalence of inherited FXIII deficiency is low (1–4 cases per million), which brings it under the category of rare bleeding disorders. Most defects associated with severe bleeding symptoms in inherited FXIII deficiency are largely due to defects in the F13A1 gene, whereas gene defects in the F13B gene have been shown to be causing mild to moderate symptoms [7]. More than 100 distinct FXIII mutations from F13A1 and F13B genes have been identified in patients with a broad spectrum of pathological phenotype severity that includes post-operative prolonged bleeding, delayed re-bleeding, and spontaneous abortion during the first trimester of pregnancy due to placental dysfunction. Over 500 cases of severe FXIII deficiency have been reported worldwide. In the past decade, clinical data have shown that although inherited FXIII deficiency is autosomal recessively inherited, the carriers or the heterozygous state of some of these FXIII gene defects can also bleed unusually when exposed to physical trauma [8]. Apart from its role in coagulation, several other roles outside coagulation have been discovered for the catalytic FXIIIA subunit. These roles encompass wound healing, chronic inflammatory bowel diseases, atherosclerosis, rheumatoid arthritis, chronic inflammatory lung diseases, chronic rhinosinusitis, solid tumors, hematological malignancies, and obesity [9]. Our group has previously reported on the novel potential binding partners of FXIIIB subunit based on co-immunoprecipitation studies i.e., α2-MG and complement factor C1q [10]. However, we could not find the direct roles of FXIIIB in complement activation in spite of its strong sequence homology and expected structural similarity to the complement factor H protein [10,11]. The FXIIIA subunit is expressed in a wide range of cells, including platelets, megakaryocytes, monocytes, and monocyte-derived cells, while the primary source of the FXIIIB subunit is hepatocytes [3,12]. Recent reports on FXIIIA expression and secretion exclude platelets and all their precursors as a major source of plasma FXIIIA. Although intracellularly the level of expression, activation, and secretion of FXIIIA is independent of its plasma partner FXIIIB subunits, it has been reported in several cases that the defect/reduction in one subunit often is accompanied by a reduction in levels for the other subunit as well. While this effect is anticipated for F13B mutations, because the FXIIIB subunit is the protective partner in the heterotetrameric complex, it is a little bit harder to explain the same observation for defects in the F13A1 gene. This compels one to investigate if there is any co-regulatory mechanism shared by the two subunits that are expressed in different lineages yet define the final available dosage of potentially active FXIII transglutaminase in plasma. Previously, it has been reported that the pro-inflammatory M1 macrophages show lower to no expression of F13A1, compared to anti-inflammatory M2 macrophages [13]. In this context, F13A1 has also been reported to be associated with carcinomas lately [14]. In several reports published earlier, based on the RNA-seq data, groups have reported a correlation of F13A1 in diabetes-prone mice, osteoarthritis, and cancer, as one of the significant hits affected by altered cytokine signaling in these pathological states, indicating its role in these inflammatory states. A study performed in 2005 reported F13A1 differential gene expression during macrophage polarization by RT-PCR and single-cell analyses [15]. The revelation that FXIIIA protein could be used as an intracellular marker for alternatively activated macrophages (the fully polarized classically (type I) and alternatively (type II) activated macrophages) compels one to look deeper at whether F13A1 has any direct role in macrophage maturation and polarization. The current availability of abundant data being submitted in expression databases such as gene expression omnibus (GEO) provides the opportunity to bioinformaticians to investigate trends and patterns within these datasets, which in turn provide us with valuable insights into several functional and physiological mechanisms. Advanced bioinformatics tools and increased computational power have made it possible for us to understand the dynamic behavior of these biological data sets. To understand the roles and involvement of FXIII subunits in dynamic biological processes intra and extracellularly considering the overall gene expression as read-outs, such as hepatocyte maturation, the development of atherosclerotic plaque, and macrophage polarization, we have utilized the publicly available RNA-microarray data sampled at different time points to understand and capture expression-switching with respect to time, and the behavior of transcriptome. Since the cells of bone-marrow and mesenchymal lineage have so far been reported to be responsible for stable F13A1 expression, we have investigated the micro-array data derived from macrophages, which are also major players in immunity. Similarly, microarray data derived from hepatocytes is investigated for F13B expression behavior. Recent reports on reduction in plasma levels of FXIIIA, upon acquired deficiency of FXIIIB subunit, also motivates one to investigate the pathways responsible for the common regulation of the two subunits [16]. This study, however, explains that such an acquired response does not affect the FXIIIA pool within the platelets. Interesting reports on platelet FXIIIA characterization also suggest that platelet FXIIIA is not responsible for the maintenance of the plasma pool of FXIII. After the identification of differentially expressed genes (DEGs) correlating with F13A and F13B expression levels in respective datasets, a common regulatory pathway is traced by characterizing the promoters and transcriptional regulators at each time point and cell type. To address the mode of FXIII expression regulation, for both of its subunits here we attempted to adopt a pure bioinformatics approach to analyze the temporal, time-specific expression array data corresponding to both the subunits in specific cell lineages with respect to the gene promoters. Differentially expressed genes with respect to the expression of the FXIII subunit genes in different cell lineages were predicted for their potential roles in cellular pathways. 2. Materials and Methods 2.1. Data Extraction Expression data were extracted from NCBI GEO (GSE128303, GSE98324, GSE39157, and GSE41571) for macrophages (time-series), hepatic progenitor, hepatocytes, and human-embryonic-stem-cells-derived hepatoblasts, respectively, [13,17,18,19,20,21]. GSE128303 and GSE98324 were available for illumina human ht12-v4 expression beadchip arrays, whereas GSE39157 and GSE41571 were analyzed using Affymetrix Human Gene 1.0 ST arrays (HuGene-1_0-st) and Affymetrix Human Genome U133 Plus 2.0 Array (HG-U133_Plus_2). As a summary, we put together the following purified human-derived expression data sets: GSE128303: In the original study corresponding to this dataset, primary human monocyte-derived macrophages isolated from four donors were matured in the presence of recombinant human IL-4, followed by LPS treatment (Salmonella enterica, 200 ng/mL) for 90 min [17]. LPS-treated samples were diluted to a final concentration of 100 ng/mL LPS for the time following the initial 90-min incubation. Samples were collected at 6 h and 24 h post-initiation of infection for a total of 12 treatments in biological quadruplicate for 48 total samples. In this present analysis, out of the 12 treatments performed by Miller et al. resulting in 48 samples, we filtered 8 samples (LPS treated) derived from 4 donors, one for each time point (6 h and 24 h). Platform: Illumina HumanHT-12 V4.0 expression beadchip. GSE98324: In the original study corresponding to this dataset, research groups at the National University of Singapore collected array data from 32 distinct human-derived samples [18]. From this comprehensive data set, we have used the array data for four samples attributed to hESCs (Human ESC-derived Hepatic Progenitor Under Base Condition). Platform: Illumina HumanHT-12 V4.0 expression beadchip. GSE39157: In the original study corresponding to this dataset, array data derived from total RNA were obtained from cultured primary hepatocytes and hESC-derived hepatic populations [19]. In the present study, we have used the primary hepatocyte and hESC-derived untreated hepatoblast culture, derived expression array data. Platform: (HuGene-1_0-st) Affymetrix Human Gene 1.0 ST Array (transcript (gene) version). GSE41571: In the original study corresponding to this dataset, expression data derived from genome-wide expression analyses of isolated macrophage-rich regions of stable and ruptured human atherosclerotic plaques were reported [20,21]. Platform: (HG-U133_Plus_2) Affymetrix Human Genome U133 Plus 2.0 Array. 2.2. Data Processing Illumina Human HT12-v4 Expression BeadChip: Raw data from GEO was downloaded as “idat” files for illumina human ht12-v4 platform. IDAT files were imported into R using “read.idat” function in “Iimma” package [22]. Data were background-corrected and quantile-normalized using “neqc” function in “limma” package. Finally, data were filtered for probes not detected in any cell type by using “detectionPvalues” method; this method identified the observed expression values of probes in comparison to the negative control probes and provides us with the p-values for probe expression. Data were also tested for batch effects using “ComBat” function in “sva” package, but no batch effect was removed as the data has a non-significant batch effect [23]. Affymetrix Arrays: The normalized series matrix file was downloaded from the NCBI GEO database for both Affymetrix array data, and this file was filtered for the detection p-value, where the probe signal was found to be statistically significant against background signal. Probes with non-significant probe signals were removed, and significant probes were further analyzed using the Qlucore Omics Explorer 3.5 (www.qlucore.com (accessed on 6 Jun 2020)) (Qlucore AB, Lund, Sweden). Data Import: All expression arrays data were imported separately into Qlucore Omics Explorer 3.5 (www.qlucore.com (accessed on 6 Jun 2020)) using import wizard with sample annotation, as well as probes annotation for individual array platforms. 2.3. Differential Gene Expression Analysis Differentially expressed genes (DEG) were identified using Qlucore Omics Explorer 3.5 (www.qlucore.com (accessed on 6 Jun 2020)). A Student t-test was used to compare two samples, whereas an ANOVA was used for multiple-sample comparison. Significance values of p < 0.05 or 5% of the false discovery rate were used as statistically significant. Fold changes were also calculated for volcano plots. Gene Ontology and Pathway Analysis: Gene ontology analyses were carried out using Cytoscape 3.7.1 [24]. Biological processes were identified using “Bingo” plugin in Cytoscape [25]. Visualizations of significant ontologies were carried out using the “EnrichmentMap” plugin in Cytoscape [26]. Tox functions were identified using ingenuity pathway analysis (IPA) (QIAGEN Inc., Cambridge, MA, USA, https://www.qiagen-bioinformatics.com/products/ingenuity-pathway-analysis (accessed on 6 Jun 2020)) [27]. Promoter Sequence: The F13A1 and F13B promoter sequences were downloaded from the eukaryotic promoter database (EPD, www.epd.epfl.ch (accessed on 6 Jun 2020)) [28,29]. The promoter sequence of 1 kb upstream and 1 kb downstream from the transcription start site was downloaded from EPD, and a 2 kb long sequence was downloaded as a “fasta” file for further transcription factor analysis. Transcription factors analysis: The transcription factors binding to the promoter of F13A1 and F13B downloaded from EPD were identified using the TRANSFAC professional database from geneXplain [30,31,32]. Transcription factor binding sites were identified as transcription factor matrices (TF-matrices; each transcription factor matrix is comprised of multiple transcription factors with same binding sites; similarly, one transcription factor could bind to multiple binding sites. All TRANSFAC analyses were carried out using the data version of 2019.3 with the selected profile of matrices with a minimum sum of false positive and false negative, and only high-quality matrices were used for the analyses [32]. Further analyses of transcription factors matrices were carried out using R. 2.4. Visualization and Plots Principal component analysis and heatmaps were generated using Qlucore Omics Explorer 3.5 (www.qlucore.com (accessed on 6 Jun 2020)). Volcano plots and correlation plots were generated using R programming. Box plots were generated using the GraphPad Prism 8. Pathways, gene networks, and tox functions plots were created using Ingenuity Pathway Analysis. Gene ontology plots were generated using Cytoscape 3.6. Transcription factors binding consensus sequences were downloaded from TRANSFAC. 3. Results 3.1. Genes Correlated with F13A1 and F13B Have Specific Biological Processes as well as a Common Function of Immune Response The F13A1 and F13B genes were observed to be expressed in macrophages and liver cells, respectively. Reversibly, no expression for the F13A1 and F13B genes was observed in macrophages and liver cells, respectively. The FXIIIA subunit expression reduces significantly with the maturation of macrophages. Macrophages at 6 h (monocyte-derived macrophages) showed high levels of the F13A1 transcript, which after 24 h goes down to ≈50% of its original expression (Figure 1A). Overall, macrophages showed 143 probes (114 probes upregulated at 6 h, 29 probes upregulated in 24 h) to be differentially expressed across 6 h and 24 h time-points at p ≤ 0.05, with a mean difference greater than 1. Additionally, 170 probes (positive correlated = 138 probes, negative correlated = 32 probes) were found to be significantly correlated with F13A1 expression in macrophages at correlation > 0.5 and with a mean difference greater than 1 (Figure 1B). The top hits reveal genes such as SERPINB2, CCL17, CCL2, CCL13, and SLC39A8 having a strong positive correlation to F13A1 expression (>0.5 Pearson’s correlation) (Figure 1C). The gene ontology analysis of negatively correlated genes showed no significant biological process, whereas positively correlated genes showed strong enrichment of response-based terms (i.e., immune response, stress response, response to wounding, etc.) (a detailed ontology list is shown in Figure 1D), sterol process biosynthetic, and endocytosis. F13B expression is not significantly different between liver progenitor and hepatocytes, but mildly high expression was observed in adult hepatocytes. No F13B transcript was observed in macrophages (i.e., above detection level) (Figure 2A). Liver progenitor and hepatocytes are very different cell types since liver progenitor cells differentiate into diverse cell types whereas hepatocytes are liver-specific cells. Differential gene expression analysis between hepatocytes and liver progenitor cells showed a high number of differentially expressed genes (14494 probes at p < 0.05 and mean difference greater than 1) (Figure 2B). Meanwhile, FXIIIB expression was showing non-significant expression difference between hepatocytes and liver progenitor; hence, only 245 probes (positive correlated = 165 probes, negative correlated = 80) were found to be significantly correlated (correlation > 0.5) with FXIIIB expression and have a mean difference above 1 between liver progenitor and hepatocytes (Figure 2C). The gene ontology analysis of correlated genes with F13B showed enrichment in terms of the immune response and wound healing-related biological processes (Figure 2D). The basal level of expression of F13B (in hepatocytes) as compared to F13A1 (in macrophages) was ≈four times higher. This might explain the higher levels of the FXIIIB2 subunit in plasma compared to the FXIIIA2 subunit (≈2 times), owing to which there is a significant amount of free unbound FXIIIB2 subunit in the plasma. 3.1.1. Genes for Both the FXIII Subunits Have a Common Inhibitor/Suppressor Transcription Factor Binding Site On analyses of the extended 2 kb long promoter for both F13A1 and F13B genes, the transcription factors (TFs) binding to these extended promoters using TRANSFAC professionals, were identified. TRANSFAC predicted 100 and 96 TF-Matrices binding to 636 and 542 binding sites on F13A1 and F13B promoters, respectively (see Supplementary Figure S1 and Supplementary Table S1). These matrices correspond to 465 and 421 probes in the expression data of macrophages and liver cells, respectively. Differential gene expression analysis of these transcription factors gave us 68 probes when macrophages at the 6 h time point were compared with macrophages at the 24 h time point. A comparison between liver progenitor and hepatocytes gave 202 probes of differentially expressed transcription factors (see Supplementary). Further, the correlation between the differentially expressed transcription factors of F13A1 and F13B was calculated. It was found that the V$EBOX_Q6_01 transcription factor matrix was found both positively and negatively correlated with F13A1 expression. In the given matrix “MXD1, SERBF2, and MITF” were found to be highly positively correlated with F13A1 expression, whereas “TCF12, MAX, HES2, MNT, MXI1, and MYCN” were found to be highly negatively correlated (Figure 3A). Similarly, V$EBOX_Q6_01 also showed a statistically significant correlation with F13B, where “HES6” was found to be highly negatively correlated with F13B. The transcription factor binding elements “MXD1 and HES6” were found to be negatively correlated (with F13B) with a Pearson’s correlation below 0.75 and p-value < 0.01 (Figure 3B). A positive correlation was observed for V$RFX_01 binding sites, where the “RFX5” transcription factor was found to be highly positively correlated with F13B expression (Figure 3B). A closer comparison of these transcription factor binding elements revealed 375 TFs common to both F13A1 and F13B genes (Figure 4A). A similar expression pattern was observed for 196 TFs (115 upregulated, and 85 downregulated) out of 375 common TFs in time series macrophages, as well as liver progenitor vs. hepatocytes, whereas the opposite pattern was observed for the remaining common 179 TFs (86 upregulated in time series macrophages, and 93 upregulated in hepatocytes vs. liver progenitor), which were predicted to bind to both F13A1 and F13B yet show a reverse pattern of expression. An assessment of canonical pathways associated with all these ‘commonly regulating’ transcription factors revealed that the TFs correlated with F13 genes expression in the given cells are majorly responsible for cellular maturation, pluripotency, and development (Figure 4B). 3.1.2. Common TFs Binding to Both Subunits Are Related to Cardiac Anomaly We have found that 80 transcription factor matrices were found to bind both F13A1 and F13B. These 80 transcription factor matrices corresponded to 375 transcription factors. Tox functions from the ingenuity pathway analysis (IPA) of these 375 transcription factors showed enrichment in congenital heart anomaly, cardiac proliferation, cardiac enlargement, liver necrosis, and liver proliferation. This tox function shows that transcription factors binding to both F13A1 and F13B play a significant role in pathological conditions such as cardiac anomaly (Figure 4C). 3.1.3. F13A1 Expression Profiles Reveal Its Participation in Macrophage Polarization Relative gene expression of F13A1 was significantly higher in M0 and M2 macrophages when compared to M1 (Figure 5A). A correlation gives us a measure of variability between two features with respect to the target variable, here being F13A expression. We found 4669 genes correlated to F13A1 expression during the M0-M1 switch, whereas we found 4817 genes in the case of M1-M2 switching (Figure 5C). The upstream regulator analysis of F13A1 and its correlated genes in both cases resulted in the prediction of common regulators (activation z scores >2 is considered significant). In the case of the M0-M1 switch, MAFB (z-score 3.945) and IL10RA (z-score 4.666) regulators are predicted to be inhibited in the genes that are correlated to F13A1 expression, whereas in the case of the M1-M2 switch, IL1B (z-score 4.249) and TFRG (z-score 3.097) are the predicted regulators to be activated, and TGFB1 (z-score 3.902), IL10RA z-score 4.972), IL-13 (z-score 4.446), and IL-4 (z-score 4.078) are the regulators predicted to be inactivated in the genes correlated to F13A1 expression (Figure 5D). 3.1.4. Stabilized Levels of F13A1 in Resident Macrophages Isolated from Ruptured and Stable Human Atheromatous Lesions No differential expression for F13A1 was observed among the array data of resident microphages isolated from ruptured and stable human atheromatous lesions, most likely because all profiles were characteristic of activated macrophages, as also indicated by hierarchical clustering of the data set (Figure 6A,B). We found 1249 genes correlated to F13A1 gene expression between the ruptured thin fibrous cap arthromere and stable plaques, whereas 4425 genes correlated to F13A1 expression as in stable calcific plaque and Stable Thick Fibrous Cap Atheroma (Figure 6C). The upstream regulator analyses of the correlated genes predicted 1L1B (z-score 2.284) as the major regulator (activation z scores > 2 is considered significant) for these correlated genes for ruptured thin fibrous cap arthromere and stable calcific plaques, whereas, in case of progression from stable calcific plaques to Stable Thick Fibrous Cap Atheroma, IL4 (z-score 4.052), IL1B (z-score 4.272), IL13 (z-score 3.527), GATA2 (z-score 2.299), CTNNB1 (z-score 3.911), and MAF8 (z-score 3.327) were found to be significantly regulating the genes correlating to the F13A1 expression pattern (Figure 6D). 4. Discussion The NCBI-GEO (gene expression and molecular abundance repository) serves as one of the largest publicly available repositories for raw as well as curated array-based expression data, deposited by the scientific fraternity for further analyses, interpretation, and validation. Such large datasets enable and promote meta-analyses where raw data generated and deposited from one working group can be accessed, analyzed, and validated using several other bioinformatics tools to derive a better understanding of biological data. In the present study, we have utilized the GSE data records for different array-data analyzed here, which defines sets of samples and how they are related (here, for example, macrophages (M1, M2, and M0), liver cells (hepatocytes and liver progenitor cells), and plaque-derived resident macrophages (from stable and ruptured plaques)). This work is an attempt to translate bioinformatics data into meaningful interpretive FXIII research that could direct future investigations into the cellular expression profile of FXIII. The multitude of data sets described in the methods section is referred to and extracted for this present overview of FXIII subunit roles and its respective subunit expression, promoter specifications, and inter-related mode of regulation. We have tried to include the expression data from all stages of respective subunit-expressing cells (macrophages and hepatocytes, for F13A1 and F13B, respectively). FXIIIA has been long been understood to be a key molecule in the inflammation-coagulation-complement axis. The bench data from several meta-analyses suggest that F13A1 expression is strongly correlated to inflammation-like cellular responses; the temporal array data analyzed for cell-specific expression also reveal that the genes correlated with the F13A1 and F13B differential expression pattern are largely involved in a common function of the immune response. The presented data here reveal that F13A1 expression levels in macrophages are strongly positively correlated to genes responsible for cell differentiation and migration, largely in an immune setup (CCL17, CCL2, and CCL13); genes responsible for indirect clot stabilization (SERPINB2); and intracellular transporters such as SLC39A8 (Figure 1). These genes have earlier also been reported to act in synergy and to be involved in the coagulation-complement axis, e.g., in an earlier report, F13A1 has been shown to be correlated with SERPINB2, MAF, IGF1, MAFB, and IL10, although the primary take-home message for this regarded the effect of Activin A on macrophage polarization, as a result of M-CSF based activation [33]. The observation that reduced plasma levels of the FXIIIB domain secondarily reduces the plasma levels of the available active FXIIIA domain is also translated into the curated array data here, where we see the basal expression of F13B genes almost four-times higher than that of F13A1 (Figure 3 and Figure 4). The strong dependency of the two subunit plasma titers, which result in secondary deficiency of FXIIIB in the absence of FXIIIA in plasma and vice versa, draws attention towards the possible common regulation of the two subunits [34,35]. We observe that the FXIII subunit genes have a common inhibitor/suppressor predicted transcription factor binding site supporting the possibility of inter-regulation at the transcript level (Figure 4). This means that the defective activation of transcription in one partner gene might lead to no activation of transcription in the other partner. More experimental validation data in this context are needed to build upon this prediction. We further find that the Common TFs binding to both subunits are related to cardiac anomaly. The association of transcriptional regulation of the F13A1 gene with cardiac anomaly does not come as a surprise for us since FXIII has often been related to defects in the cardiovascular system [36]. High levels of intracellular FXIIIA (in monocyte-derived macrophages) are reported to perform functions related to cellular remodeling, crosslinking of the cytoskeleton, microtubule assembly, etc. (given that FXIIIA has several substrates within the cell) [37]. However, similar high levels of intracellular FXIIIA (as in monocyte-derived macrophages) are not detected in phagocytic or secretory vesicles, indicating that FXIIIA might play a direct role in cell-fate determination (M1 or M2), possibly by altering the cellular substructure [15]. More recently, work published by Alshehri et al. proposed that although monocytes do not contribute to plasma FXIIIA, in the case of VTE, entrapped monocytes expose FXIIIA on their surfaces to the fibrin clot surface [12]. The study reveals differential expression of F13A1 in the presence of pro-inflammatory and anti-inflammatory cytokine-based stimulation of monocytes. On profiling the array data from M1 and M2 macrophages, strong expression of F13A1 in M2 was observed; the time-based array indicates that FXIII-A most likely contributes to macrophage polarization (Figure 5). As discussed by Alshehri et al., the monocytes entrapped in thrombus largely have an M2 phenotype, and the fact they expose FXIII is not surprising as it has established roles in wound-healing. The presence of highly correlated genes (linear regression p < 0.05) with FXIII in macrophage polarization towards M2-switch supports this notion (See Supplementary Table S1). Additionally, the upstream regulator analyses predicted (by identifying F13A1 co-expressed genes) that upstream regulators such as growth factors, transcription factors, and interleukins are targeting both F13A1- and F13A1-correlated genes, which may suggest an association between F13A1 and macrophage polarization, i.e., macrophage polarization towards an M2 phenotype and increased expression of F13A1 occur in a temporal manner and are not mutually independent events (Figure 5). There is coexistence of a common upstream regulator covey for F13A1 and its correlated genes during M0/M1 and M1/M2 switch that conjoins these two events as a cause-and-effect (Figure 5). Mice-based knock-out studies using the Cre/lox system indicated that the plasma FXIIIA pool is derived primarily from aortic resident macrophages and not from platelets [14]. The study suggests that not the monocyte-derived macrophages but resident macrophages are responsible for keeping up the plasma pool of FXIIIA, the primary aortic resident macrophages [14]. While we did not find time-point-based resident macrophage data to define the primary transcription factors that contribute to the eventual plasma FXIII levels, we were able to assess the resident macrophages, plaque-derived array data to be analyzed from another perspective. Our analysis from these resident macrophages reveals that the F13A1 gene acts as a coadjutant in plaque fate, rather than being detrimental towards its progression. The bioinformatics data reveal and support the existence of a strong role of FXIIIA in inflammation, cellular remodeling, and remodeling of atheroma as well. The lack of any significant differential expression in the three stages analyzed here strongly indicates that FXIIIA is directly involved in plaque stability; it plays no role in plaque formation, progression, rupture, and/or healing but in plaque maintenance (Figure 6, also see Supplementary Table S1). The significantly upregulated upstream regulatory element for F13A1 and its correlated genes is predicted to be “MafB” (z-score 3.945) (Figure 6), which is found to be quintessential for plaque growth by other groups by gene knock out studies [38]. However, the analyzed data set defines that the resident macrophages isolated from the plaque samples are activated. Recent data reported by Verma et al. reveal that F13A1 overexpression is seen only in the advanced stages of atherosclerotic plaques, and it is likely to be upregulated as a result of cytokine-storm in advanced stages of atherosclerotic plaque [39]. Secondly, our data only take into consideration the resident macrophages derived from plaque. As a summary and conclusion, analyses and profiling of time-series-based micro-array expression data derived from different cell types expressing (and secreting) FXIIIA and FXIIIB subunit predict the inter-regulation of expression for both the genes. FXIIIA has roles beyond coagulation and is very likely to be involved in pro-inflammatory M2 phenotype switching of monocyte-derived macrophages. Owing to its role as a stabilizer, FXIIIA is likely to be indispensable for plaque maintenance at advanced stages of atherosclerotic plaque; however, is not needed for plaque initiation. Future studies are warranted for establishing effective, direct, and exclusive roles of FXIIIA molecule towards (a) macrophage polarization, (b) regulation of F13B gene expression, and (c) progression of early-stage plaque to advanced stages, in thrombus models. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094725/s1. Click here for additional data file. Author Contributions Conceptualization: A.B.; methodology: M.A.J.; software: M.A.J.; validation: M.A.J., S.S. and A.B.; formal analysis: M.A.J. and S.S.; investigation: M.A.J. and S.S.; resources: A.B.; data curation: M.A.J., A.B. and S.S.; writing—original draft preparation: M.A.J. and S.S.; writing—review and editing: S.S., M.A.J., O.E.-M., J.O. and A.B.; visualization, M.A.J., A.B. and S.S.; supervision, A.B. and J.O.; project administration: A.B. and J.O.; and funding acquisition, S.S., O.E.-M., A.B. and J.O. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The output files of evaluations done for this work are available from the authors upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 An expression analysis of time-series macrophages (LPS treated) at 6 h and 24 h. (A) A box plot of F13A1 expression in macrophages at 6 h and macrophages at 24 h, as well as liver progenitor cells and hepatocytes. (B) A volcano plot of differentially expressed genes between 6 h and 24 h macrophages (red: significant p-value < 0.05 and absolute mean difference above 1; green: absolute mean difference above 1 and p-value > 0.05; and blue: significant p-value < 0.05 at absolute mean difference < 1) in dataset GSE128303. (C) Left: Bland–Altman plot between the correlation of F13A1 expression with other genes and the mean difference expression of genes between macrophages 6 h and 24 h; red = significantly positively correlated genes at Pearson’s correlation > 0.5 and absolute mean difference between 6 h and 24 h > 1; and green = significantly negatively correlated genes at Pearson’s correlation < −0.5 and absolute mean difference between 6 h and 24 h > 1. Right: top 6 markers from the Bland–Altmann plot between 6 h and 24 h. (D) Gene ontology (GO) analysis of significant genes from the Bland–Altman plot in part C-Left. Figure 2 An expression analysis of F13B in liver progenitor cells and hepatocytes. (A) A box plot of F13B expression in liver progenitor cells, hepatocytes, and macrophages. (B) A volcano plot of differentially expressed genes between liver progenitor cells and hepatocytes at red: significant p-value < 0.05 and absolute mean difference between liver progenitor and hepatocytes above 1; green: the absolute mean difference between liver progenitor and hepatocytes above 1 but p-value > 0.05; and blue: statistical p-value < 0.05, but the absolute mean difference between liver progenitor and hepatocytes < 1. (C) The Bland–Altman plot between the correlation of F13B expression with other gene expressions and the mean expression difference of the genes between liver progenitor cells and hepatocytes; red: significantly positively correlated genes at Pearson’s-Correlation > 0.5 and the absolute mean difference between liver progenitor and hepatocytes > 1; green: significantly negatively correlated genes at Pearson’s Correlation < −0.5 and the absolute mean difference between liver progenitor and hepatocytes > 1. (D) A gene ontology analysis of significant genes from the Bland–Altman plot in part (C). Figure 3 The transcription factor analysis of F13A1 and F13B using TRANSFAC. (A) An illustration of the predicted transcription factor binding to the F13A1 promoter; pink: the positively correlated expression of transcription factor with F13A1 expression; green: the negatively correlated expression of transcription factor with F13A1 expression. Blue: the density of the transcription factor at a particular position on the gene-promoter. A heatmap of transcription factors binding to a specific binding site represented as a transcription factor matrix. (B) An illustration of predicted transcription factor binding to the F13B promoter; pink: the positively correlated expression of the transcription factor with F13B expression; green: the negatively correlated expression of the transcription factor with F13B expression. Blue: the density of the transcription factor at a particular position. The above heatmap of the correlation between transcription factors and F13B expression; the below heatmap of transcription factors binding to a specific binding site represented as a transcription factor matrix. Figure 4 The common transcription regulation of F13A1 and F13B. (A) Left: the Venn Diagram of the positive and negative correlation of TFs binding to F13A1 and F13B, in macrophages 6 h vs. 24 h and liver progenitors cells vs. hepatocytes respectively. Right: the transcription factors expression difference in macrophage 6 h vs. 24 h and liver progenitor vs. hepatocytes for common transcription factors binding to both F13A1 and F13B. (B) The top 10 canonical pathways of common transcription factors binding to both F13A1 and F13B; red: the overlap transcription factor from our analysis; and grey: the total number of molecules in the pathway. (C) Left: the heatmap of all tox functions enriched with common transcription factors binding to both F13A1 and F13B; right: the Top 10 Tox functions of the common transcription factor binding to both F13A1 and F13B. Figure 5 An expression analysis of macrophage polarization. (A) F13A1 expression in macrophage polarization. (B) The 3D-PCA of macrophage polarization with Euclidean distance (ED) between every macrophage polarization. Blue: M0; yellow: M1; and dark pink: M2. (C) A heatmap and 3D-PCA of significant F13A1-expression-correlated genes at p < 0.05; left: significantly correlated genes with F13A1 expression in M0 to M1; right: significantly correlated genes with F13A1 expression in M1 to M2. (D) Significant upstream regulators of F13A1-expression-correlated genes in left: M0 to M1; right: M1 to M2; orange: predicted overexpressed; blue: predicted under expressed; red: overexpressed; and green: under expressed in M0 compared to M1 or M1 compared to M2. Figure 6 The expression analysis of plaque stability. (A) F13A1 expression in plaque stability. (B) 3D-PCA of plaque-stability-derived data points. Blue: Ruptured Thin Fibrous Cap Atheroma; yellow: Stable Thick Fibrous Cap Atheroma; and dark pink: Stable Fibrocalcific Plaque. (C) 3D-PCA of significant F13A1-expression-correlated genes at p < 0.05; left: significantly correlated genes with F13A1 expression in Ruptured Thin Fibrous Cap Atheroma to Stable Fibrocalcific Plaque; and right: significantly correlated genes with F13A1 expression in Stable Fibrocalcific Plaque to Stable Thick Fibrous Cap Atheroma. (D) Significant upstream regulators of F13A1-expression-correlated genes in left: Ruptured Thin Fibrous Cap Atheroma to Stable Fibrocalcific Plaque; right: Stable Fibrocalcific Plaque to Stable Thick Fibrous Cap Atheroma; orange: predicted overexpressed; blue: predicted under-expressed; red: overexpressed; and green: under-expressed in Ruptured Thin Fibrous Cap Atheroma compared to Stable Fibrocalcific Plaque or Stable Fibrocalcific Plaque compared to Stable Thick Fibrous Cap Atheroma. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Singh S. Nazabal A. Kaniyappan S. Pellequer J.-L. Wolberg A.S. Imhof D. Oldenburg J. Biswas A. The Plasma Factor XIII Heterotetrameric Complex Structure: Unexpected Unequal Pairing within a Symmetric Complex Biomolecules 2019 9 765 10.3390/biom9120765 2. Singh S. Dodt J. Volkers P. Hethershaw E. Philippou H. Ivaskevicius V. Imhof D. Oldenburg J. Biswas A. Structure functional insights into calcium binding during the activation of coagulation factor XIII A Sci. Rep. 2019 9 11324 10.1038/s41598-019-47815-z 31383913 3. Kaetsu H. Hashiguchi T. Foster D. Ichinose K. Expression and Release of the a and b Subunits for Human Coagulation Factor XIII in Baby Hamster Kidney (BHK) Cells J. Biochem. 1996 119 961 969 10.1093/oxfordjournals.jbchem.a021336 8797098 4. Greenberg C. Miraglia C. Rickles F. Shuman M. Cleavage of blood coagulation factor XIII and fibrinogen by thrombin during in vitro clotting J. Clin. Investig. 1985 75 1463 1470 10.1172/JCI111849 2860124 5. Folk J.E. Finlayson J.S. The epsilon-(gamma-glutamyl)lysine crosslink and the catalytic role of transglutaminases Adv. Protein Chem. 1977 31 1 133 10.1016/s0065-3233(08)60217-x 73346 6. Adány R. Bárdos H. Factor XIII subunit A as an intracellular transglutaminase Cell. Mol. Life Sci. 2003 60 1049 1060 10.1007/s00018-003-2178-9 12861374 7. Karimi M. Bereczky Z. Cohan N. Muszbek L. Factor XIII Deficiency Semin. Thromb. Hemost. 2009 35 426 438 10.1055/s-0029-1225765 19598071 8. Biswas A. Ivaskevicius V. Thomas A. Oldenburg J. Coagulation factor XIII deficiency. Diagnosis, prevalence and management of inherited and acquired forms Hamostaseologie 2014 34 160 166 10.5482/HAMO-13-08-0046 24503678 9. Dull K. Fazekas F. Törőcsik D. Factor XIII-A in Diseases: Role Beyond Blood Coagulation Int. J. Mol. Sci. 2021 22 1459 10.3390/ijms22031459 33535700 10. Singh S. Akhter M.S. Dodt J. Volkers P. Reuter A. Reinhart C. Krettler C. Oldenburg J. Biswas A. Identification of Potential Novel Interacting Partners for Coagulation Factor XIII B (FXIII-B) Subunit, a Protein Associated with a Rare Bleeding Disorder Int. J. Mol. Sci. 2019 20 2682 10.3390/ijms20112682 11. Akhter M.S. Singh S. Yadegari H. Ivaskevicius V. Oldenburg J. Biswas A. Exploring the structural similarity yet functional distinction between coagulation factor XIII-B and complement factor H sushi domains J. Thromb. Thrombolysis 2019 48 95 102 10.1007/s11239-019-01841-w 30915671 12. Alshehri F.S.M. Whyte C.S. Mutch N.J. Factor XIII-A: An Indispensable “Factor” in Haemostasis and Wound Healing Int. J. Mol. Sci. 2021 22 3055 10.3390/ijms22063055 33802692 13. Martinez F.O. Gordon S. Locati M. Mantovani A. Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: New molecules and patterns of gene expression J. Immunol. 2006 177 7303 7311 10.4049/jimmunol.177.10.7303 17082649 14. Beckers C.M.L. Simpson K.R. Griffin K.J. Brown J.M. Cheah L.T. Smith K.A. Vacher J. Cordell P.A. Kearney M.T. Grant P.J. Cre/lox Studies Identify Resident Macrophages as the Major Source of Circulating Coagulation Factor XIII-A Arterioscler. Thromb. Vasc. Biol. 2017 37 1494 1502 10.1161/ATVBAHA.117.309271 28596376 15. Töröcsik D. Bárdos H. Nagy L. Adány R. Identification of factor XIII-A as a marker of alternative macrophage activation Cell. Mol. Life Sci. 2005 62 2132 2139 10.1007/s00018-005-5242-9 16132226 16. Porrello A. Leslie P.L. Harrison E.B. Gorentla B.K. Kattula S. Ghosh S.K. Azam S.H. Holtzhausen A. Chao Y.L. Hayward M.C. Factor XIIIA-expressing inflammatory monocytes promote lung squamous cancer through fibrin cross-linking Nat. Commun. 2018 9 1988 10.1038/s41467-018-04355-w 29777108 17. Strilchuk A.W. Meixner S.C. Leung J. Safikhan N.S. Kulkarni J.A. Russell H.M. van der Meel R. Sutherland M.R. Owens A.P. Palumbo J.S. Sustained depletion of FXIII-A by inducing acquired FXIII-B deficiency Blood 2020 136 2946 2954 10.1182/blood.2020004976 32678423 18. Ang L.T. Tan A.K.Y. Autio M.I. Goh S.H. Choo S.H. Lee K.L. Tan J. Pan B. Lee J.J.H. Lum J.J. A Roadmap for Human Liver Differentiation from Pluripotent Stem Cells Cell Rep. 2018 22 2190 2205 10.1016/j.celrep.2018.01.087 29466743 19. El-Maarri O. Jamil M.A. Oldenburg J. Molecular Profiling of Liver Sinusoidal Endothelial Cells in Comparison to Hepatocytes: Reflection on Which Cell Type Should Be the Target for Gene Therapy Hamostaseologie 2020 40 S26 S31 10.1055/a-1282-2286 33187005 20. Miller J.L. Hill M.L. Brun J. Pountain A. Sayce A.C. Zitzmann N. Iminosugars counteract the downregulation of the interferon γ receptor by dengue virus Antivir. Res. 2019 170 104551 10.1016/j.antiviral.2019.104551 31306674 21. Lee K. Santibanez-Koref M. Polvikoski T. Birchall D. Mendelow A.D. Keavney B. Increased expression of fatty acid binding protein 4 and leptin in resident macrophages characterises atherosclerotic plaque rupture Atherosclerosis 2013 226 74 81 10.1016/j.atherosclerosis.2012.09.037 23122912 22. Ogawa S. Surapisitchat J. Virtanen C. Ogawa M. Niapour M. Sugamori K.S. Wang S. Tamblyn L. Guillemette C. Hoffmann E. Three-dimensional culture and cAMP signaling promote the maturation of human pluripotent stem cell-derived hepatocytes Development 2013 140 3285 3296 10.1242/dev.090266 23861064 23. Leek J.T. Johnson W.E. Parker H.S. Jaffe A.E. Storey J.D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments Bioinformatics 2012 28 882 883 10.1093/bioinformatics/bts034 22257669 24. Maere S. Heymans K. Kuiper M. BiNGO: A Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks Bioinformatics 2005 21 3448 3449 10.1093/bioinformatics/bti551 15972284 25. Ritchie M.E. Phipson B. Wu D. Hu Y. Law C.W. Shi W. Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies Nucleic Acids Res. 2015 43 e47 10.1093/nar/gkv007 25605792 26. Shannon P. Markiel A. Ozier O. Baliga N.S. Wang J.T. Ramage D. Amin N. Schwikowski B. Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks Genome Res. 2003 13 2498 2504 10.1101/gr.1239303 14597658 27. Krämer A. Green J. Pollard J. Jr. Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis Bioinformatics 2014 30 523 530 10.1093/bioinformatics/btt703 24336805 28. Merico D. Isserlin R. Stueker O. Emili A. Bader G.D. Enrichment map: A network-based method for gene-set enrichment visualization and interpretation PLoS ONE 2010 5 e13984 10.1371/journal.pone.0013984 21085593 29. Dreos R. Ambrosini G. Périer R.C. Bucher P. The Eukaryotic Promoter Database: Expansion of EPDnew and new promoter analysis tools Nucleic Acids Res. 2015 43 D92 D96 10.1093/nar/gku1111 25378343 30. Matys V. Kel-Margoulis O.V. Fricke E. Liebich I. Land S. Barre-Dirrie A. Reuter I. Chekmenev D. Krull M. Hornischer K. TRANSFAC and its module TRANSCompel: Transcriptional gene regulation in eukaryotes Nucleic Acids Res. 2006 34 D108 D110 10.1093/nar/gkj143 16381825 31. Qian Z. Cai Y.-D. Li Y. Automatic transcription factor classifier based on functional domain composition Biochem. Biophys. Res. Commun. 2006 347 141 144 10.1016/j.bbrc.2006.06.060 16808896 32. Dreos R. Ambrosini G. Groux R. Cavin Périer R. Bucher P. The eukaryotic promoter database in its 30th year: Focus on non-vertebrate organisms Nucleic Acids Res. 2017 45 D51 D55 10.1093/nar/gkw1069 27899657 33. Sierra-Filardi E. Puig-Kröger A. Blanco F.J. Nieto C. Bragado R. Palomero M.I. Bernabéu C. Vega M.A. Corbí A.L. Activin A skews macrophage polarization by promoting a proinflammatory phenotype and inhibiting the acquisition of anti-inflammatory macrophage markers Blood 2011 117 5092 5101 10.1182/blood-2010-09-306993 21389328 34. Biswas A. Ivaskevicius V. Thomas A. Varvenne M. Brand B. Rott H. Haussels I. Ruehl H. Scholz U. Klamroth R. Eight novel F13A1 gene missense mutations in patients with mild FXIII deficiency: In silico analysis suggests changes in FXIII-A subunit structure/function Ann. Hematol. 2014 93 1665 1676 10.1007/s00277-014-2102-4 24889649 35. Souri M. Osaki T. Ichinose A. The Non-catalytic B Subunit of Coagulation Factor XIII Accelerates Fibrin Cross-linking J. Biol. Chem. 2015 290 12027 12039 10.1074/jbc.M114.608570 25809477 36. Gemmati D. Zeri G. Orioli E. Mari R. Moratelli S. Vigliano M. Marchesini J. Grossi M.E. Pecoraro A. Cuneo A. Factor XIII-A dynamics in acute myocardial infarction: A novel prognostic biomarker? Thromb. Haemost. 2015 114 123 132 10.1160/TH14-11-0952 25947356 37. Jayo A. Conde I. Lastres P. Jiménez-Yuste V. González-Manchón C. Possible role for cellular FXIII in monocyte-derived dendritic cell motility Eur. J. Cell Biol. 2009 88 423 431 10.1016/j.ejcb.2009.04.002 19477035 38. Hasegawa H. Watanabe T. Kato S. Toshima T. Yokoyama M. Aida Y. Nishiwaki M. Kadowaki S. Narumi T. Honda Y. The role of macrophage transcription factor MafB in atherosclerotic plaque stability Atherosclerosis 2016 250 133 143 10.1016/j.atherosclerosis.2016.05.021 27214395 39. Verma S. Kumar A. Narang R. Bisoi A.K. Mitra D.K. Signature transcriptome analysis of stage specific atherosclerotic plaques of patients medRxiv 2021 10.1101/2021.06.15.21259006

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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091330 foods-11-01330 Article Study on the Flavor Compounds of Fo Tiao Qiang under Different Thawing Methods Based on GC–IMS and Electronic Tongue Technology Lin Ruirong 123 Yuan Hongfei 123 Wang Changrong 123 Yang Qingyu 123 https://orcid.org/0000-0003-3003-4423 Guo Zebin 123* Wu Jihong Academic Editor 1 Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition, Ministry of Education, Fuzhou 350002, China; 18750156585@163.com (R.L.); yhf199601@163.com (H.Y.); wcr940970864@163.com (C.W.); qingyu980206@163.com (Q.Y.) 2 State Key Laboratory of Food Safety Technology for Meat Products, Xiamen 361100, China 3 College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China * Correspondence: gzb8607@163.com; Tel.: +86-137-6383-8550 03 5 2022 5 2022 11 9 133014 4 2022 30 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). “Fo Tiao Qiang” is a famous dish with Chinese characteristics. It is delicious, rich in materials, and high in nutritional value. Through physical and chemical analysis, electronic tongue, gas chromatography–ion mobility spectroscopy, and other technologies, the present study explored the quality characteristics and flavor differences of Fo Tiao Qiang by using different thawing methods (natural thawing, ultrasonic thawing, microwave thawing, and water bath thawing). The results show that the protein content was slightly higher in Fo Tiao Qiang with ultrasonic thawing than others. The fat content of the microwave-thawed Fo Tiao Qiang was significantly lower than the other three kinds of samples. After ultrasonic thawing, the number of free amino acids in the samples were the highest and the umami taste was the best. Compared with natural thawing, most of the flavor substances decreased in ultrasonic thawing, microwave thawing, and water bath thawing. However, several substances increased, such as alpha-terpineol, beta-phenylethyl alcohol, phenylacetaldehyde, cis-rose oxide, isobutyl acetate, and 2–3-pentanedione. This study revealed the changing laws of different thawing methods on the quality characteristics and flavor characteristics of Fo Tiao Qiang. It provides theoretical guidance for the industrial production and quality control of Fo Tiao Qiang. Fo Tiao Qiang thawing method flavor substances electronic tongue GC–IMS (gas chromatography coupled to an ion mobility spectrometry) Regional Development Project of Fujian Province2019N3002 Fujian Provincial Department of Human Resources and Social SecurityMinwei Talent [2021] No. 5 This study was financially supported by the Regional Development Project of Fujian Province (2019N3002) and Fujian Provincial Department of Human Resources and Social Security (Minwei Talent [2021] No. 5). ==== Body pmc1. Introduction “Fo Tiao Qiang” occupies an important position in the traditional Chinese cuisine of Fujian, which is one of the provinces in China. It contains various popular seafoods and is rich in nutrients. Fo Tiao Qiang is usually made with abalone, sea cucumber, turtle skirt, isinglass, shiitake mushroom, tendon, flower mushroom, scallop, and pigeon egg as the ingredients, added to a boiled broth, and simmered. The soup stock ingredient of Fo Tiao Qiang includes fresh tube bones, Muscovy duck, pig intestine, native chicken, and fresh pigskin. The processing combines various cooking techniques such as frying, stir-frying, steaming, and simmering. Fo Tiao Qiang is popular among consumers because of its delicious mellow taste and high nutritional value. However, current research on Fo Tiao Qiang mainly focuses on cultural aspects, and scientific research mainly focuses on the aspect of the primary materials, sterilization technology, and shelf-life evaluation. In-depth studies on the nutritional quality and flavor characteristics of Fo Tiao Qiang are few. Thawing is the reverse process of freezing and is one of the important factors affecting the quality of frozen products. The method of thawing frozen food has an important influence on the sensory, chemical, and microbiological quality of the food. Improper thawing methods can cause fat oxidation, protein denaturation, decreased water holding capacity and microbial contamination [1], resulting in the degradation of its quality. Recently, many new and efficient thawing methods are explored, such as ultrasonic thawing, microwave thawing, ohmic thawing [2], high-voltage electrostatic field thawing [3], and radio frequency [4]. Ultrasonication can speed up the thawing process and shorten thawing time [5]. An appropriate ultrasonic power (UAT-400 W) can effectively reduce the thawing loss of meat, helping to avoid mineral and water-soluble-vitamin loss during thawing [6]. Sun et al. [7] proposed that the cavitation effect of ultrasound also produces gas cores, which can effectively reduce mechanical damage to fish tissues, thereby reducing thawing losses. Microwave heating is done with an object that is heated rapidly because of the vibrations of water molecules in the microwaves electromagnetic field. It is superior to the other thawing methods based on heat transfer from the sample surface in terms of a short thawing time [8]. In addition, microwave thawing not only has the characteristics of fast heating efficiency, energy saving, safety, and easy control, but it also effectively maintains the nutritional quality and flavor of food [9]. Different thawing methods have different heat-transfer principles and different effects on product quality. Therefore, to improve the quality of thawed products, it is necessary to choose a more appropriate thawing method. In this study, Fo Tiao Qiang thawed through different thawing methods were analyzed by electronic tongue for free amino acids, taste activity value, and taste nucleotide, and by gas chromatography–ion mobility spectrometry (GC–IMS) for volatile flavors. They reveal the changing regular pattern of different thawing methods on the quality characteristics and flavor characteristics of Fo Tiao Qiang, as well as provide theoretical guidance for its industrial production and quality control. 2. Materials and Methods 2.1. Sample Preparation All Fo Tiao Qiang samples were provided by Fujian Fliport Foods Co., Ltd. (Fuzhou, China), which were produced in January 2020. The ingredients and soup stock ingredients of Fo Tiao Qiang were burned in a porcelain altar for 8 ± 0.5 h with an open flame. After, the resultant product was canned, sterilized, cooled, and packaged. The samples of Fo Tiao Qiang were taken out of the −18 °C freezer and randomly divided into four groups. We used the following methods to thaw until the soup melted as the end of the thawing. (1) Ultrasonic thawing: The Fo Tiao Qiang sample was placed into the ultrasonic device with a power of 200 W, frequency of 40 kHz, and temperature of 25 ± 1 °C for thawing. (2) Microwave thawing: The Fo Tiao Qiang sample was placed into a microwave tray and microwaved at a frequency of 500 W to defrost. (3) Water bath thawing: The Fo Tiao Qiang sample was placed in a water bath to thaw at a temperature of 25 ± 1 °C. (4) Control group (natural thawing): The Fo Tiao Qiang samples were thawed in a ventilated room at a temperature of 25 ± 1 °C in a natural environment. Research manuscripts reporting large datasets that are deposited in a publicly available database should specify where the data have been deposited and provide the relevant accession numbers. If the accession numbers have not yet been obtained at the time of submission, please state that they will be provided during review. They must be provided prior to publication. Interventionary studies involving animals or humans, and other studies that require ethical approval, must list the authority that provided approval and the corresponding ethical approval code. 2.2. GC–IMS Analysis Analysis of the volatile compounds in the Fo Tiao Qiang samples was performed using a GC–IMS instrument (G.A.S., Dortmund, Germany) with an FS-SE-54-CB-1 capillary column (15 m × 0.53 mm × 0.5 μm; Restek, Westport, CT, USA). The samples of Fo Tiao Qiang were analyzed with the GC–IMS instrument as described by Li et.al. [9] with slight modifications. One gram of Fo Tiao Qiang sample was accurately weighed and placed into a 20 mL headspace vial. The samples were then incubated for 15 min at 80 °C. After incubation, 500 μL of the HS gas was injected with a syringe into the injector at 85 °C. The rotating speed for incubating was 500 rpm. Qualitative analysis of characteristic flavor substances was done by using Laboratory Analytical Viewer (LAV) and GC–IMS Library Search with the database of NIST 2014 (National Institute of Standards and Technology, Gaithersburg, MD, USA) and IMS2019 (G.A.S., Dortmund, Germany.). Reporter plug-in can directly compare the spectral differences between samples. Gallery plot plug-in can perform fingerprint comparison, as well as intuitive, quantitative comparison of the volatile organic compounds of samples. The dynamic principal component analysis (PCA) plug-in is used to cluster samples and quickly determine the types of unknown samples. 2.3. Electronic-Tongue Analysis The samples of Fo Tiao Qiang were analyzed with the electronic tongue as described by Ren et.al. [10] with slight modifications. The samples were first thawed in a hot water bath water (about 40 °C). The test on machine was done by mixing the sample (20 g) and purified water (80 g, Wahaha purified water) in a 250 mL beaker. The taste perception mechanism of living animals was imitated by using a taste analysis system (type of TS-5000Z) and the lipid membrane of an artificial sensor with wide area selection specificity. Using the electronic tongue, we detected the changes in the membrane potential caused by electrostatic or hydrophobic interactions between various flavor substances and artificial lipid membranes to evaluate the five basic flavors and the astringency. Artificial saliva mixed with KCl (30 mM) and tartaric acid (0.3 mM) was used as the reference solution. Each sample was tested three times in parallel, the data were analyzed using the device’s own database and software, and the radar chart and bubble chart were drawn. 2.4. Free Amino Acid (FAA) Component Analysis The FAA component was determined using the AQC(6-Aminoquinolyl-N-hydroxysuccinimidyl Carbamate) derivative method described by Zhou et al. [11] with slight modifications. Approximately 10.0 μL of the supernatant of the centrifugal fluid was filtered through a 0.22 μm microporous membrane and mixed with 70.0 μL of AccQ-Fluor borate buffer (pH 8.8), after which 20.0 μL of AccQ-Fluor reagent (3000 mg/L) was added. The solution was then vortexed and placed in an oven for 10 min at 55 °C. Finally, the solution was cooled to room temperature for testing. 2.5. Taste Activity Value (TAV) Analysis The TAV was calculated according to the following formula [12]. TAV = absolute concentration of a certain odorous substance in the sample/taste threshold of the substance 2.6. Measurement of Protein, Fat, Hydroxyproline, Total Sugar Content Protein content was determined by the Kjeldahl method according to China National Standard: GB 5009.5-2016. Fat content was determined by acid hydrolysis according to China National Standard: GB 5009.6-2016. Hydroxyproline was determined by the colorimetric evaluation according to China National Standard: GB T9695.23-2008. Total sugar content was determined by spectrophotometry according to China National Standard: GB T9695.31-2008. 2.7. Taste Nucleotide TAV was determined by liquid chromatography according to China National Standard: GB 5413.40-2016. 2.8. Equivalent Umami Concentration (EUC) The EUC was calculated according to the following formula [13]:(1)  EUC(gMSG/100 g)=∑aibi+1218(∑aibi)(∑aibi), where ai is amount of umami amino acids (g/100 g), and bi is the umami coefficient of umami amino acids relative to monosodium glutamate (MSG) (glutamate is 1.0; aspartic acid is 0.077). aj is the quantity of taste nucleotide/(g/100 g), bj is the umami coefficient of taste nucleotide relative to IMP (IMP(disodiuminosine5’-monophosphate) is 1.0; AMP(adenosine monophosphate) is 0.18; GMP(disodium guanosine5’-monophosphate) is 2.3), and 1218 is the synergy constant. 2.9. Statistical Analysis Each sample was measured three times for repeated experiments. The resulting data are represented as mean ± S.D. The experimental data were determined by ANOVA with SPSS 25.0 software (SPSS Inc., Chicago, IL, USA). The table was generated using Excel 2016 software (Microsoft Corporation, Redmond, WA, USA). The radar charts, bubble charts, and multiple histograms were generated using Origin 2018 (OriginLab, Massachusetts, MA, USA). 3. Results 3.1. Protein, Fat, Hydroxyproline, and Total Sugar Content The protein, fat, hydroxyproline, and total sugar content of different thawing methods of Fo Tiao Qiang are shown in Table 1. There was no significant difference in the protein, hydroxyproline, and total sugar content of the four samples of Fo Tiao Qiang. The content of hydroxyproline and total sugar in the four thawing methods was not much different. The protein content of the samples from ultrasonic thawing were slightly higher than other thawing methods. One study showed that ultrasonic thawing can contribute to the formation of smaller particle sizes and a higher solubility, which promote an increase in protein solubility and the formation of soluble protein [14]. In addition, the cavitation effect not only destroys the hydrophobic interactions that lead to the cross-linking of protein aggregates [15], but it also expands the structure of myofibrillar protein (MP) in combination with mild protein oxidation, thereby further promoting the increase in solubility [16]. Therefore, the protein content of the sample thawed by ultrasound is slightly higher than that of the other three thawing methods. Among the four samples from the different thawing methods, the crude fat content of the microwave-thawed Fo Tiao Qiang sample was significantly lower than that of the control group. This is mainly due to the increase in temperature, which caused the oxidation and decomposition of fat. According to reports, lipid oxidation is more likely to occur in regions with higher temperatures and pressures, and generates more free radicals with strong oxidizing abilities [17]. 3.2. FAA Component FAAs are important taste components. Table 2 shows the amino acid composition and the corresponding taste activity value of the samples from different thawing methods. A total of 17 FAAs including eight essential amino acids and nine non-essential amino acids were identified. From the result, the perspective of the total amount of amino acids under the four different thawing methods is significantly different (p < 0.05). The total amounts of amino acids from natural thawing, ultrasonic thawing, microwave thawing, and water bath thawing were 1224.40, 1290.79, 1217.67, and 1270.79 mg/100 g, respectively. A prolonged thawing time at a high temperature or local overheating will accelerate protein denaturation and lead to a significant reduction in free amino groups [14]. Studies have shown that ultrasonic thawing has a better stability and causes less damage to food [7]. Hence, the total amount of amino acids thawed by ultrasound was the highest, which is similar to the results of Bou et al. [18]. Zhang et al. [19] summarized three possible reasons that might be involved in the changes of FAAs. (1) The MP structure could be destroyed by ultrasonic treatment and thus more FAAs would migrate from the samples. (2) FAAs could go through thermal degradation under a high temperature and react with the reduced sugar, leading to the Maillard reaction. (3) FAAs could actively participate in Strecker degradation and further produce many volatile flavor compounds. Therefore, the amino acid content in different thawing processes is related to the amount of protein and amino acid degradation. In this study, the higher FAA content of the Fo Tiao Qiang after thawing was from glutamic acid, alanine, and arginine. Glutamic acid and alanine are important fresh and sweet amino acids in the Fo Tiao Qiang. Among all amino acids, the four thawing methods had the highest glutamic acid content. The ranking was ultrasonic thawing > water bath thawing > natural thawing > microwave thawing, which was consistent with the total amino acid ranking, indicating that ultrasonic thawing is beneficial to the release of amino acids [20]. TAV is proportional to the taste intensity. The synergistic interaction of various taste compounds is probably the most important factor affecting the taste of meat products [19]. It can be seen from the table that the amino acids that contributed much to the taste in the natural-thawing sample were glutamic acid (fresh), arginine (bitter/sweet), and alanine (sweet). The amino acids that contributed greatly to the taste in the ultrasonic-thawing sample were glutamic acid (fresh), methionine (bitter), and histidine (bitter). The amino acids that contributed the most to the taste in the microwave-thawing sample in decreasing order were glutamic acid (fresh), arginine (bitter/sweet), and alanine (sweet). In the water-bath-thawed sample, the most important contributions to the taste were glutamic acid (fresh), arginine (bitter/sweet), and alanine (sweet), the same as for natural thawing and microwave thawing. It was further proved that glutamic acid is the most important flavor amino acid in Fo Tiao Qiang after thawing. 3.3. Taste Nucleotide The content of taste nucleotides and their differences in different thawing methods are shown in Figure 1. Except for GMP, the other three nucleotides have significant differences. The contents of 5′-IMP, 5′-GMP, and 5′-AMP of different thawing methods and their taste activity values are shown in Table 3. Among the three kinds of nucleotides (Table 3), IMP has the highest content, indicating that IMP is the most active nucleotide in the Fo Tiao Qiang. Studies have shown that IMP is considered as a flavor enhancer and is widely used in the food industry to improve taste [21]. The synergistic effect between IMP and GMP can strongly enhance freshness [22]. Among the four thawing methods, the AMP and GMP values of ultrasonic thawing were the highest, but the IMP value was lower than that of microwave thawing. This may be because IMP has thermal instability, and the cavitation effect during ultrasonic thawing produces high temperatures and high pressures, which leads to thermal degradation and the loss of 5′-IMP [21,23]. The EUC (MSG equivalent) is generally used to measure the synergy between flavored nucleotides and savory amino acids. Research by Sabikun et al. [24] showed that 5′-nucleotides (IMP, GMP, and AMP) have a synergistic effect with aspartic and glutamic acids. After calculation, the EUC of the four thawing methods are in the order of 48.72, 60.73, 48.61, and 58.18 g MSG/100 g. The results show that the Fo Tiao Qiang with ultrasonic thawing has the highest umami intensity. 3.4. Electronic Tongue 3.4.1. Flavor Profile Figure 2 shows the outline of the Fo Tiao Qiang in different ways of thawing. We take the output of the reference solution as the tasteless point (tasteless, or 0 point), the tasteless point for the sour taste is −13, for the salty taste is −6, and for the other indicators is 0. According to this, when the taste value of the sample is lower than tasteless, it means that the sample does not have a taste; otherwise, it has taste. It can be seen from the radar chart of taste indicators that the Fo Tiao Qiang samples with different thawing methods have no sour taste. Compared with the reference solution, samples with different thawing methods have a certain difference in taste. As shown in the figure below, there are obvious differences in umami, saltiness, bitterness, and richness among the four thawing methods. 3.4.2. Umami, Saltiness, and Richness Figure 3 is the bubble chart of different thawing methods of the Fo Tiao Qiang, including saltiness, umami, and richness. The differences in saltiness, umami, and richness of the Fo Tiao Qiang should be specifically analyzed with different thawing methods. As shown in Figure 3, the stability of the three parallels of the same sample is better. The richness (the size of the bubbles) is compared first. The bigger the bubble, the greater the richness. The flavor richness of the Fo Tiao Qiang samples obtained by ultrasonic, microwave, and water-bath thawing was significantly higher than that of natural thawing. Second, the saltiness (X-axis) was compared. The saltiness of the samples obtained by water-bath thawing was significantly reduced and lower than for natural thawing. The saltiness of the samples obtained by microwave thawing was closer to natural thawing, and the saltiness of the ultrasonic-thawing samples was slightly higher than for natural thawing and water-bath thawing. Lastly, the difference in umami (Y axis) was analyzed. Compared with natural thawing, the umami taste of the samples with the water bath thawing decreased, and the umami of the samples with the microwave and ultrasonic thawing increased. Moreover, the highest umami value was the sample obtained by ultrasonic thawing. This was consistent with EUC (monosodium glutamate equivalent) findings. 3.4.3. Bitterness, Astringency, and Bitter Aftertaste Figure 4 is the bubble chart of different thawing methods of the Fo Tiao Qiang, including bitterness, astringency, and bitterness aftertaste. The bitterness and astringency of the Fo Tiao Qiang obtained by different thawing methods are analyzed as follows. As shown in Figure 4, the samples obtained by microwave thawing were close in terms of bitterness to the samples with ultrasonic thawing. The bitterness and bitter aftertaste of the samples in ultrasonic thawing were slightly enhanced compared with microwave thawing. Compared with natural thawing, the astringency of samples obtained from the other three thawing methods were significantly decreased, especially for water-bath thawing. 3.4.4. Principal Component Analysis (PCA) The results of PCA on the ingredient data are shown in Figure 5, in which samples with different thawing methods are represented by points of different colors. According to the PCA, the variance contribution rates of the first principal component (PC1) and the second principal component (PC2) were 92.3% and 7.0%, respectively, and the total contribution rate was 99.3%. The results show that PC1 and PC2 already contained a very large amount of information of the sample, which represented the original information of the sensor and reflected the overall information of the sample. The results in the figure show that there was a small overlap in the PCA distribution between the ultrasonic-thawing samples and the microwave-thawing samples, and so their overall tastes were relatively similar. There was an obvious difference between the natural thawing and water-bath-thawing sample, and the natural thawing was more significant. 3.5. Volatile Substances 3.5.1. Comparative Analysis of GC–IMS Spectra Figure 6 is the GC–IMS spectra of different thawing methods generated by the Reporter plug-in program in the LAV analysis software. The data were visually represented using a 3D spectrogram. In Figure 1, the x-, and y-axes, respectively, represent the ion migration time for identification (Dt) and the retention time of the gas chromatograph (Rt). In the figure, each point represents a volatile organic compound. From Figure 5 and Figure 6, the characteristic volatile components of the samples with different thawing methods have different GC–IMS characteristic spectrum information. 3.5.2. Qualitative Volatile Components Figure 7 shows the GC–IMS 2D spectra from Fo Tiao Qiang from different thawing methods. The entire spectra represented all volatile compounds of the samples. The red vertical line on the left side indicates the reactive ion peak (RIP), and each point on both sides of the RIP represents a volatile organic compound from the samples. The color represents the signal strength of the substance. White indicates a lower intensity, and red indicates a higher intensity. The intensity increased as the color deepened. From Figure 7, it can be intuitively concluded that there were fewer types of volatile compounds in natural thawing and water-bath thawing. The NIST database and IMS database built in the GC–IMS Library Search software was used to qualitatively analyze the substances. A total of 42 monomers and dimers of some substances were qualitatively detected, such as alcohols, aldehydes, ketones, esters, and other categories. Figure 8 shows the fingerprints of volatile substances in the different thawing methods. In the fingerprint, each row represents all volatile organic substances detected in the sample, and each column is a comparison of the same substance between different samples. We can see in Figure 8 that flavor substances such as alpha-terpineol, beta-phenylethyl alcohol, phenylacetaldehyde, cis-rose oxide, isobutyl acetate, and 2–3-pentanedione in area A were thawed by microwave, ultrasonic thawing, and water-bath thawing. Compared with the control sample, contents of these flavor substances were significantly increased. It may be because microwave thawing, ultrasonic thawing, and water-bath thawing promote molecular movement and aggravate the oxidation of fat. Terpineol, phenethyl alcohol, and rose ether have floral scents. The content of phenylacetaldehyde and cis-rose oxide (phenylacetaldehyde, cis-rose ether) in the water-bath-thawed samples increased relatively little. Studies have shown that ultrasonic treatment can accelerate lipid oxidation to produce more volatile flavor compounds, such as aldehydes, ketones, etc., and improve flavor by enhancing the interaction between volatile compounds and meat proteins [18,21,25]. In area B, a large amount of flavor substances exist in the control sample, such as aldehydes (pentanal, hexanal, heptanal, (E)-2-heptenal, octanal, (E)-2-octenal, 3-methylbutanal, 2-furfural, and benzaldehyde), alcohols (maltol, 3-methylbutan-1-ol, and 5-methylfurfuryl alcohol), and ketones (2-butanone, 1-octen-3-one). The content of the microwave-thawed sample was slightly less than that of the control sample, and the content of the water-bath-thawed sample was the least. The main reasons are that the control group had not been heated for a long time, the tissue destruction rate was low, and the protein was not easily denatured. 3-Methylbutan-1-ol, 2-furfural, pentanal, and other substances had also disappeared in the water-bath thawed samples. In area C, the water-bath-thawing sample contents of 6-methyl-5-hepten-2-one, 3-hydroxy-2-butanone, 2-heptanone, ethyl acetate, isovaleric acid, 1-octen-3-ol, (Z)-3-hexenol, alpha-pinene, and other substances were greatly increased. Isovaleric acid is a food flavor permitted by GB 2760-1996. It is mainly used to prepare cheese and cream flavors. It is also used in a trace amount of fruit flavors. Ethyl acetate has a fruity aroma, and the test data of amino acids indicates that it can be produced by more flavored amino acids by thawing in a static water bath. In summary, natural thawing, microwave thawing, ultrasonic thawing, and water-bath thawing reduced the content of most flavor substances. Here, water-bath-thawed samples declined the most. It may be because the materials in the tank were not uniformly heated by static water bath heating, and the low temperature inhibited the oxidation and decomposition of fat to a certain extent. The content of some flavor substances showed different degrees of improvement in samples obtained by microwave thawing, ultrasonic thawing, and water-bath thawing. 3.5.3. GC–IMS PCA The GC–IMS PCA results of the volatile flavor compounds of Fo Tiao Qiang under different thawing methods are shown in Figure 9. The contribution rate of PC1 was 56%, the contribution rate of PC2 was 28%, and the cumulative contribution rate was 84% (>70%), indicating that Figure 9 can represent the information of volatile substances of Fo Tiao Qiang. By observing Figure 9, we can see that the four thawing methods were clustered separately and did not overlap. The distance between microwave thawing and ultrasonic thawing was close, indicating that the volatile substances of the two samples were similar. 4. Summary In this study, four methods (natural thawing, ultrasonic thawing, microwave thawing, and water-bath thawing) were used to thaw Fo Tiao Qiang. From the perspective of physical and chemical indicators, the protein content of the ultrasonically thawed Fo Tiao Qiang is slightly higher than that of other thawing methods; the fat content of the microwave-thawed Fo Tiao Qiang is significantly lower than that of the other three types of Fo Tiao Qiang. The FAA content is determined by the combination of amino acids produced by protein solubilization and the loss of amino acids caused by amino acid degradation. Ultrasonic thawing has a good stability, and so the sample thawed by ultrasonic has the highest amino acid content. Among the four thawing methods, the glutamic acid content is the highest, which contributes the most to the taste. Taste nucleotides and umami amino acids have a synergistic effect, and EUC is generally used to measure the synergistic effect. Ultrasonically thawed Fo Tiao Qiang has the highest intensity of umami flavor, and the nucleotide that contributed the most to the flavor of Fo Tiao Qiang was 5′-IMP. The electronic tongue technology intuitively reflects the obvious difference in the taste of Fo Tiao Qiang under different thawing methods. According to the PCA chart, the overall tastes from ultrasonic thawing and microwave thawing are similar. GC–IMS identified 42 compounds of Fo Tiao Qiang. Microwave thawing, ultrasonic thawing, and water-bath thawing led to a decrease in the content of most flavor substances and an increase in the content of some flavor substances. The above results can provide a theoretical basis for the nutritional index and flavor changes in different thawing methods in order to find the best thawing method. Acknowledgments We are grateful to the study participants. Author Contributions Conception and design of the work, Z.G.; writing—original draft and writing—review & editing, R.L.; data analysis, H.Y.; data curation, C.W. and Q.Y. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data is contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Nucleotide content of different thawing method “Fo Tiao Qiang”. Note: Different letters in the figure indicate significant differences (p < 0.05). Figure 2 Radar chart of effective taste index of samples of different thawing methods of “Fo Tiao Qiang”. Figure 3 Saltiness, umami, and richness bubble chart of different thawing methods of “Fo Tiao Qiang”. Note: “A1A2A3”, “B1B2B3”, “C1C2C3”, “D1D2D3” are three parallel samples of “natural thawing, ultrasonic thawing, microwave thawing, and water bath thawing”. Figure 4 Bitterness, astringency, and bitterness aftertaste bubble chart of different thawing methods of “Fo Tiao Qiang”. Note: “A1A2A3”, “B1B2B3”, “C1C2C3”, “D1D2D3” are three parallel samples of “natural thawing, ultrasonic thawing, microwave thawing, and water bath thawing”. Figure 5 PCA principal component analysis diagram of different thawing methods of “Fo Tiao Qiang”. Figure 6 3D-topographic of different thawing methods of “Fo Tiao Qiang”. Figure 7 Results of GC–IMS spectra in different thawing methods of “Fo Tiao Qiang”. Figure 8 GC–IMS volatile substances fingerprint in different thawing methods of “Fo Tiao Qiang”. Note: A, B, C respectively represent the characteristic flavor substances of Fo Tiao Qiang under different thawing methods. Figure 9 PCA analysis chart of different thawing method of “Fo Tiao Qiang”. foods-11-01330-t001_Table 1 Table 1 The protein, hydroxyproline, fat, and total sugar content of different thawing methods of “Fo Tiao Qiang”. Sample Protein (g/100 g) Hydroxyproline (g/100 g) Fat (g/100 g) Total Sugar (g/100 g) Natural thawing 75.57 ± 1.57 a 0.016 ± 0.00 a 0.249 ± 0.02 a 0.0162 ± 0.00 a Ultrasonic thawing 76.06 ± 4.18 a 0.016 ± 0.00 a 0.197 ± 0.03 ab 0.0153 ± 0.00 a Microwave thawing 74.21 ± 1.67 a 0.014 ± 0.00 a 0.143 ± 0.00 b 0.0162 ± 0.00 a Water bath thawing 74.35 ± 4.12 a 0.015 ± 0.00 a 0.175 ± 0.09 ab 0.0154 ± 0.00 a Note: Values are expressed as mean ± SD (n = 3), and different letters in the column indicate significant differences (p < 0.05). foods-11-01330-t002_Table 2 Table 2 Composition of amino acids in different thawing methods of “Fo Tiao Qiang”. Amino Acid Taste Contribution Threshold (mg/100 g) Natural Thawing Ultrasonic Thawing Microwave Thawing Water bath Thawing Content (mg/100 g) TAV Content (mg/100 g) TAV Content (mg/100 g) TAV Content (mg/100 g) TAV Asp fresh 100 58.90 ± 3.88 b 0.59 69.34 ± 1.97 a 0.69 61.18 ± 0.74 ab 0.61 69.20 ± 7.71 a 0.69 Glu fresh 30 332.84 ± 8.20 b 11.09 371.00 ± 3.42 a 11.43 318.91 ± 4.43 c 10.63 342.84 ± 3.12 b 11.43 Ger sweet 150 62.25 ± 3.86 a 0.41 72.52 ± 2.59 a 0.41 64.80 ± 2.12 a 0.43 62.24 ± 8.01 a 0.41 Gly sweet 130 104.06 ± 3.76 b 0.80 96.74 ± 0.85 b 0.48 121.61 ± 4.08 a 0.94 130.12 ± 6.2 a 1.00 Thr sweet 260 42.67 ± 1.31 a 0.16 44.77 ± 0.20 a 0.50 41.82 ± 0.27 a 0.16 42.66 ± 3.21 a 0.16 Ala sweet 60 108.89 ± 0.93 c 1.81 119.26 ± 2.68 a 0.71 110.57 ± 4.36 bc 1.84 116.01 ± 2.18 ab 1.93 Pro sweet - 66.05 ± 1.31 b / 68.50 ± 0.73 ab / 66.20 ± 0.51 b / 71.76 ± 4.37 a / Lys sweet/bitter 50 62.49 ± 1.84 a 1.25 63.95 ± 0.20 a 1.44 57.81 ± 0.64 b 1.16 62.84 ± 3.67 a 1.26 Asn sweet - 44.96 ± 0.82 a / 49.76 ± 2.66 a / 46.28 ± 2.29 a / 45.91 ± 3.24 a / Tyr bitter - 41.45 ± 1.11 b / 46.93 ± 1.97 a / 41.09 ± 0.51 b / 41.51 ± 1.77 b / Val bitter/sweet 40 47.96 ± 0.41 b 1.20 50.98 ± 2.96 a 1.04 47.24 ± 0.28 b 1.18 50.80 ± 1.31 a 1.27 Iel bitter 90 33.70 ± 2.50 a 0.37 28.98 ± 2.20 b 0.56 29.43 ± 2.62 ab 0.33 27.96 ± 0.69 b 0.31 Leu bitter 190 67.08 ± 1.15 a 0.35 64.05 ± 1.84 ab 0.00 61.23 ± 1.52 b 0.32 61.31 ± 2.51 b 0.32 Arg bitter/sweet 50 105.41 ± 5.86 a 2.11 95.37 ± 5.91 a 0.56 104.59 ± 0.06 a 2.09 100.62 ± 1.0 a 2.01 His bitter 20 26.69 ± 0.10 b 1.33 28.68 ± 0.19 a 3.07 26.02 ± 0.52 b 1.30 28.58 ± 0.56 a 1.43 Met bitter 30 12.03 ± 0.28 bc 0.40 14.27 ± 0.62 a 3.35 29.43 ± 2.62 ab 0.33 11.17 ± 1.23 c 0.37 Trp bitter - 6.98 ± 0.23 a / 5.71 ± 0.29 b / 13.55 ± 0.20 ab / 4.67 ± 0.95 b / Totol 1224.40 ± 37.55 b 1290.79 ± 31.28 a 1217.67 ± 25.22 b 1270.19 ± 53.98 ab Note: TAV: Taste Activity Value. “-” did not find data; “/” was not calculated; the same line marked different letters indicates significant differences (p < 0.05). foods-11-01330-t003_Table 3 Table 3 Nucleotide content and their TAVs of different thawing method “Fo Tiao Qiang”. Nucleotide Threshold (mg/100 g) Natural Thawing Ultrasonic Thawing Microwave Thawing Water Bath Thawing Content (mg/100 g) TAV Content (mg/100 g) TAV Content (mg/100 g) TAV Content (mg/100 g) TAV AMP Adenosine 50 47.82 ± 6.58 b 0.96 63.73 ± 2.87 a 1.27 55.62 ± 0.91 ab 1.11 48.90 ± 1.76 b 0.98 GMP Guanylic acid 12.5 8.52 ± 0.14 a 0.68 9.60 ± 0.14 a 0.77 9.14 ± 0.80 a 0.73 9.28 ± 0.99 a 0.74 IMP Inosinic acid 25 89.53 ± 4.95 c 3.58 98.34 ± 2.84 b 3.93 91.48 ± 3.59 b 3.66 106.23 ± 1.33 a 4.25 Note: the same line marked different letters indicates significant differences (p < 0.05). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Li D. Zhao H. Muhammad A.I. Song L. Guo M. Liu D. The comparison of ultrasound-assisted thawing, air thawing and water immersion thawing on the quality of slow/fast freezing bighead carp (Aristichthys nobilis) fillets Food Chem. 2020 320 126614 10.1016/j.foodchem.2020.126614 32208187 2. Cevik M. Icier F. Numerical simulation of temperature histories of frozen minced meat having different fat contents during ohmic thawing Int. J. Therm. Sci. 2021 165 106958 10.1016/j.ijthermalsci.2021.106958 3. Jia G. Nirasawa S. Ji X. Luo Y. Liu H. Physicochemical changes in myofibrillar proteins extracted from pork tenderloin thawed by a high-voltage electrostatic field Food Chem. 2018 240 910 916 10.1016/j.foodchem.2017.07.138 28946361 4. Dong J. Kou X. Liu L. Hou L. Li R. Wang S. Effect of water, fat, and salt contents on heating uniformity and color of ground beef subjected to radio frequency thawing process Innov. Food Sci. Emerg. Technol. 2021 68 102604 10.1016/j.ifset.2021.102604 5. Cai L. Zhang W. Cao A. Cao M. Li J. Effects of ultrasonics combined with far infrared or microwave thawing on protein denaturation and moisture migration of Sciaenops ocellatus (red drum) Ultrason. Sonochemistry 2019 55 96 104 10.1016/j.ultsonch.2019.03.017 31084796 6. Guo Z. Ge X. Yang L. Ma G. Ma J. Yu Q.-l. Han L. Ultrasound-assisted thawing of frozen white yak meat: Effects on thawing rate, meat quality, nutrients, and microstructure Ultrason. Sonochemistry 2021 70 105345 10.1016/j.ultsonch.2020.105345 7. Sun Q. Kong B. Liu S. Zheng O. Zhang C. Ultrasound-assisted thawing accelerates the thawing of common carp (Cyprinus carpio) and improves its muscle quality LWT 2021 141 111080 10.1016/j.lwt.2021.111080 8. Watanabe T. Ando Y. Evaluation of heating uniformity and quality attributes during vacuum microwave thawing of frozen apples LWT 2021 150 111997 10.1016/j.lwt.2021.111997 9. Cai L. Dai Y. Cao A. Cao M. The effects of CS@Fe3O4 nanoparticles combined with microwave or far infrared thawing on microbial diversity of red seabream (Pagrus major) fillets based on high-throughput sequencing Food Microbiol. 2020 91 103511 10.1016/j.fm.2020.103511 32539943 10. Ren G. Li T. Wei Y. Ning J. Zhang Z. Estimation of Congou black tea quality by an electronic tongue technology combined with multivariate analysis Microchem. J. 2021 163 105899 10.1016/j.microc.2020.105899 11. Zhou P. Zhao F. Chen M. Ye N. Lin Q. Ouyang L. Cai X. Meng P. Gong X. Wang Y. Determination of 21 free amino acids in 5 types of tea by ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC–MS/MS) using a modified 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) method J. Food Compos. Anal. 2019 81 46 54 10.1016/j.jfca.2019.05.007 12. Moerdijk-Poortvliet T.C.W. de Jong D.L.C. Fremouw R. de Reu S. de Winter J.M. Timmermans K. Mol G. Reuter N. Derksen G.C.H. Extraction and analysis of free amino acids and 5′-nucleotides, the key contributors to the umami taste of seaweed Food Chem. 2022 370 131352 10.1016/j.foodchem.2021.131352 34788963 13. Yamaguchi T.Y.S. Ikeda T.S. NNinomiya. Measurement of the relative taste intensity of some l-α-amino acids and 5′-nucleotides J. Food Sci. 1971 36 846 849 10.1111/j.1365-2621.1971.tb15541.x 14. Li F. Wang B. Liu Q. Chen Q. Zhang H. Xia X. Kong B. Changes in myofibrillar protein gel quality of porcine longissimus muscle induced by its stuctural modification under different thawing methods Meat Sci. 2019 147 108 115 10.1016/j.meatsci.2018.09.003 30219362 15. Farahnak R. Nourani M. Riahi E. Ultrasound thawing of mushroom (Agaricus bisporus): Effects on thawing rate, protein denaturation and some physical properties LWT 2021 151 112150 10.1016/j.lwt.2021.112150 16. Zhang R. Xing L. Kang D. Zhou L. Wang L. Zhang W. Effects of ultrasound-assisted vacuum tumbling on the oxidation and physicochemical properties of pork myofibrillar proteins Ultrason. Sonochemistry 2021 74 105582 10.1016/j.ultsonch.2021.105582 17. Kang D.-C. Gao X.-Q. Ge Q.-F. Zhou G.-H. Zhang W.-G. Effects of ultrasound on the beef structure and water distribution during curing through protein degradation and modification Ultrason. Sonochemistry 2017 38 317 325 10.1016/j.ultsonch.2017.03.026 18. Bao G. Niu J. Li S. Zhang L. Luo Y. Effects of ultrasound pretreatment on the quality, nutrients and volatile compounds of dry-cured yak meat Ultrason. Sonochemistry 2022 82 105864 10.1016/j.ultsonch.2021.105864 19. Zhang J. Zhang Y. Wang Y. Xing L. Zhang W. Influences of ultrasonic-assisted frying on the flavor characteristics of fried meatballs Innov. Food Sci. Emerg. Technol. 2020 62 102365 10.1016/j.ifset.2020.102365 20. Gao X. Zhang J. Liu E. Yang M. Chen S. Hu F. Ma H. Liu Z. Yu X. Enhancing the taste of raw soy sauce using low intensity ultrasound treatment during moromi fermentation Food Chem. 2019 298 124928 10.1016/j.foodchem.2019.05.202 31272053 21. Zou Y. Kang D. Liu R. Qi J. Zhou G. Zhang W. Effects of ultrasonic assisted cooking on the chemical profiles of taste and flavor of spiced beef Ultrason. Sonochemistry 2018 46 36 45 10.1016/j.ultsonch.2018.04.005 29739511 22. Meng Q. Zhou J. Gao D. Xu E. Guo M. Liu D. Desorption of nutrients and flavor compounds formation during the cooking of bone soup Food Control 2022 132 108408 10.1016/j.foodcont.2021.108408 23. Li X. Liu Y. Wang Y. Wang J. Xu Y. Yi S. Zhu W. Mi H. Li T. Li J. Combined ultrasound and heat pretreatment improve the enzymatic hydrolysis of clam (Aloididae aloidi) and the flavor of hydrolysates Innov. Food Sci. Emerg. Technol. 2021 67 102596 10.1016/j.ifset.2020.102596 24. Sabikun N. Bakhsh A. Rahman M.S. Hwang Y.-H. Joo S.-T. Volatile and nonvolatile taste compounds and their correlation with umami and flavor characteristics of chicken nuggets added with milkfat and potato mash Food Chem. 2021 343 128499 10.1016/j.foodchem.2020.128499 33160776 25. Xu L. Zheng Y. Zhou C. Pan D. Geng F. Cao J. Xia Q. Kinetic response of conformational variation of duck liver globular protein to ultrasonic stimulation and its impact on the binding behavior of n-alkenals LWT 2021 150 111890 10.1016/j.lwt.2021.111890

PMC009xxxxxx/PMC9099570.txt

==== Front Polymers (Basel) Polymers (Basel) polymers Polymers 2073-4360 MDPI 10.3390/polym14091915 polymers-14-01915 Article Simultaneous Effects of Carboxyl Group-Containing Hyperbranched Polymers on Glass Fiber-Reinforced Polyamide 6/Hollow Glass Microsphere Syntactic Foams Kim Jincheol 1† https://orcid.org/0000-0002-8479-4586 Lee Jaewon 1† Hwang Sosan 1 Park Kyungjun 1 Hong Sanghyun 2 Lee Seojin 2 Shim Sang Eun 1* Qian Yingjie 1* Kim Kwang-Jea Academic Editor Lee Patrick Academic Editor 1 Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Michuhol-gu, Incheon 22212, Korea; 22192178@inha.edu (J.K.); 22192186@inha.edu (J.L.); bulls@inha.edu (S.H.); 22201542@inha.edu (K.P.) 2 LG Electronics Inc. 51, Gasan Digital 1-ro, Geumcheon-gu, Seoul 08592, Korea; sanghyun.hong@lge.com (S.H.); seojin710.lee@lge.com (S.L.) * Correspondence: seshim@inha.ac.kr (S.E.S.); yjqian@inha.ac.kr (Y.Q.) † These authors contributed equally to this work. 07 5 2022 5 2022 14 9 191514 3 2022 26 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The hollow glass microsphere (HGM) containing polymer materials, which are named as syntactic foams, have been applied as lightweight materials in various fields. In this study, carboxyl group-containing hyperbranched polymer (HBP) was added to a glass fiber (GF)-reinforced syntactic foam (RSF) composite for the simultaneous enhancement of mechanical and rheological properties. HBP was mixed in various concentrations (0.5–2.0 phr) with RSF, which contains 23 wt% of HGM and 5 wt% of GF, and the rheological, thermal, and mechanical properties were characterized systematically. As a result of the lubricating effect of the HBP molecule, which comes from its dendritic architecture, the viscosity, storage modulus, loss modulus, and the shear stress of the composite decreased as the HBP content increased. At the same time, because of the hydrogen bonding among the polymer, filler, and HBP, the compatibility between filler and the polymer matrix was enhanced. As a result, by adding a small amount (0.5–2.0 phr) of HBP to the RSF composite, the tensile strength and flexural modulus were increased by 24.3 and 9.7%, respectively, and the specific gravity of the composite was decreased from 0.948 to 0.917. With these simultaneous effects on the polymer composite, HBP could be potentially utilized further in the field of lightweight materials. syntactic foams hyperbranched polymer polyamide 6 hollow glass microsphere lubricant compatibilizer composites LG Electronics, Co. Ltd.This study was supported by LG Electronics, Co. Ltd. ==== Body pmc1. Introduction The international automobile market has been changing from traditional internal combustion engines to eco-friendly vehicle development, in line with corporate average fuel efficiency (CAFÉ) standards and automobile greenhouse gas (GHG) emission standards [1]. As economic and the environmental concerns for fuel consumption have evolved, lightweight materials became of great interest to the automotive industry [2,3,4,5,6,7]. In order to apply lightweight materials in the automotive industry, the mechanical strength and the processability of the material must be accompanied by reduced specific gravity. To reduce the specific gravity of the polymeric composite materials, numerous studies have been actively conducted on hollow glass microsphere (HGM)-containing lightweight syntactic foams (SFs) in various applications, such as automotive, marine, and aerospace [8,9,10,11,12,13,14,15]. HGM exhibits a low specific gravity and high electrical and thermal insulation properties. However, the addition of HGMs in higher contents results in the weakening of mechanical properties of SFs [12,16]. Addition of fibrous material, such as glass fiber (GF) or carbon fiber to SFs, can enhance the mechanical properties of the SFs; these are named reinforced syntactic foam (RSF) [17,18,19]. Nevertheless, the addition of rigid HGM and GF particles have a detrimental effect on the processability by increasing viscosity. Furthermore, due to the high shear of the extrusion process, HGM particles are broken, and this breakage results in an increase in the specific gravity of the polymer composites [9,20]. To address these issues, lubricating agents and plasticizers have been widely studied [21,22,23,24]. These materials modify the viscosity of the polymer melt, and reduce the friction; as a result, they increase the processability of the polymer composite with their addition in small amounts to the composites. The paraffin waxes, esters, and fatty acids derivatives are commonly used as lubricants for polymers [25]. Generally, when these typical lubricants are added to the composite material, the mechanical strength of the material weakens, since these lubricants have low molecular weights and low compatibility with polymer matrices [26,27]. Recently, topology-engineered polymers, such as star-shaped polymers and hyperbranched polymers have been studied, in order to be applied as lubricants [24,28]. Hyperbranched polymer (HBP) is a highly branched three-dimensional polymer. The HBP molecule has a low degree of entanglement and low viscosity due to the dendritic architecture of the molecule [29,30]. It can be utilized as a rheological modifier in polymeric composites by acting as molecular ball-bearings at the expense of the van der Waals forces [31]. According to WanG′s study [24], as the polymer chain topology changes from a linear to a hyperbranched structure, the intrinsic viscosity and the complex viscosity of the polymer decrease significantly, and the shear stability of the polymer increases as well. Besides, the abundant functional groups in the HBP molecules make it possible to form hydrogen bonding among HBP, polymer matrix, and the fillers in the composite material [32,33]. This functionality results in the compatibilization of the filler in the composite material, and could make up for the weakened mechanical strength of the syntactic foams. Gu et al. [34] increased the toughness and the mechanical strength of soybean protein film with addition of hyperbranched polyester, which forms strong hydrogen bonding with the soybean protein matrix. Peng et al. [35] improved the wettability and the interfacial adhesion of carbon fiber to an epoxy resin matrix by poly(amido amine) functionalization. As a result of its dendritic structure and abundant functional groups, HBP could act as a lubricating additive and as a compatibilizer at the same time in the GF-reinforced SF system. In the present study, the carboxyl group-containing HBP molecule was introduced to RSF composite material to reduce the viscosity and to improve the mechanical properties of the composite material simultaneously. We used polyamide 6 (PA 6) as a polymer matrix, since PA 6 is widely used in the automotive industry, and HBP can be dispersed effectively in the PA 6 matrix due to the hydrogen bonding ability of PA 6. Scanning electron microscopy (SEM) microphotographs revealed that the compatibility between filler and PA 6 polymer matrix was enhanced with the addition of a small amount of HBP (0.5–2.0 phr). The density of the RSF and ashes of the RSF were measured to calculate HGM breakage of RSF material. Tensile strength increased significantly from 59 to 73 MPa, and the specific gravity decreased from 0.948 to 0.917 with the addition of HBP. 2. Materials and Methods 2.1. Materials Injection grade Nylon-6 (Ultramid, B3S, Ludwigshafen, Germany), with a density of 1.13 g/cm3 and melt volume rate of 160 cm3/min at a temperature of 275 °C, given load of 5 kg, was supplied by BASF (Ludwigshafen, Germany). HGM (IM16K) provided by 3M (Saint Paul, SP, USA), with a true density of 0.46 g/cm3, a crush strength of 110 MPa, and average diameter of 20 μm, was used as the lightweight filler in this study. The chopped nylon-compatible-sized GF used for a reinforced filler was 995-10P grade from Owens Corning (Toledo, OH, USA). The GF grade has a nominal diameter of 10 μm, chopped length of 4 mm, and sized with amino silane coupling agent. Carboxyl group functionalized HBP, CYD-7010 (synthesized from adipic acid and hyperbranched polyester with 98:2 molar ratio), with a melt range of 135~155 °C, was supplied by Weihai CY Dendrimer Technology Corporation (Weihai, China). The chemical structures of PA 6, HGM, GF, and HBP are presented in Figure 1. 2.2. Methods 2.2.1. Sample Preparation The syntactic foams were prepared in a co-rotating twin-screw extruder (TEK-25, SM PLATEC Co., Ansan, Korea), with screw diameter of 25 mm, Do/Di = 1.55, L/D = 40, comprising two kneading zones for both dispersive and distributive mixing. Twin screw configuration is depicted in Figure S1. In order to minimize hydrolysis during the extrusion process, Nylon-6 was pre-dried at 80 °C for 24 h. The PA 6 pellets and HBP powder were fed into the main hopper first. Then, the HGM was fed into the first side feeder, after which the GF was fed into the second side feeder. All composites were melt-mixed at the same conditions under 200 rpm at a temperature range of 240/240/250/250/250/250/250/250/250/250 °C from hopper to die. The PA 6 and the HBP were pre-melted before introducing HGM fillers. The extrudates were passed through a hot water bath, pelletized, and dried at 80 °C for 24 h before injection molding. Specimens for the tensile, flexural testing, and density measurements were injection molded in a lab-scale injection molding machine (VDCII-50, JINHWA GLOTECH, Cheonan, Korea) with a clamping force of 50 tons. Injection molding was carried out at a barrel temperature profile of 190/220/230/240/240 °C from hopper to nozzle, and a mold temperature of 80 °C. The compositions and the codes of the prepared samples are reported in Table 1. 2.2.2. Characterization Complex viscosity and shear modulus were measured using an Anton Paar MCR 302 rheometer (Graz, Austria) with 25-mm parallel plate geometry. Extrudates of neat Nylon-6 and composites were molded at 240 °C. Small angle oscillatory shear (SAOS) frequency sweep tests were performed at a constant temperature of 240 °C within a linear viscoelastic regime in the range of 0.1–100 rad/s. The tensile-fractured samples for morphological observation were characterized with field-emission scanning electron microscopy (FE-SEM) using the model S-4300 from HITACHI (Tokyo, Japan). The fractured surface was sputter-coated with platinum. Right after the tensile testing, the fractured surface of each sample was dipped in liquid nitrogen for 10 min to keep the shape of the surface. The differential scanning calorimetry (DSC) analysis was conducted with NETZSCH DSC200F3 (Selb, Germany), with a sample mass of 3 mg that was set in an aluminum pan with a cover under an N2 atmosphere with a flow rate of 40 mL/min, to determine the crystallization behavior of the composites. The glass transition temperature (Tg), melting temperature (Tm), and melt crystallization temperature (Tc) were measured from the second heating and cooling cycle, respectively. The profile of the thermogram is depicted in Figure S2. The samples were first heated from 20 to 250 °C at a rate of 30 °C/min and held at 250 °C for 4 min to eliminate thermal history of the samples. The samples were then cooled down to −10 °C at a rate of 30 °C/min and held at −10 °C for 10 min. The DSC data were collected in the second cycle (segments 6 and 8 as heating and cooling, respectively). The samples were heated at a rate of 10 °C/min from −10 to 250 °C, and then held at 250 °C for 4 min. Then the samples were cooled to −10 °C at a rate of 10 °C/min. The samples were finally held at −10 °C for 4 min. The crystallinity of the samples was calculated by the following equation:(1) Xc (%)=∆HfWm·∆Ho where ∆Hf is heat of fusion for the sample, Wm is the mass fraction of the PA 6, and the ∆Ho is the heat of fusion of the theoretical 100% crystalline PA 6 (240 J/g). The non-isothermal crystallization behavior of the composites was calculated using the Avrami equation [36,37,38]:(2) 1−Vt=exp(−Zttn) where Vt is the relative volumetric fraction of crystalline, Zt is the overall crystallization rate constant which reflects both nucleation and crystal growth, and n is the Avrami index. The Vt can be obtained by the following equation:(3) Vt=WcWc+(ρcρa)(1−Wc) where Wc = ∆H(t)/∆Htotal is the crystalline mass fraction, and ρc and ρa are crystalline density (1.20 g/cm3) and amorphous density (1.09 g/cm3) of the PA 6, respectively [39]. When the crystallization rate constant is corrected by taking the cooling rate into account for the Avrami equation, which was applied only to the isothermal crystallization, the following equation is used, where the Zc is the crystallization rate constant in the non-isothermal condition:(4) logZc=logZtdT/dt Thermogravimetric analysis (TGA) was performed with PerkinElmer TGA4000 (Waltham, MA, USA) under an N2 atmosphere with a flow rate of 20 mL/min. The samples with a mass of 10 mg were contained in an aluminum pan, and measured at a heating rate of 10 °C/min from 40 to 800 °C to determine thermal stability of the composite samples. The tensile strength (ASTM D638) and flexural modulus (ASTM D790) of each specimen were performed using a universal testing machine (DUT-2TC, DAEKYUNG ENGINEERING Co., Bucheon, Korea) with a 2-ton load cell. Specimen dimensions for the tensile test are presented in Figure S1b. Samples for the flexural test having dimensions of 127 × 12.7 × 6.4 mm3 (length × width × thickness) were employed for the test in accordance with ASTM D790. The tensile tests were performed at a cross-head speed of 50 mm/min. The flexural tests were carried out in the three-point bending configuration at a cross-head speed of 1.54 mm/min. Flexural modulus was calculated from the slope of the initial linear portion of the curves. The five different samples were tested for accurate results. Two types of density measurements were conducted with a hydro-densimeter (GP300S, MATSUHAKU, Taichung, Taiwan) and a gas pycnometer (BELPycno, MicrotracBEL Corp., Osaka, Japan) to measure the bulk density of the composites and residue inorganic ashes of the composites, respectively. 3. Results and Discussion 3.1. Rheological Properties The rapid increase in complex viscosity in RSF control is shown in Figure 2a due to the high content of fillers (HGM, GF). As the contents of HBP increased, the complex viscosity of the composites was reduced across the entire frequency range. It was confirmed that the complex viscosity of RSF-COOH 2.0 decreased by 4.9 times at 0.1 rad/s compared to the neat RSF due to the addition of the HBP molecules in the composite system. Figure 2b shows that the shear stress decreased as the HBP content increased. The internal friction was alleviated by HBP, which has a low intrinsic viscosity in the molten state. HBP molecules improved the polymer chain mobility due to its lubricating effect, and this improved polymer chain mobility in filled RSF composite is on account of the dendritic architecture of HBP [40]. The reduced shear stress could contribute to the reduction in HGM breakage arising from the high shear in the extrusion process and decrease in the specific gravity of the composite. Changes in storage modulus (G′) and loss modulus (G″) of the composites for different contents of HBP in RSF are shown in Figure 2c,d. In overall frequency, the G″ was higher than the G′ value, which means the composites were measured in the predominantly viscous region. Kang et al. [41] found that the syntactic foams aggregated at higher content (higher than HGM 10 wt%), and the viscoelastic response changed from viscous to elastic behavior at low frequency. Similarly, both the storage modulus (G′) and the loss modulus (G″) of the RSF were increased compared to the neat PA 6. When HBP was added to the RSF, the G′ and G″ decreased in overall frequency. Due to the low entanglement degree of the HBP molecule itself, the lubricating effect was applied in the composite system; as a result, the overall G′ and G″ tend to decrease in RSF-COOH composites. At high frequencies, the alteration of segmental dynamics was not observed because the entanglement structure of the polymer was retained [42]. As a result, the effect of the lubrication which comes from the dendritic architecture of the HBP molecule was predominant. However, at low frequencies the slope of the G′ to the frequency was decreased in all samples compared to the RSF, and the G′ value slightly increased when 0.5 phr of HBP was added. These phenomena come from the abundant functional groups in the HBP molecule. When the entanglement of the polymer chain was released at low frequency, the unravelling of the entanglement was hindered by the hydrogen bonding among the PA 6, fillers, and the HBP molecules. A similar result was observed in Bhardwaj’s research [43]. This could be evidence that not only hydrogen bonding, but also lubrication, were functioning in the RSF-COOH composite system. 3.2. Morphology SEM microphotographs of the fractured surfaces of the composite materials after tensile testing are presented in Figure 3. In Figure 3a, without HBP, most of the HGMs are exposed to the fractured surface. However, when the HBP was added to the RSF (Figure 3b–d), the partially exposed and almost buried HGMs were observed, indicating that HBP increased the interfacial adhesion between polymer matrix and HGM. The enlarged microphotographs of the GFs are presented in Figure 3e–h. The GF surface of the neat RSF was smooth without attached PA 6 matrix. On the other hand, when HBP was added, the GF surface was covered with PA 6. On account of the enhanced interfacial adhesion of the polymer matrix to the fillers, which comes from the hydrogen bonding among the polymer matrix, fillers, and HBP, the compatibility of the fillers in the PA 6 matrix was increased, and the mechanical strength of the RSF-COOH composites could be enhanced compared to the neat RSF. It would be useful to discuss the fracture mechanism of the composite material to investigate the change of the mechanical properties of the composites with and without HBP addition. When the external load was applied to the composite, micro-cracks were generated near the filler surface due to weak interfacial adhesion with the polymer matrix [18]. Without HBP, when a high content of HGM was added, the sites of cracks increased; furthermore, the cracks propagated easily because there were neighboring cracks from other HGM particles. Since the strength of the matrix is larger than that of the interface between the HGM and polymer matrix [44], cracks on the surface of the HGM propagated easily. On the other hand, when HBP was added to the RSF composite, the filler-polymer adhesion increased due to the increased hydrogen bonding sites that came from the abundant functional groups of the HBP molecule. As a result, under the external load, the effect of the cracks on the surface of the HGMs decreased and the effect of the plastic deformation and yielding became predominant. Therefore, the mechanical strength of the RSF-COOH was higher than that of the neat RSF composite. 3.3. Crystallization Behavior The cooling curves and the DSC data of the neat PA 6, PA 6/HGM, and PA 6/GF composites at temperatures ranging from 205 to 180 °C are shown in Figure S5 and Table S1. The crystallization temperature of the PA 6/HGM 20 composite decreased compared to the neat PA 6. However, the change in crystallization temperature of the PA 6/HGM 5 and the PA 6/GF 5 samples was not significant. However, high content of HGM particles, which was associated with our RSF system, influenced the crystallization behavior significantly. The crystallization rate constant Zt decreased, and the t1/2 of the PA 6/HGM 20 increased. These phenomena reflect that the crystallization of the RSF without HBP was delayed since the HGM particles in the PA 6 matrix could act as the steric obstacle for the crystalline development of the PA 6 polymer [45]. The Tg data of the PA 6, RSF, and RSF-COOH samples are presented in Figure S6. The Tg of the samples decreased from 60.81 to 45.52 °C as the HGM and GF were introduced to the PA 6; this was due to the weak interfacial adhesion between the fillers and PA 6 [46]. However, when HBP was added to the RSF system, the Tg of the composites slightly increased from 45.52 to 46.70 °C. This indicates that HBP addition enhanced the interfacial adhesion of the fillers with the PA 6 matrix. Figure 4a presents the DSC thermograms of the neat RSF and RSF-COOH composites, and the DSC data are listed in Table 2. As can be seen in Table 2, the crystallization temperature gradually increased as the concentration of HBP increased. However, the crystallinity Xc increased as the filler content increased to 1.0 phr, and then decreased when the content of HBP further increased. A similar trend was observed in ZhanG′s study [47]. HBP can form hydrogen bonding with the PA 6 matrix and the filler surface, and the HBP molecules could act as the nucleating agent on the filler surface. When a low content of HBP was added to the composite (0–1.0 phr), crystallization of the PA 6 was accelerated by the increased amount of nuclei. As the HBP content was further increased beyond 1 phr, the growth of the crystal may be hindered by the excessive HBP molecules; as a result, the crystallinity was slightly reduced in RSF-COOH 2.0 compared to the RSF-COOH 1.0. The crystallization behavior of the RSF-COOH composites would affect the mechanical properties of the composites. The crystallization kinetics of syntactic foams in Figure S7 and Table S2 showed that the crystallization rate was slowed by the further addition of HGM. The degree of crystallinity of the RSF composites calculated by the Avrami equation is depicted in Figure 4b. As demonstrated in Table 3, t1/2 of the RSF-COOH composite decreased due to a higher crystallization rate constant as the content of HBP increased. HBP can be responsible for the crystallization rate, which was accelerated by not only enhanced chain mobility, but also by increased nucleation sites. 3.4. Thermogravimetric Analysis The extruded pellets were analyzed by TGA, which is presented in Figure 5. The residual char amount after the temperature reached 800 °C was 30 wt% in all composites, indicating the inorganic filler content in the RSF composites. The onset temperature of the thermal decomposition where the weight percent was 95% was increased from 408 to 415 °C when the HBP content increased from 0 to 0.75 phr. This result indicates that the thermal stability of the RSF composites was improved due to the enhanced interfacial adhesion between the filler and polymer matrix through the compatibilization which resulted from HBP [48]. When the HBP content was further increased to 2.0 phr, the decomposition occurred earlier at 403 °C. As a result of the lower thermal stability of HBP itself, which is presented in Figure S8, the excessive amount of HBP affects the thermal stability of the RSF-COOH composites where the content of HBP is higher than 1.0 phr. 3.5. Mechanical Properties and Specific Gravity of the Composite Figure S9a and Table S3 show that increasing weight fraction of HGMs from 0 to 20 wt% did affect the mechanical properties of the composite significantly. When the weight fraction of HGM reached to 20 wt%, the tensile strength was significantly decreased by 40.6% due to the poor dispersion of the filler and the weak interfacial adhesion of the filler to the polymer matrix (Figure S4). Figure 6 and Table 4 show the mechanical properties and the specific gravity of the PA 6, RSF control, and HBP containing RSF. The tensile strength increased by 24.3% in RSF-COOH 0.75 compared to the neat RSF. As a result of the abundant functional groups that can form hydrogen bonding, the strong interfacial adhesion between PA 6 polymers and fillers could enhance the tensile strength of the RSF-COOH composite. On the other hand, as the HBP content increased to 2.0 phr, tensile strength gradually decreased. It is interpreted that the physical property was weakened by the lubricating effect that comes from the dendritic structure of the HBP molecules. We can conclude that the optimal HBP content where the tensile strength is a maximum is 0.75–1.0 phr, and this indicates that the compatibility and the lubrication would be complementary at this content. The flexural test results of the composite are summarized in Figure 6b and Table 4. HBP had a positive effect on the flexural modulus and flexural strength. In RSF-COOH 1.0, compared to RSF-control, the flexural modulus increased from 4032 to 4424 MPa, and the flexural strength increased from 50 to 55 MPa. The increase in flexural strength is a result of the high interfacial adhesion of the HBP molecules. Furthermore, on account of the reduced filler breakage during the processing, which is summarized in Table 5, foam-core sandwich structure of the RSF-COOH composites could be formed more effectively than that with the neat RSF. Specific gravity data of the RSF samples are provided in Figure 6c. It was shown that the specific gravity continued to decrease as the content of HBP increased. This is because the hollow HGMs can be damaged not only by the high shear in the extrusion process, but also by the additional injection molding. HBP brings out economic feasibility through tribological advantage, resulting in a much lighter RSF composite due to reduced HGM breakage. HGM breakage was calculated by TGA and gas pycnometer analysis in Table 5 and Figure S11. HGM breakage of the neat RSF and RSF-COOH 2.0 was 9.14 and 2.84 vol%, respectively, which show good agreement with the tendency of the specific gravity in Figure 6c. These results can be supplementary evidence that the remarkable variation in shear stress, mentioned in Figure 3c, improved the internal friction of the composite. 4. Conclusions In this study, glass fiber-reinforced PA6 syntactic foam material was prepared with the addition of the carboxyl group-containing HBP for lightweight material applications. The morphological, rheological, and thermal properties of the composite material were characterized. It was revealed that HBP could increase mechanical properties, and could act as a rheological modifier simultaneously. The outcomes from the present study are summarized as follows:(1) In the rheological characterization, the complex viscosity and the shear stress of the RSF-COOH composites decreased across the entire frequency range compared to the neat RSF composite without HBP. The storage modulus and loss modulus tended to decrease with increasing content of HBP in the composite; however, the slope of the storage modulus at low frequency tended to decrease. These results are evidence that the lubricating effect due to the dendritic structure of HBP, in addition to hydrogen bonding, were functioning in the RSF-COOH composite at the same time. (2) The tensile strength and flexural modulus were increased by 24.3 and 9.7%, respectively, in RSF-COOH composite compared to the neat RSF. In the FE-SEM microphotographs, it was shown that the compatibility of the filler improved, and that filler-polymer adhesion enhanced when HBP was added. In addition, in DSC data, the crystallinity of the composite (Xc) increased to 22.54% with the addition of HBP in the composite. The enhanced compatibility of the filler with the polymer matrix, and crystallization behavior contributed to the increased mechanical strength of the RSF-COOH composite material. (3) As a result of the reduced shear stress of the RSF-COOH composite in the high shear-applied extrusion process, HGM breakage considerably decreased from 9.14 to 2.84%. As a result, the specific gravity of the composite significantly decreased from 0.948 to 0.917 when HBP was introduced to the RSF composite. The results show that HBP plays multiple roles in the RSF composite: modifying rheological properties, increasing mechanical properties, and reducing specific gravity. With these simultaneous effects in the RSF composite, HBP could be applied further in the lightweight materials field. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/polym14091915/s1: Figure S1: Twin-screw configuration representing extrusion process starting from left to right. HGMs and GFs are side-fed in the middle. Figure S2: DSC profile to figure out the effect of HBP contents within RSF samples on non-isothermal crystallization behavior. Data were collected from segment 6 on heating cycle to measure and calculate Tm, ∆Hf, and Xc. Segment 8 was implemented on cooling cycle to measure and calculate Tc, Tonset, ∆Hc, and ∆Hc*. Figure S3: FT-IR spectra of HBP. OH stretching in the carboxyl group is 2952 cm−1, and aliphatic O-H bending is 1427 cm−1. Aliphatic ester group of C-O stretching is 1191 cm−1, and aliphatic ether group of C-O stretching is 1149 cm−1. Figure S4: SEM microphotographs of syntactic foams on fractured surfaces after tensile test: PA 6/HGM 5 (a), PA 6/HGM 10 (b), PA 6/HGM 15 (c), and PA 6/HGM 20 (d). Figure S5: DSC thermograms of syntactic foams. The more the HGM was introduced, the lower the peak of crystallization temperature was found. Figure S6: DSC thermograms ranging from 20 to 100 °C of the PA 6 (a), RSF (b), RSF-COOH 0.5 (c), RSF-COOH 1.0 (d), and RSF-COOH 2.0 (e) for the glass transition temperature (Tg) evaluation. Tg of each sample is depicted in the plots. Figure S7: Plots of relative crystallinity (Vt) vs time for the non-isothermal crystallization of neat PA 6, syntactic foams with different HGM contents, and reinforced PA 6 composites. Figure S8: TGA thermograms of PA 6 and HBP. Figure S9: Tensile strength (a), flexural modulus (b), and specific gravity (c) of syntactic foams with various HGM contents. Figure S10: Equations for calculating HGM breakage. The density of HGM reaches 2.54 g/cm3 at 100% breakage. By exposing the pellets to 550 °C for 2 h to remove the matrix (PA 6), true densities of the residual inorganic ash consisting of HGMs and GFs were measured by gas pycnometer, which were 0.4365 and 2.4510 g/cm3, respectively. Figure S11: TGA thermograms of syntactic foams and a glass fiber-reinforced PA 6 composite. We determined actual inorganic filler contents represented by the embedded table. Table S1: DSC data for syntactic foams and a glass fiber reinforced PA 6 composite under non-isothermal crystallization. Table S2: Crystallization kinetic analysis of non-isothermal crystallization data for syntactic foams and a glass fiber-reinforced composite. Table S3: Comparison of the mechanical properties of neat PA 6, syntactic foams, and a glass fiber-reinforced PA 6 composite. Click here for additional data file. Author Contributions Conceptualization, Y.Q.; methodology, J.K., J.L.; validation, K.P., S.H. (Sosan Hwang); formal analysis, investigation, and writing—original draft preparation, J.K., J.L.; writing—review and editing, Y.Q., S.E.S.; supervision, S.E.S., Y.Q.; project administration, S.H. (Sanghyun Hong), S.L.; funding acquisition, S.E.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest Authors have no conflict to declare. Figure 1 Chemical structures of PA 6, HGM, GF, and HBP. Figure 2 Complex viscosity (a), shear stress (b), storage modulus (c), and loss modulus (d) of the neat PA6 and RSF composites with different HBP contents. Figure 3 SEM microphotographs of fractured surface of the composite samples after tensile testing: (a) RSF control, (b) RSF-COOH 0.5, (c) RSF-COOH 1.0, and (d) RSF-COOH 2.0. Enlarged microphotographs of the GFs which are in the (e) RSF control, (f) RSF-COOH 0.5, (g) RSF-COOH 1.0, and (h) RSF-COOH 2.0, respectively. Figure 4 DSC thermograms cooled at 10 °C/min (a) and plots of relative crystallinity (Vt) vs time (b) for non-isothermal crystallization of RSF composites with various HBP contents. Figure 5 Thermogravimetric analysis data for RSF containing various HBP contents. Inset: A close-up of the 420–470 °C region. Figure 6 Tensile strength (a), flexural modulus (b), and the specific gravity (c) of the RSF with various contents of HBP. polymers-14-01915-t001_Table 1 Table 1 Composition and identification details of prepared samples referred to as syntactic foams (SF), consisting of different PA 6, HGM, GF, and HBP contents. Sample Label PA 6 (wt%) HGM (wt%) GF (wt%) HBP (phr a) RSF 72 23 5 - RSF-COOH 0.5 71.6 23 5 0.5 RSF-COOH 0.75 71.5 23 5 0.75 RSF-COOH 1.0 71 23 5 1.0 RSF-COOH 2.0 70.6 23 5 2.0 a Parts per hundred of PA 6 resin. polymers-14-01915-t002_Table 2 Table 2 DSC data for RSF containing various HBP contents under non-isothermal crystallization. Sample Label Tm (°C) ∆Hf (J/g) Xc (%) Tc (°C) Tonset (°C) ∆Hc (J/g) ∆Hc* (J/g) RSF 221.3 34.68 20.00 190.8 195.1 40.98 56.70 RSF-COOH 0.5 220.8 35.00 20.40 191.3 195.4 41.16 57.57 RSF-COOH 1.0 221.1 38.39 22.54 191.7 195.7 43.30 61.01 RSF-COOH 2.0 221.0 37.34 21.86 192.4 196.2 42.36 59.51 polymers-14-01915-t003_Table 3 Table 3 Crystallization kinetic parameters of non-isothermal crystallization data for RSF containing various HBP contents. Sample Label n Zt Zc t1/2 (min) Adj. R-Square RSF 3.8 1.376 1.032 0.84 0.9997 RSF-COOH 0.5 4.1 1.337 1.029 0.85 0.9997 RSF-COOH 1.0 3.8 1.633 1.050 0.80 0.9997 RSF-COOH 2.0 3.9 1.972 1.070 0.76 0.9997 polymers-14-01915-t004_Table 4 Table 4 Comparison of the mechanical properties of neat PA 6 and RSF containing various HBP contents. Sample Code Specific Gravity Tensile Strength (MPa) Elongation (%) Flexural Modulus (MPa) Flexural Strength (MPa) PA 6 1.125 80.2 ± 2.6 13.6 ± 13.8 2843 ± 73 35.3 ± 0.9 RSF 0.948 58.8 ± 1.2 1.4 ± 0.2 4032 ± 16 50.0 ± 0.2 RSF-COOH 0.5 0.933 69.9 ± 2.2 1.4 ± 0.6 4273 ± 26 53.0 ± 0.3 RSF-COOH 0.75 0.932 73.1 ± 1.7 1.3 ± 0.3 4386 ± 13 54.6 ± 0.2 RSF-COOH 1.0 0.924 72.5 ± 1.5 1.8 ± 0.6 4424 ± 0 54.9 ± 0 RSF-COOH 2.0 0.917 70.7 ± 1.5 1.3 ± 0.2 4423 ± 36 54.6 ± 0.4 polymers-14-01915-t005_Table 5 Table 5 HGM breakage measurement results of each RSF composite containing various HBP contents. Sample Code Ash Density a (g/cm3) Residual HGM Density (g/cm3) HGM Breakage (vol%) RSF 0.5829 0.4772 9.14 RSF-COOH 0.5 0.5590 0.4596 6.07 RSF-COOH 1.0 0.5463 0.4504 3.73 RSF-COOH 2.0 0.5431 0.4470 2.84 a Measured by exposing the pellets to 550 °C for 2 h to remove the matrix (PA 6). The true density of the residual inorganic ashes consisting of HGMs and GFs was measured by gas pycnometer. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Regulations for Emissions from Vehicles and Engines Available online: https://www.epa.gov/regulations-emissions-vehicles-and-engines (accessed on 14 February 2022) 2. Sun Q. Zhou G. Meng Z. Jain M. Su X. An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications Compos. Sci. Technol. 2021 202 108560 10.1016/j.compscitech.2020.108560 33343054 3. Mallick P.K. Materials, design and manufacturing for lightweight vehicles Woodhead Publishing Sawston, UK 2020 4. Graziano A. Garcia C. Jaffer S. Tjong J. Yang W. Sain M. Functionally tuned nanolayered graphene as reinforcement of polyethylene nanocomposites for lightweight transportation industry Carbon 2020 169 99 110 10.1016/j.carbon.2020.07.040 5. Du Y. Keller T. Song C. Wu L. Xiong J. Origami-inspired carbon fiber-reinforced composite sandwich materials—Fabrication and mechanical behavior Compos. Sci. Technol. 2021 205 108667 10.1016/j.compscitech.2021.108667 6. Ozden S. Dutta N.S. Randazzo K. Tsafack T. Arnold C.B. Priestley R.D. Interfacial engineering to tailor the properties of multifunctional ultralight weight hBN-polymer composite aerogels ACS Appl. Mater. Interf. 2021 13 13620 13628 10.1021/acsami.0c16866 33689272 7. Choi D. Kil H.-S. Lee S. Fabrication of low-cost carbon fibers using economical precursors and advanced processing technologies Carbon 2019 142 610 649 10.1016/j.carbon.2018.10.028 8. Zhang X. Wang P. Zhou Y. Li X. Yang E.-H. Yu T.X. Yang J. The effect of strain rate and filler volume fraction on the mechanical properties of hollow glass microsphere modified polymer Compos. Part B Eng. 2016 101 53 63 10.1016/j.compositesb.2016.06.079 9. Cosse R.L. Araújo F.H. Pinto F.A.N.C. de Carvalho L.H. de Morais A.C.L. Barbosa R. Alves T.S. Effects of the type of processing on thermal, morphological and acoustic properties of syntactic foams Compos. Part B Eng. 2019 173 106933 10.1016/j.compositesb.2019.106933 10. Jayavardhan M.L. Doddamani M. Quasi-static compressive response of compression molded glass microballoon/HDPE syntactic foam Compos. Part B Eng. 2018 149 165 177 10.1016/j.compositesb.2018.04.039 11. Jayavardhan M.L. Bharath Kumar B.R. Doddamani M. Singh A.K. Zeltmann S.E. Gupta N. Development of glass microballoon/HDPE syntactic foams by compression molding Compos. Part B Eng. 2017 130 119 131 10.1016/j.compositesb.2017.07.037 12. Zhang L. Ma J. Effect of coupling agent on mechanical properties of hollow carbon microsphere/phenolic resin syntactic foam Compos. Sci. Technol. 2010 70 1265 1271 10.1016/j.compscitech.2010.03.016 13. Tagliavia G. Porfiri M. Gupta N. Analysis of flexural properties of hollow-particle filled composites Compos. Part B Eng. 2010 41 86 93 10.1016/j.compositesb.2009.03.004 14. Wang L. Yang X. Zhang J. Zhang C. He L. The compressive properties of expandable microspheres/epoxy foams Compos. Part B Eng. 2014 56 724 732 10.1016/j.compositesb.2013.09.030 15. Gupta N. Zeltmann S.E. Shunmugasamy V.C. Pinisetty D. Applications of polymer matrix syntactic foams Jom 2013 66 245 254 10.1007/s11837-013-0796-8 16. Swetha C. Kumar R. Quasi-static uni-axial compression behaviour of hollow glass microspheres/epoxy based syntactic foams Mater. Des. 2011 32 4152 4163 10.1016/j.matdes.2011.04.058 17. He S. Carolan D. Fergusson A. Taylor A.C. Toughening epoxy syntactic foams with milled carbon fibres: Mechanical properties and toughening mechanisms Mater. Des. 2019 169 107654 10.1016/j.matdes.2019.107654 18. Gogoi R. Manik G. Arun B. High specific strength hybrid polypropylene composites using carbon fibre and hollow glass microspheres: Development, characterization and comparison with empirical models Compos. Part B Eng. 2019 173 106875 10.1016/j.compositesb.2019.05.086 19. Kumar N. Mireja S. Khandelwal V. Arun B. Manik G. Light-weight high-strength hollow glass microspheres and bamboo fiber based hybrid polypropylene composite: A strength analysis and morphological study Compos. Part B Eng. 2017 109 277 285 10.1016/j.compositesb.2016.10.052 20. Hu Y. Mei R. An Z. Zhang J. Silicon rubber/hollow glass microsphere composites: Influence of broken hollow glass microsphere on mechanical and thermal insulation property Compos. Sci. Technol. 2013 79 64 69 10.1016/j.compscitech.2013.02.015 21. Lin C.-A. Ku T.-H. Shear and elongational flow properties of thermoplastic polyvinyl alcohol melts with different plasticizer contents and degrees of polymerization J. Mater. Process. Technol. 2008 200 331 338 10.1016/j.jmatprotec.2007.08.057 22. Wu C. McGinity J.W. Influence of methylparaben as a solid-state plasticizer on the physicochemical properties of Eudragit® RS PO hot-melt extrudates Eur. J. Pharm. Biopharm. 2003 56 95 100 10.1016/S0939-6411(03)00035-3 12837487 23. Belous A. Tchoudakov R. Tzur A. Narkis M. Alperstein D. Development and characterization of plasticized polyamides by fluid and solid plasticizers Polym. Adv. Technol. 2012 23 938 945 10.1002/pat.1988 24. Wang J. Ye Z. Zhu S. Topology-engineered hyperbranched high-molecular-weight polyethylenes as lubricant viscosity-index improvers of high shear stability Ind. Eng. Chem. Res. 2007 46 1174 1178 10.1021/ie0613624 25. Wang F.C.-Y. Buzanowski W.C. Polymer additive analysis by pyrolysis–gas chromatography J. Chromatogr. A 2000 891 313 324 10.1016/S0021-9673(00)00648-8 11043792 26. Bettini S.H. de Miranda Josefovich M.P. Munoz P.A. Lotti C. Mattoso L.H. Effect of lubricant on mechanical and rheological properties of compatibilized PP/sawdust composites Carbohydr. Polym. 2013 94 800 806 10.1016/j.carbpol.2013.01.080 23544635 27. Jacobsen S. Fritz H.-G. Plasticizing polylactide—the effect of different plasticizers on the mechanical properties Polym. Eng. Sci. 1999 39 1303 1310 10.1002/pen.11517 28. Cosimbescu L. Robinson J.W. Zhou Y. Qu J. Dual functional star polymers for lubricants RSC Adv. 2016 6 86259 86268 10.1039/C6RA17461B 29. Robinson J.W. Zhou Y. Bhattacharya P. Erck R. Qu J. Bays J.T. Cosimbescu L. Probing the molecular design of hyper-branched aryl polyesters towards lubricant applications Sci. Rep. 2016 6 18624 10.1038/srep18624 26727881 30. Zheng Y. Li S. Weng Z. Gao C. Hyperbranched polymers: Advances from synthesis to applications Chem. Soc. Rev. 2015 44 4091 4130 10.1039/C4CS00528G 25902871 31. Hawker C.J. Farrington P.J. Mackay M.E. Wooley K.L. Frechet J.M. Molecular ball bearings: The unusual melt viscosity behavior of dendritic macromolecules J. Am. Chem. Soc. 1995 117 4409 4410 10.1021/ja00120a028 32. Chen L. Qin Y. Wang X. Li Y. Zhao X. Wang F. Toughening of poly(propylene carbonate) by hyperbranched poly(ester-amide) via hydrogen bonding interaction Polym. Inter. 2011 60 1697 1704 10.1002/pi.3132 33. Wu C. Huang X. Wang G. Wu X. Yang K. Li S. Jiang P. Hyperbranched-polymer functionalization of graphene sheets for enhanced mechanical and dielectric properties of polyurethane composites J. Mater. Chem. 2012 22 7010 7019 10.1039/c2jm16901k 34. Gu W. Liu X. Gao Q. Gong S. Li J. Shi S.Q. Multiple hydrogen bonding enables strong, tough, and recyclable soy protein films ACS Sustain. Chem. Eng. 2020 8 7680 7689 10.1021/acssuschemeng.0c01333 35. Peng Q. Li Y. He X. Lv H. Hu P. Shang Y. Wang C. Wang R. Sritharan T. Du S. Interfacial enhancement of carbon fiber composites by poly(amido amine) functionalization Compos. Sci. Technol. 2013 74 37 42 10.1016/j.compscitech.2012.10.005 36. Avrami M. Granulation, Phase change, and microstructure kinetics of phase change. III J. Chem. Phy. 1941 9 177 184 10.1063/1.1750872 37. Avrami M. Kinetics of phase change. I General theory J. Chem. Phy. 1939 7 1103 1112 10.1063/1.1750380 38. Avrami M. Kinetics of phase change. II Transformation-Time relations for random distribution of nuclei J. Chem. Phy. 1940 8 212 224 10.1063/1.1750631 39. Fornes T.D. Paul D.R. Crystallization behavior of nylon 6 nanocomposites Polymer 2003 44 3945 3961 10.1016/S0032-3861(03)00344-6 40. Fan Z. Jaehnichen K. Desbois P. Haeussler L. Vogel R. Voit B. Blends of different linear polyamides with hyperbranched aromatic AB2 and A2+ B3 polyesters J. Polym. Sci. Part A Polym. Chem. 2009 47 3558 3572 10.1002/pola.23440 41. Kang D. Hwang S.W. Jung B.N. Shim J.K. Effect of hollow glass microsphere (HGM) on the dispersion state of single-walled carbon nanotube (SWNT) Compos. Part B Eng. 2017 117 35 42 10.1016/j.compositesb.2017.02.038 42. Goldansaz H. Goharpey F. Afshar-Taromi F. Kim I. Stadler F.J. van Ruymbeke E. Karimkhani V. Anomalous Rheological Behavior of Dendritic Nanoparticle/Linear Polymer Nanocomposites Macromolecules 2015 48 3368 3375 10.1021/acs.macromol.5b00390 43. Bhardwaj R. Mohanty A.K. Modification of brittle polylactide by novel hyperbranched polymer-based nanostructures Biomacromolecules 2007 8 2476 2484 10.1021/bm070367x 17605464 44. Carolan D. Mayall A. Dear J.P. Fergusson A.D. Micromechanical modelling of syntactic foam Compos. Part B Eng. 2020 183 107701 10.1016/j.compositesb.2019.107701 45. Privalko V. Kawai T. Lipalov Y.S. Crystallization of filled nylon 6 III. Non-isothermal crystallization Colloid Polym. Sci. 1979 257 1042 1048 10.1007/BF01761115 46. Jang K.-S. Low-density polycarbonate composites with robust hollow glass microspheres by tailorable processing variables Polym. Test. 2020 84 106408 10.1016/j.polymertesting.2020.106408 47. Zhang J.-F. Sun X. Mechanical properties and crystallization behavior of poly(lactic acid) blended with dendritic hyperbranched polymer Polym. Inter. 2004 53 716 722 10.1002/pi.1457 48. Lu S. Li S. Yu J. Guo D. Ling R. Huang B. The effect of hyperbranched polymer lubricant as a compatibilizer on the structure and properties of lignin/polypropylene composites Wood Mater. Sci. Eng. 2013 8 159 165 10.1080/17480272.2013.769464

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==== Front Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells11091585 cells-11-01585 Article FKBP51, AmotL2 and IQGAP1 Involvement in Cilastatin Prevention of Cisplatin-Induced Tubular Nephrotoxicity in Rats González-Fernández Rebeca 1 González-Nicolás María Ángeles 2 Morales Manuel 3 https://orcid.org/0000-0001-5177-1188 Ávila Julio 1 Lázaro Alberto 24*† https://orcid.org/0000-0002-2220-5774 Martín-Vasallo Pablo 1*† Dihazi Hassan Academic Editor 1 Laboratorio de Biología del Desarrollo, UD de Bioquímica y Biología Molecular and Centro de, Investigaciones Biomédicas de Canarias (CIBICAN), Universidad de La Laguna, Av. Astrofísico Sánchez s/n., 38206 La Laguna, Spain; refernan@ull.edu.es (R.G.-F.); javila@ull.edu.es (J.Á.) 2 Renal Physiopathology Laboratory, Department of Nephrology, Instituto de Investigación Sanitaria Gregorio Marañón, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain; rengac@yahoo.es 3 Department of Medical Oncology, Nuestra Señora de Candelaria University Hospital, 38010 Santa Cruz de Tenerife, Spain; mmoraleg@ull.edu.es 4 Department of Physiology, School of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain * Correspondence: alberlaz@ucm.es (A.L.); pmartin@ull.edu.es (P.M.-V.); Tel.: +34-922-318358 (P.M.-V.) † These authors contributed equally to this work. 09 5 2022 5 2022 11 9 158501 4 2022 06 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The immunophilin FKBP51, the angiomotin AmotL2, and the scaffoldin IQGAP1 are overexpressed in many types of cancer, with the highest increase in leucocytes from patients undergoing oxaliplatin chemotherapy. Inflammation is involved in the pathogenesis of nephrotoxicity induced by platinum analogs. Cilastatin prevents renal damage caused by cisplatin. This functional and confocal microscopy study shows the renal focal-segmental expression of TNFα after cisplatin administration in rats, predominantly of tubular localization and mostly prevented by co-administration of cilastatin. FKBP51, AmotL2 and IQGAP1 protein expression increases slightly with cilastatin administration and to a much higher extent with cisplatin, in a cellular- and subcellular-specific manner. Kidney tubule cells expressing FKBP51 show either very low or no expression of TNFα, while cells expressing TNFα have low levels of FKBP51. AmotL2 and TNFα seem to colocalize and their expression is increased in tubular cells. IQGAP1 fluorescence increases with cilastatin, cisplatin and joint cilastatin-cisplatin treatment, and does not correlate with TNFα expression or localization. These data suggest a role for FKBP51, AmotL2 and IQGAP1 in cisplatin toxicity in kidney tubules and in the protective effect of cilastatin through inhibition of dehydropeptidase-I. FKBP51 IQGAP1 AmotL2 cisplatin toxicity Spanish Ministry of Economy and Competitiveness Instituto de Salud Carlos III-Fondo de Investigación en SaludPI17/00276 PI20/01577 Fondo Europeo de Desarrollo Regional (FEDER)CI21/00111 ISCIII-RICORS2040RD21/0005/0029 Comunidad de MadridS2017-BMD-3686 Fundación SenefroSENEFRO 18/01 Fundación Mutua Madrileña2020 Gobierno de CanariasProID2020010073 This research was funded by Spanish Ministry of Economy and Competitiveness Instituto de Salud Carlos III-Fondo de Investigación en Salud (grant numbers: PI17/00276, PI20/01577 and CI21/00111 cofinanced by Fondo Europeo de Desarrollo Regional (FEDER) Funds from the European Commission, “A way of making Europe”), ISCIII-RICORS2040 (Kidney Disease, grant number RD21/0005/0029), Comunidad de Madrid (grant number S2017-BMD-3686 (CIFRA2-CM)), Fundación Senefro (Nephrology research grant SENEFRO 18/01), Fundación Mutua Madrileña (research grant 2020) to A.L., Gobierno de Canarias (cofounded by FEDER), grant number ProID2020010073), and grant Proyecto Puente al Plan Estatal 2018 by Universidad de La Laguna, to J.A., and grant number OA20/089 from the Fundación Mapfre Guanarteme, Canary Islands, Spain to M.M. ==== Body pmc1. Introduction Cisplatin is one of the most potent antineoplastics used in the treatment of various types of cancer; however, approximately one-third of patients undergoing cisplatin treatment experience acute kidney injury, with decreased glomerular filtration rate (GFR), increased serum creatinine and blood urea nitrogen (BUN), and electrolyte imbalance [1,2,3,4]. This cisplatin-induced nephrotoxicity limits the clinical use of the drug [1,4,5]. A wide body of experimental evidence indicates that cilastatin, a specific inhibitor of renal dehydropeptidase-I (DHP-I), can protect proximal tubular epithelial cells from the damage caused by cisplatin, without compromising the drug’s therapeutic effect on cancer cells [1,2,3,4,5,6,7,8]. This study aims to shed light on the mechanisms by which cilastatin protects kidney cells from cisplatin-induced toxicity. In particular, we looked at three proteins whose expression is significantly altered in leucocytes after platinum-derivative chemotherapy, namely [7] FKBP51 (FK506, tacrolimus-binding protein 51), AmotL2 (angiomotin-like 2) and IQmotif-containing GTPase-activating protein 1 (IQGAP1); these three proteins are involved in the regulation of proteins acting in a variety of processes, including cell growth, tumorigenesis, inflammation, immunity, cell plasticity and differentiation, and many others [9,10,11]. String analysis [12] and text mining show predicted and experimentally demonstrated interactions between FKBP51, AmotL2, and IQGAP1 [13]. FKBP51 is an immunophilin with peptidyl-prolyl cis-trans isomerase (rotamase) activity which acts as a co-chaperone associated with heat shock protein 90 (Hsp90), heat shock protein 70 (Hsp70) and p23; it plays a role in steroid receptor signaling, translocating from the cytosol to either the mitochondria or nucleus, where it modulates pathways involving protein kinase B (Akt), protein kinase A (PKA), nuclear factor-kappa B (NF-κB), transforming growth factor (TGF) and tumor necrosis factor alpha (TNFα) [14,15,16,17,18,19,20]. FKBP51 is abundantly expressed in tumours [21,22] and is involved in antiapoptotic processes in cancer cells [23]. Translocation of FKBP51 to the nucleus appears to be related to decreased cyclin D expression in the cell cycle [21]; also found in the nucleus is FKBP51s, an alternatively spliced isoform of FKBP51, which is induced by the co-inhibitory immune checkpoint PD-L1/PD1 [23]. AmotL2 is an angiostatin binding protein and member of the motin family [15]; it promotes vascular tube formation by regulating cell-cell interactions and also plays a role in maintaining apical-basal polarity. AmotL2 modulates signaling pathways such as the Hsp70-Bag3 pathway, in which it scaffolds the LATS1 and YAP proteins of the Hippo pathway [24]; it has also been shown to be involved in the epithelial to mesenchymal transition of a number of cancers [15]. IQGAP1 is an extraordinarily versatile scaffold protein that regulates numerous cellular processes and signaling pathways; it plays a role in complex cell functions such as tight junction formation, tissue and organ physiology, the cell cycle, angiogenesis, cell migration, cytoskeletal organization, and many others [25,26]. In the kidney, it regulates intercellular junctions that mediate glomerular filtration [25,27] and is involved in cytoskeleton formation and tubulogenesis [28,29]. For further information regarding protein structure, functional domains and other properties, see references [16] for FKBP51, [30] for Amotl2 and [31,32] for IQGAP1. The aims of this study were to determine the precise localization of cisplatin-induced inflammation in the kidney, to elucidate whether FKBP51, Amotl2 and IQGAP1 play a role in this inflammation, and to determine the effects of cilastatin on the expression of these proteins and their cellular and subcellular localization. 2. Materials and Methods 2.1. Animals Wistar Han (WKY, Rattus norvegicus) 7-week-old male rats, 250–270 g weight (Charles River Laboratories, Barcelona, Spain), were housed under controlled light (12 h light/dark cycle), temperature (23 ± 1 °C), and humidity (60 ± 10%), with free access to food consisting of Standarddiets, Altromin® (Altromin Spezialfutter GmbH & Co, Lage, Germany) and tap water. The animals’ weight was checked before the experiment and just before slaughter. The study was approved by the Institutional Board for Animal Experiments of the Gregorio Marañón Hospital (registration code 07-2008) and animals were handled at all times according to legal regulations stipulated by RD 118/2021, of February 23, on the protection of animals used for experimental scientific purposes. 2.2. Drugs Crystalline cilastatin was obtained from Merck Sharp and Dohme S.A. (Madrid, Spain) and cisplatin from Pharmacia (Barcelona, Spain). The vehicle for both drugs was normal 0.9% saline. 2.3. Experimental Protocols Experiments were performed using 24 animals, randomized into 4 groups: untreated control rats (n = 6); cilastatin-treated rats (n = 6); cisplatin-treated rats (n = 6); and cilastatin-protected cisplatin-treated rats (n = 6). The animals were treated as follows:- Cilastatin protected cisplatin-treated rats: Cisplatin was administered by intraperitoneal (IP) injection, as a single dose of 5 mg/kg body weight (bw). Cilastatin was administered IP at 75 mg/kg bw just before the time of cisplatin administration, and then every 12 h until the time of slaughter. - Cisplatin-treated rats: Cisplatin was administered IP as a single dose of 5 mg/kg bw. Saline was administered IP in the same volume as cilastatin-treated groups just before the time of cisplatin administration, and then every 12 h until the time of slaughter. - Cilastatin-treated rats: Saline was administered IP in the same volume as the cisplatin-treated groups. Cilastatin was administered IP at 75 mg/kg bw just before the time of saline administration, and then every 12 h until the time of slaughter. - Control rats: saline was administered IP in the same volumes and regimens as in the cilastatin- and/or cisplatin-treated groups. The cisplatin or saline injections were given in the same manner and volume (1 mL/100 g). The first dose of cilastatin was given just before the cisplatin injection. Saline (0.25 mL/100 g) was administered in place of cilastatin in the other groups. The dose and administration period of cisplatin was selected based on the proven effectiveness of the drug in inducing nephrotoxicity [1,33,34,35]. The dose of cilastatin was based on previous experience [1,36], which had shown that imipenem/cilastatin reduced Cyclosporin A (CsA)-induced nephrotoxicity. The urine from each animal was collected over the 24 h period before slaughter and the volume was measured. Five days after the first injection, all animals were anaesthetized with ketamine (10 mg/kg) and diazepam (4 mg/kg) and killed by exsanguination. Total blood samples were collected by insertion of a cannula into the abdominal aorta, and serum was separated for biochemical analysis. Kidneys were perfused with cold saline and quickly removed. Kidney samples were fixed in 4% paraformaldehyde (24 h) and paraffin-embedded. 2.4. Renal Function Monitoring Serum and urine creatinine concentrations and Na+ and BUN levels were measured automatically using the Dimension RxL autoanalyzer (Dade-Behring, Siemens, Eschborn, Germany) in accordance wth the manufacturer’s recommendations. The GFR was estimated based on the creatinine clearance rate. Fractional excretion of sodium was calculated as: EFNa+ = ([Na + urine]/[Na+ serum]) × ([Creatinine plasma]/[Creatinine urine]) × 100. The fractional excretion of water was calculated using: EFH2O = (urine volume/glomerular filtration rate) × 100. 2.5. Renal Histopathological Studies For light microscopy, paraffin-embedded cortex and medulla renal sections (4 µm thick) were stained with hematoxylin-eosin (H-E) (Sigma-Aldrich, St Louis, MO, USA). The kidney injury score was calculated using a previously described semiquantitative index [37]. Briefly, tubular damage scoring was defined as the blebbing of apical membranes, tubular cast formation, epithelial necrosis, tubular vacuolization and the presence of mitotic nuclei. Morphometric examination and scoring were performed by observers blinded to the animals’ treatment condition, using the following semiquantitative index: 0 points: no damage; 1 point: damage from 0 to 25% of the sample; 2 points: damage from 25 to 50% of the sample; 3 points: damage from 50 to 75% of the sample; 4 points: damage higher than 75% of the sample. The injury score was calculated as the sum of this semiquantitative assessment of tubular injury. Samples were examined with an Olympus BX-50 microscope (Olympus, Tokyo, Japan). 2.6. Western Blot Analysis Western blotting was performed as previously described [36]. In brief, renal cortex protein extracts (50 µg) were assayed by electrophoresis and separated on commercial Precast TGX gels (Bio-Rad, Hercules, CA, USA) between 10% and 15% under reducing conditions. Subsequently, they were transferred by Transfer Pack, Midi Format, 0.2 μm nitrocellulose (Bio-Rad) in transfer buffer [Tris 48 mM pH 8.8, 39 mM glycine, 0.037% SDS and 20% methanol (vol/vol)] using the Trans-Blot® TurboTM Transfer System (Bio-Rad). The membranes were blocked with 4% skim milk powder in phosphate-buffered saline (PBS)-Tween 20 0.1% for 1 h and incubated overnight at 4 °C with mouse anti-human RelA/NFΚB p65 monoclonal antibody, 1:500 (112A1021 Novus Biologicals, Bio-Techne R&D Systems, S.L.U., Madrid, Spain). As an internal control of the technique to verify equal protein loading, the membranes were also incubated with a mouse anti β-actin monoclonal antibody, 1:60,000 (Sigma Aldrich, Merck Life Science S.L.U., Madrid, Spain). The binding of the antibodies to both proteins was detected by peroxidase-conjugated anti-mouse IgG at 1:3000 (GE Healthcare, Buckinghamshire, UK) and identified by chemiluminescence with the Amersham™ ECL™ Prime Kit (GE Healthcare), using the Alliance 4.7 developer (Uvitec, Cambridge, UK). Signal quantifications were carried out with the image analysis program Image J (Image Processing and Analysis in Java). The results were expressed in arbitrary densitometry units. 2.7. Immunohistochemistry Four microns thick, 4% paraformaldehyde-fixed paraffin-embedded tissue sections were deparaffinized in xylene and hydrated in a graded series of alcohol baths. Heat-induced epitope retrieval was achieved by heating samples in sodium citrate buffer (pH 6.0) at 120 °C for 10 min in an autoclave. Non-specific sites were blocked with 5% bovine serum albumin in Tris-buffered saline (TBS) for 1 h at room temperature, then double immunofluorescence simultaneous staining was performed. Tissue sections were incubated overnight at 4 °C with mouse monoclonal anti-TNFα (52B83, dilution 1:150; #sc- 52746 Santa Cruz Biotechnology Inc., Dallas, TX, USA) and either rabbit polyclonal anti-AmotL2 (dilution 1:50; #LS-C178611; LifeSpan BioSciences, Seattle, WA, USA), rabbit polyclonal anti-FKBP51 (dilution 1:50; #ab46002; Abcam, Cam-bridge, UK) or rabbit polyclonal anti-human-IQGAP-1 (dilution 1:250; #ABT186 EMD; Millipore, Billerica, MA, USA). Samples incubated without primary antibodies were used as a negative control. Slides were incubated for 1 h at room temperature in the dark with a mixture of two secondary antibodies raised in different species and conjugated to different fluorochromes: fluorescein isothiocyanate (FITC)-conjugated goat polyclonal antibody against rabbit IgG (dilution 1:200; #F9887; Sigma-Aldrich, Saint Louis, MO, USA) and goat polyclonal antibody against mouse IgG DyLight 650 (dilution 1:100; #ab97018; Abcam). Slides were mounted with ProLong®Diamond Anti-fade Mountant with DAPI (Molecular Probes by Life technologies) to visualize cell nuclei. Slides were analyzed using a Leica SP8 confocal microscope (Leica Microsystems, Wetzlar, Germany). 2.8. Image Analysis and Statistics Three independent observers evaluated the specimens blindly. For H-E samples, observers evaluated 5 samples per rat and 15 to 20 fields per sample at 20× magnification. For confocal microscopy images (40× magnification), staining intensities were graded as absent (–), faint (+), moderate (++), or strong (+++). These cut-offs were established by consensus between investigators following an initial survey of all blindly coded sections. In cases where scoring data differed by more than one unit, the observers re-evaluated the sections to reach a consensus. In other cases, means were calculated. Observers evaluated between 20 and 50 fields per sample. All images were captured at the same magnification (40×) and with the same levels of contrast and brightness, scoring them as absent (–), faint (+), moderate (++), or strong (+++). Statistical analysis was carried out using SPSS (version 25 for Windows; IBM Corp., Armonk, NY, USA). For the analysis, – was quantified as 0, + as 1, ++ as 2, and +++ as 3. A dependence test (chi-square) was performed between the staining levels of each group of cells, and non-parametric techniques (median test and Kruskall–Wallis test) were used to analyze significant differences in the distribution of staining levels with respect to cell type. Statistics for quantitative variables in Table 1, H-E histology analysis and western blot experiments were organized as mean ± standard error of the mean (SEM). Analysis of variance (ANOVA) was performed for normally distributed continuous variables, with the least significant difference test as a post hoc approach to determine specific group differences. Statistically significant differences were accepted for bilateral α values when p < 0.05. 3. Results 3.1. Cilastatin Improves Cisplatin-Induced Nephrotoxicity Table 1 shows the effects of cisplatin and cilastatin administration on biochemical indicators of renal function. As expected, cisplatin-induced renal damage, characterized by increased serum creatinine, BUN levels, EFNa + and EFH2O, and decreased GFR compared with the control group. Cilastatin treatment partially or totally reversed these effects. Cisplatin caused polyuria in the animals, and although cilastatin appeared to decrease urine volume, this change was not statistically significant (Table 1). Administration of cilastatin alone had no effect on the parameters studied. 3.2. Cilastatin Prevents Histopathological Damage Induced by Cisplatin Administration H-E stained kidney sections from rats undergoing cisplatin treatment showed intratubular protein casts (a marker of damage) in 30 to 50% of tubules, depending on the field, with p < 0.005 compared to control (Figure 1, panel A). Samples from cilastatin-treated and cilastatin-protected cisplatin-treated rats presented an apparently normal renal morphology pattern. Figure 1, panel B shows the semiquantitative tubular damage score. 3.3. Cilastatin Diminishes Cisplatin-Induced Inflammatory NF-κB Upregulation Western blots of protein extracts from the rats’ renal cortex showed a 20 to 25% increase in expression of the p65 subunit of NF-κB after cilastatin treatment (75 mg/kg bw IP every twelve hours), and a 3 to 4-fold increase after cisplatin treatment (5 mg/kg bw IP in a single dose). Coadministration of cilastatin with cisplatin diminished cisplatin-induced inflammatory NF-κB upregulation by 51–64%. A representative western blot of the p65 subunit of NF-κB in renal cortex is shown in Figure 2, panel A. Panel B shows densitometric analysis of the p65 subunit western blots (p < 0.03 vs. all groups). 3.4. Focal and Segmental Localization of TNFα Expression Elicited by Cisplatin in Rat Kidney Tubules Renal tubules of control and cilastatin-treated rats showed homogeneous basal expression of TNFα, with a few isolated tubular cells (<1/1000) showing higher TNFα-specific fluorescence. Immunostaining for TNFα in tubules of the cisplatin (CisPt) treated group was heterogeneous, only present in some tubules grouped in foci (white arrows). These made up 5–10% of the total sectioned tubules per field. Some TNFα+ tubules showed immunofluorescence only in a region/segment of the tubule (arrowheads). TNFα-negative cells within TNFα+ tubules range from one cell to 5 or 6. Few immunolocalization signals were seen for TNFα in cilastatin-protected cisplatin-treated rat kidneys, 5–6 fold higher than control samples (Figure 3, CisPt-CIL panel, white arrows). 3.5. Expression of FKBP51 in Cilastatin-Protected Cisplatin-Treated Rat Kidney Tubular cells of normal rat kidney (Figure 4, Control panel) showed basal low-intensity immunostaining levels for TNFα and FKBP51 in cytosol. Small areas presented higher TNFα immunofluorescence in the outer glomerular capsule cells (white arrows). Some tubule cells presented more intense FKBP51 perinuclear fluorescence (yellow arrows, where yellow arrowheads point to incidental physiological cell blebbing). Cilastatin-treated rat kidney tubule cells showed immunostaining for TNFα and FKBP51 very similar in localization and intensity to that of controls. Yellow arrowheads in the CIL panels in Figure 4 point to some cell blebbing at the same levels of incidence as in the control group. The CisPt panels of Figure 4 show kidney tubule cells of cisplatin-treated rats with a high level of TNFα-specific immunofluorescence in some tubules (foci), in the cytosol of most tubule cells (white arrows) and at a lesser intensity in the cytosol of some other cells within the same tubules (arrowheads). Most tubules showed a low-level signal, though slightly brighter than controls, and some TNFα+ tubules presented abundant cellular blebbing (arrowhead). See also Figure 6, CisPt panel, where cell blebbing is more prominent and abundant within the same field. FKBP51-specific immunofluorescence presented two well-differentiated intensity levels: a low level in low TNFα-signal tubules and a higher intensity in the high TNFα-signal tubules. Nuclei showed a multi-dot fluorescence pattern (red arrow). Kidney tubule cells of cilastatin-protected cisplatin-treated rats (CisPt + CIL) had a homogeneous fluorescence pattern for both TNFα and FKBP51. TNFα was located in cytoplasm and at a very similar level to control rats, while FKBP51 was higher in both nuclei and cytosol, being more prominent in nuclei (white arrows in Figure 4, CisPt + CIL panels). In general, low TNFα fluorescence signals were found in kidney glomeruli from all experimental conditions. Low FKBP51 signals were observed in control, CIL and CisPt groups, while a clear FKBP51 signal was observed in glomerular cells (star) and capsule cells (red arrow) in the CisPt + CIL group. A significant decrease in the number of blebbing cells in this group versus the cisplatin-treated group is also observed (Figure 4, Figure 5 and Figure 6), at a ratio of 5.5:1 CisPt:CisPt + Cil (p > 0.05). 3.6. Expression of AmotL2 in Cisplatin-Treated and Cilastatin-Protected Rat Kidney The cytosol of kidney tubule cells showed medium intensity, homogeneously distributed AmotL2-specific staining (bold white arrows, Control panel, Figure 5). In some cells, immunofluorescence is most prominent around nuclei (thin white arrows). Some cells of the outer glomerular capsule showed high staining intensity for AmotL2 (white arrowheads). Glomerular cells showed low AmotL2 immunostaining (star). Tubular cells of cilastatin-treated rats (CIL panels, Figure 5) presented a homogeneous AmotL2 signal with similar localization to controls, but at a slightly but definitely increased intensity. AmotL2 staining was more intense around the nuclei of some cells, and in most nuclei appeared in a dot-like fluorescence pattern. Immunostaining for TNFα and AmotL2 was seen in the luminal side of endothelial cells of medium-sized vessels (red arrows, CIL panels, Figure 5). AmotL2/TNFα highly positive cells were found in some tubule cells of cisplatin-treated rats (bold white arrows, CisPt panels, Figure 5). Thin white arrows point to some other cells within the same tubules which show a much lower staining intensity. In both cases, staining intensity was higher at the apical brush border than in the cytosol. AmotL2/TNFα positive cells were found in the outer glomerular capsule (white arrowheads). AmotL2 fluorescence was lower in cells with high TNFα+ staining. Kidney tubule cells of cilastatin-protected cisplatin-treated rats showed a staining pattern very similar to controls, although with TNFα and AmotL2 at a slightly lower intensity (CisPt + CIL panels, Figure 5). 3.7. Expression of TNFα and IQGAP1 in Cisplatin Treated and Cilastatin Protected Rat Kidney Low-intensity immunostaining was seen for TNFα and IQGAP1 in the cytosol of tubular cells (Control panels, Figure 6). Thin yellow arrows point to more intense IQGAP1 fluorescence around nuclei in some tubule cells. The outer glomerular capsule had small areas of cells with higher IQGAP1 immunofluorescence (white arrows). Glomerular cells showed low levels of IQGAP1-specific immunostaining. Kidney tubule cells from cilastatin-treated rats (CIL panels, Figure 6) showed slightly higher levels of TNFα and IQGAP1 than controls, but with very similar localization. Glomerular cells showed a slightly more intense signal for IQGAP1. The CisPt panels in Figure 6 show a clear sample of high-intensity TNFα immunofluorescence in the cytosol of some tubule cells, inside the tubular light, as pluricellular blebbing bodies (white arrows). Red arrows indicate TNFα fluorescence at the luminal-apical border of some tubular cells; however, the immunofluorescence in most of the tubules of the field is at a much lower intensity (similar to controls) in the cell cytosol (arrowheads). Cilastatin-protected cisplatin-treated rats presented homogeneous fluorescence signals for both TNFα and IQGAP1 in kidney tubular cells. TNFα was cytoplasmic and at a similar level to controls. A few tubular cells show a TNFα-specific fluorescence signal (red arrow). IQGAP1 fluorescence is of higher intensity than in rats treated with either cilastatin or cisplatin alone. TNFα and IQGAP1 fluorescence was of very low intensity in kidney glomeruli in all experimental conditions. Table 2 shows the intensities of specific fluorescence signals for TNFα, FKBP51, AmotL2 and IQGAP1 in different kidney cell types from the four experimental conditions. 4. Discussion Previous reports from our group showed histological and functional damage and increased inflammation in rat kidneys after cisplatin administration [1]. In the current study, we confirm significant damage to renal function (Table 1), intratubular protein cast (Figure 1), and increased NF-κB (Figure 2). We also present a tubule-by-tubule and cell-by-cell analysis, which was necessary to determine the distribution of the damage. As shown in Figure 4 and summarized in Table 2, the immunophilin FKBP51 is expressed at a basal level in the cytosol of all kinds of tubule cells and was not affected significantly by cilastatin treatment. After cisplatin treatment, total-kidney NF-κB levels increased (Figure 2); however, confocal microscopy analysis showed that the expression levels of FKBP51 and TNFα seem to be inversely related. TNFα+ tubular cells showed lower levels of FKBP51 protein, while those with basal or lower levels of TNFα expression had much higher levels of FKBP51, not only in the cytosol, but also in nuclei. The immunophilins FKBP51 and FKBP52 regulate the activity of the NF-κB family of transcription factors, which are involved in a large number of different cell functions, including cell growth and development, differentiation, inflammation, and many others. The most frequent NF-κB dimer is p50/RelA(p65). FKBP51 can have inhibitory or stimulatory effects on NF-κB signaling, depending on the type of cell [16,38,39,40]. FKBP51 seems to protect against the inflammatory effects of cisplatin, as suggested by the low expression of TNFα, a marker of inflammation. The mechanism is likely threefold. Firstly, FKBP51 plays an essential role in the TNFα/NF-κB inflammation signaling pathway [16,38,39], with recent studies showing that FKBP51 impairs nuclear translocation of the p50_RelA/p65 complex, blocking the transcriptional activity of NF-κB [40,41] and consequently preventing inflammation. Secondly, FKBP51 acts as a regulator of the glucocorticoid receptor signaling pathway, and thirdly, FKBP51 acts in a more complex way, through molecular chaperoning of metabolism, with FKBP51 independently and directly regulating phosphorylation cascades and nuclear receptors [42]. These three mechanisms of action may partly explain the pleiotropic effects of FKBP51 under cisplatin toxicity in different regions and cell types of the kidney. FKBP51 expression in kidney tubule cells of cilastatin-protected cisplatin-treated rats was higher than in controls, with no expression or non-significant expression of TNFα, and low levels of NF-κB. Nuclear FKBP51 expression in this group is even higher than in the cytosol of most tubule cells. This suggests an agonistic effect of cilastatin and cisplatin on FKBP51 expression, probably through a complex mechanism that, although outside the scope of this study, would be worthy of future investigation. The fact that cilastatin and cisplatin together led to increased FKBP51 levels suggests that early antiapoptotic action mediated by FKBP51 [22] may be at least partly responsible for this group’s lower levels of cell blebbing, which is representative of cell death by apoptosis or ferroptosis [43]. Additionally of interest for further study is FKBP51s, a C-terminus-lacking isoform which is generated by alternative splicing of FKBP5 pre-mRNA. This isoform lacks the TPR domain and can be found in nuclei [23] acting as a transcriptional regulator. Further research into the functional association of immunophilins with Hsps, especially with Hsp90, will also be of particular interest. The alternative supramolecular heterocomplexes formed (NFκB, FKBP51, FKBP52, Hsps, hTERT, glucocorticoid receptor, etc.) are critical to the many pleiotropic effects previously mentioned, ultimately deciding the fate of the cell. Further study in this area is particularly warranted given that the effects vary in different types of cells [14,16,40]. Although cisplatin did not affect AmotL2 expression in kidney tubule cells with basal levels of TNFα (Figure 5 and Table 2), in inflamed TNFα+ cells, AmotL2 intensity levels were higher than in surrounding TNFα± cells. The addition of cilastatin seems to reduce TNFα expression and homogenize AmotL2 expression to control levels. AmotL2 localization seems to be always cytosolic, usually of homogeneous distribution, but more intense in the nuclei of blebbing cells, either in samples from control or cilastatin-treated rats (Figure 5) but apparently never in cisplatin-treated or cilastatin-protected cisplatin-treated rats. The increased expression of AmotL2 by cilastatin returning to basal levels under cisplatin co-administration may indicate a pre-stress activation that prevents cisplatin-induced inflammation (TNFα−). No changes in intensity or localization were detected for AmotL2 in Bowman´s external capsule cells, or glomerular or vessel cells. The absence of changes in AmotL2 expression levels either in vessels or glomerular capillaries under either combined or single treatment with cilastatin or cisplatin suggests that the role of AmotL2 in this process is as a scaffold protein regulating pools of transcription factors like LATS1/2 (Large Tumor Suppressor Kinase) [44], which ultimately regulates the key downstream target YAP (yes-associated protein) [24] in the Hippo signaling pathway. Further investigation is required to resolve this issue, especially in the light of conflicting research publications, some of which have identified angiomotin proteins as potent suppressors of YAP, while others have shown angiomotins to be YAP activators [15,44,45]; furthermore, the few studies which have looked at YAP-TNFα interrelationships have also yielded conflicting results. For example, reciprocal stimulation of TNFα and YAP signaling activities has been reported in renal tubules [46], while in MC3T3-E1 cells, YAP1 expression was downregulated after treatment with TNFα, and YAP1 attenuated the TNFα-induced activation of the NF-κB signaling pathway [47]. Cilastatin increases IQGAP1 expression along with TNFα in renal tubule cells, both in a homogeneous manner (Table 2 and Figure 6). Cisplatin elicits a higher increase of IQGAP1 only in TNFα− cells; however, cilastatin and cisplatin together increase the intensity in both TNFα− and + cells, although to a higher level in TNFα− cells (Table 2 and Figure 6). No nuclear localization was seen in any kind of cell. Both combined and individual treatment with cilastatin or cisplatin led to a slight increase in IQGAP1 expression in glomerular and glomerular capsule cells but did not lead to compartmentalized subcellular localization. Aptly described as a “molecular puppeteer”, IQGAP1 is a scaffold of, among others, the core proteins of the Hippo pathway [48], facilitating crosstalk between the Hippo network and the AKT and ERK pathways, and negatively regulating the pro-apoptotic signal mediated by this pathway [48,49,50]. This is consistent with our results, and it is conceivable that IQGAP1 and AmotL2 play complementary scaffolding roles in the Hippo-YAP pathways involved in tubule cell escape from cisplatin-induced apoptosis; however, the interaction between YAP and TNFα/NF-κB pathways seems to depend on cell type and context, as evidenced by their opposite effects in chondrocytes [51] and LPS-induced endothelial inflammation [52]. Anoikis is a form of anchorage-dependent cell death caused by the loss of cell matrix and consecutive detachment of cells (blebbing), a form of tubular cell death due to heavy metal toxicity [53]. IQGAP1, interacting with cytoskeletal proteins [25,26], may be an active component in cilastatin-mediated protection against cell death [54], thus preventing cisplatin toxicity. Finally, recently it has been shown that miR-124, a 3′-UTR of IQGAP1, might be associated with the development of inflammation in liver fibrosis [55]. Overexpression of miR-124 and knockdown of IQGAP1 led to downregulation of TNFα, IL-1β and IL-6, while knockdown of miR-124 or overexpression of IQGAP1 produced the opposite result. When compared with the findings of the present study, these results point to the activation of different pathways in different cell types, or by different causes of inflammation. Variations described in capsule and glomerular cells do not appear to be related to inflammation and are outside the scope of this article, but would nonetheless be of interest for further study. Our findings offer significant insights into the involvement of FKBP51, AmotL2 and IQGAP1 in kidney tubule cisplatin toxicity and its prevention by cilastatin. The precise roles of these three proteins and their functional co-involvement in these processes pose interesting new questions for future research. 5. Conclusions The renal inflammation caused by cisplatin toxicity is focally and segmentally localized, in some tubules grouped in foci, and to different degrees in different cells within the same tubule. Cilastatin greatly reduces the levels of inflammation (although not to basal level) and slightly increases FKBP51, AmotL2 and IQGAP1 protein expression. Cisplatin treatment modifies renal tubule FKBP51, AmotL2 and IQGAP1 expression in a cellular- and subcellular-specific manner. Expression is also dependent on the level of inflammation in the tubule cells. Cells expressing high levels of FKBP51 have no or very low expression of TNFα. Conversely, cells expressing TNFα have low levels of FKBP51. AmotL2 and TNFα seem to colocalize and their expression is increased in tubular cells. There is a complex relationship between changes in IQGAP1 expression/localization and TNFα. Finally, treatment with cilastatin and cisplatin together leads to a slight increase in IQGAP1 expression in glomerular and glomerular capsule cells. Acknowledgments We thank Deborah Rotoli for careful reading of the manuscript, corrections and advice. We thank Sonja Kennington, for English revision and advice and Felipe Rosa, Department of Mathematics, Statistics and Operational Research, University of La Laguna, for statistical analysis and advice. Author Contributions Conceptualization, P.M.-V.; Data curation, R.G.-F., M.Á.G.-N., J.Á. and A.L.; Formal analysis, M.M., A.L. and P.M.-V.; Funding acquisition, J.Á. and A.L.; Investigation, R.G.-F., M.Á.G.-N. and A.L.; Methodology, M.M.; Resources, J.Á.; Supervision, J.Á. and P.M.-V.; Writing—original draft, A.L. and P.M.-V.; Writing—review and editing, A.L. and P.M.-V. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board: The study was approved by the Institutional Board for Animal Experiments of the Gregorio Marañón Hospital Registration code 07-2008) and animals were handled at all times according to legal regulations stipulated by RD 118/2021, of 23 February. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest A.L. is co-holder of patents for cilastatin as a nephroprotector against toxic injuries (“Use of cilastatin to reduce nephrotoxicity of various compounds”, patent numbers: EP 2143429 B1; US 9,216,185 B2; US 9,522,128 B2; US 9,757,349 B2), which are assigned to FIBHGM and licensed to Telara Pharma S.L., and from Telara Pharma S.L. to Arch Biopartners. A.L. is co-founder of Telara Pharma S.L., A.L., P.M.-V. and M.A.G.-N. are shareholders of Telara Pharma S.L. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results. The other authors declare no conflicts of interest. Dedicatory Authors dedicate this article to the memory of Professor Alberto Tejedor, teacher, colleague and friend, who started the study of cilastatin as a kidney protector. Figure 1 Cilastatin reduces histopathological damage induced by cisplatin administration. (A) Representative images of the hematoxilyn-eosin-stained renal cortex and medulla of control, cilastatin, cisplatin and cisplatin + cilastatin rats (20× magnification). Arrows point to intratubular protein casts from animals treated with cisplatin. The rest of the groups presented an apparently normal renal morphology. Bar = 100 µm. (B) Semiquantitative tubular damage score. Results are expressed as mean ± s.e.m., n = 6 animals per group. * p < 0.005 vs. all other groups. Figure 2 Cilastatin diminishes cisplatin-induced inflammatory NF-κB upregulation. (A) Representative photomicrograph of western blots of the p65 subunit of NF-κB in renal cortex. (B) Densitometric analysis of the p65 subunit on western blots. Cilastatin reduced the NF-κB values previously increased by cisplatin treatment. Results are expressed as mean ± SEM, * p < 0.03 vs. all other groups. Figure 3 Focal and segmental localization of TNFα expression elicited by cisplatin in rat kidney tubules. Renal tubules of control and cilastatin (CIL)-treated groups show homogeneous basal expression of TNFα. In the cisplatin-treated group (CisPt), immunostaining for TNFα in tubules is heterogeneous, with positivity observed only in some tubules foci (white arrows), and sometimes confined to a segment of the tubule (arrowheads). Cilastatin-protected cisplatin-treated rat kidneys (CisPt-CIL), show scarce immunolocalization signals for TNFα (white arrows). 10× magnification. Bar = 40 µm. Figure 4 Expression of FKBP51 in cisplatin-treated and cilastatin-protected rat kidney. Control panels: tubular cells show low immunostaining of TNFα and FKBP51 in cytosol. White arrows point to small areas of higher TNFα fluorescence in the outer glomerular capsule cells, yellow thin arrows point to more intense FKBP51 fluorescence around nuclei in some tubule cells and yellow arrowheads point to some physiological cell blebbing. CIL panels: kidney tubule cells of cilastatin-treated rats show TNFα and FKBP51 immunostaining very similar to controls in localization and intensity. Yellow arrowheads point to some physiological cell blebbing. CisPt panels: kidney tubule cells of cisplatin-treated rats: TNFα-specific immunofluorescence appears heterogeneous within the same tubules, with several cells showing high levels in the cytosol (white arrows), while in some other cells the cytosolic signal is fainter (white arrowheads). Most tubules show a low-level signal, though slightly brighter than controls. Some tubules, such as the one indicated by the yellow arrowhead, present abundant cell blebbing. FKBP51-specific immunofluorescence presents two intensity levels: a low level in low TNFα-signal tubules and a higher level in the high TNFα-signal tubules. The immunosignal in nuclei has a multi-dot fluorescence pattern (red arrow). CisPt + CIL panels: kidney tubule cells of cilastatin-protected cisplatin-treated rats present a homogeneous fluorescence pattern for both TNFα and FKBP51. TNFα is cytoplasmic and at a similar level to controls, while FKBP51-specific fluorescence is of higher intensity in both nuclei and cytosol, being more prominent in nuclei (white arrow). TNFα fluorescence is very low in kidney glomeruli from all experimental conditions, while FKBP51 signal is low in control, CIL and CisPt groups, but has a clear signal in glomeruli cells (star) and capsule cells (red arrow). Bar = 20 µm. Figure 5 Expression of AmotL2 in the cisplatin-treated and cilastatin protected rat kidney. Control panels: tubular cells show low TNFα and homogeneous medium-intensity AmotL2 in cytosol (bold white arrows), most prominent in some cells around nuclei (thin white arrows). Some cells of the outer glomerular capsule show high staining intensity for TNFα and AmotL2 (white arrowheads). Glomerular cells show no TNFα signal and low AmotL2 staining (star). CIL panels: tubular cells of cilastatin-treated rats show homogeneous TNFα and AmotL2, with similar localization to controls, but at a slightly but definitely increased intensity level. AmotL2 staining is more intense around the nuclei of some cells, and most nuclei show AmotL2 staining in a dot-like pattern. Red arrows point to TNFα and AmotL2 immunostaining in the luminal side of endothelial cells of medium-sized vessels. CisPt panels: bold white arrows point to high-intensity TNFα-specific immunostaining in some tubule cells of cisplatin-treated rats; thin white arrows point to other cells within the same tubules with a lower staining intensity. In both cases intensity is higher at the apical brush border than in the cytosol. AmotL2/TNFα positive cells can be seen in the outer glomerular capsule (white arrowheads). AmotL2 fluorescence is lower in highly TNFα-positive cells. CisPt + CIL panels: kidney tubule cells of cilastatin-protected cisplatin-treated rats show a staining pattern very similar to that of controls, although both TNFα and AmotL2 signals are at a slightly lower intensity than in controls. 40× magnification. Bar = 20 µm. Figure 6 Expression of IQGAP1 in cisplatin-treated and cilastatin protected rat kidney. Control panels: low-intensity immunostaining for TNFα and IQGAP1 in cytosol of tubular cells. White arrows point to small areas of higher IQGAP1 immunofluorescence in outer glomerular capsule cells. Thin yellow arrows point to more intense IQGAP1 fluorescence around nuclei in some tubule cells. Glomerular cells show low expression of IQGAP1. CIL panels: kidney tubule cells of cilastatin-treated rats show slightly higher intensity TNFα and IQGAP1 staining compared to controls, with very similar localization. Red arrows indicate TNFα fluorescence in outer glomerular capsule cells. CisPt panels: kidney tubule cells of cisplatin-treated rats. High intensity TNFα fluorescence is found in the cytosol of some tubule cells inside the tubular light, as pluricellular blebbing bodies (white arrows). Yellow arrows indicate TNFα fluorescence at the luminal-apical border of some tubular cells and, at a much lower intensity (similar to controls) in the cytosol of other cells (arrowheads). CisPt + CIL panels: kidney tubule cells of cilastatin-protected cisplatin-treated rats have homogeneous TNFα and IQGAP1 fluorescence. TNFα is cytoplasmic and at a similar level to controls. A few tubular cells show TNFα fluorescence (yellow arrow). IQGAP1 fluorescence is of higher intensity. TNFα and IQGAP1 fluorescence was of very low intensity in kidney glomeruli from all experimental conditions. 40× magnification. Bar = 20 µm. cells-11-01585-t001_Table 1 Table 1 Effects of cilastatin treatment on cisplatin-induced renal toxicity in rats. Results are expressed as mean ± SEM. a p < 0.001, b p < 0.005 vs. control and control + cil; c p < 0.05 vs. control + cil; d p < 0.0001, e p < 0.001, f p < 0.0005 vs. all other groups. Cil: cilastatin; SCreat: serum creatinine; BUN: blood urea nitrogen; GFR: glomerular filtration rate; UVol: urinary volume; FE: fractional excretion. Groups SCreat (mg/dL) BUN (mg/dL) GFR (mL/min/100 g) UVol (mL/24 h) FENa+ (%) FEH2O (%) Control 0.29 ± 0.02 27.14 ± 1.65 0.76 ± 0.05 16.00 ± 3.49 0.46 ± 0.04 0.53 ± 0.13 Control + Cil 0.29 ± 0.02 26.29 ± 2.36 0.72 ± 0.05 14.21 ± 2.05 0.47 ± 0.06 0.48 ± 0.05 Cisplatin 1.48 ± 0.12 d 108.57 ± 12.67 d 0.14 ± 0.02 e 29.00 ± 3.12 b 1.55 ± 0.30 f 5.55 ± 0.84 d Cisplatin + Cil 0.63 ± 0.11 a 50.71 ± 12.48 0.46 ± 0.09 b 23.29 ± 2.06 c 0.64 ± 0.13 1.49 ± 0.25 cells-11-01585-t002_Table 2 Table 2 Intensity of specific fluorescence signal for TNFα, FKBP51, AmotL2 and IQGAP1 in kidney cell types from control, cilastatin-treated (CIL), cisplatin-treated (CisPt), cilastatin-protected cisplatin-treated (CisPt + CIL) groups of rats. Intensity levels: ± basal-faint, + low, ++ medium, and +++ high. TNFα Control CIL CisPt CisPt + CIL Tubule cells ± ± ±/+++ +/++ Ext. capsule cells ±/++ ±/++ ±/++ ±/++ Glomerulus cells ± ± ± ± FKBP51 Control CIL CisPt CisPt + CIL Tub. cells TNFα± basal ± ± ++/+++ TNFα+ ±/++ ±/++ +++ +/+++ Ext. capsule cells ± ± ± ++ Glomerulus cells ± ± ± ++ AmotL2 Control CIL CisPt CisPt + CIL Tub. cells TNFα± basal ± ± ±/++ TNFα+ ++ ++/+++ +++ ±/++ Ext. capsule cells ±/++ ±/++ ±/++ ±/++ Glomerulus cells ±/++ ±/++ ±/++ ±/++ IQGAP1 Control CIL CisPt CisPt + CIL Tub. cells TNFα± basal ± ± +++ TNFα+ ± ±/++ ±/++ ++ Ext. capsule cells ± ±/++ ±/++ ±/++ Glomerulus cells ± + + + Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Humanes B. Lazaro A. Camano S. Moreno-Gordaliza E. Lazaro J.A. Blanco-Codesido M. Lara J.M. Ortiz A. Gómez-Gómez M.M. Martín-Vasallo P. Cilastatin protects against cisplatin-induced nephrotoxicity without compromising its anticancer efficiency in rats Kidney Int. 2012 82 652 663 10.1038/ki.2012.199 22718191 2. Lazaro A. Humanes B. Jado J.C. Tejedor A. The Authors Reply Kidney Int. 2013 83 1201 1202 10.1038/ki.2013.42 23728005 3. Moreno-Gordaliza E. Giesen C. Lázaro A. Esteban-Fernández D. Humanes B. Cañas B. Panne U. Tejedor A. Jakubowski N. Gómez-Gómez M.M. Elemental Bioimaging in Kidney by LA–ICP–MS As a Tool to Study Nephrotoxicity and Renal Protective Strategies in Cisplatin Therapies Anal. Chem. 2011 83 7933 7940 10.1021/ac201933x 21913725 4. Humanes B. Camaño S. Lara J.M. Sabbisetti V. González-Nicolás M. Bonventre J.V. Tejedor A. Lázaro A. Cisplatin-induced renal inflammation is ameliorated by cilastatin nephroprotection Nephrol. Dial. Transplant. 2017 32 1645 1655 10.1093/ndt/gfx005 28340076 5. Zaballos M. Power M. Canal-Alonso M.I. González-Nicolás M.Á. Vasquez-Jimenez W. Lozano-Lominchar P. Cabrerizo-Torrente P. Palencia-García N. Gago-Quiroga S. Ginel-Feito M.D. Effect of Cilastatin on Cisplatin-Induced Nephrotoxicity in Patients Undergoing Hyperthermic Intraperitoneal Chemotherapy Int. J. Mol. Sci. 2021 22 1239 10.3390/ijms22031239 33513824 6. Shayan M. Elyasi S. Cilastatin as a protective agent against drug-induced nephrotoxicity: A literature review Expert Opin. Drug Saf. 2020 19 999 1010 10.1080/14740338.2020.1796967 32666842 7. Morales M. Ávila J. González-Fernández R. Boronat L. Soriano M. Martín-Vasallo P. Differential Transcriptome Profile of Peripheral White Cells to Identify Biomarkers Involved in Oxaliplatin Induced Neuropathy J. Pers. Med. 2014 4 282 296 10.3390/jpm4020282 25563226 8. Becerir T. Tokgün O. Yuksel S. The Therapeutic Effect of Cilastatin on Drug-Induced Nephrotoxicity: A New Perspective Eur. Rev. Med. Pharmacol. Sci. 2021 25 5436 5447 10.26355/eurrev_202109_26651 34533819 9. Rotoli D. Díaz-Flores L. Gutiérrez R. Morales M. Ávila J. Martín-Vasallo P. AmotL2, IQGAP1, and FKBP51 Scaffold Proteins in Glioblastoma Stem Cell Niches J. Histochem. Cytochem. 2021 70 9 16 10.1369/00221554211025480 34165350 10. Wei T. Lambert P.F. Role of IQGAP1 in Carcinogenesis Cancers 2021 13 3940 10.3390/cancers13163940 34439095 11. Kästle M. Kistler B. Lamla T. Bretschneider T. Lamb D. Nicklin P. Wyatt D. FKBP51 modulates steroid sensitivity and NFκB signalling: A novel anti-inflammatory drug target Eur. J. Immunol. 2018 48 1904 1914 10.1002/eji.201847699 30169894 12. Szklarczyk D. Franceschini A. Wyder S. Forslund K. Heller D. Huerta-Cepas J. Simonovic M. Roth A. Santos A. Tsafou K.P. STRING v10: Protein–protein interaction networks, integrated over the tree of life Nucleic Acids Res. 2015 43 D447 D452 10.1093/nar/gku1003 25352553 13. Rotoli D. Morales M. Maeso M.-C. Ávila J. Pérez-Rodríguez N.D. Mobasheri A. van Noorden C.J.F. Martín-Vasallo P. IQGAP1, AmotL2, and FKBP51 Scaffoldins in the Glioblastoma Microenvironment J. Histochem. Cytochem. 2019 67 481 494 10.1369/0022155419833334 30794467 14. Lagadari M. Zgajnar N.R. Gallo L.I. Galigniana M.D. Hsp90-binding immunophilin FKBP51 forms complexes with hTERT enhancing telomerase activity Mol. Oncol. 2016 10 1086 1098 10.1016/j.molonc.2016.05.002 27233944 15. Lv M. Shen Y. Yang J. Li S. Wang B. Chen Z. Li P. Liu P. Yang J. Angiomotin Family Members: Oncogenes or Tumor Suppressors? Int. J. Biol. Sci. 2017 13 772 781 10.7150/ijbs.19603 28656002 16. Zgajnar N. de Leo S. Lotufo C. Erlejman A. Piwien-Pilipuk G. Galigniana M. Biological Actions of the Hsp90-Binding Immunophilins FKBP51 and FKBP52 Biomolecules 2019 9 52 10.3390/biom9020052 17. Fries G. Gassen N. Rein T. The FKBP51 Glucocorticoid Receptor Co-Chaperone: Regulation, Function, and Implications in Health and Disease Int. J. Mol. Sci. 2017 18 2614 10.3390/ijms18122614 18. Maiarù M. Tochiki K.K. Cox M.B. Annan L.V. Bell C.G. Feng X. Hausch F. Géranton S.M. The Stress Regulator FKBP51 Drives Chronic Pain by Modulating Spinal Glucocorticoid Signaling Sci. Transl. Med. 2016 8 325ra19 10.1126/scitranslmed.aab3376 19. Poletti F. González-Fernández R. García M.-P. Rotoli D. Ávila J. Mobasheri A. Martín-Vasallo P. Molecular-Morphological Relationships of the Scaffold Protein FKBP51 and Inflammatory Processes in Knee Osteoarthritis Cells 2021 10 2196 10.3390/cells10092196 34571845 20. D’Arrigo P. Russo M. Rea A. Tufano M. Guadagno E. del Basso De Caro M.L. Pacelli R. Hausch F. Staibano S. Ilardi G. A Regulatory Role for the Co-Chaperone FKBP51s in PD-L1 Expression in Glioma Oncotarget 2017 8 68291 68304 10.18632/oncotarget.19309 28978117 21. Tufano M. D’Arrigo P. D’Agostino M. Giordano C. Marrone L. Cesaro E. Romano M.F. Romano S. PD-L1 Expression Fluctuates Concurrently with Cyclin D in Glioblastoma Cells Cells 2021 10 2366 10.3390/cells10092366 34572014 22. Gallo L.I. Lagadari M. Piwien-Pilipuk G. Galigniana M.D. The 90-kDa Heat-shock Protein (Hsp90)-binding Immunophilin FKBP51 Is a Mitochondrial Protein That Translocates to the Nucleus to Protect Cells against Oxidative Stress J. Biol. Chem. 2011 286 30152 30160 10.1074/jbc.M111.256610 21730050 23. Romano S. D’Angelillo A. Staibano S. Simeone E. D’Arrigo P. Ascierto P.A. Scalvenzi M. Mascolo M. Ilardi G. Merolla F. Immunomodulatory Pathways Regulate Expression of a Spliced FKBP51 Isoform in Lymphocytes of Melanoma Patients Pigment. Cell Melanoma Res. 2015 28 442 452 10.1111/pcmr.12378 25895097 24. Baldan S. Meriin A.B. Yaglom J. Alexandrov I. Varelas X. Xiao Z.-X.J. Sherman M.Y. The Hsp70–Bag3 Complex Modulates the Phosphorylation and Nuclear Translocation of Hippo Pathway Protein Yap J. Cell Sci. 2021 134 jcs259107 10.1242/jcs.259107 34761265 25. Grahammer F. Schell C. Huber T.B. The Podocyte Slit Diaphragm—from a Thin Grey Line to a Complex Signalling Hub Nat. Rev. Nephrol. 2013 9 587 598 10.1038/nrneph.2013.169 23999399 26. Tanos B.E. Perez-Bay A. Salvarezza S. Vivanco I. Mellinghoff I. Osman M. Sacks D.B. Rodriguez-Boulan E. IQGAP1 Controls Tight Junction Formation Through Differential Regulation of Claudin Recruitment J. Cell Sci. 2015 128 853 862 10.1242/jcs.118703 25588839 27. Liu Y. Liang W. Yang Y. Pan Y. Yang Q. Chen X. Singhal P.C. Ding G. IQGAP1 Regulates Actin Cytoskeleton Organization in Podocytes through Interaction with Nephrin Cell. Signal. 2015 27 867 877 10.1016/j.cellsig.2015.01.015 25652011 28. Lai L.-W. Yong K.-C. Lien Y.-H.H. Site-Specific Expression of IQGAP1, a Key Mediator of Cytoskeleton, in Mouse Renal Tubules J. Histochem. Cytochem. 2008 56 659 666 10.1369/jhc.2008.950113 18413651 29. Goldspink D.A. Rookyard C. Tyrrell B.J. Gadsby J. Perkins J. Lund E.K. Galjart N. Thomas P. Wileman T. Mogensen M.M. Ninein Is Essential for Apico-Basal Microtubule Formation and CLIP-170 Facilitates Its Redeployment to Non-Centrosomal Microtubule Organizing Centres Open Biol. 2017 7 160274 10.1098/rsob.160274 28179500 30. Huang T. Zhou Y. Zhang J. Cheng A.S.L. Yu J. To K.F. Kang W. The Physiological Role of Motin Family and Its Dysregulation in Tumorigenesis J. Transl. Med. 2018 16 98 10.1186/s12967-018-1466-y 29650031 31. Abel A.M. Schuldt K.M. Rajasekaran K. Hwang D. Riese M.J. Rao S. Thakar M.S. Malarkannan S. IQGAP1: Insights into the Function of a Molecular Puppeteer Mol. Immunol. 2015 65 336 349 10.1016/j.molimm.2015.02.012 25733387 32. Peng X. Wang T. Gao H. Yue X. Bian W. Mei J. Zhang Y. The Interplay between IQGAP1 and Small GTPases in Cancer Metastasis Biomed. Pharmacother. 2021 135 111243 10.1016/j.biopha.2021.111243 33434854 33. Francescato H.D.C. Costa R.S. Scavone C. Coimbra T.M. Parthenolide Reduces Cisplatin-Induced Renal Damage Toxicology 2007 230 64 75 10.1016/j.tox.2006.10.025 17156909 34. do Amaral C.L. Francescato H.D.C. Coimbra T.M. Costa R.S. Darin J.D.C. Antunes L.M.G. Bianchi M.D.L.P. Resveratrol Attenuates Cisplatin-Induced Nephrotoxicity in Rats Arch. Toxicol. 2008 82 363 370 10.1007/s00204-007-0262-x 18026934 35. Lee K.W. Jeong J.Y. Lim B.J. Chang Y.-K. Lee S.-J. Na K.-R. Shin Y.-T. Choi D.E. Sildenafil Attenuates Renal Injury in an Experimental Model of Rat Cisplatin-Induced Nephrotoxicity Toxicology 2009 257 137 143 10.1016/j.tox.2008.12.017 19152827 36. Camano S. Lazaro A. Moreno-Gordaliza E. Torres A.M. de Lucas C. Humanes B. Lazaro J.A. Milagros Gomez-Gomez M. Bosca L. Tejedor A. Cilastatin Attenuates Cisplatin-Induced Proximal Tubular Cell Damage J. Pharmacol. Exp. Ther. 2010 334 419 429 10.1124/jpet.110.165779 20435919 37. Lazaro A. Gallego-Delgado J. Justo P. Esteban V. Osende J. Mezzano S. Ortiz A. Egido J. Long-Term Blood Pressure Control Prevents Oxidative Renal Injury Antioxid. Redox Signal. 2005 7 1285 1293 10.1089/ars.2005.7.1285 16115034 38. Bouwmeester T. Bauch A. Ruffner H. Angrand P.-O. Bergamini G. Croughton K. Cruciat C. Eberhard D. Gagneur J. Ghidelli S. A Physical and Functional Map of the Human TNF-α/NF-ΚB Signal Transduction Pathway Nat. Cell Biol. 2004 6 97 105 10.1038/ncb1086 14743216 39. Annett S. Moore G. Robson T. FK506 Binding Proteins and Inflammation Related Signalling Pathways; Basic Biology, Current Status and Future Prospects for Pharmacological Intervention Pharmacol. Ther. 2020 215 107623 10.1016/j.pharmthera.2020.107623 32622856 40. Erlejman A.G. de Leo S.A. Mazaira G.I. Molinari A.M. Camisay M.F. Fontana V. Cox M.B. Piwien-Pilipuk G. Galigniana M.D. NF-ΚB Transcriptional Activity Is Modulated by FK506-Binding Proteins FKBP51 and FKBP52 J. Biol. Chem. 2014 289 26263 26276 10.1074/jbc.M114.582882 25104352 41. Wochnik G.M. Rüegg J. Abel G.A. Schmidt U. Holsboer F. Rein T. FK506-Binding Proteins 51 and 52 Differentially Regulate Dynein Interaction and Nuclear Translocation of the Glucocorticoid Receptor in Mammalian Cells J. Biol. Chem. 2005 280 4609 4616 10.1074/jbc.M407498200 15591061 42. Smedlund K.B. Sanchez E.R. Hinds T.D. FKBP51 and the Molecular Chaperoning of Metabolism Trends Endocrinol. Metab. 2021 32 862 874 10.1016/j.tem.2021.08.003 34481731 43. Mishima E. Sato E. Ito J. Yamada K. Suzuki C. Oikawa Y. Matsuhashi T. Kikuchi K. Toyohara T. Suzuki T. Drugs Repurposed as Antiferroptosis Agents Suppress Organ Damage, Including AKI, by Functioning as Lipid Peroxyl Radical Scavengers J. Am. Soc. Nephrol. 2020 31 280 296 10.1681/ASN.2019060570 31767624 44. Kim M. Kim M. Park S. Lee C. Lim D. Role of Angiomotin-like 2 Mono-ubiquitination on YAP Inhibition EMBO Rep. 2016 17 64 78 10.15252/embr.201540809 26598551 45. Yi C. Shen Z. Stemmer-Rachamimov A. Dawany N. Troutman S. Showe L.C. Liu Q. Shimono A. Sudol M. Holmgren L. The P130 Isoform of Angiomotin Is Required for Yap-Mediated Hepatic Epithelial Cell Proliferation and Tumorigenesis Sci. Signal. 2013 6 ra77 10.1126/scisignal.2004060 24003254 46. Xu C. Wang L. Zhang Y. Li W. Li J. Wang Y. Meng C. Qin J. Zheng Z.-H. Lan H.-Y. Tubule-Specific Mst1/2 Deficiency Induces CKD via YAP and Non-YAP Mechanisms J. Am. Soc. Nephrol. 2020 31 946 961 10.1681/ASN.2019101052 32253273 47. Yang B. Sun H. Xu X. Zhong H. Wu Y. Wang J. YAP1 Inhibits the Induction of TNF-α-stimulated Bone-resorbing Mediators by Suppressing the NF-κB Signaling Pathway in MC3T3-E1 Cells J. Cell. Physiol. 2020 235 4698 4708 10.1002/jcp.29348 31642068 48. Quinn N.P. García-Gutiérrez L. Doherty C. von Kriegsheim A. Fallahi E. Sacks D.B. Matallanas D. IQGAP1 Is a Scaffold of the Core Proteins of the Hippo Pathway and Negatively Regulates the Pro-Apoptotic Signal Mediated by This Pathway Cells 2021 10 478 10.3390/cells10020478 33672268 49. Roy M. Li Z. Sacks D.B. IQGAP1 Binds ERK2 and Modulates Its Activity J. Biol. Chem. 2004 279 17329 17337 10.1074/jbc.M308405200 14970219 50. Chen F. Zhu H.-H. Zhou L.-F. Wu S.-S. Wang J. Chen Z. IQGAP1 Is Overexpressed in Hepatocellular Carcinoma and Promotes Cell Proliferation by Akt Activation Exp. Mol. Med. 2010 42 477 483 10.3858/emm.2010.42.7.049 20530982 51. Deng Y. Lu J. Li W. Wu A. Zhang X. Tong W. Ho K.K. Qin L. Song H. Mak K.K. Reciprocal Inhibition of YAP/TAZ and NF-ΚB Regulates Osteoarthritic Cartilage Degradation Nat. Commun. 2018 9 4564 10.1038/s41467-018-07022-2 30385786 52. Lv Y. Kim K. Sheng Y. Cho J. Qian Z. Zhao Y.-Y. Hu G. Pan D. Malik A.B. Hu G. YAP Controls Endothelial Activation and Vascular Inflammation Through TRAF6 Circ. Res. 2018 123 43 56 10.1161/CIRCRESAHA.118.313143 29794022 53. Ge J. Huang Y. Lv M. Zhang C. Talukder M. Li J. Li J. Cadmium Induced Fak -Mediated Anoikis Activation in Kidney via Nuclear Receptors (AHR/CAR/PXR)-Mediated Xenobiotic Detoxification Pathway J. Inorg. Biochem. 2022 227 111682 10.1016/j.jinorgbio.2021.111682 34902763 54. Mo C. Li J. Yang S. Guo H. Liu Y. Luo X. Wang Y. Li M. Li J. Zou Q. IQGAP1 Promotes Anoikis Resistance and Metastasis through Rac1-Dependent ROS Accumulation and Activation of Src/FAK Signalling in Hepatocellular Carcinoma Br. J. Cancer 2020 123 1154 1163 10.1038/s41416-020-0970-z 32632148 55. Yang J. Xu C. Wu M. Wu Y. Jia X. Zhou C. Zhang X. Ge S. Li Z. Zhang L. MicroRNA-124 Inhibits Hepatic Stellate Cells Inflammatory Cytokines Secretion by Targeting IQGAP1 through NF-ΚB Pathway Int. Immunopharmacol. 2021 95 107520 10.1016/j.intimp.2021.107520 33743313

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095514 ijerph-19-05514 Article Feasibility Trial of Yoga Programme for Type 2 Diabetes Prevention (YOGA-DP) among High-Risk People in India: A Qualitative Study to Explore Participants’ Trial- and Intervention-Related Barriers and Facilitators Mishra Pallavi 1 Harris Tess 2 Greenfield Sheila Margaret 3 Hamer Mark 4 Lewis Sarah Anne 5 https://orcid.org/0000-0003-4330-666X Singh Kavita 1 Nair Rukamani 6 Mukherjee Somnath 6 Manjunath Nandi Krishnamurthy 7 Tandon Nikhil 8 Kinra Sanjay 9 Prabhakaran Dorairaj 1 https://orcid.org/0000-0002-3235-8168 Chattopadhyay Kaushik 5* Tchounwou Paul B. Academic Editor 1 Centre for Chronic Disease Control, New Delhi 110016, India; pallavi@ccdcindia.org (P.M.); kavita@ccdcindia.org (K.S.); dprabhakaran@ccdcindia.org (D.P.) 2 Population Health Research Institute, St. George’s University of London, London SW17 0RE, UK; tharris@sgul.ac.uk 3 Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; s.m.greenfield@bham.ac.uk 4 Institute Sport Exercise and Health, Division of Surgery and Interventional Science, University College London, London W1T 7HA, UK; m.hamer@ucl.ac.uk 5 Lifespan and Population Health Academic Unit, School of Medicine, University of Nottingham, Nottingham NG5 1PB, UK; sarah.lewis@nottingham.ac.uk 6 Bapu Nature Cure Hospital and Yogashram, New Delhi 110091, India; research@bnchy.org (R.N.); soumikmukherjee987@gmail.com (S.M.) 7 Swami Vivekananda Yoga Anusandhana Samsthana, Bengaluru 560105, India; nkmsharma@svyasa.org 8 All India Institute of Medical Sciences, New Delhi 110029, India; nikhil_tandon@hotmail.com 9 Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; sanjay.kinra@lshtm.ac.uk * Correspondence: kaushik.chattopadhyay@nottingham.ac.uk 01 5 2022 5 2022 19 9 551415 3 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Yoga-based interventions can be effective in preventing type 2 diabetes mellitus (T2DM). We developed a Yoga programme for T2DM prevention (YOGA-DP) and conducted a feasibility randomised controlled trial (RCT) among high-risk people in India. This qualitative study’s objective was to identify and explore participants’ trial- and intervention-related barriers and facilitators. The feasibility trial was conducted at two Yoga centres in New Delhi and Bengaluru, India. In this qualitative study, 25 trial participants (13 intervention group, 12 control group) were recruited for semi-structured interviews. Data were analysed using deductive logic and an interpretative phenomenological approach. Amongst intervention and control participants, key barriers to trial participation were inadequate information about recruitment and randomisation processes and the negative influence of non-participants. Free blood tests to aid T2DM prevention, site staff’s friendly behaviour and friends’ positive influence facilitated trial participation. Amongst intervention participants, readability and understanding of the programme booklets, dislike of the Yoga diary, poor quality Yoga mats, difficulty in using the programme video, household commitment during home sessions, unplanned travel, difficulty in practising Yoga poses, hesitation in attending programme sessions with the YOGA-DP instructor of the opposite sex and mixed-sex group programme sessions were key barriers to intervention participation. Adequate information was provided on T2DM prevention and self-care, good venue and other support provided for programme sessions, YOGA-DP instructors’ positive behaviour and improvements in physical and mental well-being facilitated intervention participation. In conclusion, we identified and explored participants’ trial- and intervention-related barriers and facilitators. We identified an almost equal number of barriers (n = 12) and facilitators (n = 13); however, intervention-related barriers and facilitators were greater than for participating in the trial. These findings will inform the design of the planned definitive RCT design and intervention and can also be used to design other Yoga interventions and RCTs. Yoga physical activity barriers facilitators prevention type 2 diabetes prediabetes qualitative research randomised controlled trial feasibility UK’s FCDO/MRC/NIHR/Welcome Trust Joint Global Health TrialsMR/R018278/1 This study was funded by the UK’s FCDO/MRC/NIHR/Welcome Trust Joint Global Health Trials (MR/R018278/1). The funding agencies had no role in designing the study or in writing the paper. ==== Body pmc1. Introduction The 2019 International Diabetes Federation report estimated that 77 million people in India were living with diabetes, with this number expected to increase to 101 million by 2030 [1]. Another 77 million people in the country are at high risk of developing type 2 diabetes mellitus (T2DM) because of raised blood glucose levels but below the established threshold for T2DM [2]. One of the major contributors to T2DM is an unhealthy lifestyle, including physical inactivity and an unhealthy diet [3]. Past studies have found lower physical activity levels and unhealthy dietary practices among people living in India [2,4,5]. Therefore, screening people at high risk of developing T2DM and subsequently offering them an effective lifestyle intervention could be a cost-effective prevention strategy [3]. Evidence suggests that health interventions are more successful if informed by people’s local socio-cultural expectations and health beliefs [6]. Yoga has traditionally been part of the Indian culture, and Yoga-based interventions are more likely to be accepted by Indians [7,8]. Yoga incorporates physical activities and a healthy diet, which results in a disciplined body and mind [9]. Yoga-based interventions can be easily replicated across diverse populations and settings. Yoga relies on a gentle approach, and these interventions can be delivered with a low to moderate level of guidance [7]. Other benefits of a Yoga-based intervention are that it is less expensive to run and can also be practised at home or indoors [7]. Yoga is considered to be safe and can be practised by people with a range of comorbidities as it comprises low- and moderate-intensity activities that help strengthen muscles [7,10]. Previous studies have generated some evidence on the beneficial effects of Yoga in T2DM and metabolic syndrome [11,12,13,14], suggesting that Yoga has the potential to prevent T2DM among high-risk individuals. We developed a Yoga programme for T2DM prevention (YOGA-DP) among high-risk populations in India. The YOGA-DP is a structured lifestyle education and exercise intervention provided over 24 weeks [15]. A randomised control trial (RCT) is planned to evaluate its effectiveness. Prior to this definitive RCT, we conducted a feasibility RCT [16], as part of which we used semi-structured interviews to identify and explore participants’ trial- and intervention-related barriers and facilitators. Additionally, we conducted semi-structured interviews with individuals who declined to participate in the study, published elsewhere [17]. 2. Materials and Methods The detailed feasibility RCT protocol is published elsewhere [15]. The feasibility trial was carried out at two Yoga centres—one in northern India (Bapu Nature Cure Hospital and Yogashram (BNCHY, New Delhi, India)) and one in southern India (Swami Vivekananda Yoga Anusandhana Samsthana (SVYASA, Bengaluru, India)). We used a multipronged approach, such as door-to-door campaigns, posters and screening camps to identify potential participants, i.e., adults at high risk of T2DM as their fasting blood glucose (FBG) level was between 100 and 125 mg/dL [18]. The intervention: YOGA-DP intervention comprises of structured lifestyle education and a Yoga-based exercise programme, which was provided over 24 weeks. This programme was delivered by qualified YOGA-DP instructors (male and female), who were also provided with formal training on the intervention. These YOGA-DP instructors ran the group Yoga sessions locally (such as at Yoga centres and community centres) at different times (with evening and weekend sessions) so that participants could attend the Yoga session at their convenience. During the first three months, the participants were delivered at least two YOGA-DP sessions weekly at the session site, and they were advised to follow YOGA-DP booklet part I (giving information on their condition (i.e., at ‘high risk’ of developing T2DM) and on how to prevent T2DM). In the remaining three months, they were provided with a YOGA-DP booklet part II (giving information on yoga practice to prevent T2DM) and a YOGA-DP video on a USB flash drive to practice Yoga at home without any supervision, and they scheduled at least one session every four weeks at the session site [15]. The YOGA-DP instructor also phoned them weekly to offer support and help and to resolve any problems with their unsupervised sessions. For the unsupervised sessions, participants were also provided with a YOGA-DP diary for self-reporting of Yoga practice, including types and minutes [15]. The control group: in India, there is no standard lifestyle intervention for people at high risk of T2DM, thus, control group participants received a leaflet on routine lifestyle advice to prevent T2DM [15]. The leaflet was provided by a different team member (i.e., not by the YOGA-DP instructor) to avoid contamination. This might have helped in lowering the attrition and made the control group participants feel that there were benefits to participation [15]. For this qualitative study, after the completion of the feasibility trial, intervention and control group participants who had completed six months of participation were recruited from both trial sites. One intervention group participant who stopped the intervention but continued participating in the trial was also interviewed to understand the barriers which hindered participation in the intervention group. They were invited to participate in a semi-structured interview with a trained qualitative researcher from the Centre for Chronic Disease Control (CCDC), New Delhi, India, not involved in the feasibility trial participant recruitment. Out of the total 65 participants who were randomised in the feasibility trial, 25 (38%) (13 intervention group, 12 control group) agreed to participate in the semi-structured interview. These interviews were conducted to identify and explore participants’ trial and intervention related barriers and facilitators. Although we started reaching data saturation by the sixth and seventh interviews in each group, we conducted further interviews to ensure that we did not miss any new and unique information and to cover a broader socio-demographic spread of participants [19,20]. The participant information sheet and consent form (available in Hindi, Kannada and English) were read and shared with participants before the interview. Written informed consent was obtained from those interested in participating, including for digital recording of interviews. The qualitative researcher conducted interviews, either face-to-face at the participants’ house (n = 12) or by telephone (n = 13) [21,22], depending on availability and convenience, from December 2019 to July 2020. The researcher spoke to the participants two to three times over the phone before the actual interview to become acquainted and make them comfortable about the interview process. Interviews were conducted in Hindi (n = 22), Kannada (n = 2) or English (n = 1) as preferred by the participants and using a pre-tested interview guide available in these languages. The female qualitative researcher is bilingual and fluent in English and Hindi and has experience in non-communicable diseases and health systems research in low- and middle-income countries. Kannada interviews were conducted with the help of an interpreter, who translated the interview questions from English to Kannada for participants and participants’ responses from Kannada to English for the researcher. The interpreter supported the researcher in the process of in-depth probing. The interview guide had some key open-ended questions, which were adapted to the participants’ responses and probed further to capture detail and develop a deeper understanding of each answer. The interviews were digitally recorded and transcribed verbatim by professional transcribers and then translated from Hindi to English by a professional translator if needed. Kannada interviews were transcribed and translated into English by the interpreter hired to assist in conducting Kannada interviews. The qualitative researcher ensured the quality of the final transcripts (for interviews in Hindi and English) by listening to the audio files and constantly comparing these with the transcripts to rule out the possibility of any missing data by the transcriber. Similarly, to ensure the quality of the Kannada transcripts, a local study staff member at SVYASA listened to the audio files in Kannada and compared these with the transcript to rule out the possibility of any missing data by the transcriber. During and after data collection, the qualitative researcher familiarised herself with the data by reading the transcripts multiple times. The researcher coded all the interviews using the interpretative phenomenological approach (IPA), and deductive logic with the help of QSR-NVivo 10 software for data management [23,24]. IPA helped in capturing the detailed overview of participants’ lived experiences, as it is not bound by any pre-existing theoretical preconceptions [23]. Interviews with the participants from both groups helped identify and explore the trial-specific barriers and facilitators. The interviews with intervention group participants were useful in understanding the specific barriers and facilitators of participation in the intervention. The researcher coded and analysed the interviews of the control group first and then the intervention group. The original data were reflected continuously to ensure participants’ experiences and perceptions were accurately captured. In the first stage of coding, the response from the participants was coded using meaningful chunky statements, and in the second stage, the chunky statements were reduced to fewer words to move closer to the ‘core essence’ [25]. Finally, in the third stage, the researcher encapsulated the ‘core essence’ of the central meaning of the participants’ lived experiences in one or two words [25]. After assigning codes to transcripts, summaries were prepared from the coded data. The summaries were organised into overarching categories and later assigned themes and sub-themes. The process was continuously discussed with the study investigators (including a senior qualitative researcher) for refinement. Once the emergent themes were captured, the researcher identified the connection between themes and organised them in chronological order, the way they emerged in the transcript and these themes were further organised in theoretical order to make sense of the connection between themes [25]. The data were interpreted using the language, metaphors, symbols, repetitions, pause and context of the participants and the initial reflexivity of the researcher using field diary and reflexivity notes [26]. The researcher was aware of her age, gender, affiliation with the study site (not a BNCHY staff member), the place of the interviews while preparing the reflexivity notes and their impact on interviews and interactions with participants. Ethics approval for this study was obtained from the following research ethics committees: Faculty of Medicine and Health Sciences, University of Nottingham (UK), CCDC (India), BNCHY (India) and SVYASA (India). 3. Results The median age of participants was 41 years, and 13 participants (out of 25) were female (Table 1). Interview duration ranged from 20 to 60 min (average 37 min). The average of the telephonic interviews was 33 min, and for face-to-face interviews, it was 41. Similarly, the average duration of Hindi interviews was 35, and for Kannada, it was 49 min. All the participants were married, and four of them had less than ten years of formal education. The gross monthly income of the participants ranged between INR 10,000 and 245,000. There were 11 participants who had a family history of diabetes. We identified and explored participants’ trial- and intervention-related barriers and facilitators. The findings are presented through four major themes, each of which has several sub-themes (Table 2). All participant quotes represented below are anonymised but attributed by age, gender and study arm. 3.1. Barriers to Trial Participation This theme captures the potential barriers that influenced a participant’s decision to participate in the feasibility trial. This theme captures the experiences and perceptions of both control and intervention group participants. Detailed information about recruitment and randomisation processes: Some participants were either unaware of the recruitment and randomisation processes or did not have adequate information about their recruitment to a particular group. Some of them thought they were recruited to a specific group because of their age and blood test report. “As far as I know, my sugar level (diabetes) is on the borderline, that is why. If I practice Yoga, I can prevent diabetes. They said that your sugar level is on the borderline if you continue practising Yoga, you can control (prevent T2DM)”. (Age: 33 years; Female; Intervention) Some participants assumed they were recruited to the control group because they had informed the site staff about their busy schedule, and also, they were not interested in practising Yoga. At the same time, many of them were not aware of the intervention group and mentioned their inclination toward joining the intervention group. Lack of detailed information about recruitment and randomisation and desire to get recruited in a particular group could have been a barrier in retaining participants in the trial. “Because I told them that I have lots of work to do in the morning and I do not have interest in it, so they did not keep me in Yoga group”. (Age: 43 years; Female; Control) Poor experience in the control group regarding the enhanced care leaflet: Some control group participants said they did not receive the enhanced care leaflet meant for the control group from the site staff. “No, I did not receive that. I just got a photocopy of my reports”. (Age: 64 years; Female; Control) Many participants acknowledged receiving the enhanced care leaflet, but they claimed that it was not of any use to them as they were already aware of the information mentioned in the leaflet. Some of them also misunderstood it only as a diet chart to be followed to prevent T2DM. “That (leaflet) had suggestions to increase everything that one was doing. As the Research Assistant asked me to increase exercise a little bit. Have more green vegetables… I got a little help. Nothing much because I knew everything (that was mentioned in the leaflet)”. (Age: 47 years; Male; Control) The negative influence of non-participants: Some non-participants in this study had tried to dissuade participants from taking part in the feasibility trial as they were of the view that the glucometer used at the time of screening gave false results. “Other people also got their tests done and learnt about their high Sugar, so they told us not to pay much attention and said that their machines were not working properly. There is no need for it; nothing will happen, and that it is not worth it”. (Age 44 years; Female; Intervention) Frequency of the blood test (e.g., FBG): The majority of participants opined that the blood test should be conducted once in the middle of the feasibility trial. They believed that the blood test after three months could have given a report about their health, and they could have taken health-related decisions based on that. “After receiving my recent report, I felt that if the test was done after three months, then I would have known that my sugar level had increased from 102 to 105 in 3 months, then I would have been more serious”. (Age: 27 years; Female; Control) 3.2. Facilitators to Trial Participation This captures the factors that facilitated the participation and retention of participants in the intervention and control group. Adequate information about the feasibility trial and processes: Some participants were employed at the site and were informed about the blood test and the YOGA-DP intervention by site staff. They were also aware that they were recruited into the feasibility trial as they were at risk of developing T2DM. These factors helped participants make an informed decision about taking part and adhering to the trial processes. “They informed me that Yoga sessions would take place, and I shall have to participate in that. They told me that they were doing some research, and they would assess the report of my blood test and decide. They told me that I would be given Yoga sessions at the site, and after that, I shall have to practice that at home”. (Age: 43 years; Male; Intervention) Some of the participants shared that they understood the randomisation and recruitment processes. They mentioned that the site staff had informed them about randomisation and recruitment to their respective groups, and they decided to be a part of that group and follow the processes. “They told me that one would be the Yoga group, and in the other group, only blood test and routine check-ups would be done. They told me that they would decide which group I would be recruited to. So, I agreed to that. So, they just gave me information that two groups will be formed”. (Age: 34 years; Female; Intervention) Free blood tests, positive experiences of the testing process: Many of the control group participants confirmed that they came for the screening because of the free of cost capillary blood test and confirmatory venous blood test. “I have to attend every camp which is organised free of cost… Now I usually have to go to the hospital for a check-up after making an appointment. After scheduling an appointment, I have to fast. Then they will check, and then the report comes on the next day; it becomes a bit hectic. That is why I do not prefer it”. (Age: 47 years; male; Intervention) None of the participants reported facing challenges during the blood sample collection, which was a positive experience. “It was good, and there was no problem”. (Age: 43 years; Female; Control) “No, I did not face any problem”. (Age: 43 years; Male; Intervention) Some participants mentioned that they appeared for the blood test only because the behaviour of the site staff made them comfortable, and they decided to appear for the test. Some of them also shared that the appointment for the blood test was made as per the participant’s preference, because of which they did not face any problem during the blood test. “… the person who collected my blood sample was very cooperative. When I went for the blood test he gave me 15–20 min of his time after every other patient left. Even last time, I was allotted 10:30 AM, but it took 15 min extra for me as I kept pulling away my arms out of fear. But he was very supportive”. (Age: 27 years; Female; Control) Some participants also mentioned that they trusted the laboratory and procedures followed during the blood test. Trust in the blood collection process and testing laboratory also positively influenced the participant’s decision to come for the blood test. “…there was nothing lacking as the laboratory where they performed the tests is a good one. I observed their process and (experienced) how responsibly they were handling us and performing our tests, which was very good to see”. (Age: 39 years; Female; Control) Some of the control group participants went for the blood test to find out if their glucose levels had increased. They mentioned that usually they went to a nearby dispensary to have a diabetes blood test but decided to come to the feasibility trial site as the test was already happening here “I thought that at least I would get to know if I have Sugar or not. I get it (test) done sometimes at the dispensary also. I decided to get it done since they were doing it. I didn’t see any problem in doing so. I get it (test) done sometimes at the dispensary also…So I went for the tests straight away as I had not eaten since morning”. (Age: 64 years; Female; Control) To gain adequate information to prevent T2DM: The motivation of the control group participants to participate in the feasibility trial was to prevent T2DM. They found it easier by enrolling in a programme that focused on T2DM prevention. “The biggest motivating to participate in this study was it was a win-win opportunity for me because I had to control (prevent) diabetes anyway. And you also wanted to recruit a person who is willing to control his diabetes. So, there was nothing to lose. So, I was motivated, and I thought that this was such good research and I should also become a part of it”. (Age: 47 years; Male; Control) Professional behaviour of the site staff: While talking about their experience at the trial site, many participants mentioned that the site staff were friendly. The behaviour of the site staff influenced many control group participants and positively impacted their decision to participate in the feasibility trial. “The best part I felt was your team; they supported me completely. They managed time according to my availability, whether it was the Trial Coordinator or the Research Assistant. So, it was nice. Instead of dictating us on time, you changed your timing according to the participant or client. Even if there was a delay, you adjusted accordingly. So, you gave priority to our preferences”. (Age: 47 years; Male; Control) The positive influence of friends: Many participants said their friends suggested that they go for the blood test. Friends also played a vital role in motivating participants to go for the blood test and participate in the feasibility trial. “They called everybody in my neighbourhood saying that they were conducting free blood tests, and everybody asked me, “Why do not you come?” So, I went for the tests as I was already on an empty stomach at that time”. (Age: 43 years; Female; Control) Trust in the trial sites and the range of healthcare services they provide: Some other participants trusted the health facility (feasibility trial site) and its staff; thus, they decided to come for the blood test. Trust was one of the key factors which facilitated participation in the intervention group. “I went there because a camp was organised. I knew about Bapu Nature (trial site) for quite some time. When I came here for tests, they told me that my sugar level was high”. (Male; Age: 44; Intervention) 3.3. Barriers to Participation in the Intervention This theme captures the barriers shared by the participants from the intervention group, which may have a bearing on adherence to the programme sessions. Difficulty in reading and understanding the language of the programme booklets: Some participants mentioned that the readability and understanding of the booklet were difficult, and they were unable to grasp the information provided in them. Because of the difficulty in readability and understanding, some of them could not use the booklet to change their lifestyle and practise Yoga. “It should have been easy so that people could understand it easily, like what all to avoid. What habit to develop and what to forgo. So, an easy language will make people understand it more easily”. (Age: 44 years; Male; Intervention) Difficulty in capturing the duration and sequence of the Yoga poses (asanas) in the programme diary: Participants shared their experience of filling up the programme diary as they could not capture the time spent for Yoga poses. Some of them could fill in the diary and follow the instructions given at the site-based sessions for the same. However, it was difficult for many others to fill in the details in the programme diary. “I used to find it difficult early on, but as I started to follow it, I did not find it difficult later. In the initial 1–2 pages, I thought as to how to mention time in this, but I got an idea later on”. (Age: 35 years; Female; Intervention) “Yes, it would have been better even without it (diary). If someone does not want to do it, he/she will fill it up without practising Yoga”. (Age: 44 years; Male; Intervention) Some participants also mentioned that they did not receive any diary from the site staff. Other participants did not have an adequate understanding of the diary. “I have not got the dairy. I follow the books which is given to me and during free time I practice (Yoga) also”. (Age: 33 years; Female; Intervention) “Yes, they asked us to mention what time we got up, what kind of breakfast we had, and what type of food we ate. We also had to mention the time of the food and what time we went to bed (to sleep). We also had to mention the changes that we had witnessed in the past six months”. (Age: 33 years; Male; Intervention) Lack of interest in filling in the diary and clarity about the same hindered monitoring of adherence to the unsupervised programme sessions among participants. Difficulty in using the programme video during unsupervised sessions: Intervention group participants were provided with a video to facilitate the unsupervised sessions. Some participants stated that they did not find the programme video useful, and they never used it and some of them used booklets for their unsupervised sessions. Perceived lack of usability of the programme video was a barrier to practising Yoga poses and adhering to the unsupervised sessions. “No, I have not watched that video even once, and I have not practiced Yoga since Sir (YOGA-DP instructor) taught us (stopped taking session). I have committed a mistake by not watching that video, but I will definitely watch it”. (Age: 25 years; Female; Intervention) “I found it easy with the book. I used to keep the book in front of me and finish the Yoga poses quickly. I was able to do it with the help of the book”. (Age: 44 years; Female; Intervention) Some of them suggested providing the web link for the video instead of providing a full-length video in a pen drive. Some of them also mentioned that they could not run the pen drive on their television. “If you could give us some link of the website or share any application that would have been helpful as these days people do not use pen drive you could have shared the videos over WhatsApp as well”. (Age: 33 years; Male; Intervention) Poor quality of Yoga mats: Some participants registered complaints about the hardness of the Yoga mats and noted that the quality of the Yoga mat could have been better. Poor quality Yoga mats caused discomfort among participants and emerged as a barrier in practising Yoga poses. “The quality of the mats is not good because it is very thin when you practice Yoga on it. Sometimes it feels that our hand is stuck to the mat. And in the thicker mats, there is no such problem in practising”. (Age: 47 years; Male; Intervention) Household commitment and unavailability of the YOGA-DP instructors hindered unsupervised sessions: After completing three months of supervised sessions, intervention group participants had to complete 21 unsupervised sessions at home. Most participants said that it was challenging for them to practice Yoga at home due to their household responsibilities. The household commitment was one of the barriers to adherence to the programme sessions. “Here, she would make us relax. At home, these things were not possible because we had household responsibilities. I would do the same exercise at home for 35–40 min, but here I might do it for two hours. So, this happened with me at home”. (Age: 62 years; Female; Intervention) Some of the participants explained that they could not adhere to the timing and subsequent steps of the Yoga poses in the unsupervised sessions. They also mentioned that there was no one to rectify their mistakes in the unsupervised session and help them with practising Yoga poses. Lack of supervision and support was also a barrier in adherence to programme sessions. “Yes, you can say that household responsibility was a factor, but I did not enjoy a Yoga session without supervision. There should be someone to teach us how to do and what to do”. (Age: 36 years; Male; Intervention) Missed supervised sessions due to unplanned travel: Many intervention group participants had to miss a few sessions due to unplanned travel; however, they attended compensatory sessions after returning. One of the participants also had to rush through one of the sessions because of her unexpected travel. “I did not miss it actually, but rushed through my session in a hurry, as there was some family function and I had to leave with someone for that”. (Age: 35 years; Female; Intervention) “Sir (YOGA-DP Instructor) used to make me do everything that I used to miss in those two classes. It’s not as if I’ve missed anything”. (Age: 25 years; Female; Intervention) Difficulty in practising Yoga poses: Some of the intervention group participants said that they did not have any experience of Yoga, and they faced some difficulty in practising different Yoga poses, such as sun salutation (surya namaskar) in the beginning. “At the outset, as it happens with everyone, I also had some difficulty, but later on with practice, everything got normal, and I did not face any problem. Everything is a little difficult at the beginning. In the beginning, it was difficult. Later on, there was no problem, and I started liking it (Yoga)”. (Age: 36 years; Male; Intervention) They mentioned that with practice, they were able to do it with ease after some time. Some of them could not practice these exercises because of their existing health-related conditions. “When I started doing it, sometimes I pulled my veins and developed pain in my legs. When I used to go back after doing Yoga, then while climbing stairs, I felt a pull in my veins. When I continued doing it, it gradually got loose. For a week or two, I used to think, “what I have chosen to be a part of?” I felt as if my body was aching even more. But after continuing with it, it gradually got better”. (Age: 43 years; Male; Intervention) Some male participants shared that they had to miss a few sessions because of their health issues, such as fever or hypertension, whereas some female participants missed their sessions on their menstruation days. “I missed 1–2 classes due to (increase in) Blood Pressure, but I completed it later on”. (Age: 43 years; Male; Intervention) “I used to miss my classes during my periods, or if I had to go to my mother’s house”. (Age: 25 years; Female; Intervention) Difficulty in practising Yoga poses was a barrier for some participants, who had never practised Yoga before. This could have affected adherence to programme sessions among participants. Hesitation in attending programme sessions with the YOGA-DP instructor of the opposite sex: Some of the male participants reported their discomfort while practising Yoga under the supervision of a female YOGA-DP instructor. They mentioned that with male YOGA-DP instructors, they could share their problems openly but not with the female YOGA-DP instructor, which negatively influenced their practice of Yoga poses. “…sometimes the Yoga Instructor Sir (YOGA-DP instructor) was not available, so we used to ask the Yoga Instructor Ma’am (YOGA-DP instructor) to do it (to take YOGA-DP sessions), but we used to feel uncomfortable in that. We preferred the Yoga Instructor, Sir”. (Age: 43 years; Male; Intervention) Similarly, some female participants shared that they preferred the female YOGA-DP instructor. They felt that they would have felt cautious about their clothes and body movement with a male YOGA-DP instructor. Different gender of the YOGA-DP instructor was also cited as one of the barriers across male and female groups. “When I came here, they told me in the first meeting that male participants will get training from the male instructor (YOGA-DP instructor) and females will get from a female instructor (YOGA-DP instructor), which attracted me a lot. Ladies sometimes wear clothes with deep necks, we also have to raise our legs during exercise, everything has to be done, so I liked this thing here that male got training from the male instructor and female got from the female instructor”. (Age: 44 years; Female; Intervention) Hesitation in attending group programme sessions: Some participants stated that they preferred individual sessions. They felt that in individual sessions, YOGA-DP instructors could pay more attention to one participant, which was not possible in a group session. One of the participants also shared that he was hesitant in attending a group session as he did not want others to laugh at him if he could not do a particular Yoga pose properly. Thus, group sessions were found to be a barrier for some participants in attending the programme sessions. “I feel that for those who do not know Yoga for them, individual sessions are better. If I do not know anything, the instructor (YOGA-DP instructor) can pay more attention to teaching me in an individual session than in group sessions. As we were given private sessions, she paid attention to us…” (Age: 44 years; Female; Intervention) “People may laugh at you if you practice Yoga in a group. Suppose someone is able to do any Yoga pose, and the other person is not able to do properly, everyone thinks differently, but people may laugh at you”. (Age: 44 years; Male; Intervention) Some participants suggested that there should be separate groups for young and old participants as they felt that the pace of doing exercise was slower among older adults. Group composition also influenced the practice of Yoga poses among participants. “It should be age-wise. Because Young people are able to do it (practice Yoga) quickly and old people take time in doing it”. (Age: 40 years; Female; Intervention) 3.4. Facilitators to Participate in the Intervention This theme captures the key factors based on the experiences and perceptions of the participants, which facilitated participation in the intervention group. Programme booklets helped in adhering to the unsupervised programme sessions: While talking about their experience with the programme booklet, some participants felt that they had limited opportunity to read the booklet. They said that they read the booklet as and when they have time. However, many participants also mentioned that they read the booklet and referred to that during the home-based sessions. They used the booklet to know the exact pose and sequence of Yoga poses. They were of the view that pictures were helpful in understanding various steps of the Yoga poses. “I used to refer to the book and practice. I used to keep the book with me while practising Yoga at home, it helped me, and otherwise, it was difficult to remember. The book helped me in remembering the steps”. (Age: 36 years; Male; Intervention) Adequate information on T2DM prevention and self-care: Many participants pointed out that when they got to know that they were at a high risk of developing T2DM, they wanted to prevent the condition, which motivated them to come for the programme sessions. “Actually, I had not imagined that I would be pre-diabetic. So, next day only, Sir (Trial Coordinator) told me that you are (at) pre-diabetic (stage) and we are organising Yoga classes, so will you participate in it? So, I replied yes, I will, because I wanted to cure myself, as no one in my family has it (diabetes)”. (Age: 25 years; Female; Intervention) Some other participants said that they were motivated to participate in the session because they could take out time for self-care by doing that. Programme sessions gave them a sense of self-care which motivated them to spare time to come for the sessions and practice Yoga. “It is just that I was taking out two hours time from my schedule and practising Yoga. The YOGA-DP instructor taught us well… No, I also used to feel relaxed. My body was relaxed, and I felt light”. (Age: 60 years; Female; Intervention) Many participants liked being in the intervention group as they learnt something, and also lost body fat. They also mentioned that had they been in the other group, they would not have learnt anything. They believed that they could practice Yoga only because they were part of this group, and thus, they adhered to the programme sessions. “I liked being in this group because I got to learn something new. Because I would never have practiced Yoga any other way, but when I was recruited to this group (intervention group), I thought I would learn something new. I thought of trying it because I love to do a new thing, so I found this thing right”. (Age: 47 years; Male; Intervention) Good venue and other support provided for programme sessions: Some participants mentioned specific factors because of which they could attend the programme sessions. For example, proximity to the programme venue helped them participate in the sessions. “Yes, because I had time and also because this place was closer to my house. I had various reasons to come here. First, it is beneficial for our health, secondly because of time, thirdly because it is close to my house. It was a combination of all three factors which helped me to participate in the study”. (Age: 44 years; Male; Intervention) “I would have skipped it if it was far from my home”. (Age: 35 years; Female; Intervention) Participants also discussed their experiences at the venue, which influenced adherence to the programme sessions. Many participants felt that the venue was comfortable, and the hall was big. They felt comfortable at the venue while practising Yoga poses. “No, it (venue) was comfortable only. The group was small. It was comfortable, there was no problem in that (venue)”. (Age: 36 years; Male; Intervention) Some participants reported that support and props provided as part of this feasibility trial, such as mats, pen drive and travel reimbursement, motivated them to attend the programme sessions. “…nobody in this world will give you anything for free, including Yoga classes, CDs, Yoga Mats, uniform etc., and nobody is bothered about you. Everybody thinks about themselves only. If the government (Research Team) is giving us Yoga classes, uniforms, Yoga mats for free, why should not we go there?” (Age; 33 years; Male; Intervention) Professional behaviour of the YOGA-DP instructors: Invariably, at both sites, all the intervention group participants had a good experience with the YOGA-DP instructor and received all the help they required at the site. Some other participants felt gratitude for the YOGA-DP instructor as they were not charging for the sessions and imparting training for the betterment of the participants’ health. They also mentioned that they acquired motivation from the YOGA-DP instructor to come for the sessions. “They used to call us frequently. YOGA-DP instructor was never strict with us, even if we had to miss a few sessions due to some personal reasons. He would motivate us for the next session. He would explain everything nicely about the exercise and body. He was not benefiting from that personally, but he was doing that for us as he never charged money. He was doing everything for us. He did not think about his benefits but thought about us”. (Age: 36 years; Male; Intervention) Some participants mentioned that they liked the YOGA-DP instructor’s approach of demonstrating all the Yoga poses by practising in front of participants. They also appreciated the YOGA-DP instructor for their problem-solving attitude. The demonstration of Yoga poses by the YOGA-DP instructor helped participants in practising them with precision. “He used to work hard with me. I have seen trainers at other places who teach you Yoga once or twice and after that ask you to do it on your own. But he (YOGA-DP Instructor) stayed with me throughout and used to practice Yoga with me. Since I did not do Yoga before, so he would teach me by practising on his own”. (Age: 43 years; Male; Intervention) Some participants pointed out that the YOGA-DP instructor was punctual, and they never had to wait at the site. They said YOGA-DP instructors provided care to them and used to ask them about their well-being and Yoga practice at home, which made them adhere to the programme sessions at the site. “Because if we had to come here by 6 am, YOGA-DP instructor would be here at that time, even before that. We never had to wait for her. She fully cooperated with us”. (Age: 44 years; Female; Intervention) “If they did not call us (for supervised sessions), they used to ask about it (unsupervised sessions at home) when we used to go for sessions site-based (supervised) sessions. They used to ask about our sessions, if we had filled our notebook (YOGA-DP Diary), about the duration of our session, diet control etc”. (Age: 44 years; Female; Intervention) The new learning experience of Yoga: One participant was motivated to participate in the feasibility trial because she found this research good. She wanted to step out and learn something new, which motivated her to participate. Innovative experience and perceived lack of harm because of Yoga positively influenced participants’ decisions to participate in the intervention group. “One reason was that when we step outside, we learn something or the other. Another reason was if Yoga does not benefit us, it would not harm us either. So, I can take out 1 h for Yoga, and there is no harm in doing it”. (Age: 35 years; Female; Intervention) Improvements to physical and mental well-being: Positive physical and mental changes after joining the programme session were mentioned, such as changes in body shape, weight and flexibility. Some participants mentioned that their stress level had reduced and they could sleep appropriately, which motivated them to practice Yoga poses. “Yes, there has been a lot of changes physically. My belly size had increased way too much, which is fine now. I feel a lot more active than before”. (Age: 40 years; Female; Intervention) Some of them also witnessed a change in their behaviour and lifestyle after participating in the programme sessions. Yoga poses also helped them with managing their stress and anxiety, which motivated them to come for the programme sessions. “Earlier, I used to get irritated and got angry a lot. After these sessions, I feel like staying cool. If my kids are doing something, I am like, “It is okay, and you can continue doing it for a while”. I feel as if some positivity is there after doing this (practicing Yoga)”. (Age: 44 years; Female; Intervention) Scheduling programme sessions as per participants’ preferences: Some participants reported developing a routine because of participating in this intervention. They mentioned they started getting up early in the morning and practising Yoga more systematically in a time-bound fashion. Yoga helped many participants follow a disciplined lifestyle which motivated them to adhere to the programme sessions. “Earlier I used to get up late but now I get up by 6 or 7 am. After that I practice Yoga. It is better than what it was before”. (Age: 36 years; Male; Intervention) “Good things have happened because previously I used to practice whenever I got time, and now madam (YOGA-DP Instructor) started teaching yoga systematically and properly, and I am following that”. (Age: 33 years; Female; Intervention) Some participants felt excited to attend the programme sessions, and they also asked the YOGA-DP instructor for extra sessions. One participant felt trapped after getting recruited to the intervention group; however, he started liking the programme sessions with time and the help of the YOGA-DP instructor. Thus, participants’ interest in Yoga also motivated them to participate in the programme sessions infallibly. “Yes, in the beginning, I felt like I got trapped. I am telling you. But our YOGA-DP instructor said that “try it once or twice; after that, you share your experience”. When I started, I felt happy. I thought that this was a good thing, and gradually I developed an interest in this. It was better than that because I do not like restrictions”. (Age: 47 years; Male; Intervention) Some participants also had a specific liking for different Yoga poses. These Yoga poses helped them start their day with positive energy. Liking for various Yoga poses also made many participants adhere to the programme sessions. “I liked a few things in the starting, one was sun salutation and boat pose also, I had to raise my leg and sit. Everything was new to me”. (Age: 47 years; Male; Intervention) “I liked doing sun salutation, the whole cycle of it. I used to sweat in it and feel energy afterwards. I liked it. I like doing it at home too, even if I am able to do only one cycle. After waking up in the morning, I do one cycle of it, get activated and get on with my work”. (Age: 35 years; Female; Intervention) Some participants joined the programme sessions as they were free, while others joined because they felt grateful that someone else was making efforts to take care of their health. The free viability of Yoga training and the selfless attitude of the YOGA-DP instructors facilitated participation in the intervention group. “…what happens is, people, pay to do Yoga outside (instructors or Yoga institutes) and here we were taught Yoga for free, so I felt nice about it”. (Age: 57 years; Male; Intervention) While discussing session preferences, many participants preferred sessions on weekends as they were free from family and professional responsibilities. Many also preferred morning sessions. Thus, the availability of sessions as per participants’ convenience helped participants to come for the programme sessions. “My kids have their holidays on weekends, so we used to go to classes while our kids were asleep. Also, our main objective was to do Yoga on an empty stomach in the morning; that is why we used to come in the morning”. (Age: 44 years; Female; Intervention) “On Sundays, kids have their holiday, so a person is mostly free during morning and evening. On Saturdays too, I am busy as I drop my kids to school”. (Age: 43 years; Male; Intervention) Most participants felt the frequency of the programme sessions should be increased from two days as they wanted to come for the sessions more frequently. Some participants also requested the study team to continue the sessions even after the completion of the feasibility trial. “I did not find anything lacking in these sessions; everything was perfect. All I can say is that you can perhaps increase the number of classes from two (sessions) a week. There are seven days, so out of that (sessions) can be organised on three days perhaps”. (Age: 35 years; Female; Intervention) Participants also preferred group sessions over individual sessions. They believed individual sessions were boring, whereas, in a group session, they learnt from each other, and in a group, they felt competitive and tried to outperform other participants. Thus, the participants who preferred group sessions were invited in a group which made them adhere to the programme sessions. “Group sessions are good, but individual session is not good. Individual sessions are boring. What will you teach a single person? Group sessions are more enjoyable than individual sessions. In a group, you get to learn by seeing others”. (Age: 36 years; Male; Intervention) “The important thing is that it is good to practice Yoga in a group, as we compete with each other. As I am doing better than him, he is not doing better than me”. (Age: 33 years; Male; Intervention) 4. Discussion This qualitative study explored trial-and intervention-related barriers and facilitators within a feasibility RCT of a Yoga-based intervention to prevent T2DM among high-risk people in India. The various trial-related barriers included inadequate information about the recruitment and randomisation processes, as explored in previous studies [27,28]. One of the possible reasons for inadequate information among participants could be the gap (six months) between the trial and in-depth interviews, due to which they could not recall the procedure. Many participants in the control group felt that they were recruited into this group because of their blood glucose level as compared to the participants in the intervention group. Some of them knew about the two groups in the feasibility trial but were not concerned about how and why they were recruited to a certain group and were not aware of the aim of the randomisation. Some of them also had poor experiences regarding the enhanced care leaflet. Most of the participants in the trial were happy with the blood sample collection and appreciated that the site made appropriate arrangements for the participants according to their convenience. However, most suggested that a blood test should have happened after three months to provide information about their health. However, some participants accepted the frequency of the blood tests and felt that a test before six months would not have shown anything about their health. We systematically developed the YOGA-DP intervention after reviewing the scientific literature and summarised “the heterogeneous contents of successful and relevant Yoga interventions” [15]. We involved a range of stakeholders, including healthcare, medical and Yoga experts and practitioners and the public, to explore the issues of safety and acceptability [15]. Some of the barriers reported by intervention group participants included difficulty in comprehending the language of the programme booklets, difficulty in capturing duration and sequence of the Yoga poses in the programme diary, poor quality Yoga mats, problems with the Yoga videos, difficulty in practising Yoga poses and household commitment during the unsupervised sessions. A previous study on barriers and facilitators in physical activity participation among women also identified that lack of time prevented many from getting involved in physical activity [29]. We also found that group sessions could be a facilitator (for those who found them motivating) or a barrier (for those who preferred individual sessions or were concerned with gender or mixed-age groups). A previous study has also highlighted that fear of being compared to others in the Yoga session was a barrier to participation in the study [30]. There were many facilitators, such as adequate information provided on T2DM prevention and self-care, good venue and other support provided for the programme sessions, cordial behaviour of the YOGA-DP instructors, improvements to physical and mental well-being, learning something new and scheduling programme sessions as per participants’ preferences. The desire to improve physical health and mood and try something new were the few facilitators to participation in a previous study on Yoga intervention as well [30]. Reasons to take part included the prevention of T2DM and weight loss. Other participants referred to the YOGA-DP instructor’s altruism and the research staff that motivated them to adhere to the programme sessions. Previous studies have also highlighted that conditional altruism made many participants participate in a study [31,32]. For other participants, free Yoga classes and proximity to the venue was essential in keeping them motivated to adhere to the programme sessions. Most participants reported no challenges in attending the programme sessions and practising the exercises, and no serious adverse events were recorded. Muscle pain and soreness were reported by some at the start of the session, which they overcame with their regular practice. This is consistent with prior work on reporting similar symptoms among Yoga participants [33]. Intervention group participants found the programme booklet helpful while practising at home as compared to the video, which many of them could not watch. However, almost all participants reported that they could not practice Yoga at home in a disciplined manner, following recommended frequency and duration, because of the unsupervised nature of the home-based sessions. They did not have any motivation to adhere to the programme session at home as there was no one to help them with their practice and rectify their mistakes. Intervention group participants also mentioned that they had developed a very good relationship with the YOGA-DP instructors because of their positive and professional attitude. In Bengaluru, an opposite-sex YOGA-DP instructor was acceptable, although this was not the case at the Delhi site. While developing our intervention, we had already taken the gender of participants and YOGA-DP instructors into consideration and recruited both male and female YOGA-DP instructors for the participants to make the intervention more acceptable [15]; however same-sex YOGA-DP instructors were not available on some occasions. The crucial facilitators based on the positive experience of participants included free blood tests, cordial behaviour of the site staff and improvements to physical and mental well-being. A number of suggestions were made for the future main RCT, including improving the quality of the Yoga mats, readability and understanding of the YOGA-DP booklets and the programme video (and/or making it available online or via WhatsApp) and increasing the frequency of YOGA-DP sessions. Strengths and Limitations of the Study To the best of our knowledge, this is the first qualitative study identifying and exploring the barriers and facilitators in conducting a Yoga-based trial to prevent T2DM among high-risk individuals in India. One of the strengths of this study is that we were able to recruit participants from diverse sociodemographic backgrounds, age-range and languages spoken, which helped in identifying and exploring the intervention- and trial-related barriers and facilitators in a more inclusive way. Though we started reaching data saturation in the responses of participants after six or seven interviews in both groups, we continued interviewing more participants to capture any unique specific information [19,20]. One of the limitations of this study was that many interviews were conducted over the telephone due to the COVID-19 pandemic, which hampered ice-breaking with the participants and observation of their body language and facial interaction while conducting the semi-structured interview. Though the researcher spoke to the participants twice or thrice before the actual interview, in-person interviews could have generated more data based on participant observation as some of the telephonic interviews conducted in Kannada and Hindi were short in duration. Another limitation was that participants who were lost to follow-up when contacted over the phone [34], did not agree to participate in this qualitative study. One intervention group participant who stopped the intervention but continued participating in the trial was also interviewed. 5. Conclusions We identified and explored participants’ trial- and intervention-related barriers and facilitators, which will inform the design of the planned definitive RCT design and intervention, as well as other Yoga interventions and RCTs. We will address the issues that negatively influenced the trial and intervention participation and adherence and promote the facilitators to improve trial and intervention participation and adherence. In this study, we could identify an almost equal number of barriers (n = 12) and facilitators (n = 13); however, intervention-related barriers and facilitators were more than for participation in the trial. Acknowledgments The authors would like to extend thanks to all those who participated in the study. Author Contributions K.C. conceptualised and designed the study with the help of T.H., S.M.G., M.H., S.A.L., N.K.M., N.T., S.K. and D.P.; P.M. collected and analysed the data and wrote the first draft of the manuscript with the help of K.C.; K.C., T.H., S.M.G., M.H., S.A.L., K.S., R.N., S.M., N.K.M., N.T., S.K. and D.P. contributed significantly to the revision of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was reviewed and approved by the following research ethics committees: Faculty of Medicine and Health Sciences, University of Nottingham, UK; CCDC, India; BNCHY, India; and SVYASA, India. The participants provided their written informed consent to participate in this study. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper if applicable. Data Availability Statement The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ijerph-19-05514-t001_Table 1 Table 1 Sociodemographic details of participants. n = 25 Intervention = 13 Control = 12 Intervention Group Control Group Sociodemographic characteristics Age (years) 25–64 (range) (Median 41) 25–60 (range) (Median 41.5) 28–64 (range) (Median 41) Sex Female 13 7 6 Male 12 7 5 Marital status Married 25 14 11 Formal education (years) ≤10 4 1 3 >10 21 13 8 Employed Yes 15 7 8 No 10 7 3 Gross monthly household income (INR) 10,000–245,000 (range) (median 25,000) 10,000–80,000 (range) (median 20,000) 12,000–245,000 (range) (median 42,000) Family history of diabetes 11 6 5 ijerph-19-05514-t002_Table 2 Table 2 Themes and sub-themes. Themes Sub-Themes Barriers to trial participation Detailed information about recruitment and randomisation processes Poor experience in the control group regarding the enhanced care leaflet The negative influence of non-participants Frequency of the blood test (e.g., FBG) Facilitators to trial participation Adequate information about the trial and related processes Free blood tests and positive experience of the testing process To gain adequate information to prevent T2DM Professional behaviour of the site staff The positive influence of friends Trust in the trial sites and the range of healthcare services they provide Barriers to participation in the intervention Difficulty in reading and understanding the language of the programme booklets Difficulty in capturing duration and sequence of the Yoga poses (asanas) in the programme diary Difficulty in using the programme video during unsupervised sessions Poor quality of Yoga mats Household commitment and unavailability of the YOGA-DP instructors hindered unsupervised programme sessions Missed supervised sessions due to unplanned travel Difficulty in practising Yoga poses Hesitation in attending programme sessions with the YOGA-DP instructor of the opposite sex Hesitation in attending group programme sessions Facilitators to participate in the intervention Programme booklets helped in adhering to the unsupervised programme sessions Adequate information was provided on T2DM prevention and self-care Good venue and other support provided for programme sessions Professional behaviour of the YOGA-DP instructors The new learning experience of Yoga Improvements to physical and mental well-being Scheduling programme sessions as per participant’s preferences Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. International Diabetes Federation (IDF) IDF Diabetes Atlas 9th ed. International Diabetes Federation Brussels, Belgium 2019 2. Anjana R.M. Pradeepa R. Deepa M. Datta M. Sudha V. Prevalence of diabetes and prediabetes in urban and rural India: Phase I results of the ICMR-INDIAB study Diabetologia 2011 54 3022 3027 10.1007/s00125-011-2291-5 21959957 3. National Institute for Health and Care Excellence (NICE) Preventing Type 2 Diabetes: Risk Identification and Interventions for Individuals at High Risk NICE Manchester, UK 2012 4. Gulati S. Mishra A. Sharma M. Dietary fats and oils in India Curr. Diabetes Rev. 2017 13 438 443 10.2174/1573399812666160811165712 27501784 5. Minocha S. Thomas T. Kurpad A.V. Are ‘fruits and vegetables’ intake really what they seem in India? Eur. J. Clin. Nutr. 2018 72 603 608 10.1038/s41430-018-0094-1 29459786 6. Medical Research Council (MRC) Developing and Evaluating Complex Interventions MRC London, UK 2008 7. Anderson J.G. Taylor A.G. The metabolic syndrome and mind-body therapies: A systematic review J. Nutr. Metab. 2011 2011 276419 10.1155/2011/276419 21773016 8. Anjana R. Ranjani H. Unnikrishnan R. Weber M. Mohan V. Narayan K.V. Exercise patterns and behaviour in Asian Indians: Data from the baseline survey of the diabetes community lifestyle improvement program Diabetes Res. Clin. Pract. 2015 107 77 84 10.1016/j.diabres.2014.09.053 25458336 9. Feuerstein G. The Deeper Dimensions of Yoga: Theory and Practice Shambhala Publications Boston, MA, USA 2003 10. National Health Service (NHS) A Guide to Yoga: Exercise 2018 Available online: https://www.nhs.uk/live-well/exercise/guide-to-yoga/ (accessed on 2 September 2019) 11. Cramer H. Lauche R. Haller H. Steckhan N. Michalsen A. Dobos G. Effects of Yoga on cardiovascular disease risk factors: A systematic review and meta-analysis Int. J. Cardiol. 2014 173 170 183 10.1016/j.ijcard.2014.02.017 24636547 12. Cramer H. Langhorst J. Dobos G. Lauche R. Yoga for metabolic syndrome: A systematic review and meta-analysis Eur. J. Prev. Cardiol. 2016 23 1982 1993 10.1177/2047487316665729 27550905 13. Kumar V. Jagannathan A. Philip M. Thulasi A. Angadi P. Raghuram N. Role of Yoga for patients with type II diabetes mellitus: A systematic review and meta-analysis Compl. Ther. Med. 2016 25 104 112 10.1016/j.ctim.2016.02.001 14. Cui J. Yan J.-H. Yan L.-M. Pan L. Le J.-J. Guo Y.-Z. Effects of Yoga in adults with type 2 diabetes mellitus: A meta-analysis J. Diabetes Investig. 2017 8 201 209 10.1111/jdi.12548 15. Chattopadhyay K. Mishra P. Manjunath N.K. Harris T. Hamer M. Greenfield S.M. Wang H. Singh K. Lewis S.A. Tandon N. Development of a yoga program for type-2 diabetes prevention (YOGA-DP) among high-risk people in India Front. Public Health 2020 8 548674 10.3389/fpubh.2020.548674 33313032 16. Chattopadhyay K. Mishra P. Singh K. Harris T. Hamer M. Greenfield S.M. Lewis S.A. Manjunath N.K. Nair R. Mukherjee S. Yoga programme for type-2 diabetes prevention (YOGA-DP) among high risk people in India: A multicentre feasibility randomised controlled trial protocol BMJ Open 2020 10 e036277 10.1136/bmjopen-2019-036277 32895271 17. Mishra P. Greenfield S.M. Harris T. Hamer M. Lewis S.A. Singh K. Nair R. Mukherjee S. Manjunath N.K. Harper D.R. Yoga program for type 2 diabetes prevention (YOGA-DP) among high-risk people: Qualitative study to explore reasons for non-participation in a feasibility randomized controlled trial in India Front. Public Health 2021 9 682203 10.3389/fpubh.2021.682203 34540780 18. Buysschaert M. Medina J.L. Buysschaert B. Bergman M. Definitions (and current controversies) of diabetes and prediabetes Curr. Diabetes Rev. 2016 12 8 13 10.2174/1573399811666150122150233 25612821 19. Green J. Thorogood N. Qualitative Methods for Health Research 3rd ed. SAGE London, UK 2014 20. Given L.M. The SAGE Encyclopedia of Qualitative Research Methods SAGE Thousand Oaks, CA, USA 2008 Volume 1 21. Cachia M. Millward L. The telephone medium and semi-structured interviews: A complementary fit Qual. Res. Organ. Manag. 2011 6 265 277 10.1108/17465641111188420 22. Musselwhite K. Cuff L. McGregor L. King K.M. The telephone interview is an effective method of data collection in clinical nursing research: A discussion paper Int. J. Nurs. Stud. 2007 44 1064 1070 10.1016/j.ijnurstu.2006.05.014 16844128 23. Smith J.A. Flowers P. Larkin M. Interpretative Phenomenological Analysis SAGE London, UK 2009 24. Douglas E.P. Beyond the interpretive: Finding meaning in qualitative data Proceedings of the ASEE Annual Conference and Exposition Columbus, OH, USA 24–28 June 2017 25. Alase A. The Interpretative Phenomenological Analysis (IPA): A Guide to a Good Qualitative Research Approach IJELS 2017 5 9 19 10.7575/aiac.ijels.v.5n.2p.9 26. Pietkiewicz I. Smith J.A. A practical guide to using interpretative phenomenological analysis in qualitative research psychology Pycho. J. 2012 18 361 369 27. Kombe M.M. Zulu J.M. Michelo C. Sandøy I.F. Commmunity perspectives on randomisation and fairness in a cluster randomised controlled trial in Zambia BMC Med. Ethics 2019 20 99 10.1186/s12910-019-0421-7 31864351 28. Grant J.B. Mackinnon A.J. Christensen H. Walker J. Participants’ perceptions of motivation, randomisation and withdrawal in a randomised controlled trial of interventions for prevention of depression J. Med. Ethics 2009 35 768 773 10.1136/jme.2008.028035 19948934 29. Mathews E. Lakshmi J.K. Ravindran T.K. Pratt M. Thankappan K.R. Perceptions of barriers and facilitators in physical activity participation among women in Thiruvananthapuram City, India Glob. Health Promot. 2016 23 27 36 10.1177/1757975915573878 30. Combs M.A. Thron B.E. Barriers and facilitators to yoga use in a population of individuals with self-reported chronic low back pain: A qualitative approach Complement. Ther. Clin. Pract. 2014 20 268 275 10.1016/j.ctcp.2014.07.006 25130139 31. McCann S.K. Campbell M.K. Entwistle V.A. Reasons for participating in randomised controlled trials: Conditional altruism and considerations for self Trials 2010 11 31 10.1186/1745-6215-11-31 20307273 32. O’Keeffe S. Weitkamp K. Isaacs D. Target M. Eatough V. Midgley N. Parents’ understanding and motivation to take part in a randomized controlled trial in the field of adolescent mental health: A qualitative study Trials 2020 21 1 13 10.1186/s13063-020-04857-3 31898511 33. Cramer H. Ward L. Saper R. Fishbein D. Dobos G. Lauche R. The Safety of Yoga: A systematic review and meta-analysis of randomized controlled trials Am. J. Epidemiol. 2015 182 281 293 10.1093/aje/kwv071 26116216 34. Saarijärvi M. Bratt E.L. When face-to-face interviews are not possible: Tips and tricks for video, telephone, online chat, and email interviews in qualitative research Eur J. Cardiovasc Nurs. 2021 20 392 396 10.1093/eurjcn/zvab038 33893797

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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092723 molecules-27-02723 Perspective Drug Repurposing for COVID-19: A Review and a Novel Strategy to Identify New Targets and Potential Drug Candidates Rodrigues Liliana *† Bento Cunha Renata † Vassilevskaia Tatiana https://orcid.org/0000-0001-9676-6251 Viveiros Miguel Cunha Celso Larue Ross Academic Editor Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Rua da Junqueira 100, 1349-008 Lisboa, Portugal; rbentocunha@ihmt.unl.pt (R.B.C.); tatianav@ihmt.unl.pt (T.V.); mviveiros@ihmt.unl.pt (M.V.); ccunha@ihmt.unl.pt (C.C.) * Correspondence: lrodrigues@ihmt.unl.pt † These authors contributed equally to this work. 23 4 2022 5 2022 27 9 272321 3 2022 21 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) was first identified in the province of Wuhan, China. Since then, there have been over 400 million confirmed cases and 5.8 million deaths by COVID-19 reported worldwide. The urgent need for therapies against SARS-CoV-2 led researchers to use drug repurposing approaches. This strategy allows the reduction in risks, time, and costs associated with drug development. In many cases, a repurposed drug can enter directly to preclinical testing and clinical trials, thus accelerating the whole drug discovery process. In this work, we will give a general overview of the main developments in COVID-19 treatment, focusing on the contribution of the drug repurposing paradigm to find effective drugs against this disease. Finally, we will present our findings using a new drug repurposing strategy that identified 11 compounds that may be potentially effective against COVID-19. To our knowledge, seven of these drugs have never been tested against SARS-CoV-2 and are potential candidates for in vitro and in vivo studies to evaluate their effectiveness in COVID-19 treatment. SARS-CoV-2 COVID-19 drug repurposing computer-aided drug discovery ==== Body pmc1. Introduction The emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) created a worldwide public health emergency. SARS-CoV-2 is the causative agent of coronavirus disease 2019 (COVID-19) and was first isolated during an outbreak of SARS in the province of Wuhan, China, in December 2019 [1]. Due to its rapid dissemination to several countries and virtually all continents, the World Health Organization (WHO) declared a pandemic in March 2020 and there have been over 400 million confirmed cases and 5.8 million deaths of COVID-19 reported worldwide until February 2022 [2]. At present, the situation is still vastly uncontrolled in many parts of the world. Coronaviruses are large, enveloped, positive-sense, single-stranded RNA viruses found to infect different animal species, including reptiles, birds, and mammals. It has been widely reported that coronaviruses, similarly to other viruses, can occasionally “jump” between species and adapt to the new host. The Middle East respiratory syndrome coronavirus (MERS-CoV) and the severe acute respiratory syndrome coronavirus (SARS-CoV) are recent examples of the adaptation to infect and replicate in humans of coronaviruses previously thought to be confined to their natural host reservoirs—bats. However, zoonotic transmission of MERS and SARS-CoV to humans was not direct but rather involved as intermediate hosts, dromedary camels and civets, respectively. Similarly to MERS-CoV and SARS-CoV, SARS-CoV-2 perhaps also had a zoonotic origin. It is probably that it also originated in bats, but an intermediate host could not still be unequivocally identified. SARS-CoV-2 is primarily transmitted through direct contact with respiratory virus-containing droplets and aerosols from infected individuals. Coughing, sneezing, and nasal discharge are important sources of contagium. However, the identification of SARS-CoV-2 genetic material in several organs points to a broad tropism, not only restricted to the upper and lower respiratory tracts. This may partly be explained by the fact that the main cellular receptor for SARS-CoV-2, angiotensin-converting enzyme 2 (ACE-2), is expressed in several human tissues and organs [3]. Most common COVID-19 symptoms include fever, cough, fatigue, and dyspnoea [4]. However, impairment of neurologic, cardiac, liver, kidney, and many other organ functions were reported in patients and convalescent individuals. Disease outcome is not rarely fatal, most commonly due to severe viral pneumonia symptoms affecting especially elder people and immunosuppressed individuals. Moreover, the presence of other concomitant clinical conditions, such as chronic cardiac disease and diabetes, are also thought to represent important risk factors affecting disease outcome. Humans are infected regularly and worldwide with the so-called seasonal coronaviruses, which usually cause a respiratory disease with mild symptoms. They are not recognized as an important public health threat, and development of a specific anti-viral treatment or preventive vaccine was not considered a priority. Therefore, when SARS-CoV-2 emerged, there were no specific antiviral treatments for coronavirus diseases, including COVID-19. Classical approaches to identify new specific anti-viral compounds as well as development of new therapeutic options is a long and complex process that may take several years. In this context, drug repositioning has emerged as a promising and potentially useful approach to identify already approved drugs for treatment of other diseases, including COVID-19 [5]. The main advantages of drug repositioning include the availability of information about pharmacokinetics, pharmacodynamics, and toxicity, of a given drug of interest [6]. Using similar strategies to search for anti-SARS-CoV-2 compounds may significantly shorten the time needed to find an effective treatment for COVID-19, reducing disease burden, including number of hospital admissions, deaths, and long-term sequelae. Since the beginning of the pandemic, several potential anti-SARS-CoV-2 drugs have been under investigation in clinical trials, including remdesivir (initially developed by Gilead for Hepatitis C treatment), chloroquine and hydroxychloroquine (well-known drugs used in malaria treatment), tocilizumab (a monoclonal antibody used in rheumatoid arthritis), favipiravir (an anti-influenza drug), Kaletra (used for HIV treatment), and more recently masitinib (a kinase inhibitor used for mast cell tumour treatment in animals) [7]. More recently, the EU approved the emergency use of Lagevrio (also known as molnupiravir developed by Merck) and Paxlovid (Pfizer) to treat adults with COVID-19 who do not require supplemental oxygen and who are at increased risk of developing severe COVID-19 [8]. Here, we will focus on developments in state-of-the-art research concerning drug repurposing for COVID-19 treatment. SARS-CoV-2 specific factors that are known to interact with host cellular machinery and represent potential targets for drug repositioning will be discussed. Finally, we will present our findings using a drug repurposing strategy to identify new anti-SARS-CoV-2 compounds that may be potentially effective in COVID-19 treatment. 2. Key Targets for Drug Development Similarly to other coronaviruses, the SARS-CoV-2 RNA genome encodes four major structural proteins: spike (S), nucleocapsid (N), membrane (M), and envelope (E). In addition, the virus genome encodes sixteen non-structural proteins (Nsp 1–16), all of which are required during different steps of the virus replication cycle [4,9]. These proteins interact with the host cellular machinery for virus replication and production of new virions. As an example, viral entry into cells occurs via clathrin-mediated endocytosis after interaction of SARS-CoV-2 S protein with the cellular ACE2 receptor [3]. Theoretically, any SARS-CoV-2 encoded protein may represent a valid and potential therapeutic target. 2.1. SARS-CoV-2 Drug Targets SARS-CoV-2 structural proteins play different roles in virus replication. The S protein is responsible for attachment to the cell receptor playing a role in internalization of the virus, also defining host-tissue tropism, and viral transmission capacity [10]. It is composed of two functional subunits, S1 and S2. Subunit S1 is responsible for binding to host cell receptor ACE-2 and contains two identified domains: N-terminal domain (NTD) and receptor binding domain (RBD). Subunit S2 is responsible for fusion of viral and cellular membranes and contains seven domains: fusion peptide (FP), heptad repeat 1 (HR1), central helix (CH), connector domain (CD), heptad repeat 2 (HR2), transmembrane domain (TM), and cytoplasmic tail (CT) [9,10]. The cleavage site at the border between S1 and S2 subunits is called S1/S2 protease cleavage site [10]. Some host proteases were found to promote this cleavage, namely type II transmembrane serine protease (TMPRSS2) and furin. Cleavage at the S1/S2 border promotes viral entry into host cells. The E protein is the smallest of the major structural proteins and is part of the lipid-containing envelope of SARS-CoV-2. It has a well-established role in assembly of virions, envelope formation, budding, and pathogenesis. Along with its interaction with M protein for viral envelope assembly, E protein also interacts with accessory proteins and host cell proteins. More recent evidence seems to indicate that changes in E protein stability may affect viral conformation and functional processes, potentially affecting pathogenesis of SARS-CoV-2 [11]. However, further studies are needed to confirm this hypothesis. The N protein is the most abundant protein expressed by SARS-CoV-2 in infected cells. It plays a crucial role in packaging the viral RNA genome into long, flexible, helical ribonucleoprotein (RNP) complexes [12,13]. Three distinct and highly conserved domains were identified in this protein: a N-terminal domain (NTD), a C-terminal domain (CTD) and an RNA-binding domain (RBD). In addition, the N protein plays an essential structural role through a network of interactions with virus genomic RNA, M protein, and making complexes with other N protein molecules [13]. The M protein is the most abundant protein in the virion envelope and has three transmembrane domains and a large carboxyl-terminal tail. It plays a fundamental role in virion assembly and might also display ion channel activity [12,14]. In addition, recent evidence suggests that M protein, in association with N protein, may play a role in assembly of the nucleocapsid core into progeny virions [14]. The sixteen non-structural proteins are encoded by two ORFs, 1a and 1b, and originate by specific cleavage events of either polyprotein 1a or polyprotein 1b [12]. They play diverse important roles in the virus replication cycle, and their functions are summarized in Table 1. The deeper understanding and knowledge of structure, function, and cellular targets of SARS-CoV-2 encoded proteins may allow developing and repurposing molecules capable of interfering with their functions. Ultimately, this may lead to development of a potential specific and effective treatment for COVID-19. 2.2. Host-Based Drug Targets An increasing body of evidence supports a paradigm where virus-interacting host molecules are expected to represent the next frontier in antiviral drug discovery. These cellular proteins are essential players in modulation of virus replication. Targeting host proteins has obvious advantages over targeting virus proteins. One of the main reasons is the widely reported loss of efficacy of antiviral agents due to the high mutation rate of viral genomes that may ultimately potentiate the emergence and selection of new resistant variants. However, there are also some important drawbacks. One of them is the fact that many host functions targeted by drugs, are essential for maintaining proper cell function and homeostasis. As consequence, severe toxic effects are often associated with administration of this type of compounds. Entry of SARS-CoV-2 into cells involves the attachment of S protein to the ACE2 receptor located at the cell surface. This process facilitates viral entry and is associated with subtle conformational changes [3]. After SARS-CoV-2 interaction with the ACE2 receptor, host type II transmembrane protease serine 2 (TMPRSS2) catalyses the cleavage of SARS-CoV-2 spike protein triggering viral entry [27]. Thus, both Spike/ACE2 interaction and TMPRSS2 cleavage activity may represent important potential targets for antiviral intervention. Another important step in SARS-CoV-2 entry into host cells involves clathrin-mediated endocytosis (CME) [28]. In fact, recent evidence suggests that CME is also crucial for viral entry since clathrin-heavy chain knockdown significantly reduces viral infectivity [10,28]. Bayati and co-workers have recently proposed a viral infectivity model for SARS-CoV-2 involving three key steps: (1) viral S protein binds to the plasma membrane of cells expressing the ACE2 receptor; (2) ACE2/virus complex undergoes rapid clathrin-mediated endocytosis with virus delivery to the lumen of the endosome; (3) viral envelope and lumen of the endosomal membrane fuse, promoting viral RNA release into the cytosol and subsequent steps of the replication cycle [28]. Blocking any of these steps may help preventing virus infection, and consequently may also represent valid starting targets for drug repositioning. Besides SARS-CoV-2 interaction with host factors required for entry, the virus also interacts with factors required for viral RNA synthesis and virion assembly (such as the endoplasmic reticulum (ER), Golgi components and associated vesicular trafficking pathways), as well as factors required for translation of viral mRNA [29]. In fact, screening studies have identified various proteins localizing to the ER, the ER-Golgi intermediate compartment, and the Golgi apparatus as critical for virus replication highlighting the roles of these compartments in translation of SARS-CoV-2 proteins and further virion assembly [30]. 3. Pharmacological Approaches against COVID-19 Even with effective vaccines already available, it is essential to identify and develop new drugs for COVID-19 treatment in order to decrease the burden of disease, including the number of hospital stays and mortality, especially in high-risk groups. Multiple efforts are being made to achieve this goal. On June 2021, the Biden administration allocated more than USD 3 billion to accelerate the discovery and development of the next generation of COVID-19 treatments. As of December 2021, there were 2019 drug studies listed in Clinicaltrials.gov and 655 mapped drug names [7]. At present, COVID-19 patient management is still largely focused on relief of symptoms and respiratory support. In patients presenting moderate to severe COVID-19 symptoms, several drugs have been tested including antiviral compounds, inflammation inhibitors, low molecular weight heparins, and plasma immunoglobulins [31]. In most cases, these drugs were already approved to treat other conditions, a strategy known as drug repurposing or repositioning. It is estimated that development of a new pharmacologically active drug costs, on average, approximately USD 1.24 billion. This includes the whole process from traditional drug discovery to market introduction. In the case of drug repurposing, this process is estimated to be at least 40% less expensive [32,33]. Moreover, it usually takes 10–16 years to develop a new drug using the traditional drug discovery approach, while an average of 8 years is needed to develop a repurposed drug. In fact, a repurposed drug can enter directly to preclinical testing and clinical trials, thus reducing the risk, time, and costs associated with drug development [32,33]. Next, we conduct an overview of different repurposed agents that have been considered for COVID-19 treatment (Table 2). Unfortunately, some of them did not show benefits for patients, but others are still in use albeit with variable efficacy. We focused on the most relevant compounds tested until now, including antiviral and antiparasitic drugs, steroids, signalling inhibitors, and monoclonal antibodies, albeit new compounds should be added to this list as new evidence arises on the mechanism of infection of SARS-CoV-2 and new pharmacological approaches are envisaged to control it. 3.1. Antiparasitic Drugs 3.1.1. Chloroquine and Hydroxychloroquine Chloroquine is an antimalarial agent with anti-inflammatory and immunomodulatory activities that has attracted interest as a potential therapeutic option for treatment of COVID-19-associated pneumonia [34,35,36,37]. Hydroxychloroquine, chloroquine’s hydroxylated form, displays a similar mechanism of action but has shown better tolerability allowing its use in long-term treatment of rheumatological disorders [38,39]. Both compounds have been used mainly in prevention and treatment of malaria and chronic inflammatory diseases such as systemic lupus erythematosus and rheumatoid arthritis [38,39,40]. However, they have also shown a broad antiviral activity against HIV, SARS-CoV, Marburg, Zika, Dengue, and Ebola viruses. This fact raised the interest of the scientific community to explore their use as anti-SARS-CoV-2 agents in the treatment of COVID-19 [36,37]. Previous studies have shown that chloroquine and hydroxychloroquine interfere with virus entry and decapsidation due to its ability to modulate endosomal pH, interfere with glycosylation status of host ACE2 receptor, and compete with the spike protein in binding to gangliosides [37,40]. Moreover, both compounds were shown to modulate the immune system by affecting cell signalling and the production of proinflammatory cytokines [37,41]. These features made hydroxychloroquine an attractive and commonly used repurposed drug during the initial phase of the COVID-19 pandemic. Several clinical trials with these drugs have been carried out since then, but the results were disappointing. In fact, they have shown a lack of efficacy in both postexposure prophylaxis and treatment of mild/moderate COVID-19, as well as inability to reduce mortality rates when compared to the standard care supporting treatment. Additionally, severe side effects were observed, namely relating to cardiovascular problems (QT prolongation with fatal arrhythmias), liver or kidney damage, retinopathy, and hypoglycaemia [36,37,42,43,44]. The absence of clearly proved benefits coupled with safety concerns has contributed to the decision of the WHO to discontinue hydroxychloroquine clinical trials for treatment of COVID-19 patients [43]. 3.1.2. Ivermectin Ivermectin is a broad spectrum anti-parasitic agent approved by the Food and Drug Administration (FDA) as an oral treatment for intestinal strongyloidiasis and onchocerciasis and as a topical treatment for pediculosis and rosacea [45]. It was suggested that the activity of ivermectin against SARS-CoV-2 might be due to the inhibition of host importin α/β-mediated nuclear transport of proteins [46]. Previous studies have demonstrated that ivermectin may decrease SARS-CoV-2 replication in vitro but mostly at higher concentrations than those reached with the authorised doses [47,48]. Usually, ivermectin is well tolerated at therapeutic doses for anti-parasitic treatment, but side effects could increase with the much higher concentrations that would be needed for this drug to be effective against SARS-CoV-2. Moreover, the current evidence from clinical trials on the use of ivermectin to treat COVID-19 patients is inconclusive, with some studies showing no benefit and others reporting a potential benefit in the prevention or treatment of COVID-19. In fact, the WHO recommends the use of ivermectin only within clinical trials. 3.2. Signalling Inhibitors 3.2.1. Baricitinib Baricitinib is a small molecule inhibitor of the Janus-associated kinases 1 and 2 (JAK1 and JAK2), approved for treatment of rheumatoid arthritis [36,49,50]. Baricitinib was selected as a potential repurposed drug against SARS-CoV-2 through an artificial intelligence algorithm. It was demonstrated that the mechanism of action against COVID-19 relies on the modulation of the cytokine storm caused by the infection as well as the inhibition of virus entry into host cells [49]. Clinical trials have shown that baricitinib in combination with remdesivir was more effective than remdesivir alone in reducing recovery time in COVID-19 patients receiving high-flow oxygen or non-invasive ventilation [51]. The emergency use of baricitinib in combination with remdesivir for treatment of hospitalized COVID-19 patients requiring oxygen or mechanical ventilation was authorized by the FDA in November 2020 [52]. Later, in July 2021, the FDA revised the emergency use authorization for baricitinib, now authorizing its use alone, without remdesivir [53]. On April 2021, the European Medicines Agency (EMA) started assessing the extension of indication of baricitinib for treatment of COVID-19 in hospitalised patients who require supplemental oxygen. 3.2.2. Masitinib Masitinib is a tyrosine kinase inhibitor previously evaluated for treatment of several non-communicable diseases such as cancer, asthma, Alzheimer’s disease, multiple sclerosis, and amyotrophic lateral sclerosis [54,55,56,57,58]. It has been shown that masitinib may also act as a broad antiviral agent by inhibiting the activation of virus-specific proteins, namely the proteases of two positive-strand RNA viruses, coronaviruses, and picornaviruses. This compound was shown to be effective in vitro against all SARS-CoV-2 variants of concern [59]. Experiments in mice also showed significant reduction in virus titres in lungs. Masitinib has been shown to completely inhibit the SARS-CoV-2 main protease, 3CL, essential for viral replication and well conserved among coronaviruses [60]. In September 2021, AB Science has obtained approval from the Regulatory Authorities of Russia and South Africa to commence a phase 2 clinical trial with masitinib for COVID-19 treatment. 3.3. Monoclonal Antibodies Tocilizumab Tolicizumab is a monoclonal antibody, approved for treatment of rheumatoid arthritis and other autoimmune rheumatic diseases such as systemic juvenile idiopathic arthritis [61]. The mechanism of action consists of binding to soluble and membrane-bound interleukin 6 (IL-6) receptors, thus preventing IL-6 activity. This cytokine plays a role in inflammation processes and its elevated production is associated with development of acute respiratory distress syndrome in COVID-19 patients [62,63]. Therefore, agents such as tocilizumab could display potential beneficial effects against COVID-19. Most clinical trials have reported that treatment with tocilizumab has reduced the mortality rate comparatively to non-treated patients and with no evidence of significant toxicity effects [64,65]. It was also shown that patients that mostly benefit from the use of tocilizumab in combination with standard care, are those presenting moderate to severe symptoms, although not yet requiring mechanical ventilation [66]. Tocilizumab, when used together with standard care, reduced the probability of progression to mechanical ventilation and death rates in hospitalized patients with COVID-19 pneumonia [66]. However, at least one study demonstrated that early administration of tocilizumab did not influence the mortality rate or time of recovery [67]. In July 2021, tocilizumab became the second drug recommended by the WHO for COVID-19 treatment (dexamethasone, an anti-inflammatory drug, was recommended in September 2020) [68]. 3.4. Steroids Dexamethasone Dexamethasone is a glucocorticoid commonly used to treat severe allergies, asthma, several forms of arthritis and intestinal disorders. It is part of the WHO list of essential medicines [69]. This drug displays strong anti-inflammatory and immunosuppressant properties and was recommended in the second half of 2020 for treatment of COVID-19 patients who need mechanical ventilation or supplemental oxygen. Dexamethasone acts by binding to the glucocorticoid receptor triggering a signalling cascade that ultimately results in inhibition of expression of inflammatory genes and stimulation of expression of anti-inflammatory genes [70]. In COVID-19 patients, this drug acts by suppressing the overstimulation of the immune system, namely the type 1 interferon response, caused by SARS-CoV-2 infection of the lungs [71]. Dexamethasone was the first drug to display a significant impact in reducing the death rate of hospitalized patients with severe symptoms, ranging from 20% to 35% [72]. 3.5. Antiviral Drugs 3.5.1. Umifenovir Umifenovir (ArbidolTM) is an indole carboxylic acid derivative that presents inhibitory activity against a variety of viruses such as parainfluenza, influenza A and B, and hepatitis C virus [73,74,75]. It was developed by Pharmastandard for the treatment of influenza and is currently used mainly in Russia and China. The mechanism of action consists of preventing the virus-cell membrane fusion and virus-endosome internalization through the incorporation of umifenovir molecules into the cell membrane [76,77]. Moreover, it was shown that umifenovir can enhance the humoral immune response and interferon production. It has been hypothesized that the combination of umifenovir with interferons may produce a synergistic therapeutic effect against SARS-CoV-2 [78]. Previous studies have also shown that the combination of umifenovir with lopinavir-ritonavir was associated with an increased RT-PCR SARS-CoV-2 negative conversion rate, when compared with treatment with lopinavir-ritonavir alone [79]. A recent randomized clinical trial showed that umifenovir did not improve mortality rates and did not decrease the need for mechanical ventilation and time to clinical improvement [80]. 3.5.2. Remdesivir Remdesivir (VekluryTM) was originally developed by Gilead Sciences, Inc. (Foster City, CA, USA) as a potential anti-Hepatitis C virus candidate and was later repurposed and tested against Ebola and Marburg viruses in clinical trials. In both cases, its development was stopped due to the lack of solid evidence about its efficacy [81,82]. When administered, the GS-441524 monophosphate prodrug is intracellularly converted into the corresponding triphosphate that acts as adenosine ribonucleotide triphosphate analogue. It was shown to inhibit the activity of the virus-encoded RNA-dependent RNA polymerase, impairing RNA synthesis and replication [83,84]. This prodrug was thought to be a potential promising candidate to be repurposed for COVID-19 treatment since almost the beginning of the pandemic. Phase III clinical trials were carried out in early 2020. However, the efficacy of remdesivir was, in several moments, questionable and surrounded in controversy, due to the lack of evidence of its efficacy in mortality reduction. Several important adverse side effects were observed, including hepatocellular toxicity, nausea, anaemia, kidney injury, hypotension, respiratory failure, and constipation [85]. Nevertheless, remdesivir is one of the medications recommended by the EMA and the FDA for treatment of severe COVID-19 since it may reduce hospitalization time [86,87]. 3.5.3. Favipiravir Favipiravir (brand name Avigan™) is a nucleoside analogue prodrug that mimics both adenosine and guanosine. It was initially developed for treatment of seasonal influenza by Toyama Chemical and is available as a therapeutic agent in some countries such as China and Japan [88]. Favipiravir displays a mechanism of action similar to that of remdesivir, acting by inhibiting viral RNA-dependent RNA polymerase activity [89,90,91]. This compound was initially used for treatment of COVID-19 in Wuhan. Since then, several clinical trials have been carried out to evaluate its efficacy against SARS-CoV-2. There is still limited data available, but there is evidence pointing to improvement of some clinical and radiological indicators. However, no reduction in mortality or differences in oxygen-support requirement were observed [92,93]. Large-cohort clinical trials began in May 2021 and are currently ongoing [94]. 3.5.4. Molnupiravir Molnupiravir (Lagevrio™, Merck) was the first oral, direct-acting antiviral shown to be highly effective at reducing nasopharyngeal SARS-CoV-2 titres, and to have a significant benefit in reducing hospitalization or death in mild COVID-19 [95,96]. It is a prodrug of N4-hydroxycytidine that is converted into the active form 5′-triphosphate by host kinases. The active 5′-triphosphate serves as a competitive substrate for the viral RNA-dependent RNA polymerase and causes an antiviral effect through the accumulation of mutations after each viral replication cycle. This drug was originally developed as a possible treatment of diseases caused by RNA viruses, namely influenza viruses and encephalitic alphaviruses, but also showed a broad-spectrum antiviral activity against several coronaviruses, including SARS-CoV-2, in preclinical studies [96]. Recently, the pharmaceutical company Merck released the final analysis of a clinical trial that demonstrated that molnupiravir reduced the risk of hospitalization and death among high-risk patients by 30%, instead of the earlier estimate of 50%. EMA granted emergency use authorization of Lagevrio™ (molnupiravir) in patients who do not require supplemental oxygen and who are at increased risk of developing severe COVID-19. Furthermore, FDA also authorized the use of molnupiravir in certain adult patients. 3.5.5. Lopinavir and Ritonavir Lopinavir and ritonavir (Kaletra™, Abbott) are used for the management of AIDS. These drugs specifically inhibit one of the key factors required during the virus replication cycle, the virus-encoded protease responsible for processing newly synthesized virus polyproteins [97]. Previous studies have shown that these compounds may also be effective against MERS and SARS viruses whose genomes also code for specific proteases with similar functions [98,99]. As a consequence, they became attractive as potential anti-SARS-CoV-2 drugs. In fact, it was suggested that lopinavir-ritonavir could decrease SARS-CoV-2 replication in vitro through inhibition of the virus-specific 3CL1 proprotease [100]. However, results from subsequent multiple clinical trials were controversial regarding the capacity of these drugs to improve disease outcomes. The WHO-promoted Solidarity trials stopped testing this combination due the absence of clear benefits, including to the lack of mortality reduction in hospitalized patients [101]. 3.5.6. Paxlovid A more effective treatment with Paxlovid™ (Pfizer), showed 89% efficacy in reducing hospitalization and death. Paxlovid™ consists of a combination of nirmatrelvir (PF-07321332) and ritonavir. Nirmatrelvir belongs to a group of compounds previously shown to specifically inhibit the coronavirus protease 3CL and successfully tested against SARS and Feline coronaviruses [102,103]. It cannot be considered a true repurposed drug since it was initially synthesized with the purpose to be tested against SARS-CoV-2. Nirmatrelvir acts by binding to the active site of the SARS-CoV-2 serine protease 3CL specifically inhibiting its activity. Ritonavir is another protease inhibitor commonly used for HIV/AIDS and hepatitis C treatment [104]. When administered together with ritonavir, PF-07321332 is degraded slower inside the cell, its concentrations remain higher for longer periods of time, and the efficacy is increased. EMA authorized the use Paxlovid™ in January 2022. In addition, FDA also authorized the emergency use of Paxlovid™ for treatment of mild-to- moderate COVID-19 in certain adults and paediatric patients. 4. In Silico Repurposing Strategies to Identify Potential Drugs and Drug Targets against COVID-19 Presently, drug repurposing no longer depends on serendipitous observations, but is instead the result of the application of computational and biological strategies that allow the quick and effective selection of the most promising repurposed candidates [105]. In general, drug repurposing follows one of two principles: (i) drug-based, which is directed to the discovery of new uses for a particular drug; (ii) target-based, which selects targets based on their homology to a target for which a drug has already been approved. An example of an in silico drug repurposing approach is to take advantage of the large amount of data publicly available in online databases that provide information on thousands of therapeutic drugs [106,107,108]. Thus, it is possible to identify a list of approved agents with predictive activity against SARS-CoV-2 that may be directly testable in preclinical and clinical trials for COVID-19. Moreover, the development and implementation of machine learning and artificial intelligence (AI) methods can greatly revolutionize computational drug repurposing and accelerate the discovery of anti-COVID-19 repurposed drugs [109]. Computer-aided approaches applied to drug discovery against COVID-19 have mostly employed docking screen, molecular simulation, pharmacophore models, or machine learning-based virtual screens [110]. There are several reviews that summarize the use of machine learning and AI approaches in COVID-19 drug discovery [32,33,111,112,113,114,115,116,117]. Machine learning-aided molecular docking has been frequently used for virtual screening, involving the following steps: dataset of druglike or approved molecules; crystal structure or homology model of the target; molecular docking programs; compute resources [112,118,119]. Several molecules have been identified by docking to fit the binding site of various SARS-CoV-2 proteins essential for viral replication [116]. A known example of the identification of a potential anti-COVID-19 drug through the implementation of an AI-based approach is baricitinib [49,120]. This approach integrated biomedical data from structured and unstructured sources and targeted the inhibition of the host protein AAK1, thus identifying baricitinib [49,120]. Nevertheless, computational approaches still face many challenges such as protein flexibility and the accuracy of binding affinity prediction, selection of the most relevant protein structure, flexibility and druggability of the receptor, among others [114]. Therefore, it is crucial to continue to develop other in silico repurposing tools and approaches. In the following section, we will describe our in silico drug repurposing strategy for identification of drugs with potential activity against COVID-19 based on genomic, chemical, structural and functional evidence and similarity between viral and host proteins. An In Silico Repurposing-Chemogenomic Approach to Identify New Drugs with Potential Efficacy against COVID-19 Both virus and host proteins can be explored as potential targets for drug repurposing in the fight against COVID-19. Targeting viral proteins has the advantage of not interfering with the host machinery, while targeting host proteins has the advantage of selecting broad-spectrum agents capable of modulating virus–host interactions at different stages of the replication cycle, including viral attachment and entry, which may prevent several downstream disease outcomes. In the approach to be described in this section, we searched for approved drugs that may target structural and non-structural viral proteins as well as host proteins involved in viral entry into cells, namely the ACE2 receptor, TMPRSS2, and clathrin-mediated endocytosis-related proteins. The rational workflow of the strategy is presented in Figure 1. This strategy was based on a methodology previously described and can be easily adapted to several microorganisms and metabolic pathways [106,107,108]. Initially, two lists of proteins were compiled that included: (1) SARS-CoV-2 encoded proteins and (2) human proteins involved in virus entry into cells. Proteins and their respective functions were compiled from the UniProtKB and NCBI databases (Table S1) [121,122]. In the case of UniProtKB, the strategy was as follows: (i) Enter UniProtKB database [121]; (ii) Search for “SARS-CoV-2 proteins” or “Endocytosis mediated by clathrin”; (iii) Select the proteins from the SARS-CoV-2 replication cycle or human proteins that are involved in SARS-CoV-2 entry into host’s cells. The corresponding protein sequences were used to interrogate DrugBank, a publicly available online database that provides detailed information on drugs and their targets [123,124]. DrugBank uses a search strategy that relies on the principle of homology, where each query (query = SARS-CoV-2 proteins and query = human protein involved in SARS-CoV-2 entry into cells) results in a similarity comparison with all drug targets known to the database. Only proteins with a statistical similarity corresponding to an expectation value (E-value) of ≤10−20 were considered potential targets [107]. The E-value represents the expected number of times a homology match will occur at random in a given set of trials. From the identified targets, only the ones predicted to interact with approved drugs were selected. For the structural proteins, only one approved drug was obtained, associated with the structural S protein. Interestingly, our in silico approach identified the S protein as both the predicted and approved target. For the 16 non-structural predicted protein targets, one approved protein target, the SARS-CoV replicase polyprotein 1ab, associated with one approved drug was obtained. Thus, for the SARS-CoV-2 proteins the two approved drugs identified for the DrugBank were bamlanivimab and remdesivir, a monoclonal antibody and an antiviral compound, respectively, already under investigation and also under use for the treatment of severe COVID-19 disease [87,125]. The fact that these two drugs, which are under investigation, were identified through our in silico analytical strategy validates our method. Regarding the two human predicted protein targets involved in viral entry into host cells, the DrugBank database identified 25 approved protein targets associated with 73 approved drugs (Table S1). Considering that the two drugs identified for the SARS-CoV-2 proteins are under use for treatment of COVID-19, we focused on narrowing the number of drugs identified through the DrugBank database for the human predicted protein targets involved in the viral entry into the host cell. For this, the functional regions of the approved drug targets and human targets involved in viral entry into host cells were compared using the ConSurf Server [126]. This bioinformatics’ tool estimates the evolutionary conservation of amino acid positions in a protein, based on the phylogenetic relationships between homologous sequences [127]. This procedure was performed to estimate the conservation of active sites between proteins and the preservation of affinity for the predicted SARS-CoV-2 drugs. The parameters for the analysis were selected as previously described [107]. Briefly, the degree of conservation of the amino acids within the active site of each approved drug target was estimated using 150 homologues from other organisms with similar sequences in the UniProt database. Sequences below the identity cut-off of <35% or presenting similarity >95% were excluded using the algorithm CD-HIT to filter out redundant sequences. The MAFFT-L-INS-I method was used to construct a multiple sequence alignment of the homologous sequences and position-specific conservation scores were computed using the empirical Batesian method. Then, the functional regions of each approved drug target were visually compared with the corresponding human target involved in SARS-CoV-2 entry into cells. The results obtained were classified as functional residues with high (≥80%) or moderate conservation (60–79%). When the conservation between functional residues is less than 59%, the putative targets were excluded from further analyses. This strategy resulted in a list of two potential druggable proteins involved in SARS-CoV-2 entry into host cells (25% of the interrogated human targets) that could interact with 11 approved drugs. Table 3 presents these targets and their corresponding potential drugs (detailed data provided in Table S2). Nine drugs that may inhibit TMPRSS2, a cellular proteinase involved in facilitating SARS-CoV-2 entry into host cells, and two drugs with potential activity against the ACE2 receptor were identified. The drugs identified with potential activity against ACE2 were chloroquine and hydroxychloroquine, while for TMPRSS2 we found alpha-1-proteinase inhibitor, aprotinin, aluminium, aluminium phosphate, aluminium acetate, filgrastim, pegfilgrastim, cyproterone acetate and mifepristone (Table 3). These drugs belong to distinct classes and have different therapeutic indications, namely palliative treatment for prostatic carcinoma (cyproterone acetate and mifepristone), decrease in neutropenia (filgrastim and pegfilgrastim) or prophylaxis of Malaria disease (chloroquine and hydroxychloroquine). The PubMed database was used to verify if the identified compounds have already been tested against SARS-CoV-2. As already described above, chloroquine and its derivative, hydroxychloroquine, are two anti-malarial and autoimmune disease drugs that have recently been reported as having a potential broad-spectrum antiviral activity [128,129]. The mechanism of action of both drugs has not been completely elucidated but will likely involve the increase in endosomal pH with consequent interference on virus fusion and decapsidation processes. It has also been shown that both compounds can also inhibit nucleic acids replication, glycosylation of viral proteins, virus assembly, virion transport, and virus release, to achieve its antiviral effects [129,131]. In addition to the antiviral activity, the two compounds are also believed to display immunomodulatory effects that may act synergistically to enhance the overall antiviral effect in vivo [128]. Taking this into consideration, initial evidence suggested that early treatment with either chloroquine or hydroxychloroquine may help prevent the progression of the disease to a critical, possible lethal, state [129]. By contrast, recent findings show that, in vitro, both chloroquine and hydroxychloroquine are not capable of inhibiting SARS-CoV-2 replication [132,133]. Due to the lack of solid clinical evidence on the beneficial effects of chloroquine and hydroxychloroquine, together with the observation of important adverse effects in some patients, both drugs are not currently recommended for COVID-19 treatment, as previously discussed. Nevertheless, one should not completely rule out any of these therapies as they may potentially show a positive synergistic effect, at lower doses, in controlling the severity of symptoms caused by SARS-CoV-2 infection. Alpha-1-proteinase inhibitor, also known as Alpha 1 antitrypsin (A1AT), a circulating extracellular protein capable of inhibiting extracellular proteases, was approved by the FDA for treatment of A1AT deficiency. Azouz and co-workers have recently demonstrated that A1AT can efficiently inhibit TMPRSS2 proteolytic activity with subsequent impairing of S protein processing, and consequent restriction of SARS-CoV-2 entry into cells [130]. Aprotinin is a serine protease inhibitor used for the prophylaxis of blood loss. Aprotinin has been described to inhibit SARS-CoV-2 replication in vitro. Bojkova and co-workers have recently shown that aprotinin can function as an entry inhibitor by interfering with SARS-CoV-2 S protein activation by TMPRSS2 in lower concentration ranges than those defined for A1AT [131]. The treatment with entry inhibitors, either alone or in synergy with other anti-COVID-19 agents may represent a promising antiviral strategy to fight this pandemic [130,131]. Aluminium salts, namely, aluminium phosphate and aluminium acetate, are common in nature and have been used for many years in wound healing and bleeding control. However, the information available regarding the therapeutic use of these molecules in humans is very scarce. In addition to therapeutic uses, aluminium salts are also commonly included as adjuvants in vaccine formulations. Some recent studies point to potential antiviral effects of aluminium salts on both clinical and laboratory outcomes in COVID-19 patients [134]. Filgrastim and its pegylated form, pegfilgrastim, are haematopoietic growth factors that stimulate the proliferation and differentiation of committed progenitor cells of the granulocyte-neutrophil lineage into functionally mature neutrophils [135]. Recently, these drugs have been used to treat COVID-19 patients, since they were found to prevent neutropenic fever. Since administration of these drugs has also been associated with the emergence of cytokine storm in COVID-19 patients, caution should be taken when considering them as a broader potential therapeutic option [136]. Cyproterone acetate (CPA) is a compound with anti-androgen effect used since the 1980s to assist with feminisation and suppression of testosterone [137,138]. There is no evidence of having antiviral activity specifically against SARS-CoV-2. However, the androgen receptor (AR) regulates TMPRSS2 gene and, although not exclusively, ACE2. This way, higher expression of the AR may correlate with increased disease severity in COVID-19 patients. As such, anti-androgens, such as CPA, are potential candidates to test during SARS-CoV-2 infection, in order to decrease severity of COVID-19 disease [139]. Mifepristone is a synthetic steroid, commonly used for medically induced abortions as it is a glucocorticoid and progesterone receptor antagonist [140]. Although not having reported activity against SARS-CoV-2, mifepristone has shown antiviral activity against HIV-1 [141] and can inhibit nuclear import by the importin α/β1-heterodimer, central to HIV-1 viral replication [142]. As mentioned before, ivermectin also targets the nuclear import pathway of proteins and was not capable of inhibiting SARS-CoV-2 replication at tolerated doses. However, mifepristone’s mode of action as receptor agonist may deserve further attention in preliminary experimental assays. In this study, we used an in silico target-based chemogenomics strategy, integrating SARS-CoV-2 genomics data with drug-target information provided by publicly available database to predict new drugs with potential activity against SARS-CoV-2. This systematic in silico approach follows the concept that ‘‘similar targets have similar ligands’’ to identify 11 clinically approved compounds that could be potentially effective against COVID-19. Several in silico studies have demonstrated that genome-wide data is a useful resource for identifying drugs and drug targets that can potentially be used for drug repurposing in COVID-19 [112,143]. Recently, Li and colleagues identified 30 drugs for repurposing by analysing the genome sequence of three main viral family members of the coronavirus and relating them to the human disease-based pathways using a network of bioinformatics analysis grounded on disease pathways, protein–protein interaction and graph theory combined with analysis algorithms to connect disease-related genes with potential viral drug-targets [144]. Furthermore, Zhou et al. described a combination of network-based methodologies for repurposed drug combination, which allowed identifying melatonin as a potential prevention and treatment compound for COVID-19 [145]. Similarly to other computer-aided approaches to drug discovery, our in silico predictions need to be validated experimentally. It is mandatory to clarify if the identified drugs never tested against SARS-CoV-2 present anti-virus biological activity and if their mechanism of action involves the suggested target. It can never be ruled out that the in vivo activity may be compromised by their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. However, if their activity and efficacy still remain to be promising, these compounds could represent important leads in COVID-19 drug discovery. 5. Concluding Remarks The global health emergency of the COVID-19 pandemic has called for the need to accelerate drug discovery and rapidly identify effective drugs and therapeutic options. Drug repurposing is a strategy that has been widely used to reduce research time and associated costs and risks. Although repurposed drugs are still required to go through clinical trials, it is undeniable that this strategy can rapidly reveal effective drugs, including those that have previously failed against their original purpose. Recently, several reviews have focused on drug repurposing strategies applied to the evaluation of existing drugs for treatment of COVID-19 [32,33,111,112,113,114,115,116,117]. Most of these reviews give an overview of potential molecular drug targets of SARS-CoV-2, the currently available therapeutic approaches for the disease, and drug repurposing as a strategy to identify new drugs. The use of computational tools is frequently highlighted due to their significant contribution to this field. Moreover, some reviews put in evidence both experimental and computational drug repurposing strategies [110]. In this work, we follow what may be considered a similar approach by reviewing key drug targets of SARS-CoV-2 and therapeutic strategies used for COVID-19. In addition, we included an in silico drug repurposing-chemogenomic analytical strategy previously used by our group in an attempt to repurpose drugs for malaria and tuberculosis [106,107,108]. This novel approach now allowed identifying 11 molecules with a potential anti-viral effect against SARS-CoV-2. Four of these drugs, such as chloroquine, hydroxychloroquine, aprotinin and alpha-1-proteinase inhibitor, have already been tested in vitro against SARS-CoV-2, thus validating the used strategy. The other seven molecules are predicted to inhibit the cellular proteinase TMPRSS2 and, as of the writing of this article, have never been tested in vitro against SARS-CoV-2. These drugs are aluminium, aluminium phosphate, aluminium acetate, filgrastim, pegfilgrastim, cyproterone acetate and mifepristone. They may represent valid candidates for further studies aimed at evaluating their effectiveness against COVID-19. Similarly to other computational approaches to drug discovery, our in silico predictions need to be validated experimentally. In fact, in vitro and in vivo studies are essential to validate the efficacy of a repurposed drug and to ensure its usage at safe concentrations. In addition, investigating synergistic interactions between these drugs and others already undergoing clinical trials may improve the probability of finding effective and tolerable therapeutic combinations for this threatening disease. Finally, compounds that display marked anti-SARS-CoV-2 activity, alone or synergistically, at safe concentrations, should be tested in pharmacodynamic and pharmacokinetic studies before their final selection as potential candidates in clinical trials. In conclusion, even though drug repurposing is an attractive approach to decrease the bottlenecks of conventional drug discovery, it still faces many challenges from a scientific and a regulatory point of view. However, the emergence of new SARS-CoV-2 variants of interest puts evidence on the continuing need for new and effective drugs to treat COVID-19. Drug repurposing has the potential to rapidly identify new and safe drugs that can prevent patient hospitalisation, until the advent of newly developed drugs that are highly effective against SARS-CoV-2. Acknowledgments FCT for funds to GHTM–UID/04413/2020. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules27092723/s1, Table S1: List of potential drug targets and respective functions, Table S2: List of potential anti-SARS-CoV-2 drugs and their predicted targets. Click here for additional data file. Author Contributions Conceptualization, L.R., M.V. and C.C.; methodology, L.R. and R.B.C.; original draft preparation, L.R. and R.B.C.; review and editing, L.R., R.B.C. and C.C.; supervision, T.V., M.V. and C.C. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by Fundação para a Ciência e a Tecnologia (FCT) “Apoio Especial RESEARCH4COVID-19 project no 434”. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Sample Availability Samples of the compounds are not available from the authors. Figure 1 Flowchart summarizing the in silico drug repurposing strategy and corresponding results. molecules-27-02723-t001_Table 1 Table 1 Coronavirus structural and non-structural proteins. Protein Function Structural S Cellular attachment and internalization of the virus [15] E Assembly of virions [16] N Package of the viral genome [17] M Assembly of virions and possible ion channel activity [16] Non-structural NSP1 Inhibitor of host gene expression [18] NSP2 Disruption of intracellular host signalling [19] NSP3 Polyprotein processing [20]; Replication organelle formation NSP4 Viral replication-transcription complex [21] NSP5 Main protease [12] NSP6 Autophagy lysosome delivery [22]; Replication organelle formation NSP7 Subunit of the RdRP holoenzyme; Forms complex with NSP8 and NSP12 [23] NSP8 Subunit of the RdRP holoenzyme; Makes heterodimer with NSP7 and NSP12 [23] NSP9 Viral replication NSP10 Assembly of a functional replication and transcription complex; Stimulates NSP14 and NSP16 activities [24] NSP11 Unknown NSP12 RNA-dependent RNA polymerase [25] NSP13 RNA helicase, involved in replication and transcription [26] NSP14 Proofreading 3′-5′ exoribonuclease [12] NSP15 Endoribonuclease [12] NSP16 Mediates mRNA cap 2′-O-ribose methylation to the 5′-cap structure of viral mRNAs [24] molecules-27-02723-t002_Table 2 Table 2 Most studied repurposed drugs/molecules for COVID-19 treatment. Repurposed Drug/Molecule Original Approved Therapeutic Use Probable Mechanism of Action against COVID-19 Baricitinib Rheumatoid arthritis Modulates cytokine production. Chloroquine and Hydroxychloroquine Malaria, chronic inflammatory diseases. Prevents virus entry and decapsidation. Modulates the host immune system. Dexamethasone Inflammatory conditions (e.g., bronchial asthma, endocrine and rheumatic disorders). Binds to the cellular glucocorticoid receptor, modulates production of pro-inflammatory and anti-inflammatory signals. Favipiravir Influenza virus Inhibits virus RNA synthesis. Ivermectin Anti-parasitic. Intestinal strongyloidiasis and onchocerciasis, pediculosis and rosacea. Inhibits the cellular importin α/β-mediated nuclear transport of proteins. Lopinavir-Ritonavir HIV/AIDS Inhibits the virus 3CL protease. Masitinib Cancer, asthma, Alzheimer’s disease, multiple sclerosis, amyotrophic lateral sclerosis. Inhibits the virus 3CL protease. Molnupiravir Influenza viruses and encephalitic alphaviruses. Inhibits virus RNA synthesis. Remdesivir Ebola virus Inhibits virus RNA synthesis. Tocilizumab Rheumatoid arthritis, other autoimmune rheumatic diseases. Inhibits IL-6 activity. Umifenovir Influenza and other respiratory viruses. Blocks virus attachment and entry. Modulates immune response and interferon production. molecules-27-02723-t003_Table 3 Table 3 Potential anti-SARS-CoV-2 drugs and predictive targets identified in this study. Drug Name Drug Category Human Target In Vitro Activity against SARS-CoV-2 Chloroquine Quinolines and derivatives ACE2 EC50  =  1.13 μM [128] Hydroxychloroquine Quinolines and derivatives ACE2 EC50 = 0.72 μM [129] Alpha-1-proteinase inhibitor Carboxylic acids and derivatives TMPRSS2 IC50 = 357 nM (TMPRSS2 inhibitor) [130] Aluminium Homogeneous post-transcriptional metal compounds TMPRSS2 Not tested Aluminium acetate Carboxylic acids and derivatives TMPRSS2 Not tested Aluminium phosphate Post-transition metal oxoanionic compounds TMPRSS2 Not tested Aprotinin Carboxylic acids and derivatives TMPRSS2 IC50 = 0.32–1.65 μM [131] Cyproterone acetate Steroids and steroid derivatives TMPRSS2 Not tested Filgrastim Carboxylic acids and derivatives TMPRSS2 Not tested Mifepristone Steroids and steroid derivatives TMPRSS2 Not tested Pegfilgrastim Carboxylic acids and derivatives TMPRSS2 Not tested Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. World Health Organization Coronavirus Disease (COVID-19) Available online: https://www.who.int/news-room/q-a-detail/coronavirus-disease-COVID-19 (accessed on 11 February 2022) 2. WHO Coronavirus (COVID-19) Dashboard Available online: https://COVID19.who.int/ (accessed on 11 February 2022) 3. Yadav R. Chaudhary J.K. Jain N. Chaudhary P.K. Khanra S. Dhamija P. Sharma A. Kumar A. Handu S. Role of structural and non-structural proteins and therapeutic targets of SARS-CoV-2 for COVID-19 Cells 2021 10 821 10.3390/cells10040821 33917481 4. Fagbule O.F. 2019 Novel coronavirus Ann. Ib. Postgrad. Med. 2019 17 108 110 32669985 5. Serafin M.B. Bottega A. Foletto V.S. da Rosa T.F. Hörner A. Hörner R. Drug repositioning is an alternative for the treatment of coronavirus COVID-19 Int. J. Antimicrob. Agents 2020 55 105969 10.1016/j.ijantimicag.2020.105969 32278811 6. Zheng W. Sun W. Simeonov A. Drug repurposing screens and synergistic drug-combinations for infectious diseases Br. J. Pharmacol. 2017 175 181 191 10.1111/bph.13895 28685814 7. Views of COVID-19 Studies Listed on ClinicalTrials.gov Available online: https://clinicaltrials.gov/ct2/COVID_view (accessed on 16 February 2022) 8. EMA Issues Advice on Use of Lagevrio (Molnupiravir) for the Treatment of COVID-19 Available online: https://www.ema.europa.eu/en/news/ema-issues-advice-use-lagevrio-molnupiravir-treatment-COVID-19 (accessed on 11 February 2022) 9. Wang M.Y. Zhao R. Gao L.J. Gao X.F. Wang D.P. Cao J.M. SARS-CoV-2: Structure, biology, and structure-based therapeutics development Front. Cell Infect. Microbiol. 2020 10 587269 10.3389/fcimb.2020.587269 33324574 10. Walls A.C. Park Y.J. Tortorici M.A. Wall A. McGuire A.T. Veesler D. Structure, function, and antigenicity of the SARS-CoV-2 Spike Glycoprotein Cell 2020 181 281 292 10.1016/j.cell.2020.02.058 32155444 11. Rahman M.S. Hoque M.N. Islam M.R. Islam I. Mishu I.D. Rahaman M.M. Sultana M. Hossain M.A. Mutational insights into the envelope protein of SARS-CoV-2 Gene Rep. 2021 22 100997 10.1016/j.genrep.2020.100997 33319124 12. O’Leary V.B. Dolly O.J. Höschl C. Černa M. Ovsepian S.V. Unpacking pandora from its box: Deciphering the molecular basis of the SARS-CoV-2 coronavirus Int. J. Mol. Sci. 2020 22 386 10.3390/ijms22010386 13. Zeng W. Liu G. Ma H. Zhao D. Yang Y. Liu M. Mohammed A. Zhao C. Yun Y. Xie J. Biochemical characterization of SARS-CoV-2 nucleocapsid protein Biochem. Biophys. Res. Commun. 2020 527 618 623 10.1016/j.bbrc.2020.04.136 32416961 14. Thomas S. The structure of the membrane protein of SARS-CoV-2 resembles the sugar transporter SemiSWEET Pathog. Immun. 2020 5 363 10.20411/pai.v5i1.377 15. Li F. Structure, function, and evolution of coronavirus Spike proteins Annu. Rev. Virol. 2016 3 237 261 10.1146/annurev-virology-110615-042301 27578435 16. Ruch T.R. Machamer C.E. The coronavirus E protein: Assembly and beyond Viruses 2012 4 363 382 10.3390/v4030363 22590676 17. McBride R. van Zyl M. Fielding B.C. The coronavirus nucleocapsid is a multifunctional protein Viruses 2014 6 2991 3018 10.3390/v6082991 25105276 18. Huang C. Lokugamage K.G. Rozovics J.M. Narayanan K. Semler B.L. Makino S. SARS coronavirus nsp1 protein induces template-dependent endonucleolytic cleavage of mRNAs: Viral mRNAs are resistant to nsp1-induced RNA cleavage PLoS Pathog. 2011 7 e1002433 10.1371/journal.ppat.1002433 22174690 19. Cornillez-Ty C.T. Liao L. Yates J.R. Kuhn P. Buchmeier M.J. Severe acute respiratory syndrome coronavirus nonstructural protein 2 interacts with a host protein complex involved in mitochondrial biogenesis and intracellular signaling J. Virol. 2009 83 10314 10318 10.1128/JVI.00842-09 19640993 20. Lei J. Kusov Y. Hilgenfeld R. Nsp3 of coronaviruses: Structures and functions of a large multi-domain protein Antivir. Res. 2018 149 58 74 10.1016/j.antiviral.2017.11.001 29128390 21. Sakai Y. Kawachi K. Terada Y. Omori H. Matsuura Y. Kamitani W. Two-amino acids change in the nsp4 of SARS coronavirus abolishes viral replication Virology 2017 510 165 174 10.1016/j.virol.2017.07.019 28738245 22. Cottam E.M. Whelband M.C. Wileman T. Coronavirus NSP6 restricts autophagosome expansion Autophagy 2014 10 1426 1441 10.4161/auto.29309 24991833 23. Te Velthuis A.J.W. Van Den Worm S.H.E. Snijder E.J. The SARS-coronavirus nsp7+nsp8 complex is a unique multimeric RNA polymerase capable of both de novo initiation and primer extension Nucleic Acids Res. 2012 40 1737 1747 10.1093/nar/gkr893 22039154 24. Decroly E. Debarnot C. Ferron F. Bouvet M. Coutard B. Imbert I. Gluais L. Papageorgiou N. Sharff A. Bricogne G. Crystal structure and functional analysis of the SARS-coronavirus RNA cap 2′-o-methyltransferase nsp10/nsp16 complex PLoS Pathog. 2011 7 e1002059 10.1371/journal.ppat.1002059 21637813 25. Subissi L. Posthuma C.C. Collet A. Zevenhoven-Dobbe J.C. Gorbalenya A.E. Decroly E. Snijder E.J. Canard B. Imbert, I. One severe acute respiratory syndrome coronavirus protein complex integrates processive RNA polymerase and exonuclease activities Proc. Natl. Acad. Sci. USA 2014 111 E3900 E3909 10.1073/pnas.1323705111 25197083 26. Jang K.J. Jeong S. Kang D.Y. Sp N. Yang Y.M. Kim D.E. A high ATP concentration enhances the cooperative translocation of the SARS coronavirus helicase nsP13 in the unwinding of duplex RNA Sci. Rep. 2020 10 4481 10.1038/s41598-020-61432-1 32161317 27. Mei M. Tan X. Current strategies of antiviral drug discovery for COVID-19 Front. Mol. Biosci. 2021 8 671263 10.3389/fmolb.2021.671263 34055887 28. Bayati A. Kumar R. Francis V. McPherson P.S. SARS-CoV-2 infects cells after viral entry via clathrin-mediated endocytosis J. Biol. Chem. 2021 296 100306 10.1016/j.jbc.2021.100306 33476648 29. V’kovski P. Kratzel A. Steiner S. Stalder H. Thiel V. Coronavirus biology and replication: Implications for SARS-CoV-2 Nat. Rev. Microbiol. 2020 19 155 170 10.1038/s41579-020-00468-6 33116300 30. Bailey A.L. Diamond M.S. A Crisp(r) new perspective on SARS-CoV-2 biology Cell 2021 184 15 17 10.1016/j.cell.2020.12.003 33338422 31. Stasi C. Fallani S. Voller F. Silvestri C. Treatment for COVID-19: An overview Eur. J. Pharmacol. 2020 889 173644 10.1016/j.ejphar.2020.173644 33053381 32. Sahoo B.M. Ravi Kumar B.V.V. Sruti J. Mahapatra M.K. Banik B.K. Borah P. Drug repurposing strategy (DRS): Emerging approach to identify potential therapeutics for treatment of novel coronavirus infection Front. Mol. Biosci. 2021 26 628144 10.3389/fmolb.2021.628144 33. Napolitano F. Zhao Y. Moreira V.M. Tagliaferri R. Kere J. D’Amato M. Greco D. Drug repositioning: A machine-learning approach through data integration J. Cheminf. 2013 5 30 10.1186/1758-2946-5-30 34. Savarino A. Boelaert J.R. Cassone A. Majori G. Cauda R. Effects of chloroquine on viral infections: An old drug against today’s diseases? Lancet Infect. Dis. 2003 3 722 727 10.1016/S1473-3099(03)00806-5 14592603 35. Pastick K.A. Okafor E.C. Wang F. Lofgren S.M. Skipper C.P. Nicol M.R. Pullen M.F. Rajasingham R. McDonald E.G. Lee T.C. Review: Hydroxychloroquine and chloroquine for treatment of SARS-CoV-2 (COVID-19) Open Forum Infect. Dis. 2020 7 ofaa130 10.1093/ofid/ofaa130 32363212 36. Mulaw Belete T. An up-to-date overview of therapeutic agents for the treatment of COVID-19 disease Clin. Pharmacol. 2020 12 203 212 10.2147/CPAA.S284809 33363416 37. Xu J. Xue Y. Zhou R. Shi P.Y. Li H. Zhou J. Drug repurposing approach to combating coronavirus: Potential drugs and drug targets Med. Res. Rev. 2021 41 1375 1426 10.1002/med.21763 33277927 38. Shippey E.A. Wagler V.D. Collamer A.N. Hydroxychloroquine: An old drug with new relevance Cleve. Clin. J. Med. 2018 85 459 467 10.3949/ccjm.85a.17034 29883308 39. Schrezenmeier E. Dörner T. Mechanisms of action of hydroxychloroquine and chloroquine: Implications for rheumatology Nat. Rev. Rheumatol. 2020 16 155 166 10.1038/s41584-020-0372-x 32034323 40. Liu J. Cao R. Xu M. Wang X. Zhang H. Hu H. Li Y. Hu Z. Zhong W. Wang M. Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro Cell Discov. 2020 6 16 10.1038/s41421-020-0156-0 32194981 41. Gao J. Tian Z. Yang X. Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies Biosci. Trends 2020 14 72 73 10.5582/bst.2020.01047 32074550 42. Cortegiani A. Ippolito M. Ingoglia G. Iozzo P. Giarratano A. Update I. A systematic review on the efficacy and safety of chloroquine/hydroxychloroquine for COVID-19 J. Crit. Care 2020 59 176 190 10.1016/j.jcrc.2020.06.019 32683212 43. Axfors C. Schmitt A.M. Janiaud P. Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19: An international collaborative meta-analysis of randomized trials Nat. Commun. 2021 12 2349 10.1038/s41467-021-22446-z 33859192 44. Gallus S. Clavenna A. Lugo A. Does hydroxychloroquine reduce mortality for COVID-19? Eur. J. Intern. Med. 2020 82 21 22 10.1016/j.ejim.2020.10.015 33127218 45. Temple C. Hoang R. Hendrickson R.G. Toxic effects from ivermectin use associated with prevention and treatment of COVID-19 N. Engl. J. Med. 2021 20 2197 2198 10.1056/NEJMc2114907 34670041 46. Wagstaff K.M. Sivakumaran H. Heaton S.M. Harrich D. Jans D.A. Ivermectin is a specific inhibitor of importin α/β-mediated nuclear import able to inhibit replication of HIV-1 and dengue virus Biochem. J. 2012 443 851 856 10.1042/BJ20120150 22417684 47. Caly L. Druce J.D. Catton M.G. Jans D.A. Wagstaff K.M. The FDA-approved drug ivermectin inhibits the replication of SARS-CoV-2 in vitro Antivir. Res. 2020 178 104787 10.1016/j.antiviral.2020.104787 32251768 48. Lehrer S. Rheinstein P.H. Ivermectin docks to the SARS-CoV-2 spike receptor-binding domain attached to ACE2 In Vivo 2020 34 3023 3026 10.21873/invivo.12134 32871846 49. Richardson P. Griffin I. Tucker C. Smith D. Oechsle O. Phelan A. Rawling M. Savory E. Stebbing J. Baricitinib as potential treatment for 2019-nCoV acute respiratory disease Lancet 2020 395 e30 e31 10.1016/S0140-6736(20)30304-4 32032529 50. Stebbing J. Phelan A. Griffin I. Tucker C. Oechsle O. Smith D. Richardson P. COVID-19: Combining antiviral and anti-inflammatory treatments Lancet Infect. Dis. 2020 20 400 402 10.1016/S1473-3099(20)30132-8 32113509 51. Kalil A.C. Patterson T.F. Mehta A.K. Tomashek K.M. Wolfe C.R. Ghazaryan V. Marconi V.C. Ruiz-Palacios G.M. Hsieh L. Kline S. ACTT-2 Study Group Members. Baricitinib plus remdesivir for hospitalized adults with COVID-19 N. Engl. J. Med. 2021 384 795 807 10.1056/NEJMoa2031994 33306283 52. Coronavirus (COVID-19) Update: FDA Authorizes Drug Combination for Treatment of COVID-19 Available online: https://www.fda.gov/news-events/press-announcements/coronavirus-COVID-19-update-fda-authorizes-drug-combination-treatment-COVID-19 (accessed on 25 November 2021) 53. Coronavirus (COVID-19) Update: July 30, 2021 | FDA Available online: https://www.fda.gov/news-events/press-announcements/coronavirus-COVID-19-update-july-30-2021 (accessed on 25 November 2021) 54. Ottaiano A. Capozzi M. De Divitiis C. De Stefano A. Botti G. Avallone A. Tafuto S. Gemcitabine mono-therapy versus gemcitabine plus targeted therapy in advanced pancreatic cancer: A meta-analysis of randomized phase III trials Acta Oncol. 2017 56 377 383 10.1080/0284186X.2017.1288922 28256961 55. Humbert M. de Blay F. Garcia G. Prud’homme A. Leroyer C. Magnan A. Tunon-de-Lara J.M. Pison C. Aubier M. Charpin D. Masitinib, a c-kit/PDGF receptor tyrosine kinase inhibitor, improves disease control in severe corticosteroid-dependent asthmatics Allergy 2009 64 1194 1201 10.1111/j.1398-9995.2009.02122.x 19614621 56. Folch J. Petrov D. Ettcheto M. Pedrós I. Abad S. Beas-Zarate C. Lazarowski A. Marin M. Olloquequi J. Auladell C. Masitinib for the treatment of mild to moderate Alzheimer’s disease Exp. Rev. Neurother. 2015 15 587 596 10.1586/14737175.2015.1045419 57. Vermersch P. Benrabah R. Schmidt N. Zéphir H. Clavelou P. Vongsouthi C. Dubreuil P. Moussy A. Hermine O. Masitinib treatment in patients with progressive multiple sclerosis: A randomized pilot study BMC Neurol. 2012 12 36 10.1186/1471-2377-12-36 22691628 58. Mora J.S. Genge A. Chio A. Estol C.J. Chaverri D. Hernández M. Marín S. Mascias J. Rodriguez G.E. Povedano M. Masitinib as an add-on therapy to riluzole in patients with amyotrophic lateral sclerosis: A randomized clinical trial Amyotroph. Lateral Scler. Frontotemp. Degener. 2020 21 5 14 10.1080/21678421.2019.1632346 31280619 59. Drayman N. DeMarco J.K. Jones K.A. Azizi S.A. Froggatt H.M. Tan K. Maltseva N.I. Chen S. Nicolaescu V. Dvorkin S. Masitinib is a broad coronavirus 3CL inhibitor that blocks replication of SARS-CoV-2 Science 2021 373 931 936 10.1126/science.abg5827 34285133 60. Anand K. Ziebuhr J. Wadhwani P. Mesters J.R. Hilgenfeld R. Coronavirus main proteinase (3CLpro) structure: Basis for design of anti-SARS drugs Science 2003 300 1763 1767 10.1126/science.1085658 12746549 61. Ogata A. Tanaka T. Tocilizumab for the treatment of rheumatoid arthritis and other systemic autoimmune diseases: Current perspectives and future directions Int. J. Rheumatol. 2012 2012 946048 10.1155/2012/946048 22315615 62. Sabaka P. Koščálová A. Straka I. Hodosy J. Lipták R. Kmotorková B. Kachlíková M. Kušnírová A. Role of interleukin 6 as a predictive factor for a severe course of COVID-19: Retrospective data analysis of patients from a long-term care facility during COVID-19 outbreak BMC Infect. Dis. 2021 21 308 10.1186/s12879-021-05945-8 33781216 63. Santa Cruz A. Mendes-Frias A. Oliveira A.I. Dias L. Matos A.R. Carvalho A. Capela C. Pedrosa J. Castro A.G. Silvestre R. Interleukin-6 Is a biomarker for the development of fatal severe acute respiratory syndrome coronavirus 2 pneumonia Front. Immunol. 2021 12 613422 10.3389/fimmu.2021.613422 33679753 64. Mariette X. Hermine O. Tharaux P. Resche-Rigon M. Steg P.G. Porcher R. Ravaud P. Effectiveness of tocilizumab in patients hospitalized with COVID-19: A follow-up of the CORIMUNO-TOCI-1 randomized clinical trial JAMA Intern. Med. 2021 181 1241 1243 10.1001/jamainternmed.2021.2209 34028504 65. Wei Q. Lin H. Wei R.G. Chen N. He F. Zou D.H. Wei J.R. Tocilizumab treatment for COVID-19 patients: A systematic review and meta-analysis Infect. Dis. Poverty 2021 10 71 10.1186/s40249-021-00857-w 34001244 66. Salama C. Mohan S.V. Tocilizumab in patients hospitalized with COVID-19 pneumonia. Reply N. Engl. J. Med. 2021 384 1473 1474 10.1056/NEJMoa2030340 67. Rosas I.O. Bräu N. Waters M. Go R.C. Hunter B.D. Bhagani S. Skiest D. Aziz M.S. Cooper N. Douglas I.S. Tocilizumab in hospitalized patients with severe COVID-19 pneumonia N. Engl. J. Med. 2021 384 1503 1516 10.1056/NEJMoa2028700 33631066 68. World Health Organization Therapeutics and COVID-19: Living Guideline, 24 September 2021 World Health Organization Geneva, Switzerland 2021 Available online: https://apps.who.int/iris/handle/10665/345356 (accessed on 25 November 2021) 69. World Health Organization World Health Organization Model List of Essential Medicines: 22nd List, 2021 World Health Organization Geneva, Switzerland 2021 70. Yasir M. Goyal A. Bansal P. Sonthalia S. Corticosteroid Adverse Effects StatPearls Publishing Treasure Island, FL, USA 2022 71. Sinha S. Rosin N.L. Arora R. Labit E. Jaffer A. Cao L. Farias R. Nguyen A.P. de Almeida L.G.N. Dufour A. Dexamethasone modulates immature neutrophils and interferon programming in severe COVID-19 Nat. Med. 2022 28 201 211 10.1038/s41591-021-01576-3 34782790 72. The Recovery Collaborative Group Dexamethasone in hospitalized patients with COVID-19 N. Engl. J. Med. 2021 384 693 704 10.1056/NEJMoa2021436 32678530 73. Boriskin Y.S. Pécheur E.I. Polyak S.J. Arbidol: A broad-spectrum antiviral that inhibits acute and chronic HCV infection Virol. J. 2006 3 56 10.1186/1743-422X-3-56 16854226 74. Blaising J. Polyak S.J. Pécheur E.I. Arbidol as a broad-spectrum antiviral: An update Antivir. Res. 2014 107 84 94 10.1016/j.antiviral.2014.04.006 24769245 75. Pécheur E.I. Borisevich V. Halfmann P. Morrey J.D. Smee D.F. Prichard M. Mire C.E. Kawaoka Y. Geisbert T.W. Polyak S.J. The synthetic antiviral drug arbidol inhibits globally prevalent pathogenic viruses J. Virol. 2016 90 3086 3092 10.1128/JVI.02077-15 26739045 76. Teissier E. Zandomeneghi G. Loquet A. Lavillette D. Lavergne J.P. Montserret R. Cosset F.L. Böckmann A. Meier B.H. Penin F. Mechanism of inhibition of enveloped virus membrane fusion by the antiviral drug arbidol PLoS ONE 2011 6 e15874 10.1371/journal.pone.0015874 21283579 77. Vankadari N. Arbidol: A potential antiviral drug for the treatment of SARS-CoV-2 by blocking the trimerization of viral spike glycoprotein? Int. J. Antimicrob. Agents 2020 56 105998 10.1016/j.ijantimicag.2020.105998 32360231 78. Xu P. Huang J. Fan Z. Huang W. Qi M. Lin X. Song W. Yi L. Arbidol/IFN-α2b therapy for patients with corona virus disease 2019: A retrospective multicenter cohort study Microbes Infect. 2020 22 200 205 10.1016/j.micinf.2020.05.012 32445881 79. Deng L. Li C. Zeng Q. Liu X. Li X. Zhang H. Hong Z. Xia J. Arbidol combined with LPV/r versus LPV/r alone against Corona Virus Disease 2019: A retrospective cohort study J. Infect. 2020 81 e1 e5 10.1016/j.jinf.2020.03.002 80. Darazam I.A. Shokouhi S. Mardani M. Pourhoseingholi M.A. Rabiei M.M. Hatami F. Shabani M. Moradi O. Gharehbagh F.J. Irvani S.S.N. Umifenovir in hospitalized moderate to severe COVID-19 patients: A randomized clinical trial Int. Immunopharmacol. 2021 99 107969 10.1016/j.intimp.2021.107969 34273635 81. Warren T.K. Jordan R. Lo M.K. Ray A.S. Mackman R.L. Soloveva V. Siegel D. Perron M. Bannister R. Hui H.C. Therapeutic efficacy of the small molecule GS-5734 against Ebola virus in rhesus monkeys Nature 2016 531 381 385 10.1038/nature17180 26934220 82. Müller C. Schulte F.W. Lange-Grünweller K. Obermann W. Madhugiri R. Pleschka S. Ziebuhr J. Hartmann R.K. Grünweller A. Broad-spectrum antiviral activity of the eIF4A inhibitor silvestrol against corona-and picornaviruses Antivir. Res. 2018 150 123 129 10.1016/j.antiviral.2017.12.010 29258862 83. Brown A.J. Won J.J. Graham R.L. Dinnon K.H. 3rd Sims A.C. Feng J.Y. Cihlar T. Denison M.R. Baric R.S. Sheahan T.P. Broad spectrum antiviral remdesivir inhibits human endemic and zoonotic deltacoronaviruses with a highly divergent RNA dependent RNA polymerase Antivir. Res. 2019 169 104541 10.1016/j.antiviral.2019.104541 31233808 84. Gordon C.J. Tchesnokov E.P. Woolner E. Perry J.K. Feng J.Y. Porter D.P. Götte M. Remdesivir is a direct-acting antiviral that inhibits RNA-dependent RNA polymerase from severe acute respiratory syndrome coronavirus 2 with high potency J. Biol. Chem. 2020 295 6785 6797 10.1074/jbc.RA120.013679 32284326 85. Cusinato J. Cau Y. Calvani A.M. Mori M. Repurposing drugs for the management of COVID-19 Exp. Opin. Ther. Pat. 2021 31 295 307 10.1080/13543776.2021.1861248 86. FDA Approves First Treatment for COVID-19 Available online: https://www.fda.gov/news-events/press-announcements/fda-approves-first-treatment-COVID-19 (accessed on 25 November 2021) 87. Veklury | European Medicines Agency Available online: https://www.ema.europa.eu/en/medicines/human/EPAR/veklury (accessed on 25 November 2021) 88. Joshi S. Parkar J. Ansari A. Vora A. Talwar D. Tiwaskar M. Patil S. Barkate H. Role of favipiravir in the treatment of COVID-19 Int. J. Infect. Dis. 2021 102 501 508 10.1016/j.ijid.2020.10.069 33130203 89. Baranovich T. Wong S.S. Armstrong J. Marjuki H. Webby R.J. Webster R.G. Govorkova E.A. T-705 (Favipiravir) induces lethal mutagenesis in influenza A H1N1 viruses in vivo J. Virol. 2013 87 3741 3751 10.1128/JVI.02346-12 23325689 90. Jin Z. Smith L.K. Rajwanshi V.K. Kim B. Deval J. The ambiguous base-pairing and high substrate efficiency of T-705 (Favipiravir) Ribofuranosyl 5′-triphosphate towards influenza A virus polymerase PLoS ONE 2013 8 e68347 10.1371/journal.pone.0068347 23874596 91. Oestereich L. Lüdtke A. Wurr S. Rieger T. Mũnoz-Fontela C. Günther S. Successful treatment of advanced Ebola virus infection with T-705 (favipiravir) in a small animal model Antivir. Res. 2014 105 17 21 10.1016/j.antiviral.2014.02.014 24583123 92. Vaidyanathan G. Scientists criticize use of unproven COVID drugs in India Nature 2020 587 187 188 10.1038/d41586-020-03105-7 33169025 93. Shrestha D.B. Budhathoki P. Khadka S. Shah P.B. Pokharel N. Rashmi P. Favipiravir versus other antiviral or standard of care for COVID-19 treatment: A rapid systematic review and meta-analysis Virol. J. 2020 17 141 10.1186/s12985-020-01412-z 32972430 94. Favipiravir to be Investigated as a Possible COVID-19 Treatment for at-Home Recovery in the Principle Trial Available online: https://www.principletrial.org/news/favipiravir-to-be-investigated-as-a-possible-COVID-19-treatment-for-at-home-recovery-in-the-principle-trial (accessed on 25 November 2021) 95. Fischer W. Eron J.J. Holman W. Cohen M.S. Fang L. Szewczyk L.J. Sheahan T.P. Baric R. Mollan K.R. Wolfe C.R. Molnupiravir, an oral antiviral treatment for COVID-19 medRxiv 2021 17 preprint 10.1101/2021.06.17.21258639 96. Singh A.K. Singh A. Singh R. Misra A. Molnupiravir in COVID-19: A systematic review of literature Diabetes Metab. Syndr. 2021 15 102329 10.1016/j.dsx.2021.102329 34742052 97. Oldfield V. Plosker G.L. Lopinavir/ritonavir: A review of its use in the management of HIV infection Drugs 2006 66 769 802 10.2165/00003495-200666090-00012 16706551 98. Chu C.M. Cheng V.C. Hung I.F. Wong M.M. Chan K.H. Chan K.S. Kao R.Y. Poon L.L. Wong C.L. Guan Y. HKU/UCH SARS Study Group. Role of lopinavir/ritonavir in the treatment of SARS: Initial virological and clinical findings Thorax 2004 59 252 256 10.1136/thorax.2003.012658 14985565 99. Arabi Y.M. Alothman A. Balkhy H.H. Al-Dawood A. AlJohani S. Harbi A.S. Kojan S. Jeraisy A.M. Deeb A.M. Assiri A.M. Treatment of Middle East respiratory syndrome with a combination of lopinavir-ritonavir and interferonb1b (MIRACLE trial): Study protocol for a randomized controlled trial Trials 2018 19 81 10.1186/s13063-017-2427-0 29382391 100. He J. Hu L. Huang X. Wang C. Zhang Z. Wang Y. Zhang D. Ye W. Potential of coronavirus 3C like protease inhibitors for the development of new anti-SARS-CoV-2 drugs: Insights from structures of protease and inhibitors Int. J. Antimicrob. Agents 2020 56 106055 10.1016/j.ijantimicag.2020.106055 32534187 101. WHO COVID-19 Solidarity Therapeutics Trial Available online: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov/solidarity-clinical-trial-for-COVID-19-treatments (accessed on 12 August 2021) 102. Pillaiyar T. Manickam M. Namasivayam V. Hayashi Y. Jung S.H. An overview of severe acute respiratory syndrome-coronavirus (SARS-CoV) 3CL protease inhibitors: Peptidomimetics and small molecule chemotherapy J. Med. Chem. 2016 59 6595 6628 10.1021/acs.jmedchem.5b01461 26878082 103. Pedersen N.C. Kim Y. Liu H. Kankanamalage G.A.C. Eckstrand C. Groutas W.C. Bannasch M. Meadows J.M. Chang K.O. Efficacy of a 3C-like protease inhibitor in treating various forms of acquired feline infectious peritonitis J. Feline Med. Surg. 2018 20 378 392 10.1177/1098612X17729626 28901812 104. Hull M.W. Montaner J.S. Ritonavir-boosted protease inhibitors in HIV therapy Ann. Med. 2011 43 375 388 10.3109/07853890.2011.572905 21501034 105. Sultana J. Crisafulli S. Gabbay F. Lynn E. Shakir S. Trifirò G. Challenges for drug repurposing in the COVID-19 pandemic era Front. Pharmacol. 2020 11 588654 10.3389/fphar.2020.588654 33240091 106. Bispo N.A. Culleton R. Silva L.A. Cravo P. A systematic in silico search for target similarity identifies several approved drugs with potential activity against the Plasmodium falciparum apicoplast PLoS ONE 2013 8 e59288 10.1371/annotation/0bbd3579-5212-4dcf-a5ef-dd3d8e26f287 23555651 107. Neves B.J. Braga R.C. Bezerra J.C.B. Cravo P.V.L. Andrade C.H. In silico repositioning-chemogenomics strategy identifies new drugs with potential activity against multiple life stages of Schistosoma mansoni PLoS Negl. Trop. Dis. 2015 9 e3435 10.1371/journal.pntd.0003435 25569258 108. Rodrigues L. Cravo P. Viveiros M. Efflux pump inhibitors as a promising adjunct therapy against drug resistant tuberculosis: A new strategy to revisit mycobacterial targets and repurpose old drugs Exp. Rev. Anti. Infect. Ther. 2020 18 741 757 10.1080/14787210.2020.1760845 32434397 109. Schneider P. Walters W.P. Plowright A.T. Sieroka N. Listgarten J. Goodnow R.A. Jr. Fisher J. Jansen J.M. Duca J.S. Rush T.S. Rethinking drug design in the artificial intelligence era Nat. Rev. Drug Discov. 2020 19 353 364 10.1038/s41573-019-0050-3 31801986 110. Khataniar A. Pathak U. Rajkhowa S. Jha A.N. A comprehensive review of drug repurposing strategies against known drug targets of COVID-19 COVID 2022 2 148 167 10.3390/covid2020011 111. Mohamed K. Yazdanpanah N. Saghazadeh A. Rezaei N. Computational drug discovery and repurposing for the treatment of COVID-19: A systematic review Bioorg. Chem. 2021 106 104490 10.1016/j.bioorg.2020.104490 33261845 112. Arshadi K.A. Webb J. Salem M. Cruz E. Calad-Thomson S. Ghadirian N. Collins J. Diez-Cecilia E. Kelly B. Goodarzi H. Artificial intelligence for COVID-19 drug discovery and vaccine development Front. Artif. Intell. 2020 3 65 10.3389/frai.2020.00065 33733182 113. Sharma P.P. Bansal M. Sethi A. Poonam Pena L. Goel V.K. Grishina M. Chaturvedi S. Kumar D. Rath B. Computational methods directed towards drug repurposing for COVID-19: Advantages and limitations RSC Adv. 2021 11 36181 36198 10.1039/D1RA05320E 35492747 114. Gopal D. Skariyachan S. Recent perspectives on COVID-19 and computer-aided virtual screening of natural compounds for the development of therapeutic agents towards SARS-CoV-2 Methods in Pharmacology and Toxicology Springer Berlin/Heidelberg, Germany 2020 115. Gurung A.B. Ali M.A. Lee J. Farah M.A. Al-Anazi K.M. An updated review of computer-aided drug design and its application to COVID-19 Biomed. Res Int. 2021 2021 8853056 10.1155/2021/8853056 34258282 116. Fadlalla M. Ahmed M. Ali M. Elshiekh A.A. Yousef B.A. Molecular docking as a potential approach in repurposing drugs against COVID-19: A systematic review and novel pharmacophore models Curr. Pharmacol. Rep. 2022 ahead of print 1 15 10.1007/s40495-022-00285-w 35381996 117. Liu Y. Gan J. Wang R. Yang X. Xiao Z. Cao Y. DrugDevCovid19: An atlas of anti-COVID-19 compounds derived by computer-aided drug design Molecules 2022 27 683 10.3390/molecules27030683 35163948 118. Ewing T.J.A. Makino S. Skillman A.G. Kuntz I.D. DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases J. Comput. Aided. Mol. Des. 2001 15 411 428 10.1023/A:1011115820450 11394736 119. Pagadala N.S. Syed K. Tuszynski J. Software for molecular docking: A review Biophys. Rev. 2017 9 91 102 10.1007/s12551-016-0247-1 28510083 120. Stebbing J. Krishnan V. de Bono S. Ottaviani S. Casalini G. Richardson P.J. Monteil V. Lauschke V.M. Mirazimi A. Youhanna S. Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients EMBO Mol. Med. 2020 12 e12697 10.15252/emmm.202012697 32473600 121. UniProt Available online: https://www.uniprot.org/ (accessed on 12 August 2021) 122. National Centre for Biotechnology Information (NCBI) Available online: https://www.ncbi.nlm.nih.gov/ (accessed on 12 August 2021) 123. DrugBank Available online: https://go.drugbank.com/ (accessed on 12 August 2021) 124. Wishart D.S. Feunang Y.D. Guo A.C. Lo E.J. Marcu A. Grant J.R. Sajed T. Johnson D. Li C. Sayeeda Z. DrugBank 5.0: A major update to the DrugBank database for 2018 Nucleic Acids Res. 2018 46 D1074 D1082 10.1093/nar/gkx1037 29126136 125. EMA Issues Advice on Use of Antibody Combination (Bamlanivimab/Etesevimab) Available online: https://www.ema.europa.eu/en/news/ema-issues-advice-use-antibody-combination-bamlanivimab-etesevimab (accessed on 15 December 2021) 126. The ConSurf Server Available online: https://consurf.tau.ac.il/ (accessed on 12 August 2021) 127. Ashkenazy H. Abadi S. Martz E. Chay O. Mayrose I. Pupko T. Ben-Tal N. ConSurf 2016: An improved methodology to estimate and visualize evolutionary conservation in macromolecules Nucleic Acids Res. 2016 44 W344 W350 10.1093/nar/gkw408 27166375 128. Wang M. Cao R. Zhang L. Yang X. Liu J. Xu M. Shi Z. Hu Z. Zhong W. Xiao G. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro Cell Res. 2020 30 269 271 10.1038/s41422-020-0282-0 32020029 129. Yao X. Ye F. Zhang M. Cui C. Huang B. Niu P. Liu X. Zhao L. Dong E. Song C. In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Clin. Infect. Dis. 2020 71 732 739 10.1093/cid/ciaa237 32150618 130. Azouz N.P. Klingler A.M. Callahan V. Akhrymuk I.V. Elez K. Raich L. Henry B.M. Benoit J.L. Benoit S.W. Noé F. Alpha 1 antitrypsin is an inhibitor of the SARS-CoV-2-priming protease TMPRSS2 Pathog. Immun. 2021 6 55 74 10.20411/pai.v6i1.408 33969249 131. Bojkova D. Bechtel M. McLaughlin K.M. McGreig J.E. Klann K. Bellinghausen C. Rohde G. Jonigk D. Braubach P. Ciesek S. Aprotinin inhibits SARS-CoV-2 replication Cells 2020 9 2377 10.3390/cells9112377 33143316 132. Hoffmann M. Mösbauer K. Hofmann-Winkler H. Kaul A. Kleine-Weber H. Krüger N. Gassen N.C. Müller M.A. Drosten C. Pöhlmann S. Chloroquine does not inhibit infection of human lung cells with SARS-CoV-2 Nature 2020 585 588 590 10.1038/s41586-020-2575-3 32698190 133. Ou T. Mou H. Zhang L. Ojha A. Choe H. Farzan M. Hydroxychloroquine-mediated inhibition of SARS-CoV-2 entry is attenuated by TMPRSS2 PLoS Pathog. 2021 17 e1009212 10.1371/journal.ppat.1009212 33465165 134. Demir A. Erayman İ. Doğan O. Kekilli M. Influence of aluminum salts on COVID-19 infected patients Turk. J. Med. Sci. 2020 50 1771 1780 10.3906/sag-2009-140 33315350 135. Frampton J.E. Lee C.R. Faulds D. Filgrastim: A review of its pharmacological properties and therapeutic efficacy in neutropenia Drugs 1994 48 731 760 10.2165/00003495-199448050-00007 7530630 136. Spencer H.C. Wurzburger R. COVID-19 presenting as neutropenic fever Ann. Hematol. 2020 99 1939 1940 10.1007/s00277-020-04128-w 32535707 137. Giorgi E.P. Shirley I.M. Grant J.K. Stewart J.C. Androgen dynamics in vitro in the human prostate gland. Effect of cyproterone and cyproterone acetate Biochem. J. 1973 132 465 474 10.1042/bj1320465 4125095 138. Angus L.M. Nolan B.J. Zajac J.D. Cheung A.S. A systematic review of antiandrogens and feminization in transgender women Clin. Endocrinol. 2021 94 743 752 10.1111/cen.14329 139. Fagan N. Meah N. York K. Bokhari L. Fletcher G. Chen G. Tobin D.J. Messenger A. Irvine A.D. Sinclair R. Shedding light on therapeutics in alopecia and their relevance to COVID-19 Clin. Dermatol. 2021 39 76 83 10.1016/j.clindermatol.2020.12.015 33972056 140. Autry B.M. Wadhwa R. Mifepristone StatPearls Publishing Treasure Island, FL, USA 2021 141. Schafer E.A. Venkatachari N.J. Ayyavoo V. Antiviral effects of mifepristone on human immunodeficiency virus type-1 (HIV-1): Targeting Vpr and its cellular partner, the glucocorticoid receptor (GR) Antivir. Res. 2006 72 224 232 10.1016/j.antiviral.2006.06.008 16889838 142. Martin A.J. Jans D.A. Antivirals that target the host IMPα/β1-virus interface Biochem. Soc. Trans. 2021 49 281 295 10.1042/BST20200568 33439253 143. Messina F. Giombini E. Agrati C. Vairo F. Bartoli A.T. Al Moghazi S. Piacentini M. Locatelli F. Kobinger G. Maeurer M. COVID 19 INMI Network Medicine for IDs Study Group. COVID-19: Viral-host interactome analyzed by network based approach model to study pathogenesis of SARS-CoV-2 infection J. Transl. Med. 2020 18 233 10.1186/s12967-020-02405-w 32522207 144. Li X. Yu J. Zhang Z. Ren J. Peluffo A.E. Zhang W. Zhao Y. Wu J. Yan K. Cohen D. Network bioinformatics analysis provides insight into drug repurposing for COVID-2019 Med. Drug Discov. 2021 10 100090 10.1016/j.medidd.2021.100090 33817623 145. Zhou Y. Hou Y. Shen J. Huang Y. Martin W. Cheng F. Network based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2 Cell Discov. 2020 6 14 10.1038/s41421-020-0153-3 32194980

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091128 animals-12-01128 Review The Feeding Behaviour Habits of Growing-Finishing Pigs and Its Effects on Growth Performance and Carcass Quality: A Review Fornós Marta 1 Sanz-Fernández Santos 2 Jiménez-Moreno Encarnación 1 Carrión Domingo 1 https://orcid.org/0000-0002-5828-7142 Gasa Josep 3 https://orcid.org/0000-0003-0148-2892 Rodríguez-Estévez Vicente 2* Babicz Marek Academic Editor Szyndler-Nędza Magdalena Academic Editor 1 Cargill Animal Nutrition, 50170 Mequinenza, Spain; fornos.marta@gmail.com (M.F.); encarnacion_jimenez@cargill.com (E.J.-M.); domingo_carrion@cargill.com (D.C.) 2 Department of Animal Production, Universidad de Córdoba, 14071 Córdoba, Spain; v22safes@uco.es 3 Animal Nutrition and Welfare Service, Department of Animal and Food Sciences, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain; josep.gasa@uab.cat * Correspondence: pa2roesv@uco.es; Tel.: +34-957-21-80-83 28 4 2022 5 2022 12 9 112831 3 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary The study of feeding behaviour habits (FBHs) of growing-finishing pigs is of interest due to its influence on growth performance and carcass quality. The present review collates the available scientific data regarding the internal and external factors affecting the FBHs and its influence on growth performance and carcass quality. Factors explored were age, sex, breed, space allowance, feeder design, feed form, diet composition, and environmental conditions. The reviewed data indicate that the factors explored affect the FBHs of growing-finishing pigs. Moreover, meal size and feeding rate were the two FBHs most related with performance, being positively correlated with average daily feed intake, growth rate, and final body weight, but with no clear effect on feed efficiency, whereas the few studies regarding the influence of FBHs on carcass traits indicate a positive correlation between meal size and feeding rate with backfat thickness. Therefore, the available data provide evidence that modifying FBHs may improve the performance of grow-ing-finishing pigs, but not necessarily feed efficiency. Abstract Based on the available data of feeding behaviour habits (FBHs), this work aimed to discuss which type of pig, according to its FBHs, performs better and is more efficient. As pigs grow, average daily feed intake, meal size, and feeding rate increase, whereas small variations or even decreases in time spent eating and daily feeder visits have been reported. Moreover, the sex, breed, space allowance, feeder design, feed form, diet composition, and environmental conditions modify FBHs. On the other hand, the literature indicates the existence of four types of pigs: pigs that eat their daily feed intake in many short meals (nibblers) or in few large meals (meal eaters) combined with eating fast (faster eaters) or slow (slow eaters). The available scientific literature about ad libitum fed pigs suggests that pigs eating faster with bigger meals eat more, gain more weight, and are fatter than pigs eating less, slower, and with smaller meals. However, the feeding rate and the meal size do not influence feed efficiency. In conclusion, studies comparing growing-finishing pigs with similar feed intake, but different feeding rate and meal size are needed to better understand the influence of FBHs on feed efficiency. growing-finishing pig feeding behaviour carcass growth performance This research received no external funding. ==== Body pmc1. Introduction Feed cost represents approximately 65% of the cost production of a pig kg deadweight [1]. Therefore, the search for strategies to improve the utilisation rate of nutrients during the growing-finishing period is of permanent interest [2,3,4]. One of the important factors influencing the performance and carcass quality of growing-finishing pigs is feeding behaviour habits (FBHs) [5], which can be described not only by average daily feed intake (ADFI), but also by other criteria such as the daily number of feeder visits, the daily time spent eating, the feed consumed per feeder visit or the rhythm of ingesta, among others. These can be registered and calculated thanks to the availability in the market of automatic feeding systems [6]. It is known that the ADFI is directly related to energy and nutrient intake [7]; however, FBHs influence the digestion and absorption of feed nutrients [2,8]. Meal size is one of the factors that influences the digestibility of nutrients [9]. In fact, de Haer et al. [10] reported that meal size and feeding rate influence the growth performance of growing-finishing pigs, with pigs eating small meals and slower being leaner and with a lower average daily gain (ADG), with poor influence of the number of meals and the time spent eating with performance. In addition, Carcò et al. [5] concluded that the feeding rate is the most correlated FBH parameter with growth performance being positively related with ADG and final body weight (BW). Furthermore, few studies have evaluated the influence of FBHs on carcass quality traits [5,10,11]. The first aim of the present review was to collate and compare data showing the effect of internal (age, sex, and breed) and external factors (group size and feeder space allowance, feeder design, feed distribution and feed form, diet composition and environmental conditions) on the FBHs of growing-finishing pigs. The second aim was to collate and compare the published data regarding the influence of FBHs on the growth performance and carcass quality traits of growing-finishing pigs. The implications of FBHs as a strategy to improve performance and carcass quality are summarised. 2. A Description of the Feeding Behaviour Habits of Growing-Finishing Pigs Table 1 and Figure 1 include the different published criteria used to describe the FBHs of growing-finishing pigs and its interrelation, respectively. The FBH parameters were average daily feed intake (ADFI, total feed consumed per pig and day), feeder visits per day (TV, number of feeder visits per pig and day), meals per day (TM, number of meals per pig and day), time spent eating (TD, total time spent eating per pig and day), visit size (VS, feed consumed per feeder visit), meal size (MS, feed consumed per meal), and feeding rate (FR, feed intake per minute spent eating). A determinate number of feeder visits conducted consecutively within a period by the same pig are often clustered into one meal [6,10,11,12,13,14,15,16]. However, the period selected between feeder visits conducted consecutively by the same pig to determine a meal varies from one minute [15] to 28.3 min [16] between studies. Therefore, when comparing FBH parameters such as MS between studies, it is important to know the criteria used to define one meal. We suggest that the standardisation of a criterion to define a meal is of interest. 3. Internal Factors That Influence Feeding Behaviour Habits of Growing-Finishing Pigs 3.1. Age A summary of the effect of age on the FBHs of growing-finishing pigs is shown in Table 2. As pigs grow, the ADFI increases; however, the magnitude of the ADFI increase is variable among studies. Labroue et al. [11] and Andretta et al. [15] reported an increase in the ADFI of around 60% in pigs of similar BW, from 35 to 95–100 kg BW and from 30 to 100 kg BW, respectively; whereas Carcò et al. [5] reported a smaller quadratic increase in the ADFI in pigs from 47 to 145 kg BW and Hyun et al. [16] obtained an increase in the ADFI of 23% in pigs from 27 to 82 kg BW. On the other hand, pigs eat their ADFI from frequent feeder visits in weaned pigs to few and larger feeder visits in sows together with an increase in the FR [17,18]. The changes in the TV and VS may be due to larger stomach size as pigs grow. In fact, stomach size increases from 30 mL to 3.5 L from birth to a finishing pig [19]. Therefore, we hypothesize that 20 kg BW pigs ingesta could be limited by their stomach capacity and as a consequence, carry out a higher number of small feeder visits to achieve the desired ADFI. For instance, as growing-finishing pigs grow, ADFI, VS, MS, and FR increase, whereas small variations or even decreases in the TV, TM, and TD have been reported [5,11,15,16,20]. However, a large variability in the percentage of increase or decrease in all FBHs exists between studies. In terms of TV or TM, Labroue et al. [11] reported an increase in TV of 28% in pigs from 40 to 60 kg BW and a reduction of 11% in pigs from 60 to 90 kg BW; whereas Hyun et al. [16] and Gonyou and Lou [20] obtained a reduction of 17% in the TM and of 24% in the TV, respectively, in pigs of similar BW. In addition, Andretta et al. [15] and Carcò et al. [5] reported small variations in terms of TM and TV as pigs grew, respectively. On the other hand, reductions from five to 45% in the TD [11,15,16,20] and increases from 45 to 123% in the VS or MS [11,15,16] together with increases from 22 to 133% in the FR as pigs grow have been reported [11,15,16,20]. 3.2. Sex The contradictory results regarding the effect of sex on the FBHs shown in several studies could be due to the different level of competition access to the feeder [11,15,16,21,22,23,24,25]. No differences between sex in terms of the FBHs of growing-finishing pigs were found in the meta-analysis of Averós et al. [21]. Similarly, Hyun et al. [16] only found differences between sexes in terms of TM, being higher for castrated males than for entire males and females; whereas Andretta et al. [15] reported no differences in terms of TM between castrated males and females. On the other hand, Cross et al. [22] observed that females spent an average of 6.2 min per day less in the feeder than castrated males, a result in line with the findings of Brown-Brandl et al. [25]. Moreover, Pichler et al. [23] observed bigger and longer meals for growing-finishing entire males than for females with no other FBHs showing differences between sex. In contrast, Young and Lawrence [24] observed a tendency for smaller and shorter feeder visits in entire males than females. In addition, Andretta et al. [15] reported a 19.23% smaller MS for females compared to castrated males. Furthermore, Labroue et al. [11] reported lower MS, ADFI, and TD in entire males than in castrated males with no significant differences in terms of TM, TV, and FR between both groups. Furthermore, Andretta et al. [15] indicated that females had a 6.6% lower FR than castrated males (39.9 vs. 42.7 g/min, females and castrated males, respectively). 3.3. Breed Breed modifies the FBHs of growing-finishing pigs [26,27,28,29]. Fernández et al. [26] classified Large White and Pietrain pigs as nibbler pigs due to more frequent and smaller feeder visits per day than Duroc and Landrace pigs. These results are in keeping with the findings of Labroue et al. [27], who reported more frequent smaller feeder visits for Large White than for Landrace pigs. Likewise, Baumung et al. [28] observed that Large White pigs ate their ADFI in more TV, with less TD and lower FR, whereas Landrace pigs tended to eat their ADFI in fewer and larger feeder visits. In addition, Quiniou et al. [29] concluded that Pietrain pigs could be characterised by eating their ADFI in more frequent, smaller meals than Meishan pigs, with Large White pigs in an intermediate position. On the other hand, Landrace and Large White pigs were classified as fast eater pigs due to the fact that they spent less TD with higher FR than Duroc and Pietrain pigs [26]. In agreement with those results, Labroue et al. [27] reported smaller differences in terms of FR with an average of 39.9 g/min for Large White and 41.5 g/min for Landrace pigs. In fact, Fernández et al. [26] suggested that each breed could be described as follows: Duroc pigs as meal and slow eaters, Landrace pigs as meal and fast eaters, Large White pigs as nibblers and fast eaters, and Pietrain pigs as nibblers and slow eaters. Despite the inconsistencies among studies of the impact of age, sex, and breed on the FBHs, all of them indicate that the three factors influence FBH. Although different intervals of BW were evaluated in the cited studies, it was found that as pigs grow, ADFI, MS, and FR increase, while decreases or small variations in TD, TV, and TM occur. The results concerning the sex effect on FBHs are confusing, suggesting that the external conditions such as housing conditions or internal factors such as age or breed used could modify FBHs. In fact, most of the authors observed different FBHs when comparing different breeds. Therefore, when comparing the FBH results of different scientific data sources, these factors must be considered. 4. External Factors That Influence Feeding Behaviour Habits of Growing-Finishing Pigs 4.1. Group Size and Feeder Space Allowance The EU Directive 2008/120/EC [30] determines the minimum stocking density for growing-finishing pigs at different BWs, which is an important factor, as it is demonstrated that it affects the stress levels of growing-finishing pigs [31]. In addition, later studies have observed that increasing group size in growing-finishing pigs in an adequate pen floor space and feeder ratio does not impact their welfare and growth performance [32]. These results suggest that an important factor is feeder access competency. In fact, it has been observed that individually housed pigs eat their ADFI in smaller, more frequent meals, spending more TD on account of a lower FR than group-housed pigs [12,33]. Moreover, when increasing the group size from two to 12 growing pigs per pen (from 27 to 48 kg BW) with the same stocking density of 0.9 m2/pig and with a single-space feeder, pigs reduced the TD and increased the FR with lower ADFI and ADG with no effect on the feed conversion ratio (FCR) [34]. When increasing the group size from five to 20 pigs per pen in 34 kg BW pigs for 29 days keeping the same stocking density of 1.06 m2/pig with a single-space feeder, pigs ate their DFI in fewer and larger feeder visits with higher FR with no impact on performance results (no differences in ADFI, ADG, and FCR) [35]. In finishing pigs, the increase from two to 12 pigs in group size increased the TD, MS, and FR and reduced the TV with no effect on ADFI, ADG, or FCR [36]. Therefore, these results suggest that growing-finishing pigs may modify their FBHs due to the feeder-space restricted situation rather than due to the increase in group size. In fact, Averós et al. [21] predicted that pigs fed under feeder space-restricted conditions increase their FR, make shorter feeder visits, and reduce the TD, results in agreement with Gonyou and Brumm [37]. In fact, Nielsen et al. [38] suggested that the FR may be used as an indicator of social constraint. Therefore, not only is pen floor space important, but it is also important to have the correct feeder ratio. In fact, an insufficient ratio of feeders in group-housed growing-finishing pigs may limit the nutritional requirements of the pigs. However, what does an adequate feeder ratio mean? Linear feeder space is defined as “the linear cm of feeder available per pig within a pen” (total feeder length per pen/total pigs per pen). PIC [39] recommends a minimum between 4.7 and 5.0 cm per pig for dry feeders and between 2.9 and 3.1 cm for wet–dry feeders in pigs from 27 kg BW to target BW to minimize feed waste without decreasing the ADFI of pigs. In fact, Smit et al. [40] observed that 3.4 cm of linear feeder space per pig in wet–dry feeders was enough as they obtained the same growth and final BW with lower ADFI than pigs with one more extra feeder, suggesting that the extra feeder allowed pigs to waste feed. Moreover, Morrison et al. [41] compared growing entire males pigs housed in deep-litter (pen of 200 pigs with 1 m2/pig and 8.3 pigs/feeding space) vs. pigs housed in conventional system (pen of 45 pigs with 0.70 m2/pig and 8.5 pigs/feeding space) from 20 to 22 weeks of age and observed that pigs housed in deep-litter spent less TD, with fewer and larger feeder visits, with a lower frequency of social interactions around the feeder compared to pigs in conventional treatment, concluding that the competency between pigs in the conventional system may be responsible for the shorter and more frequent feeder visits and that pigs are able to modify their FBHs in order to maintain performance under limitations in feeder space. In this sense, Rodríguez-Estévez et al. [42] found that free range pigs modified their foraging group size depending on the grazed resource, with 5.0 animals/group when pigs were grazing in an open pasture versus 5.8 when they were eating acorns under an oak crown because they were conditioned by the crown space to avoid competition when foraging, sharing a mean grazing surface to forage acorns of 8.9 m2/pig. On the other hand, growing-finishing pigs showed two peaks of feed intake throughout the day (one in the morning and another in the afternoon) [15,16,33], which has also been observed in free range finishing pigs grazing natural resources [43]. During these two peaks, which are accentuated under heat stress conditions [22], the competition access to the feeder increases. In fact, increasing the group size from 10 to 30 pigs increased the feeder occupancy rates due to increased feeding activity during the night and at midday [44], whereas increasing group size from 18 to 22 with an extra feeder allowed pigs to eat according to their preferent diurnal pattern instead of eating at other moments of the day [40]. Moreover, the hierarchy within a pen also influences the FBHs with fewer and larger visits for the high-ranking pigs than the low-ranking pigs [45]. Therefore, under feeder space restrictions, the hierarchy may distinctly modify FBH. These results highlight the importance of analysing the FBH at an individual level. In fact, the authors of the present review have presented a new approach [non-published study] to detect the maintenance of the FBHs at an individual level and broadly, the results indicate that most pigs maintain their FBHs throughout the growing-finishing period, except for ADFI, which is the most difficult FBH to predict. 4.2. Automatic Feeding Systems Used to Record Feeding Behaviour Habits Different types of automatic feeding systems exist in the market to record the FBH of group-housed growing-finishing pigs. In Table 3, a summary of the automatic feeding systems used and the FBH measured in previous studies is presented. In these systems, pigs are individually identified with a data-carrying transponder with a unique code per pig detected by the reader system installed in the trough [46]. Most of the systems record the start and end time, the duration and the amount of feed intake of each feeder visit, and the pig BW can be registered by the installation of a load cell; from these data, the different FBH parameters can be calculated. animals-12-01128-t003_Table 3 Table 3 Summary of the automatic feeding systems used and of the feeding behaviour habits measured in previous studies. Feeding Behaviour Parameter IVOG-Station (Figure 2) Compident Pig-MLP (Figure 3) ACEMA 48 (Figure 4) F.I.R.E., Hunday Electronics Similar System to the Used in Hyun et al. [16] Recording System in a Commercial Trough (See Figure 5) ADFI 1 [4,8,10,12,26,47,48] [5,49] [11] [16] [34,36] TV 2 [4,8,10,12,26,47,48] [5,49] [16] [34,36] TM 3 [8,10,12,26] [11] [16] TD 4 [4,8,10,12,26,47,48] [5,49] [11] [16] [34,36] [25] MS 5 [8,10,12,26] [11] [16] VS 6 [4,8,10,12,26,47,48] [5,49] [16] [34,36] FR 7 [4,8,10,12,26,47,48] [5,49] [11] [16] [34,36] 1 ADFI (average daily feed intake). 2 TV (number of feeder visits per pig and day). 3 TM (number of meals per pig and day according to each paper methodology; where a meal is: the successive feeder visits within five minutes [10]; the successive feeder visits within two minutes [11]. Carcò et al. [5] analysed the daily number of feeder visits. 4 TD (total minutes spent eating per pig and day). 5 MS (feed consumed per meal). 6 VS (feed consumed per feeder visit). 7 FR (feed intake per minute spent eating). Figure 2 IVOG—A station for individual feed intake recording in group housing (Instentec B.V., Marknesse, the Netherlands) used in the studies of De Haer and Merks, [12], De Haer et al. [10], De Haer and de Vries, [8], Georgsson and Svendsen, [47,48], Rauw et al. [4], and Fernández et al. [26] (Source: [www.insentec.eu], accessed on 5 April 2022). Figure 3 Compident MLP (Schauer Agrotonic GmbH, Austria) used in the study of Garrido-Izard et al. [49]. (a) Weighing scale. (b) Feeding station used during the experiment (Source: [49]). Figure 4 Electronic feeding station referred to as ACEMA “48” used in the study of Labroue et al. [11]. (1) Access door to the feeder. (2) Access corridor to the trough. (3) Adjustable side. (4) Trough door. (5) Feed hopper. (6) Mechanism to fill up the trough (Source: [11]). Figure 5 Schema of the panel and a photo of the panel after installation (Source: [25]). One of the available automatic feeding systems is the IVOG-Station (Individual feed intake recording in group housing, Instentec B.V., Marknesse, the Netherlands; Figure 2). This system consists of a dry-single space feeder placed on load cells with an adjustable fence that provides head and neck protection for the pig in front of the feeder. This system has been used in the studies of De Haer and Merks, [12], De Haer et al. [10], De Haer and de Vries, [8], Georgsson and Svendsen, [47,48], Rauw et al. [4] and Fernández et al. [26]. Another type of automatic feeding system is the Compident Pig-MLP (Schauer Agrotonic, Austria; Figure 3), which can feed growing-finishing pigs ad libitum and ration up to four different feeds at the same time and was used in the study of Carcò et al. [5] with lateral barriers to avoid competition among the pigs during the feeder visit together with a gate placed in front of the trough that permits only one pig inside the feeder. In the study of Garrido-Izard et al. [49], the Compident MLP (Schauer Agrotonic GmbH, Austria) was also used and equipped with an individual animal scale with lateral barriers to determine individual animal weight from 35 to 120 kg BW by measuring the weight of the front and back parts of the pig. Labroue et al. [11] used a system referred to as “ACEMA 48” (Figure 4). This system consists of a trough, which allowed them to weigh the feed and a gate to avoid the entrance of more than one pig into the trough at the same time. Feed is weighed before and after each feeder visit and if the amount of feed after the visit of a pig is below 400 g, the hopper is refilled up to 1200 g. Hyun et al. [16] used recording equipment (F.I.R.E., Hunday Electronics, Newcastle-upon-Tyne, UK) consisting of a trough connected to a load cell equipped with a full-length protective crate to prevent the entrance of more than one pig at any time. Hyun and Ellis [34,36] used a similar feed intake recording system with a crate in front of the trough (Osborne Industries, Osborne, KS). On the other hand, Brown-Brandl et al. [25] developed a system to record the TD per pig in a commercial trough by a radio frequency identification system in growing-finishing pigs (Figure 5). It is known that the type of automatic feeding system used influences FBH of growing-finishing pigs [6,48]. Therefore, due to the existence or not of lateral barriers to protect the head and neck while the pig is eating, or due to the presence or not of a gate to prevent the access of more than one pig to the feeder, the FBHs differ. In fact, the model of the meta-analysis of Averós et al. [21] predicted that the use of protection barriers within individual feeders increased the TD and reduced the TV, FR, and FCR compared to when using feeders without protection barriers. Moreover, Bruininx et al. [50], comparing weaning pigs allotted in the IVOG feeding station versus pigs allotted in commercial single-space dry feeders for 34 days, obtained higher ADFI during the first 13 days for the pigs reared in the IVOG system, but during the remaining 21 days and overall, the ADG and the FCR did not differ between systems. In growing-finishing pigs, a higher ADFI and poorer FCR were obtained in pigs allotted in IVOG stations compared to conventional feeders [47], whereas similar ADG but lower ADFI and FCR were reported in growing- [34] and finishing pigs [36] fed by electronic feeders compared to those pigs fed by conventional feeders. The reasons for the lower ADFI or improved FCR in pigs fed by electronic feeders compared to conventional feeders may be a consequence of the lower feed waste due to the design of the feeder or because only one pig can access the trough of the automatic feeding systems at any one time, reducing the competency in the feeder if it is compared to conventional feeders. 4.3. Feed Form and Feed Distribution Growing-finishing pigs can be fed with different feed forms (mash or pelleted feed), with different water level availability in the feeder (dry feeders or wet–dry feeders) and by different feed distribution systems (ad libitum or restricted). Therefore, in this subsection, a review of the available scientific data regarding the effect of those factors on FBHs and performance of growing-finishing pigs is presented (Table 4). MacDonald and Gonyou [51] reported that growing-pigs (35–45 kg BW pigs) and finishing-pigs (90–100 kg BW) spent more time eating when feed was in dry mash than in dry pellet form. On average, pelleted fed pigs spent 11.5% less time eating than mash fed pigs. Those results are in agreement with Li et al. [52], who reported a 23.5% and a 37.1% reduction in the TD in growing and finishing pigs, respectively, with pigs fed with pellets compared to pigs fed with mash; furthermore, the pigs fed with pelleted feed had a higher FR and a lower feeder occupancy rate. These results are in concordance with Laitat et al. [53], who observed that weaned pigs needed more time to achieve the same ADFI when feeding a mash diet than a pelleted diet due to lower FR. MacDonald and Gonyou [51] and Li et al. [52] analysed the combined effect of feed form (mash vs. pellet) and water availability (dry vs. wet–dry feeders) in growing-finishing pigs. In both growing (20 to 60 kg BW) and finishing (60 to 100 kg BW) pigs, Li et al. [52] observed an interactive effect of feed form and water availability with the dry-mash fed pigs spending a longer time eating due to their lower FR than any other treatment. These results are consistent with the previous findings of MacDonald and Gonyou [51]. In addition, Gonyou and Lou [20] also observed that growing-finishing pigs fed ad libitum by wet-dry feeders spent 17% less time eating than pigs fed by dry feeders, suggesting that growing-finishing pigs prefer wet–dry to dry feeders [40]; furthermore, pigs fed by wet–dry feeders had higher ADFI and ADG and pigs were less lean. In the study of Li et al. [52], the effect of feed form and water availability on performance was analysed in growing and in finishing pigs. In both phases, water availability did not influence FCR, the most efficient pigs being those fed a pelleted diet. Additionally, FBHs of growing-finishing pigs differed when the same feed was offered: dry or dry feed diluted with water (88.6 vs. 27.8% dry matter, dry and dry-feed diluted, respectively) twice per day; growing-finishing pigs fed with dry feed diluted with water spent around 50% less time than pigs fed with dry feed with no differences in terms of performance [54]. On the other hand, the meta-analysis of Averós et al. [21] reported that pigs fed restrictively ate in longer feeder visits and were more active, perhaps because the pigs visited the feeder to check whether there was feed available, than pigs fed ad libitum. On extensive farms, in which pigs have access to restricted feed together with ad libitum access to fodder and grass, the feeding behaviour of pigs depends on a large number of factors such as the dietary supplementation, grazing management, and grass quality, among others [55]. 4.4. Diet Composition Several studies have evaluated the effect of diet composition on the FBHs of growing-finishing pigs. The main factor that modifies the ADFI of a pig is the energy content of the diet; a pig fed with a low energy diet eats more feed per day compared to a pig fed with a high energy diet in order to achieve the required daily energy [40]. In fact, the dilution of the energy concentration of the diet can be carried out by increasing the dietary fibre level, which may be used as a strategy to reduce stereotypic behaviour and to enhance welfare by its satiety effect after a meal by reducing feed motivation [56,57]. In fact, pigs fed with a low nutrient density spent longer eating per day and per feeder visit compared to pigs fed with a higher nutrient density diet [23]. In addition, Quemeneur et al. [58] concluded that the inclusion of fibre (a mix of wheat, soy, and sugar beet pulp fibres) decreased meal frequency, increased MS, whereas the supplementation of aleurone decreased the TM with no effect on MS. On the other hand, lysine content in the diet reduced the number and increased the length and size of feeder visits [16]. Carcò et al. [59] observed that pigs increased ADFI and tended to increase the FR with reduced amino acid content in the diet to achieve nutritional requirements. Furthermore, the flavour and the palatability of feed may stimulate the appetite of pigs. In fact, the inclusion of flavouring additives such as dextrose increases the ADFI of pigs, although there are discrepancies about this fact in the literature [7]. On the other hand, Iberian finishing pigs under extensive conditions depending on natural resources without compound feed remain active, foraging acorns and grass an average of 369 min per day, which is approximately 60% of winter daylight hours; this kind of slow eating would be very dependent on the natural diet [60]. 4.5. Environmental Conditions The effect of high temperature on ADFI, pig activity, and performance has been widely studied [13,21,61,62]. The meta-analysis of Renaudeau et al. [63] shows that the reduction in ADFI and ADG under high temperature is higher in heavier than in lighter growing-finishing pigs (Figure 6). However, few studies have evaluated the effect of environmental conditions on the FBHs of growing-finishing pigs (Table 5). In growing pigs (from 21 to 30 kg BW), Collin et al. [14] reported a reduction of 30% in ADFI, 32% in MS, and 27% in TD with a negative impact on BW gain (−37%) after thirteen consecutive days at 33 °C compared to the control group reared at 23 °C. In heavier pigs (62 kg BW), a decrease of 24% in ADFI, 21% in TV, and 28% in TD were observed when the temperature was increased from 19 to 29 °C for three or four consecutive days at 19, 22, 25, 27, or 29 °C [13]. In fact, Cross et al. [22] observed a reduction of approximately four minutes in TD when growing-finishing pigs were under heat stress conditions. The reduction in ADFI under heat stress is probably a strategy to reduce body heat production [64], which comes from maintenance, physical activity, and feed intake [61]. Moreover, the feed intake schedule changes under different environmental conditions. Under hot conditions, pigs reduce their physical activity [61] and spend more time lying and less time eating [65]. Cross et al. [22] observed that under thermoneutral conditions, most feeder activities were carried out from 6:00 to 17:59 h, while when pigs were suffering heat stress, a peak feeding activity occurred between 6:00 and 08:59 h, a reduction during midday, and another peak of feeder activity between 18:00 and 20:59 h in all breeds and genders studied. The reviewed scientific data regarding the effect of external factors on the FBHs of growing-finishing pigs highlights the importance of the knowledge of each of the factors explored as all of them impact on the FBHs. In intensive conditions, pigs are allotted in groups in pens that can differ in terms of size, number, and type of feeders or stocking density, among others. The reviewed data indicate that growing-finishing pigs are able to adapt their FBHs to achieve the desired ADFI to maintain growth. Therefore, depending on housing conditions, pigs change their FBHs. On the other hand, feed form and feed distribution influence the FBHs; pigs fed in dry mash spend more time eating than pigs fed in dry pelleted feed due to lower FR, whereas when water is available in the feeder, their ADFI and FR increase, but with no influence on FCR. These results indicate that the feeder occupancy rates are higher when pigs are fed in mash, suggesting that the stocking density recommended could depend on the feed form offered. Continuing with parameters related with diet, its composition is of high importance. It is widely known that ADFI depends mainly on diet energy density, with a higher ADFI in pigs fed with low-density diets than pigs fed with high-density diets. However, the type of fibre used or the amino acid content can also modify the FBHs of growing-finishing pigs. Finally, the magnitude of the impact of environmental conditions on ADFI was higher in older than in younger pigs, also distinctly affecting the FBHs depending on the age. 5. Feeding Behaviour Typologies In this section, the correlations between the FBH parameters of growing-finishing pigs reported in the available scientific data are presented [4,11,12,16,24,26,49] (Table 6). De Haer and Merks [12] and Labroue et al. [27] distinguished two types of pigs by their number and size of meals: “nibbler” pigs (many short meals every day) and “meal eater” pigs (a few long meals every day). In fact, strong and negative correlations between MS and TV have been reported, indicating the existence of pigs eating many short meals and pigs eating a few large meals [11,12,16,24,26,49]. Moreover, Fernández et al. [26] also found a strong and positive correlation between VS and the duration of the feeder visits in all of the breeds studied (Duroc, Landrace, Large White, Pietrain r ≥ 0.87; p < 0.05), suggesting no differences in terms of FR between nibbler and meal eater pigs. Moreover, the authors also classified pigs by their rhythm of ingesta, distinguishing “fast eaters” and “slow eaters”. This classification is supported by the strong and negative correlation reported by the available scientific data between FR and TD, indicating that pigs with a higher FR spend less time eating [4,11,12,16,24,26,49] whereas low correlations have been reported between TV and MS with TD and FR [4,11,12,16,24,26,49]. Therefore, the correlations of the reviewed scientific data suggest and support the four feeding behaviour typologies suggested by Fernández et al. [26] in growing-finishing pigs based on the number and size of the daily feeder visits (nibbler and meal eater pigs) and on the rhythm of ingesta (fast and slow eater pigs): nibbler-fast eater, nibbler-slow eater, meal-fast eater, and meal-slow eater pig. 6. The Relation between Feeding Behaviour Habits and Growth Performance In this section, the correlations between the FBH parameters and performance results of growing-finishing pigs are presented [4,5,10,11,12,16,24,26,49] (Table 7 and Table 8). Broadly, the correlations reported between the FBHs and growth performance are moderate with a maximum of 0.59 observed between TD and ADFI. It is well-known that ADFI is directly related with energy and nutrient intake [7] whereas the size and frequency of meals affect the digestibility of nutrients [2,9]. It follows that the use of feed energy and nutrients depends on different metabolic mechanisms, which may be modified by FBHs such as meal frequency [9,66]. In humans, Schwarz et al. [67] and Toschke et al. [68] showed that, besides calorie intake, TM and MS are additional factors that affect BW and body composition whereas in pigs, MS and FR are the two FBHs most strongly and positively related with ADFI, ADG, and BW; however, the former have little effect on FCR [4,5,10,11,12,16,24,26,49]. Labroue et al.’s [27] results suggested that breeding to increase appetite would lead to fast meal eater pigs instead of nibbler pigs and concluded that MS and FR are the two FBH parameters most related with performance and are correlated with ADG. In agreement with these results, Carcò et al. [5] found that FR was the most highly correlated FBH with ADFI, final BW, and ADG; however, it was not correlated with gain to feed ratio and they suggested that the manipulation of FR would affect feed intake and as a consequence, growth performance. Likewise, Andretta et al. [15] found a negative correlation between MS and FR with gain to feed ratio, suggesting that MS and FR negatively influence nutrient utilisation, probably as a consequence of its effects on the passage rate or digestive enzyme activity [8,10]. However, only four studies have been found regarding the influence of MS and FR on feed efficiency and all have reported low correlations [5,11,16,49]. The only FBH parameter with significant influence on FCR was the TD with a positive correlation [5,11,16,49], which suggests that pigs spending a shorter time eating have better FCR. Nevertheless, these results are in contrast to pigs grazing on natural resources because most of the energy intake (54.1%) is to cover maintenance requirements [60]. In summary, the correlations reported by the reviewed authors suggest that increases in FR are associated with higher ADFI, higher growth rates, and less TD; in addition, increases in MS are associated with higher ADFI and higher growth rates. However, these increases in FR and MS did not show any influence on feed efficiency. Controversial correlations have been reported between TV and performance [4,5,10,11,12,16,24,26,49]. In fact, de Haer and Merks [12] reported a positive correlation of TV with ADFI and ADG whereas Labroue et al. [11], Hyun et al. [16], Rauw et al. [4], and Fernández et al. [26] reported negative correlations, with neither of the cited studies showing an influence on FCR. Moreover, Schulze et al. [69] concluded that TV is independent from growth performance in boars. However, various authors have evaluated the effect of feeding frequency (feeding pigs at certain intervals of time during the day) on the performance of growing-finishing pigs with contradictory results. In the 70s, Allee et al. [70] reported that 22 kg BW pigs fed ad libitum were less efficient than pigs fed a single daily meal (2 h/24 h). A later study with heavier pigs (from 25–35 to 100 kg BW) also concluded that the more efficient pigs individually housed had fewer meals per day and shorter TD with higher MS [10]. In addition, Le Naou et al. [66] observed that 30 kg BW pigs allotted in individual cages and fed with the same amount of feed twice per day improved their ADG by 6.4% and their FCR by 4% compared to pigs fed 12 times per day, results which are in agreement with Liu et al. [71]. These results could be explained because pigs with fewer meals per day may reduce their maintenance requirements [72]. The energy requirements of pigs are divided into two fractions: energy needed for production and energy needed for maintenance. Energy for maintenance is defined as “the level of feeding at which the requirements for energy are just met to ensure the continuity of vital processes so that there is no net gain or loss of energy and nutrients in tissue or animal products” [73]. However, energy requirements for maintenance change depend on the physical activity of the pig. In fact, compared to resting, when a sow is standing, she almost doubles her body heat production [74] and McDonald et al. [75] reported that body heat production rate increases by 95% above the resting level when a 40 kg BW pig is standing. Van Milgen et al. [73] observed that body heat production due to activity represented between eight and 13% of the metabolizable energy intake in growing pigs. Therefore, it could be hypothesised that more meals per day would increase the energy requirements for maintenance and therefore penalize performance. In addition, pigs fed once or twice are generally less sensitive to the excitement associated with the distribution of feed than animals receiving multiple small meals, wasting less energy [76]. However, Schneider et al. [77], studying the effect of restricted feeding frequency from six to two meals per day with a similar amount of feed provided in both treatments (68 and 114 kg BW pigs allotted in pens of 10 pigs) observed a positive effect of the number of meals, with an increase in ADG and an improvement in FCR. Similarly, Colpoys et al. [78] obtained lower ADG and ADFI in growing gilts fed twice per day than fed ad libitum with no effect on FCR. These results are partially in agreement with those reported by Jia et al. [2], who concluded that feeding the same daily amount of feed once, twice, or five times a day modified digestion processes and performance. In fact, ADG, together with the apparent total tract digestibility of protein and fat, improved with five feeding times per day compared to feeding only once per day, however, those pigs obtained poorer FCR. Therefore, the reviewed studies indicate that, in restricted fed pigs, the frequency of feeding modifies performance. Thus, it could be hypothesised that a change in feeding frequency for pigs under a restricted feeding regime could modify MS and FR. Furthermore, in pigs fed ad libitum, this hypothesis could explain the low, contradictory correlations reported between TV and performance results, while MS and FR have been strongly correlated with ADFI and ADG but not with FCR [4,5,10,11,12,16,24,26,49]. In summary, most of the papers reviewed showed a positive influence of TD, MS, and FR on ADFI, whereas only MS and FR were mostly positively related with ADG; the influence of TV on ADFI and ADG was not clear, together with low and contradictory correlations between the FBHs and FCR. 7. The Relation between Feeding Behaviour Habits and Carcass Quality Traits Despite the big economic interest in achieving specific carcass quality traits, few studies have evaluated the influence of FBHs on carcass quality traits (Table 9). The three found studies reported strong and positive correlations between ADFI, MS, and FR with backfat thickness whereas one of the two found studies showed strong and negative influences between ADFI, MS, and FR with lean percentage [5,10,11]. These results suggest that pigs eating large and faster meals may be fatter than pigs eating small and slower meals. In the same direction, Rauw et al. [4], studying growing-finishing pigs (Duroc barrows) allotted in group and fed ad libitum, observed that the pigs that ate faster, ate more, and spent less time eating and had higher fat deposition values. Similarly, Kavlak and Uimari [79] reported positive correlations between FR and backfat thickness and Stote et al. [80] and Toschke et al. [68] concluded that large energy intake meals led to higher adipose tissue deposition than eating smaller meals in humans. In addition, Carcò et al. [5] observed a high influence of FR on carcass quality traits in grouped housed pigs. In fact, it was observed that pigs eating faster had higher carcass weight, higher proportion of fat in the carcass, and lower proportions of carcass lean cuts than pigs eating slower (12.6 vs. 38.2 g/min). However, Colpoys et al. [78] did not find any correlation between FR, ADFI, ADG, protein or fat deposition, and lean estimated by X-ray tomography; their study was conducted with a small number of gilts fed ad libitum or twice a day. On the other hand, low correlations have been reported between TV and TD with carcass quality traits [5,10,11]. In terms of feed efficiency, the literature indicates that pigs eating more and faster grow faster and are fatter, but with no effect on feed efficiency [4,5,10]. In summary, despite finding only a few studies, the results regarding the correlation between FBHs and carcass quality suggest that pigs that eat more, with higher MS, and eat faster, may have thicker backfat thickness and lower lean percentage values. 8. Conclusions First, since several definitions of a meal can be found in the literature, it is recommended to standardise the criteria or use the parameter feeder visit instead of the meal concept. Second, it was confirmed that the feeding behaviour of growing-finishing pigs is influenced by internal and external factors. Therefore, when analysing the feeding behaviour of growing-finishing pigs, it is important to clarify which interval of time or interval of weights, sex, breed, group size and feeder space allowance, feeder design, feed form, diet composition, and environmental conditions are used in each experiment. Third, different types of pigs according to their feeding behaviour habits were identified according to the combination of the number and size of their meals (nibbler/meal eaters) with their feeding rate (slow/fast pigs). It is important to highlight that these types of pigs may exist in the same pen; therefore, there is individual variability influenced by housing conditions, individual temperament, and hierarchy within the pen. Therefore, it would be of interest to know the feeding behaviour habits of pigs with the same ADFI; this would help to evaluate the influence of the number of feeder visits, meal size, and feeding rate on feed efficiency and body composition because reducing the feeding behaviour to only the ADFI is very simplistic and does not consider those other factors. Regarding the literature reviewed, the only feeding behaviour habit found to influence feed efficiency was the time spent eating, suggesting that pigs spending less time eating have better FCR. This result could be explained by the fewer energy maintenance requirements needed. However, pigs eating faster spent less time eating, but feeding rate was not correlated with FCR. Moreover, pigs eating faster with bigger meals had higher ADFI and higher final BW, but with no differences in FCR than pigs eating slower, less, and with smaller meals; moreover, the few scientific data regarding the influence of feeding behaviour habits on carcass quality traits indicate that the former were fatter and less lean than the latter. In conclusion, the available scientific data provide evidence that meal size and feeding rate are the two feeding behaviour habits most correlated with performance, being positively correlated with ADFI, ADG, final BW, and backfat thickness, but with no effect on feed efficiency. Therefore, more research into pigs eating the same ADFI with different feeding behaviour habits is needed to better understand the relationship between feeding behaviour habits, feed efficiency, and carcass quality traits. It is expected that the use of feeding stations and sensors in smart farming may fill the current gaps of knowledge regarding feeding behaviour and related factors; besides, other feeding behaviour parameters aside from ADFI could be considered in genetic selection programmes. Acknowledgments This work is part of a research project funded by the Spanish Ministry of Science and Innovation (Project IDI-20170552) and was also supported by a research fellowship to Marta Fornos from the National Sub-Programme for Training of Programme for the Promotion of Talent and its Employability in R&D&i of the Ministry of Science and Innovation (DI-16-08489). Author Contributions Conceptualisation, M.F., V.R.-E. and S.S.-F.; Methodology, M.F., V.R.-E. and S.S.-F.; Software, M.F. and S.S.-F.; Validation, M.F., S.S.-F. and V.R.-E.; Formal analysis, M.F.; Investigation, M.F., V.R.-E. and S.S.-F.; Resources, V.R.-E., S.S.-F., E.J.-M. and D.C.; Data curation, M.F. and V.R.-E.; Writing—original draft presentation, M.F.; Writing -review and editing, J.G., E.J.-M., D.C., S.S.-F. and V.R.-E.; Visualisation, M.F.; Supervision J.G., E.J.-M., D.C., S.S.-F. and V.R.-E.; Project administration, E.J.-M., D.C., J.G. and V.R.-E. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Data Availability Statement No new data were created or analyzed in this study. Data sharing is not applicable to this article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Interrelations of the feeding behaviour habits (FBHs). Average daily feed intake (ADFI), number of feeder visits per pig and day (TV), number of meals per pig and day (TM), total minutes spent eating per pig and day (TD), feed consumed per feeder visit (VS), feed consumed per meal (MS), and feed intake per minute spent eating (FR). Figure 6 The effects of ambient temperature and pig BW on (a) ADFI and (b) ADG (Renaudeau et al. [63]). animals-12-01128-t001_Table 1 Table 1 Individual feeding behaviour parameters and the criteria used to compute them. Parameter Nomenclature Criterion Average daily feed intake (kg/d) ADFI Total feed consumed per pig and day Feeder visits per day (n/d) TV Number of feeder visits per pig and day Meals per day (n/d) TM Number of meals per pig and day Time spent eating (min/d) TD Total minutes spent eating per pig and day Visit size (g/feeder visit) VS Feed consumed per feeder visit Meal size (g/meal) MS Feed consumed per meal Feeding rate (g/min) FR Feed intake per minute spent eating Average daily feed intake (ADFI), number of feeder visits per pig and day (TV), number of meals per pig and day (TM), total minutes spent eating per pig and day (TD), feed consumed per feeder visit (VS), feed consumed per meal (MS), and feed intake per minute spent eating (FR). animals-12-01128-t002_Table 2 Table 2 Effect of age on the feeding behaviour habits of growing-finishing pigs. Reference Initial and Final BW, kg ADFI (kg of Feed/d) 1 TV (Feeder Visits/d) 2 TM (Meals/Day) 3 TD (Minutes Spent Eating/d) 4 VS (Feed Consumed/ Feeder Visit) 5 MS (Feed Consumed/Meal) 6 FR (Feed Consumed/min) 7 [11] ** 35 to 95–100 kg 1.75 to 2.81 (increased by 60%) From 40 to 60 kg: from 14 to 18 (increased by 28%) From 60 to 90 kg: from 18 to 16 (reduced by 11%) From 63.7 to 49.6 (reduced by 22%) From 278 to 621 (increased by 123%) From 28.6 to 58.8 (increased by 106%) [16] 27 to 82 kg 1.55 to 1.9 kg/d (increased by 23%) From 7.25 to 6 (reduced by 17%) From 109 to 60 (reduced by 45%) From 220 to 320 (increased by 45%) From 15 to 35 (increased by 133%) [20] 40 vs. 80 kg - 40 kg BW: 55.6 80 kg BW: 42.2 (reduced by 24%) 40 kg BW: 102 80 kg BW: 85.6 (reduced by 16%) - - 40 kg BW: 35.6 80 kg BW: 43.5 (increased by 22%) [15] 30 to 100 kg 2.13 to 3.4 (increase by 60%) From 11 to 11.3 (increased by 3%) From 68.3 to 65.1 (reduced by 5%) From 194 to 301 (increased by 55%) From 31.4 to 50.2 (increased by 60%) [5] 47 to 145 kg Increased Small variations Reduced Increased Increased 1 ADFI (average daily feed intake). 2 TV (number of feeder visits per pig and day). 3 TM (number of meals per pig and day according to each paper methodology; where a meal is the successive feeder visits within two minutes [11]; the successive visits within 28.3 min intervals [16]; and the successive feeder visits within one minute [15]. Gonyou and Lou, [20] reported the number of entrances into the feeder. 4 TD (total minutes spent eating per pig and day). 5 VS (feed consumed per feeder visit). 6 MS (feed consumed per meal). 7 FR (feed intake per minute spent eating). ** Predicted values from a model. animals-12-01128-t004_Table 4 Table 4 The effect of feed form on the feeding behaviour habits of growing-finishing pigs. Reference Breed 1 Phase and Kg BW Floor Space Allowance (m2/pig) Feed Form and Distribution 2 TD (Minutes Spent Eating/d) 3 FR (Feed Consumed/min) 4 Pellet Mash Pellet Mash [51] No data 25–35 kg BW 95, 110, and 125% feeder capacity Mash vs. Pellet Dry vs. Wet–dry feeder Ad libitum Dry: 68.9 b Wet–dry: 65.5 b Dry: 78.6 a Wet–dry: 69.7 b - 90–100 kg BW 80, 102.5, and 125% feeder capacity [53] P × (LW × L) 8 to 26 kg BW 0.67, 0.5, and 0.4 Mash vs. Pellet Ad libitum 112.8 b 175.2 a 6 4 [54] ** D × (Y × L) 20 to 115 kg BW 0.8 Dry feed vs. dry feed diluted with water Twice per day Dry: 8.6 ± 2.7 min - - - Liquid: 3.6 ± 1.3 min [52] No data (PIC) 20 to 60 kg BW 0.54 Mash-Pellet Dry vs. Wet–dry feeder Ad libitum Dry: 81.8 b Wet–dry: 79.3 b Dry: 106.9 a Wet–dry: 71.6 b Dry: 25.9 b Wet–dry:27.2 b Dry: 19.7 c Wet–dry: 33.4 a 60 to 100 kg BW 0.76 Dry: 67.0 b Wet–dry: 65.1 b Dry: 106.5 a Wet–dry: 66.6 b Dry: 39.5 a Wet–dry: 43.4 a Dry: 25.6 b Wet–dry: 46.7 a 1 Duroc (D), landrace (L), Large White (LW), Pietrain (P), Yorskshire (Y). 2 Dry or wet–dry feeder refers to different water level availability in the feeder [51,52], whereas in the study of Zoric et al. [54], pigs were fed twice per day with dry feed or with dry feed diluted with water (88.6 vs. 27.8% dry matter, dry and dry-feed diluted, respectively). 3 TD (total minutes spent eating per pig and day). 4 FR (feed intake per minute spent eating). a,b Values with different superscripts differ (p < 0.1). ** Mean effective time per feeding (i.e., when the first pig left the trough). animals-12-01128-t005_Table 5 Table 5 The effect of environmental conditions on the feeding behaviour habits of growing-finishing pigs. Reference Environmental Challenge BW (kg) Breed 1 Density (m2/pig) Floor Type I/GH 2 ADFI (kg of Feed/d) 3 TV (Feeder Visits/d) or TM (Meals/d) 4 TD (Minutes Spent Eating/d) 5 MS (Feed Consumed/Meal) 6 FR (Feed Consumed/min) 7 [13] From 19 °C to 29 °C (three–four consecutive days at 19, 22, 25, 27 or 29 °C) 62 kg P × LW 1.2 (3 pigs/pen) Metal slatted GH Reduced by 24% * Reduced by 21% ** Reduced by 28% *** Reduced by 17% = [14] 13 days at 33 °C vs. at 23 °C From 21 kg to 30 kg BW (LW × L) × P 0.73 (5 pigs/pen) Metal slatted GH Reduced by 30% ** Reduced by 30% Reduced by 27% ** Reduced by 32% * = [22] Ambient temperatures from May 2014 to April 2016 Four groups (n = 240) 4-month grow-out period D, L and Y 0.80 (40 pigs/pen) - GH - Reduced in L pigs 4 min/d less at emergency THI level - - 1 Duroc (D), Landrace (L), Large White (LW), Pietrain (P), Yorkshire (Y). 2 Individual (I) or Group Housing (GH). 3 ADFI (average daily feed intake). 4 Quiniou et al. [13] and Collin et al. [14] analysed the number of meals per pig and day; according to their paper methodology; where a meal is: the successive feeder visits by the same pig within two minutes. Cross et al. [22] reported the number of feeder visits per pig and day (TV). 5 TD (total minutes spent eating per pig and day). 6 MS (feed consumed per meal: according to each paper’s methodology). 7 FR (feed intake per minute spent eating). * p < 0.05, ** p < 0.01, *** p < 0.001. animals-12-01128-t006_Table 6 Table 6 Correlation results between feeding behaviour habits obtained in different studies. TV (Feeder Visits/d) 1 or TM (Feeder Visits/d or Meals/d) 2 TD (Minutes Spent Eating/d) 3 VS (Feed Consumed/Visit) 4 or MS (Feed Consumed/Meal) 5 References 6 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 TD (minutes spent eating/d) 3 0.50 −0.02 0.25 0.17 −0.06 −0.29 to 0.14 0.48 VS (feed consumed/visit) 4 or MS (feed consumed /meal) 5 −0.76 −0.43 *** −0.78 *** −0.84 * - −0.84 * to −0.77 * −0.84 −0.16 −0.01 −0.04 0.01 - −0.05 to 0.30 * −0.35 FR (feed consumed/min) 7 −0.20 −0.09 0.08 −0.26 * −0.1 −0.24 to 0.30 −0.31 −0.66 −0.76 *** −0.59 *** −0.79 * −0.31 *** −0.78 * to −0.67 * −0.83 0.25 0.27 *** 0.14 0.34 * - −0.08 to 0.23 0.42 1 TV (number of feeder visits per pig and day). 2 TM (number of meals per pig and day according to each paper methodology; where a meal is: the successive feeder visits within five minutes [12]; the successive feeder visits within two minutes [11]; and the successive visits within 28.3 min intervals [16]. Young and Lawrence [24], Rauw et al. [4], Fernández et al. [26], and Garrido-Izard et al. [49] analysed the daily number of feeder visits. 3 TD (total minutes spent eating per pig and day). 4 VS (feed consumed per feeder visit). 5 MS (feed consumed per meal). 6 References: (1) [12] (Dutch Landrace, 25–35 to 100 kg BW, boars and gilts); (2) [11] (Large White and French Landrace, from 35 to 95–100 kg BW, boars and castrated males); (3) [24] (Large White × Landrace, initial weight of 32 kg BW, males and females); (4) [16] (PIC Line 26 males × Camborough females, from 27 to 82 kg BW, boars, barrows and gilts); (5) [4] (Duroc, from 38 to 130 kg BW, barrows); (6) [26] (Pietrain); and (7) [49] (Landrace, 35–50 to 107–165 kg BW, males). 7 FR (feed intake per minute spent eating). *, *** stand for p < 0.05, and p < 0.001. animals-12-01128-t007_Table 7 Table 7 Correlation results between feeding behaviour habits and average daily feed intake (ADFI). ADFI (kg of Feed/d) 1 References 2 1 2 3 4 5 6 7 8 9 TV (feeder visits/d) 3 or TM (meals/d) 4 0.48 −0.06 −0.16 ** 0.07 −0.28 * −0.19 ** −0.11 to 0.01 −0.003 0.20 TD (minutes spent eating/d) 5 0.59 0.55 ** 0.26 *** 0.51 *** 0.25 * 0.28 *** −0.02 to 0.39 * −0.14 0.28 VS (feed consumed/visit) 6 or MS (feed consumed/meal) 7 0.03 0.02 0.42 *** 0.40 ** 0.70 * - 0.28 * to 0.43 * 0.20 * 0.21 FR (feed consumed/min) 8 0.17 0.21 ** 0.37 *** 0.21 0.31 * 0.26 *** 0.32 * to 0.59 * 0.51 *** 0.27 1 ADFI (average daily feed intake). 2 References: (1) [12] (Dutch Landrace, 25–35 to 100 kg BW, boars and gilts); (2) [10] (Dutch Landrace and Great Yorkshire, 25–35 to 10 kg BW, boars and gilts); (3) [11] (Large White and French Landrace, from 35 to 95–100 kg BW, boars and castrated males); (4) [24] (Large White × Landrace, initial weight of 32 kg BW, males and females); (5) [16] (PIC Line 26 males × Camborough females, from 27 to 82 kg BW, boars, barrows and gilts); (6) [4] (Duroc, from 38 to 130 kg BW, barrows); (7) [26] (Pietrain); (8) [5] (Topigs Talent × PIC, from 86 to 145 kg BW, barrows); and (9) [49] (Landrace, 35–50 to 107–165 kg BW, males). 3 TV (number of feeder visits per pig and day). 4 TM (number of meals per pig and day according to each paper methodology; where a meal is: the successive feeder visits within five minutes [12]; the successive feeder visits within two minutes [11]; and the successive visits within 28.3 min intervals [16]. Young and Lawrence [24], Rauw et al. [4], Fernández et al. [26], and Garrido-Izard et al. [49] analysed the daily number of feeder visits. 5 TD (total minutes spent eating per pig and day). 6 VS (feed consumed per feeder visit). 7 MS (feed consumed per meal). 8 FR (feed intake per minute spent eating). *, **, *** stand for p < 0.05, p < 0.01, and p < 0.001. animals-12-01128-t008_Table 8 Table 8 Correlation results between the feeding behaviour habits and growth parameters obtained in different studies. ADG 1 Final BW FCR 2 References 3 1 2 3 4 5 6 3 6 2 3 a 6 a 7 a TV (feeder visits/d) 4 or TM (meals/d) 5 0.18 ** 0.01 - −0.16 * −0.26 * to −0.09 −0.07 −0.02 −0.11 0.00 0.14 −0.11 0.18 TD (minutes spent eating/d) 6 −0.06 0.17 *** 0.02 0.19 ** 0.12 to 0.39 * −0.25 * −0.01 −0.25 * 0.15 ** −0.24 * −0.22 * 0.33 VS (feed consumed/visit) 7 or MS (feed consumed/meal) 8 0.41 ** 0.19 *** 0.38 * - 0.28 * to 0.54 * 0.25 * 0.2 9* 0.27 ** 0.02 −0.29 * 0.12 −0.08 FR (feed consumed/min) 9 0.50 ** 0.20 *** 0.32 * 0.38 *** 0.10 to 0.43 * 0.54 *** 0.35 * 0.52 *** −0.00 0.06 0.15 −0.16 1 ADG (average daily gain). 2 FCR (feed conversion ratio). 3 References: (1) [10] (Dutch Landrace and Great-Yorkshire, 25–35 to 100 kg BW, boars and gilts); (2) [11] (Large White and French Landrace, from 35 to 95–100 kg BW, boars and castrated males); (3) [16] (PIC Line 26 males × Camborough females, from 27 to 82 kg BW, boars, barrows and gilts); (4) [4] (Duroc, from 38 to 130 kg BW, barrows); (5) [26] (Pietrain); (6) [5] (Topigs Talent × PIC, from 86 to 145 kg BW, barrows); and (7) [49] (Landrace, 35–50 to 107–165 kg BW, males). 4 TV (number of visits per pig and day). 5 TM (number of meals per pig and day according to each paper methodology; where a meal is: the successive feeder visits within five minutes [10]; the successive feeder visits within two minutes [11]; and the successive visits within 28.3 min intervals [16]. Rauw et al. [4], Fernández et al. [26], Carcò et al. [5], and Garrido-Izard et al. [49] analysed the daily number of feeder visits. 6 TD (total minutes spent eating per pig and day). 7 VS (feed consumed per feeder visit). 8 MS (feed consumed per meal). 9 FR (feed intake per minute spent eating). a Gain to feed ratio. *, **, *** stand for p < 0.05, p < 0.01, and p < 0.0001. animals-12-01128-t009_Table 9 Table 9 Correlation results between feeding behaviour habits and carcass quality obtained by different studies. Backfat Thickness (mm) Loin Depth (mm) Lean Percentage (%) References 1 1 2 3 3 1 3 ADFI 2 0.35 ** 0.36 *** 0.59 *** 0.04 −0.39 ** −0.07 TV (feeder visits/d) 3 or TM (meals/d) 4 −0.15 * −0.07 0.06 −0.01 0.06 0.04 TD (minutes spent eating/d) 5 −0.05 0.08 −0.05 −0.01 −0.03 0.06 VS (feed consumed/visit) 6 or MS (feed consumed/meal) 7 0.33 ** 0.16 ** 0.09 0.08 −0.21 ** −0.05 FR (feed consumed/min) 8 0.35 ** 0.13 * 0.27* −0.028 −0.29 ** −0.06 1 References (1) [10] (Dutch Landrace and Great Yorkshire, 25–35 to 100 kg BW, boars and gilts); (2) [11] (Large White and French Landrace, from 35 to 95–100 kg BW, boars and castrated males); and (3) [5] (Topigs Talent × PIC, from 86 to 145 kg BW, barrows). 2 ADFI (average daily feed intake). 3 TV (number of feeder visits per pig and day). 4 TM (number of meals per pig and day according to each paper methodology; where a meal is: the successive feeder visits within five minutes [10]; the successive feeder visits within two minutes [11]. Carcò et al. [5] analysed the daily number of feeder visits. 5 TD (total minutes spent eating per pig and day). 6 VS (feed consumed per feeder visit). 7 MS (feed consumed per meal). 8 FR (feed intake per minute spent eating). *, **, *** stand for p < 0.05, p < 0.01, and p < 0.001. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. InterPIG 2020 Pig Cost of Production in Selected Countries 2020 Available online: https://afly.co/zhc6 (accessed on 29 January 2022) 2. Jia M.L. Zhang H. Xu J. Su Y. Zhu W.Y. Feeding frequency affects the growth performance, nutrient digestion and absorption of growing pigs with the same daily feed intake Livest. Sci. 2021 250 9 10.1016/j.livsci.2021.104558 3. Lee J.J. Choe J. Kang J. Cho J.H. Park S. Perez-Maldonado R. Cho J.Y. Park I.H. Kim H.B. Song M. Dietary protease improves growth rate and protein digestibility of growing-finishing pigs J. Anim. Sci. Technol. 2020 62 313 320 10.5187/jast.2020.62.3.313 32568259 4. Rauw W.M. Soler J. Tibau J. Reixach J. Raya L.G. Feeding time and feeding rate and its relationship with feed intake, feed efficiency, growth rate, and rate of fat deposition in growing Duroc barrows J. Anim. Sci. 2006 84 3404 3409 10.2527/jas.2006-209 17093234 5. Carcò G. Gallo L. Dalla Bona M. Latorre M.A. Fondevila M. Schiavon S. The influence of feeding behaviour on growth performance, carcass and meat characteristics of growing pigs PLoS ONE 2018 13 15 10.1371/journal.pone.0205572 6. Maselyne J. Saeys W. Van Nuffel A. Review: Quantifying animal feeding behaviour with a focus on pigs Physiol. Behav. 2015 138 37 51 10.1016/j.physbeh.2014.09.012 25447478 7. Nyachoti C.M. Zijlstra R.T. de Lange C.F.M. Patience J.F. Voluntary feed intake in growing-finishing pigs: A review of the main determining factors and potential approaches for accurate predictions Can. J. Anim. Sci. 2004 84 549 566 10.4141/A04-001 8. De Haer L.C.M. De Vries A.G. Feed-intake patterns of and feed digestibility in growing pigs housed individually or in groups Livest. Prod. Sci. 1993 33 277 292 10.1016/0301-6226(93)90008-6 9. Chassé E. Guay F. Knudsen K.E.B. Zijlstra R.T. Létourneau-Montminy M.P. Toward Precise Nutrient Value of Feed in Growing Pigs: Effect of Meal Size, Frequency and Dietary Fibre on Nutrient Utilisation Animals 2021 11 2598 10.3390/ani11092598 34573564 10. De Haer L.C.M. Luiting P. Aarts H.L.M. Relations among individual (residual) feed-intake, growth-performance and feed-intake pattern of growing pigs in-group housing Livest. Prod. Sci. 1993 36 233 253 10.1016/0301-6226(93)90056-N 11. Labroue F. Guéblez R. Sellier P. Meunier-Salaün M.C. Feeding-behavior of group-housed Large White and Landrace pigs in French central test stations Livest. Prod. Sci. 1994 40 303 312 10.1016/0301-6226(94)90097-3 12. De Haer L.C.M. Merks J.W.M. Patterns of daily food-intake in growing pigs Anim. Prod. 1992 54 95 104 10.1017/S0003356100020614 13. Quiniou N. Dubois S. Noblet J. Voluntary feed intake and feeding behaviour of group-housed growing pigs are affected by ambient temperature and body weight Livest. Prod. Sci. 2000 63 245 253 10.1016/S0301-6226(99)00135-9 14. Collin A. van Milgen J. Dubois S. Noblet J. Effect of high temperature on feeding behaviour and heat production in group-housed young pigs BJN 2001 86 63 70 10.1079/BJN2001356 15. Andretta I. Pomar C. Kipper M. Hauschild L. Rivest J. Feeding behavior of growing-finishing pigs reared under precision feeding strategies J. Anim. Sci. 2016 94 3042 3050 10.2527/jas.2016-0392 27482691 16. Hyun Y. Ellis M. McKeith F.K. Wilson E.R. Feed intake pattern of group-housed growing-finishing pigs monitored using a computerized feed intake recording system J. Anim. Sci. 1997 75 1443 1451 10.2527/1997.7561443x 9250503 17. Bigelow J.A. Houpt T.R. Feeding and drinking patterns in young pigs Physiol. Behav. 1988 43 99 109 10.1016/0031-9384(88)90104-7 3413258 18. Auffray P. Marcilloux J.C. Analysis of porcine feeding patterns from weaning to adulthood Reprod. Nutr. Dev. 1980 20 1625 1632 10.1051/rnd:19800905 7349498 19. Lærke H.N. Hedemann M.S. The Digestive System of The Pig (Chapter 5) Nutritional Physiology of Pigs—Online Publication Videcenter for Svineproduktion Foulum, Denmark 2012 20. Gonyou H.W. Lou Z. Effects of eating space and availability of water in feeders on productivity and eating behavior of grower/finisher pigs J. Anim. Sci. 2000 78 865 870 10.2527/2000.784865x 10784175 21. Averós X. Brossard L. Dourmad J.Y. de Greef K.H. Edwards S.A. Meunier-Salaün M.C. Meta-analysis on the effects of the physical environment, animal traits, feeder and feed characteristics on the feeding behaviour and performance of growing-finishing pigs Animal 2012 6 1275 1289 10.1017/S1751731112000328 23217231 22. Cross A.J. Brown-Brandl T.M. Keel B.N. Cassady J.P. Rohrer G.A. Feeding behavior of grow-finish swine and the impacts of heat stress Transl. Anim. Sci. 2020 4 986 992 10.1093/tas/txaa023 23. Pichler J. Schwarz C. Gierus M. Schedle K. Choice feeding in fattening pigs: Effect of diets differing in nutrient density on feeding behaviour and fattening performance Czech J. Anim. Sci. 2020 65 247 257 10.17221/111/2020-CJAS 24. Young R.J. Lawrence A.B. Feeding behaviour of pigs in groups monitored by a computerized feeding system Anim. Prod. 1994 58 145 152 10.1017/S0003356100007182 25. Brown-Brandl T.M. Rohrer G.A. Eigenberg R.A. Analysis of feeding behavior of group housed growing-finishing pigs Comput. Electron. Agric. 2013 96 246 252 10.1016/j.compag.2013.06.002 26. Fernández J. Fàbrega E. Soler J. Tibau J. Ruiz J.L. Puigvert X. Manteca X. Feeding strategy in group-housed growing pigs of four different breeds Appl. Anim. Behav. Sci. 2011 134 109 120 10.1016/j.applanim.2011.06.018 27. Labroue F. Guéblez R. Sellier P. Genetic parameters of feeding behaviour and performance traits in group-housed Large White and French Landrace growing pigs Genet. Sel. Evol. 1997 29 451 468 10.1186/1297-9686-29-4-451 28. Baumung R. Lercher G. Willam A. Sölkner J. Feed intake behaviour of different pig breeds during performance testing on station Arch. Tierz. 2006 49 77 88 10.5194/aab-49-77-2006 29. Quiniou N. Dubois S. Le Cozler Y. Bernier J.F. Noblet J. Effect of growth potential (body weight and breed/castration combination) on the feeding behaviour of individually kept growing pigs Livest. Prod. Sci. 1999 61 13 22 10.1016/S0301-6226(99)00048-2 30. The European Commission Commission Recommendation (EU) 2016/336 of 8 March 2016 on the Application of Council Directive 2008/120/EC Laying down Minimum Standards for the Protection of Pigs as Regards Measures to Reduce the Need for Tail-Docking Off. J. Eur. Union 2016. Available online: https://eur-lex.europa.eu/eli/reco/2016/336/oj (accessed on 16 April 2019) 31. Cornale P. Macchi E. Miretti S. Renna M. Lussiana C. Perona G. Mimosi A. Effects of stocking density and environmental enrichment on behavior and fecal corticosteroid levels of pigs under commercial farm conditions J. Vet. Behav. 2015 10 569 576 10.1016/j.jveb.2015.05.002 32. Schmolke S.A. Li Y.Z. Gonyou H.W. Effect of group size on performance of growing-finishing pigs J. Anim. Sci. 2003 81 874 878 10.2527/2003.814874x 12723074 33. Bornett H.L.I. Morgan C.A. Lawrence A.B. Mann J. The effect of group housing on feeding patterns and social behaviour of previously individually housed growing pigs Appl. Anim. Behav. Sci. 2000 70 127 141 10.1016/S0168-1591(00)00146-5 11080556 34. Hyun Y. Ellis M. Effect of group size and feeder type on growth performance and feeding patterns in growing pigs J. Anim. Sci. 2001 79 803 810 10.2527/2001.794803x 11325183 35. Nielsen B.L. Lawrence A.B. Whittemore C.T. Effect of group-size on feeding behaviour, social behaviour, and performance of growing pigs using single-space feeders Livest. Prod. Sci. 1995 44 73 85 10.1016/0301-6226(95)00060-X 36. Hyun Y. Ellis M. Effect of group size and feeder type on growth performance and feeding patterns in finishing pigs J. Anim. Sci. 2002 80 568 574 10.2527/2002.803568x 11890394 37. Gonyou H.W. Brumm M.C. Swine Nutrition 2nd ed. Lewis A.J. Southern L.L. CRC Press Boca Raton, FL, USA 2001 499 518 38. Nielsen B.L. On the interpretation of feeding behaviour measures and the use of feeding rate as an indicator of social constraint Appl. Anim. Behav. Sci. 1999 63 79 91 10.1016/S0168-1591(99)00003-9 39. PIC Wean to Finish Guidelines. PIC Available online: https://afly.co/zlh6 (accessed on 31 January 2022) 40. Smit M.N. Zhou X. Landero J.L. Young M.G. Beltranena E. Dietary energy level, feeder space, and group size on growth performance and carcass characteristics of growing-finishing barrows and gilts Transl. Anim. Sci. 2021 5 15 10.1093/tas/txab122 34405134 41. Morrison R.S. Hemsworth P.H. Cronin G.M. Campbell R.G. The social and feeding behaviour of growing pigs in deep-litter, large group housing systems Appl. Anim. Behav. Sci. 2003 82 173 188 10.1016/S0168-1591(03)00067-4 42. Rodríguez-Estévez V. Sánchez-Rodríguez M. Gómez-Castro A.G. Edwards S.A. Group sizes and resting locations of free range pigs when grazing in a natural environment Appl. Anim. Behav. Sci. 2010 127 28 36 10.1016/j.applanim.2010.08.010 43. Rodríguez-Estévez V. García A. Peña F. Gómez A.G. Foraging of Iberian fattening pigs grazing natural pasture in the dehesa Livest. Sci. 2009 120 135 143 10.1016/j.livsci.2008.05.006 44. Walker N. The effects on performance and behavior of number of growing pigs per mono-place feeder Anim. Feed. Sci. Technol. 1991 35 3 13 10.1016/0377-8401(91)90094-9 45. Hoy S. Schamun S. Weirich C. Investigations on feed intake and social behaviour of fattening pigs fed at an electronic feeding station Appl. Anim. Behav. Sci. 2012 139 58 64 10.1016/j.applanim.2012.03.010 46. Maselyne J. Van Nuffel A. De Ketelaere B. Vangeyte J. Hessel E.F. Sonck B. Saeys W. Range measurements of a High Frequency Radio Frequency Identification (HF RFID) system for registering feeding patterns of growing-finishing pigs Comput. Electron. Agric. 2014 108 209 220 10.1016/j.compag.2014.08.006 47. Georgsson L. Svendsen J. One or two feeders for groups of 16 growing-finishing pigs: Effects on health and production Acta Agric. Scand. A. Anim. Sci. 2001 51 257 264 10.1080/09064700152717245 48. Georgsson L. Svendsen J. Degree of competition at feeding differentially affects behavior and performance of group-housed growing-finishing pigs of different relative weights J. Anim. Sci. 2002 80 376 383 10.2527/2002.802376x 11881927 49. Garrido-Izard M. Correa E.C. Requejo J.M. Diezma B. Continuous Monitoring of Pigs in Fattening Using a Multi-Sensor System: Behavior Patterns Animals 2020 10 52 10.3390/ani10010052 31888006 50. Bruininx E. van der Peet-Schwering C.M.C. Schrama J.W. den Hartog L.A. Everts H. Beynen A.C. The IVOG feeding station: A tool for monitoring the individual feed intake of group-housed weanling pigs J. Anim. Physiol. Anim. Nutr. 2001 85 81 87 10.1046/j.1439-0396.2001.00305.x 51. Mac Donald K.A.M. Gonyou H.W. Effect of feed presentation on the feeding behaviour of grower/finisher pigs. Annual Research Report Prairie Swine Centre Inc. Saskatoon, SK, Canada 2000 25 26 52. Li Y.Z.Z. McDonald K.A. Gonyou H.W. Determining feeder space allowance across feed forms and water availability in the feeder for growing-finishing pigs J. Swine Health Prod. 2017 25 174 182 53. Laitat M. Vandenheede M. Désiron A. Canart B. Nicks B. Influence of diet form (pellets or meal) on the optimal number of weaned pigs per feeding space J. Swine Health Prod. 2004 12 288 295 54. Zoric M. Johansson S.E. Wallgren P. Behaviour of fattening pigs fed with liquid feed and dry feed Porc. Health Manag. 2015 1 8 10.1186/s40813-015-0009-7 55. Rivero M.J. Rodríguez-Estévez V. Pietrosemoli S. Carballo C. Cooke A.S. Kongsted A.G. Forage Consumption and Its Effects on the Performance of Growing Swine-Discussed in Relation to European Wild Boar (Sus scrofa L.) in Semi-Extensive Systems: A Review Animals 2019 9 457 10.3390/ani9070457 56. de Leeuw J.A. Bolhuis J.E. Bosch G. Gerrits W.J.J. Effects of dietary fibre on behaviour and satiety in pigs Proc. Nutr. Soc. 2008 67 334 342 10.1017/S002966510800863X 18715518 57. Kallabis K.E. Kaufmann O. Effect of a high-fibre diet on the feeding behaviour of fattening pigs Archiv. Tierzucht 2012 55 272 284 10.5194/aab-55-272-2012 58. Quemeneur K. Montagne L. Le Gall M. Lechevestrier Y. Labussiere E. Relation between feeding behaviour and energy metabolism in pigs fed diets enriched in dietary fibre and wheat aleurone Animal 2020 14 508 519 10.1017/S1751731119002246 31609193 59. Carcò G. Dalla Bona M. Carraro L. Latorre M.A. Fondevila M. Gallo L. Schiavon S. Influence of mild feed restriction and mild reduction in dietary amino acid content on feeding behaviour of group-housed growing pigs Appl. Anim. Behav. Sci. 2018 198 27 35 10.1016/j.applanim.2017.09.020 60. Rodríguez-Estévez V. Sánchez-Rodríguez M. García A. Gómez-Castro A.G. Feed conversion rate and estimated energy balance of free grazing Iberian pigs Livest. Sci. 2010 132 152 156 10.1016/j.livsci.2010.05.019 61. Kerr B.J. Yen J.T. Nienaber J.A. Easter R.A. Influences of dietary protein level, amino acid supplementation and environmental temperature on performance, body composition, organ weights and total heat production of growing pigs J. Anim. Sci. 2003 81 1998 2007 10.2527/2003.8181998x 12926782 62. Le Bellego L. van Milgen J. Noblet J. Effects of high ambient temperature on protein and lipid deposition and energy utilization in growing pigs Anim. Sci. 2002 75 85 96 10.1017/S1357729800052863 63. Renaudeau D. Gourdine J.L. St-Pierre N.R. A meta-analysis of the effects of high ambient temperature on growth performance of growing-finishing pigs J. Anim. Sci. 2011 89 2220 2230 10.2527/jas.2010-3329 21297065 64. Cervantes M. Antoine D. Valle J.A. Vásquez N. Camacho R.L. Bernal H. Morales A. Effect of feed intake level on the body temperature of pigs exposed to heat stress conditions J. Therm. Biol. 2018 76 1 7 10.1016/j.jtherbio.2018.06.010 30143283 65. Brown-Brandl T.M. Eigenberg R.A. Nienaber J.A. Kachman S.D. Thermoregulatory profile of a newer genetic line of pigs Livest. Prod. Sci. 2001 71 253 260 10.1016/S0301-6226(01)00184-1 66. Le Naou T. Le Floc'h N. Louveau I. van Milgen J. Gondret F. Meal frequency changes the basal and time-course profiles of plasma nutrient concentrations and affects feed efficiency in young growing pigs J. Anim. Sci. 2014 92 2008 2016 10.2527/jas.2013-7505 24663180 67. Schwarz N.A. Rigby B.R. La Bounty P. Shelmadine B. Bowden R.G. A Review of Weight Control Strategies and Their Effects on the Regulation of Hormonal Balance J. Nutr. Metab. 2011 15 237932 10.1155/2011/237932 21822485 68. Toschke A.M. Küchenhoff H. Koletzko B. von Kries R. Meal frequency and childhood obesity Obesity Research 2005 13 1932 1938 10.1038/oby.2005.238 16339125 69. Schulze V. Roehe R. Bermejo J.L. Looft H. Kalm E. The influence of feeding behaviour on feed intake curve parameters and performance traits of station-tested boars Livest. Prod. Sci. 2003 82 105 116 10.1016/S0301-6226(03)00034-4 70. Alle G.L. Romsos D.R. Leveille G.A. Baker D.H. Metabolic adaptation induced by meal-eating in the pig J. Nutr. 1972 102 1115 1122 10.1093/jn/102.9.1115 71. Liu J.B. Liu Z.Q. Chen L. Zhang H.F. iTRAQ-based proteomic analysis reveals alterations in the liver induced by restricted meal frequency in a pig model Nutrition 2016 32 871 876 10.1016/j.nut.2016.01.020 27106395 72. Sharma V.D. Young L.G. Brown R.G. Buchanan J. Smith G.C. Effects of frequency of feeding on energy metabolism and body composition of young pigs Can. J. Anim. Sci. 1973 53 157 164 10.4141/cjas73-024 73. van Milgen J. Quiniou N. Noblet J. Modelling the relation between energy intake and protein and lipid deposition in growing pigs Anim. Sci. 2000 71 119 130 10.1017/S1357729800054941 74. Noblet J. Shi X.S. Dubois S. Energy cost of standing activity in sows Livest. Prod. Sci. 1993 34 127 136 10.1016/0301-6226(93)90041-F 75. McDonald T.P. Jones D.D. Barrett J.R. Albright J.L. Miles G.E. Nienaber J.A. Hahn G.L. Measuring the heat increment of activity in growing-finishing swine Trans. ASABE 1988 31 1180 1186 10.13031/2013.30841 76. Friend D.W. Cunningham H.M. Effects of feeding frequency on metabolism, rate and efficiency of gain and on carcass quality of pigs J. Nutr. 1964 83 251 256 10.1093/jn/83.3.251 14191425 77. Schneider J.D. Tokach M.D. Goodband R.D. Nelssen J.L. Dritz S.S. DeRouchey J.M. Sulabo R.C. Effects of restricted feed intake on finishing pigs weighing between 68 and 114 kilograms fed twice or 6 times daily J. Anim. Sci. 2011 89 3326 3333 10.2527/jas.2010-3154 21934028 78. Colpoys J.D. Johnson A.K. Gabler N.K. Daily feeding regimen impacts pig growth and behavior Physiol. Behav. 2016 159 27 32 10.1016/j.physbeh.2016.03.003 26957037 79. Kavlak A.T. Uimari P. Estimation of heritability of feeding behaviour traits and their correlation with production traits in Finnish Yorkshire pigs J. Anim. Breed. Genet. 2019 136 484 494 10.1111/jbg.12408 31172608 80. Stote K.S. Baer D.J. Spears K. Paul D.R. Harris G.K. Rumpler W.V. Strycula P. Najjar S.S. Ferrucci L. Ingram D.K. A controlled trial of reduced meal frequency without caloric restriction in healthy, normal-weight, middle-aged adults Am. J. Clin. Nutr. 2007 85 981 988 10.1093/ajcn/85.4.981 17413096

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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092225 cancers-14-02225 Article Screening for Prognostic Biomarkers in Metastatic Adrenocortical Carcinoma by Tissue Micro Arrays Analysis Identifies P53 as an Independent Prognostic Marker of Overall Survival Hescot Segolene 1 Faron Matthieu 2 Kordahi Manal 3 Do Cao Christine 4 Naman Annabelle 5 Lamartina Livia 5 Hadoux Julien 5 Leboulleux Sophie 5 https://orcid.org/0000-0001-8388-3766 Pattou Francois 6 Aubert Sébastien 7 https://orcid.org/0000-0003-1604-6823 Scoazec Jean-Yves 3 Al Ghuzlan Abir 3*† Baudin Eric 5† Stigliano Antonio Academic Editor 1 Department of Nuclear Medicine, Institut Curie, 92210 Saint Cloud, France; segolene.hescot@curie.fr 2 Department of Surgery, Gustave Roussy, 94805 Villejuif, France; matthieu.faron@gustaveroussy.fr 3 Department of Pathology, Gustave Roussy, 94805 Villejuif, France; manal_kordahi@hotmail.com (M.K.); jean-yves.scoazec@gustaveroussy.fr (J.-Y.S.) 4 Department of Endocrinology, Centre Hospitalier Universitaire Lille, 59000 Lille, France; christine.docao@chru-lille.fr 5 Department of Endocrine Oncology, Gustave Roussy, 94805 Villejuif, France; a.naman@live.fr (A.N.); livia.lamartina@gustaveroussy.fr (L.L.); julien.hadoux@gustaveroussy.fr (J.H.); sophie.leboulleux@hcuge.ch (S.L.); eric.baudin@gustaveroussy.fr (E.B.) 6 Department of General and Endocrine Surgery, Centre Hospitalier Universitaire Lille, Université de Lille, 59000 Lille, France; pattou@univ-lille2.fr 7 Institut of Pathology, Centre Hospitalier Universitaire Lille, 59000 Lille, France; sebastien.aubert@chru-lille.fr * Correspondence: abir.alghuzlan@gustaveroussy.fr; Tel.: +33-142-114-211 † These authors contributed equally to this work. 29 4 2022 5 2022 14 9 222516 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary The aim of our retrospective study was to identify and prioritize potential prognostic parameters in a well characterized metastatic ACC population. We identified for the first time P53 as an independent prognostic marker of metastatic adrenocortical carcinoma after mENSAT-GRAS parameter adjustment. This biomarker is easily available and should be considered in clinical practice together with Ki67 for the management of patient with advanced ACC. Moreover, this study underlies the importance of adjustment of potential biomarkers to validated prognostic factors in order to avoid the accumulation of invalidated biomarkers not usable in clinical practice. Abstract Advanced adrenocortical carcinoma (ACC) has poor but heterogeneous prognosis. Apart from Ki67 index, no prognostic or predictive biomarker has been validated in advanced ACC, so far. We aimed at analyzing expression of a large panel of proteins involved in known altered pathways in ACC (cell cycle, Wnt/ß-catenin, methylation) to identify and prioritize potential prognostic or predictive parameters metastatic ACC population. We conducted a retrospective multicentric study. Overall survival (OS) and partial response according to RECIST 1.1 were primary endpoints. TMA was set up and 16 markers were analyzed. Modified ENSAT and GRAS parameters were characterized for prognostic adjustment. Results: We included 66 patients with a mean age at metastatic diagnosis of 48.7 ± 15.5 years. Median survival was 27.8 months. After adjustment to mENSAT-GRAS parameters, p53 and PDxK were prognostic of OS. No potential biomarker has been identified as predictive factor of response. We identified for the first time P53 as an independent prognostic marker of metastatic adrenocortical carcinoma after mENSAT-GRAS parameter adjustment. Prognostic impact of Wnt/ß-catenin alterations was not confirmed in this cohort of metastatic ACC. adrenocortical carcinoma prognostic tissue-micro-array p53 HRA-Pharma and Association SurrénalesThis work was supported by HRA-Pharma and Association Surrénales. ==== Body pmc1. Introduction Adrenocortical carcinoma (ACC) is a rare cancer originating from the adrenal cortex with an incidence of less than 0.7–1.5 per 1 million people per year [1]. Its prognosis is poor: almost 50% of ACC are metastatic at initial diagnosis and when localized, the risk of recurrence is high especially in case of Ki-67 index > 10% [2,3,4,5,6]. The median overall survival (OS) of metastatic ACC patients varies between 10 and 20 months with a 5-year survival around 10% [1]. However, the prognosis is variable and long survivors have been recently described [7,8]. Nowadays, prognostic factors of advanced ACC are clinical and pathological parameters [8]. Recently, the new mENSAT TNM classification combined with GRAS parameters (Grade defined by Weiss score below or above 6 or Ki-67 below or above 20%; R0 resection status; age below or above 50 years; tumor- or hormone-related symptoms) was shown to allow the best risk stratification in term of OS in stage III–IV ACC patients [9]. No prognostic molecular marker has emerged aside from Ki-67 based on mENSAT-GRAS adjustment [10,11,12]. Different behavior of advanced ACC in term of survival suggests a different biology. Several recent-omics studies have highlighted molecular pathways involved in ACC tumorigenesis and attempted to identify a prognostic role of molecular classifications [10,13]. Hypermethylation appears to be associated with increased aggressiveness and a signature of the methylation status of 4 genes (PAX5, PAX6, PYCARD and GSTP1) was shown to correlate to OS independently of ENSAT stage and Ki-67 [14]. Pangenomic studies have identified genetic alterations in 50% of ACC, the most frequent genes involved belonging to cell cycle and Wnt-β-catenin pathways [15,16,17]. Their prognostic impact has been suggested in many studies but neither validated in an independent research laboratory nor validated against the most accurate clinicopathological classifications, namely mENSAT-GRAS. From a methodological standpoint, simple and robust methodology applicable in every specialized center is needed. Immunohistochemistry for protein expression analysis can therefore be considered as a relevant tool. Historically, based on ACC-related inherited syndrome, β-catenin and p53 have been evaluated by β-catenin nuclear staining or aberrant p53 expression using immunochemistry in ACC patients. These alterations were classified as having a prognostic role but not validated as independent prognostic factors with respect to mENSAT-GRAS criteria [18]. During the last decade, many molecular candidates with a potential prognostic impact have emerged, mostly studied one after the other without prioritization, but no single one is currently validated as mentioned in the most recent guidelines [19]. In the same manner, several predictive factors of response to mitotane and platinum-based therapy have been proposed but their validation is still pending [20,21,22,23]. Therefore, we studied expression of a large set of relevant target protein in tissue micro arrays (TMA) issued from a large and well characterized cohort of metastatic ACC patients with the aim to correlate their expression to OS and response to treatment and to prioritize their use in routine practice. 2. Materials and Methods 2.1. Clinical Data Inclusion criteria were histologically proved stage IV ACC with tissue available for TMA analysis. In this case, 66 adult patients followed in two centers (CHU Lille and Gustave Roussy), were selected for the study. An informed consent was obtained from all patients. The medical file of each patient was reviewed by one investigator (SH) to record all clinical parameters at the time of metastasis diagnosis and sample collection, as well as data about treatment outcomes including response to therapy according to RECIST 1.1 criteria [24]. The description and cutoff values of each parameter are given in Table 1. Cutoff values were chosen in order to limit the number of subgroups considering the size of the cohort. In this case, 55 samples originated from primary tumor while 11 were from metastasis when the primary was not available in the same way as previous [10,25]. For 2 patients, matched primary-metastasis samples were available and no difference was found. Chemotherapy was administrated before time of sampling in 4 patients. The study was approved by Gustave Roussy ethical committee. 2.2. Selected Biomarkers Proteins were selected according to literature data, as follows: Proteins involved in main altered pathways in ACC pathogenesis, including:- cell cycle: p16, p53, Rb, ATM, [26]-Wnt-β-catenin: β-catenin, LEF1 pathway [27], - others proteins involved in adrenal steroidogenesis or tumorigenesis: GATA6 [28], SF1 [29], - methylation markers: MGMT [30], PAX6, GSTP1 [14]. Potential predictive factors of response, to platinum-based chemotherapy including: PDxK [31] or, to mitotane including: RMM1 [20], SOAT1 [23], TSPO [21] and FATE1 [22] or to immunotherapy: PDL1. Their physiological role and potential role in ACC are detailed in Table 2. 2.3. Tissue Microarrays Construction Tissue microarrays (TMA) were prepared by the Laboratory of Experimental and Translational Pathology (PETRA), Gustave Roussy Cancer Campus from selected tissue material. All the H&E slides from the 66 cases were examined by two pathologists (AA and MK) for diagnosis confirmation. In each case, one representative slide was selected and marked for two areas with high tumor cellularity. Three punches of 1 mm in diameter from each block were obtained to avoid bias due to tumor heterogeneity, randomly distributed in the recipient block. In this study, four TMA of 27 to 122 samples each were prepared. 2.4. Immunohistochemistry Immunohistochemical techniques were carried out by the Laboratory of Experimental and Translational Pathology (PETRA), Gustave Roussy Cancer Campus. Staining platforms, antibody clones, dilutions and the pattern of the staining are detailed in supplemental Table S1. Expression of each protein was analyzed by qualitative staining (expression or absence of expression) for Rb, LEF1, SF1, GSTP1, PDxK and FATE1, (overexpression, i.e., expression of 100% of cells) for p53 and p16, localization of staining (presence of nuclear staining of 100% of cells) for beta-catenin or quantitative staining (H-score, mean of 3 samples) for ATM, GATA6, MGMT, PAX6, RRM1, SOAT1 and TSPO. These methods were determined depending on protein function and literature results and are detailed in Table 2 ([32]) Cut-off for H-score was homogeneously determined at 150 for each relevant protein considering the repartition of their expressions patterns (similar to medians). Different type of staining patterns for all protein are provided in Figure S1. 2.5. Statistical Analysis Quantitative variables were presented as mean (standard deviation (sd)) and qualitative variables as count (percentage). Overall survival, as primary endpoint, was calculated according to the Kaplan-Meier method from the time of metastatic diagnosis to the date of death from any cause. Univariable analysis used a single variable Cox proportional hazard model. Any protein achieving a p < 0.05 in the univariable model was subsequently tested in a multivariable model with the other significant proteins. A prespecified multivariable model adjusting the significant proteins between them and for the mENSAT-GRAS criteria in order to evaluate the added prognostic value of new putative parameter and to prioritize. Response to therapy were tested by binary logistic regression according to RECIST 1.1 and long term survival. Long term survival was defined as an overall survival longer than 24 months and considered as a binary variable as no patient was censored before 24 months. Association between proteins and long terms survivor was evaluated with a single variable binary logistic model. 3. Results 3.1. Clinicopathological Characteristics The clinical and pathological characteristics of the 66 patients are summarized in Table 1. All patients in our cohort were metastatic, 36.4% with synchronous metastasis and 40.9% had three or more metastatic organs. All patients were characterized according to mENSAT-GRAS criteria including mean age at metastatic disease of 48.70 ± 15.5 years and hormonal secretion present in 38 patients (58.5%). Weiss score was above 6 in 36 (67.9%) cases. Ki67 index was higher than 20% in 21 (32.3%) cases. There was no oncocytic ACC in the cohort. 3.2. Expression Profile of Biomarkers All expression profiles are described in Table 2 and detailed according to clinicopathological criteria in Figure 1. P53 was overexpressed in 11 tumors (16.9%; Figure 2); Rb was lost in 9 (17.3%). P16 was overexpressed in 33 (50.6%) from which 5 were Rb negative. At least one biomarker of the cell cycle was altered in 95.4% of patients. These expression profiles were not mutually exclusive. A nuclear expression of β-catenin, as a marker of Wnt-β-catenin pathway activation, was described in 11 cases (16.9%). LEF1 was expressed in 30 cases (46.2%). At least one biomarker of the Wnt-β-catenin pathway was altered in 49.2% of patients. Mutual P53 overexpression and nuclear expression of β-catenin were associated in 3 cases. No correlation was found between abnormalities in cell cycle proteins (p53, Rb/p16, ATM) and Wnt/β-catenin pathway (β-catenin, LEF1). GATA6 expression was low in 34 cases (52.3%) while SF1 was expressed in 20 cases (30.3%). MGMT expression was low in 22 patients (33.3%). GSTP1 expression was lost in 49 cases (76.6%) and PAX6 expression was low in 35 cases (54.7%). At least one biomarker of methylation was altered in 84.8% of patients (Figure 1). About potential predictive markers of response to therapy, PDxK, RRM1, SOAT1, TSPO and FATE1 expressions were high in, respectively, 63.1%, 72.3%, 53.8%, 49.2% and 29.2% of samples (Figure 2). Of note, no expression of PDL1 was found in our cohort. 3.3. Prognostic Value Median overall survival (OS) from time of metastatic diagnosis was 28 months [23.5–36.5] and 1-year survival and 5 year-survival were 80.3 and 22.7%, respectively (Figure 3). In this case, 38 patients (58%) were alive at 24 months and therefore considered as long survivors. In univariable analysis, overall survival from the time of metastatic disease was statistically associated with the expression pattern of p53, GSTP1, PDxK, FATE1 and RMM1 while in multivariable analysis PDxK and GSTP1 expression remained significantly associated with worst prognosis (Table 3). When adjusted to mENSAT GRAS validated prognostic markers, p53 and PDxK positive staining were independently associated to overall survival with an Odds Ratio of 2.24 and 2.73, respectively (Table 3; Figure 4). Moreover, overexpression of p53 staining (p = 0.021) and TSPO level of expression (p = 0.0071) were significantly lower in long survivors (defined by an overall survival > 24 months). 3.4. Predictive Markers of Response to Therapy All patients received mitotane at the time of metastasis with median treatment duration of 28.5 ± 34.8 months. Of them, 23 received mitotane prior to recurrence. Plasma mitotane levels were available in 53 patients and reached 14 mg/l in 86.8% of them. Here, 52 patients (78.8%) received platinum-based chemotherapy associated or not to mitotane. In this case, 50 out of 66 patients had RECIST 1.1 evaluable disease; the others received locoregional treatments of all targets or died before first evaluation. Best response according to RECIST 1.1 criteria was partial response or stable disease for 17 (34%) and 16 (32%) of cases, respectively. In this case, 17 patients (34%) had progressive disease whatever the line of treatment. No biomarker was found to be significantly associated with response to treatment according to RECIST 1.1. Mitotane duration and plasma levels were predictive of best response. 4. Discussion Here, 16 putative biomarkers were analyzed in a large series of 66 metastatic ACC. The aim of our study was to identify and prioritize independent prognostic biomarkers through their immunohistochemical pattern of expression, which could be easily used in the diagnostic setting in all centers. To that end, TMA of a large cohort of patients with metastatic ACC was studied for a large set of biomarkers analyzed at three same times with an appropriate mENSAT-GRAS criteria characterization. This strategy is complementary to the “one after the other” evaluation of single biomarker inconsistently adjusted for most relevant clinical prognostic. The overall survival of the cohort from the time of metastatic disease was quite high (median 28 months) allowing the analysis of long term survivors. This long term OS may be explained by the selection of patients with available tissue of the primary tumor most frequently achieved in good prognostic advanced ACC. Mirroring the long term OS, the rate of response was at the upper range of the literature. Our study identified for the first time P53 as the strongest prognostic molecular biomarker, independent prognostic marker of metastatic adrenocortical carcinoma after mENSAT-GRAS parameter adjustment. Relevant biomarkers were selected according to the main altered pathways in ACC pathogenesis discovered in previous studies. As compared to, the expression of biomarkers such as P53, Rb, GATA6 or SOAT1 [18,23,33,34] was consistent with that reported in previously published data except from SF1 that was less often positive in our cohort than in others [29,34]. Some previous studies suggested that cell cycle abnormalities at the protein level in ACC were associated with poor prognosis [18,33,35]. We confirm in this study that P53 overexpression is a factor of poor prognosis and demonstrate for the first time that it is an independent prognostic marker in a multivariate analysis adjusted for mENSAT-GRAS criteria. Neither other cell cycle-related protein expression pattern nor the alteration of the cell cycle pathway as a whole (by any altered protein studied) provided added prognostic value. On the other hand, the prognostic relevance of β-catenin expression is not validated in this cohort and no added prognostic value of LEF1 or the combined alteration of both proteins could be identified neither. Discrepant results may be explained by a different subgroup analysis since our study was performed in metastatic ACC specifically, with an OS calculated from the time of metastatic disease diagnosis. Jouinot et al. have shown that hypermethylation provide prognostic information that remains significant after grade adjustment in stage I–IV ACC patients [14]. Their data were based on the evaluation of the methylation status by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) in a panel of 4 genes. In our study, protein expression of 3 known validated epigenetic-targets was used. With this methodology, we found a correlation between low GSTP1 expression and overall survival. However, no biomarker of hypermethylation is prognostic in our multivariable analysis after mENSAT-GRAS adjustment and therefore suitable for clinical prognostic use. Positive expression of PDxK (involved in vitamin B-related metabolic processes) was described for the first time as a potential prognostic parameter that warrants further validation. Indeed, its expression is negatively correlated to survival in lung cancer [31]. PDxK and GSTP1 expressions have been previously correlated to resistance to platinum-based chemotherapy in ovarian and esophageal carcinomas [36,37]. However, the negative expression of these two markers is not significantly associated with response to platinum in our cohort. These results may be explained by the low number of response but also by the fact that tumor responses may not be strictly related to platinum-based chemotherapy but also due to mitotane combined treatment. As a surrogate marker, we looked for prognostic factors of long term survival (>24 months) and identified a significant association at univariable level with absence of p53 overexpression and low TSPO expression. Further studies should confirm the hypothesis of their role as predictive markers of response to platinum-based therapy or mitotane. Only mitotane duration and plasma levels were predictive of best response. We failed to identify potential predictive markers of response to Mitotane. That might be also explained by a lack of power. However, as recently published in a larger ENSAT cohort, SOAT1 is not predictive of response to mitotane [23], neither other candidates such as RRM1were found to correlate to tumor response. Evaluation of response to mitotane remains challenging because of its delayed response pattern and potential association to chemotherapy [7,38]. No predictive factor is validated to date for metastatic ACC and further studies are needed [39]. Our study has some limitations: it is retrospective; the use of TMA has the interest to make it possible to study simultaneously a large number of samples, but because of small size of the cores, sample bias (including tumor heterogeneity) might be higher than in the study of whole sections. Samples include primary and metastasis. However, results of the two patients with both primary and metastatic available tissues did not show any additional molecular event. Moreover, we have noticed the same limitation in recent remarkable manuscripts (ref [11] Mohan et al.). As most of retrospective prognostic studies, impact of treatments is not taken into account for the prognostic analysis. In addition, as for all similar studies that aim at looking for predictive markers of response in ACC, the response to mitotane is difficult to describe. In accordance with recent publications, the study could be extended to other potential prognostic factors such as VAV2 [25], TERT [40], EZH2 [41], FSCN1 [42], GoS2 [11] or other markers of senescence (P21, phosphor-H2AX). However, none of this biomarker was validated in metastatic ACC specifically after adjustment to mENSAT-GRAS parameters. Moreover, in contrast with previous microarrays studies, this one is the first that includes a comprehensive clinical and pathological characterization that focus on metastatic ACC and allows a multivariate analysis with mENSAT-GRAS criteria [43]. Finally, last limitation is that no genomic profiling data are available in this adult cohort. 5. Conclusions To conclude, we identified for the first time P53 as an independent prognostic marker of metastatic adrenocortical carcinoma after mENSAT-GRAS parameter adjustment. This biomarker is easily available and should be considered in clinical practice together with Ki67 for the management of patient with advanced ACC. Moreover, most of the previously potential prognostic parameters are not validated in our study. Our study underlies the importance of adjustment of potential new biomarkers to validated prognostic factors in well-defined population of ACC patients regarding their TNM stage in order to avoid the accumulation of invalidated redundant biomarkers providing no additional information in clinical practice. Acknowledgments HRA-Pharma and Association Surrénales for their financial support. The Platform of Experimental and Translational Pathology–CNRS UMS3655–INSERM US23 AMMICA–Gustave Roussy, for their help. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14092225/s1, Figure S1: Representative pictures of immunohistochemical staining of different markers. 1. overexpressed ATM in 100% of cells. 2. ATM with heterogeneous expression (20% strong, 20% weak and 60% moderate. H-score: 200). 3. positive Beta-cat with nuclear and cytoplasmic staining. 4. negative Beta-cat with membranous normal staining. 5. heterogeneous weak staining of Fat1. 6. high expressed Fat1 (strong cytoplasmic staining in 100% of cells). 7. positive nuclear staining of Gata6. 8. negative Gata6. 9. moderate cytoplasmic staining of GSTP1. 10. negative GSTP1. 11. Ki67 positive in 10% of cells. 12. Ki67 positive in 90% of cells. 13. Lef1 positive in 100% of cells. 14. heterogeneous expression of Lef1. 15. positive MGMT with nuclear staining (5×). 16. negative MGMT, see nuclear staining in normal endothelial cells. 17. overexpressed P16 with strong nuclear and cytoplasmic staining in 100% of cells. 18. negative P16. 19. wild type staining of P53 characterized by an admixture of negative cells, weakly and strongly positive cells. 20. positive overexpressed P53; strong staining in 100% of cells. 21. positive Pax6 with moderate staining. 22. strongly expressed Pax6. 23. conserved expression of Rb. 24. loss of expression of Rb, see positive endothelial normal cells. 25. strongly expressed RMM1. 26. moderately expressed RRM1. 27. positive SF1 with nuclear staining. 28. loss of staining of SF1. 29. SOAT1: weakly positive in few cells. 30. highexpressed pattern of SOAT1. Table S1: Protein analysis: reference and methods of analysis. Click here for additional data file. Author Contributions Conceptualization, S.H. and E.B.; methodology, A.A.G.; software, M.F.; validation, J.-Y.S.; formal analysis, S.H. and L.L.; investigation, M.K., A.A.G. and A.N.; writing—original draft preparation, S.H.; writing—review and editing, M.F., A.A.G., C.D.C., J.H., S.L., F.P., S.A. and E.B. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of GUSTAVE ROUSSY. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available in this article and supplementary material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Expression profile of biomarkers according to clinico-pathological criteria. Figure 2 P53 and PDXk expression in ACC. (A,B) Hematoxylin and eosin (H&E) stains (10×). (C–F) Immunostaining (10×); (C) P53 overexpression staining pattern; (D) Wild type staining of P53 (characterized by an admixture of negative cells, weakly and strongly positive cells); (E) immunopositive tumor for PDxK; (F) immunonegative tumor for PDxK. Figure 3 Overall Survival from date of metastatic diagnosis in the cohort. Figure 4 Survival curves of univariable analysis. (A) P53 and (B) PDxK. cancers-14-02225-t001_Table 1 Table 1 Clinicopathological characteristics. Variable Category N Evaluable Total N (%) At initial diagnosis Age 66 47.7 (±15.5) years Sex Ratio 66 23 M/43F Stage I–II 66 22 (33.3) III 20 (30.3) IV 24 (36.4) Tumoral syndrome Yes 65 36 (55.4) Hormonal secretion Yes 65 38 (58.5) Tumor size ≤10 cm 64 26 (40.6) >10 cm 38 (59.4) Weiss score 3 to 5 53 17 (32.1) 6 to 9 36 (67.9) Ki67 ≤20 65 44 (67.7) >20 21 (32.3) Resection status R0 R1/R2 51 42 (84.3) 9 (15.7) At metastatic diagnosis Age 66 48.7 (±15.5) years Symptoms 65 38 (58.5) Stage IVA IVB IVC 66 22 (33) 17 (26) 27 (41) Treatments Mitotane duration (months) 60 28.5 (±34.8) Mitotane > 14 mg/L 53 46 (86.8) Treated with platinum Yes 66 52 (78.8) Best response CR/PR 50 17 (34) SD 16 (32) PD 17 (34) Disease control > 12 months Yes 50 23 (34.8) CR: complete response; PR: partial response, SD: stable disease; PD: progression disease. cancers-14-02225-t002_Table 2 Table 2 Analysis of selected biomarkers. Protein Function/Pathway Relevant Pattern Potential Role in ACC n (%) P53 tumor suppressor/cell cycle Overexpression Prognostic 11 (16.9) P16 tumor suppressor/cell cycle Overexpression Prognostic 33 (50.8) Rb (retinoblastoma) tumor suppressor/cell cycle Loss of expression Prognostic 9 (17.3) ATM (ataxia telangiectasia mutated) kinase activated by DNA double-strand breaks High expression * Prognostic 28 (43.1) ß-catenin intracellular signal transducer/Wnt-pathway Nuclear expression (activation) Prognostic 11 (16.9) LEF1 (lymphoid enhancer-binding factor 1) transcription factor, downstream mediator/Wnt-pathway Positive staining Prognostic 30 (46.2) GATA6 (GATA-binding protein 6) transcription factor/adrenal steroidogenesis Low expression * Prognostic 34 (52.3) SF1 (Steroidogenic factor 1) transcription factor/adrenal development Positive staining Prognostic 20 (30.3) MGMT (O6-alkylguanine DNA alkyltransferase) DNA repair protein Low expression * Prognostic 22 (33.3) PAX6 (Paired box protein 6) transcription factor/encoded by hypermethylated gene Low expression * Prognostic 35 (54.7) GSTP1 (Glutathione S-Transferase Pi 1) enzyme/detoxification/encoded by hypermethylated gene Loss of expression Prognostic 49 (76.6) PDxK (Pyridoxal kinase) vitamin B-related metabolic processes Positive staining Predictive of response to platin 41 (63.1) RRM1 (Ribonucleotide Reductase Catalytic Subunit M1) enzyme/production of deoxyribonucleotide High expression * Prognostic and predictive of resistance to mitotane 47 (72.3) SOAT1 (Sterol O-Acyltransferase 1) adrenal steroidogenesis, potential target of mitotane High expression * Potential target of mitotane 35 (53.8) TSPO (Translocator protein) adrenal steroidogenesis, potential target of mitotane High expression * Potential target of mitotane 31 (49.2) FATE1 (Fetal and Adult Testis-Expressed 1) encoded by a gene targeted by SF1 Positive staining Predictive of response to mitotane 19 (29.2) * defined as H-Score > 150 (high) or <150 (low). cancers-14-02225-t003_Table 3 Table 3 Univariate and multivariate analysis of protein expression as prognostic factors of overall survival without and with adjustment for mENSAT GRAS. Variable Category HR p HR p HR p Univariate Multivariate Multivariate (adjusted for mENSAT GRAS) P53 Negative 1 0.0011 1 0.19 1 0.048 Positive 2.93 [1.49–5.75] 1.69 [0.8–3.56] 2.24 [1.05–4.74] PDxK Negative 1 0.0083 1 0.024 1 0.0027 Positive 2.14 [1.2–3.81] 2.11 [1.09–4.09] 2.73 [1.38–5.37] GSTP1 Negative 1 0.028 1 0.019 Positive 1.96 [1.06–3.62] 2.27 [1.19–4.32] FATE1 Negative 1 0.04 1 0.14 Positive 1.82 [1.02–3.26] 1.61 [0.86–3.01] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Baudin E. Adrenocortical Carcinoma Endocrinol. Metab. Clin. N. Am. 2015 44 411 434 10.1016/j.ecl.2015.03.001 26038209 2. Icard P. Goudet P. Charpenay C. Andreassian B. Carnaille B. Chapuis Y. Cougard P. Henry J.F. Proye C. Adrenocortical Carcinomas: Surgical Trends and Results of a 253-Patient Series from the French Association of Endocrine Surgeons Study Group World J. Surg 2001 25 891 897 10.1007/s00268-001-0047-y 11572030 3. Kerkhofs T.M.A. Verhoeven R.H.A. Van der Zwan J.M. Dieleman J. Kerstens M.N. Links T.P. Van de Poll-Franse L.V. Haak H.R. Adrenocortical Carcinoma: A Population-Based Study on Incidence and Survival in the Netherlands since 1993 Eur. J. Cancer 2013 49 2579 2586 10.1016/j.ejca.2013.02.034 23561851 4. Fassnacht M. Allolio B. Clinical Management of Adrenocortical Carcinoma Best Pract. Res. Clin. Endocrinol. Metab. 2009 23 273 289 10.1016/j.beem.2008.10.008 19500769 5. Asare E.A. Wang T.S. Winchester D.P. Mallin K. Kebebew E. Sturgeon C. A Novel Staging System for Adrenocortical Carcinoma Better Predicts Survival in Patients with Stage I/II Disease Surgery 2014 156 1378 1385 1378–1385; discussion 1385–1386 10.1016/j.surg.2014.08.018 25456914 6. Beuschlein F. Weigel J. Saeger W. Kroiss M. Wild V. Daffara F. Libe R. Ardito A. Al Ghuzlan A. Quinkler M. Major Prognostic Role of Ki67 in Localized Adrenocortical Carcinoma after Complete Resection J. Clin. Endocrinol. Metab. 2015 100 841 849 10.1210/jc.2014-3182 25559399 7. Vezzosi D. Do Cao C. Hescot S. Bertherat J. Haissaguerre M. Bongard V. Drui D. De La Fouchardière C. Illouz F. Borson-Chazot F. Time Until Partial Response in Metastatic Adrenocortical Carcinoma Long-Term Survivors Horm. Cancer 2018 9 62 69 10.1007/s12672-017-0313-6 29071575 8. Libé R. Clinical and Molecular Prognostic Factors in Adrenocortical Carcinoma Minerva Endocrinol. 2019 44 58 69 10.23736/S0391-1977.18.02900-0 30221891 9. Libé R. Borget I. Ronchi C.L. Zaggia B. Kroiss M. Kerkhofs T. Bertherat J. Volante M. Quinkler M. Chabre O. Prognostic Factors in Stage III-IV Adrenocortical Carcinomas (ACC): An European Network for the Study of Adrenal Tumor (ENSAT) Study Ann. Oncol. 2015 26 2119 2125 10.1093/annonc/mdv329 26392430 10. Assié G. Jouinot A. Fassnacht M. Libé R. Garinet S. Jacob L. Hamzaoui N. Neou M. Sakat J. de La Villéon B. Value of Molecular Classification for Prognostic Assessment of Adrenocortical Carcinoma JAMA Oncol. 2019 5 1440 10.1001/jamaoncol.2019.1558 31294750 11. Mohan D.R. Lerario A.M. Else T. Mukherjee B. Almeida M.Q. Vinco M. Rege J. Mariani B.M.P. Zerbini M.C.N. Mendonca B.B. Targeted Assessment of G0S2 Methylation Identifies a Rapidly Recurrent, Routinely Fatal Molecular Subtype of Adrenocortical Carcinoma Clin. Cancer Res. 2019 25 3276 3288 10.1158/1078-0432.CCR-18-2693 30770352 12. Fassnacht M. Assie G. Baudin E. Eisenhofer G. de la Fouchardiere C. Haak H.R. de Krijger R. Porpiglia F. Terzolo M. Berruti A. Adrenocortical Carcinomas and Malignant Phaeochromocytomas: ESMO-EURACAN Clinical Practice Guidelines for Diagnosis, Treatment and Follow-Up Ann. Oncol 2020 31 1476 1490 10.1016/j.annonc.2020.08.2099 32861807 13. Lippert J. Appenzeller S. Liang R. Sbiera S. Kircher S. Altieri B. Nanda I. Weigand I. Gehrig A. Steinhauer S. Targeted Molecular Analysis in Adrenocortical Carcinomas: A Strategy Toward Improved Personalized Prognostication J. Clin. Endocrinol. Metab. 2018 103 4511 4523 10.1210/jc.2018-01348 30113656 14. Jouinot A. Assie G. Libe R. Fassnacht M. Papathomas T. Barreau O. DE LA Villeon B. Faillot S. Hamzaoui N. Neou M. DNA Methylation Is an Independent Prognostic Marker of Survival in Adrenocortical Cancer J. Clin. Endocrinol. Metab. 2016 102 923 932 10.1210/jc.2016-3205 15. Zheng S. Cherniack A.D. Dewal N. Moffitt R.A. Danilova L. Murray B.A. Lerario A.M. Else T. Knijnenburg T.A. Ciriello G. Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma Cancer Cell 2016 30 363 10.1016/j.ccell.2016.07.013 16. Assié G. Letouzé E. Fassnacht M. Jouinot A. Luscap W. Barreau O. Omeiri H. Rodriguez S. Perlemoine K. René-Corail F. Integrated Genomic Characterization of Adrenocortical Carcinoma Nat. Genet. 2014 46 607 612 10.1038/ng.2953 24747642 17. Juhlin C.C. Goh G. Healy J.M. Fonseca A.L. Scholl U.I. Stenman A. Kunstman J.W. Brown T.C. Overton J.D. Mane S.M. Whole-Exome Sequencing Characterizes the Landscape of Somatic Mutations and Copy Number Alterations in Adrenocortical Carcinoma J. Clin. Endocrinol. Metab. 2014 100 E493 E502 10.1210/jc.2014-3282 25490274 18. Ragazzon B. Libé R. Gaujoux S. Assié G. Fratticci A. Launay P. Clauser E. Bertagna X. Tissier F. de Reyniès A. Transcriptome Analysis Reveals That P53 and {beta}-Catenin Alterations Occur in a Group of Aggressive Adrenocortical Cancers Cancer Res. 2010 70 8276 8281 10.1158/0008-5472.CAN-10-2014 20959480 19. Fassnacht M. Dekkers O. Else T. Baudin E. Berruti A. de Krijger R. Haak H. Mihai R. Assie G. Terzolo M. European Society of Endocrinology Clinical Practice Guidelines on the Management of Adrenocortical Carcinoma in Adults, in Collaboration with the European Network for the Study of Adrenal Tumors Eur. J. Endocrinol. 2018 179 G1 G46 10.1530/EJE-18-0608 30299884 20. Volante M. Terzolo M. Fassnacht M. Rapa I. Germano A. Sbiera S. Daffara F. Sperone P. Scagliotti G. Allolio B. Ribonucleotide Reductase Large Subunit (RRM1) Gene Expression May Predict Efficacy of Adjuvant Mitotane in Adrenocortical Cancer Clin. Cancer Res. 2012 18 3452 3461 10.1158/1078-0432.CCR-11-2692 22547773 21. Hescot S. Amazit L. Lhomme M. Travers S. DuBow A. Battini S. Boulate G. Namer I.J. Lombes A. Kontush A. Identifying Mitotane-Induced Mitochondria-Associated Membranes Dysfunctions: Metabolomic and Lipidomic Approaches Oncotarget 2017 8 109924 109940 10.18632/oncotarget.18968 29299119 22. Doghman-Bouguerra M. Finetti P. Durand N. Parise I.Z.S. Sbiera S. Cantini G. Canu L. Hescot S. Figueiredo M.M.O. Komechen H. Cancer-Testis Antigen FATE1 Expression in Adrenocortical Tumors Is Associated with A Pervasive Autoimmune Response and Is A Marker of Malignancy in Adult, but Not Children, ACC Cancers 2020 12 689 10.3390/cancers12030689 23. Weigand I. Altieri B. Lacombe A.M.F. Basile V. Kircher S. Landwehr L.-S. Schreiner J. Zerbini M.C.N. Ronchi C.L. Megerle F. Expression of SOAT1 in Adrenocortical Carcinoma and Response to Mitotane Monotherapy: An ENSAT Multicenter Study J. Clin. Endocrinol. Metab. 2020 105 2642 2653 10.1210/clinem/dgaa293 24. Eisenhauer E.A. Therasse P. Bogaerts J. Schwartz L.H. Sargent D. Ford R. Dancey J. Arbuck S. Gwyther S. Mooney M. New Response Evaluation Criteria in Solid Tumours: Revised RECIST Guideline (Version 1.1) Eur. J. Cancer 2009 45 228 247 10.1016/j.ejca.2008.10.026 19097774 25. Sbiera S. Sbiera I. Ruggiero C. Doghman-Bouguerra M. Korpershoek E. de Krijger R.R. Ettaieb H. Haak H. Volante M. Papotti M. Assessment of VAV2 Expression Refines Prognostic Prediction in Adrenocortical Carcinoma J. Clin. Endocrinol. Metab. 2017 102 3491 3498 10.1210/jc.2017-00984 28911143 26. De Martino M.C. Al Ghuzlan A. Aubert S. Assié G. Scoazec J.-Y. Leboulleux S. Do Cao C. Libè R. Nozières C. Lombès M. Molecular Screening for a Personalized Treatment Approach in Advanced Adrenocortical Cancer J. Clin. Endocrinol. Metab. 2013 98 4080 4088 10.1210/jc.2013-2165 23979958 27. El Wakil A. Lalli E. The Wnt/Beta-Catenin Pathway in Adrenocortical Development and Cancer Mol. Cell. Endocrinol. 2011 332 32 37 10.1016/j.mce.2010.11.014 21094679 28. Kiiveri S. Liu J. Arola J. Heikkilä P. Kuulasmaa T. Lehtonen E. Voutilainen R. Heikinheimo M. Transcription Factors GATA-6, SF-1, and Cell Proliferation in Human Adrenocortical Tumors Mol. Cell. Endocrinol. 2005 233 47 56 10.1016/j.mce.2005.01.012 15767045 29. Sbiera S. Schmull S. Assie G. Voelker H.-U. Kraus L. Beyer M. Ragazzon B. Beuschlein F. Willenberg H.S. Hahner S. High Diagnostic and Prognostic Value of Steroidogenic Factor-1 Expression in Adrenal Tumors J. Clin. Endocrinol. Metab. 2010 95 E161 E171 10.1210/jc.2010-0653 20660055 30. Cosentini D. Badalamenti G. Grisanti S. Basile V. Rapa I. Cerri S. Spallanzani A. Perotti P. Musso E. Laganà M. Activity and Safety of Temozolomide in Advanced Adrenocortical Carcinoma Patients Eur. J. Endocrinol. 2019 181 681 689 10.1530/EJE-19-0570 31639772 31. Galluzzi L. Vitale I. Senovilla L. Olaussen K.A. Pinna G. Eisenberg T. Goubar A. Martins I. Michels J. Kratassiouk G. Prognostic Impact of Vitamin B6 Metabolism in Lung Cancer Cell Rep. 2012 2 257 269 10.1016/j.celrep.2012.06.017 22854025 32. McCarty K.S. Szabo E. Flowers J.L. Cox E.B. Leight G.S. Miller L. Konrath J. Soper J.T. Budwit D.A. Creasman W.T. Use of a monoclonal anti-estrogen receptor antibody in the immunohistochemical evaluation of human tumors Cancer Res. 1986 46 4244 4248 33. Ragazzon B. Libé R. Assié G. Tissier F. Barreau O. Houdayer C. Perlemoine K. Audebourg A. Clauser E. René-Corail F. Mass-Array Screening of Frequent Mutations in Cancers Reveals RB1 Alterations in Aggressive Adrenocortical Carcinomas Eur. J. Endocrinol. 2014 170 385 391 10.1530/EJE-13-0778 24347427 34. Parviainen H. Schrade A. Kiiveri S. Prunskaite-Hyyryläinen R. Haglund C. Vainio S. Wilson D.B. Arola J. Heikinheimo M. Expression of Wnt and TGF-β Pathway Components and Key Adrenal Transcription Factors in Adrenocortical Tumors: Association to Carcinoma Aggressiveness Pathol. Res. Pract. 2013 209 503 509 10.1016/j.prp.2013.06.002 23866946 35. Giordano T.J. Kuick R. Else T. Gauger P.G. Vinco M. Bauersfeld J. Sanders D. Thomas D.G. Doherty G. Hammer G. Molecular Classification and Prognostication of Adrenocortical Tumors by Transcriptome Profiling Clin. Cancer Res. 2009 15 668 676 10.1158/1078-0432.CCR-08-1067 19147773 36. Fekete J.T. Ősz Á. Pete I. Nagy G.R. Vereczkey I. Győrffy B. Predictive Biomarkers of Platinum and Taxane Resistance Using the Transcriptomic Data of 1816 Ovarian Cancer Patients Gynecol. Oncol. 2020 156 654 661 10.1016/j.ygyno.2020.01.006 31973910 37. Yamamoto Y. Konishi H. Ichikawa D. Arita T. Shoda K. Komatsu S. Shiozaki A. Ikoma H. Fujiwara H. Okamoto K. Significance of GSTP1 for Predicting the Prognosis and Chemotherapeutic Efficacy in Esophageal Squamous Cell Carcinoma Oncol. Rep. 2013 30 1687 1694 10.3892/or.2013.2606 23842854 38. Hescot S. Leboulleux S. Caramella C. Paci A. Lombes M. Berdelou A. Baudin E. Early Progression under Mitotane and Polychemotherapy Does Not Mean Failure in Adrenocortical Carcinoma Patient Ann. Endocrinol. 2017 78 67 69 10.1016/j.ando.2016.10.001 39. Millis S.Z. Ejadi S. Demeure M.J. Molecular Profiling of Refractory Adrenocortical Cancers and Predictive Biomarkers to Therapy Biomark. Cancer 2015 7 69 76 10.4137/BIC.S34292 26715866 40. Svahn F. Paulsson J.O. Stenman A. Fotouhi O. Mu N. Murtha T.D. Korah R. Carling T. Bäckdahl M. Wang N. TERT Promoter Hypermethylation Is Associated with Poor Prognosis in Adrenocortical Carcinoma Int. J. Mol. Med. 2018 42 1675 1683 10.3892/ijmm.2018.3735 29956721 41. Drelon C. Berthon A. Mathieu M. Ragazzon B. Kuick R. Tabbal H. Septier A. Rodriguez S. Batisse-Lignier M. Sahut-Barnola I. EZH2 Is Overexpressed in Adrenocortical Carcinoma and Is Associated with Disease Progression Hum. Mol. Genet. 2016 25 2789 2800 10.1093/hmg/ddw136 27149985 42. Poli G. Ruggiero C. Cantini G. Canu L. Baroni G. Armignacco R. Jouinot A. Santi R. Ercolino T. Ragazzon B. Fascin-1 Is a Novel Prognostic Biomarker Associated With Tumor Invasiveness in Adrenocortical Carcinoma J. Clin. Endocrinol. Metab. 2019 104 1712 1724 10.1210/jc.2018-01717 30476173 43. Ip J.C.Y. Pang T.C.Y. Glover A.R. Soon P. Zhao J.T. Clarke S. Robinson B.G. Gill A.J. Sidhu S.B. Immunohistochemical Validation of Overexpressed Genes Identified by Global Expression Microarrays in Adrenocortical Carcinoma Reveals Potential Predictive and Prognostic Biomarkers Oncologist 2015 20 247 256 10.1634/theoncologist.2014-0392 25657202

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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091189 animals-12-01189 Article Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein https://orcid.org/0000-0002-4358-9236 Tiezzi Francesco 12* https://orcid.org/0000-0003-4706-7846 Fleming Allison 3 Malchiodi Francesca 4 Su Guosheng Academic Editor Ebrahimie Esmaeil Academic Editor 1 Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144 Firenze, Italy 2 Department of Animal Science, North Carolina State University, Raleigh, NC 27695, USA 3 Lactanet Canada, Guelph, ON N1K 1E5, Canada; afleming@lactanet.ca 4 The Semex Alliance, Guelph, ON N1H 6J2, Canada; fmalchiodi@semex.com * Correspondence: francesco.tiezzi2@unifi.it 06 5 2022 5 2022 12 9 118904 2 2022 04 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Simple Summary Genomic selection models aim at predicting the performance of individuals with the use of genomic markers. In animal breeding, prediction models are seldomly tested for their ability to predict new individuals’ performance under different environmental conditions, despite the changes in management and diet that the industry undergoes. In this study, we propose a method to use milk infrared spectra as descriptors of environmental variation among herds. These descriptors can be incorporated in genomic prediction models similarly to how genomic markers are included. The inclusion of environmental descriptors is shown to improve the predictive ability for new genotypes under new environmental conditions. Abstract The purpose of this study was to provide a procedure for the inclusion of milk spectral information into genomic prediction models. Spectral data were considered a set of covariates, in addition to genomic covariates. Milk yield and somatic cell score were used as traits to investigate. A cross-validation was employed, making a distinction for predicting new individuals’ performance under known environments, known individuals’ performance under new environments, and new individuals’ performance under new environments. We found an advantage of including spectral data as environmental covariates when the genomic predictions had to be extrapolated to new environments. This was valid for both observed and, even more, unobserved families (genotypes). Overall, prediction accuracy was larger for milk yield than somatic cell score. Fourier-transformed infrared spectral data can be used as a source of information for the calculation of the ‘environmental coordinates’ of a given farm in a given time, extrapolating predictions to new environments. This procedure could serve as an example of integration of genomic and phenomic data. This could help using spectral data for traits that present poor predictability at the phenotypic level, such as disease incidence and behavior traits. The strength of the model is the ability to couple genomic with high-throughput phenomic information. genomic selection spectral data genotype by environment interaction This research received no funding. ==== Body pmc1. Introduction Genomic prediction models are oriented towards predicting the performance of new individuals with the use of genomic markers. The ability of genomic prediction models to predict across environments in livestock is seldomly tested. In addition, these environmental effects will exert the same pressure on each candidate; such models do not need to account for effects other than the genetic one. However, environmental components definitely exert an effect on the phenotype, which needs to be considered in extrapolating predictions to new environments, i.e., ensuring the portability of the predictions to different environmental conditions. In addition, these environmental changes could exert different effects depending on the genotype, and different genotypes may react differently to environmental changes [1,2]. In other words, there could be a presence of genotype by environment interaction (GxE). In breeding plans, the new genotypes are usually tested in herds (or flocks, or stations) that are part of an established organization, which means that these genotypes are tested under known environmental conditions. Sometimes, new herds could join the breeding program, or the same herds could make changes in management, either intentionally or unintentionally [3,4]. In addition, some environmental conditions are not fully controllable by the farmers, meaning that some environmental variables could fall outside the known range. For example, climate change could lead livestock to experience environmental conditions not experienced before [5,6], making the heat load parameter fall outside of the known range. Figure 1 shows the three different scenarios for the prediction of performance under new genotypes and/or environmental conditions. Here, sires (i.e., genotypes, families) are reported in rows, while herds (i.e., environments) are reported in columns. Each herd show several herd-year-season classes, which define the temporary environmental variance within the permanent location. Sires 1 to 10 are considered known or proven. Likewise, herds 1 to 4 are considered known environments, already being part of the breeding organization. Phenotypic information belonging to sires 1 to 10 and herds 1 to 4 is considered a training set and labeled as section ‘A’. The performance of known sires could be extrapolated to new herds (5 and 6), which differ from the known ones for a number of parameters. This would correspond to section B, i.e., known genotypes in new environments. Conversely, the prediction of new sires’ performance (11 to 16) in known herds is what is commonly practiced in genomic selection, and that would correspond to section C. Finally, the most challenging scenario would be to predict the performance of new sires in new herds, i.e., section D. Although scenarios C and D might seem unrealistic, we should keep in mind that herd management and environmental conditions are in constant change, and this scenario is more relevant when farming conditions (e.g., diet, climate) tend to change quickly. Therefore, there is aneed to consider predictions for new environments in the same way that we consider predictions for new genotypes. For the former, the use of environmental covariates might be useful. In the implementation of cross-environment genomic prediction, the choice of the environmental covariates is not trivial. Several attempts have been taken in using different sets of variables, from climate records to management parameters [7,8,9], and from geographical to spatial coordinates [10,11]. Some authors have also proposed the use of the estimates for contemporary group itself or some a posteriori estimation of it, in order to make full use of the data [12,13]. Here, a first model needs to be implemented using the contemporary group as a fixed, cross-classified effect. Best linear unbiased estimates (BLUE) of contemporary groups are then merged back to the original dataset and used as a fixed linear covariate. This is needed to obtain variables that only contain environmental variability and are not collinear to the genetic component (or any other). The average phenotypic value of a contemporary group could include some environmental variation, because not all genotypes are included in every contemporary group. Therefore, such BLUE provide an average contemporary group performance, adjusted for genetic (and other) effects; therefore, their variation is determined by the environmental component alone. However, this method shows a pitfall in cross-validation, since the trait itself needs to be recorded in the environmental classes (i.e., herds) used for validation. This brings the need to use a predictor that can be (easily and cheaply) recorded in new environmental classes before the actual trait has to. In the era of high-throughput phenotyping, there is a need to re-think animal breeding models to account for the vast amount of data generated by the fast-developing field of sensor technology [14]. Fourier-transformed, mid-infrared spectral (FTIR) information offers an alternative as an inexpensive, high-throughput predictor or indicator. FTIR is largely used in the agricultural and livestock industries for the high-throughput assessment of several qualitative measures, especially when the phenotype would be expensive to measure using wet-lab chemistry. Several studies have investigated how to include this source of information into breeding programs [15,16,17]. One potential use of spectral information could be to include all the spectral variables into the model as environmental descriptors [18]. This approach does not require the development of calibration equations for the prediction of specific variables; instead, it only requires the extraction of the environmental component from this variable (and the removal of the genetic component). The calibration equation used in this approach will be implicit in the use of the spectral covariates in the prediction model, which can be updated at every round of genetic evaluation. Even in absence of knowledge about the association between specific wavenumbers and the trait of interest, this allows us to inform the models about the ‘environmental coordinates’ of the phenotype to predict. If, supposedly, some wavenumbers are associated with the presence of certain fatty acids in the milk, and it is the herd diet determining the presence of those fatty acids, the FTIR absorbance at those wavenumbers will contain information about the diet. In support of this hypothesis, FTIR spectral data have been used to successfully discriminate milk samples based on feeding or grazing systems [19,20]. The spectral wavelengths have also been shown to be in association with diseases incidence [21] and the cows’ metabolic status [22], which suggest the strong relationship between the spectral data and the herd status, in general. Overall, expecting the presence of systematic environmental variation in the milk spectrum, such environmental variation could be used for different modeling purposes at no cost because of the routine collection and storage of spectral data. The environmental variation present in the spectrum could be associated with certain environmental conditions (e.g., heat stress), therefore giving the possibility to be used as indicator. In addition, the spectral data show high dimensionality, which relates to the possibility to capture complex environmental variation. All this could be exploited in prediction models aimed at predicting outside of the known environmental range, but a proper (cross-) validation is needed. The objective of this study was to test the value of FTIR information as environmental covariates in genomic prediction models, for the prediction of new genotypes in new environments. 2. Materials and Methods 2.1. Phenotypic Data Phenotypic data used in this study came from the Lactanet Canada database. Test-day records for milk yield (MY), somatic cell score (SCS), and mid-infrared spectral data were made available together with test dates, herd identifiers, and pedigree information. Spectra data included absorbance for 1060 wavenumbers (WVN) from FOSS MilkoScan FT6000 spectrophotometers (Foss, Hillerød, Denmark). Each WVN refers to a specific wavelength in the infra-red range of the spectrum [23]; the WVN have a discontinuous numbering from 5010 to 925 cm−1. Information about lactation number and stage of lactation was also available. The herd-year-season class (HYS) was created by combining year and season of test date with the herd. Seasons were created as in Rovere et al. [23], i.e., January–March, April–June, July–September, and October–December. Stage of lactation classes were created as 13 monthly classes, with the 13th class including records up to the 18th month of lactation. An open ‘fourth or later’ lactation number class was also created. Stage and number of lactations were combined into 52 number by stage of lactation (NSL) classes. The initial dataset included more than 10 million records on 1.3 million cows. Editing was performed by removing test-day records beyond the 18th month of lactation (540 days), removing cows with less than 12 records available and HYS classes with less than 20 records. Merging the spectral data generated a dataset that included 1,540,935 records, from 84,131 cows. Records were removed if records for any of the spectral variables exceeded the five standard deviations from the mean. Hereinafter, this dataset will be referred to as Data1full. A reduced dataset, including only herds with at least 30 HYS classes, was also created and will be referred to as Data1reduced (N = 571,440). Both datasets are described in Table 1. 2.2. Genomic Data Genomic information for 1992 bulls was provided by The Semex Alliance. Individuals were genotyped with the Illumina SNP50 Beadchip. A total of 45,187 SNPs were available. Editing included the removal of markers with call rate below 0.90 and minor allele frequency below 0.05. After editing, 38,024 markers were left for analysis. Only 483 bulls will be then used for analysis; see below. 2.2.1. Data Analysis Overview This study proposes a multi-step approach. First, environmental information had to be extracted from the phenotypic and spectral data (steps 1 and 2). Then, the Kernel-based genomic prediction models were implemented on the condensed information as extracted from the first step. The Kernel-based models were used for variance components estimation (step 3) and cross-validation (step 4). 2.2.2. Step 1: Estimation of Herd-Year-Season Deviations Datasets Data1full and Data1reduced were used in the first step of the study. This step aimed at the estimation of Best Linear Unbiased Estimates (BLUEs) for the HYS classes in order to build environmental covariates to be used in the next steps [12,13]. Milk yield, SCS and each spectral wavenumber was analyzed using the following model:(1) yijkl=NSLi+HYSj+ak+pk+ϵijkl where yijkl is the phenotypic record for the lth observation of the kth cow, in the jth HYS and ith NSL class, NSLi is the fixed effect of the ith number by stage of lactation class, HYSj is the fixed effect of the jth herd-year-season class, ak is the additive genetic effect of the kth individual, pk is the cow permanent environmental effect of the kth individual, and ϵijkl is the residual. The vector of additive genetic effects was defined as a ~ N(0, Aσa2), where A is a pedigree-derived numerator relationship matrix and σa2 is the additive genetic variance. The vector of cow permanent environmental effects was defined as p ~ N(0, Iσp2), where I is an identity matrix and σp2 is the cow permanent environmental variance. The vector of residuals was defined as ϵ ~ N(0, Iσϵ2), where σϵ2 is the residual variance and I is an identity matrix. Variance components estimates for each wavenumber and production traits were obtained using Data1reduced using the software Gibbs2f90 [24] version 1.86; a total of 35,000 iterations were run, discarding the first 5000 as burn-in and thinning every 10 iterations. As no specifications about the prior were passed to the program, the variance components were assigned flat priors (i.e., no shrinkage) and fixed effects were assigned bounded uniform priors. For the random effects, the software uses normal distribution priors with mean equal to 0 and variance equal to the estimated variance at each iteration. Convergence was assessed by visual inspection of trace plots and Geweke’s test implemented in the ‘coda’ package in R [25]. Once the variance components were estimated, the model solutions and their standard errors (for the fixed and random effects) necessary for the following steps were obtained using Data1full and the software BLUPf90 [26] by fixing the variance components to the estimated values. Heritability (h2) and repeatability (r2) were defined as h2=σa2σa2+σp2+σe2 and r2=σa2+σp2σa2+σp2+σe2. A dataset containing all the BLUEs for the HYS effect was created, including solutions for MY, SCS, and all the 1060 wavenumbers. The HYS BLUEs for each MY, SCS, and WVN were centered to null mean and unit variance. Principal components (based on the covariance matrix) were extracted from the HYS BLUEs for the 1060 wavenumbers using the native R function princomp [27]. 2.2.3. Step 2: Calculation of Herd-Year-Season Daughter-Yield-Deviations Using solutions from models in step 1, daughter-yield deviations for each bull in each herd-year-season class (hysDYD) were calculated [9]. The hysDYD were defined by pre-correcting the phenotypic data for the number by stage of lactation class, then averaged by sire-HYS class. The hysDYD were then weighted for the within-HYS effective daughter contribution (EDC) to account for the different amount of information contained in each hysDYD value, given by the different number of sire’s daughters and their records. Here, EDC were calculated following the sixth method proposed by Fikse and Banos [28]. Using Data1full, a total of 518,669 hysDYD observations were made available. These were edited by keeping only those belonging to genotyped sires and showing an EDC of at least 1.6, forcing sires to be present in at least 3 HYS classes, HYS classes to show at least 3 sires and herds having at least 3 HYS classes. This generated Data2, which contained 16,891 observations on 483 sires, 406 herds and 3316 HYS classes (Table 2). 2.2.4. Step 3: Estimation of Variance Components Different models including additive genetic and environmental effects were implemented, as well as models that included their interaction. Variance components estimation was carried out using dataset Data2. A model with the two main effects was first defined as:(2) yij=μ+gi+ej+ϵij where μ is the intercept, yij is the hysDYD for the ith sire in the jth HYS, gi is the additive genetic effect of the ith sire, ej is the environmental effect for the jth HYS, and ϵij is the random residual. The vector of additive genetic effects was defined as g ~ N(0,Gσg2), where G is a genomic relationship matrix and σg2 is the estimated additive genetic variance. The genomic relationship matrix was built according to the first method described by VanRaden [29] using the software preGSf90 [30]. The vector of environmental effects ej was defined in different ways depending on the model. A baseline model (Base) was defined and considered the environmental effect as random uncorrelated, i.e., e ~ N(0, Iσe2), where I is an identity matrix and σe2 is the environmental variance. A set of models considered the environmental effect which included covariance matrices among the HYS classes (also known as Kernels [31,32]). Here, the vector of environmental effects was defined as e ~ N(0, Eσe2), where E is a matrix that reports the covariance among the HYS classes based on the environmental covariates. Such covariance matrix is built as E=XX′, where X is a matrix that contains the environmental covariates (in columns) for each HYS class (in rows). The columns in X report the environmental covariates (e.g., BLUE for MY, SCS and the WVN) centered to null mean and unit variance, so that the E matrix does not need to be rescaled. In fitting the model, since data involve multiple records per sire and HYS class, the genetic covariance structure of additive effects was defined as ZGZ′, while the environmental covariance structure was defined as WEW′, where Z is the (sire by observation) incidence matrix and W is the (HYS class by observation) incidence matrix [7], while G and E were as defined above. The choice of the environmental covariates to be included in X defined the model. In model AWN, HYS BLUEs for all the 1060 wavenumbers were used. This means that X was a matrix with 1060 columns and a number of rows equal to the number of HYS included in the analysis, i.e., 16,891 (Table 2). In models PC2, E is a two-column matrix with the first two principal components extracted from the HYS BLUEs. Similarly, PC10 included the first 10 principal components, while model PC20 included the first 20, PC30 included the first 30 and model PC40 included the first 40 principal components. The first 2, 10, 20, 30 and 40 components absorbed 62.7%, 89.5%, 93.8%, 95.8%, and 96.6% of the whole WVN variance, respectively. In model PROD, covariance was defined on HYS BLUEs for MY and SCS, defining a X matrix with 2 columns. A summary of the environmental covariates used in the models is reported in Table 3. A model with the interaction between the additive genetic and environmental effects was also defined, as in:(3) Yij=μ+gi+ej+geij+ϵij where yij, μ, gi, ej and ϵij are as defined in equation [3], and geij is the interaction term. The vector for the interaction effect was defined as ge ~ N(0, [ZGZ′°WEW′]σge2), where ZGZ′°WEW′ denotes the Hadamard product between the additive genetic and environmental kernels, and σge2 is the variance for the interaction term [7,9]. Again, the environmental component was defined in different ways depending on the environmental covariates included in E. For each set of environmental covariates, a model as in Formula (2) (without interaction term) and a model as in Formula (3) (with the interaction term) were implemented. 2.2.5. Step 4: Cross-Validation The relevance of each set of environmental covariates to improve the prediction models was tested using cross-validation. As outlined above, the predictive ability for models that differ for their inclusion of environmental covariates needs to be tested on schemes that introduce new genotypes but also new environments. The model validation was carried out as a repeated four-fold cross-validation. This involved the following steps: (1) sampling 100 sires and 100 herds from Data2; (2) defining the validation sets (B, C, and D altogether, Figure 1) as the records belonging to the sampled 100 sires and 100 herds; (3) defining the training set (A, as pictured in Figure 1) as the remainder of Data2; (4) fitting the models on the training set in order to obtain solutions for all the sires and HYS classes, including those for which the phenotypes were removed from the training set; (5) obtaining predictions for the training and validation sets by summing the respective solutions as defined by each model; (6) calculating the prediction accuracy as the Pearson correlation between predicted and observed hysDYD. The prediction accuracy was calculated separately for each of the sections B, C, and D: the hysDYD that belonged to the sampled herds and the non-sampled sires were assigned the B validation set, the hysDYD that belonged to the sampled sires and the non-sampled herds were assigned the C validation set, and the hysDYD that belonged to both the sampled sires and sampled herds were assigned to the D validation set. The six steps of the cross-validation were repeated 20 times in order to have an appropriate representation of sires and herds in the training and validation sets. For each of the 20 replicates, a unique combination of new sires and new herds was sampled to define the four sections (A, B, C, and D), and each replicate generated a value of accuracy for each section. On average, 60% of the records were assigned to the training set (section A), 40% of the records were assigned to the validation set, 18% in section B, 15% in section C and 7% in section D. The mean and standard deviation of the accuracy over the 20 replicates were calculated and used to compare model performance. 2.2.6. Model Implementation for Steps 3 and 4 All models were fitted using the R function BGLR [33]; kernels were used using the Reproducing Kernel Hilbert Spaces definition after eigenvalue decomposition was carried out [34]. The environmental effect in Base was implemented as a Bayesian Ridge regression. A total of 75,000 iterations were run, discarding the first 25,000 as burn-in and thinning every 10 iterations. Convergence was assessed by visual inspection of trace plots and the Geweke’s test implemented in the ‘coda’ package in R [25]. 3. Results 3.1. Variance Decomposition of Spectral Data Heritability and repeatability for each of the 1060 WVN is reported in Figure 2. Estimates of heritability and repeatability for MY and SCS are also reported as horizontal lines in the same plot (solid line for MY, dashed line for SCS). Estimates of heritability were 0.20 and 0.11 for MY and SCS, respectively, while estimates of repeatability were 0.40 and 0.34. The heritability estimates show different values across the WVN range, and repeatability estimates appear to follow a pattern similar to the heritability, suggesting that the cow permanent environmental contribution is constant across the wavenumbers. Both heritability and repeatability were stable between, approximately, WVN 5000 and 4200 (with values around 0.18 and 0.23, respectively); a decline in both parameters’ estimates brought them to the null value around WVN 3600, with the exception of a peak around WVN 3700 (0.30 for heritability, 0.38 for repeatability). The null estimate values were found for WVN from 3600 to 3070, with the exception of a short peak around WVN 3450 (0.03 for heritability, 0.04 for repeatability). Starting from WVN 3050, both parameters increased dramatically for most of the remainder of the WVN, with some exceptions. While the heritability values were, on average, around 0.35, and the repeatability values were around 0.45, lower values were found between WVN 2600 and 2500 (0.2 heritability, 0.25 repeatability) and between WVN 1670 and 1610, showing null values for both parameters. Below WVN 1610, both parameters showed irregular estimates, with heritability being 0.38 and repeatability being 0.46, on average. 3.2. Genotype, Environment and Their Interaction on the Studied Traits Figure 3 and Figure 4, on the top panel, the proportion of variance explained by the additive genetic effect (G), environmental effect (E), and their interaction (GxE) term. For MY, the E component was the strongest effect, at least for models Base and PROD. When spectral kernels were used, the E component was still large with model AWN but smaller with models PC10 to PC40. The E component was almost null with model PC2. The G component was somewhat constant across models, with a slight inflation when the E component was smaller, suggesting some tradeoff between the two effects. The GxE component was mostly small, with the exception of the PROD and PC models. For SCS, the E component was smaller in magnitude but followed the same pattern, with the exception of the PROD model, which showed low estimates. The G component was constantly larger than the E component. The GxE component was still small but larger in proportion to the other two components, especially for model PROD. Model Base considered the E component as a random uncorrelated effect; therefore, the solutions for the HYS classes were assumed to be independent and without constraints. This model showed the largest estimates of environmental variance across both traits. For MY, model PROD showed similar E estimates, suggesting that the two covariates (BLUE for MY and SCS) describe the whole variation among herds. For SCS, model PROD showed lower E magnitude than Base, suggesting that there is environmental variation not fully captured by the two covariates. Model AWN was the spectra-enabled model that captured most of the E variance for both traits. The models that used the principal components of the WNV showed scarce ability to absorb variance, although there was an increase in variance absorbed for both traits when increasing the number of principal components used. This suggest that all the variation in the FTIR spectral data could, and should, be used for maximizing the (environmental) variance explained by the model. The GxE component was small as expected. Still, it absorbed ~4% and ~3% of the variance for MY and SCS, respectively, under model PROD. Other models showed lower estimates of the GxE components. 3.3. Cross-Validation, without the Inclusion of the GxE Interaction Term Results for the three cross-validation scenarios (Figure 1) are reported in the lower panels of Figure 3 and Figure 4 for MY and SCS, respectively. Dots represent the average predictive ability across the twenty replicates; error bars report the standard deviation of the prediction accuracy across the replicates. The black dots (and bars) refer to the models that included the G and E terms, the blue dots (and bars) refer to the models that included the G, E and GxE terms. The model Base included the E term as an uncorrelated random effect (no Kernel included); therefore, the interaction term could not be fitted. The section B reports a scenario where information from ‘known’ sires is predicted under new environments. Here, the model that used an uncorrelated random effect (Base) to fit the E component underperformed compared to models that included environmental covariates. For MY, the predictive ability for the Base model was 0.20, while models PROD showed 0.75, followed by models AWN with 0.50. The rest of the models showed lower predictive ability, still larger than Base. Only model PC2 showed comparable performance to the Base model. For SCS, again, all covariate-based models performed better than the Base model (0.24), but with smaller margin. The best-performing models were AWN and PROD (0.29 and 0.30, respectively). PC again showed comparable performance to Base. Section C reports a scenario comparable to genomic selection, with the information from new sires being predicted under known environments. For both traits, only model PROD was able to outperform model Base (0.68 vs. 0.61 for MY, 0.25 vs. 0.16 for SCS). All other models underperformed model Base, with PC2 showing the worst performance. Section D reports genomic prediction results achieved for new sires into new environments. The two traits showed a different pattern. For MY, all models outperformed Base, which has null (~0.0) prediction accuracy. The best performing model was again PROD, followed by AWN. PC2 was again the lowest performing covariate-informed model (0.10). For SCS, smaller differences were found between models, but some models outperformed Base (0.13). PROD was again the best performing model (0.24), followed by AWN. All other models performed similarly to Base. 3.4. Cross-Validation, with the Inclusion of the GxE Interaction Term All models that included the GxE interaction term performed equally, if not slightly worse, than the respective model without the term. This could be a reflection of the small magnitude of the estimated GxE effect. 4. Discussion 4.1. Spectral Information in a Precision Livestock Farming Framework The field of phenomics is rapidly gaining attention, appearing promising for the non-finite nature of the phenomes as opposed, for example, to the genomes [14]. Milk spectral data have already been used for decades yet remain an important source of information at the commercial level. The literature on the use of milk spectral data for predicting phenotypes of interest is vast. Using spectral data, while some traits can be better predicted than others, lately, the interest has shifted towards the integration of spectral and genomic information. In its simplest implementation, spectral-predicted phenotypes can be included in multi-variate models together with the wet-lab measured phenotype of interest [35,36]. This has shown some improvement in predictive ability, although such improvement largely depends on the trait and the quality of the spectral calibration equations. In different implementations, these two sources of data have been successfully integrated in the same models for the prediction of both fat and protein composition [37,38], where both genomic markers and spectral information served as predictors. The difference between the methods proposed in the other studies [37,38], and this study resides in the fact that, here, spectral information was only used for its environmental component. Although the comparison was not made in a straightforward manner, the two approaches serve different purposes. We opted for using only the environmental component of the spectrum for the assumptions that (i) the genomic markers would absorb the genetic component and (ii) the explicit purpose of modeling environmental variation. In addition, the modeling of the GxE component would have been hampered by the presence of genetic variation in the spectral data [12,18]. 4.2. Variance Decomposition of Spectral Data This study took advantage of a large dataset that included productive records but also spectral data. To the authors’ best knowledge, this study has used the largest spectral dataset for variance components estimation up to date. The first step in this study involved extracting the environmental variation from the spectral data. The estimates of heritability for all the spectral wavenumbers show a similar pattern as found in previous research. Both Rovere et al. [23], who worked on a subset of this dataset, and Wang and Bovenhuis [37], who worked on a different dataset, found the same pattern for heritability across the spectral variables. 4.3. Spectral Information as Environmental Covariate Based on results from the present study, the environmental component of mid-infrared spectra could be used as covariate in genomic prediction models. The estimation of variance components for MY and SCS using Kernel regression shows promising results, with a sizable and constant genetic component and different contribution of the environmental kernel depending on the covariates used. Model PROD, which uses the BLUEs of the traits themselves as covariates, shows the largest estimation of variance for MY, but spectral information shows larger estimates for SCS. These results could be due to the fact that SCS shows little HYS variation per se (0.08), which reflects the inability of the MY/SCS BLUE estimates to represent that environmental variation. Conversely, the AWN model was able to capture more environmental variation for SCS. The approach used in this study for the use of spectral information in genomic prediction models is similar to the one used by Krause et al. [18], who used hyperspectral information (based on reflectance) of wheat canopy to inform prediction models. In that study, an effort to integrate genomic and spectral information into the same model was carried out: the environmental variation for a given genotype in a given site-year was extracted in order to remove the collinearity between the genomic and spectral covariates, which makes it even more similar to this study. Wheat canopy, just like milk composition, is determined by both genetic and environmental effects, so that the same statistical methods can be applied to pursue the improvement of genomic prediction models. 4.4. Genomic Predictions across Environments This study used solely milk yield and somatic cell score as phenotypes of interest. Other routinely recorded traits, such as fat and protein percentage, could not be used because they are nowadays predicted using infrared spectroscopy [39], which would have led to an inherent collinearity between the phenotype and the spectral predictors. Although the relevance of such traits is acknowledged, we could not proceed with the analysis of those traits for this reason. The results from the cross-validation are different depending on the scenario, as expected. Predictions based on spectral data have been found to provide dramatically different results based on how the training and validation sets were created. Wang and Bovenhuis [37] reported that across-herd predictions of bovine methane emissions showed much lower accuracy than within-herd predictions. Dadousis et al. [40], in predicting goat milk coagulation traits, showed that model predictive ability depended largely on the farm(s) included in the validation set. In prediction scenario C, to be considered equivalent to a common genomic selection scenario, none of the environmental covariates provided meaningful contribution to the predictive ability of the models. Such covariates appear as non-informative when predictions are drawn to known environments, i.e., there is no need to extrapolate to ‘new’ environmental conditions. In scenario B, where predictions for the ‘known’ genotypes were extrapolated to new environments, PROD was the best-performing model, with stronger advantage over Base for MY. Unfortunately, model PROD is unrealistic and should only be used for comparison, as an upper bound that the environmental-covariate-informed model could reach. In order to implement model PROD, phenotypes for the ‘new’ environments need to be measured in order to obtain the best linear unbiased estimates for the same environments. If phenotypes are available for these environments, predictions are then not needed, which totally defeats the purpose of predicting the performance in such environments. Spectral information seems promising in providing environmental coordinates for the ‘new’ environments. Model AWN did not outperform model PROD but did outperform model Base in scenarios B and D. Especially in the latter, where predictions for new genotypes are extrapolated to new environments, there was a large advantage of model AWN over model Base, indicating the need to inform the prediction models with environmental covariates but also the opportunity in using the spectral data as sources of environmental variation. 4.5. The Dimensionality of Milk Spectral Data as Environmental Descriptors In this study, we also attempted to reduce the dimensionality of the spectral data by using the most relevant principal components to build the environmental kernel. The use of the principal components did not seem to provide any advantage. Yet, it appears that a number of components larger than 40 would be needed to fulfill the potential of the spectral data to absorb phenotypic variance or predict across environments. In fact, the first 40 principal components only explained about 65% of the total spectral variation, which was made up of 3316 HYS classes. 5. Conclusions The present study showed a simple procedure to include the environmental component of the spectral information into genomic predictions models as a set of covariates using Kernel regression. The results showed that this method was particularly advantageous when genomic predictions for new genotypes under new environmental conditions have to be obtained. Fourier-transformed infrared spectral data represent a useful source of information for the calculation of the ‘environmental coordinates’ of a given farm in a given time. Farming conditions are evolving, and livestock will be subject to new environmental conditions. Genomic prediction models could take advantage of environmental information in order to extrapolate candidates’ performance to new environments. In general, the goal is to link the different environmental blocks (e.g., herds, herd-year-season classes) using some function that could be reflective of their management strategies or general environmental conditions. The herds are no longer considered independent but are assumed to be connected based on the covariates used. Because of this connection between the herds, a practical implementation of this method could be to obtain FTIR-derived coordinates for each new herd season. These coordinates would then be used in a second genomic prediction model such as the one used in this study. For any trait of interest, the model would yield genomic predictions for new herd seasons based on the genomic information and the FTIR-derived coordinates. This approach could be particularly advantageous in presence of a large genotype by environment component, which was not detected in this study. Part of this reason could be the limited number of models tested, since the study was oriented towards the use of the spectral data rather than the estimation of this component. Suggesting a different use of spectral information, this study is an example of the integration of genomic and phenomic data. With the proposed procedure, calibration equations are not needed because only the environmental component of the spectral variables is used. This could help using spectral data for traits that present poor predictability at the phenotypic level, such as disease incidence and behavioral phenotypes. Further research should focus on the reduced computational challenge of incorporating the spectral data. Acknowledgments The authors want to thank the other collaborators at Lactanet Canada and The Semex Alliance for sharing their data and make this study possible. Author Contributions F.T., A.F. and F.M. conceived the study. F.T. designed the experiment performed the statistical analysis and wrote the manuscript. A.F. and F.M. contributed to interpretation of the results. All authors contributed to manuscript review and editing. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical review and approval were waived for this study due to the use of data that were already collected. The data were collected under routine data recording. Informed Consent Statement Not applicable. Data Availability Statement Data are property of Lactanet Canada, The Semex Alliance and the individual dairy producers. Data may available under a research agreement. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Cross-validation scheme for combinations of genotypes (sires) and environments (herds) to be included in the validation sets. Sires 1 to 10 are considered known or proven. Herds 1 to 4 are considered known environments. Phenotypic information belonging to sires 1 to 10 and herds 1 to 4 could be considered a training set and labeled as section (A). The performance of known sires could be extrapolated to new herds (5 and 6); this would correspond to section (B), i.e., known genotypes in new environments. Conversely, prediction of new sires’ performance (11 to 16) in known herds corresponds to section (C). Finally, the most challenging scenario would be to predict the performance of new sires in new herds, i.e., section (D). Figure 2 Heritability and repeatability for each of the 1060 wavenumbers used in the study. The solid blue and red lines report the heritability and repeatability estimates for milk yield, while the dashed lines report the same parameter estimates for somatic cell score. Each wavenumber refers to a specific wavelength in the infra-red range of the spectrum and show a discontinuous numbering that goes from 5010 to 925 cm−1. Figure 3 Proportion of variance components explained by the additive genetic effect (G), environmental effect (E) and their interaction (GxE) term, together with predictive ability of the respective models under the different scenarios for milk yield (MY). The black dots (and bars) refer to the models that included the G and E terms; the blue dots (and bars) refer to the models that included the G, E, and GxE terms. Figure 4 Proportion of variance components explained by the additive genetic effect (G), environmental effect (E), and their interaction (GxE) term, together with predictive ability of the respective models under the different scenarios for somatic cell score (SCS). The black dots (and bars) refer to the models that included the G and E terms, the blue dots (and bars) refer to the models that included the G, E, and GxE terms. animals-12-01189-t001_Table 1 Table 1 Descriptive statistics for the datasets including test-day records and used in the study. Data1full Data1reduced Number of records 1,540,935 571,440 Number of cows 84,131 29,057 Numbers of sires 5759 3540 Number of dams 69,665 23,523 Number of individuals in pedigree 419,586 177,916 Number of herds 768 214 Number of herd-year-season classes 28,222 9766 Milk Yield, kg 35.66 (10.36) 35.47 (10.42) Somatic Cell Score 2.36 (1.92) 2.38 (1.92) animals-12-01189-t002_Table 2 Table 2 Descriptive statistics for the datasets including herd-year-season daughter-yield-deviations. Data2 Number of sire-herd-year-season classes 16,891 Minimum EDC 1 per class 1.60 Average EDC 1 per class 2.9 Maximum EDC 1 per class 29.9 Number of herd-year-season classes 3316 Minimum frequency per hys class 3 Average frequency per hys class 5.1 Maximum frequency per hys class 29 Numbers of sires 483 Minimum frequency per sire 3 Average frequency per sire 35.0 Maximum frequency per sire 781 Number of herds 406 Minimum frequency of HYS per herd 3 Average frequency of HYS per herd 8.2 Maximum frequency of HYS per herd 25 1 EDC: effective daughter contribution. animals-12-01189-t003_Table 3 Table 3 List and definition of the environmental covariates as they were used in the 8 models. Model Definition of Environmental Covariates BASE Uncorrelated HYS classes. AWN Covariance based on the 1060 WVN 1. PC2 Covariance based on the first 2 principal components of the 1060 WVN. PC10 Covariance based on the first 10 principal components of the 1060 WVN. PC20 Covariance based on the first 20 principal components of the 1060 WVN. PC30 Covariance based on the first 30 principal components of the 1060 WVN. PC40 Covariance based on the first 40 principal components of the 1060 WVN. PROD Covariance based on MY and SCS. 1 WVN: Fourier-transformed infrared wavenumber. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Mulder H.A. Bijma P. Effects of genotype× environment interaction on genetic gain in breeding programs J. Anim. Sci. 2005 83 49 61 10.2527/2005.83149x 15583042 2. Mulder H.A. Bijma P. Hill W.G. Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance Genetics 2007 175 1895 1910 10.1534/genetics.106.063743 17277375 3. Gauly M. Bollwein H. Breves G. Brügemann K. Dänicke S. Daş G. Wrenzycki C. Future consequences and challenges for dairy cow production systems arising from climate change in Central Europe—A review Animal 2013 7 843 859 10.1017/S1751731112002352 23253935 4. Kipling R.P. Bannink A. Bellocchi G. Dalgaard T. Fox N.J. Hutchings N.J. Scollan N.D. Modeling European ruminant production systems: Facing the challenges of climate change Agri. Syst. 2016 147 24 37 10.1016/j.agsy.2016.05.007 5. Nardone A. Ronchi B. Lacetera N. Ranieri M.S. Bernabucci U. Effects of climate changes on animal production and sustainability of livestock systems Livest. Sci. 2010 130 57 69 10.1016/j.livsci.2010.02.011 6. Das R. Sailo L. Verma N. Bharti P. Saikia J. Impact of heat stress on health and performance of dairy animals: A review Vet. World 2016 9 260 10.14202/vetworld.2016.260-268 27057109 7. Jarquín D. Crossa J. Lacaze X. Du Cheyron P. Daucourt J. Lorgeou J. de los Campos G. A reaction norm model for genomic selection using high-dimensional genomic and environmental data Theor. Appl. Genet. 2014 127 595 607 10.1007/s00122-013-2243-1 24337101 8. Crossa J. de los Campos G. Maccaferri M. Tuberosa R. Burgueño J. Pérez-Rodríguez P. Extending the marker× environment interaction model for genomic-enabled prediction and genome-wide association analysis in durum wheat Crop Sci. 2016 56 2193 2209 10.2135/cropsci2015.04.0260 9. Tiezzi F. de Los Campos G. Gaddis K.P. Maltecca C. Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle J. Dairy Sci. 2017 100 2042 2056 10.3168/jds.2016-11543 28109596 10. Cuyabano B.C.D. Rovere G. Lim D. Kim L.H.K. Lee S.H. Gondro C. GPS Coordinates for Modelling Correlated Herd Effects in Genomic Prediction Models Applied to Hanwoo Beef Cattle Animals 2021 11 2050 10.3390/ani11072050 34359178 11. Selle M.L. Steinsland I. Powell O. Hickey J.M. Gorjanc G. Spatial modelling improves genetic evaluation in smallholder breeding programs Genet. Sel. Evol. 2020 52 69 10.1186/s12711-020-00588-w 33198636 12. Silva F.F. Mulder H.A. Knol E.F. Lopes M.S. Guimarães SE F. Lopes P.S. Bastiaansen J.W.M. Sire evaluation for total number born in pigs using a genomic reaction norms approach J. Anim. Sci. 2014 92 3825 3834 10.2527/jas.2013-6486 24492557 13. Chen S.Y. Freitas P.H. Oliveira H.R. Lázaro S.F. Huang Y.J. Howard J.T. Brito L.F. Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms Genet. Sel. Evol. 2021 53 51 10.1186/s12711-021-00645-y 34139991 14. Pérez-Enciso M. Steibel J.P. Phenomes: The current frontier in animal breeding Genet. Sel. Evol. 2021 53 22 10.1186/s12711-021-00618-1 33673800 15. Gengler N. Soyeurt H. Interest, recording and possible use of new phenotypes from fine milk composition Proceedings of the 9th World Congress of Genetics Applied to Livestock Production Leipzig, Germany 1–6 August 2010 16. Belay T.K. Dagnachew B.S. Boison S.A. Ådnøy T. Prediction accuracy of direct and indirect approaches, and their relationships with prediction ability of calibration models J. Dairy Sci. 2018 101 6174 6189 10.3168/jds.2017-13322 29605329 17. Bonfatti V. Vicario D. Degano L. Lugo A. Carnier P. Comparison between direct and indirect methods for exploiting Fourier transform spectral information in estimation of breeding values for fine composition and technological properties of milk J. Dairy Sci. 2017 100 2057 2067 10.3168/jds.2016-11951 28109603 18. Krause M.R. González-Pérez L. Crossa J. Pérez-Rodríguez P. Montesinos-López O. Singh R.P. Mondal S. Hyperspectral reflectance-derived relationship matrices for genomic prediction of grain yield in wheat G3 Genes Genomes Genet. 2019 9 1231 1247 10.1534/g3.118.200856 19. Valenti B. Martin B. Andueza D. Leroux C. Labonne C. Lahalle F. Ferlay A. Infrared spectroscopic methods for the discrimination of cows′ milk according to the feeding system, cow breed and altitude of the dairy farm Int. Dairy J. 2013 32 26 32 10.1016/j.idairyj.2013.02.014 20. Molle G. Cabiddu A. Decandia M. Sitzia M. Ibba I. Giovanetti V. Caredda M. Can FT-Mid-Infrared Spectroscopy of Milk Samples Discriminate Different Dietary Regimens of Sheep Grazing With Restricted Access Time? Front. Vet. Sci. 2021 8 211 10.3389/fvets.2021.623823 21. Denholm S.J. Brand W. Mitchell A.P. Wells A.T. Krzyzelewski T. Smith S.L. Wall E. Coffey M.P. Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning J. Dairy Sci. 2020 103 9355 9367 10.3168/jds.2020-18328 32828515 22. Ho P.N. Luke T.D.W. Pryce J.E. Validation of milk mid-infrared spectroscopy for predicting the metabolic status of lactating dairy cows in Australia J. Dairy Sci. 2021 104 4467 4477 10.3168/jds.2020-19603 33551158 23. Rovere G. de Los Campos G. Tempelman R.J. Vazquez A.I. Miglior F. Schenkel F. Fleming A. A landscape of the heritability of Fourier-transform infrared spectral wavelengths of milk samples by parity and lactation stage in Holstein cows J. Dairy Sci. 2019 102 1354 1363 10.3168/jds.2018-15109 30580946 24. Misztal I. Aguilar I. Legarra A. Vitezica Z. Manual for BLUPF90 Family of Programs 2015 Available online: http://nce.ads.uga.edu/wiki/lib/exe/fetch.php?media=blupf90_all7.pdf (accessed on 18 February 2022) 25. Plummer M. Best N. Cowles K. Vines K. CODA: Convergence diagnosis and output analysis for MCMC R News 2006 6 7 11 26. Misztal I. Tsuruta S. Strabel T. Auvray B. Druet T. Lee D.H. BLUPF90 and related programs (BGF90) Proceedings of the 7th World Congress on Genetics Applied to Livestock Production Montpellier, France 19–23 August 2002 743 744 27. R Development Core Team R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing Vienna, Austria 2013 Available online: https://www.R-project.org/ (accessed on 18 February 2022) 28. Fikse W.F. Banos G. Weighting factors of sire daughter information in international genetic evaluations J. Dairy Sci. 2001 84 1759 1767 10.3168/jds.S0022-0302(01)74611-5 11467826 29. VanRaden P.M. Efficient methods to compute genomic predictions J. Dairy Sci. 2008 91 4414 4423 10.3168/jds.2007-0980 18946147 30. Aguilar I. Misztal I. Johnson D.L. Legarra A. Tsuruta S. Lawlor T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score J. Dairy Sci. 2010 93 743 752 10.3168/jds.2009-2730 20105546 31. De los Campos G. Gianola D. Rosa G.J. Reproducing kernel Hilbert spaces regression: A general framework for genetic evaluation J. Anim. Sci. 2009 87 1883 1887 10.2527/jas.2008-1259 19213705 32. Morota G. Gianola D. Kernel-based whole-genome prediction of complex traits: A review Front. Genet. 2014 5 363 10.3389/fgene.2014.00363 25360145 33. Pérez P. de Los Campos G. Genome-wide regression and prediction with the BGLR statistical package Genetics 2014 198 483 495 10.1534/genetics.114.164442 25009151 34. Janss L. de Los Campos G. Sheehan N. Sorensen D. Inferences from genomic models in stratified populations Genetics 2012 192 693 704 10.1534/genetics.112.141143 22813891 35. Cecchinato A. Toledo-Alvarado H. Pegolo S. Rossoni A. Santus E. Maltecca C. Tiezzi F. Integration of Wet-Lab Measures, Milk Infrared Spectra, and Genomics to Improve Difficult-to-Measure Traits in Dairy Cattle Populations Front. Genet. 2020 11 1131 10.3389/fgene.2020.563393 33133149 36. Van den Berg I. Ho P.N. Luke TD W. Haile-Mariam M. Bolormaa S. Pryce J.E. The use of milk mid-infrared spectroscopy to improve genomic prediction accuracy of serum biomarkers J. Dairy Sci. 2021 104 2008 2017 10.3168/jds.2020-19468 33358169 37. Wang Q. Bovenhuis H. Combined use of milk infrared spectra and genotypes can improve prediction of milk fat composition J. Dairy Sci. 2020 103 2514 2522 10.3168/jds.2019-16784 31882213 38. Baba T. Pegolo S. Mota L.F. Peñagaricano F. Bittante G. Cecchinato A. Morota G. Integrating genomic and infrared spectral data improves the prediction of milk protein composition in dairy cattle Gen. Sel. Evol. 2021 53 29 10.1186/s12711-021-00620-7 39. Luinge H.J. Hop E. Lutz ET G. Van Hemert J.A. De Jong EA M. Determination of the fat, protein and lactose content of milk using Fourier transform infrared spectrometry Anal. Chim. Acta 1993 284 419 433 10.1016/0003-2670(93)85328-H 40. Dadousis C. Cipolat-Gotet C. Stocco G. Ferragina A. Dettori M.L. Pazzola M. Vacca G.M. Goat farm variability affects milk Fourier-transform infrared spectra used for predicting coagulation properties J. Dairy Sci. 2021 104 3927 3935 10.3168/jds.2020-19587 33589253

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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092698 molecules-27-02698 Review An Insight into All Tested Small Molecules against Fusarium oxysporum f. sp. Albedinis: A Comparative Review Kaddouri Yassine 1 Benabbes Redouane 2 Ouahhoud Sabir 2 https://orcid.org/0000-0002-8562-4749 Abdellattif Magda 3* https://orcid.org/0000-0003-3673-7904 Hammouti Belkheir 4 https://orcid.org/0000-0001-7333-697X Touzani Rachid 4* Amato Jussara Academic Editor 1 Laboratory of Inorganic Chemistry, Department of Chemistry, University of Helsinki, P.O. Box 55, FI-00014 Helsinki, Finland; y.kaddouri@ump.ac.ma 2 Laboratoire de Bioressources, Biotechnologie, Ethnopharmacologie et Santé (LBBES), Department of Biology, Faculty of Sciences, University Mohamed Premier, Oujda 11022, Morocco; red.bes72@gmail.com (R.B.); ouhaddouch@yahoo.fr (S.O.) 3 Chemistry Department, College of Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia 4 Laboratory of Applied Chemistry and Environment (LCAE), Faculty of Sciences, University Mohammed Premier, Oujda 11022, Morocco; hammoutib@gmail.com * Correspondence: m.hasan@tu.edu.sa (M.A.); r.touzani@ump.ac.ma (R.T.) 22 4 2022 5 2022 27 9 269806 2 2022 18 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Bayoud disease affects date palms in North Africa and the Middle East, and many researchers have used various methods to fight it. One of those methods is the chemical use of synthetic compounds, which raises questions centred around the compounds and common features used to prepare targeted molecules. In this review, 100 compounds of tested small molecules, collected from 2002 to 2022 in Web of Sciences, were divided into ten different classes against the main cause of Bayoud disease pathogen Fusarium oxysporum f. sp. albedinis (F.o.a.) with structure–activity relationship (SAR) interpretations for pharmacophore site predictions as (δ−···δ−), where 12 compounds are the most efficient (one compound from each group). The compounds, i.e., (Z)-1-(1.5-Dimethyl-1H-pyrazole-3-yl)-3-hydroxy but-2-en-1-one 7, (Z)-3-(phenyl)-1-(1,5-dimethyl-1H-pyrazole-3-yl)-3-hydroxyprop-2-en-1-one 23, (Z)-1-(1,5-Dimethyl-1H-pyrazole-3-yl)-3-hydroxy-3-(pyridine-2-yl)prop-2-en-1-one 29, and 2,3-bis-[(2-hydroxy-2-phenyl)ethenyl]-6-nitro-quinoxaline 61, have antifungal pharmacophore sites (δ−···δ−) in common in N1---O4, whereas other compounds have only one δ− pharmacophore site pushed by the donor effect of the substituents on the phenyl rings. This specificity interferes in the biological activity against F.o.a. Further understanding of mechanistic drug–target interactions on this subject is currently underway. pyrazole imidazole B-keto-enol amino acid quinoxaline Bayoud Fusarium oxysporum f. sp. albedinis ==== Body pmc1. Introduction Bayoud disease [1,2,3,4,5], caused by the telluric fungus pathogen Fusarium oxysporum f. sp. albedinis (F.o.a) [6,7,8,9], represents the leading dangerous agent of date palms cultivation, having killed more than 15 million Moroccan and Algerian date palm trees. Fungal infection causes significant implications, threatening date palms with high morbidity and mortality every year worldwide. Therefore, new antifungal inhibitors must be discovered urgently, especially those with new modes of action, low toxicity, and bioavailability, and are effective for responsive and drug-resistant fungi [10,11,12,13,14,15]. Due to their biological activity and chemical properties in recent years, fused heterocyclic compounds containing bridgehead nitrogen or oxygen donor atoms have drawn further interest. Indeed, several classes are reported in this review as pyrazole- and imidazole-based derivatives [16] presented in different biomolecules, such as histidine [17], histamine [18], and natural products [19]; this is an exciting building block [20]. Specifically, in recent decades, 4,5-diarylpyrazoles [21] and 2,5-diarylimidazoles [22] have gained interesting recognition as possible biomolecules in the field of drug development. Many biological and pharmacological properties are related to these structures [23]. βKeto-enol compounds [24,25,26,27] are found in many natural products as coumarin derivatives and play an important role in medicine and in the development of coordination chemistry as stable complexes. Imidazothiazole derivatives [28,29,30] are attractive nitrogen-containing heterocyclic ring-like histidine, biotin, nucleic acid, purine, etc., and have a broad spectrum of biological and pharmacological diverse activities. Pyrazolic compounds [31] have established widespread potential biological activities, such as anti-inflammatory [32,33,34], antianxiety [35], antipyretic [36], antimicrobial [37,38,39,40], antiviral [41], antitumor [42,43,44], anticonvulsant [36,45,46,47], etc. Quinoxalines [48] are polyfunctionalized compounds with interesting biological activities, such as anti-human immunodeficiency virus (anti-HIV) and antidiabetic agents. Benzimidazole-1,2,3-triazole hybrid molecules [49] are hybrid compounds consisting of benzimidazole and 1,2,3-triazole, where both of them have a broad range of biological activities. N,N′-bipyrazole piperazine derivatives [50] are established as polypharmacological mixed ligands with several biological activities reported in the literature [51,52,53,54]. Meanwhile, Schiff base derivatives [53] have different biological functions, such as anti-inflammatory [55], antifungal [56], and antibacterial effects [57], and are commonly used as carriers of catalysts [58], optical chemical receptors [59], thermo-stable products [60], agents of metal complexion [61], inhibitors of corrosion [62], and stabilizers of polymers [63]. 2. Pyrazole- and Imidazole-Based Derivatives After some modifications, the agar diffusion approach is used for the antifungal analysis of pyrazole- and imidazole-based derivatives. In short, after isolation and preparation of the Fusarium fungus, the sterilized solution of the six compounds tested (1–6) in dimethyl sulfoxide (DMSO) is mixed with the potato dextrose agar (PDA) medium as an emulsifier at different concentrations using the method mentioned in the literature [16]. These compounds were synthesized by Takfaoui et al. using direct diarylation of pyrazoles and imidazoles with aryl halides, using palladium as the catalyst, DMAc as the solvent, and CsOAc as the base [64,65]. Using a non-linear regression algorithm curve of the concentration/percentage of inhibition, the half-maximal inhibitory concentration (IC50) was measured using Graphpad Prism software. DMSO-distilled water mixture was used as the negative control; no recognized antibiotic can specifically treat this infection. The IC50 values are given in (Table 1) below. In the pyrazole derivatives, compound 4 (IC50 = 99.1 μg/mL) has the best fungus inhibition of all the tested compounds, where it contains p-C6H4 groups on the phenyl rings as an electron-donating character, and the high toxicity effect of the phenyl groups on the F.o.a. Furthermore, compound 1 (IC50 = 110.9 μg/mL), presenting m-CF3 groups on both phenyl rings, displays good activity close to that of compound 4. However, the following compound is from the imidazole series (compound 5) containing p-Cl groups on phenyl rings with an IC50 value equal to 114.7 μg/mL. The substitution of the phenyl rings by formyl (COH) groups (compound 6) is highly unfavorable for inhibitory potency [16]. 3. β-Keto-enol Derivatives a β-Keto-enol Pyridine and Furan Derivatives Using the agar diffusion process, we determined the in vitro antifungal ability of 11 compounds (7–17) against the pathogenic fungus (F.o.a). The synthetic route of the target compounds (7–17) was carried out following Claisen condensation under mild conditions [24,26,67,68,69,70,71,72,73,74]. Using the protocol described in the literature [27], the percentages of inhibition and semi-maximal inhibitory concentration (IC50) were measured and estimated using the inhibition percentage non-linear regression equation, while benomyl was used as a positive control (Table 2). As presented in Table 2, the fungal activity of 7 is very substantial, though it decreases slightly in the case of 10 because of ethoxy phenyl groups, which commonly have pharmacophore sites (δ−···δ+), as presented in Figure 1, due to their physicochemical properties and their ability to penetrate the envelope of fungal cells and enter their cellular place of action, thus displaying more excellent activity in [27]. b (Z)-3(3-bromophenyl)-1-(1,5-dimethyl-1H-pyrazol-3yl)-3-hydroxyprop-2-en-1-one derivatives The agar diffusion technique was tested for in vitro antifungal function (ADT), where the literature reported the protocol details [7]. The optical density values were measured for each culture at 625 nm, and the inhibition percentage (%) is expressed as (D0 − Dx)/D0 × 100. D0 is the diameter of the mycelial growth of the culture witness, and Dx is the diameter of the mycelial growth (Table 3). The target biomolecules 18–23 based on βketo-enol and pyrazole entities and pyridine were prepared using a one-pot in situ condensation method, similar to the procedures in the literature [24]. As presented in Table 3, only compounds 22 and 23 reach values close to the standard (benomyl), as they belong to the same family. Such variations depend on the radical group attached to the fragment of pyrazole keto-enol, where compound 23 has a phenyl ring attached instead of the methyl group in compound 22. In addition, numerous molecular improvements are currently being made to these compounds as antifungal candidates [25]. c β-Keto-enol pyrazolic compounds The in vitro antifungal potential of ten prepared βKeto-enol pyrazolic compounds against the pathogen F.o.a was determined by the agar diffusion technique reported in the literature [26], and the half-maximal inhibitory concentration (IC50) was determined using a non-linear regression algorithm of the concentration-inhibition percentage graph, with benomyl used as a positive control. In addition, the target biomolecules 24–30 based on βketo-enol and pyrazole entities were prepared by a one-pot in situ condensation method, which is similar to the procedures given in the literature [24]. On the other hand, most of these molecules demonstrate potent antifungal action against F.o.a, as seen in Table 4. These were based on the structure–activity relationships (S.A.R.s). Where a stimulating effect is exerted against F.o.a of the substitution pattern, we found compound 28 in the 3-thiophene group. In contrast, compound 30 with the 2-naphthalene group led the same inhibition percentage of 94% as the benomyl fungicide, while the best antifungal activity was found for compound 29 containing the 2-pyridine group IC50 of 60.84 μg/m. The existence of the R substituent should be further exploited [8] to evaluate the S.A.R.s for this novel class of antifungal agents. 4. Imidazothiazole Derivatives The synthesis of various types of imidazothiazoles 31–35 is potentially helpful for developing biologically active heterocycles. The synthetic methods are practical and straightforward and are conceivably applicable to analogous heterocyclic systems possessing nitrogen and sulfur [30,75,76,77,78,79,80,81,82]. The antifungal action of five imidazothiazole derivatives 31–35 is carried out on an F.o.a using the concentrations C1, C2, C3, C4, and C5 as 5.0, 1.0, 0.2, 0.05, and 0.01 mg/mL, respectively. Each compound was prepared at various concentrations in the potato dextrose agar (PDA) before the fungus was cultured using the protocol described in the literature [28]. The IC50 was calculated using the linear regression equation between the normal logarithm concentrations and growth inhibition percentages. From Table 5, the antifungal test of the five imidazothiazole derivatives tested against F.o.a. at five different concentrations acted differently, while all the molecules showed interesting results. Indeed, the best antifungal activity is found for compound 33 due to three methyl substituents on the ortho and para positions of the phenyl ring with IC50 not exceeding 20.00 μg/mL [28]. 5. Pyrazolic Compounds Monopyrazolic heterocyclic compounds 36–55 were prepared in excellent yields by condensing one equivalent of hydroxymethylpyrazole with one equivalent of primary amines [83,84,85]. The antifungal behavior, as defined in the literature, was calculated by the agar diffusion technique [31], with the linear regression equation between the normal logarithm of the concentrations and the growth inhibition percentages calculated at the half-maximal inhibitory concentration (IC50). The pyrazolic derivatives 50, 51, and 53–55 were screened in vitro for their antifungal potential against F.o.a and collected in Table 6, where compounds 50 and 55 showed an excellent efficacy of IC50 = 86 μM and 168 μM, respectively, arguably due to the presence of the two phenyl moieties. Due to the (-Br) group, which is an essential source of electronegativity, compound 53 showed a moderate potential with an IC50 = 284 μM. The two other pyrazoles tested demonstrated low antifungal function [31]. 6. Quinoxalines A variety of 2,3-bifunctionalized quinoxalines (56–61) have been prepared by the condensation of 1,6-disubstituted-hexan-1,3,4,6-tetraones with o-phenylenediamine, (R,R)-1,2-diaminocyclohexane, and p-nitro-o-phenylenediamine [86,87,88]. The antifungal activity of six prepared quinoxaline compounds’ antifungal activity was measured against F.o.a, as described in the method in the literature [48]. Based on Table 7, the most effective inhibitor is nitroquinoxaline 61, which produces 51% inhibition of the growth of Fusarium at a concentration of 72 mg/L due to its small nitro groups that disturb the cell membrane, with some intracellular target and electron-withdrawing solid group. At the same time, compounds 56, 60, and 59 are less effective but produce appreciable growth inhibition at comparable concentrations [48]. 7. Benzimidazole-1,2,3-triazole Hybrid Molecules A series of hybrid molecules 62–69 was prepared by condensing 4-(trimethylsilylethynyl)benzaldehyde with substituted o-phenylenediamines. These, in turn, were reacted with 2-(azidomethoxy)ethyl acetate in a Cu alkyne–azide cycloaddition (CuAAC) to generate the 1,2,3-triazole pharmacophore under microwave assistance [89,90,91,92]. The eight new benzimidazole-1,2,3-triazole hybrid molecules were tested against F.o.a using the method described in the literature [49], and their linear growth and sporulation inhibitory rates are presented in Table 8. Based on Table 8, all compounds were tested at a 20 mg/mL concentration, with Pelt, a systemic fungicide and benzimidazole precursor (70% of methyl thiophanate), as the positive control. Compound 66 shows a significantly increased rate with (17.01 and 30.62%) (p < 0.05) against F.o.a, which uniquely holds a CF3 group fixed to the benzimidazole core, a lipophilic group known to modulate absorption and metabolism, and may explain the enhanced activity [49]. 8. N,N′-Bipyrazole Piperazine Derivatives Novel bipyrazoles 70–73 possessing piperazine or a mimed piperazine ring spacer were prepared in a one-step reaction in excellent yields. First, it condensed two hydroxymethylpyrazole derivatives with one equivalent of cyclic and acyclic piperazine [93,94,95,96]. As stated in the literature, in vitro antibacterial and antifungal activity is tested by the agar diffusion technique [50] using pathogenic strains of F.o.a. In contrast, streptomycin was used in the antibacterial assay as a reference compound for quality reasons. Therefore, the minimal concentration of inhibition (M.I.C.) is the lowest concentration of the tested compound that has inhibited the development of the micro-organism. As presented in Table 9, four tested compounds showed differential anti-proliferative activity against F.o.a, as the best M.I.C. value was found for compound 71 of 5 μg/mL. These results are explained by the piperazine ring spacer and the carboxylate moiety at the three-position of the pyrazole rings that considerably increases the antifungal activity [50]. 9. Bipyrazolic Tripodal Derivatives A series of novel bipyrazolic tripodal derivatives 74–81 was prepared in one step, with good and excellent yields. Then, one equivalent of the appropriate amine derivatives was added to a solution of two equivalents of the substituted hydroxymethylpyrazole in acetonitrile, and the mixture was continued under stirring at room temperature for 4–5 days. Finally, the crude material was evaporated, washed with water and CH2Cl2, and purified by silica gel column flash chromatography to give the target product 74–81 [52]. The eight compounds containing bipyrazolic tripod derivatives are tested in vitro for their efficacy against Fusarium oxysporum f. Isolated from a date palm with vascular fusariosis, F.o.a was used as the protocol described in the literature [52]. The minimum inhibition concentration (M.I.C.) is the lowest dose of the compound that can inhibit micro-organism development. From data in Table 10, the presence of the methyl as electron donor groups on the pyrazole rings increased the antifungal activity for compounds 74, 76, 78, and 80, but has a counter effect on the phenyl ring, e.g., in the case of compounds 80 and 81 which have M.I.C. values of 40 and 80 μg/mL, respectively. Additionally, nitro substituent as an electron-withdrawing group for compound 79 increased its effect compared with compound 77 [52]. 10. Schiff Base Derivatives Twelve new Schiff base derivatives are prepared using the condensation reaction of different amino-substituted compounds (such as aniline, pyridine-2-amine, o-toluidine, 2-nitrobenzenamine, 4-aminophenol, and 3-aminopropanol) and substituted aldehydes (such as nicotinaldehyde, o,m,p-nitrobenzaldehyde, and picolinaldehyde) in ethanol with acetic acid as a catalyst [53]. The agar diffusion technique against Fusarium oxysporum f evaluated the in vitro antifungal activities of all the new Schiff base derivative compounds, including F.o.a fungus, as described earlier [53]. In the presence of a concentration of the tested compound over the mycelium diameter of the reference culture multiplied by 100, it is found that the inhibition proportion of a molecule is proportional to the ratio of the mycelium diameter of the culture. Therefore, the minimal concentration of inhibition (M.I.C.) is the lowest dose of the compound, which inhibited the growth of the microorganism when the mixture (DMSO/EtOH + distilled water) is used as a negative control without any standard reference drug. On the contrary, based on their M.I.C. values in Table 11, the in vitro antifungal assay findings showed that most of the screened ligands exhibited high to moderate activity against F.o.a. The maximum activity was 0.02 µg/mL, shown by compound 84, followed by compounds 87, 88, and 93 with M.I.C. values equal to 0.04 µg/mL, while compound 83 showed the most negligible M.I.C. value of 0.9 µg/mL. Other products also have numerous activities, with M.I.C.s varying from 0.08 µg/mL for compound 92 to 0.30 µg/mL for compound 86. Comparing both the structures of 83 and 84, it can be inferred that the presence at the ortho position of the phenyl ring of a strong electron-withdrawing group, such as nitro moiety (NO2), is very appropriate for increasing antifungal efficiency; the presence of an electron donation group, such as methyl moiety (CH3) for antifungal action, is unfavorable in the period. Unfortunately, though, the correct variables that influence the antifungal ability of these derivatives are difficult to ascertain with these early investigations. Further investigations using other models and techniques are essential for this [53]. 11. Amino Acids Pyrazole Compounds The functional pyrazolyl derivatives 94–100 were prepared by condensing two equivalents of (3,5-dimethyl-1H-pyrazole-1-yl)methanol with one equivalent of amino acid ester hydrochloride derivatives (commercially available) in anhydrous solvents. All reactions were carried out at room temperature under stirring conditions for 4 to 6 days in an inert atmosphere [42,97,98,99,100,101,102,103,104,105,106]. The activities of the pyrazole compound amino acids and the agar techniques determined 94–100. The yeast of the F.o.a was isolated from a date palm touched by the vascular Fusarium prepared in a PDA medium at 37 g/L [54]. Based on Table 12, compared to blank culture, the inhibition rates of F.o.a development ranged from 0 to 480 mg/L for ester hydrochloride amino acids or their tripodal pyrazolic homologs. Inhibition activity against the growth of F.o.a. was shown by the various compounds studied, except 94 and 95. However, the rate of this inhibition changes from one molecule to another. Compound 98 has the best antifungal activity due to methyl substituents as electron donor groups in methyl alaninate (alanine ester) as the amino acid; these products’ structural and electronic diversity affected their biological activities. Further developments on this subject are currently in progress in order to understand their mechanistic interactions [54]. 12. Comparison Using Structure–Activity Relationship To understand this structure–activity relationship and the modes of action of these new biologically active molecules, we can carry out a theoretical study with bioinformatics molecular modeling (DFT, Docking, and ADME-Tox studies) after studying the mechanism of the reaction using conceptual DFT [107,108]. As a result, we obtained various prospective targeted drugs as inhibitors for Bayoud disease (Figure 2). As presented in Figure 2, compounds 7, 23, 29, and 61 have the antifungal pharmacophore sites (δ−···δ−) in common in N1---O4, whereas other compounds have only one δ− pharmacophore site pushed by the donor effect of the substituents on the phenyl rings; this specificity interferes in the biological activity against F.o.a. 13. Conclusions This review uses 100 compounds of tested small molecules divided into ten classes against Fusarium oxysporum f. sp. albedinis (F.o.a). First, compound 4 (IC50 = 99.1 μg/mL) has the best fungus inhibition over all the pyrazole and imidazole derivatives, containing electron-donating character as para phenyl substituents. Furthermore, it is displays high toxicity in the phenyl groups on the F.o.a. Second, from βketo-enol derivatives, compounds 7, 23, 29, and 61 have the antifungal pharmacophore sites (δ−···δ−) in common in N1---O4, whereas other compounds have only one δ− pharmacophore site pushed by the donor effect of the substituents on the phenyl rings; this specificity interferes in the biological activity against F.o.a. Moreover, these products’ structural and electronic diversity can affect their biological activities. Further developments on this subject are currently in progress to better understand their mechanistic interactions. Acknowledgments The authors thank the (ANPMA/CNRST/UMP 2020–2023 Project: Formulations fongiques, insecticide ou acaricides d’huiles essentielles des plantes aromatiques et médicinales et de leurs extraits aqueux) for their support. M.H.A expresses thanks to the Researchers Supporting Project TURSP2020/91 of Taif University, Taif, Saudi Arabia. Funding The review was funded by ANPMA/CNRST/UMP 2020–2023 Project, and Taif University Researchers Supporting Project TURSP2020/91, Taif, Saudi Arabia. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Antibacterial and antifungal pharmacophore sites for compound 7. Figure 2 Chemical structure of the best active compounds from the group. molecules-27-02698-t001_Table 1 Table 1 IC50 values of the tested pyrazole- and imidazole-based derivatives tested against F.o.a. ID. Structure IC50 μg/mL μM 1 110.9 299.4 2 153.2 538.8 3 165.1 509.1 4 99.1 256.4 5 114.7 378.3 6 194.5 667.1 Compared with literary works, we found that the pyrazole skeleton and its derivatives exhibited excellent inhibitory activity against Fusarium oxysporum [66]. molecules-27-02698-t002_Table 2 Table 2 IC50 values of the tested βketo-enol pyridine and furan derivatives against F.o.a. ID Structure IC50 μg/mL μM 7 12.83 8 NS NS 9 NS NS 10 17 11 36 12 - - 13 - - 14 - - 15 - - 16 - - 17 - - molecules-27-02698-t003_Table 3 Table 3 Volume is withdrawn, a diameter of the strain and inhibition percentages of the tested (Z)-3(3-bromophenyl)-1-(1,5-dimethyl-1H-pyrazole-3yl)-3-hydroxyprop-2-en-1-one derivatives 18–23 against F.o.a. ID Structure Volume Is Withdrawn (μL) Diameter of the Strain in the Presence of the Drug (cm) Inhibition (%) 18 50 200 500 5.0 3.8 2.7 0 24 46 19 50 200 500 5.0 3.5 2.3 0 30 54 20 50 200 500 5.0 3.6 2.5 0 28 50 21 50 200 500 5.0 3.8 3.2 0 24 36 22 50 200 500 1.2 0.9 0.5 76 82 90 23 50 200 500 2.0 1.3 0.2 60 74 96 Benomyl 50 200 500 2.3 1.1 0.3 54 78 94 molecules-27-02698-t004_Table 4 Table 4 IC50 values of the tested βketo-enol pyrazolic derivatives against F.o.a. ID Structure IC50 μg/mL μM 24 - - 25 260.74 71 26 - - 27 - - 28 193.31 48.00 29 60.84 14.80 30 181.30 53.00 molecules-27-02698-t005_Table 5 Table 5 IC50 values of the tested imidazothiazole derivatives against F.o.a. ID Structure IC50 (μg/mL) 31 50.00 32 70.00 33 20.00 34 60.00 35 50.00 molecules-27-02698-t006_Table 6 Table 6 IC50 values of the tested pyrazolic compounds against F.o.a. ID Structure IC50 (μM) 36 - 37 751 38 2507 39 406 40 398 41 333 42 2755 43 2550 44 2486 45 2614 46 1223 47 697 48 2856 49 2322 50 86 51 662 52 2592 53 284 54 - 55 168 molecules-27-02698-t007_Table 7 Table 7 Percent growth inhibition at different concentrations for quinoxaline compounds tested against F.o.a. ID Structure Percent Growth Inhibition (Concentration, mg/L) C1 C2 C3 56 9 (20) 7 (40) 22 (80) 57 9 (60) 15 (120) 15 (180) 58 17 (60) 17 (120) 19 (180) 59 21 32 35 (180) 60 15 (34) 31 (67) 33 (134) 61 29 (18) 31 (36) 51 (72) molecules-27-02698-t008_Table 8 Table 8 Linear growth and inhibitory sporulation rates of benzimidazole-1,2,3-triazole hybrid molecules tested against F.o.a. ID Structure Linear Growth-Inhibitory Rates (%) Sporulation Inhibitory Rates (%) 62 3.02 ± 0.96 −5.85 ± 0.04 63 −1.59 ± 0.05 16.36 ± 0.2 64 2.7 ± 0.16 −34.79 ± 0.72 65 −0.16 ± 0.02 21.94 ± 0.26 66 17.01 ± 0.96 30.62 ± 0.5 67 2.3 ± 0.29 −77.59 ± 2.64 68 −1.41 ± 0.3 −61.05 ± 1.34 69 −14 ± 0.05 −48.72 ± 2.35 molecules-27-02698-t009_Table 9 Table 9 M.I.C. values of N,N′-bipyrazole piperazine derivatives tested against F.o.a. ID Structure M.I.C. μg/mL μM 70 10 33.06 71 5 11.94 72 10 32.85 73 20 47.56 molecules-27-02698-t010_Table 10 Table 10 M.I.C. values of bipyrazolic tripodal compounds tested against F.o.a. ID Structure M.I.C. μg/mL μM 74 2.5 8.05 75 5 11.73 76 2.5 8.08 77 40 94.7 78 2.5 7.05 79 5 10.63 80 40 123.84 81 80 182.14 molecules-27-02698-t011_Table 11 Table 11 M.I.C. values of Schiff base derivatives compounds tested against F.o.a. ID Structure MIC (μg/mL) 82 0.10 83 0.90 84 0.02 85 0.25 86 0.30 87 0.04 88 0.04 89 0.12 90 0.25 91 0.20 92 0.08 93 0.04 molecules-27-02698-t012_Table 12 Table 12 MIC values of amino acids pyrazole compound tested against F.o.a. ID Structure MIC (mg/L) 94 - 95 - 96 17 97 15 98 0.3 99 10 100 0.5 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ibrahim E.B. Mohamed M. Rafik B. Bayoud disease of date palm in Algeria: History, epidemiology and integrated disease management Afr. J. Biotechnol. 2015 14 542 550 10.5897/AJBX2014.14292 2. Bouissil S. Guérin C. Roche J. Dubessay P. Alaoui-Talibi E. Pierre G. Michaud P. Mouzeyar S. Delattre C. El Modafar C. Induction of Defense Gene Expression and the Resistance of Date Palm to Fusarium oxysporum f. sp. Albedinis in Response to Alginate Extracted from Bifurcaria bifurcata Mar. Drugs 2022 20 88 35200618 3. M’Hammed E. Fatiha D. Ayada D. Said B. Mohamed K. Catalytic and synthesis of new compound based on geranium oil Egyp. J. Chem. 2021 64 7341 7346 10.21608/ejchem.2021.65454.3402 4. Belaidi H. Toumi-Benali F. Benzohra I.E. Biocontrol of bayoud disease (Fusarium oxysporum f. sp. albedinis) on deglet-nour variety of date palm (Phoenix dactylifera L.) in south western oases of Algeria Agric. Sci. Digest 2021 41 450 454 10.18805/ag.D-304 5. Komeil D.A. Abdalla M.Y. El-Bebany A.F. Basyony A.B.A. Resistance marker detection in ten date palm cultivars to the wilt pathogen, Fusarium oxysporum Asian J. Plant Sci. 2021 20 363 369 10.3923/ajps.2021.363.369 6. Tantaoui A. Ouinten M. Geiger J.P. Fernandez D. Characterization of a single clonal lineage of Fusarium oxysporum f. sp. albedinis causing Bayoud disease of date palm in Morocco Phytopathology 1996 86 787 792 10.1094/Phyto-86-787 7. Khalil N.M. Ali H.M. Ibrahim A.E. Biochemical Activity of Propolis Alcoholic Extracts against Fusarium oxysporum hm89 Egyp. J. Bot. 2022 62 197 212 10.21608/ejbo.2021.74897.1687 8. Shalaby M.G. Al-Hossainy A.F. Abo-Zeid A.M. Mobark H. Mahmoud Y.A.G. Synthesis, characterization, physicochemical properties, and in-vitro anti-bacterial evaluation for doped Fe-Fusarium J. Mol. Str. 2022 1259 132643 10.1016/j.molstruc.2022.132643 9. Hallasgo A.M. Hauser C. Steinkellner S. Hage-Ahmed K. Single and coinoculation of Serendipita herbamans with arbuscular mycorrhizal fungi reduces Fusarium wilt in tomato and slows disease progression in the long-term Biol. Control 2022 168 104876 10.1016/j.biocontrol.2022.104876 10. Sedra M. Lazrek B.H. Fusarium oxysporum f. sp. Albedinis Toxin Characterization and Use for Selection of Resistant Date Palm to Bayoud Disease Springer Cham, Switzerland 2011 253 270 11. Picot S. Beugnet F. Leboucher G. Bienvenu A.-L. Drug resistant parasites and fungi from a one-health perspective: A global concern that needs transdisciplinary stewardship programs One Health 2022 14 100368 10.1016/j.onehlt.2021.100368 34957316 12. Bankaitis V.A. Tripathi A. Chen X.-R. Igumenova T.I. New strategies for combating fungal infections: Inhibiting inositol lipid signaling by targeting Sec14 phosphatidylinositol transfer proteins Adv. Biol. Reg. 2022 84 100891 10.1016/j.jbior.2022.100891 35240534 13. Alarjani K.M. Huessien D. Rasheed R.A. Kalaiyarasi M. Green synthesis of silver nanoparticles by Pisum sativum L. (pea) pod against multidrug resistant foodborne pathogens J. King Saud Univ. Sci. 2022 34 101897 10.1016/j.jksus.2022.101897 14. Green R.M. Bicker K.L. Development of an Anti-Biofilm Screening Technique Leads to the Discovery of a Peptoid with Efficacy against Candida albicans ACS Infect. Diseas. 2022 8 310 320 10.1021/acsinfecdis.1c00449 35107257 15. Vanzolini T. Bruschi M. Rinaldi A.C. Magnani M. Fraternale A. Multitalented Synthetic Antimicrobial Peptides and Their Antibacterial, Antifungal and Antiviral Mechanisms Int. J. Mol. Sci. 2022 23 545 10.3390/ijms23010545 35008974 16. Abrigach F. Rokni Y. Takfaoui A. Khoutoul M. Doucet H. Asehraou A. Touzani R. In vitro screening, homology modeling and molecular docking studies of some pyrazole and imidazole derivatives Biomed. Pharmacother. 2018 103 653 661 10.1016/j.biopha.2018.04.061 29679907 17. Madany N.M.K. Shehata M.R. Mohamed A.S. Ovothiol—A isolated from sea urchin eggs suppress oxidative stress, inflammation, and dyslipidemia resulted in restoration of liver activity in cholestatic rats Biointerf. Res. Appl. Chem. 2022 12 8152 8162 18. Bulut M. Çelebi Sezer Y. Ceylan M.M. Alwazeer D. Koyuncu M. Hydrogen-rich water can reduce the formation of biogenic amines in butter Food Chem. 2022 384 132613 10.1016/j.foodchem.2022.132613 35258003 19. Dantas T.S. de Oliveira A.M. Ferreira M.R.A. Soares L.A.L. Therapeutic potential of croton blanchetianus for the treatment of gastric ulcers: A brief review Biointerf. Res. Appl. Chem. 2022 12 8219 8230 20. Pakornchote T. Ektarawong A. Sukserm A. Pinsook U. Bovornratanaraks T. Presence and absence of intrinsic magnetism in graphitic carbon nitrides designed through C–N–H building blocks Sci. Rep. 2022 12 2343 10.1038/s41598-022-05590-4 35149743 21. Teng Q.-H. Sun G.-X. Luo S.-Y. Wang K. Liang F.-P. Design, syntheses and antitumor activities evaluation of 1,5-diaryl substituted pyrazole secnidazole ester derivatives J. Heter. Chem. 2021 58 1656 1664 10.1002/jhet.4302 22. Yang Z. Fang Y. Kim J.-M. Lee K.-T. Park H. Synthesis of halogenated 1,5-diarylimidazoles and their inhibitory effects on lps-induced pge2 production in raw 264.7 cells Molecules 2021 26 6093 10.3390/molecules26206093 34684673 23. Mohamady S. Kralt B. Samwel S.K. Taylor S.D. Efficient One-Pot, Two-Component Modular Synthesis of 3,5-Disubstituted Pyrazoles ACS Omega 2018 3 15566 15574 10.1021/acsomega.8b02304 31458212 24. Radi S. Tighadouini S. Feron O. Riant O. Bouakka M. Benabbes R. Mabkhot Y.N. Synthesis of Novel beta-Keto-Enol Derivatives Tethered Pyrazole, Pyridine and Furan as New Potential Antifungal and Anti-Breast Cancer Agents Molecules 2015 20 20186 20194 10.3390/molecules201119684 26569202 25. Tighadouini S. Benabbes R. Tillard M. Eddike D. Haboubi K. Karrouchi K. Radi S. Synthesis, crystal structure, DFT studies and biological activity of (Z)-3-(3-bromophenyl)-1-(1,5-dimethyl-1H-pyrazol-3-yl)-3-hydroxyprop-2-en-1-one Chem. Cent. J. 2018 12 122 10.1186/s13065-018-0492-4 30474759 26. Tighadouini S. Radi S. Abrigach F. Benabbes R. Eddike D. Tillard M. Novel β-keto-enol Pyrazolic Compounds as Potent Antifungal Agents. Design, Synthesis, Crystal Structure, DFT, Homology Modeling, and Docking Studies J. Chem. Inf. Model. 2019 59 1398 1409 10.1021/acs.jcim.8b00828 30935197 27. Tighadouini S. Radi S. Benabbes R. Youssoufi M.H. Shityakov S. El Massaoudi M. Garcia Y. Synthesis, Biochemical Characterization, and Theoretical Studies of Novel beta-Keto-enol Pyridine and Furan Derivatives as Potent Antifungal Agents ACS Omega 2020 5 17743 17752 10.1021/acsomega.0c02365 32715261 28. Koudad M. El Hamouti C. Elaatiaoui A. Dadou S. Oussaid A. Abrigach F. Pilet G. Benchat N. Allali M. Synthesis, crystal structure, antimicrobial activity and docking studies of new imidazothiazole derivatives J. Iran. Chem. Soc. 2019 17 297 306 10.1007/s13738-019-01766-4 29. Kassab R.M. Gomha S.M. Muhammad Z.A. El-Khouly A.S. Synthesis, biological profile, and molecular docking of some new bis-imidazole fused templates and investigation of their cytotoxic potential as anti-tubercular and/or anticancer prototypes Med. Chem. 2021 17 875 886 10.2174/1573406417666201208121458 33292124 30. Haddad Y. Remes M. Adam V. Heger Z. Toward structure-based drug design against the epidermal growth factor receptor (EGFR) Drug Discov. Today 2021 26 289 295 10.1016/j.drudis.2020.10.007 33075469 31. Abrigach F. Karzazi Y. Benabbes R. El Youbi M. Khoutoul M. Taibi N. Karzazi N. Benchat N. Bouakka M. Saalaoui E. Synthesis, biological screening, P.O.M., and 3D-QSAR analyses of some novel pyrazolic compounds Med. Chem. Res. 2017 26 1784 1795 10.1007/s00044-017-1888-8 32. Bandgar B.P. Gawande S.S. Bodade R.G. Gawande N.M. Khobragade C.N. Synthesis and biological evaluation of a novel series of pyrazole chalcones as anti-inflammatory, antioxidant and antimicrobial agents Bioorg. Med. Chem. 2009 17 8168 8173 10.1016/j.bmc.2009.10.035 19896853 33. Alegaon S.G. Alagawadi K.R. Garg M.K. Dushyant K. Vinod D. 1,3,4-Trisubstituted pyrazole analogues as promising anti-inflammatory agents Bioorg. Chem. 2014 54 51 59 10.1016/j.bioorg.2014.04.001 24793214 34. Li Y.R. Li C. Liu J.C. Guo M. Zhang T.Y. Sun L.P. Zheng C.J. Piao H.R. Synthesis and biological evaluation of 1,3-diaryl pyrazole derivatives as potential antibacterial and anti-inflammatory agents Bioorg. Med. Chem. Lett. 2015 25 5052 5057 10.1016/j.bmcl.2015.10.028 26490095 35. Khan M.F. Alam M.M. Verma G. Akhtar W. Akhter M. Shaquiquzzaman M. The therapeutic voyage of pyrazole and its analogs: A review Eur. J. Med. Chem. 2016 120 170 201 10.1016/j.ejmech.2016.04.077 27191614 36. Alam J. Alam O. Alam P. Naim M.J. A Review on Pyrazole chemical entity and Biological Activity Inter. J. Pharm. Sci. Res. 2015 6 1433 1442 37. Chovatia P.T. Akabari J.D. Kachhadia P.K. Zalavadia P.D. Joshi H.S. Synthesis and selective antitubercular and antimicrobial inhibitory activity of 1-acetyl-3,5-diphenyl-4,5-dihydro-(1h)-pyrazole derivatives J. Serb. Chem. Soc. 2006 71 713 720 10.2298/JSC0607713C 38. Khanage S.G. Mohite P.B. Pandhare R.B. Raju S.A. Microwave Assisted Synthesis of 1-[5-(Substituted Aryl)-1H-Pyrazol-3-yl]-3,5-Diphenyl-1H-1,2,4-Triazole as Antinociceptive and Antimicrobial Agents Adv. Pharm. Bull. 2014 4 105 112 24511473 39. Hamada N.M.M. Abdo N.Y.M. Synthesis, characterization, antimicrobial screening and free-radical scavenging activity of some novel substituted pyrazoles Molecules 2015 20 10468 10486 10.3390/molecules200610468 26060913 40. Elshaier Y.A. Barakat A. Al-Qahtany B.M. Al-Majid A.M. Al-Agamy M.H. Synthesis of Pyrazole-Thiobarbituric Acid Derivatives: Antimicrobial Activity and Docking Studies Molecules 2016 21 1337 10.3390/molecules21101337 41. Kucukguzel S.G. Coskun I. Aydin S. Aktay G. Gursoy S. Cevik O. Ozakpinar O.B. Ozsavci D. Sener A. Kaushik-Basu N. Synthesis and characterization of celecoxib derivatives as possible anti-inflammatory, analgesic, antioxidant, anticancer and anti-HCV agents Molecules 2013 18 3595 3614 10.3390/molecules18033595 23519201 42. El Kodadi M. Benamar M. Ibrahim B. Zyad A. Malek F. Touzani R. Ramdani A. Melhaoui A. New synthesis of two tridentate bipyrazolic compounds and their cytotoxic activity tumor cell lines Nat. Prod. Res. 2007 21 947 952 10.1080/14786410701371314 17691042 43. Insuasty B. Tigreros A. Orozco F. Quiroga J. Abonía R. Nogueras M. Sanchez A. Cobo J. Synthesis of novel pyrazolic analogues of chalcones and their 3-aryl-4-(3-aryl-4,5-dihydro-1H-pyrazol-5-yl)-1-phenyl-1H-pyrazole derivatives as potential antitumor agents Bioorg. Med. Chem. 2010 18 4965 4974 10.1016/j.bmc.2010.06.013 20594863 44. Yahyi A. Et-Touhami A. Yahyaoui R. Touzani R. Synthesis, Characterization by Means of I.R., 1H, 13C-N.M.R. and Biological Investigations on New Diorganotin Carboxylic Acid Derivatives Lett. Drug Des. Discov. 2010 7 534 540 10.2174/157018010791526241 45. Ajay Kumar K. Jayaroopa P. Pyrazoles: Synthetic strategies and their pharmaceutical applications-an overview Int. J. Pharm. Tech. Res. 2013 5 1473 1486 46. Kucukguzel S.G. Senkardes S. Recent advances in bioactive pyrazoles Eur. J. Med. Chem. 2015 97 786 815 10.1016/j.ejmech.2014.11.059 25555743 47. Küçükgüzel Ş.G. Çıkla-Süzgün P. Recent advances bioactive 1,2,4-triazole-3-thiones Eur. J. Med. Chem. 2015 97 830 870 10.1016/j.ejmech.2014.11.033 25563511 48. Waring M.J. Ben-Hadda T. Kotchevar A.T. Ramdani A. Touzani R. El Kadiri S. Hakkou A. Bouakka M. Ellis T. 2,3-Bifunctionalized quinoxalines: Synthesis, DNA interactions and evaluation of anticancer, anti-tuberculosis and antifungal activity Molecules 2002 7 641 656 10.3390/70800641 49. Ouahrouch A. Ighachane H. Taourirte M. Engels J.W. Sedra M.H. Lazrek H.B. Benzimidazole-1,2,3-triazole hybrid molecules: Synthesis and evaluation for antibacterial/antifungal activity Arch. Pharm. 2014 347 748 755 10.1002/ardp.201400142 50. Radi S. Toubi Y. Hakkou A. Souna F. Himri I. Bouakka M. Synthesis, Antibacterial and Antifungal Activities of Novel N,N’-bipyrazole Piperazine Derivatives Lett. Drug Des. Discov. 2012 9 853 857 10.2174/157018012803307941 51. Klenc J. Raux E. Barnes S. Sullivan S. Duszynska B. Bojarski A.J. Strekowski L. Synthesis of 4-Substituted 2-(4-Methylpiperazino) pyrimidines and Quinazoline Analogs as Serotonin 5-HT 2A Receptor Ligands J. Heter. Chem. 2009 46 1259 1265 52. Radi S. Toubi Y. Hamdani I. Hakkou A. Souna F. Himri I. Bouakka M. Synthesis, antibacterial and antifungal activities of some new bipyrazolic tripodal derivatives Res. J. Chem. Sci. 2012 2 40 44 53. Toubi Y. Abrigach F. Radi S. Souna F. Hakkou A. Alsayari A. Muhsinah A.B. Mabkhot Y.N. Synthesis, antimicrobial screening, homology modeling, and molecular docking studies of a new series of Schiff base derivatives as prospective fungal inhibitor candidates Molecules 2019 24 3250 10.3390/molecules24183250 31500095 54. Boussalah N. Touzani R. Souna F. Himri I. Bouakka M. Hakkou A. Ghalem S. El Kadiri S. Antifungal activities of amino acid ester functional pyrazolyl compounds against Fusarium oxysporum f. sp. albedinis and Saccharomyces cerevisiae yeast J. Saudi Chem. Soc. 2013 17 17 21 10.1016/j.jscs.2011.02.016 55. Xing A. Zeng D. Chen Z. Synthesis, crystal structure and antioxidant activity of butylphenol Schiff bases: Experimental and DFT study J. Mol. Str. 2022 1253 132209 10.1016/j.molstruc.2021.132209 56. Aljamali N.M. Jawad S.F. Preparation, spectral characterization, thermal study, and antifungal assay of (Formazane-mefenamic acid)–derivatives Egyp. J. Chem. 2022 65 449 457 10.21608/ejchem.2021.88727.4266 57. Jambulingam M. AnandaThangadurai S. Vijayabaskaran M. Designing and Synthesis of Some Transition Metal Complexes Derived from Schiff Bases for Anti-Bacterial Activity J. Med. Chem. Sci. 2022 5 10 18 58. Mokhtari P. Mohammadnezhad G. Anti-cancer properties and catalytic oxidation of sulfides based on vanadium (V) complexes of unprotected sugar-based Schiff-base ligands Polyhedron 2022 215 115655 10.1016/j.poly.2022.115655 59. Murakami M. Kouyama T. Crystal structure of squid rhodopsin Nature 2008 453 363 367 10.1038/nature06925 18480818 60. Saavedra C.P. Encinas M.V. Araya M.A. Pichuantes S.E. Vásquez C.C. Biochemical characterization of a thermostable cysteine synthase from Geobacillus stearothermophilus V Biochimie 2004 86 481 485 10.1016/j.biochi.2004.06.003 15308337 61. Levitskiy O.A. Aglamazova O.I. Grishin Y.K. Nefedov S.E. Magdesieva T.V. Corey-Chaykovsky cyclopropanation of dehydroalanine in the Ni(II) coordination environment: Electrochemical vs. chemical activation Electrochim. Acta 2022 409 139980 10.1016/j.electacta.2022.139980 62. Shenoy K.V. Venugopal P.P. Reena Kumari P.D. Chakraborty D. Anti-corrosion investigation of a new nitro veratraldehyde substituted imidazopyridine derivative Schiff base on mild steel surface in hydrochloric acid medium: Experimental, computational, surface morphological analysis Mater. Chem. Phys. 2022 281 125855 10.1016/j.matchemphys.2022.125855 63. Hajri A.K. Jamoussi B. Albalawi A.E. Alhawiti O.H.N. Alsharif A.A. Designing of modified ion-imprinted chitosan particles for selective removal of mercury (II) ions Carbohydr. Polym. 2022 286 119207 10.1016/j.carbpol.2022.119207 35337492 64. Takfaoui A. Zhao L. Touzani R. Soulé J.-F. Dixneuf P.H. Doucet H. One pot Pd(OAc)2-catalysed 2,5-diarylation of imidazoles derivatives Tetrahedron 2014 70 8316 8323 10.1016/j.tet.2014.09.012 65. Takfaoui A. Zhao L. Touzani R. Dixneuf P.H. Doucet H. Palladium-catalysed direct diarylations of pyrazoles with aryl bromides: A one step access to 4,5-diarylpyrazoles Tetrahedron Lett. 2014 55 1697 1701 10.1016/j.tetlet.2014.01.079 66. Wu Z.B. Park H.Y. Xie D.W. Yang J.X. Hou S.T. Shahzad N. Kim C.K. Yang S. Synthesis, biological evaluation, and 3D-QSAR studies of N- (Substituted pyridine-4-yl)-1-(substituted phenyl)-5-trifluoromethyl- 1H- pyrazole-4-carboxamide derivatives as potential succinate dehydrogenase inhibitors J. Agric. Food Chem. 2021 69 1214 1223 10.1021/acs.jafc.0c05702 33480684 67. Tighadouini S. Radi S. Garcia Y. Selective chemical adsorption of Cd(II) on silica covalently decorated with a β-ketoenol-thiophene-furan receptor Mol. Syst. Des. Eng. 2020 5 1037 1047 10.1039/C9ME00140A 68. Radi S. Tighadouini S. Bacquet M. Degoutin S. Dacquin J.-P. Eddike D. Tillard M. Mabkhot Y.N. β-Keto-enol Tethered Pyridine and Thiophene: Synthesis, Crystal Structure Determination and Its Organic Immobilization on Silica for Efficient Solid-Liquid Extraction of Heavy Metals Molecules 2016 21 888 10.3390/molecules21070888 69. Radi S. Tighadouini S. Eddike D. Tillard M. Mabkhot Y.N. Crystal Structure of (Z)-1-(1,5-dimethyl-1H-pyrazol-3-yl)-3-hydroxy-3-(4-methoxyphenyl)prop-2-en-1-one, C15H16N2O3 Z. Kristallogr. New Cryst. Struct. 2017 232 199 200 10.1515/ncrs-2016-0190 70. Radi S. Tighadouini S. Eddike D. Tillard M. Mabkhot Y.N. Crystal Structure of (Z)-1-(1,5-dimethyl-1H-pyrazol-3-yl)-3-hydroxy-3-phenylprop-2-en-1-one, C14H14N2O2 Z. Kristallogr. New Cryst. Struct. 2017 232 201 202 71. Radi S. Tighadouini S. Eddike D. Tillard M. Mabkhot Y.N. Crystal Structure of (Z)-1-(1,5-dimethyl-1H-pyrazol-3-yl)-3-(4-ethoxyphenyl)-3-hydroxyprop-2-en-1-one, C16H18N2O3 Z. Kristallogr. New Cryst. Struct. 2017 232 207 208 10.1515/ncrs-2016-0196 72. Radi S. Tighadouini S. Eddike D. Tillard M. Mabkhot Y.N. Crystal Structure of (Z)-1-(1,5-dimethyl-1H-pyrazol-3-yl)-3-hydroxy-3-(p-toly)prop-2-en-1-one, C15H16N2O2 Z. Kristallogr. New Cryst. Struct. 2017 232 209 210 10.1515/ncrs-2016-0199 73. Radi S. Tighadouini S. Eddike D. Tillard M. Mabkhot Y.N. Crystal Structure of (Z)-3-hydroxy-3-(4-methoxyphenyl)-1-(pyridin-2-yl)prop-2-en-1-one, C15H13NO3 Z. Kristallogr. New Cryst. Struct. 2017 232 235 236 10.1515/ncrs-2016-0219 74. Tighadouini S. Radi S. Ferbinteanu M. Garcia Y. Highly Selective Removal of Pb(II) by a Pyridylpyrazole-β-ketoenol Receptor Covalently Bonded onto the Silica Surface ACS Omega 2019 4 3954 3964 10.1021/acsomega.8b03642 31459604 75. Peng Y.-H. Liao F.-Y. Tseng C.-T. Kuppusamy R. Li A.S. Chen C.H. Fan Y.S. Wang S.Y. Wu M.H. Hsueh C.C. Unique Sulfur-Aromatic Interactions Contribute to the Binding of Potent Imidazothiazole Indoleamine 2,3-Dioxygenase Inhibitors J. Med. Chem. 2020 63 1642 1659 10.1021/acs.jmedchem.9b01549 31961685 76. Adole V.A. Jagdale B.S. Pawar T.B. Sagane A.A. Ultrasound promoted stereoselective synthesis of 2,3-dihydrobenzofuran appended chalcones at ambient temperature S. Afr. J. Chem. 2020 73 35 43 10.17159/0379-4350/2020/v73a6 77. Morigi R. Vitali B. Prata C. Palomino R.A.N. Graziadio A. Locatelli A. Rambald M. Leoni A. Investigation on the effects of antimicrobial imidazo[2,1-b]Thiazole derivatives on the genitourinary microflora Med. Chem. 2018 14 311 319 10.2174/1573406413666171010110819 29032761 78. Abdel-Wahab B.F. Khidre R.E. Awad G.E.A. Design and Synthesis of Novel 6-(5-Methyl-1H-1,2,3-triazol-4-yl)-5-[(2-(thiazol-2-yl)hydrazono)methyl]imidazo[2,1-b]thiazoles as Antimicrobial Agents J. Heter. Chem. 2017 54 489 494 10.1002/jhet.2610 79. Jallapally A. Addla D. Yogeeswari P. Sriram D. Kantevari S. 2-Butyl-4-chloroimidazole based substituted piperazine-thiosemicarbazone hybrids as potent inhibitors of Mycobacterium tuberculosis Bioorg. Med. Chem. Let. 2014 24 5520 5524 10.1016/j.bmcl.2014.09.084 25451998 80. Rani N. Sharma A. Gupta G.K. Singh R. Imidazoles as potential antifungal agents: A review Med. Chem. 2013 13 1626 1655 10.2174/13895575113139990069 81. Mohamed H.A. Abdel-Wahab B.F. Synthetic access to imidazo[2,1-b]thiazoles J. Sulf. Chem. 2012 33 589 604 10.1080/17415993.2012.695792 82. Abdel-Wahab B.F. Mohamed H.A. Imidazobenzothiazoles: Synthesis and application J. Sulf. Chem. 2012 33 335 349 10.1080/17415993.2012.674132 83. Touzani R. Ramdani A. Ben-Hadda T. El Kadiri S. Maury O. Le Bozec H. Dixneuf P.H. Efficient synthesis of new nitrogen donor containing tripods under microwave irradiation and without solvent Synth. Commun. 2001 31 1315 1321 10.1081/SCC-100104040 84. Lamsayah M. Khoutoul M. Abrigach F. Oussaid A. Touzani R. Selective liquid-liquid extraction of fe(II) and cd(II) using n,n’-pyrazole bidentate ligands with theoretical study investigations Separ. Sci. Tech. 2015 50 2170 2176 85. Khoutoul M. Abrigach F. Zarrouk A. Benchat N.-E. Lamsayah M. Touzani R. New nitrogen-donnor pyrazole ligands for excellent liquid-liquid extraction of Fe2+ ions from aqueous solution, with theoretical study Res. Chem. Interm. 2015 41 3319 3334 10.1007/s11164-013-1435-2 86. Touzani R. Ben-Hadda T. El Kadiri S. Ramdani A. Maury O. Le Bozec H. Toupet L. Dixneuf P.H. Solution, solid state structure and fluorescence studies of 2,3-functiolized quinoxalines: Evidebce for π-delocalized keto-enamine form with N-H..O intramolecular hydrogen bonds New J. Chem. 2001 25 391 395 10.1039/b009667i 87. Daoud A. Cheknane A. Touzani R. Hilal H.S. Boulouiz A. Simulation of the Electrochemical Properties of Dye-Sensitized Solar Cells Based on Quinoxaline Dyes: Effects of Hydroxyl Group Numbers and Positions J. Electr. Mater. 2021 50 5656 5663 10.1007/s11664-021-09113-1 88. Bouabdallah I. Zidane I. Touzani R. Hacht B. Ramdani A. Quinoxalines and tetraketones for metal cations extraction Arkivoc 2006 10 77 81 10.3998/ark.5550190.0007.a10 89. Tornøe C.W. Christensen C. Meldal M. Peptidotriazoles on Solid Phase:  [1,2,3]-Triazoles by Regiospecific Copper(I)-Catalyzed 1,3-Dipolar Cycloadditions of Terminal Alkynes to Azides J. Org. Chem. 2002 67 3057 3064 10.1021/jo011148j 11975567 90. Rostovtsev V.V. Green L.G. Fokin V.V. Sharpless K.B. A stepwise huisgen cycloaddition process: Copper(I)-catalyzed regioselective “ligation” of azides and terminal alkynes Angew. Chem. Int. Ed. 2002 41 2565 2599 10.1002/1521-3773(20020715)41:14<2596::AID-ANIE2596>3.0.CO;2-4 91. Meldal M. Tornøe C.W. Cu-Catalyzed Azide–Alkyne Cycloaddition Chem. Rev. 2008 108 2952 3015 10.1021/cr0783479 18698735 92. Pradere U. Roy V. Mc Brayer T.R. Schinazi R.F. Agrofoglio L.A. Preparation of ribavirin analogues by copper- and ruthenium-catalyzed azide-alkyne 1,3-dipolar cycloaddition Tetrahedron 2008 64 9044 9051 10.1016/j.tet.2008.07.007 34321698 93. Al-Ghorbani M. Gouda M.A. Baashen M. Alharbi O. Almalki F.A. Ranganatha L.V. Piperazine Heterocycles as Potential Anticancer Agents: A Review Pharm. Chem. J. 2022 10.1007/s11094-022-02597-z 94. Sanka B.M. Tadesse D.M. Bedada E.T. Mengesha E.T. Babu G.N. Design, synthesis, biological screening and molecular docking studies of novel multifunctional 1,4-di (aryl/heteroaryl) substituted piperazine derivatives as potential antitubercular and antimicrobial agents Bioorg. Chem. 2021 119 105568 10.1016/j.bioorg.2021.105568 34968884 95. Desai N.C. Rupala Y.M. Khasiya A.G. Shah K.N. Pandit U.P. Khedkar V.M. Synthesis, biological evaluation, and molecular docking study of thiophene-, piperazine-, and thiazolidinone-based hybrids as potential antimicrobial agents J. Heter. Chem. 2021 59 75 87 10.1002/jhet.4366 96. Harit T. Malek F. Ameduri B. Fluorinated polymers based on pyrazole groups for fuel cell membranes Eur. Polym. J. 2016 79 72 81 10.1016/j.eurpolymj.2016.04.017 97. Garbacia S. Hillairet C. Touzani R. Lavastre O. New nitrogen-rich tripodal molecules based on bis(pyrazol-1-ylmethyl)amines with substituents modulating steric hindrances and electron density of donor sites Collect. Czech. Chem. Commun. 2005 70 34 40 10.1135/cccc20050034 98. Roh S.-G. Park Y.-C. Park D.-K. Kim T.-J. Jeong J.H. Synthesis and characterization of a Zn(II) complex of a pyrazole-based ligand bearing a chiral L-alaninemethylester Polyhedron 2001 20 1961 1965 10.1016/S0277-5387(01)00788-4 99. Scarpellini M. Wu A.J. Kampk J.W. Pecoraro V.L. Corroborative models of the cobalt(II) inhibited Fe/Mn superoxide dismutases Inorg. Chem. 2005 44 5001 5010 10.1021/ic050281h 15998028 100. Bouabdallah I. Touzani R. Zidane I. Ramdani A. Synthesis of new tripodal ligand: N,N-bis[(1,5-dimethylpyrazol-3-yl)methyl]benzylamine. Catecholase activity of two series of tripodal ligands with some copper (II) salts Catal. Commun. 2007 8 707 712 10.1016/j.catcom.2006.08.034 101. Touzani R. Garbacia S. Lavastre O. Yadav V.K. Carboni B. Efficient solution phase combinatorial access to a library of pyrazole- and triazole-containing compounds J. Comb. Chem. 2003 5 375 378 10.1021/cc030100b 12857105 102. Touzani R. Vasapollo G. Scorrano S. Del Sole R. Manera M.G. Rella R. El Kadiri S. New complexes based on tridentate bispyrazole ligand for optical gas sensing Mater. Chem. Phys. 2011 126 375 380 10.1016/j.matchemphys.2010.11.008 103. Boussalah N. Touzani R. Bouabdallah I. El Kadiri S. Ghalem S. Oxidation catalytic properties of new amino acid based on pyrazole tripodal ligands Int. J. Acad. Res. 2009 1 137 143 104. Boussalah N. Touzani R. Bouabdallah I. El Kadiri S. Ghalem S. Synthesis, structure and catalytic properties of tripodal amino-acid derivatized pyrazole-based ligands J. Mol. Catal. A Chem. 2009 306 113 117 10.1016/j.molcata.2009.02.031 105. Spadoni G. Balsamini C. Bedini A. Duranti E. Tontini A. Short synthesis of tryptophane and β-carboline derivatives by reaction of indoles with N-(diphenylmethylene)-α,β-didehydroamino acid esters J. Heterocycl. Chem. 1992 29 305 309 10.1002/jhet.5570290205 106. Zumbuehl A. Stano P. Sohrmann M. Dietiker R. Peter M. Carreira E.M. Synthesis and investigation of tryptophan—Amphotericin B conjugates ChemBioChem 2009 10 1617 1620 10.1002/cbic.200900096 19533712 107. Qian A. Zheng Y. Wang R. Wei J. Cui Y. Cao X. Yang Y. Design, synthesis, and structure-activity relationship studies of novel tetrazole antifungal agents with potent activity, broad antifungal spectrum and high selectivity Bioorg. Med. Chem. Lett. 2017 28 344 350 10.1016/j.bmcl.2017.12.040 29289430 108. Xiao Z.P. Ma T.W. Liao M.L. Feng Y.T. Peng X.C. Li J.L. Li Z.P. Wu Y. Luo Q. Deng Y. Tyrosyl-tRNA synthetase inhibitors as antibacterial agents: Synthesis, molecular docking and structure-activity relationship analysis of 3-aryl-4-arylaminofuran-2(5H)-ones Eur. J. Med. Chem. 2011 46 4904 4914 10.1016/j.ejmech.2011.07.047 21856050

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094940 ijms-23-04940 Article Glucocorticoid Receptor β Isoform Predominates in the Human Dysplastic Brain Region and Is Modulated by Age, Sex, and Antiseizure Medication Westcott Rosemary 1 Chung Natalie 1 https://orcid.org/0000-0002-7498-1994 Ghosh Arnab 2 https://orcid.org/0000-0003-3577-2257 Ferguson Lisa 3 Bingaman William 3 Najm Imad M. 3 https://orcid.org/0000-0003-4078-0278 Ghosh Chaitali 14* Zaitsev Aleksey Academic Editor Khazipov Roustem Academic Editor 1 Cerebrovascular Research, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; westcor@ccf.org (R.W.); nchung@ramapo.edu (N.C.) 2 Department of Inflammation and Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; ghosha3@ccf.org 3 Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA; fergusl3@ccf.org (L.F.); bingamb@ccf.org (W.B.); najmi@ccf.org (I.M.N.) 4 Department of Biomedical Engineering and Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH 44195, USA * Correspondence: ghoshc@ccf.org; Tel.: +1-216-445-0559; Fax: +1-216-444-9198 29 4 2022 5 2022 23 9 494007 4 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The glucocorticoid receptor (GR) at the blood–brain barrier (BBB) is involved in the pathogenesis of drug-resistant epilepsy with focal cortical dysplasia (FCD); however, the roles of GR isoforms GRα and GRβ in the dysplastic brain have not been revealed. We utilized dysplastic/epileptic and non-dysplastic brain tissue from patients who underwent resective epilepsy surgery to identify the GRα and GRβ levels, subcellular localization, and cellular specificity. BBB endothelial cells isolated from the dysplastic brain tissue (EPI-ECs) were used to decipher the key BBB proteins related to drug regulation and BBB integrity compared to control and transfected GRβ-overexpressed BBB endothelial cells. GRβ was upregulated in dysplastic compared to non-dysplastic tissues, and an imbalance of the GRα/GRβ ratio was significant in females vs. males and in patients > 45 years old. In EPI-ECs, the subcellular localization and expression patterns of GRβ, Hsp90, CYP3A4, and CYP2C9 were consistent with GRβ+ brain endothelial cells. Active matrix metalloproteinase levels and activity increased, whereas claudin-5 levels decreased in both EPI-ECs and GRβ+ endothelial cells. In conclusion, the GRβ has a major effect on dysplastic BBB functional proteins and is age and gender-dependent, suggesting a critical role of brain GRβ in dysplasia as a potential biomarker and therapeutic target in epilepsy. epilepsy blood–brain barrier focal cortical dysplasia glucocorticoid receptor cytochrome P450 matrix metalloproteinase heat-shock protein National Institute of Neurological Disorders and Stroke/National Institutes of HealthR01NS095825 This work is supported in part by the National Institute of Neurological Disorders and Stroke/National Institutes of Health grant R01NS095825 awarded to Chaitali Ghosh. ==== Body pmc1. Introduction The glucocorticoid receptor (GR) has recently been uncovered as a critical molecular regulator of drug permeability and barrier integrity at the epileptic blood–brain barrier (BBB), where it is found to be overexpressed and to have accelerated maturation [1,2,3]. After alternative splicing of the human GR transcript, multiple isoforms of this receptor are produced, two of the most well-characterized being GRα and GRβ [4,5]. These two GR isoforms differ at the carboxyl terminus [5,6], and due to the splicing at this position, GRβ is not able to bind ligands like glucocorticoids [5,6]. Although GRα is the classic GR isoform—binding glucocorticoids and activating transcription of glucocorticoid receptor element-containing genes—GRβ has shown important implications in inflammation and diseases like rheumatoid arthritis, asthma, and glioma [7,8,9], but the independent roles of GRα and GRβ isoforms have not yet been investigated in epilepsy. Focal cortical dysplasia (FCD) is a common epilepsy pathology that stems from focal malformations in the cerebral cortex [10], where neuroinflammation is prominent [11,12]. Pharmacoresistance in epilepsy still remains a major clinical challenge, as about one-third of epilepsy patients are non-responsive to antiseizure medications (ASMs) [13,14], and local drug metabolism and efflux activity at the BBB play a critical role in this phenomenon [3,15]. Cytochrome P450 (CYP) drug-metabolizing enzymes and efflux transporters (e.g., P-glycoprotein, Pgp) are functionally important at the BBB and could contribute to pharmacoresistance in epilepsy [1,2,15]. The expression of these enzymes and drug efflux transporters has been found to be regulated by the glucocorticoid receptor (GR) [1,2,3]. The importance of the GRβ isoform has been implicated in other brain disorders, such as glioma, where GRβ plays a critical part in the reactive astrocyte phenotype [9]. However, the specific role of GRβ in the human epileptic brain is not well established and could be an important target for drug regulation and BBB properties in epilepsy. To identify the involvement of the GRα and GRβ isoforms in FCD, we used cortical brain tissues from patients who underwent surgery for refractory epilepsy to determine: (1) the expression pattern of GRα and GRβ in dysplastic (epileptic) and non-dysplastic (relative control) tissues, (2) changes in GRα/GRβ ratio based on gender and age of these individuals, (3) the expression of neurovascular GR isoform localization in dysplastic vs. non-dysplastic brain tissue, and (4) the subcellular localization of GRα and GRβ based on the ASM combination taken by these patients before surgery as CYP dependent or a partially/independent metabolic pathway. To delineate the involvement of these two GR isoforms in BBB endothelial cells, where GR has been found to have a significant role [1,2,3], we used control primary human brain microvascular endothelial cells, with and without overexpressed GRβ by transfection, and compared that to primary dysplastic human brain endothelial cells (EPI-ECs) isolated from the well-characterized dysplastic brain region. We compared and evaluated the association of GRβ with the subcellular localization and expression levels of other key protein targets involved in drug metabolism and penetration through the BBB (CYP enzymes, P-glycoprotein) and GR regulation (Hsp90). Additionally, in these brain endothelial cells, we investigated the involvement of GRβ in BBB integrity (MMP-9, occludin, claudin-5) and matrix metalloproteinase (MMP) activity, extracellular matrix-degrading proteins responsible for a multitude of events linked to homeostasis and several physiological processes. Together, these data will elucidate the distinct roles of GRα and GRβ in the FCD brain and BBB, providing a deeper understanding of the significance of GR isoforms in epilepsy. 2. Results 2.1. Decreasing GRα/GRβ Ratio Is Dependent on Age and Gender in Human Dysplastic Brain Tissues The cortical brain tissues from dysplastic and non-dysplastic regions from patients with FCD (n = 14) revealed significant (* p < 0.0001) GRβ overexpression in the dysplastic vs. non-dysplastic brain regions, while GRα expression did not change (Figure 1a). This increase in GRβ expression levels in dysplastic vs. non-dysplastic tissue was found to be dependent on gender. Female patients (n = 9) showed a significant decrease in the GRα/GRβ ratio (* p = 0.0409) in dysplastic tissues compared to non-dysplastic, a trend that was not observed in male patients (n = 5, Figure 1b). Additionally, changes in the GRα/GRβ ratio in dysplastic compared to non-dysplastic brain tissues were also shown to be age-dependent, with a significant decrease in the ratio only being observed in dysplastic tissue of patients over 45 years old compared to non-dysplastic (* p = 0.0381, Figure 1c). 2.2. Differential Expression and Localization of GRα and GRβ Is Evident in Dysplastic and Non-Dysplastic Human Brain Tissues The histology of cortical brain tissues resected from the epileptic lesion (dysplastic) and from the surrounding, relatively normal brain area (non-dysplastic) was confirmed by cresyl violet staining and visualization of dysmorphic neurons, characteristic of FCD pathology (n = 3 patients, Figure 2a). In these same patients, DAB staining of both GRα and GRβ isoforms showed that, in general, GRβ levels were significantly elevated (* p = 0.0155) and GRα levels significantly decreased (* p = 0.0116) in the dysplastic brain region compared to the non-dysplastic region in these patients (Figure 2a). Co-immunohistochemistry of GRα with NeuN (neuronal nuclei marker) and GFAP (glial fibrillary acidic protein) confirmed the presence of GRα in the neurons and astrocytes of both the dysplastic and non-dysplastic brain regions (Figure 2b). GRβ staining was most prominent in the neurons and of the dysplastic tissues and scattered in the astrocytes (Figure 2b). Both GR isoforms were consistently expressed in the microvessels of dysplastic brain tissues in the cortex, marked with dotted lines in a few locations for reference (Figure 2b). 2.3. Antiseizure Drug Combination Regulates Subcellular Localization of GRα and GRβ Isoforms in Human Cortical Brain Tissue The cytosolic fraction of cortical brain tissue from the non-dysplastic regions of FCD patients taking ASMs as two or more CYP-mediated medications (n = 5) shows a significant increase (* p = 0.000476) in cytosolic GRα expression compared to the dysplastic tissue (Figure 3a). Compared to the nuclear fraction, there are significantly greater GRα levels (* p = 0.0256) in the cytosolic fraction in the non-dysplastic tissue of the CYP-mediated + CYP-mediated ASMs group, which is opposite to what is observed in the dysplastic tissue, showing significantly increased nuclear GRα (* p = 0.0306). Additionally, the nuclear fractions from these same tissues revealed increased levels of GRβ in dysplastic tissues compared to non-dysplastic (* p < 0.0001, Figure 3a). In the nuclear fraction of dysplastic tissues from this group, GRβ is significantly increased (* p = 0.000266) compared to the dysplastic cytosolic fraction, but between the non-dysplastic cytosolic and nuclear fractions, there is no difference in GRβ expression. The cytosolic and nuclear fractions of brain tissues from patients taking ASM combinations as CYP+NON-CYP-mediated (n = 4) showed a different pattern of GRα and GRβ localization. There is no significant difference in GRα or GRβ expression between non-dysplastic and dysplastic tissues of this group in either subcellular fraction or between the cytosolic and nuclear fractions with both GR isoforms evaluated (Figure 3b). 2.4. GRβ Overexpression in Human Brain Microvascular Endothelial Cells Regulates Expression and Subcellular Localization of Critical BBB Proteins and MMP Activity The human brain microvascular endothelial cells (HBMECs, n = 3) transfected with HA-tagged GRβ (HBMEC+HA-GRβ, n = 3) and dysplastic/epileptic endothelial cells (EPI-ECs, n = 2) evaluated by Western blot (shown by the representative blots, Figure 4a, and quantification in Figure 4b) show changes in the subcellular localization of the GR isoforms and a heat-shock protein chaperone (Hsp90) critical for GR maturation and function, compared to HBMECs (non-transfected control group, Figure 4). In HBMEC controls, GRα was only found in the cytosol, whereas in cells with overexpressed GRβ, GRα was found mostly in the nuclear fraction (Figure 4). In EPI-ECs, GRα was found in the cytoplasmic and partially in the nuclear fractions and was not significantly impacted by drug treatment. After GRβ overexpression in HBMECs, GRα levels increased in the nucleus after OXC, LEV, or DEX treatment for 24 h but not in the cytosol (Figure 4), which is reversed in the case of HBMEC/control endothelial cells (non-transfected). In all three cell types, the GRβ localization remained most prominent in the nuclear fraction and was unaffected by drug treatment (Figure 4). In both the cytosolic and nuclear fractions, EPI-ECs showed the highest GRβ expression of the three cell types, determined by the two-way ANOVA group effect. Hsp90 expression was increased in the cytosol after 24 h of OXC, LEV, or DEX treatment but only in HBMEC+HA-GRβ (Figure 4). Hsp90 was not extensively found in the nucleus of HBMECs. However, besides the cytosolic fractions, Hsp90 expression was also prominent in the nuclear fraction in HBMEC+HA-GRβ (* p = 0.000152) and EPI-ECs (* p < 0.0001) compared to HBMECs, analyzed by two-way ANOVA group effect. The expression changes in the three cell types and with drug treatment were also evaluated for downstream proteins relating to drug efflux activity and local drug metabolism at the BBB. Pgp was found in the cytosolic fraction in HBMEC and EPI-EC but was only observed in the nuclear fraction in HBMECs with GRβ overexpression. Pgp expression in the HBMEC and HBMEC+HA-GRβ increased after 24 h of each drug treatment—OXC, LEV, and DEX (Figure 4). Cytosolic and nuclear CYP3A4 and CYP2C9 expression was significantly increased in HBMEC+HA-GRβ (CYP3A4 cytosolic: * p < 0.0001, CYP3A4 nuclear: * p = 0.000487, CYP2C9 cytosolic: * p < 0.0001, CYP2C9 nuclear: * p = 0.000161) and EPI-ECs (CYP3A4 cytosolic: * p < 0.0001, CYP3A4 nuclear: * p < 0.0001, CYP2C9 cytosolic: * p < 0.0001, CYP2C9 nuclear: * p < 0.0001) compared to HBMECs, according to two-way ANOVA group effect. A 24 h LEV treatment significantly decreased the nuclear expression of both CYP enzymes in HBMEC+HA-GRβ (CYP3A4: * p = 0.0415, CYP2C9: * p = 0.0355), while 24 h OXC treatment significantly increased CYP3A4 levels (* p = 0.0268) in the cytosol in HBMEC, both compared to their respective vehicle controls at 24 h (Figure 4a,b). GRβ overexpression and drug treatment also altered the levels of protein targets responsible for BBB integrity. There was significantly more active MMP-9 expression in HBMEC+HA-GRβ (* p < 0.0001) and EPI-ECs (* p = 0.000174) compared to HBMECs (Figure 5a). However, drug treatment minimally impacted the pro MMP-9 (p = 0.0880) and active MMP-9 (p = 0.300) levels, evaluated by the two-way ANOVA treatment group effect. Occludin levels were also non-significantly changed within GRβ overexpression compared to non-transfected HBMECs (p = 0.252) and were also not affected by drug treatment. In contrast, claudin-5 levels were significantly decreased in EPI-ECs (* p < 0.0001) and HBMEC+HA-GRβ (* p < 0.0001) compared to HBMECs. In HBMECs, claudin-5 levels were significantly increased after 24 h of OXC (* p < 0.0001), LEV (* p = 0.0361), and DEX (* p = 0.000918) treatment compared to the vehicle control (Figure 5a). Drug treatment did not affect claudin-5 levels in HBMEC+HA-GRβ and EPI-ECs (Figure 5a). In addition to changing expression levels, the activity of MMPs (MMP-2 and MMP-9) also showed alterations between cell types but were further unaffected by drug treatment (Figure 5b). Pro MMP-9, pro MMP-2, and active MMP-2 activity were all significantly increased in HBMEC+HA-GRβ (pro MMP-9: * p < 0.0001, pro MMP-2: * p < 0.0001, active MMP-2: * p < 0.0001) and EPI-ECs (pro MMP-9: * p < 0.0001, pro MMP-2: * p < 0.0001, active MMP-2: * p = 0.0180) compared to HBMECs. 3. Discussion GR has already proven to be an important player in drug-resistant epilepsy due to focal cortical dysplasia (FCD), but the individual roles and clinical significance of the brain GRα and GRβ isoforms in FCD have not been well defined. The current study identifies for the first time that upregulated GRβ or a decreased GRα/GRβ ratio in the dysplastic brain could contribute to pathogenesis and drug response in pharmacoresistant epilepsy, particularly in certain subsets of patients, such as females and those over 45 years old. By recognizing the imbalance of these two GR isoforms in the dysplastic brain region compared to an adjacent relatively non-dysplastic region, which could be a biomarker of the dysplastic focus, and the effect of GRβ on drug response in BBB endothelial cells, the mechanism underlying the BBB involvement in drug-resistant epilepsy is further unveiled. We found that of the two GR isoforms, GRβ is overexpressed in the dysplastic brain region compared to a non-dysplastic brain region of the same patients (Figure 1), whereas GRα isoform expression was not significantly overexpressed in the dysplastic brain. Previously, our group discovered that total GR is overexpressed in the dysplastic brain [1,2,3], suggesting that a great proportion of GR overexpression is possibly due to GRβ based on these novel findings. Although the expression and ratio of GRα and GRβ isoforms in epilepsy have not yet been reported until now, interestingly, this information has been found to be pertinent to other diseases such as asthma, rheumatoid arthritis, and glioma [7,8,9]. Sex and age differences relating to GR have been implicated in inflammatory bowel disease (IBD) as well [16] which is consistent with our case, where a significant difference in the dysplastic vs. non-dysplastic GRα/GRβ ratio in female patients and in patients > 45 years old was identified. Reports also indicate that female patients with IBD were more likely to develop a dependence on glucocorticoid treatment compared to male patients, who were less likely to relapse after glucocorticoid dose reduction [16]. In general, sex differences have been identified in epilepsy, with FCD being more common in male pediatric epilepsy patients compared to females [17]. The relationship between a decreased GRα/GRβ ratio in female patients compared to males in this study would be interesting to further investigate, such as the possibility that females with a lower GRα/GRβ ratio could be more susceptible to the development of focal cortical dysplasia in epilepsy. This could be further investigated. Additionally, age played a statistically significant role in glucocorticoid response in these IBD patients, with glucocorticoid-resistant patients being older than responders [16]. GRβ is known to be involved in glucocorticoid resistance in multiple diseases [18,19], so the current findings of GRβ overexpression and a dependency of sex and age in the GRα/GRβ ratio in dysplastic compared to non-dysplastic brain tissue are consistent with findings in other disorders related to inflammatory factors. Treatment with corticosteroids, such as prednisolone, has been successful in managing seizures in some pediatric epilepsy patients [20,21], although steroid treatment for older adult epilepsy has not been as extensively studied. Steroid treatment in older patients with focal cortical dysplasia may not be as successful due to the decreased ratio of GRα/GRβ, possibly contributing to glucocorticoid resistance. In glioma, GRβ was also found to be overexpressed in the nuclei of injured astrocytes, where it was associated with β-catenin. After GRβ downregulation, the reactive astrocyte phenotype seen in glioma was dampened, showing that overexpression of this particular GR isoform is functionally relevant to the disease phenotype and pathogenesis of glioma [9]. In terms of epilepsy, GRβ overexpression could have similar effects at multiple levels of the neurovasculature. We were able to detect GRβ overexpression predominantly in the dysplastic microvessels, astrocytes, and neurons, and GRα was also located in these cell types, which was expected due to the importance of glucocorticoid signaling in brain function and regulation in these cells [22,23,24]; although this isoform was not as robustly expressed as GRβ which is clearly distinguishable within dysplastic and non-dysplastic brain regions. It has been previously implicated that a decreasing GRα/GRβ ratio (lower GRα and higher GRβ levels), which is what we see in this current study, relates to the ability of GRβ to act as a dominant negative regulator of GRα function [25,26]. In addition to expression changes, the drug regimen of the FCD patients affected the subcellular localization of GRα and GRβ isoforms levels (Figure 3). Previous studies have shown that GR is the upstream regulator of CYP3A4, CYP2C9, and Pgp expression [1,2]. Here, the GR isoform subcellular localization was followed in individuals that received multiple CYP-mediated ASMs vs. a combination of CYP+NON-CYP-mediated ASMs within the dysplastic and non-dysplastic brain regions. In the dysplastic tissue of the CYP+CYP group, both GRα and GRβ were primarily located in the nuclear fraction, the functionally active location. Both GR isoforms in the CYP+NON-CYP ASM group trended more towards the cytosolic fraction in the dysplastic and non-dysplastic tissues. GRα moves to the nucleus only after ligand binding, so the CYP+CYP ASM combination could trigger faster GR maturation and nuclear translocation through a drug-dependent mechanism that is not present with CYP+NON-CYP ASM combinations, possibly facilitated by heat-shock protein interaction with GR [3,27,28]. With that finding in mind, we further asked whether GRβ was the governing GR isoform that caused the changes in subcellular localization with drug treatment in EPI-ECs. Our overall goal was to determine if the expression and subcellular localization changes in targets important for BBB drug regulation observed between EPI-ECs and control endothelial cells could be attributed to GRβ overexpression. One possible explanation for increased nuclear GRα levels in endothelial cells with overexpressed GRβ could be that GRβ either drives GRα into the nucleus or traps it there, possibly modulating the downstream events differently in a disease state; however, this warrants further investigation. Because GRβ expression itself is driven by other factors, like cytokine levels, and it does not bind ligands [5,6], it is possible that drug monotherapy does not play as much of a role in its expression and nuclear translocation as polytherapy, as seen in Figure 3. In terms of GR regulation, Hsp90 is a major target for GR maturation and nuclear translocation [27,28]. However, Hsp90 does not only interact with the GRα isoform. It has been previously shown that Hsp90 is essential for GRβ nuclear translocation and that increased nuclear Hsp90 levels correspond with GRβ overexpression in glaucomatous trabecular meshwork cells [29]. In EPI-ECs and HBMEC+HA-GRβ, there were increased nuclear levels of Hsp90 compared to HBMEC. In other reports, nuclear Hsp90 accumulation was reported to be positively associated with metastasis and negatively associated with survival in patients with non-small cell lung cancer [30]. Interestingly, we show for the first time that GRβ overexpression contributes to the nuclear accumulation of Hsp90 in epilepsy. Hsp90 accumulation in the nucleus relating to GRβ overexpression could have clinical relevance in epilepsy which should be further investigated. The subcellular localization of Hsp90 could be related to GR maturation, which is associated with the expression of downstream targets, such as cytochrome P450 enzymes CYP3A4 and CYP2C9. Both of these CYP isoforms had elevated expression in EPI-ECs and in HBMEC+HA-GRβ, with localization in both the cytosol and nucleus, which suggests that these CYP enzymes are functional in the nucleus in epileptic endothelial cells, which is associated with GRβ overexpression. CYP1B1, another CYP isoform, mRNA has also been previously found in the cytoplasm and nucleus of human neurons and astrocytes in the cortex of the brain; although, the nuclear function remains unclear [31]. The role of nuclear CYP3A4 and CYP2C9 in epilepsy relating to GRβ overexpression needs to be explored in the future. In both EPI-ECs and HBMEC+HA-GRβ, unlike claudin-5, occludin levels were not significantly changed by drug treatment and remained relatively similar among the three cell types. Claudin-5 expression increased after 24 h of treatment with OXC, LEV, and DEX in HBMEC control cells [32,33] but not in HBMEC+HA-GRβ or EPI-ECs. This discrepancy could allude to the notion that, in this scenario, claudin-5 levels could not be rescued by pharmacological treatment due to the high levels of GRβ in the non-responding cells. In a study done with bone marrow-derived macrophages, LPS-induced resistance to DEX treatment was attributed to a 7-fold increase in GRβ mRNA levels in these cells [34], which could explain the resistance to DEX-mediated claudin-5 increase in HBMEC+HA-GRβ or EPI-ECs in our study. Interestingly, a recent study has also found that claudin-5 expression was significantly decreased 1.97-fold in epileptic brain microvessels compared to controls, but occludin expression was not significantly different between the two groups [35]. This supporting evidence further confirms that the decrease in tight junction proteins in the epileptic brain region may not afflict all types of tight junction proteins, and we describe here for the first time that GRβ may play a role in that phenomenon. Tight junction proteins can also be broken down by matrix metalloproteinases (MMPs), like MMP-9 [36], exacerbating the epileptic condition. Not only can MMP-9, as a calcium-dependent zinc-containing endopeptidase critical for neurovascular homeostasis, afflict BBB damage, but it also affects neuronal function [37,38]. Increased expression of the active form of MMP-9 and increased MMP-2 activity in HBMEC+HA-GRβ and EPI-ECs was not significantly affected by drug treatment (OXC, LEV, or DEX for 24 h), which could imply that MMP function in the dysplastic BBB is a pathological issue that is not rescued or worsened by drug treatment. GRβ overexpression has been found to enhance the expression of tumor necrosis factor-α (TNF-α) in a human monocyte cell line [39], and similarly, MMP-9 expression has been found to be increased by TNF-α in a human epithelial cell line [40]. The increase in MMP expression and activity observed in HBMEC+HA-GRβ and EPI-ECs could be related to cytokine production, such as TNF-α, which is likely mediated by GRβ overexpression. A role for GR isoforms has been implicated in components of the blood, such as monocytes and platelets, in major depressive disorder [39] and immune thrombocytopenia [41,42]; although, there is little to no evidence of GR isoforms in the blood of epilepsy patients. Clinical studies have shown neuronal migration disorders in the lesioned vs. non-lesional patients and detected epileptogenicity and have shown to produce clustered magnetoencephalography spike sources under total intravenous anesthesia. It would be interesting to investigate whether the GRα/GRβ difference that was observed in the dysplastic brain tissue compared to the non-dysplastic brain tissue of these patients could be detected in the blood of epilepsy patients as a disease biomarker. In conclusion, the GRα/GRβ imbalance that is observed in the dysplastic tissue of patients, particularly females and those above 45 years old, compared to the non-dysplastic tissue could be a critical marker of the diseased brain region. While GRβ overexpression in brain microvascular endothelial cells altered the subcellular localization and expression of multiple protein targets vital to the proper functioning of the neurovasculature (summarized in Figure 6). Delineating the predominant GR isoform in the dysplastic region could allow for future isoform-specific targeting that would be critical for BBB functional homeostasis in the dysplastic brain region and better-targeted therapy for patients with drug-resistant epilepsy. 4. Materials and Methods 4.1. Ethical Approval Informed consent was obtained from patients prior to tissue procurement under a Cleveland Clinic Institutional Review Board-approved protocol (IRB #07-322). This study was compliant with the principles outlined in the Declaration of Helsinki, and the authors understand the ethical principles. Brain specimens from both male and female subjects (n = 23) with pharmacoresistant epilepsy were obtained following focal surgical resections. Brain tissues from epileptic/dysplastic (DYS/EPI) and non-dysplastic/relative normal (NON-DYS) regions were resected after prior non-invasive (scalp video-EEG monitoring, magnetic resonance imaging, and positron emission tomography) and invasive (stereo-electro encephalography) evaluations. The non-dysplastic resected tissue region from each subject was considered as an internal relative control to the dysplastic tissue. The experimental outline is provided in Figure S1. Additional patient information (age, gender, ASMs, seizure frequency, epilepsy duration, resected tissue region, pathology, and experimental use of tissue) is summarized in Table 1. 4.2. Tissue Lysate Preparation and Fractionation Approximately 50 mg of fresh-frozen human cortical tissue resected from patients with drug-resistant epilepsy due to FCD (n = 14) was lysed with radioimmunoprecipitation assay (RIPA; Sigma-Aldrich, Burlington, MA, USA, cat. R0278) buffer combined with 1× protease inhibitor cocktail (Sigma, cat. P8340) as previously described [3,15]. To obtain cytoplasmic and nuclear fractions of the tissue, 50 mg of fresh-frozen tissue (n = 9 patients) was fractionated using the NE-PER Nuclear and Cytoplasmic Extraction Reagents kit (Thermo Fisher Scientific, Waltham, MA, USA, cat. 78833) according to the manufacturer’s instructions and as previously described [1]. The protein concentration of the lysates was estimated by the Bradford method. 4.3. Western Blotting For the human brain tissue lysates, GRα and GRβ were separated by 8% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and later transferred to polyvinylidene fluoride (PVDF) membranes (EMD Millipore Corp., Burlington, MA, USA, cat. IPVH00010) by semidry transfer (Trans-Blot© SD Semi-Dry Transfer Cell, Bio-Rad, Hercules, CA, USA). In brief, the membranes were probed overnight at 4 °C with the respective primary antibody followed by the appropriate secondary antibody for 1 h at room temperature (Supplementary Table S1), as previously described [15]. For the target proteins, the PVDF membranes were incubated in stripping buffer (Thermo Scientific, cat. 21059) for 20 min at room temperature followed by blocking of the membranes in 5% milk for 4 h before re-probing. In each case, the protein expression was normalized by β-actin (total lysate and cytoplasmic fractions) or proliferating cell nuclear antigen (PCNA, nuclear fractions) as loading controls, and the densitometric quantification of the images was performed using ImageJ software (National Institute of Health, Bethesda, MD, USA). Western blot using cell lysates and subcellular fractions for GRα, GRβ, Hsp90, Pgp, CYP3A4, CYP2C9 (8% gels) MMP-9, occludin, and claudin-5 (10% gels) were performed in a similar manner as stated above. Antibody information can be found in Table S1 and full representative blots in Figure S2. 4.4. Histology by Cresyl Violet Staining Gross anatomical evaluation of brain tissue specimens from patients who had undergone surgical resection for intractable epilepsy due to FCD from dysplastic compared to the respective non-dysplastic region was performed by cresyl violet histological staining on brain slices (n = 3 patients, 5 sections each) for observation of the cellular structures to identify dyslamination, ectopic neurons, and vascular malformations [43]. 4.5. Diaminobenzidine Staining Brain sections (n = 3 patients, 5 sections each) were permeabilized (0.3% TWEEN in 0.1 M PBS), blocked for endogenous peroxidase (0.3% hydrogen peroxide in methanol) and non-specific staining (5% normal goat serum in 0.1 M PBS + 0.4% Triton-X 100), and incubated at 4 °C overnight with GRα or GRβ primary antibodies. The detailed method has been described previously [43,44]. After washing, the sections were incubated for 1 h at room temperature with the respective biotinylated secondary antibody followed by 1 h with the avidin/biotin complex (Vector Labs, Burlingame, CA, USA, Elite Vectastain ABC kit, cat. PK-6102), visualization with diaminobenzidine (DAB) (Vector Labs, peroxidase substrate kit, SK-4100; nickel omitted), dehydration, and mounting with Permount (Thermo Fisher Scientific, cat. SP15-500). Primary and secondary antibodies used are listed in Table S1. Images were obtained by bright field microscopy using a Leica DMIL microscope and Q Capture for image acquisition. Quantification of the DAB staining (n = 4 images/patient) was performed using ImageJ software (National Institutes of Health). The background was removed using the brightness and contrast controls and the Rolling Ball Radius function. Images were converted to 8-bit, and the threshold was maintained by using the Adjust Threshold function. The resulting highlights after adjustment were then measured for average relative DAB intensity using the Measure function. Origin Pro 9.0 Software (version: 90E, Origin Lab Corp., Northampton, MA, USA) was then utilized to identify significant differences in expression between the dysplastic and non-dysplastic brain tissue regions. 4.6. Immunofluorescence Staining We also determined the expression and localization patterns of these two GR isoforms by immunofluorescence staining on contiguous brain slices (n = 4 patients, 5 sections each). The slices were immunostained for GRα and GRβ. Astrocytic (GFAP: glial fibrillary acidic protein) and neuronal (NeuN: neuronal nuclei) markers were also used to identify the cellular localization of the two GR isoforms. The concentrations and sources of all primary and secondary antibodies used are listed in Supplementary Table S1. After blocking for 1 h, the sections were incubated with the targeted primary antibody overnight at 4 °C followed by the respective secondary antibody for 2 h at room temperature. The tissues were blocked for autofluorescence with Sudan Black prior to mounting with VECTASHIELD® Mounting Medium with DAPI (Vector Laboratories, cat. H-1200). Images were acquired by fluorescence microscopy using a Leica DMIL LED microscope with a gain of 1.0. The acquired images were processed using ImageJ software. Antibody information can be found in Table S1. 4.7. Primary Brain Endothelial Cell Culture We used primary microvascular endothelial cells derived from brain specimens resected from patients with drug-resistant epilepsy (human epileptic endothelial cells (EPI-ECs), n = 2), as described earlier [44], obtained from EPI brain regions. Briefly, resected brain tissue specimens were incubated in collagenase type II (2 mg/mL; Thermo Fisher Scientific, cat. 17101-015) at 37 °C for 40 min to dissociate the ECs. The collagenase was then washed with endothelial cell medium 1.5 g/100 mL MCDB-105 (Sigma-Aldrich, cat. M6395), 15 mg/100 mL endothelial cell growth supplement (EMD Millipore, cat. 02-102), 800 U/100 mL heparin (Sigma-Aldrich, cat. H3149), 10% fetal bovine serum (Atlas Biologicals, Fort Collins, CO, USA, cat. F-0500-DR), and 1% penicillin/streptomycin), and the dissociated cells were plated initially in fibronectin-coated (Sigma-Aldrich, cat. F4759; 3 μg/cm2) 75 cm2 tissue culture flasks [1,2]. Primary control human brain microvascular endothelial cells (HBMECs) were purchased from Cell Systems (Kirkland, WA, USA, cat. ACBRI 376). The HBMECs were used as a control compared to the EPI-ECs and for transfection. According to the company, the HBMECs were dissociated from normal human brain cortical tissue obtained from healthy donors using a Beckman elutriation system and characterized by von Willebrand factor staining. Other specific details are available on the company website (Cell Systems, https://cell-systems.com/products/human-brain-microvascular-endothelial-cells-acbri-376?variant=37945739019 [accessed on 28 January 2022]). All cell culture treatment experiments were performed in 100 mm Petri dishes at 70–80% confluency. 4.8. Overexpression of HA-GRβ by Transfection To simulate the increase in GRβ expression observed in the dysplastic tissue compared to non-dysplastic, HBMECs were transfected with HA-tagged GRβ DNA (1.075 µg/µL). The custom HA-tagged GRβ plasmid was obtained from OriGene Technologies utilizing the open reading frame (ORF) from cat. RC220377 (OriGene Technologies, Rockville, MD, USA) cloned in a pCMV6-AC-HA vector (OriGene Technologies, cat. PS100004). To achieve this transfection, 5 µg of HA-GRβ DNA was mixed in serum-free Dulbecco’s modified eagle medium (DMEM/F12) and was later combined with a 30 µg mixture of lipofectamine (Thermo Fisher Scientific, cat. 18324-012) in serum-free DMEM to form the DNA+lipofectamine complex. This mixture was set aside for 25 min at room temperature. Once formed, this DNA+lipofectamine complex was combined with additional serum-free DMEM and added to the 100 mm Petri dish of 70% confluent HBMECs and left to incubate for 5 h at 37 °C. After the incubation was complete, the serum-free media containing the DNA+lipofectamine complex was aspirated, the plate was washed with 0.1 M phosphate-buffered saline (PBS), and the PBS was replaced with normal HBMEC media (Cell Systems, cat. 4Z0-500) until the following day when subsequent drug treatment experiments were performed. These transfected cells will be denoted throughout as “HBMEC+HA-GRβ”. 4.9. Drug Treatment with Cellular Fractionation To determine the effect of ASM (oxcarbazepine: OXC or levetiracetam: LEV) or GR agonist (dexamethasone: DEX) treatment on the subcellular localization of various protein targets crucial for drug metabolism/transport and BBB integrity, HBMECs, HBMEC+HA-GRβ, and EPI-ECs were divided into four treatment groups each: vehicle control, OXC (25 µg/mL), LEV (15 µg/mL), and DEX (10 µM) for 24 h. The cells were fractionated into cytoplasmic and nuclear fractions using the NE-PER Nuclear and Cytoplasmic Extraction Reagents kit as described above (Thermo Fisher Scientific, cat. 78833) at 6 h (HBMEC and HBMEC+ HA-GRβ) and 24 h (HBMEC, HBMEC+HA-GRβ, and EPI-EC) and analyzed by Western blot. Protein concentration was estimated by the Bradford method. Cell culture supernatant samples were also collected at each time point. 4.10. Determining MMP Activity by Zymography MMP activity was determined by gelatin zymography using the samples obtained from the endothelial cell supernatant with and without drug treatment. A total of 20 µL of each sample was loaded into gelatin zymography gels (Thermo Fisher Scientific, cat. ZY00102BOX) and run at 100 V for about 2 h [45]. The gels were then incubated in renaturing buffer (2.5% Triton-X 100 in distilled water) for 30 min at room temperature followed by 1× developing buffer (Thermo Fisher Scientific, cat. LC2671) for 30 min at room temperature to equilibrate the gels. Then, the gels were incubated at 37 °C in 1× developing buffer for 18 h. Gels were stained with 0.5% Coomassie Brilliant Blue R-250 (Bio-Rad Laboratories, cat. 161-0400) prepared in destaining solution (60% distilled water, 30% methanol, 10% acetic acid) for 30 min, and cleared with destain solution for 30 min to 1 h to visualize the bands before imaging. Images were processed and quantified densitometrically using ImageJ software. Origin Pro 9.0 Software was then utilized to identify significant differences in MMP activity. 4.11. Data Analysis and Statistics Origin Pro 9.0 Software was used for data analysis and statistical interpretation of data. Paired t-test was used to compare dysplastic and non-dysplastic brain tissue regions of the same individual patient. One-way or two-way analysis of variance (ANOVA) was utilized to compare multiple groups, with a Tukey post hoc test. All data are presented as mean with standard deviation (SD), and p < 0.05 was considered to be statistically significant. Acknowledgments We would like to acknowledge Mohammed Hossain for some Western blot analysis and Sherice Williams for assisting with immunohistochemistry staining and image acquisition/quantification. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094940/s1. Click here for additional data file. Author Contributions R.W. drafted the manuscript and performed part of the cell culture experiments, western blot, quantification, and analysis. N.C. performed immunohistochemistry and Western blot analysis and quantification. A.G. assisted with cell transfection and Western blot analysis. W.B., L.F. and I.M.N. helped to provide the patient tissues used for this experiment. C.G. designed the study/experiments and helped with data analysis and manuscript drafting. All authors participated in editing the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the Cleveland Clinic (IRB #07-322). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data that do not compromise ethical standards and patient confidentiality will be available upon reasonable request. Conflicts of Interest I.N. serves on the Speaker Bureau for Eisai, Inc., and as a member of the ad hoc advisory board for Eisai, Inc. and LivaNova. None of the other authors have any potential conflict of interest to disclose. Figure 1 Overexpression of GRβ in the dysplastic brain region compared to non-dysplastic is age and gender-dependent. (a) Western blot shows a significant increase (* p < 0.0001) in GRβ (~90 kDa) expression in dysplastic (DYS/EPI) compared to non-dysplastic (NON-DYS) brain tissues from patients with FCD (n = 14). There was no significant difference in the expression pattern of GRα (~94 kDa) between dysplastic and non-dysplastic tissues. β-actin (~43 kDa) was used as a loading control and for normalization. (b) The GRα/GRβ ratio using values obtained from the Western blot in (a) was plotted and compared based on the gender of each patient (n = 9 females and 5 males). The female group showed a significant decrease (* p = 0.0409) in the GRα/GRβ ratio in dysplastic vs. non-dysplastic tissues, corresponding to low GRα and high GRβ levels. There was no significant difference in the GRα/GRβ ratio in dysplastic vs. non-dysplastic tissues in the male patients, implying that GRβ overexpression in the dysplastic region of these patients is gender-dependent. (c) Patients from (a) were grouped into three age brackets (0–20 years old, 21–45 years old, and >45 years old) based on their age at the time of surgery. The GRα/GRβ ratio followed a decreasing trend with age in dysplastic compared to non-dysplastic brain tissues, and there was a significantly decreased ratio (* p = 0.0381) in patients that were above 45 years old. Western blots were performed in duplicate. All values are presented as mean with SD by paired t-test. Figure 2 Altered GRα and GRβ expression patterns with differences in neurovascular localization in the dysplastic human brain. (a) Cresyl violet (CV) histological staining of the dysplastic (DYS/EPI) vs. non-dysplastic (NON-DYS) cortical regions of a patient with FCD shows dysmorphic neurons and balloon cells in the dysplastic region compared to the relatively normal cortical structure in the non-dysplastic region. Diaminobenzidine (DAB) immunohistochemistry of patient tissues (n = 3 patients) confirms increased GRβ isoform levels in the dysplastic brain tissue compared to the non-dysplastic tissue (* p = 0.0155). GRα levels are also decreased (* p = 0.0116) in the dysplastic tissue compared to non-dysplastic. Images were obtained using a Leica DMIL brightfield microscope. Scale bar = 50 µm. Values are presented as mean with SD by paired t-test. (b) Immunofluorescent co-staining of GRα and GRβ with neuronal (NeuN) and astrocytic (GFAP) markers in dysplastic (EPI) vs. non-dysplastic human brain tissues (n = 3) elucidates the localization of GRα in both the neurons (white arrows) and astrocytes (yellow arrows) in dysplastic and non-dysplastic brain tissue. GRβ immunofluorescent staining shows extensive localization in neurons (NeuN) and astrocytes (GFAP) in the dysplastic tissue in relation to the non-dysplastic tissue. Select microvessels are lined for reference with a dotted white line, where both GRα and GRβ immunostaining is evident. Images were obtained using a Leica DMIL LED microscope with a gain of 1.0. Scale bar = 20 μm. Figure 3 GRα and GRβ subcellular localization in human dysplastic brain tissues is dependent on the antiseizure medication (ASM) combination. (a) In patients who took a combination of two or more cytochrome P450 (CYP)-mediated ASMs (n = 5 patients), cytoplasmic GRα (~94 kDa) was significantly decreased (* p = 0.000476) and nuclear GRβ (~90 kDa) significantly elevated (* p < 0.0001) in dysplastic compared to non-dysplastic tissues. (b) In patients who took a combination of CYP-mediated and NON-CYP-mediated ASMs (n = 4 patients), there were no significant differences between GRα or GRβ expression in dysplastic and non-dysplastic tissues in either the cytoplasm or nucleus. β-actin (~43 kDa) and PCNA (~35 kDa) were used as loading controls for the cytosolic and nuclear fractions, respectively, and for normalization. Western blots were performed in duplicate. All values are presented as mean with SD by one-way ANOVA with a Tukey post hoc test. Figure 4 GRβ alters the expression and subcellular localization of GRα and other key drug regulatory-related proteins in human brain endothelial cells. (a) Protein targets critical for drug metabolism and transport at the BBB showed altered expression and subcellular localization patterns in HBMEC+HA-GRβ (n = 3) and EPI-ECs (n = 2) compared to HBMECs (n = 3) with endogenous GRβ levels by Western blot. Quantification is shown in (b). GRα (~94 kDa) was only present in the cytosol of HBMECs but was highly present in the nuclear fraction of HBMEC+HA-GRβ. EPI-ECs showed a pattern of GRα subcellular localization that was a mixture of what was seen in HBMECs and HBMEC+HA-GRβ, with expression in the cytosol and nucleus. Oxcarbazepine (OXC), levetiracetam (LEV), and dexamethasone (DEX) treatments all significantly increased the expression of GRα after 24 h in the cytosol of HBMECs and in the nuclear fraction of HBMEC+HA-GRβ but caused no change in GRα expression in EPI-ECs. After HA-GRβ overexpression in HBMECs, GRβ (~90 kDa) was exclusively localized in the nucleus and negligible in the cytosol, but in EPI-ECs it was present in both the cytoplasmic and nucleus. Also, Hsp90 (~90 kDa) was almost explicitly seen in the cytosolic fraction of HBMECs, but HA-GRβ overexpression caused Hsp90 to be found in the nuclear fraction as well as the cytosolic, which is consistent with what was observed in EPI-ECs. Pgp (~170 kDa) was only expressed in the cytosol of HBMECs and EPI-ECs but in the nucleus of HBMEC+HA-GRβ. After OXC, LEV, or DEX treatment for 24 h, Pgp levels in the cytosol and nucleus were increased in HBMEC+HA-GRβ; although, only 24 h DEX treatment increased cytosolic Pgp expression in HBMECs. CYP3A4 (~57 kDa) and CYP2C9 (~59 kDa) levels in the cytosol and nucleus were both significantly lower in HBMECs with endogenous GRβ compared to HBMEC+HA-GRβ (CYP3A4 cytosolic: * p < 0.0001, CYP3A4 nuclear: * p = 0.000487, CYP2C9 cytosolic: * p < 0.0001, CYP2C9 nuclear: * p = 0.000161) and EPI-ECs (CYP3A4 cytosolic: * p < 0.0001, CYP3A4 nuclear: * p < 0.0001, CYP2C9 cytosolic: * p < 0.0001, CYP2C9 nuclear: * p < 0.0001). Although 24 h OXC treatment significantly increased cytosolic CYP3A4 levels in HBMECs, 24 h LEV treatment significantly decreased nuclear CYP3A4 and CYP2C9 levels in HBMEC+HA-GRβ. EPI-ECs show elevated levels of both of these CYP enzymes compared to HBMECs, but drug treatment did not affect expression levels. β-actin (~43 kDa) and PCNA (~35 kDa) were used as loading controls for the cytosolic and nuclear fractions, respectively, and for normalization. Western blots were performed in duplicate. All values are presented as mean with SD by two-way ANOVA with a Tukey post hoc test. Figure 5 Overexpressed GRβ in human brain endothelial cells and EPI-ECs increases active MMP-9 protein levels, decreases Claudin-5 expression, and increases MMP activity. (a) HBMEC+HA-GRβ shows increased levels of the active form of MMP-9 (~82 kDa) compared to HBMECs with endogenous GRβ but no change in the levels of the pro form (~92 kDa) of this protein. Occludin (~65 kDa) levels remain unchanged with drug treatment and GRβ expression levels, but 24 h treatment of OXC (* p < 0.0001), LEV (* p = 0.0361), or DEX (* p = 0.000918) increased Claudin-5 (~18 kDa) levels in HBMECs but not HBMEC+HA-GRβ or EPI-ECs. β-actin (~43 kDa) was used as a loading control and for normalization. (b) Representative MMP activity shown by gelatin zymography. Quantification of HBMEC+HA-GRβ overexpressed cells showed significantly elevated MMP-2 pro and active forms (* p < 0.0001 for both) compared to HBMECs with endogenous GRβ. Similar changes in MMP activity were seen in EPI-ECs compared to HBMECs (pro MMP-9: * p = 0.00193, pro MMP-2: * p < 0.0001, active MMP-2: * p = 0.0180). Western blots were performed in duplicate. All values (a,b) are presented as mean with SD by two-way ANOVA with a Tukey post hoc test. Figure 6 Summarizing the importance of GRβ overexpression in the dysplastic brain. We found an imbalance of GRα and GRβ, with increased GRβ levels, in the dysplastic brain region compared to a non-dysplastic region in patients with focal cortical dysplasia, particularly in females or individuals greater than 45 years old. The GR isoform imbalance, with GRβ being dominant in the dysplastic brain region, causes changes in the subcellular localization and expression patterns of critical BBB proteins related to drug regulation and BBB integrity as well as MMP activity in dysplastic endothelial cells. This is confirmed by overexpressing GRβ in normal brain microvascular endothelial cells which is found more comparable to dysplastic conditions. Delineating the role of GRβ in the dysplastic brain brings us one step closer to improved targeted therapy for epilepsy patients with focal cortical dysplasia. Figure created with BioRender.com (accessed on 6 April 2022). ijms-23-04940-t001_Table 1 Table 1 Demographic details. ID# Age (Yrs) Sex ASMs CYP- Mediated ASMs Seizure Freq. (Per Week) Duration of Epilepsy (Yrs) Resected Region Pathology Details Exp. Use 62 28 F CLB LEV OXC CLB OXC 1 ± 1 22 Left mesial frontal lobe FCD; Mild focal perivascular chronic inflammation; Focal subpial gliosis; Focal perivascular white matter atrophy IHC, WB 44 13 M LTG ZNS ZNS 3 ± 1 9 Right frontal lobe FCD; Nodular heterotopia; Perivascular chronic inflammation; Perivascular white matter atrophy, subpial gliosis WB 46 34 F LEV TPM TPM 1 26 Right frontal lobe FCD; Perivascular chronic inflammation; focal changes consistent with remote infarct/contusion damage; Subpial gliosis WB 28 64 F TPM LEV OXC TPM OXC 1 27 Left frontal lobe Focal cortical architectural disorganization consistent with FCD; Microcalcification; Focal perivascular white matter atrophy; Mild focal perivascular inflammation IHC, WB 61 10 M CLB LTG FBM CLB 1 8 Right superior frontal lobe FCD; Rare perivascular chronic lymphocytic inflammation; No balloon cells IHC, WB 66 25 F LTG BRV 7 3 Left frontal lobe Cortex with minimal non-specific findings and no large dysmorphic neurons; Architecture minimally distorted WB 51 1 F VGB LCM LCM 2 ± 1 1 Left frontal lobe FCD; Mild focal perivascular chronic inflammation WB 53 24 M CBZ ZNS CBZ ZNS 4 ± 1 19 Right occipital lobe FCD; Focal perivascular white matter atrophy; Mild focal perivascular chronic inflammation; Subpial gliosis WB 56 16 F LCM PER RUF LCM PER RUF Not noted 15 Left occipital lobe/temporal lobe FCD; Mild focal cortical dysplasia, marked neuronal loss and gliosis WB 38 29 F PHT ZNS CLB PHT ZNS CLB 14 ± 2 24 Left temporal lobe/frontal lobe FCD, Mild focal cortical architectural disorganization; Mild focal perivascular chronic inflammation WB 41 13 F OXC CLB CLZ OXC CLB CLZ 1 14 Right frontal lobe FCD, Focal architectural disorganization and Subpial gliosis WB 43 32 M OXC ZNS OXC ZNS 5 ± 11 30 Left parietal lobe FCD, Mild focal cortical architectural disorganization; Subpial gliosis; Contusional damage; Perivascular chronic inflammation WB 76 4 M LCM CLZ LCM CLZ 7 ± 1 3 Left lateral temporal lobe Changes consistent with remote infarcts/ischemic damage with microcalcification; Gliosis; Focal giant cells; Focal chronic inflammation WB 26 27 M LTG ZNS ZNS 1 11 Left frontal lobe Mild focal cortical architectural disorganization; Focal changes consistent with remote ischemic damage; Subpial gliosis; Meningeal fibrosis with perivascular and meningeal chronic inflammation WB 42 20 F LTG CLB CLB 10 ± 2 9 Left lateral temporal lobe FCD, Focal architectural disorganization and Subpial gliosis WB 33 37 M LTG LCM LCM 1 15 Right frontal lobe FCD, Focal cortical architectural disorganization; Subpial gliosis; Focal contusional damage WB 29 47 F ZNS CITA ZNS CITA Not noted Not noted Left lateral temporal lobe Focal subpial gliosis WB 80 55 F OXC LTG OXC 3 7 Temporal lobe Mild cortical architectural abnormality; Mild diffuse subpial gliosis; Mild perivascular fibrosis WB 86 62 M PHT ZNS PHT ZNS 1 62 Left temporal lobe Diffuse subpial gliosis; Microscopic subacute infarct-like foci (gliosis and macrophages) WB 88 49 M OXC LEV ZNS CLZ LOR OXC ZNS CLZ 1 every 2 months 2 Left frontal lobe Mild focal cortical architectural disorganization consistent with FCD; Focal changes consistent with contusional damage/infarct; Meningeal chronic inflammation; Subpial gliosis WB 142 23 M LCM CLB LCM CLB 0.75 2 Left anterior temporal lobe FCD WB 167 42 F CLB LTG CLB 1 per month 9 Right temporal lobe Mild focal cortical architectural disorganization consistent with FCD; Mild focal perivascular white matter atrophy; Subpial gliosis WB 160 20 F LTG LCM MDZ LCM MDZ 1 per month 18 Right temporal lobe Mild focal cortical architectural disorganization consistent with FCD; Mild focal perivascular white matter atrophy; Subpial gliosis WB 9 22 M PHT CLB LTG PHT CLB 1 per month 18 Right frontal lobe Focal cavitary changes and gliosis consistent with focal infarct/contusional damage; Focal perivascular white matter atrophy; Subpial gliosis Cell culture WB 111 35 M ZNS CLB CLZ ZNS CLB CLZ 3 ± 1 8 Right temporal lobe Mild focal cortical architectural disorganization suggestive of FCD; Perivascular white matter atrophy; Mild perivascular chronic inflammation; Focal subpial gliosis Cell culture WB Abbreviations: Yrs: years; ASM: Antiseizure medications; F: Female; M: Male; LEV: levetiracetam; OXC: oxcarbazepine; TPM: topiramate; BRV: brivaracetam; ESL: eslicarbazepine acetate; CLB: clobazam; LTG: lamotrigine; ZNS: zonisamide; VGB: vigabatrin; LCM: lacosamide; CBZ: carbamazepine: PER: perampanel; RUF: rufinamide; LCR: levocarnitine; FBM: felbamate; CLZ: clonazepam; DZP: diazepam; GBP: gabapentin; LOR: lorazepam; MDZ: midazolam; PHT: phenytoin; FCD: focal cortical dysplasia; Exp. use: experimental use; IHC: immunohistochemistry; WB: Western blot. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ghosh C. Hossain M. Mishra S. Khan S. Gonzalez-Martinez J. Marchi N. Janigro D. Bingaman W. Najm I. Modulation of glucocorticoid receptor in human epileptic endothelial cells impacts drug biotransformation in an in vitro blood-brain barrier model Epilepsia 2018 59 2049 2060 10.1111/epi.14567 30264400 2. Ghosh C. Hossain M. Solanki J. Najm I.M. Marchi N. Janigro D. Overexpression of pregnane X and glucocorticoid receptors and the regulation of cytochrome P450 in human epileptic brain endothelial cells Epilepsia 2017 58 576 585 10.1111/epi.13703 28199000 3. Hossain M. Williams S. Ferguson L. Bingaman W. Ghosh A. Najm I.M. Ghosh C. Heat Shock Proteins Accelerate the Maturation of Brain Endothelial Cell Glucocorticoid Receptor in Focal Human Drug-Resistant Epilepsy Mol. Neurobiol. 2020 57 4511 4529 10.1007/s12035-020-02043-9 32748370 4. Oakley R.H. Sar M. Cidlowski J.A. The human glucocorticoid receptor beta isoform. Expression, biochemical properties, and putative function J. Biol. Chem. 1996 271 9550 9559 10.1074/jbc.271.16.9550 8621628 5. Pujols L. Mullol J. Perez M. Roca-Ferrer J. Juan M. Xaubet A. Cidlowski J.A. Picado C. Expression of the human glucocorticoid receptor alpha and beta isoforms in human respiratory epithelial cells and their regulation by dexamethasone Am. J. Respir. Cell Mol. Biol. 2001 24 49 57 10.1165/ajrcmb.24.1.4024 11152650 6. Lu N.Z. Cidlowski J.A. The origin and functions of multiple human glucocorticoid receptor isoforms Ann. N. Y. Acad. Sci. 2004 1024 102 123 10.1196/annals.1321.008 15265776 7. Derijk R.H. Schaaf M.J. Turner G. Datson N.A. Vreugdenhil E. Cidlowski J. de Kloet E.R. Emery P. Sternberg E.M. Detera-Wadleigh S.D. A human glucocorticoid receptor gene variant that increases the stability of the glucocorticoid receptor beta-isoform mRNA is associated with rheumatoid arthritis J. Rheumatol. 2001 28 2383 2388 11708406 8. Hamid Q.A. Wenzel S.E. Hauk P.J. Tsicopoulos A. Wallaert B. Lafitte J.J. Chrousos G.P. Szefler S.J. Leung D.Y. Increased glucocorticoid receptor beta in airway cells of glucocorticoid-insensitive asthma Am. J. Respir. Crit. Care Med. 1999 159 1600 1604 10.1164/ajrccm.159.5.9804131 10228133 9. Yin Y. Zhang X. Li Z. Deng L. Jiao G. Zhang B. Xie P. Mu H. Qiao W. Zou J. Glucocorticoid receptor beta regulates injury-mediated astrocyte activation and contributes to glioma pathogenesis via modulation of beta-catenin/TCF transcriptional activity Neurobiol. Dis. 2013 59 165 176 10.1016/j.nbd.2013.07.013 23906498 10. Blumcke I. Thom M. Aronica E. Armstrong D.D. Vinters H.V. Palmini A. Jacques T.S. Avanzini G. Barkovich A.J. Battaglia G. The clinicopathologic spectrum of focal cortical dysplasias: A consensus classification proposed by an ad hoc Task Force of the ILAE Diagnostic Methods Commission Epilepsia 2011 52 158 174 10.1111/j.1528-1167.2010.02777.x 21219302 11. Arena A. Zimmer T.S. van Scheppingen J. Korotkov A. Anink J.J. Muhlebner A. Jansen F.E. van Hecke W. Spliet W.G. van Rijen P.C. Oxidative stress and inflammation in a spectrum of epileptogenic cortical malformations: Molecular insights into their interdependence Brain Pathol. 2019 29 351 365 10.1111/bpa.12661 30303592 12. Butler T. Ichise M. Teich A.F. Gerard E. Osborne J. French J. Devinsky O. Kuzniecky R. Gilliam F. Pervez F. Imaging inflammation in a patient with epilepsy due to focal cortical dysplasia J. Neuroimaging 2013 23 129 131 10.1111/j.1552-6569.2010.00572.x 21223436 13. Aronica E. Gorter J.A. Jansen G.H. van Veelen C.W. van Rijen P.C. Leenstra S. Ramkema M. Scheffer G.L. Scheper R.J. Troost D. Expression and cellular distribution of multidrug transporter proteins in two major causes of medically intractable epilepsy: Focal cortical dysplasia and glioneuronal tumors Neuroscience 2003 118 417 429 10.1016/S0306-4522(02)00992-2 12699778 14. Sisodiya S.M. Heffernan J. Squier M.V. Over-expression of P-glycoprotein in malformations of cortical development Neuroreport 1999 10 3437 3441 10.1097/00001756-199911080-00032 10599858 15. Williams S. Hossain M. Ferguson L. Busch R.M. Marchi N. Gonzalez-Martinez J. Perucca E. Najm I.M. Ghosh C. Neurovascular Drug Biotransformation Machinery in Focal Human Epilepsies: Brain CYP3A4 Correlates with Seizure Frequency and Antiepileptic Drug Therapy Mol. Neurobiol. 2019 56 8392 8407 10.1007/s12035-019-01673-y 31243719 16. Lucafo M. Bramuzzo M. Selvestrel D. Da Lozzo P. Decorti G. Stocco G. Gender May Influence the Immunosuppressive Actions of Prednisone in Young Patients With Inflammatory Bowel Disease Front. Immunol. 2021 12 673068 10.3389/fimmu.2021.673068 34054855 17. Ortiz-Gonzalez X.R. Poduri A. Roberts C.M. Sullivan J.E. Marsh E.D. Porter B.E. Focal cortical dysplasia is more common in boys than in girls Epilepsy Behav. 2013 27 121 123 10.1016/j.yebeh.2012.12.035 23416281 18. Chikanza I.C. Mechanisms of corticosteroid resistance in rheumatoid arthritis: A putative role for the corticosteroid receptor beta isoform Ann. N. Y. Acad. Sci. 2002 966 39 48 10.1111/j.1749-6632.2002.tb04200.x 12114257 19. Sousa A.R. Lane S.J. Cidlowski J.A. Staynov D.Z. Lee T.H. Glucocorticoid resistance in asthma is associated with elevated in vivo expression of the glucocorticoid receptor beta-isoform J. Allergy Clin. Immunol. 2000 105 943 950 10.1067/mai.2000.106486 10808175 20. Gupta R. Appleton R. Corticosteroids in the management of the paediatric epilepsies Arch. Dis. Child. 2005 90 379 384 10.1136/adc.2004.051375 15781928 21. Verhelst H. Boon P. Buyse G. Ceulemans B. D’Hooghe M. Meirleir L.D. Hasaerts D. Jansen A. Lagae L. Meurs A. Steroids in intractable childhood epilepsy: Clinical experience and review of the literature Seizure 2005 14 412 421 10.1016/j.seizure.2005.07.002 16087358 22. Forster C. Silwedel C. Golenhofen N. Burek M. Kietz S. Mankertz J. Drenckhahn D. Occludin as direct target for glucocorticoid-induced improvement of blood-brain barrier properties in a murine in vitro system J. Physiol. 2005 565 475 486 10.1113/jphysiol.2005.084038 15790664 23. Hartmann J. Dedic N. Pohlmann M.L. Hausl A. Karst H. Engelhardt C. Westerholz S. Wagner K.V. Labermaier C. Hoeijmakers L. Forebrain glutamatergic, but not GABAergic, neurons mediate anxiogenic effects of the glucocorticoid receptor Mol. Psychiatry 2017 22 466 475 10.1038/mp.2016.87 27240530 24. Tertil M. Skupio U. Barut J. Dubovyk V. Wawrzczak-Bargiela A. Soltys Z. Golda S. Kudla L. Wiktorowska L. Szklarczyk K. Glucocorticoid receptor signaling in astrocytes is required for aversive memory formation Transl. Psychiatry 2018 8 255 10.1038/s41398-018-0300-x 30487639 25. Al Heialy S. Gaudet M. Ramakrishnan R.K. Mogas A. Salameh L. Mahboub B. Hamid Q. Contribution of IL-17 in Steroid Hyporesponsiveness in Obese Asthmatics Through Dysregulation of Glucocorticoid Receptors alpha and beta Front. Immunol. 2020 11 1724 10.3389/fimmu.2020.01724 32849611 26. Gougat C. Jaffuel D. Gagliardo R. Henriquet C. Bousquet J. Demoly P. Mathieu M. Overexpression of the human glucocorticoid receptor alpha and beta isoforms inhibits AP-1 and NF-kappaB activities hormone independently J. Mol. Med. 2002 80 309 318 10.1007/s00109-001-0302-6 12021843 27. Dittmar K.D. Demady D.R. Stancato L.F. Krishna P. Pratt W.B. Folding of the glucocorticoid receptor by the heat shock protein (hsp) 90-based chaperone machinery. The role of p23 is to stabilize receptor.hsp90 heterocomplexes formed by hsp90.p60.hsp70 J. Biol. Chem. 1997 272 21213 21220 10.1074/jbc.272.34.21213 9261129 28. Kirschke E. Goswami D. Southworth D. Griffin P.R. Agard D.A. Glucocorticoid receptor function regulated by coordinated action of the Hsp90 and Hsp70 chaperone cycles Cell 2014 157 1685 1697 10.1016/j.cell.2014.04.038 24949977 29. Zhang X. Clark A.F. Yorio T. Heat shock protein 90 is an essential molecular chaperone for nuclear transport of glucocorticoid receptor beta Invest. Ophthalmol. Vis. Sci. 2006 47 700 708 10.1167/iovs.05-0697 16431970 30. Su J.M. Hsu Y.Y. Lin P. Chang H. Nuclear Accumulation of Heat-shock Protein 90 Is Associated with Poor Survival and Metastasis in Patients with Non-small Cell Lung Cancer Anticancer Res. 2016 36 2197 2203 27127123 31. Muskhelishvili L. Thompson P.A. Kusewitt D.F. Wang C. Kadlubar F.F. In situ hybridization and immunohistochemical analysis of cytochrome P450 1B1 expression in human normal tissues J. Histochem. Cytochem. 2001 49 229 236 10.1177/002215540104900210 11156691 32. Na W. Shin J.Y. Lee J.Y. Jeong S. Kim W.S. Yune T.Y. Ju B.G. Dexamethasone suppresses JMJD3 gene activation via a putative negative glucocorticoid response element and maintains integrity of tight junctions in brain microvascular endothelial cells J. Cereb. Blood Flow Metab. 2017 37 3695 3708 10.1177/0271678X17701156 28338398 33. Zielinska K.A. Van Moortel L. Opdenakker G. De Bosscher K. Van den Steen P.E. Endothelial Response to Glucocorticoids in Inflammatory Diseases Front. Immunol. 2016 7 592 10.3389/fimmu.2016.00592 28018358 34. Haim Y.O. Unger N.D. Souroujon M.C. Mittelman M. Neumann D. Resistance of LPS-activated bone marrow derived macrophages to apoptosis mediated by dexamethasone Sci. Rep. 2014 4 4323 10.1038/srep04323 24608810 35. Sato R. Ohmori K. Umetsu M. Takao M. Tano M. Grant G. Porter B. Bet A. Terasaki T. Uchida Y. An Atlas of the Quantitative Protein Expression of Anti-Epileptic-Drug Transporters, Metabolizing Enzymes and Tight Junctions at the Blood-Brain Barrier in Epileptic Patients Pharmaceutics 2021 13 2122 10.3390/pharmaceutics13122122 34959403 36. Chen F. Ohashi N. Li W. Eckman C. Nguyen J.H. Disruptions of occludin and claudin-5 in brain endothelial cells in vitro and in brains of mice with acute liver failure Hepatology 2009 50 1914 1923 10.1002/hep.23203 19821483 37. Rempe R.G. Hartz A.M.S. Soldner E.L.B. Sokola B.S. Alluri S.R. Abner E.L. Kryscio R.J. Pekcec A. Schlichtiger J. Bauer B. Matrix Metalloproteinase-Mediated Blood-Brain Barrier Dysfunction in Epilepsy J. Neurosci. 2018 38 4301 4315 10.1523/JNEUROSCI.2751-17.2018 29632167 38. Wilczynski G.M. Konopacki F.A. Wilczek E. Lasiecka Z. Gorlewicz A. Michaluk P. Wawrzyniak M. Malinowska M. Okulski P. Kolodziej L.R. Important role of matrix metalloproteinase 9 in epileptogenesis J. Cell Biol. 2008 180 1021 1035 10.1083/jcb.200708213 18332222 39. Chiang T.I. Hung Y.Y. Wu M.K. Huang Y.L. Kang H.Y. TNIP2 mediates GRbeta-promoted inflammation and is associated with severity of major depressive disorder Brain Behav. Immun. 2021 95 454 461 10.1016/j.bbi.2021.04.021 33932528 40. Lee I.T. Lin C.C. Wu Y.C. Yang C.M. TNF-alpha induces matrix metalloproteinase-9 expression in A549 cells: Role of TNFR1/TRAF2/PKCalpha-dependent signaling pathways J. Cell. Physiol. 2010 224 454 464 10.1002/jcp.22142 20333651 41. Moraes L.A. Paul-Clark M.J. Rickman A. Flower R.J. Goulding N.J. Perretti M. Ligand-specific glucocorticoid receptor activation in human platelets Blood 2005 106 4167 4175 10.1182/blood-2005-04-1723 16131566 42. Yung K.C. Xu C.W. Zhang Z.W. Yu W.J. Li Q. Xu X.R. Han Y.F. Wang X.J. Yin J. Investigation on glucocorticoid receptors within platelets from adult patients with immune thrombocytopenia Hematology 2020 25 37 42 10.1080/16078454.2019.1710025 31905108 43. Ghosh C. Marchi N. Desai N.K. Puvenna V. Hossain M. Gonzalez-Martinez J. Alexopoulos A.V. Janigro D. Cellular localization and functional significance of CYP3A4 in the human epileptic brain Epilepsia 2011 52 562 571 10.1111/j.1528-1167.2010.02956.x 21294720 44. Ghosh C. Gonzalez-Martinez J. Hossain M. Cucullo L. Fazio V. Janigro D. Marchi N. Pattern of P450 expression at the human blood-brain barrier: Roles of epileptic condition and laminar flow Epilepsia 2010 51 1408 1417 10.1111/j.1528-1167.2009.02428.x 20074231 45. Ratnikov B.I. Deryugina E.I. Strongin A.Y. Gelatin zymography and substrate cleavage assays of matrix metalloproteinase-2 in breast carcinoma cells overexpressing membrane type-1 matrix metalloproteinase Lab. Investig. 2002 82 1583 1590 10.1097/01.LAB.0000038555.67772.DB 12429818

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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092753 molecules-27-02753 Article Evaluation of the In Vitro Antiparasitic Effect of the Essential Oil of Cymbopogon winterianus and Its Chemical Composition Analysis https://orcid.org/0000-0002-0001-7238 Pereira Pedro Silvino 1* Oliveira Carlos Vinicius Barros 2 Maia Ana Josicleide 2 Vega-Gomez Maria Celeste 3 Rolón Miriam 3 Coronel Cathia 3 Duarte Antônia Eliene 2 https://orcid.org/0000-0002-6634-4207 Coutinho Henrique Douglas Melo 4* Siyadatpanah Abolghasem 5 https://orcid.org/0000-0002-4393-2380 Norouzi Roghayeh 6 Sadati Seyed Jafar Adnani 7 https://orcid.org/0000-0002-2730-7788 Wilairatana Polrat 8* Silva Teresinha Gonçalves 1 Jerz Gerold Academic Editor 1 Department of Antibiotics, Federal University of Pernambuco (UFPE), Av. Artur de Sá, s/n, Cidade Universitária, Recife 54740-520, PE, Brazil; teresinha100@gmail.com 2 Laboratory of Pharmacology and Molecular Chemistry, Regional University of Cariri (URCA), 1161 Cel. Antonio Luiz Avenue, Crato 63105-000, CE, Brazil; viniciusbluesky@gmail.com (C.V.B.O.); anajosicleide.maia@gmail.com (A.J.M.); duarte105@yahoo.com.br (A.E.D.) 3 Centro Para El Desarrollo De La Investigación Científica (CEDIC), Fundación Moisés Bertoni, Manduvira 635, Asunción C.P. 1255, Paraguay; mcvegagomez@gmail.com (M.C.V.-G.); rolonmiriam@gmail.com (M.R.); cathiacoronel@gmail.com (C.C.) 4 Microbiology and Molecular Biology Laboratory, Regional University of Cariri (URCA), 1161 Cel. Antonio Luiz Avenue, Crato 63105-000, CE, Brazil 5 Ferdows School of Paramedical and Health, Birjand University of Medical Sciences, Birjand 9717853577, Iran; asiyadatpanah@yahoo.com 6 Department of Pathobiology, Faculty of Veterinary Medicine, University of Tabriz, Tabriz 516661647, Iran; roghayehnorouzi123@gmail.com 7 Department of Microbiology & Immunology, Faculty of Medicine, Qom University of Medical Sciences, Qom 3736175513, Iran; jafaradnani@yahoo.com 8 Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand * Correspondence: pedro.sillvino@gmail.com (P.S.P.); hdmcoutinho@gmail.com (H.D.M.C.); polrat.wil@mahidol.ac.th (P.W.) 25 4 2022 5 2022 27 9 275326 3 2022 22 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Cymbopogon winterianus, known as “citronella grass”, is an important aromatic and medicinal tropical herbaceous plant. The essential oil of C. winterianus (EOCw) is popularly used to play an important role in improving human health due to its potential as a bioactive component. The present study aimed to identify the components of the essential oil of C. winterianus and verify its leishmanicidal and trypanocidal potential, as well as the cytotoxicity in mammalian cells, in vitro. The EOCw had geraniol (42.13%), citronellal (17.31%), and citronellol (16.91%) as major constituents. The essential oil only exhibited significant cytotoxicity in mammalian fibroblasts at concentrations greater than 250 μg/mL, while regarding antipromastigote and antiepimastigote activities, they presented values considered clinically relevant, since both had LC50 < 62.5 μg/mL. It can be concluded that this is a pioneer study on the potential of the essential oil of C. winterianus and its use against the parasites T. cruzi and L. brasiliensis, and its importance is also based on this fact. Additionally, according to the results, C. winterianus was effective in presenting values of clinical relevance and low toxicity and, therefore, an indicator of popular use. C. winterianus geraniol cytotoxicity leishmanicidal trypanocidal ==== Body pmc1. Introduction Neglected tropical diseases (NTDs) are a diverse group of tropical infections common in low-income populations in developing regions of Africa, Asia, and the Americas. Two of the main pathologies that fall into this category are Mucocutaneous leishmaniasis and Trypanosomiasis, caused by the protozoa Leishmania braziliensis and Trypanosoma cruzi, respectively, both belonging to the Trypanosomatidae family, class Kinetoplastea. Treatments for such infections are expensive, so it has been estimated that controlling NTDs would require between USD 2 billion and USD 3 billion in funding over the next five-to-seven years [1,2]. Mucocutaneous leishmaniasis, caused by the parasite L. braziliensis, leads to the partial or total destruction of the mucous membranes of the nose, mouth, and throat. More than 90% of cases of Mucocutaneous leishmaniasis occur in Bolivia, Brazil, Ethiopia, and Peru [3]. The use of chemotherapeutics, such as miltelfosine, and pentavalent antimonials, such as N-methyl-glucamine antimoniate, is often the first step in the treatment of Leishmania infections [4]. Recent evaluations have shown increased resistance to antimonials in some endemic areas, limiting their effectiveness and demanding a more species-specific solution when possible [5]. Two pentavalent antimony products available in the US are sodium stibogluconate and meglumine antimoniate. The recommended dosage for both is 20 mg/kg/day for 28 to 30 days in mucocutaneous and visceral leishmaniasis [6]. Chagas disease is caused by the protozoan T. cruzi transmitted by the feces of triatomines, which are contaminated with metacyclic trypomastigotes and ejected by the insect after feeding [7]. T. cruzi invades and multiplies as amastigotes within many different types of host cells, including muscle cells, macrophages, and fibroblasts [8]. Chagas disease is common in parts of Mexico, Central America, and South America, where an estimated 8 million people are infected [9]. Current options for the treatment of Chagas disease are restricted to benznidazole and nifurtimox, which are not well tolerated and imply frequent discontinuation of treatment [10]. In this scenario, there are essential oils (EOs) from several plant species with antiprotozoal properties that have become potential chemotherapeutic agents [11,12]. EOs are insoluble in inorganic solvents (water) but soluble in organic solvents (ether, alcohol, fixed oils). They are volatile liquids, with a characteristic odor, and are widely used in the perfumery, aromatherapy, and cosmetics industry; they are also increasingly important in the pharmaceutical scene due to their wide range of applications and biological activities [13]. Java citronella (Cymbopogon winterianus Jowitt ex Bor.) is an aromatic grass belonging to the Poaceae family that provides essential oils by stem distillation. It is widely used as a source in perfumery, soap, cosmetics, and flavoring industries. Leaf-blades are linear, tapering gradually to a long, membranous, acuminate shape, and up to 1 m long and 1.5 cm wide. C. winterianus is an industrially important perennial multi-crop cultivated in parts of tropical and subtropical areas of Asia, Africa, and America [14,15]. The study of C. winterianus in this research is due to its varied popular use and its diverse biological activities. Therefore, the present study aimed to identify the components and verify the leishmanicidal and trypanocidal power, as well as the in vitro cytotoxicity of the essential oil C. winterianus (EOCw). 2. Results The chromatographic profile (chromatogram) of EOCw (Figure 1) revealed by gas chromatography with mass spectrometry (GC/MS), indicates a single substance with retention time = 31.299 min and maximum detection intensity (most concentrated). As can be seen in Table 1, the chemical composition of the EOCw presented as major constituents in ascending order of concentration: citronellol (16.91%), citronellal (17.31%), and geraniol (42.13%), followed by other compounds in lower concentrations. In Figure 2, it is graphically observed that the cytotoxic activity of the EOCw had a relatively high LC50 of 96.56 μg/mL, which is desired for products intended for human consumption. Table 2 shows, from a different perspective, the same promising result observed in Figure 2, which would be the low cytotoxicity exhibited by EOCw against mammalian cells that would normally be infected by the parasites; cell damage only showed to be significant from the concentration of 125 µg/mL. According to Figure 3 and Figure 4, the EOCw presented inhibition values considered very promising for the promastigote and epimastigote forms of L. brasiliense and T. cruzi, with LC50 values of 44.98 μg/mL and 72.60 μg/mL, for Leishmania and Trypanosoma, respectively, with performance equivalent to that of Pentamidine, at a concentration of 125 μg/mL. Additionally, observing Table 3 and Table 4, it can be inferred that the EOCw showed survival percentage values considered very promising for the promastigote and epimastigote forms of L. brasiliense and T. cruzi, respectively. Figure 5 shows the log-dose vs. cytotoxicity curves of EOCw for fibroblasts, promastigotes, and epimastigotes estimated through non-linear regression of means, demonstrating that the anti-kinetoplastid effect was more intense than the cytotoxic effect in fibroblasts. 3. Discussion More than 200 different components present in pure essential oils have been reported. These mixtures typically contain phenylpropanoic derivatives or terpenes [16]. In general, gas chromatography (GC) is used for the analysis of volatile constituents present in essential oils, and liquid chromatography (LC) is used for the analysis of non-volatile constituents [17]. Usually, most essential oils are composed of volatile fractions, which contain monoterpenes, sesquiterpenes, and their oxygenated derivatives, where aliphatic alcohols, esters, and aldehydes may also be present [18,19]. The main compound found in the essential oil of C. winterianus using the GC technique with mass spectrometry was geraniol (3,7-dimethyl-2,6-octadien-8-ol) (42.13%), an acyclic monoterpenic alcohol in which biosynthesis occurs mainly in the cytosol of glandular trichomes via geranyl monophosphate (GP) through the action of a Nudix hydrolase [20,21]. Secondarily, citronellal (17.31%) and citronellol (16.91%) were detected in median concentrations, in which biosynthesis is related to the expression of heterodimeric geranyl diphosphate synthases (GPPS-SSU) and plastid geranylgeranyl diphosphate (GGPP) [22]. Essential oils of Cymbopogon spp. are diverse in chemical composition and have many bioactivities and potentials of great pharmaceutical and medicinal significance [23]. In this genus, it is possible to observe a remarkable variation in the composition and yield of the essential oil, which varies from 0.3% in C. travancorensis to 1.2% in C. martinii. The main components of citral essential oil “a” and “b” were detected in Cymbopogon pendulus, C. flexuosus, and C. citratus with the largest in C. citratus. Cymbopogon confertiflorus and C. nardus var. confertiflorus present an essential oil with a high content of geraniol (67.7% and 46.0%, respectively), and another group including C. nardus var. nardus, C. nardus var. Java II, and C. winterianus have less geraniol in their essential oil (ranging from 20% to 25%) [24,25]. Regarding the composition of the EOCw, the results obtained in the present study differ slightly from those already observed in the literature, according to which the proportion of citronellal (up to 40.23%) was higher than that of geraniol (up to 22.78%), with citronellol always having the third-highest proportion [26,27]. In the study by Kakaraparthi et al. [28], it is possible to observe that the proportion of geraniol has a significant positive correlation (0.60) with the maximum temperature to which the plant is exposed. Studies that evaluated the cytotoxic effect of essential oils of species of the Cymbopogon genus on mammalian cells showed that these are usually similar to that observed in the present study for C. winterianus (LC50 = 96.56 µL/mL) (Figure 2 and Figure 5, Table 2) so that the LC50 varies in the range of 50–300 µL/mL, where an LC50 > 50 µL/mL is indicated as non-cytotoxic [29,30]. In fact, in Cymbopogon spp. with a similar proportion of constituents to that observed here in EOCW, a cytoprotective effect is observed [31]. In the literature, a great variation in the antioxidant capacity of EOCw can be observed (IC50 = 12. 66 ± 0.56/743 ± 18 μg/mL), especially with regard to its capacity to reduce the 2,2-diphenyl radical -1-picrylhydrazyl (DPPH), which may be related to its great variability in its composition [32,33]. Essential oil of C. winterianus, as well as that of C. citratus, has already been shown to inhibit cytotoxicity in murine neutrophils through a mechanism not related to free radical scavenging [34]. The low cytotoxicity observed here (Figure 2 and Figure 5, Table 2) is probably due to the absence of compounds known to be toxic to mammalian cells in EOCw (Table 1), such as citral [35]. In the study by Sinha et al. [36], a weak cytotoxic effect of citronella essential oil on human lymphocytes was observed, although the use of geraniol had the opposite effect. Many human cell lines did not show genotoxic or clastogenic/aneugenic effects when exposed to high concentrations (100 μg/mL) of geraniol [37]. It has been shown that geraniol, despite its mild cytotoxicity in human lymphocytes, is able to scavenge free radicals similarly to butylated hydroxytoluene (BHT), ascorbic acid, and α-tocopherol, which are potent antioxidants [38]. Regarding citronellal, the second most-abundant compound in EOCw (Table 1), it is known to be non-toxic to mammalian cells (LC50 > 50 μg/mL) [30]. Few studies reporting the leishmanicidal effects of essential oils from species of the Cymbopogon genus have been reported, the majority of which cite the oil of C. citratus as a potent leishmanicidal agent, with LC50 values = 25 μg/mL and 1.7 µg/mL for Leishmania infantum and L. amazonensis, respectively, where the latter was superior to the pentamidine drug used here [39,40]. The leishmanicidal effects of EOCw observed here (Figure 3 and Figure 5, Table 3) are almost certainly due to a large number of oxygenated terpenes present in its composition (Table 1), which, as in C. citratus, demonstrate a strong leishmanicidal effect, especially for L. braziliensis [41]. Geraniol, identified here in large quantities in the EOCw (Table 1), did not show antipromastigote activity against L. braziliensis at a concentration of 100 µg/mL in the study by Carneiro et al. [42]; however, in the same study, it was shown that citronellal has excellent antipromastigote activity. Other plant species whose essential oils contain major amounts of citronellal, such as Eucalyptus citriodora, also exhibit good leishmanicidal effects [43]. Different species of Leishmania seem to be significantly affected by geraniol, which, in these cases, has LC50 = 3.78 µg/mL and 5.57 µg/mL for L. infantum and L. major, respectively [44]. In vitro analyses using molecular docking demonstrated that geraniol is strongly anchored by the molecules of L. major uridine diphosphate–glucose pyrophosphorylase (LmajUGPase), L. major methionyl t-RNA synthetase (LmajMetRS), and L. infantum nicotinamidase (LinfPnC1) [45]. The same type of evaluation indicated the spermidine synthase (SpdS) enzyme as a possible anchoring site for geraniol in L. donovani; however, linalool, with similar potential, does not present a good leishmanicidal effect [46,47]. Citral, molecularly similar to geraniol, is capable of causing considerable ultrastructural changes in Leishmania spp., including mitochondrial and kinetoplast swelling, autophagosomal structures, nuclear membrane rupture, and nuclear chromatin condensation, which would justify the antipromastigote effect observed here (Figure 3 and Figure 5, Table 3) [39]. Exposure to high concentrations of eugenol, another oxygenated monoterpene, also caused extensive fatal cell damage in Leishmania spp. promastigotes, such as cells with two or more flagella, swollen mitochondria and altered inner mitochondrial membrane, with a significant increase in the number of cristae, indicating an associated mechanism of action. to mitochondrial damage [48]. The performance of EOCw in inhibiting the epimastigote form of Trypanosoma cruzi (Figure 4 and Figure 5, Table 4) was similar to that observed in studies of the same scope using species of the genus Cymbopogon [49,50]. Cymbopogon citratus has already demonstrated a potent trypanocidal effect (LC50 = 3.2 μg/mL) against Trypanosoma brucei, that is, almost as efficient as the standard drug pentamidine used in our study, where its major component, citral, was found to be responsible for this performance, presenting a similar effect (LC50 = 18.9 μg/mL) [51]. Different forms of T. cruzi have already been shown to have different sensitivities to oxygenated monoterpenes such as geraniol and citronellal; trypomastigote forms are much more susceptible to its cytotoxic effects than epimastigotes [52]. Citral, abundant in Cymbopogon citratus essential oil, exhibits an exceptional trypanocidal effect on epimastigotes, presenting an LC50 = 42 μg/mL for T. cruzi, which is not observed in different preparations such as methanol extracts (68.25 μg/mL), probably due to the low concentration of citral [53,54,55]. One study observed that the antiproliferative effect of C. citratus essential oil was derived from its main constituent (citral) in the three evolutionary forms of T. cruzi (LC50/24 h < 50 μg/mL for citral), which, based on the ultrastructural analysis, induce cytoplasmic and nuclear extraction, while the plasma membrane remained morphologically preserved in the parasites [56]. T. cruzi cells exposed to oxygenated monoterpenes such as geraniol and citral showed typical characteristics of apoptosis, such as cytoplasmic bubble, cell shrinkage, absence of flagellum, loss of mitochondrial membrane potential, nuclear chromatin condensation, and DNA fragmentation probably due to loss of mitochondrial function [57,58]. 4. Materials and Methods 4.1. Plant Material, Selection, and Identification Cymbopogon winterianus leaves were collected in the morning at the Medicinal Plants Garden of the Regional University of Cariri (URCA), Crato, Ceará, Brazil, and authenticated by Prof. Afranio Fernandes at the Department of Biology at the Federal University of Ceará. Specimens of the plant are deposited at the Herbarium Prisco Bezerra, Fortaleza, Ceará, Brazil, voucher n° 43.194. 4.2. Obtaining Essential Oil from C. winterianus Fresh leaves were cut into pieces and then washed and macerated with 99.9% ethanol for 72 h at room temperature. The essential oil was obtained in a Clevenger apparatus by hydrodistillation. Fresh leaves of C. winterianus were placed in a 5 L flask, together with 3 L of distilled water, and heated for 2 h. Then, the obtained mixture was separated, and the essential oil of C. winterianus was treated with anhydrous sodium sulfate, filtered, and kept under refrigeration until the moment of analysis. 4.3. Essential Oil Chemical Identification The mass detection method applied in this study (secondary electron multiplier with conversion dynode) has the highest sensitivity and is the most suitable technique for estimating concentrations [59]. Oil analysis was performed with a Shimadzu GC/MS apparatus—QP2010 series (GC/MS system): Rtx-5MS capillary column (30 m × 0.25 mm, film thickness of 0.25 μm); helium carrier gas at 1.5 mL/min; injector temperature 250 °C; detector temperature 290 °C; column temperature 60–180 °C to 5 °C/min, then 180–280 °C to 10 °C/min (10 min). The scan speed was 0.5 scan/sec from m/z 40 to 350, and the split ratio was 1:200. Injected volume was 1 µL of (25 µL (essential oil)/5 mL CHCl3) (1:200). The solvent cut-off time was 2.5 min. The mass spectrometer was operated using 70 eV of ionization energy. The identification of the individual components was based on their mass spectral fragmentation based on the NIST 08 mass spectral library, retention indices, and comparison with published data. The relative retention rates were disregarded, since the manufacturer of the chromatography equipment used (Shimadzu©) indicated that measurement errors would increase for target peaks located far from the reference peak, making it difficult to find a relationship with a chemical structure [60]. 4.4. Antiparasitic Activity 4.4.1. Cell Lines Used Strains of CL-B5 parasites (clone CL-B5) were used for in vitro evaluation of activity on T. cruzi [61]. Parasites transfected with the β-galactosidase gene from Escherichia coli (LacZ) were provided by Dr. F. Buckner through the Gorgas Memorial Institute (Panamá). The epimastigote forms were cultivated in tryptose liver infusion at 28 °C, supplemented with 10% fetal bovine serum (FBS), 10 U/mL of penicillin, and 10 μg/mL of streptomycin at pH 7.2 and incubated with different concentrations of essential oil (1000; 500; 250; 125; 62.5; 31.5 μg/mL) and collected during the exponential growth phase [62]. The in vitro antileishmanial activity was established using L. braziliensis promastigotes (MHOM/CW/88/UA301) at 26 °C, cultured in Schneider’s medium for insects, supplemented with 10% (v/v) of fetal serum heat-inactivated calf, 2% normal human urine (v/v) plus penicillin and streptomycin [62]. The forms were seeded and incubated with different concentrations of essential oil (1000; 500; 250; 125; 62.5; 31.5 μg/mL). 4.4.2. Reagents Resazurin sodium substance was obtained from Sigma-Aldrich (St. Louis, MO, USA) and stored at 4 °C protected from light. Resazurin solution was prepared with 1% phosphate buffer, pH 7, and previously sterilized by filtration. Subsequently, Chlorophenol red-β-D-galactopyranoside (CPRG, Roche, Indianapolis, IN, USA) was dissolved in a 0.9% solution of Triton X-100 (pH 7.4). Penicillin G (Ern, SA, Barcelona, Spain), streptomycin (Reig Jofre SA, Barcelona, Spain), and dimethylsulfoxide (DMSO) were also used. 4.4.3. In Vitro Epimastigote Sensitivity Assay Assays were performed as described by Vega et al. [63], with crops that did not reach the stationary phase. Epimastigote forms were seeded at 1 × 105 per mL in 200 μL, in 96-well microdilution plates, which were incubated at 28 °C for 72 h. Then, 50 µL of CPRG solution was added to give a final concentration of 200 µM. Plates were incubated at 37 °C for an additional 6 h. Absorbance reading was performed in a spectrophotometer at 595 nm. Concentrations were tested in triplicate. Each experiment was performed twice separately. The percentage of inhibition (% AE) was calculated as follows:% AE = [(AE_AEB)/(AC_ACB)] × 100 where AE = absorbance of the experimental group; AEB = compound blank; AC = absorbance control group; CBA = culture environment blank. The essential oil was previously dissolved in DMSO. The concentration of DMSO (dimethylsulfoxide) used to allow the solubility of the oil was not greater than 0.01%. The effectiveness of Pentamidine as a trypanocidal drug was also determined. 4.4.4. In Vitro Leishmanicidal Assay The tests were performed according to Mikus and Steverding [64] with some modifications. Oil activity was evaluated in triplicate. Promastigote forms (2.5 × 105 parasites/well) were cultured in 96-well plastic plates. Samples were dissolved in dimethylsulfoxide (DMSO). Different dilutions of compounds up to 200 mL of the final volume were added. After 48 h at 26 °C, 20 µL of resazurin solution was added and the oxidation-reduction was measured at 570 to 595 nm. Percentages of antipromastigotes (AP%) were calculated. The effectiveness of the reference leishmanicidal drug pentamidine was also determined. 4.5. Fibroblasts Cytotoxic Assays To measure cell viability in mammalian cells, a colorimetric assay with resazurin was used. NCTC 929 fibroblasts were seeded (5 × 104 cells/well) in 96-well flat-bottom microdilution plates with 100 µL of RPMI 1640 medium for 24 h at 37 °C and cultured in 5% CO2 for cells to adhere to the plates. The medium was replaced by different concentrations of essential oil (1000; 500; 250; 125; 62.5; 31.5 μg/mL) in 200 μL of medium and incubated for another 24 h. Growth controls were included. Then, a volume of 20 μL of 2 mM resazurin solution was added and the plates were placed in the incubator for another 3 h to assess cell viability. Resazurin reduction was determined by measuring the wavelength absorbance at 490 nm and 595 nm. Each concentration was tested three times. The cytotoxicity of each compound was estimated by calculating the percentage of cytotoxicity (%C). 4.6. Statistical Analysis Results are expressed as mean ± standard error of the mean (SEM) of three independent experiments performed in triplicate. Concentrations capable of causing 50% lethality (LC50) were calculated by non-linear regression log-dose vs. mean ± standard error of the mean, using GraphPad Prism software version 6.0. 5. Conclusions This study elucidated the composition and revealed, for the first time, the antiparasitic effect of the essential oil of C. winterianus, especially against L. braziliensis, but also against T. cruzi. Furthermore, we were able to determine a low cytotoxic effect of this natural product against mammalian cells, which enables possible applications in vivo. Therefore, future studies with the isolated constituents of the essential oil of C. winterianus need to be evaluated regarding the molecular mechanisms of interaction with kinetoplastid and human cells. Acknowledgments The authors would like to thank the Postgraduate Studies in Biological Sciences at the Federal University of Pernambuco, UFPE. Author Contributions Conceptualization, P.S.P. and T.G.S.; methodology, M.C.V.-G.; validation, M.R. and C.C.; formal analysis, M.C.V.-G., S.J.A.S. and A.J.M.; investigation, C.V.B.O.; writing—original draft preparation, A.E.D. and C.V.B.O.; writing—review and editing, P.S.P., T.G.S., A.S., R.N. and H.D.M.C.; visualization, T.G.S., P.W. and H.D.M.C. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Sample Availability Samples of the compound are not available from the authors. Figure 1 GC/MS chromatogram of the essential oil of C. winterianus with total ion current (TIC) peak reports. * Total Íon Current. Figure 2 Cytotoxicity of the essential oil of C. winterianus, with the confidence interval for oil at 95% (87.07–107.10). LC50 was obtained through non-linear regression of means. Figure 3 Cytotoxicity of the promastigote L. brasiliensis treated with essential oil of C. winterianus. LC50, with the confidence interval for oil at 95% (35.55–56.92). LC50 was obtained through non-linear regression of means. Figure 4 Cytotoxicity of the epimastigote T. cruzi treated with essential oil of C. winterianus. LC50 confidence interval for oil is 95% (50.63–104.10). LC50 was obtained through non-linear regression of means. Figure 5 Log-dose vs. cytotoxicity curves for NCTC 929 fibroblasts, L. braziliensis promastigotes, and T. cruzi epimastigotes were estimated by non-linear regression of means. molecules-27-02753-t001_Table 1 Table 1 Chemical composition (%) of the essential oil of C. winterianus. Components RT (min) a (%) Limonene 17.88 4.24 Citronellal 25.27 17.31 Citronellol 29.70 16.91 Geraniol 31.29 42.13 β-elemene 39.37 2.69 δ-Cadinene 46.65 1.05 Elemol 47.24 6.71 Germacrene 47.80 4.44 Guaiol 48.87 1.14 Nerolidol 52.70 3.38 Total 100.00 a Retention time. molecules-27-02753-t002_Table 2 Table 2 Survival of fibroblasts exposed to the essential oil of C. winterianus. Natural Product Conc. µg/mL %C ±%DS C. winterianus 1000 0 – 500 0 – 250 2.15 0.49 125 35.79 0.80 62.5 89.96 0.70 31.5 90.96 0.77 molecules-27-02753-t003_Table 3 Table 3 Survival of the promastigote L. brasiliensis treated with the essential oil of C. winterianus. Natural Product Conc. µg/mL C. winterianus %S ±%DS Conc. µg/mL Pentamidine %S ±%DS C. winterianus 1000 0 - 500 0 - 250 0 - 125 0 - 100 5.7 0.2 62.5 39.13 2.11 31.5 65.56 1.02 25 10.7 0.4 6.2 40.5 0.2 3.2 83.6 0.9 molecules-27-02753-t004_Table 4 Table 4 Survival of the epimastigote T. cruzi treated with the essential oil of C. winterianus. Natural Product Conc. µg/mL C. winterianus %S ± %DS Conc. g/mL Pentamidine %S ±%DS C. winterianus 1000 0 – 500 0 – 250 0 – 125 0 – 100 0 0.7 62.5 74.89 1.70 50 6.6 0.5 31.5 83.88 2.52 10 15.4 0.6 1.0 56.3 0.5 0.5 85.4 0.6 0.1 99.6 0.3 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hotez P.J. A Plan to Defeat Neglected Tropical Diseases Sci. Am. 2010 302 90 96 10.1038/scientificamerican0110-90 20063641 2. Archibald J.M. Simpson A.G.B. Slamovits C.H. Margulis L. Melkonian M. Chapman D.J. Corliss J.O. Handbook of the Protists Archibald J.M. Simpson A.G.B. Slamovits C.H. Margulis L. Melkonian M. Chapman D.J. Corliss J.O. Springer International Publishing Cham, Switzerland 2017 978-3-319-32669-6 3. WHO Leishmaniasis Available online: https://www.who.int/news-room/fact-sheets/detail/leishmaniasis (accessed on 3 August 2021) 4. Darcis G. Van der Auwera G. Giot J.-B. Hayette M.-P. Tassin F. Arrese Estrada J. Cnops L. Moutschen M. de Leval L. Leonard P. Recurrence of visceral and muco-cutaneous leishmaniasis in a patient under immunosuppressive therapy BMC Infect. Dis. 2017 17 478 10.1186/s12879-017-2571-x 28687071 5. Kedzierski L. Leishmaniasis Hum. Vaccin. 2011 7 1204 1214 10.4161/hv.7.11.17752 22048116 6. Sundar S. Chakravarty J. Leishmaniasis: An update of current pharmacotherapy Expert Opin. Pharmacother. 2013 14 53 63 10.1517/14656566.2013.755515 23256501 7. Gibson W. Kinetoplastea Handbook of the Protists Springer International Publishing Cham, Switzerland 2016 1 50 8. Andrade L.O. Andrews N.W. The Trypanosoma cruzi–host-cell interplay: Location, invasion, retention Nat. Rev. Microbiol. 2005 3 819 823 10.1038/nrmicro1249 16175174 9. CDC Chagas Disease: Epidemiology and Risk Factors Available online: https://www.cdc.gov/parasites/chagas/epi.html (accessed on 3 August 2021) 10. Altcheh J. Castro L. Dib J.C. Grossmann U. Huang E. Moscatelli G. Pinto Rocha J.J. Ramírez T.E. Prospective, historically controlled study to evaluate the efficacy and safety of a new paediatric formulation of nifurtimox in children aged 0 to 17 years with Chagas disease one year after treatment (CHICO) PLoS Negl. Trop. Dis. 2021 15 e0008912 10.1371/journal.pntd.0008912 33412557 11. Monzote L. Scherbakov A.M. Scull R. Satyal P. Cos P. Shchekotikhin A.E. Gille L. Setzer W.N. Essential Oil from Melaleuca leucadendra: Antimicrobial, Antikinetoplastid, Antiproliferative and Cytotoxic Assessment Molecules 2020 25 5514 10.3390/molecules25235514 12. Rottini M.M. Amaral A.C.F. Ferreira J.L.P. Oliveira E.S.C. Silva J.R.d. Taniwaki N.N. Santos A.R.d. Almeida-Souza F. de Souza C.d.F. Calabrese K.D. Endlicheria bracteolata (Meisn.) Essential Oil as a Weapon Against Leishmania amazonensis: In Vitro Assay Molecules 2019 24 2525 10.3390/molecules24142525 13. Lynch M.C. Cortelli S.C. McGuire J.A. Zhang J. Ricci-Nittel D. Mordas C.J. Aquino D.R. Cortelli J.R. The effects of essential oil mouthrinses with or without alcohol on plaque and gingivitis: A randomized controlled clinical study BMC Oral Health 2018 18 6 10.1186/s12903-017-0454-6 29321067 14. Shasany A.K. Lal R.K. Patra N.K. Darokar M.P. Garg A. Kumar S. Khanuja S.P.S. Phenotypic and RAPD diversity among Cymbopogon winterianus Jowitt accessions in relation to Cymbopogon nardus Rendle Genet. Resour. Crop Evol. 2000 47 553 559 10.1023/A:1008712604390 15. Katiyar R. Gupta S. Yadav K. Cymbopogon Winterianus: An Important Species for Essential Java Citronella Oil and Medicinal Value Proceedings of the National Conference on Forest Biodiversity: Earth’s Living Treasure 22 May 2011 115 118 16. Rao V.P.S. Pandey D. Extraction of Essential Oil and Its Applications Ph.D. Thesis National Institute of Technology Rourkela, India 2006 17. Zellner B.D.A. Dugo P. Dugo G. Mondello L. Chapter 4: Natural Variability of Essential Oil Components Handbook of Essential Oils CRC Press Boca Raton, FA, USA 2015 104 143 18. Jurevičiūtė R. Ložienė K. Bruno M. Maggio A. Rosselli S. Composition of essential oil of lemon thyme (Thymus × citriodorus) at different hydrodistillation times Nat. Prod. Res. 2019 33 80 88 10.1080/14786419.2018.1434642 29394873 19. Hanif M.A. Nisar S. Khan G.S. Mushtaq Z. Zubair M. Essential Oils Essential Oil Research Springer International Publishing Cham, Switzerland 2019 3 17 20. Bergman M.E. Bhardwaj M. Phillips M.A. Cytosolic geraniol and citronellol biosynthesis require a Nudix hydrolase in rose-scented geranium (Pelargonium graveolens) Plant J. 2021 107 493 510 10.1111/tpj.15304 33949016 21. Christoforides E. Fourtaka K. Andreou A. Bethanis K. X-ray crystallography and molecular dynamics studies of the inclusion complexes of geraniol in β-cyclodextrin, heptakis (2,6-di-O-methyl)-β-cyclodextrin and heptakis (2,3,6-tri-O-methyl)-β-cyclodextrin J. Mol. Struct. 2020 1202 127350 10.1016/j.molstruc.2019.127350 22. Gutensohn M. Orlova I. Nguyen T.T.H. Davidovich-Rikanati R. Ferruzzi M.G. Sitrit Y. Lewinsohn E. Pichersky E. Dudareva N. Cytosolic monoterpene biosynthesis is supported by plastid-generated geranyl diphosphate substrate in transgenic tomato fruits Plant J. 2013 75 351 363 10.1111/tpj.12212 23607888 23. Ganjewala D. Cymbopogon essential oils: Chemical compositions and bioactivities Int. J. Essent. Oil Ther. 2009 3 56 65 24. Akhila A. Essential Oil-Bearing Grasses The genus Cymbopogon CRC Press London, UK 2010 9780849378577 25. Khanuja S.P.S. Shasany A.K. Pawar A. Lal R.K. Darokar M.P. Naqvi A.A. Rajkumar S. Sundaresan V. Lal N. Kumar S. Essential oil constituents and RAPD markers to establish species relationship in Cymbopogon Spreng. (Poaceae) Biochem. Syst. Ecol. 2005 33 171 186 10.1016/j.bse.2004.06.011 26. Beneti S.C. Rosset E. Corazza M.L. Frizzo C.D. Di Luccio M. Oliveira J.V. Fractionation of citronella (Cymbopogon winterianus) essential oil and concentrated orange oil phase by batch vacuum distillation J. Food Eng. 2011 102 348 354 10.1016/j.jfoodeng.2010.09.011 27. Simic A. Rančic A. Sokovic M.D. Ristic M. Grujic-Jovanovic S. Vukojevic J. Marin P.D. Essential Oil Composition of Cymbopogon winterianus and Carum carvi. and Their Antimicrobial Activities Pharm. Biol. 2008 46 437 441 10.1080/13880200802055917 28. Kakaraparthi P.S. Srinivas K.V.N.S. Kumar J.K. Kumar A.N. Rajput D.K. Sarma V.U.M. Variation in the essential oil content and composition of Citronella (Cymbopogon winterianus Jowitt.) in relation to time of harvest and weather conditions Ind. Crops Prod. 2014 61 240 248 10.1016/j.indcrop.2014.06.044 29. Koba K. Sanda K. Guyon C. Raynaud C. Chaumont J.-P. Nicod L. In vitro cytotoxic activity of Cymbopogon citratus L. and Cymbopogon nardus L. essential oils from Togo Bangladesh J. Pharmacol. 2008 4 29 34 10.3329/bjp.v4i1.1040 30. Kpoviessi S. Bero J. Agbani P. Gbaguidi F. Kpadonou-Kpoviessi B. Sinsin B. Accrombessi G. Frédérich M. Moudachirou M. Quetin-Leclercq J. Chemical composition, cytotoxicity and in vitro antitrypanosomal and antiplasmodial activity of the essential oils of four Cymbopogon species from Benin J. Ethnopharmacol. 2014 151 652 659 10.1016/j.jep.2013.11.027 24269775 31. Tofiño-Rivera A. Ortega-Cuadros M. Galvis-Pareja D. Jiménez-Rios H. Merini L.J. Martínez-Pabón M.C. Effect of Lippia alba and Cymbopogon citratus essential oils on biofilms of Streptococcus mutans and cytotoxicity in CHO cells J. Ethnopharmacol. 2016 194 749 754 10.1016/j.jep.2016.10.044 27765606 32. Scherer R. Wagner R. Duarte M.C.T. Godoy H.T. Composição e atividades antioxidante e antimicrobiana dos óleos essenciais de cravo-da-índia, citronela e palmarosa Rev. Bras. Plantas Med. 2009 11 442 449 10.1590/S1516-05722009000400013 33. Leite B.L.S. Bonfim R.R. Antoniolli A.R. Thomazzi S.M. Araújo A.A.S. Blank A.F. Estevam C.S. Cambui E.V.F. Bonjardim L.R. Albuquerque Júnior R.L.C. Assessment of antinociceptive, anti-inflammatory and antioxidant properties of Cymbopogon winterianus leaf essential oil Pharm. Biol. 2010 48 1164 1169 10.3109/13880200903280000 20738158 34. Silva M.R. Ximenes R.M. da Costa J.G.M. Leal L.K.A.M. de Lopes A.A. de Barros Viana G.S. Comparative anticonvulsant activities of the essential oils (EOs) from Cymbopogon winterianus Jowitt and Cymbopogon citratus (DC) Stapf. in mice Naunyn Schmiedebergs Arch. Pharmacol. 2010 381 415 426 10.1007/s00210-010-0494-9 20237771 35. Hasim H. Nasution S.P. Kurniawati S.O. Rachmawati I. Cytotoxic Activity of Citral from Cymbopogon nardus as Anticancer of MCM-B2 Cell Curr. Biochem. 2020 7 29 36 10.29244/cb.7.1.4 36. Sinha S. Jothiramajayam M. Ghosh M. Mukherjee A. Evaluation of toxicity of essential oils palmarosa, citronella, lemongrass and vetiver in human lymphocytes Food Chem. Toxicol. 2014 68 71 77 10.1016/j.fct.2014.02.036 24650756 37. Queiroz T.B. Santos G.F. Ventura S.C. Hiruma-Lima C.A. Gaivão I.O.M. Maistro E.L. Cytotoxic and genotoxic potential of geraniol in peripheral blood mononuclear cells and human hepatoma cell line (HepG2) Genet. Mol. Res. 2017 16 1 12 10.4238/gmr16039777 38. Gateva S. Jovtchev G. Stankov A. Georgieva A. Dobreva A. Mileva M. The potential of geraniol to reduce cytotoxic and genotoxic effects of MNNG in plant and human lymphocyte test-systems S. Afr. J. Bot. 2019 123 170 179 10.1016/j.sajb.2019.03.005 39. Machado M. Pires P. Dinis A.M. Santos-Rosa M. Alves V. Salgueiro L. Cavaleiro C. Sousa M.C. Monoterpenic aldehydes as potential anti-Leishmania agents: Activity of Cymbopogon citratus and citral on L. infantum, L. tropica and L. major Exp. Parasitol. 2012 130 223 231 10.1016/j.exppara.2011.12.012 22227102 40. Santin M.R. dos Santos A.O. Nakamura C.V. Dias Filho B.P. Ferreira I.C.P. Ueda-Nakamura T. In vitro activity of the essential oil of Cymbopogon citratus and its major component (citral) on Leishmania amazonensis Parasitol. Res. 2009 105 1489 1496 10.1007/s00436-009-1578-7 19669793 41. Ceole L.F. Cardoso M.D.G. Soares M.J. Nerolidol, the main constituent of Piper aduncum essential oil, has anti- Leishmania braziliensis activity Parasitology 2017 144 1179 1190 10.1017/S0031182017000452 28482935 42. Carneiro J.N.P. Albuquerque R.S. Leite N.F. Machado A.J.T. de Brito D.I.V. Rolón M. Vega C. Coronel C. Coutinho H.D.M. Morais-Braga M.F.B. Avaliação Da Atividade Tripanocida, Leishmanicida e Citotóxica do Geraniol e Citronelal Cad. Cult. Ciênc. 2015 13 29 36 10.14295/cad.cult.cienc.v13i2.841 43. Brito A.M.G. Avaliação da Atividade Antileishmanial dos óleos Essenciais das Plantas Cymbopogon citratus (DC.) Stapf., Eucalyptus citriodora Hook., Mentha arvensis L., e Mentha piperita L. Ph.D. Thesis Tiradente University Aracaju, Brazil 2019 44. Essid R. Rahali F.Z. Msaada K. Sghair I. Hammami M. Bouratbine A. Aoun K. Limam F. Antileishmanial and cytotoxic potential of essential oils from medicinal plants in Northern Tunisia Ind. Crops Prod. 2015 77 795 802 10.1016/j.indcrop.2015.09.049 45. Ogungbe I. Setzer W. In-silico Leishmania Target Selectivity of Antiparasitic Terpenoids Molecules 2013 18 7761 7847 10.3390/molecules18077761 23823876 46. Vidhya V.M. Dubey V.K. Ponnuraj K. Identification of two natural compound inhibitors of Leishmania donovani Spermidine Synthase (SpdS) through molecular docking and dynamic studies J. Biomol. Struct. Dyn. 2018 36 2678 2693 10.1080/07391102.2017.1366947 28797195 47. Youssefi M.R. Moghaddas E. Tabari M.A. Moghadamnia A.A. Hosseini S.M. Farash B.R.H. Ebrahimi M.A. Mousavi N.N. Fata A. Maggi F. In Vitro and In Vivo Effectiveness of Carvacrol, Thymol and Linalool against Leishmania infantum Molecules 2019 24 2072 10.3390/molecules24112072 48. Ueda-Nakamura T. Mendonça-Filho R.R. Morgado-Díaz J.A. Korehisa Maza P. Prado Dias Filho B. Aparício Garcia Cortez D. Alviano D.S. do Rosa M.S.S. Lopes A.H.C.S. Alviano C.S. Antileishmanial activity of Eugenol-rich essential oil from Ocimum gratissimum Parasitol. Int. 2006 55 99 105 10.1016/j.parint.2005.10.006 16343984 49. Muhd Haffiz J. Norhayati I. Getha K. Nor Azah M.A. Mohd Ilham A. Lili Sahira H. Roshan Jahn M.S. Muhd Syamil A. Chemical composition and in vitro antitrypanosomal activity of fractions of essential oil from Cymbopogon nardus L. Trop. Biomed. 2013 30 9 14 23665703 50. Rojas J. Ronceros S. Palacios O. Sevilla C. Efecto anti-Trypanosoma cruzi del aceite esencial de Cymbopogon citratus (DC) Stapf (Hierba luisa) en ratones Balb/c An. Fac. Med. 2012 73 7 10.15381/anales.v73i1.803 51. Costa S. Cavadas C. Cavaleiro C. Salgueiro L. do Céu Sousa M. In vitro susceptibility of Trypanosoma brucei brucei to selected essential oils and their major components Exp. Parasitol. 2018 190 34 40 10.1016/j.exppara.2018.05.002 29778466 52. Cardoso J. Soares M.J. In vitro effects of citral on Trypanosoma cruzi metacyclogenesis Mem. Inst. Oswaldo Cruz 2010 105 1026 1032 10.1590/S0074-02762010000800012 21225200 53. Azeredo C.M.O. Soares M.J. Combination of the essential oil constituents citral, eugenol and thymol enhance their inhibitory effect on Crithidia fasciculata and Trypanosoma cruzi growth Rev. Bras. Farmacogn. 2013 23 762 768 10.1590/S0102-695X2013000500007 54. Kouassi E. Coulibaly I. Rodica P. Pintea A. Ouattara S. Odagiu A. HPLC Phenolic Compounds Analysis and Antifungal Activity of extract’s from Cymbopogon citratus (DC) Stapf against Fusarium graminearum and Fusarium oxysporum sp. tulipae. J. Sci. Res. Rep. 2017 14 1 11 10.9734/JSRR/2017/33810 55. Molina-Garza Z.J. Bazaldúa-Rodríguez A.F. Quintanilla-Licea R. Galaviz-Silva L. Anti-Trypanosoma cruzi activity of 10 medicinal plants used in northeast Mexico Acta Trop. 2014 136 14 18 10.1016/j.actatropica.2014.04.006 24742906 56. Santoro G.F. Cardoso M.G. Guimarães L.G.L. Freire J.M. Soares M.J. Anti-proliferative effect of the essential oil of Cymbopogon citratus (DC) Stapf (lemongrass) on intracellular amastigotes, bloodstream trypomastigotes and culture epimastigotes of Trypanosoma cruzi (Protozoa: Kinetoplastida) Parasitology 2007 134 1649 1656 10.1017/S0031182007002958 17686189 57. Moreno É.M. Leal S.M. Stashenko E.E. García L.T. Induction of programmed cell death in Trypanosoma cruzi by Lippia alba essential oils and their major and synergistic terpenes (citral, limonene and caryophyllene oxide) BMC Complement. Altern. Med. 2018 18 225 10.1186/s12906-018-2293-7 30053848 58. dos Anjos D.O. Sobral Alves E.S. Gonçalves V.T. Fontes S.S. Nogueira M.L. Suarez-Fontes A.M. Neves da Costa J.B. Rios-Santos F. Vannier-Santos M.A. Effects of a novel β–lapachone derivative on Trypanosoma cruzi: Parasite death involving apoptosis, autophagy and necrosis Int. J. Parasitol. Drugs Drug Resist. 2016 6 207 219 10.1016/j.ijpddr.2016.10.003 27770751 59. Shimadzu Corporation Gas Chromatography-Mass Spectrometry (GC-MS) Available online: https://www.shimadzu.eu.com/sites/shimadzu.seg/files/SEG/GCMSBASIC.pdf (accessed on 15 April 2022) 60. Shimadzu Corporation Relative Retention Available online: https://www.ssi.shimadzu.com/products/gas-chromatography-mass-spectrometry/relative_retention.html (accessed on 15 April 2022) 61. Le-Senne A. Muelas-Serrano S. Fernández-Portillo C. Escario J.A. Gómez-Barrio A. Biological characterization of a beta-galactosidase expressing clone of Trypanosoma cruzi CL strain Mem. Inst. Oswaldo Cruz 2002 97 1101 1105 10.1590/S0074-02762002000800006 12563473 62. Roldos V. Nakayama H. Rolón M. Montero-Torres A. Trucco F. Torres S. Vega C. Marrero-Ponce Y. Heguaburu V. Yaluff G. Activity of a hydroxybibenzyl bryophyte constituent against Leishmania spp. and Trypanosoma cruzi: In silico, in vitro and in vivo activity studies Eur. J. Med. Chem. 2008 43 1797 1807 10.1016/j.ejmech.2007.11.007 18192088 63. Vega C. Rolón M. Martínez-Fernández A.R. Escario J.A. Gómez-Barrio A. A new pharmacological screening assay with Trypanosoma cruzi epimastigotes expressing beta-galactosidase Parasitol. Res. 2005 95 296 298 10.1007/s00436-005-1300-3 15682334 64. Mikus J. Steverding D. A simple colorimetric method to screen drug cytotoxicity against Leishmania using the dye Alamar Blue® Parasitol. Int. 2000 48 265 269 10.1016/S1383-5769(99)00020-3 11227767

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093407 materials-15-03407 Article Investigation of Concrete Shrinkage Reducing Additives Statkauskas Martynas * https://orcid.org/0000-0002-9836-1239 GRINYS Audrius https://orcid.org/0000-0001-8176-4413 Vaičiukynienė Danutė Li Ning Academic Editor Faculty of Civil Engineering and Architecture, Kaunas University of Technology, Studentų Str. 48, LT-51367 Kaunas, Lithuania; audrius.grinys@ktu.lt (A.G.); danute.vaiciukyniene@ktu.lt (D.V.) * Correspondence: martynas.statkauskas@ktu.edu; Tel.: +370-63-743883 09 5 2022 5 2022 15 9 340729 3 2022 05 5 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This paper analyzes the efficiency of shrinkage reducing additives for the shrinkage deformations of ordinary Portland cement (OPC) concrete and its mechanical properties. OPC concrete was modified with an organic compound-based shrinkage reducing additive (SRA), quicklime, polypropylene fiber, and hemp fiber. It was found that a combination of 2.5% quicklime and 1.5% SRA led to the highest reduction in shrinkage deformations in concrete, and the values of shrinkage reached up to 40.0%. On the contrary, compositions with 1.5% SRA were found to have a significant reduction in compressive strength after 100 freeze-thaw cycles. Hemp fiber did not show a significant shrinkage reduction, but it is an environmentally friendly additive, which can improve OPC concrete flexural strength. Polypropylene fiber can be used in conjunction with shrinkage reducing additives to improve other mechanical properties of concrete. It was observed that 3.0 kg/m3 of polypropylene fiber in concrete could increase flexural strength by 11.7%. Moreover, before degradation, concrete with polypropylene fiber shows high fracture energy and decent residual strength of 1.9 MPa when a 3.5 mm crack appears. The tests showed a compressive strength decrease in all compositions with shrinkage reducing additives and its combinations after 28 days of hardening. concrete shrinkage shrinkage reducing additives quicklime polypropylene fiber hemp fiber This research received no external funding. ==== Body pmc1. Introduction Concrete is one of the most common building materials in the world due to its affordable price and particularly good mechanical properties. Nowadays, wide concrete surfaces with wide open surfaces are especially popular in the concrete industry: thin-walled structures, monolithic elements of bridges, or seamless floors. During the hardening of OPC concrete, shrinkage deformations may occur which could lead to various undesirable cracks and fissures. Many scientists are looking for ways to reduce or eliminate the shrinkage of concrete without changing the main properties of concrete [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]. Shrinkage of concrete can be described as a decrease in volume, regardless of its consistency, which can result from a variety of chemical reactions or a decrease in relative humidity or a slightly saturated porous system. Deformation of materials is often divided into chemical, plastic, carbonization, autogenous, and drying shrinkage and depends on the initial setting time and hydration mechanism [1]. In the early stages of hydration, chemical shrinkage occurs. It is caused by newly formed hydration products with a smaller volume compared to the volume of initial components [2]. Plastic shrinkage is defined as the loss of water by evaporation after the addition of fresh concrete until it becomes hard [3]. Various chemical reactions between carbon dioxide and cement hydration products cause shrinkage of carbonation. In some literature [2,4], autogenic shrinkage of concrete is described as the result of self-drying and chemical processes. This drastically reduces water demand and the water to a cement ratio that is between 0.2 and 0.42. Lack of moisture in the environment causes internal cement dehydration and consequent drying shrinkage. Many authors report that an effective way to reduce shrinkage deformations is to use fibers and shrinkage-reducing additives that improve the properties of concrete [5,6,7,8,9,10,11,12,13,14,15,16,17,18]. Ullah et al. [5] investigated early age autogenous shrinkage using different types of fibrous materials (steel, plastic, and glass). The study found that a dose of 0.38% fiber volume reduced autogenous shrinkage. Using this number of fibers, it was found that polypropylene fibers had a better effect on autogenous shrinkage compared to steel or glass fiber. Park et al. [6] studied high-performance cement composites containing polypropylene and fiberglass. The findings showed that properties such as compressive strength or tensile strength were higher when polypropylene fiber was used in cement composites compared to glass fiber. The researchers also found that the addition of any of these fibers (>1% by weight) would reduce the shrinkage of the cement composites. It was also found that higher amounts of fiber led to higher efficiency. Many studies [5,6,7,8,9,10] analyzed the performance of SRA (shrinkage reducing additives) in concrete. Most authors concluded that even a small amount of SRA is sufficient to reduce shrinkage deformations. Zhan and He [7] concluded that SRA is used to delay the hydration reaction of OPC in the early stages due to organic compounds. These compounds reduce the polarity of the OPC and increase the specific surfaces, so more water is needed for hydration. In general, SRA is more effective than geopolymeric materials because the cement matrix does not crack so easily; the cracks are much smaller in width; and large pores of the OPC matrix are reduced. Saliba et al. [8] studied the long-term shrinkage of concrete when SRA was used. The study found that the addition of SRA (1% by weight of OPC) to the concrete reduced the long-term drying shrinkage to 56% and 31% after 7 days of curing at a water to cement ratio of 0.65 and 0.43, respectively. The authors [11] investigated the influence of the propylene glycol effect on concrete shrinkage and mechanical properties using different water/cement ratios. The results showed a decrease in slump and compression with tensile strength (a higher water/cement ratio leads to an even greater decrease). The use of SRA also reduced the free shrinkage (up to 50%) caused by drying. Many authors [12,13,14,15,16] agree that CaO expansive additives are an excellent way to compensate for concrete shrinkage deformations. CaO additives are a great way to deal with cracks in concrete due to their ability to expand (~90%) by reacting with water. According to Zhao et al. [12], the addition of a CaO additive enriches the hydration process of the cement, especially when a 2% dose is used. The hydration process of the cement intensifies by increasing the temperature of the mixture due to the exothermic reaction of CaO hydration. Polat et al. [13] showed that after 28 days of hardening, the autogenous shrinkage of the concrete was reduced by 42%, 47%, and 80% using an expansive CaO dose of 2.5%, 5.0%, and 7.5% (wt. of cement), respectively. Previous studies [15,16] show that expansive additives such as CaO led to faster hydration, resulting in rapid expansion in the early stages, but much slower in the later stages. Therefore, the use of MgO additives reduces shrinkage at a later stage due to the slow rate of hydration, which results in long-term slow expansion. For this reason, magnesium oxide additives are a better choice for long-term shrinkage compensation. Wang et al. [17] investigated extremely high-quality concrete based on various expansive additives such as highly reactive magnesium oxide, moderately reactive magnesium oxide, and calcium oxide. The study shows that CaO additives better compensate for autogenous shrinkage because they are less sensitive to moisture compared to MgO-based additives. Çomak et al. [18] studied hemp fibers in reinforced cement mortars with different ratios (0, 1, 2, and 3% by volume of the mix) and lengths (6, 12 and 18 mm). Studies show that 2% of hemp fiber has a significantly higher effect on the mechanical properties of cement mortars. The authors concluded that the best results are obtained using 12 mm long and 2–3% (wt. of mix volume) hemp fiber. The aim of this study was to investigate the effectiveness of various additives and their combinations in monitoring the influence of shrinkage deformations on concrete mixtures and its mechanical properties. OPC concrete was modified with SRA (organic compound shrinkage reducing additive), quicklime, polypropylene, and hemp fiber to determine the effect of different additives on the properties (density, consistency, air content) of the fresh concrete mix and mechanical properties and durability of hardened concrete (compressive, flexural strength, freeze-thaw resistance, and porosity parameters). 2. Materials Ordinary cement CEM I 42.5 R with the fineness of 390 m2/kg was used. The powder of quicklime CL 90 with the fineness of 300 m2/kg and reactivity class R5 was incorporated. The amount of quicklime was 1.5% and 2.5% (wt. of OPC) The chemical composition of OPC and quicklime is presented in Table 1. This experimental study was performed using hemp and polypropylene fibers, and liquid phase shrinkage reducing agents (SikaControl −50) as well. In all mixtures, the same water/cement ratio of 0.53 was applied. Coarse aggregate gravel (fr. 4/16 mm) was used with its particle density of 2600 kg/m3, while fine aggregate sand (fr. 0/4 mm) with its particle density of 2650 kg/m3 was incorporated. In all concrete mixtures, the same amounts of coarse and fine aggregates were added (1006 kg/m3 and 870 kg/m3, respectively). The particles size distribution of concrete aggregate is shown in Figure 1 (curve in red). The granulometric curve of the mixture for aggregates was formed, and it was determined that the curve did not exceed the Lithuanian Standard LST 1974:2012 [19] requirements. To reduce the amount of water in concrete, polycarboxylate polymer-based SP (superplasticizer) was used. The admixture has the density of 1.06 ± 0.02 kg/l, pH of 4.4 ± 1, total chloride ion content of <0.1%, and equivalent sodium oxide content of <0.4%. The dosage of superplasticizer was 0.5% (wt. of OPC). SRA based on organic compound has the density of 0.935 ± 0.02 kg/L, total chlorine ion content of <0.1%, and equivalent sodium oxide content of <0.5%. The dosage of SRA was 0.5% and 1.5% (wt. of OPC). Two types of fiber (polypropylene and hemp) were incorporated in the concrete. The density of polypropylene fiber was 0.91 g/cm3, melting point of 160–170 °C, tensile strength of 500 MPa, tensile modulus of elasticity of 5.2 GPa, length of 38 mm, and diameter of 0.7 mm. Hemp fiber has a density of 0,16 g/cm3, melting point of 140 °C, length of 30–60 mm, and diameter of 0.6 mm. For this research, 3 kg/m3 of each fiber were used in concrete. Under the laboratory conditions, various mixtures (Table 2) were made to examine the efficiency of different additives and their combinations while observing the influence on the shrinkage deformations in concrete mixtures as well as the mechanical properties. By combination of initial materials, 11 different mixture compositions with the same water/cement ratio (0.53) were prepared (Table 2). 3. Experimental Procedure The granulometry of aggregates was performed according to EN 933-1 (Figure 1). Three fresh concrete tests were made: the slump was determined following standard EN 12350-2, air content of compacted fresh concrete according to standard EN 12350-7, and the density of fresh concrete according to standard EN 12350-6. The concrete mixtures were prepared in the “Zyklos” concrete mixer. The specimens were formed following standard EN 206. The sizes of specimens were standard cubic (100 × 100 × 100 mm) and prism (75 × 75 × 250 mm) which compacted on the vibrational table. The specimens were hydrated for about 20 h in the molds, and, after that they were demolded, cubic specimens were cured in water for 28 days, while prism specimens were cured in air for 90 days. Six hardened concrete tests were made: the density of hardened concrete specimens was determined according to standard EN 12390-6, the compressive strength of hardened concrete according to following standard EN 12390-3, and the flexural strength of hardened concrete according to standard EN 12390-5. Concrete fracture energy was calculated according to CMOD (crack mouth opening displacement) curves. Areas under the CMOD curves were found by using the “Originpro” software [20]. The shrinkage measurement of concrete was determined according to standard EN 12390-16. The concrete prisms length was measured after 3, 7, 14, 28, 56, and 90 days of hardening (Figure 2). Concrete shrinkage strain was calculated following Equation (1):(1) εcst,t0 = l(t0) − lcstL0; where: εcst,t0 is the total shrinkage strain of the specimen at the time t; L0 is gauge length; l(t0) is the initial length at the time t0; lcst is the length at time t. The concrete prism weight was evaluated after 3, 7, 14, 28, 56, and 90 days of hardening, and the change in mass of concrete was calculated according to the following Equation (2):(2) Xcs = Wcst − Wt0Wt0; where: Xcs is total change in mass of the specimen at the time t; Wcst is the initial weight at the time t; Wt0 is the weight at time t. Freeze-thaw resistance of concrete was determined by volumetric freezing after immersion in water following Lithuanian standard LST 1428.17:2016 [21]. This test method was used to find out the effect of 100 freeze-thaw cycles on the compressive strength of concrete when different shrinkage reducing additives were incorporated. The freeze-thaw resistance test lasted about 35 days. The porosity parameters were set by measuring the kinetics of water adsorption according to Russian standard GOST 12730.4-78 [22]. This test method was used to find out total, open, and closed porosity of the concrete (Figure 3). Freeze-thaw resistance and porosity parameters test methods are very well described in the literature [23]. The microstructures of fibers and hardened cement pastes were determined according to scanning electron microscopy with a high-resolution scanning electron microscope (ZEISS EVO MA10). 4. Results 4.1. Fresh Concrete Test Results Test results showed an obvious change in the workability of fresh concrete properties (Table 3) when different additives are incorporated. A reference mixture slump value was 180 mm, resulting in the high workability of the S4 slump class. Most of the batches with earlier mentioned additives have the same or lower slump value than the reference mixture. The slump increased to 190 mm for concrete mixtures with 0.5% and 1.5% (wt. of OPC) of SRA. SRA slightly improved the workability of the concrete mixture because this additive reduces surface tension of the mixing water in the liquid stage, and free water appears in the fresh mixture. A similar explanation is provided in a previous study [5]. The slump slightly decreased in the concrete with 1.5% and 2.5% (wt. of OPC) of quicklime powder; also the workability of the concrete mixture slightly decreased. It was assumed that small amounts of quicklime powder do not significantly affect the slump class, but higher amounts (>2.5% wt. of OPC) of this additive could reduce the slump, because the hydration process of quicklime requires additional water in concrete. Similar observations were made in this study [24]. Concrete with polypropylene fiber decreased the slump value to 110 mm, resulting in the high workability of the S3 slump class. Concrete with hemp fiber decreased slump even more, to 60 mm, resulting in the medium workability of the S2 slump class. The reduction in workability could be explained by the high porosity of the fibers, which could absorb water. Similar observations were made by authors [25,26]. In addition, most of the specimens had acceptable slumps, and there was no detected concrete bleeding or segregation during the experiment. The fresh concrete density for a reference mixture was 2356 kg/m3; air content was 3.4%. Compared to the reference mixture, most of the selected shrinkage reducing additives did not have a significant influence on fresh concrete density. The highest density was obtained in concrete with 1.5 (% wt. of OPC) SRA, and the lowest in concrete with 3.0 kg/m3 hemp fiber. The highest air content was also obtained in concrete with 3.0 kg/m3 hemp fiber. High air content leads to an assumption that hemp fiber creates interaction between fresh concrete density and air content. The following study [23] explains hemp fiber influence on fresh concrete density and air content. The authors concluded that incorporation of hemp fibers in concrete mixtures notably increases voids’ content under the effect of entrapped air, particularly when the amount of fiber was increased. High air content could be related to the high fiber content, which creates a lot of pores and reduced density and content of pulp in the fresh state as well as poor dispersion of the fibers while the amount of fiber is high. Moreover, a formation of hemp balls is probable, causing heterogeneous parts in the cement matrix and preventing water from entering the concrete, this way making the composite less porous. The densities and air content of all other compositions remained quite similar to the reference mixture. 4.2. Hardened Concrete Test Results 4.2.1. Compressive Strength of Concrete The change in compressive strength of concrete modified with different additives (SRA, quicklime, polypropylene, and hemp fiber) and their combinations is given in Figure 4. The experiment revealed that the modification of concrete with additives had a significant effect on the compressive strength of the concrete. Reference specimens (CNTRL) without additives had the average compressive strength of 42.5 and 45.5 MPa after 7 and 28 days, respectively. The used additives led to the decrease in compressive strength after 7 and 28 days of hardening. Polypropylene fiber slightly reduces the strength of concrete after 7 and 28 days when compared with the reference mixture. Specimens with 3.0 kg/m3 polypropylene fiber (POL3.0) reduced compressive strength by 2.8% and 0.9% after 7 and 28 days, respectively. Similar results were obtained in the study [27] where polypropylene fibers do not particularly affect the compressive strength of concrete. Specimens with 3.0 kg/m3 hemp fiber (CNB3.0) reduced compressive strength by 6.1% and 7.9%. The following study [26] observation confirmed that hemp fibers do not improve concrete compressive strength, which decreases when the addition surpasses 0.25% due to the heterogeneous dispersion of the fibers in the form of balls. The highest decrease in compressive strength, when compared with the reference mixture, was obtained for specimens with the combination of 3.0 kg/m3 hemp fiber, 2.5% quicklime, and 1.5% SRA (CNB3.0Ca2.5SR1.5). Compressive strength was reduced by 15.3% and 16.9%. Specimens with 0.5% shrinkage reducing admixture (SR0.5) reduced compressive strength by 10.1% and 5.3% after 7 and 28 days, respectively. Specimens with 1.5% shrinkage reducing admixture (SR1.5) decreased compressive strength by 12.2% and 7.9%. It can be assumed that the more SRA admixture that is in the concrete, the greater the reduction in compressive strength. the observation was made that SRA slows concrete hydration reactions; in this way, slow formation of calcium silicate hydrate (C-S-H) causes a decrease in compressive strength [11]. The addition of 1.5% quicklime powder (Ca1.5) reduced compressive strength by 4.5% and 6.2% after 7 and 28 days, respectively. Specimens with 2.5% quicklime (Ca2.5) reduced compressive strength by 6.8% and 8.1%. It is assumed that a small amount of quicklime does not cause a huge loss in compressive strength but overdosing (>2.5% wt. of cement) can be expected to reduce the compressive strength quite sharply. The slowdown in the growth in compressive strength may be due to the high expansion stress generated by the hydration of quicklime [11]. The combination of quicklime and SRA reduced compressive strength even more. When 1.5% of quicklime and 1.5% of SRA (Ca1.5SR1.5) were used, compressive strength after 7 and 28 days was reduced by 12.9% and 10.3%, respectively. Moreover, when 2.5% of quicklime and 1.5% of SRA (Ca2.5SR1.5) were used, compressive strength after 7 and 28 days was reduced by 14.1% and 12.3%. It can be assumed that SRA and quicklime acting together can have an even greater negative effect on the compressive strength of concrete than acting alone. During the analysis of the densities of the concrete specimens used for the compressive strength test, the average densities of all compositions remained similar. The highest average density of 2423 kg/m3 was recorded in the composition SR1.5 and the lowest of 2307 kg/m3 in the composition CNB3.0Ca2.5SR1.5. Observing that the densities of the specimens containing 3.0 kg/m3 of hemp fiber were lower, it was decided to determine the relationship between the specimen density and fresh concrete air content (Figure 5). It is assumed that the more air involved in the fresh concrete, the lower the density of the hardened concrete specimen. It was also observed that the specimens with the lowest densities had the lowest compressive strengths. Thus, a correlation between the following indicators occurs: high amount of air content in fresh concrete leads to low density hardened concrete, this way leading to a lower compressive strength. Moreover, there is a possibility that the small differences between the densities could happen technologically due to the potentially unequal compaction times. 4.2.2. Flexural Strength of Concrete The change in flexural strength of concrete modified with different additives (SRA, quicklime, polypropylene, and hemp fiber) and their combinations is given in Figure 6. Reference specimens (CNTRL) without additives had the average flexural strength of 7.7 MPa. The incorporation of polypropylene fibers in concrete had contradictory results. Specimens with a combination of 3.0 kg/m3 polypropylene fiber, 2.5% quicklime, and 1.5% SRA (POL3.0Ca2.5SR1.5) showed the highest increase in flexural strength of 11.7%. Meanwhile, specimens only with 3.0 kg/m3 polypropylene fiber (POL3.0) showed the lowest values of flexural strength results; it decreased by 18.1%. At the design stage of the concrete compositions, an increase in flexural strength was expected to be seen in both compositions with polypropylene fiber, as in the study [25]. A decrease in flexural strength could be related to the poor dispersion of fibers. The interfacial transition zone of polypropylene fibers with OPC paste was investigated by using Scanning Electron Microscope (SEM) analysis (Figure 7a). It was determined that the surface of polypropylene fiber is relatively smooth and homogeneous which could be the reason for the reduction in flexural strength [28]. The use of hemp fibers in concrete had a positive impact on flexural strength results. Specimens with 3.0 kg/m3 hemp fiber (CNB3.0) increased flexural strength by 6.5%. The surface of hemp fiber is rougher than the surface of polypropylene fibers (Figure 7b). The reason for the increase in flexural strength could be an increased adhesion between the fiber and OPC-based matrix, due to its rough surface [28]. The SRA shrinkage reducing admixture for 0.5% led to a slight increase in flexural strength by 1.1% when compared with reference specimens, although specimens with 1.5% shrinkage reducing admixture (SR1.5) reduced flexural strength by 9.1%. It is assumed that a small amount of SRA does not negatively affect flexural strength but overdosing (≥1.5% wt. of OPC) can negatively affect concrete flexural strength. Similar flexural strength results were obtained with quicklime powder. Specimens with 1.5% quicklime (Ca1.5) increased flexural strength by 2.6%, and a large amount (2.5%) of quicklime (Ca2.5) decreased flexural strength by 3.9%. Concrete potential against fracture was determined by calculating fracture energy, according to study [20]. In this research, fracture energy was calculated to estimate hemp and polypropylene fiber toughness. Fracture energy can be calculated by finding an area under a flexural stress-strain curve until failure. An area under the curve shows the concrete ability to absorb energy. A larger area signifies that concrete can absorb more energy before failure. Area under the CMOD curve was found with software “Originpro” (Figure 8). Table 4 shows the calculated area according to study [29] for respective specimens. The reference mixture fracture energy is 132–166 N/m. The highest fracture energy was obtained in specimens with 3.0 kg/m3 polypropylene fiber: (POL3.0)646and 741 N/m, (POL3.0Ca2.5SR1.5)871 and 1050 N/m. The specimen (POL3.0Ca2.5SR1.5) reached the maximum flexural strength (8.5 MPa), and the specimen cracked but did not experience rapid rupture and continued to withstand the flexural load. The specimen withstood 26.7% of the maximum flexural load at the 0.5 mm crack and 27.2% at the 3.5 mm crack. This phenomenon is explained by the fact that, when the specimen is no longer able to withstand a high flexural load, a crack appears. Under continued loading, the width of the crack gradually increases, but as the crack opens, polypropylene fibers in the concrete structure engage and prevent the specimen from flexing completely. Thus, for this reason, specimens with polypropylene fiber have a residual flexural strength and a high fracture energy. Polypropylene fiber is a great choice to protect concrete from sudden cracking. This fiber is evenly distributed in the concrete, thus creating a kind of 3D grid, so it has excellent reinforcement properties of concrete, which help to take over concrete tensile stresses. Sudden cracking was observed in specimens with 3.0 kg/m3 (CNB3.0 and CNB3.0Ca2.5SR1.5) hemp fiber. The specimens did not reinforce concrete properly, and fracture energy was minimal. It is assumed that in order to avoid sudden concrete breakdown, it is advisable to choose polypropylene instead of hemp fiber, because polypropylene fiber absorbs tensile stresses and has a high fracture energy. 4.2.3. Drying Shrinkage of Concrete A free-drying shrinkage test was performed on all the specimens, as shown in Figure 9. Length of the specimens was measured at intervals of 1, 3, 7, 14, 28, 56, and 90 days. The tests showed that the reference specimen (CNTRL) average free-drying shrinkage was 0.410 mm/m. It was observed that mostly shrinkage occurs in the early stage of hardening. During the first 28 days, 79.5% of all contractions appeared. Meanwhile, during the rest of the test (29–90 days), the shrinkage of the samples was negligible. The largest concrete shrinkage deformations occur during the first 28 days, as during these days the OPC hydration is most intense. The intensive formation of the hydration products (calcium silicate hydrate) causes a sudden change in the structure of the concrete pores, which becomes the cause of shrinkage. Analyzing the shrinkage results after 90 days of curing, a reduction in shrinkage was observed in all concrete compositions when compared to the reference composition. The percentages of shrinkage reduction, when compared to reference specimen results, after 7, 28, and 90 days are given in Table 5. After analyzing the obtained research results, it could be stated that SRA and quicklime had a significant impact on concrete free-drying shrinkage reduction. It is assumed that a small amount of SRA (0.5–1.5% wt. of cement) in the concrete could significantly reduce concrete free-drying shrinkage to 28.3%. Similar experimental results are shown in study [7,8,9,10,11]. Meanwhile, a small amount of quicklime (1.5–2.5% wt. of cement) in the concrete can reduce shrinkage up to 21.5%. Both additives, depending on the amount applied, rapidly reduce the shrinkage of the concrete, and when combined, can show even better results and reduce shrinkage by as much as 40.0%. Theoretically, these two additives could reduce concrete shrinkage even more, but it should be very carefully considered whether too much of these additives would not affect the other mechanical properties of the concrete. Thus, the practical implementation of this idea would require further research, with larger dosages of additives. The use of hemp and polypropylene fiber to reduce concrete shrinkage was not as effective as expected. The use of these fibers alone can reduce shrinkage by only 5.9 and 9.3%. In order to obtain more detailed results, further studies should be performed with different fiber characteristics and dosages. While performing the free-drying shrinkage test, the changes in the mass of concrete specimens were observed, as shown in Figure 10. Test results showed that after 90 days of hardening, neither concrete composition lost more than 2% of the weight. The change in mass of the reference specimens after 9 days was 1.59%. The highest change in the weight of concrete was observed in the first days; as much as 34.0% of the total weight loss occurred during the first 3 days, and as much as 81.8% after 28 days of hardening. It is assumed that in the first days, the highest amount of free water evaporates from the concrete structure, resulting in the largest changes in the mass of the concrete. After noticing that most of the changes in length and weight occur during the first 28 days, it was decided to graph the relationship between these indicators. In the graph (Figure 11), all compositions of concrete mixes are arranged in descending order of shrinkage after 28 days. The relationship between the shrinkage and change in mass showed that as soon as shrinkage decreases, the change in mass increases. It is assumed that the more shrinkage deformations are reduced, the greater the change in mass can occur. 4.2.4. Freeze-Thaw Resistance of Concrete The freeze–thaw resistance of concrete is important for concrete structures which are used in cold countries. The performance of concrete modified with different additives (SRA, quicklime, polypropylene, and hemp fiber) and their combinations after 100 freezing-thawing cycles was investigated. All mixtures’ results were compared with the reference concrete. After 100 cycles, the samples were visually inspected (Figure 12a–k). Examination of freezing-thawing affected specimens showed a tendency for specimens containing 1.5% SRA to crack (Figure 12j,k) or to decompose completely (Figure 12e,h,i). This phenomenon is explained by the fact that a large amount of SRA prevents free water from escaping from the concrete, so when the freeze-thaw cycle occurs, the free water in concrete capillaries freezes and gradually destroys the structure of the specimen, weakening its mechanical properties. The compressive strength of the specimens was tested after 100 freezing and thawing cycles. Figure 13 illustrates compressive strength results after 100 freeze-thaw cycles. During the analysis of the compressive strength results after 100 freeze-thaw cycles, it was observed that in nine of the eleven compositions, a decrease in the compressive strength occurs compared to the initial compressive strength after 28 days of hardening. The tests showed that the reference specimen (CNTRL) increased by 3.7% (47.2 MPa) from the initial compressive strength (45.5 MPa). POL3.0 specimens increased compressive strength by 10.6%. The hemp fiber (CNB3.0) led to the decrease in compressive strength by 8.8%. Specimens with 1.5% and 2.5% quicklime (Ca1.5 and Ca2.5) decreased compressive strength by 4.2% and 4.3%, respectively. Specimens with 0.5% SRA (SR0.5) compressive strength decreased by 6.7%. Moreover, specimens with hemp fiber, quicklime, and SRA (CNB3.0Ca2.5SR1.5) lost 12.2% of their initial strength. The highest decrease in compressive strength was obtained in specimens with 1.5% SRA, but POL3.0Ca2.5SR1.5). SR1.5, Ca1.5SR1.5, Ca2.5SR1.5 specimens lost 100% of compressive strength due to complete degradation of specimens. Specimens (POL3.0Ca2.5 SR1.5) lost 44.3% of their initial compressive strength. It is assumed that none of aforementioned additives increases concrete resistance to freezing-thawing cycles. High SRA (≥1.5% wt. of cement) content can cause concrete cracking and deterioration of its mechanical properties. In order to use concrete with SRA in places where freezing-thawing cycles occur, it is advisable to incorporate systems that increase freeze-thaw resistance, such as air entrainers or prefabricated air bubbles. 4.2.5. Porosity Parameters of Concrete By measuring the kinetics of water adsorption, concrete porosity parameters were determined. Total, open, and closed porosity is calculated by using the water adsorption test [30]. The reference specimen adsorbed 4.81% of water after 48 h (Table 6). CNB3.0 specimens adsorbed the highest amount of water 21.6%, and Ca2.5 specimens adsorbed the lowest amount of water 6.2% by comparing with the reference composition. The relationship between specimen densities and water adsorption was observed. It assumed that concrete with higher densities has the lowest water adsorption. Thus, the lower the density of the concrete specimens, the easier it is for the concrete to adsorb water, so it is necessary to increase the density of the concrete or the closed porosity to reduce the water adsorption. The types of concrete for porosity results are illustrated in Figure 14. The total porosity of the reference specimen is 15.45% of which 70.9% is open porosity and 29.1% is closed porosity. CNB3.0 specimens had the highest porosity: total 18.68%, open 12.79%, and closed 5.89%. Compared to the reference specimen porosity, concrete with hemp fiber (CNB3.0) increased total porosity by 20.9%, open by 16.8%, and closed by 30.6%. It can be assumed that hemp fiber is a light, low-density material that tends to adsorb water, resulting in high porosity. The lowest total porosity of 13.79% was obtained in the specimen with a combination of 1.5% quicklime and 1.5% SRA (Ca1.5SR1.5) compared to the reference concrete total porosity that was decreased by 10.7%. The lowest open porosity of 10.4% was obtained in the specimen with 2.5% quicklime (Ca2.5); open porosity was decreased by 5.0%. The lowest closed porosity of 2.44% was obtained in the specimen with 1.5% SRA (SR1.5); closed porosity was decreased by 45.9%. After analyzing the obtained research results, it could be stated that concrete specimens with high open porosity are able to adsorb the highest amount of water, and specimens with higher closed porosity are able to withstand a greater number of freeze-thaw cycles. 5. Conclusions The following conclusions were drawn from the research: The results of the experiment showed a significant reduction in concrete shrinkage when local quicklime powder is used as a shrinkage reducing additive. It was found that a small amount of local quicklime powder (>2.5% wt. of OPC) can reduce concrete shrinkage up to 21.5%. In addition, interactions with other shrinkage-reducing additives, such as SRAs based on organic compounds, can achieve even better shrinkage-reducing results. The combination of 1.5% SRA and 2.5% quicklime, which reduced shrinkage deformations up to 40%, was recommended. The drying shrinkage is closely related to physical and mechanical properties of concrete as well. The compressive strength test showed a strength decrease in all investigated compositions after 28 days of hardening. The highest decrease about 16.9% was obtained in composition (CNB3.0Ca2.5SR1.5) and the lowest 0.9% in composition (POL3.0). Flexural strength tests showed the highest strength increase (11.7%) in concrete with 3.0 kg/m3 polypropylene fiber. Meanwhile, the lowest strength had (POL3.0Ca2.5SR1.5) specimens with the 2.5% quicklime and 1.5% SRA addition. Moreover, this concrete had the highest fracture energy and residual strength of 1.9 MPa when a 3.5 mm crack appeared. The parameters of water adsorption kinetics show that concretes with higher densities adsorb less water, while concretes with high closed porosity withstand higher amounts of freeze-thaw cycles. The water adsorption property of hemp fiber has been found to have a significant effect on the properties of concrete. Compared to the reference concrete, the use of 3.0 kg/m3 hemp fiber reduced concrete workability, but increased air content, which is the main factor in the increase in closed porosity of hardened concrete. Compositions with 1.5% SRA were found to have a significant reduction in compressive strength after 100 freeze-thaw cycles. This observation is closely related to the morphology of hemp fibers. Author Contributions Conceptualization, M.S. and A.G.; methodology, D.V.; formal analysis, D.V.; investigation, M.S.; resources, A.G.; writing—original draft preparation, M.S.; writing—review and editing, A.G. and D.V.; visualization, M.S.; supervision, A.G. and D.V. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Granulometric curve of concrete aggregates mix. Figure 2 Images of prism length measurement after 90 days; (a) setting zero; (b) length measurement. Figure 3 Images of measuring the kinetics for water adsorption; (a) dry specimens; (b) wet specimens; (c) specimen weight measurement; (d) specimen weight measurement in water. Figure 4 The compressive strength of concrete after 7 and 28 days. Figure 5 Relationship between specimen density after 28 days and air content. Figure 6 The change in flexural strength of concrete. Figure 7 The morphology of polypropylene and hemp fibers; (a) surface of polypropylene fiber; (b) surface of hemp fiber. Figure 8 The function of stress and CMOD of concrete. Figure 9 Free-drying shrinkage after 90 days of concrete hardening. Figure 10 The changes in mass of concrete after 3, 28, and 90 days. Figure 11 Relationship between shrinkage and change in mass after 28 days. Figure 12 Images of the degradation for concrete specimens after 100 freeze-thaw cycles; (a) CNTRL; (b) POL3.0; (c) CNB3.0; (d) SR0.5; (e) SR1.5; (f) Ca1.5; (g) Ca2.5; (h) Ca1.5SR1.5; (i) Ca2.5SR1.5; (j) POL3.0Ca2.5SR1.5; (k) CNB3.0Ca2.5SR1.5. Figure 13 The change in compressive strength of concrete after 100 freeze-thaw cycles. Figure 14 Total, open, and closed porosity of concrete. materials-15-03407-t001_Table 1 Table 1 Oxide compositions of OPC and calcium quicklime powder, %. Oxide CEM I 42.5 R CL 90 Q CaO 63.2 95.91 SiO2 20.4 0.52 Al2O3 4.0 0.06 Fe2O3 3.6 0.05 MgO 2.4 0.29 K2O 0.9 - Na2O 0.2 - SO3 3.1 - Loss on ignition (%) 2.15 1.04 materials-15-03407-t002_Table 2 Table 2 The mixtures of initial materials for 1 m3 concrete mixtures. Notation CEM I 42.5 R, kg Water, L Gravel (4/16), kg Sand (0/4), kg CL 90 Q, kg Fiber, kg Additives, (% wt. of OPC) Polypropylene Hemp SP SRA Reference 319 169 1006 870 - - - 0.5 POL3.0 319 169 1006 870 - 3.00 - 0.5 CNB3.0 319 169 1006 870 - - 3.00 0.5 SR0.5 319 169 1006 870 - - - 0.5 0.5 SR1.5 319 169 1006 870 - - - 0.5 1.5 Ca1.5 319 169 1006 870 4.79 - - 0.5 Ca2.5 319 169 1006 870 7.98 - - 0.5 Ca1.5SR1.5 319 169 1006 870 4.79 - - 0.5 1.5 Ca2.5SR1.5 319 169 1006 870 7.98 - - 0.5 1.5 POL3.0Ca2.5SR1.5 319 169 1006 870 7.98 3.00 - 0.5 1.5 CNB3.0Ca2.5SR1.5 319 169 1006 870 7.98 - 3.00 0.5 1.5 materials-15-03407-t003_Table 3 Table 3 Fresh concrete properties. Notation Slump, mm Density kg/m3 Air Content, % Reference 180 2356 3.4 POL3.0 110 2354 3.2 CNB3.0 60 2303 5.4 SR0.5 190 2349 3.8 SR1.5 190 2368 3.3 Ca1.5 170 2344 4.1 Ca2.5 160 2345 3.7 Ca1.5SR1.5 190 2365 3.1 Ca2.5SR1.5 180 2356 3.2 POL3.0Ca2.5SR1.5 120 2345 3.1 CNB3.0Ca2.5SR1.5 70 2310 4.5 materials-15-03407-t004_Table 4 Table 4 Fracture energy used to break the specimens. Notation Work, J Fracture Energy, N/m Residual Flexural Strength at 0.5 mm, MPa Residual Flexural Strength at 3.5 mm, MPa CNTRL 1.19 132 0 0 1.49 166 0 0 POL3.0 6.67 741 1.64 1.36 5.81 646 1.55 1.32 CNB3.0 1.99 221 0.36 0 1.83 203 0.07 0 SR0.5 1.15 128 0 0 1.40 156 0 0 SR1.5 1.18 131 0 0 1.12 124 0.05 0 Ca1.5 1.20 133 0 0 1.72 191 0.17 0 Ca2.5 1.22 136 0.15 0 1.25 139 0.16 0 Ca1.5SR1.5 1.03 114 0.04 0 1.66 184 0.11 0 Ca2.5SR1.5 0.76 84 0 0 1.61 179 0.08 0 POL3.0Ca2.5SR1.5 9.45 1050 2.27 2.10 7.84 871 1.73 1.73 CNB3.0Ca2.5SR1.5 1.26 140 0.04 0 1.52 169 0.21 0 materials-15-03407-t005_Table 5 Table 5 The shrinkage reduction of concrete specimens after 7, 28, and 90 days. Notation Shrinkage Reduction (%) After: 7 Days 28 Days 90 Days CNB3.0 8.5 12.9 5.9 POL3.0 9.9 8.6 9.3 Ca1.5 18.3 14.7 12.7 SR0.5 28.2 21.5 18.0 Ca2.5 19.7 18.4 21.5 CNB3.0Ca2.5SR1.5 31.0 25.2 27.3 SR1.5 36.6 30.1 28.3 Ca1.5SR1.5 42.3 33.7 32.7 POL3.0Ca2.5SR1.5 59.2 38.0 38.5 Ca2.5SR1.5 62.0 39.3 40.0 materials-15-03407-t006_Table 6 Table 6 Durability parameters of hardened concrete. Notation Water Adsorption, % Concrete Density, kg/m3 Kf Predicted Cycles CNTRL 4.81 2274 4.58 715 POL3.0 5.38 2258 3.57 573 CNB3.0 5.85 2188 5.12 770 SR0.5 5.55 2260 2.94 468 SR1.5 5.56 2283 2.14 327 Ca1.5 5.00 2279 3.79 609 Ca2.5 4.51 2306 4.13 658 Ca1.5SR1.5 4.75 2319 2.80 445 Ca2.5SR1.5 5.35 2289 2.40 376 POL3.0Ca2.5SR1.5 5.37 2270 3.14 503 CNB3.0Ca2.5SR1.5 5.44 2236 4.31 683 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Rezvani M. Proske T. Graubner C.A. Modelling the drying shrinkage of concrete made with limestone-rich cements Cem. Concr. Res. 2019 115 160 175 10.1016/j.cemconres.2018.09.003 2. Wu L. Farzadnia N. Shi C. Zhang Z. Wang H. Autogenous shrinkage of high-performance concrete: A review Constr. Build. Mater. 2017 149 62 75 10.1016/j.conbuildmat.2017.05.064 3. Wyrzykowski M. Ghourchian S. Münch B. Griffa M. Kaestner A. Lura P. Plastic shrinkage of mortars cured with a paraffin-based compound—Bimodal neutron/X-ray tomography study Cem. Concr. Res. 2021 140 106289 10.1016/j.cemconres.2020.106289 4. Gribniak V. Kaklauskas G. Kliukas R. Jakubovskis R. Shrinkage effect on short-term deformation behavior of reinforced concrete–When it should not be neglected Mater. Des. 2013 51 1060 1070 10.1016/j.matdes.2013.05.028 5. Ullah F. Al-Neshawy F. Punkki J. Early Age Autogenous Shrinkage of Fibre Reinforced Concrete Nord. Concr. Res. 2018 59 59 72 10.2478/ncr-2018-0015 6. Park J.J. Kim S. Shin W. Choi H.J. Park G.J. Yoo D.Y. High performance photocatalytic cementitious materials containing synthetic fibers and shrinkage-reducing admixture Materials 2020 13 1828 10.3390/ma13081828 7. Zhan P. He Z. Application of shrinkage reducing admixture in concrete: A review Constr. Build. Mater. 2019 201 676 690 10.1016/j.conbuildmat.2018.12.209 8. Arezoumandi M. Feasibility of crack free reinforced concrete bridge deck from materials composition perspective: A state of the art review Front. Struct. Civ. Eng. 2015 9 91 103 10.1007/s11709-015-0274-1 9. Mehdipour I. Khayat K.H. Effect of shrinkage reducing admixture on early expansion and strength evolution of calcium sulfoaluminate blended cement Cem. Concr. Compos. 2018 92 82 91 10.1016/j.cemconcomp.2018.06.002 10. Rahman M. Chen Y. Ibrahim A. Lindquist W. Tobias D. Krstulovich J. Gonzalez D. Hingi R. Study of Drying Shrinkage Mitigating Concrete Using Scaled Bridge Bays Int. J. Civ. Engin. 2020 18 73 10.1007/s40999-019-00460-z 11. Kioumarsi M. Azarhomayun F. Haji M. Shekarchi M. Effect of shrinkage Reducing Admixture on Drying Shrinkage of Concrte with Different w/c Ratios Materials 2020 13 5721 10.3390/ma13245721 33333959 12. Zhao H. Jiang K. Di Y. Xu W. Li W. Tian Q. Liu J. Effects of curing temperature and superabsorbent polymers on hydration of early-age cement paste containing a CaO-based expansive additive Mater. Struct. 2019 52 108 10.1617/s11527-019-1407-0 13. Polat R. Demirboga R. Khushefati W.H. Effects of nano and micro size of CaO and MgO, nano-clay and expanded perlite aggregate on the autogenous shrinkage of mortar Constr. Build. Mater. 2015 81 268 275 10.1016/j.conbuildmat.2015.02.032 14. Zhao H. Liu H. Wan Y. Ghantous R.M. Li J. Liu Y. Ni Y. Guan J. Mechanical properties and autogenous deformation behavior of early-age concrete containing pre-wetted ceramsite and CaO-based expansive agent Conctr. Build. Mater. 2021 267 120992 10.1016/j.conbuildmat.2020.120992 15. Mo L.W. Fang J.W. Hou W.H. Ji X.K. Yang J.B. Fan T.T. Wang H.L. Synergetic effects of curing temperature and hydration reactivity of MgO expansive agents on their hydration and expansion behaviours in cement pastes Constr. Build. Mater. 2019 207 206 217 10.1016/j.conbuildmat.2019.02.150 16. Zhao H. Hiang Y. Xie D. Xu W. Wang Y. Li H. Tian Q. Liu J. Effects of CaO-based and MgO-based expansion agent, curing temperature and restraint degree on pore structure of early-age mortar Constr. Build. Mater. 2020 257 119572 10.1016/j.conbuildmat.2020.119572 17. Wang Y. Tian Q. Li H. Wang Y. Humidity Sensitivity of Hydration of Expansive Agent and Its Expansive Efficiency in Ultra-High Performance Concrete Crystals 2022 12 195 10.3390/cryst12020195 18. Çomak B. Bideci A. Bideci Ö.S. Effects of hemp fibers on characteristics of cement based mortar Constr. Build. Mater. 2018 169 794 799 10.1016/j.conbuildmat.2018.03.029 19. LST 1974:2012 Rules for the Application of LST EN 206-1 and Additional National Requirements Lithuanian Standardization Department Vilnius, Lithuania 2012 20. Grinys A. Balamurugan M. Augonis A. Ivanauskas E. Mechanical properties and Durability of Rubberized and Glass Powder Modified Rubberized Concrete for Whitetopping Structures Materials 2021 14 2321 10.3390/ma14092321 33947072 21. LST 1428-17:2016 Concrete-Test method-Part 17: Determination of frost resistance to volumetric freezing and thawing Lithuanian Standardization Department Vilnius, Lithuania 2016 22. GOST 12730.4-78 Concretes. Methods of Determination of Porosity Parameters International Standard Moscow, Russia 2007 23. Grinys A. Augonis A. Daukšys M. Pupeikis D. Mechanical properties and durability of rubberized and SBR latex modified rubberized concrete Constr. Build. Mater. 2020 248 118584 10.1016/j.conbuildmat.2020.118584 24. Pan Z. Zhu Y. Zhang D. Chen N. Yang Y. Cai X. Effect of expansive agents on the workability, crack resistance and durability of shrinkage-compensating concrete with low contents of fibers Constr. Build. Mater. 2020 259 119768 10.1016/j.conbuildmat.2020.119768 25. Söylev T.A. Özturan T. Durability, physical and mechanical properties of fiber-reinforced concretes at low-volume fraction Constr. Build. Mater. 2014 73 67 75 10.1016/j.conbuildmat.2014.09.058 26. Ziane S. Khelifa M.R. Mezhoud S. Civil and environmental engineering reports a study of the durability of concrete reinforced with hemp fibers exposed to external sulfatic attack. Civil And Environmental Engineering Reports CEER 2020 30 0158 0184 27. Corinaldesi V. Nardinocchi A. Mechanical characterization of Engineered Cement-based Composites prepared with hybrid fibres and expansive agent Compos. Part B. 2016 98 389 396 10.1016/j.compositesb.2016.05.051 28. Stelea L. Filip I. Lisa G. Ichim M. Drobotă M. Sava C. Mureșan A. Characterisation of Hemp Fibres Reinforced Composites Using Thermoplastic Polymers as Matrices Polymers 2022 14 481 10.3390/polym14030481 35160470 29. Grinys A. Sivilevičius H. Pupeikis D. & Ivanauskas E. Fracture of concrete containing crumb rubber J. Civ. Eng. Manag. 2013 19 447 455 10.3846/13923730.2013.782335 30. Skripkiūnas G. Grinys A. Janavičius E. Porosity and durability of rubberized concrete Proceedings of the Second International Conference on Sustainable Construction Materials and Technologies Ancone, Italy 28–30 June 2010

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093001 materials-15-03001 Article A Study on Design of S-Duct Structures and Air Intake for Small Aircraft Applied to High Strength Carbon–Epoxy Composite Materials Lim Semyeong 1 Choi Won 2 https://orcid.org/0000-0001-8671-4378 Park Hyunbum 1* Jones AC Rhys Academic Editor Niendorf Thomas Academic Editor 1 Department of Mechanical Engineering, Kunsan National University, 558 Daehak-ro, Miryong-dong, Gunsan 54150, Korea; amuse3030@daum.net 2 Aero Machinery R&D Center, Hanhwa Aerospace, Asanvalleynam-ro, Dunpo-Myeon, Asan 31409, Korea; tailer49@daum.net * Correspondence: swordship@daum.net; Tel.: +82-063-469-4729; Fax: +82-063-469-7433 20 4 2022 5 2022 15 9 300120 3 2022 19 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Recently, many structural parts using composite materials are being applied to small aircraft and UAV in the world. The aim of this work is to design the engine intake structure of a small aircraft. For structural safety evaluation, a finite element analysis method was applied. In this work, structural design and numerical analysis of air intake and s-duct structures for small aircraft were performed. The target structure is composed of an s-duct and a cylindrical intake structure. Firstly, an investigation of the mechanical properties of carbon/epoxy material was conducted. The distributed pressure load and acceleration condition was applied to the structural design. The structural design load was investigated considering safety factors. The structural analysis was performed to analyze the validity of the design results. Through the structural analysis using the finite element analysis method, it was confirmed that the designed air intake structure is safe. The manufacturing of the prototype structure will be carried out based on the designed result. unmanned aerial vehicles air intakes structural design finite element analysis carbon–epoxy composite ==== Body pmc1. Introduction Applications of composite materials have been diversified for lightweight aircraft designs. This is because composite materials are very advantageous in weight lightening of the existing metallic material of the aircraft. Carbon fiber composite materials are mostly applied to design aircraft structures. In this study, carbon/epoxy composite materials were applied to carry out structural design and analysis research for the air intake structures where air is flowed inside the engine. As a result of reviewing the preceding research results in this study, it was determined that research on aircraft air intake component design has been significantly conducted. However, most previous studies were carried out on the aerodynamic shape design component. There were insufficient research results that applied composite materials to conduct lightweight design in terms of structural design. Therefore, carbon/epoxy composite materials were applied to carry out the lightweight design and analysis research for the engine intake in this work. As a result of investigation on previous study results related to aircraft intake design and analysis, Pedro David Bravo-Mosquera et al. conducted integration assessment of conceptual design and intake aerodynamics of a non-conventional air-to-ground fighter aircraft. These studies provided extensive data to evaluate the effects of specific aircraft design variables on dorsal intake performance, such as the integration of the cockpit, the boundary layer diverter, and several delta wing planforms [1]. Vittorio Vercillo et al. performed a study on modeling of the icing of air intake protection grids of aircraft engines. In this work, a physical model was validated for icing of air intake protection grids of engines [2]. F. Bagnoli et al. conducted research on failure analysis of an aircraft auxiliary power unit air intake door. In this work, the design of a new door as well as the material were introduced, thus obtaining the necessary functional improvements [3]. Zeyang Zhou et al. carried out a study on the mixed design of radar/infrared stealth for an advanced fighter intake and exhaust system. To improve the overall stealth performance of the aircraft’s intake and exhaust systems, a mixed design approach (MDA) is presented in this work [4]. Mohammad R. Soltani el al. performed a study on numerical simulation and parametric study of a supersonic intake. In this work, a computational fluid dynamics code was developed to compute the flow inside and around a supersonic external compression axisymmetric intake [5]. Wenbiao Gan et al. conducted a study on design optimization of a three-dimensional diffusing S-duct using a modified SST turbulent model. This paper examines design optimization of a three-dimensional diffusing S-duct using a modified k–ω shear stress transport (SST) turbulent model as a turbulence prediction method [6]. H. Kim et al. performed research on shape design optimization of embedded engine inlets for the N2B hybrid wing–body configuration. In this work, the N2B hybrid wing–body aircraft with embedded engines was conceptually designed to meet environmental and performance goals for the generation transport set [7]. Guoping Huang et al. conducted a study on the design method of the internal waverider inlet under the non-uniform upstream for inlet/forebody integration. In this work, a novel bump-integrated three-dimensional internal waverider inlet (IWI) design method is presented for high-speed inlet/forebody integration [8]. Lee M. et al. performed research on the conceptual redesign of the B-1B bomber inlets for improved supersonic performance. This paper presents a conceptual study of two alternative inlet concepts for the United States Air Force B-1B bomber to provide improved supersonic performance with the expansion of capabilities for high-altitude, high-speed flight at Mach 2.0 [9]. Shuvayan Brahmachary et al. conducted a study on multi-point design optimization of a high-performance intake for scramjet-powered ascent flight. This paper presents the results and insights obtained from a first-ever multi-point multi-objective optimization study of an axisymmetric scramjet intake conducted by means of surrogate-assisted evolutionary algorithms coupled with high-fidelity computational fluid dynamics [10]. Guoxing Song et al. performed a study on experimental simulation methodology and spatial transition of complex distortion fields in a S-shaped inlet. In this paper, a subsonic S-shaped inlet test rig was constructed, and eight configurations of curved-edge plate-type distortion generators were installed in the intake channel to create a complex distorted flow field downstream [11]. Michael M. Wojewidka et al. carried out a numerical study of complex flow physics and coherent structures of the flow through a convoluted duct. In this work, phase analysis of modes in convoluted ducts are reported in the public domain for the first time and offer promise of a tailored, active flow control strategy [12]. Liu Jun et al. performed investigation of translation scheme turbine-based combined-cycle inlet mode transition. The steady and unsteady flow characteristics of the inlet mode transition were studied through wind tunnel tests and numerical simulations [13]. Gyuho Kim et al. conducted a study on failure analysis of an aircraft APU exhaust duct flange due to low cycle fatigue at high temperatures. A detailed investigation of crack-induced fracture surface was conducted using scanning electron microscopy (SEM) and computer-aided thermal-stress analysis [14]. Miroslaw Wroblewski et al. conducted a study on areas of investigation into air intake systems for the impact on compressor performance stability in aircraft turbine engines. This paper presents selected areas of research into the surge and stall of axial compressors used in aircraft turbine engines based on scientific publications in recent years [15]. A. Kozakiewicz et al. performed a study on the impact of the intake vortex on the stability of the turbine jet engine intake system. The article presents a numerical analysis of the intake system of a turbine jet engine in terms of parameter stability along its duct, following the occurrence of an intake vortex [16]. A. Kozakiewicz et al. conducted an analysis of the gust impact on the inlet vortex formation of the fuselage-shielded inlet of a jet-engine-powered aircraft. In this study, the analysis of the impact of changes in speed, angle, and the direction of gust on vortex development was conducted [17]. C. Soutis performed a study on fiber-reinforced composites in aircraft construction. In this paper, a review of recent advances using composites in modern aircraft construction is presented and it is argued that fiber-reinforced polymers, especially carbon-fiber-reinforced plastics (CFRP) can and will in the future contribute more than 50% of the structural mass of an aircraft [18]. A. Grbovic et al. carried out a study on the experimental and numerical evaluation of fracture characteristics of composite material used in aircraft engine cover manufacturing. In this work, the design of the composite engine cover of light aircraft was roughly presented [19]. M. Finley performed a study on composites that provide greener aircraft engines. In this work, the trend of composite materials used in aircraft engines was presented [20]. Many research works on aerodynamic design for air intake of aircraft were performed. However, little research work has been carried out to design and conduct a numerical analysis of small aircraft structures using composite materials. The aim of this work is to design the engine intake structure of a small aircraft. In this study, a high-strength carbon/epoxy composite was applied to conduct the structural design and analysis of small aircraft structures. For structural safety evaluation, a finite element analysis method was applied. Finally, structural design and numerical analysis of air intake and s-duct structures for small aircraft were performed. 2. Mechanical Properties of Carbon/Epoxy Materials In this study, a high-strength carbon/epoxy composite was adopted for structural design. The carbon fiber and epoxy matrix is a material optimized for aircraft structures to reduce weight. Recently, most aircraft are designed by adopting carbon fiber for weight reduction. Therefore, carbon fiber was adopted for the structural design of the target small aircraft. In this work, investigation of mechanical properties of a carbon/epoxy composite is performed as a precedent study on the design of air intake structures using a carbon fiber composite. The carbon fiber/epoxy composite specimens were manufactured by the autoclave manufacturing process. The specimen test was performed by the ASTM strength test method. The tensile strength test was performed by ASTM D3039 [21]; the compressive strength test was performed by ASTM D6641 [22]; the flexural strength test was performed by ASTM D790 [23]; and the shear strength test was performed by ASTM D5379 [24]. The Universal Testing Machine of Shimadzu AG-250KNX was applied. The equipment was manufactured by SUNGSAH HI TECH in the Republic of Korea. The test speed of the equipment was 0.001~500 mm/min. Figure 1, Figure 2, Figure 3 and Figure 4 show the tested result of a tensile and compression specimen [25]. The mechanical properties after the specimen test were used for the structural design. The design using carbon/epoxy composite was performed after investigation of the mechanical properties of the specimen. In this work, the fracture shape was also investigated and analyzed by applying the failure theory. The Tsai-Wu failure criterion was adopted [26,27]. Figure 2 and Figure 4 show the fiber failure shape of the carbon composite specimen. In the case of tensile specimens, the fiber fracture behavior after matrix damage is shown. In the case of compression specimens, the fibers at both ends are broken by compression, showing the type of damage. 3. Structural Design This study carried out structural design and analysis on the s-duct and air intake in the front of a small aircraft engine. The materials applied for structural design were carbon/epoxy composite ones. Through the preceding research, as the material was applied to the manufacture of the small aircraft, mechanical properties of F6273C-07M, carbon/epoxy fabric prepreg of Toray Industries Inc., were applied. The mechanical properties from the specimen test were applied to the design. For the target structure’s thickness, the thickness of one ply of prepreg was 0.22 mm, and accordingly, the final thickness and stacking angle were determined. The design loading conditions are the pressure distribution load and acceleration status. Table 1 shows the load conditions for structural design. The structural design was carried out considering the distributed load and acceleration conditions. Figure 5 shows pressure distribution by CFD analysis result. The safety factor 1.5 was considered. The design requirements were applied according to the composite materials handbook (CMH-17-3G) [28]. Firstly, the design method of the netting rule was used for the initial design. The design method for determining the mixture was used to detail the design. The target structure consists of two parts: a plate part and a curved panel. The design of the plate part was performed considering the laminate constitutive theory [29,30]. The curved panel was designed considering the curved beam theory [31,32]. Since a curved beam is such a generic feature, we treated the specific configuration for which transverse tensile stresses become significant and may precipitate the failure of a structure. We assumed that characterization as a panel stress elastic problem is adequate. Figure 6 shows the curved beam configuration. A solution to the posed curved beam problem results from a formulation in polar coordinates and the identification of an airy-type stress function. We used the equation of the radial and tangential stress component as follows. The following equations were used to design the curved structure of the duct; σr is radial stress, k is shear coefficients, and σθ is tangential stress. The structural design was performed by comparing the stress calculated using the following equation and the yield strength of the material under the applied load:(1) σr=−Mb2hG1−1−abk+11−ab2krbk−1⋯−1−abk−11−ab2kark+1 where, (2) k=EθEr  (3) G=121−ab2 ⋯−k1−ab2k1−abk+12k+1−1−abk−12k−1ab2 (4) σθ=−Mb2hG1−1−abk+11−ab2kkrbk−1⋯+1−abk−11−ab2kkark+1 A similar expression was derived by Timoshenko for an isotropic curved beam. In this study, the design of a curved structure was performed using the above equation. The geometric factors (b, a, h, and r) are illustrated in Figure 6. Finally, the thickness of the target structure was defined. The design result of the initial structure was determined to be 1.1 mm. The laminate sequence is [45°/0°/45°/0°/45°]. The thickness of 1 ply is 0.22 mm. 4. Structural Analysis of S-Duct and Results Discussion Structural analysis was conducted for the structural design result to examine structural safety. The commercial software used was MSC. Nastran, which is a finite element analysis method, was used to carry out the structural analysis. The structural analysis was carried out to analyze stress, displacement, and buckling. A three-dimensional shape for structural analysis was investigated to generate a finite element analysis model. The result of generating the finite element analysis model to carry out structural analysis in this study is shown in Figure 7. The total number of elements generated for structural analysis was 2,161,305 elements. The four-node composite shell element was applied for the finite element model. For the boundary condition, the connecting part was applied as the fixed boundary condition. Figure 8 shows the boundary condition for structural analysis. For the application load, the pressure distribution load and acceleration condition were taken into account to carry out structural analysis by applying the safety factor of 1.5 for each case. The load case one is a case of −6G acceleration in the direction of z. As a result of structural analysis of the load case one, the maximum stress was examined as 2.62 MPa tension and 1.80 MPa compression at layer one which is the external outer-most layer. It was examined that internal layer two had 1.72 MPa tension, and 1.09 MPa compression, and layer five, which is the internal outer-most layer, had 1.93 MPa tension and 2.51 MPa compression. Therefore, it was confirmed to be safe. The result of displacement analysis was investigated as 0.10 mm at the side part. The displacement was confirmed to be safe. As for the buckling analysis, the load factor of first buckling was 35. Therefore, it was examined to be a sufficiently stable structure against buckling. Figure 9, Figure 10 and Figure 11 show the result of stress and displacement through the structural analysis of load case one. The load case two is a case of +3G acceleration in the direction of z. This case was confirmed to be the same result as the load case one. As a result of structural analysis, the maximum stress was examined as 2.62 MPa tension and 1.80 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 1.72 MPa tension and 1.90 MPa compression, and layer five, which is the internal outer-most layer, had 1.93 MPa tension and 2.51 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 0.10 mm at the side part, so the displacement was also confirmed to be safe enough. As a result of the buckling analysis, the first buckling load factor was 35, so it was examined to be a sufficiently stable structure against buckling. Load case three is a case of +2G acceleration in the direction of y. For this case, as a result of structural analysis, the maximum stress was examined as 1.90 MPa tension and 1.07 MPa compression at layer one which is the external outer-most layer. It was examined that internal layer two had 8.17 MPa tension and 9.65 MPa compression, and layer five, which is the internal outer-most layer, had 11.7 MPa tension and 15.8 MPa compression, so it was confirmed to be safe enough. The displacement analysis result was examined as 2.43 mm at the internal part. As a result of the buckling analysis, the first buckling load factor was 2.82. Therefore, it was examined to be a sufficiently stable structure against buckling. The load case four is a case of +20G acceleration in the direction of x. As a result of structural analysis, the maximum stress was examined as 5.28 MPa tension and 2.36 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 2.79 MPa tension and 1.74 MPa compression, and layer five, which is the internal outer-most layer, had 2.75 MPa tension and 3.57 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 0.18 mm at the side part. As a result of the buckling analysis, the first buckling load factor was 2.8. Therefore, it was examined to be a sufficiently stable structure against buckling. The load case five is a case of +20G acceleration in the direction of y. This case was also confirmed to be the same as the load case three. As a result of structural analysis, the maximum stress was examined as 1.90 MPa tension and 1.07 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 8.17 MPa tension and 9.65 MPa compression, and layer five, which is the internal outer-most layer, had 11.7 MPa tension and 15.8 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 2.43 mm at the internal part. As a result of the buckling analysis, the first buckling load factor was 2.8. Therefore, it was examined to be a sufficiently stable structure against buckling. As the load case six is a case of +20G acceleration in the direction of z, it was confirmed to be the same as load cases one and two. As a result of the structural analysis, the maximum stress was examined as 2.62 MPa tension and 1.80 MPa compression at layer one, which is the external outer-most layer. It was examined that the internal layer two had 1.72 MPa tension and 1.90 MPa compression, and layer five, which is the internal outer-most layer, had 1.93 MPa tension and 2.51 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 0.10 mm at the side part, so the displacement was also confirmed to be safe enough. As a result of buckling analysis, the first buckling load factor was 35, so it was examined to be a sufficiently stable structure against buckling. In this study, structural analysis of the designed result was performed. As a result of examining the stress and displacement analysis results, it was confirmed to be a safe structure. Table 2 shows a summary of the structural analysis results of the s-duct structure. The structural analysis was performed for a total of six cases in this study. The tensile stress and compressive stress were confirmed to be sufficiently safe as a result of examining the safety factor. It was confirmed that it was sufficiently safe when compared with the results of other studies on the design and analysis of aircraft to which the composite material was applied. 5. Structural Analysis of Air Intake and Results Discussion After performing the structural analysis of the s-duct component, the structural analysis of the air intake was performed. The three-dimensional shape of the structural design result was analyzed to generate a finite element analysis model. The result of generating the finite element analysis model to carry out structural analysis in this study is shown in Figure 12. The total number of elements generated for structural analysis was 34,167. For the boundary condition, the connecting part was applied as the fixed boundary condition. Figure 12 shows the boundary conditions. For the application load, the pressure distribution load and acceleration condition were taken into account to carry out structural analysis by applying the safety factor of 1.5 for each case. In this work, the contents of previous studies were improved and applied [33]. Load case 1 is a case of −6G acceleration in the direction of z. As a result of the structural analysis of load case one, the maximum stress was examined as 1.27 MPa tension and 1.80 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 0.486 MPa tension and 1.09 MPa compression, and layer five, which is the internal outer-most layer, had 1.17 MPa tension and 1.27 MPa compression. Therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 3.94 mm at the connecting part, so the displacement was also confirmed to be safe enough. As a result of buckling analysis, the first buckling load factor was 1.1. Therefore, it was examined to be a sufficiently stable structure against buckling. Load case two is a case of +3G acceleration in the direction of z. This case was confirmed to be the same result as load case one. As a result of the structural analysis, the maximum stress was examined as 1.27 MPa tension and 1.80 MPa compression at layer one which is the external outer-most layer. It was examined that internal layer two had 0.486 MPa tension and 1.09 MPa compression, and layer five, which is the internal outer-most layer, had 1.17 MPa tension and 1.27 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 3.94 mm at the connecting part, so the displacement was also confirmed to be safe enough. As a result of the buckling analysis, the first buckling load factor was 1.1, so it was examined to be a sufficiently stable structure against buckling. Load case three is a case of +2G acceleration in the direction of y. For this case, as a result of the structural analysis, the maximum stress was examined as 2.0 MPa tension and 2.22 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 0.845 MPa tension and 1.74 MPa compression, and layer five, which is the internal outer-most layer, had 1.21 MPa tension and 2.15 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 46 mm at the side. As a result of the buckling analysis, the primary buckling load factor was 0.038. Therefore, it was examined to be a little bit unstable locally against displacement and buckling. The load case four is a case of +20G acceleration in the direction of x. As a result of the structural analysis, the maximum stress was examined as 7.37 MPa tension and 19.6 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 4.86 MPa tension and 20.9 MPa compression, and layer five, which is the internal outer-most layer, had 9.10 MPa tension and 11.0 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 46.6 mm at the top, so the displacement was considered to be a little bit high locally. As a result of buckling analysis, the first buckling load factor was 0.1, so it was examined to be a locally unstable structure against buckling. Load case five is a case of +20G acceleration in the direction of y. This case was also confirmed to be the same as load case three. As a result of the structural analysis, the maximum stress was examined as 2.0 MPa tension and 2.22 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 0.845 MPa tension and 1.74 MPa compression, and layer five, which is the internal outer-most layer, had 1.21 MPa tension and 2.15 MPa compression; therefore, it was confirmed to be safe enough. The displacement analysis result was examined as 46 mm at the side. As a result of the buckling analysis, the first buckling load factor was 0.038, so it was examined to be a little bit unstable locally against displacement and buckling. As load case six is a case of +20G acceleration in the direction of z, it was confirmed to be the same as load cases one and two. As a result of the structural analysis, the maximum stress was examined as 1.27 MPa tension and 1.80 MPa compression at layer one, which is the external outer-most layer. It was examined that internal layer two had 0.486 MPa tension and 1.09 MPa compression, and layer five, which is the internal outer-most layer, had 1.17 MPa tension and 1.27 MPa compression; therefore, so it was confirmed to be safe enough. The displacement analysis result was examined as 3.94 mm at the connecting part, so the displacement was also confirmed to be safe enough. As a result of the buckling analysis, the first buckling load factor was 1.1, so it was examined to be a sufficiently stable structure against buckling. As a result of the structural analysis on the structural design result of the aircraft component with composite materials applied in this study, it was examined that the plate and cylinder structure shape, which is the connecting part, was vulnerable to buckling. Therefore, the final design result was that the number of the relevant part’s laminated layers was increased to redesign, and as a result of the final structural analysis, it was confirmed to secure structural safety. The design result of the final structure was determined to be 1.54 mm. The laminate sequence is [45°/0°/45°/0°/45°/0°/45°]. Table 3 shows a summary of the structural analysis results for the air intake structure. Figure 13, Figure 14 and Figure 15 show the result of stress and displacement through the final structural analysis of load case one. Structural analysis was performed for a total of six cases in this study. The tensile stress and compressive stress were confirmed to be sufficiently safe as a result of examining the safety factors. It was confirmed that it was sufficiently safe when compared with the results of other studies on the design and analysis of aircraft to which the composite material was applied. 6. Conclusions The aim of this work was to design the engine intake structure of a small aircraft. For structural safety evaluation, a finite element analysis method was applied. In this study, structural design and analysis were carried out on the s-duct and engine intake, which is an aircraft structure with composite materials applied, to examine the structural safety. The netting rule and the rule of mixture considering the composite laminate theory were used for the initial structural design. The target structure consists of two parts. It consists of a plate part and a curved panel. The design of plate part was performed considering the laminate constitutive theory. Structural analysis was carried out using MSC NASTRAN, which is a commercial finite element analysis software. For the load used for structural analysis, the safety factor of 1.5 was applied after considering the pressure distribution load and the acceleration condition, and the boundary condition was applied as the fixed boundary condition of the connecting part. The structural analysis examined stress, displacement, and buckling. As a result of examining the stress and displacement analysis results, it was determined to be a safe structure. As a result of examining the vulnerability to buckling, it was confirmed to be stable enough. Therefore, the structural design result through this study was analyzed to be valid. In the future, manufacturing of a prototype will be carried out using the structural design results presented in this work. Furthermore, future structural tests are planned to reflect the structural analysis results. Author Contributions S.L.: conceptualization, software, validation, writing—original draft preparation. W.C.: visualization, project administration, funding acquisition. H.P.: writing—review and editing and work guidance. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (no. 2018R1D1A1B07043553). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available on reasonable request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Abbreviations M Bending moment E Elastic modulus a Inner radius b Outer radius r Radius h Thickness k Shear coefficients σr Radial stress σθ Tangential stress Figure 1 Tensile test of the manufactured specimen. Figure 2 Investigation of the fracture surface of the tensile specimen. Figure 3 Compression test of the manufactured specimen. Figure 4 Investigation of the fracture surface of the compression specimen. Figure 5 Pressure distribution by CFD analysis. (a) Pressure distribution of intercooler; (b) pressure distribution of radiator. Figure 6 Curved beam configuration. Figure 7 Finite element model of S-duct. Figure 8 Boundary condition of S-duct. Figure 9 Stress analysis result: layer 1. Figure 10 Stress analysis result: layer 2. Figure 11 Displacement analysis result. Figure 12 Boundary condition. Figure 13 Stress analysis result: layer 1. Figure 14 Stress analysis result: layer 2. Figure 15 Displacement analysis result. materials-15-03001-t001_Table 1 Table 1 Load cases. Load Cases Acceleration Pressure Outside (Pa) Inside (Pa) Load case 1 z axis −6G −424.63 725.5 Load case 2 z axis +3G −424.63 725.5 Load case 3 y axis +2G −424.63 725.5 Load case 4 x axis +20G −424.63 725.5 Load case 5 y axis +20G −424.63 725.5 Load case 6 z axis +20G −424.63 725.5 materials-15-03001-t002_Table 2 Table 2 Structural analysis results of s-duct structure. Load Cases Acceleration Stress Tension (MPa) Compression (MPa) Load case 1 z axis −6G 2.62 1.8 Load case 2 z axis +3G 2.62 1.8 Load case 3 y axis +2G 1.9 1.07 Load case 4 x axis +20G 5.28 2.36 Load case 5 y axis +20G 1.9 1.07 Load case 6 z axis +20G 2.62 1.8 materials-15-03001-t003_Table 3 Table 3 Structural analysis results of air intake structure. Load Cases Acceleration Stress Tension (MPa) Compression (MPa) Load case 1 z axis −6G 2.7 1.49 Load case 2 z axis +3G 2.7 1.49 Load case 3 y axis +2G 2.11 1.13 Load case 4 x axis +20G 24.8 12.4 Load case 5 y axis +20G 2.11 1.13 Load case 6 z axis +20G 2.7 1.49 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Bravo-Mosquera P.D. Abdalla A.M. Cerón-Muñoz H.D. Catalano F.M. Integration assessment of conceptual design and intake aerodynamics of a non-conventional air-to-ground fighter aircraft Aerosp. Sci. Technol. 2019 86 497 519 10.1016/j.ast.2019.01.059 2. Vercillo V. Karpen N. Laroche A. Javier Guillén A.M. Tonnicchia S. Jorge R. Bonaccurso E. Analysis and modelling of icing of air intake protection grids of aircraft engines Cold Reg. Sci. Technol. 2019 160 265 272 10.1016/j.coldregions.2019.01.012 3. Bagnoli F. Bernabei M. Ciliberto A. Failure analysis of an aircraft auxiliary power unit air intake door Eng. Fail. Anal. 2011 18 284 294 10.1016/j.engfailanal.2010.09.007 4. Zhou Z. Huang J. Mixed design of radar/infrared stealth for advanced fighter intake and exhaust system Aerosp. Sci. Technol. 2021 110 106490 10.1016/j.ast.2021.106490 5. Soltani M.R. Younsi J.S. Farahani M. Masoud A. Numerical simulation and parametric study of a supersonic intake. Proceedings of the Institution of Mechanical Engineers Part G J. Aerosp. Eng. 2013 227 467 479 10.1177/0954410012436620 6. Gan W. Zhang X. Design optimization of a three-dimensional diffusing S-duct using a modified SST turbulent model Aerosp. Sci. Technol. 2017 63 63 72 10.1016/j.ast.2016.12.016 7. Kim H. Liou M.-S. Shape design optimization of embedded engine inlets for N2B hybrid wing–body configuration Aerosp. Sci. Technol. 2013 30 128 149 10.1016/j.ast.2013.07.011 8. Huang G. Zuo F. Qiao W. Design method of internal waverider inlet under non-uniform upstream for inlet/forebody integration Aerosp. Sci. Technol. 2018 74 160 172 10.1016/j.ast.2018.01.012 9. Lee M. Berra J.W. Slater S. Olcmen M. Conceptual redesign of the B-1B bomber inlets for improved supersonic performance Aerosp. Sci. Technol. 2015 45 476 483 10.1016/j.ast.2015.06.017 10. Brahmachary S. Fujio C. Ogawa H. Multi-point design optimization of a high-performance intake for scramjet-powered ascent flight Aerosp. Sci. Technol. 2020 107 106362 10.1016/j.ast.2020.106362 11. Song G. Li J. Tang M. Wu Y. Luo Y. Experimental simulation methodology and spatial transition of complex distortion fields in a S-shaped inlet Aerosp. Sci. Technol. 2021 116 106855 10.1016/j.ast.2021.106855 12. Wojeodka M. White C. Shahpar S. Kontis K. Numerical study of complex flow physics and coherent structures of the flow through a convoluted duct Aerosp. Sci. Technol. 2022 121 107191 10.1016/j.ast.2021.107191 13. Jun L. Huacheng Y. Wenfang C. Rongwei G. Investigation of translation scheme turbine-based combined-cycle inlet mode transition Aerosp. Sci. Technol. 2021 116 106894 10.1016/j.ast.2021.106894 14. Kim G. Lee B. Lu H. Rongwei J.P. Failure analysis of an aircraft APU exhaust duct flange due to low cycle fatigue at high temperatures Eng. Fail. Anal. 2012 20 97 104 10.1016/j.engfailanal.2011.11.003 15. Wroblewski M. Adamczyk M. Kozakiewicz A. Areas of investigation into air intake systems for the impact on compressor performance stability in aircraft turbine engines Adv. Sci. Technol. Res. J. 2022 16 62 74 10.12913/22998624/143290 16. Kozakiewicz A. Frant M. Majcher M. Impact of the intake vortex on the stability of the turbine jet engine intake system Int. Rev. Aerosp. Eng. 2021 14 173 180 10.15866/irease.v14i4.20223 17. Kozakiewicz A. Frant M. Analysis of the gust impact on inlet vortex formation of the fuselage-shielded inlet of an jet engine powered aircraft J. Theor. Appl. Mech. 2013 51 993 1002 18. Soutis C. Fibre reinforced composites in aircraft construction Prog. Aerosp. Sci. 2005 41 143 151 10.1016/j.paerosci.2005.02.004 19. Grobovic A. Kastratovic G. Bozic Z. Bozic Z. Obradovic A. Sedmak A. Sedmak S. Experimental and numerical evaluation of fracture characteristics of composite material used in the aircraft engine cover manufacturing Eng. Fail. Anal. 2022 137 106286 10.1016/j.engfailanal.2022.106286 20. Finley M. Composites make for greener aircraft engines Reinf. Plast. 2008 52 24 25 10.1016/S0034-3617(08)70033-X 21. ASTM D3039/D3039M-17 Standard Test Method for TENSILE properties of Polymer Matrix Composite Materials ASTM International West Conshohocken, PA, USA 2017 Available online: www.astm.org (accessed on 24 March 2021) 22. ASTM D6641/D6641M-16e1 Standard Test Method for Compressive Properties of Polymer Matrix Composite Materials Using a Combined Loading Compression(CLC) Test Fixture ASTM International West Conshohocken, PA, USA 2016 Available online: www.astm.org (accessed on 24 March 2021) 23. ASTM D790-17 Standard Test Methods for Flexural Properties of Unreinforced and Reinforced Plastics and Electrical Insulating Materials ASTM International West Conshohocken, PA, USA 2017 Available online: www.astm.org (accessed on 24 March 2021) 24. ASTM D5379/D5379M-19 Standard Test Method for Shear Properties of Composite Materials by the V-Notched Beam Method ASTM International West Conshohocken, PA, USA 2019 Available online: www.astm.org (accessed on 24 March 2021) 25. Park H. Kong C. Shin C. Investigation on damage tolerance of thick laminate for aircraft composite structure J. Korean Soc. Compos. Mater. 2012 25 105 109 10.7234/kscm.2012.25.4.105 26. Michael W.H. Stress Analysis of Fiber-Reinforced Composite Materials McGraw-Hill New York, NY, USA 1998 27. Li S. Sitnikova E. Liang Y. Kaddour A. The Tsai-Wu failure criterion rationalised in the context of UD composites Compos. Part A 2017 102 207 217 10.1016/j.compositesa.2017.08.007 28. CMH-17 Composite Materials Handbook—Vol.3. Polymer Matrix Composites: Materials Usage, design and Analysis SAE Interantional Warrendale, PA, USA 2012 29. Kong C. Lee H. Park H. Design and manufacturing of automobile hood using natural composite structure Compos. Part B 2016 91 18 26 10.1016/j.compositesb.2015.12.033 30. Lee H. Park H. Study on structural design and manufacturing of sandwich composite floor for automotive structure Materials 2021 14 1732 10.3390/ma14071732 33916112 31. Keith T. Kedward J.M.W. Delaware Composite Design Encyclopedia Technomic Publishing Co., Inc. Lancaster, PA, USA 1990 Volume 5 32. Albazzan M. Harik R. Tatting B. Gurdal Z. Efficient design optimization of nonconventional laminated composites using lamination parameters: A state of the art Compos. Struct. 2019 209 362 374 10.1016/j.compstruct.2018.10.095 33. Choi H. Park H. A study on the structural design and analysis of air intake of unmanned aerial vehicles applied to composite materials J. Aerosp. Syst. Eng. 2022 16 81 85

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093029 materials-15-03029 Article Thermal Properties of Illite-Zeolite Mixtures up to 1100 °C https://orcid.org/0000-0003-2118-9917 Csáki Štefan 1 Sunitrová Ivana 1 https://orcid.org/0000-0002-7589-9474 Lukáč František 23 https://orcid.org/0000-0002-0621-7222 Łagód Grzegorz 4 https://orcid.org/0000-0001-9923-8366 Trník Anton 15* Moissette Alain Academic Editor 1 Department of Physics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Tr. A. Hlinku 1, 94974 Nitra, Slovakia; scsaki@ukf.sk (Š.C.); ivka.sunitrova@gmail.com (I.S.) 2 Institute of Plasma Physics of the Czech Academy of Sciences, Za Slovankou 3, 18200 Prague 8, Czech Republic; lukac@ipp.cas.cz 3 Faculty of Mathematics and Physics, Charles University, V Holešovičkách 2, 180000 Prague 8, Czech Republic 4 Faculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B, 20-618 Lublin, Poland; g.lagod@pollub.pl 5 Department of Materials Engineering and Chemistry, Faculty of Civil Engineering, Czech Technical University in Prague, Thákurova 7, 16629 Prague, Czech Republic * Correspondence: atrnik@ukf.sk; Tel.: +421-37-6408-616 21 4 2022 5 2022 15 9 302928 3 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Illitic clays are the commonly used material in building ceramics. Zeolites are microporous, hydrated crystalline aluminosilicates, they are widely used due to their structure and absorption properties. In this study, illitic clay (Füzérradvány, Hungary) was mixed with natural zeolite (Nižný Hrabovec, Slovakia) with up to 50 wt.% of zeolite content. The samples were submitted to thermal analyses, such as differential thermal analysis, differential scanning calorimetry, thermogravimetry, and dilatometry. In addition, the evolution of thermal diffusivity, thermal conductivity, and specific heat capacity in the heating stage of firing were measured and discussed. The amount of the physically bound water in the samples increased along with the amount of zeolite. The temperature of the illite dehydroxylation (peak temperature) was slightly shifted to lower temperatures, from 609 °C to 575 °C (for sample IZ50). On the other hand, the mass loss and the shrinkage of the samples significantly increased with the zeolite content in the samples. Sample IZ50 reached 10.8% shrinkage, while the sample prepared only from the illitic clay contracted by 5.8%. Nevertheless, the temperature of the beginning of the sintering (taken from the dilatometric curves) decreased from 1021 °C (for illitic clay) to 1005 °C (for IZ50). The thermal diffusivity and thermal conductivity values decreased as the amount of zeolite increased in the samples, thus showing promising thermal insulating properties. illitic clay zeolite clinoptilolite thermal expansion thermal diffusivity thermal conductivity specific heat capacity ==== Body pmc1. Introduction Illite is one of the most abundant clay minerals which is widely used in the production of traditional ceramic materials, including pottery, tiles, etc. [1]. The illitic clay used in this study was mined in northeastern Hungary and its dominant mineral phase is illite. The structure of illite is built up of three sheets—an octahedral sheet sandwiched between two tetrahedral sheets. Between each T-O-T an interlayer cation is placed, which, in most cases, is a potassium cation [2,3,4]. However, some sites are unoccupied, and thus, water molecules populate those vacancies. Depending on the arrangement of the octahedral cations, the illite has several polytypes. The polytype of the studied illite was identified as 1M [5] and its chemical formula can be expressed as:K0.78Ca0.02(Mg0.34Al1.69Fe0.02III)[Si3.35Al0.65]O10(OH)2·nH2O Illite undergoes several physicochemical processes during heating, namely evaporation of the physically bound water, dehydroxylation, and sintering. The X-ray diffraction reflections of illite remain observable up to the temperature of 850 °C [6,7]. Zeolites are crystalline, microporous, hydrated, aluminosilicates containing alkali metals or alkaline earth metals. They crystallize in the monoclinic crystal system. The structure is built up from [SiO4]4− and [AlO4]5− tetrahedrons, which are interconnected by oxygen ions [8,9,10,11]. In the three-dimensional framework, there is a system of channels or cage-like cavities, where alkali cations (K+, Na+, Ca2+) or small molecules, such as H2O are placed [12,13,14]. Zeolites have excellent cation exchange properties, thus they are suitable for water and wastewater treatment [9,15,16,17,18]. Moreover, zeolites are widely used in agriculture, building industry, rubber industry, chemical industry, paper industry, households and also in medicine [12,19,20,21,22,23,24]. Zeolites can be divided into several family groups. Mineral clinoptilolite is from the family group of heulandites. This mineral group includes minerals, such as heulandites and clinoptilolite, both of which are crystallized in a monoclinic system and their chemical composition is very similar. The difference between these minerals is in the Si/Al ratio and this affects the thermal stability. The structure of clinoptilolite is destroyed above the temperature of 1000 °C, where amorphization occurs. Several papers have been devoted to the study of the mechanical, thermophysical, and electric properties of illitic clay and its mixtures with different additions (e.g., fly ash [25,26,27], calcite [28]). Nonetheless, according to the authors’ knowledge, there is no data about the mixtures of illitic clay and natural zeolite. Blends of kaolin and natural zeolite were investigated in [29]. It was shown that zeolite supports the densification of a ceramic body, thus shifting the sintering to lower temperatures. The aim of this study was to investigate the feasibility of illite-zeolite mixtures and to describe the processes occurring in the mixtures during firing in terms of differential thermal analysis, thermogravimetry, and thermodilatometry. In addition, the thermal diffusivity, conductivity, and specific heat capacity of the prepared samples were measured. Zeolite, being a microporous aluminosilicate is expected to lower the sintering temperature and improve the thermal properties compared with the pure illitic clay. The improvement in the thermal properties is expected through an increase in the porosity of the products due to the addition of zeolite. 2. Materials and Methods Illitic clay was mined near the town of Füzérradvány in northeastern Hungary. The mineralogical composition of illitic clay is as follows: illite (80 wt.%), quartz (12 wt.%), montmorillonite (4 wt.%), and feldspar (4 wt.%) [30]. Zeolite was received from the company ZEOCEM, a.s. (Nižný Hrabovec, Slovakia) as product ZeoBau Micro 50 [31]. The dominant mineral phase in the zeolite sample was Na-clinoptilolite (58.2 wt.%). In addition, cristobalite (12.2 wt.%), illite with mica and albite (9.6 wt.%), quartz (0.7 wt.%), and amorphous phase (19.3 wt.%) were identified as impurities in the sample [22]. The chemical composition of the samples is presented in Table 1. Zeolite was obtained in a powder form with a diameter of particles <50 μm, while the illitic clay had diverse particle sizes, from several μm up to the cm range. Thus, further processing of the clay was needed in terms of mechanical treatment—starting with the crushing and milling the illitic clay. After crushing, the clay was dried for 2 h at 110 °C. The milling was conducted for 3 min at 350 rpm in the Retsch PM100 planetary ball mill. In the next step, the as-prepared powder was sieved to obtain a powder with particle sizes <100 μm. The mixtures were prepared by adding 10, 20, 30, 40, and 50 wt.% of zeolite powder to the illitic clay by dry mixing. The studied samples were labeled as IZ10, IZ20, IZ30, IZ40, and IZ50, according to the natural zeolite content, whereas the pure illitic clay and zeolite samples were labeled as ILB and ZEO (see Table 2). To obtain a plastic mass, the green material was mixed with distilled water and the samples were prepared with the help of a laboratory extruder (Ø = 14 mm and l = 150 mm). The samples were then dried in the air under laboratory conditions for one week. The samples for thermal analyses, as well as for the microstructure observations were adapted in the final step. Cylindrical samples of dimensions Ø = 14 mm and l = 16 mm were prepared for differential thermal analysis and with dimensions of Ø = 14 mm and l = 30 mm for thermodilatometry. Disc samples were prepared for thermal diffusivity measurements with a thickness of 2.5 mm and a diameter of 12.5 mm. Differential scanning calorimetry was carried out on powder samples. Differential thermal analysis (DTA) and thermogravimetry (TG) were performed using the upgraded Derivatograph 1100° (MOM Budapest, Budapest, Hungary) [32]. The measurements were carried out in a static air atmosphere from room temperature up to 1050 °C with a heating rate of 5 °C/min. Bulk alumina was used as the reference material. Differential scanning calorimetry (DSC) was carried out using a Netzsch Pegasus 404 F3 (NETZSCH Holding, Selb, Germany) in a dynamic Ar atmosphere with a flow rate of 40 mL/min from room temperature to 1100 °C with a heating rate of 5 °C/min. Thermodilatometry (TDA) was performed on a laboratory made dilatometer from room temperature to 1100 °C with a heating rate of 5 °C/min in a static air atmosphere. The bulk density was calculated from thermogravimetric and thermodilatometric results to obtain its actual values during firing, according to the following equation:(1) ρ=ρ0Δm/m0(1+Δl/l0)3 , where ρ0 is the bulk density of green samples at room temperature. The open porosity was calculated with the help of the experimentally determined bulk density and matrix density. The bulk density was obtained from the volume and mass of the cylindrical samples. The matrix density was measured using helium pycnometry (Pycnomatic ATC, Thermo Fisher Scientific, Waltham, MA, USA). The thermal diffusivity (a) measurements were performed on a Linseis LFA 1000 (Linseis Messgeraete GmbH, Selb, Germany) up to 900 °C. Measurements were taken in 100 °C steps, 5 shots per sample. Heat capacity (cp) was measured simultaneously with the thermal diffusivity. Alumina was used as a reference material. The thermal conductivity (λ) was then calculated for each shot using the equation (2) λ=ρ×cp×a. The measurement was carried out in a vacuum. To achieve equal adsorption and emission properties of all samples, their faces were covered with a thin layer of graphite. Phase compositions of samples were determined by powder X-ray diffraction (PXRD) methods. The measurements were carried out on vertical powder θ-θ diffractometer D8 Discover (Bruker AXS, Karlsruhe, Germany) using Cu Kα radiation with a Ni Kβ filter. The diffracted beam was detected by the 1D detector LynxEye. Bragg–Brentano geometry was employed with a 0.5 deg fixed divergent slit in the primary beam. The angular range was from 10 to 100° 2θ, step size 0.03° 2θ and the total time in each step was 192 s (the 1D detector is composed of 192 point detectors). Phase identification was conducted using X’Pert HighScore program which accessed the PDF-2 database of crystalline phases. Quantitative Rietveld refinement was performed in TOPAS V5, aiming at the determination of wt.% of all the identified phases following the theory from [33,34]. Small texture correction was included in order to improve the intensities of reflections, see the March–Dollase approach for details [35]. The size of coherently diffracting domains (CDD) and microstrains was evaluated by quantitative Rietveld analysis from the broadening of diffraction peaks using TOPAS V5 software (Bruker AXS, Karlsruhe, Germany). It was assumed that small crystallites and microstrains contribute to the broadening of Lorentzian and Gaussian components of pseudo-Voigt function, respectively [36]. 3. Results and Discussion 3.1. Differential Thermal Analysis TA of the zeolite sample exhibits a significant endothermic peak in the temperature range from room temperature to ~400 °C (Figure 1a). This peak represented the evaporation of the physically bound water from the pores and the crystal surfaces [21,37]. Similarly, the illitic clay manifests an endothermic peak at temperatures up to ~300 °C, also representing the liberation of the physically bound water. However, this reaction consumes less energy in the illitic clay than in the zeolite sample. The physically bound water is present in the illite in three layers, thus its removal also occurs in three consecutive steps [38]. The process became more emphasized as the part of zeolite increased in the mixture. Moreover, the offset of the dehydration peak gradually shifted to higher temperatures as the zeolite content in the samples increased, in hand with the reaction enthalpy of the process. Once the dehydration process was finished, the dehydroxylation of the illite started (around the temperature of 400 °C). The dehydroxylation of illite is a two-step process; in the first step, the chemically bound water is removed from the cis-vacant illite sites. This is followed by the second step, running at higher temperatures, where the OH− groups are liberated from the trans-vacant illite structure [4]. The increasing zeolite amount affected this process as well: as its amount increased, the peaks became less significant, and their positions shifted to lower temperatures (Figure 1b). The first step of the dehydroxylation (peak temperature) was shifted from 608 °C (for illitic clay) to 573 °C (for IZ50). The peak temperature of the second step of dehydroxylation decreased from 714 °C (for illitic clay) to 700 °C (for IZ50). The decreasing peak temperature of the dehydroxylation was not evident in all cases. Sample IZ10 exhibited little higher dehydroxylation temperatures compared to the illitic clay (~by 10 °C in both steps of the process). As the dehydroxylation finished, sintering assisted by viscous flow took place. The shift of the endothermic peak corresponding to the crystallization of new mineral phases was negligible. However, natural zeolite serves as a fluxing agent; thus, the sintering temperatures of the ceramic bodies should be shifted to lower values [33,34]. 3.2. Differential Scanning Calorimetry DSC of the prepared mixtures and initial materials (illitic clay and zeolite) is presented in Figure 2. The same features are observable on the DSC curves in the initial stage of heating as on the DTA records. However, due to the higher sensitivity of the DSC apparatus, two-step evaporation of the physically bound water is observable up to 250 °C on the illitic clay curve. In the first step, the weakly bound physically bound water is removed from the crystal surfaces. The second step corresponds to the liberation of tightly bound adsorption water [39]. This feature remained observable, even if the sample contained 50 wt.% of zeolite. With an increase in the temperature, the next step took place (500–700 °C), i.e., the illite dehydroxylation. The two-step character of the process is clearly visible on all curves belonging to the samples containing illite. The temperature shift of the dehydroxylation was not observed on the DSC curves. There were no observed processes in the zeolite sample, except the dehydration at low temperatures and the amorphous phase formation in hand with the sintering process. The structure of the zeolite was destroyed at temperatures above 850 °C (the endothermic peak on the DSC curve) [13,40]. Sintering of the samples containing illite started at higher temperatures, namely around 1000 °C. 3.3. Mass Change The zeolite sample exhibited a continuous decrease in its mass from room temperature up to ~800 °C (Figure 3a). This decrease can be related to the continuous release of the entrapped water molecules [41]. The overall mass loss of the sample reached 11.36% at 1050 °C. The sample prepared from illitic clay exhibited two main mass losses—the first in the temperature interval from room temperature up to ~300 °C, where the physically bound water was evaporated from the sample. The mass loss reached 2.8% in this region. The mixtures containing the zeolite exhibited higher mass losses. Thus, the mass losses of the mixtures gradually increased from 3.5% (for IZ10) to 5.3% (for IZ50). The next significant mass loss was observed during the illite dehydroxylation. For the illitic clay sample, the decrease in the sample mass reached 3.9% over the temperature interval from 450 °C to 750 °C. The mass loss in the discussed region gradually decreased, as the zeolite content in the sample increased. This feature was caused by the fact that zeolite does not undergo dehydroxylation, as it does not contain OH− groups in the structure. The overall mass losses increased along with zeolite content. For the illitic clay sample, the value of the mass loss reached 6.9%. A comparison of the mass losses of the individual samples is visualized in Figure 3b. The addition of zeolite significantly increased the overall mass loss. The mass loss of the sample IZ50 increased by 9.5%, which was almost 3% higher than that of the illitic clay. 3.4. Thermal Expansion The zeolite sample suffered a slight contraction up to ~870 °C (Figure 4a). This contraction reached 1.9% and can be related to the removal of the water molecules from the zeolite cavities and capillaries. At ~870 °C, a progressive shrinkage of the zeolite sample started, which indicated the start of the sintering and appearance of the glassy phase. Moreover, the zeolite structure collapsed at the above-mentioned temperature and an amorphous phase was formed. The overall shrinkage of the sample reached 14.5% at 1100 °C. The sample prepared from the illitic clay exhibited a continuous thermal expansion up to the start of the dehydroxylation process (~470 °C). This expansion reached 0.3%. During the dehydroxylation, and due to the α→β transformation of quartz, the expansion became more pronounced, reaching 1.3% at 690 °C. This expansion is thus the superposition of the two competitive processes. The α→β transformation of quartz brings about around 0.68% expansion [42]. During dehydroxylation, the ring of the tetrahedral sheet of the illite expands to allow the water molecules to pass, which contributed to the expansion as well. The two-step character of the illite dehydroxylation was also observable on the temperature dependence of the coefficient of linear thermal expansion curves (Figure 5), where two distinct peaks marked the process. Once the dehydroxylation was finished, a continuous expansion of the illitic clay sample was observed. This is related to the expansion of the b and c axes and the simultaneous shrinkage of the a axis and β angle of the dehydroxylated illite crystals [7]. At ~920 °C, a progressive shrinkage started marking the start of the sintering assisted by viscous flow. The overall shrinkage reached 5.6%. The TDA curves of the mixtures exhibit similar features to those of the illitic clay. The influence of the zeolite addition, regardless of its amount, was not significant up to the start of the sintering; the expansion of the samples did not differ at temperatures up to 400 °C (0.27%). Before the start of the sintering process, the relative length changes of the samples reached 1.54% and 1.31% for the illitic clay and the IZ50 sample, respectively. Thus, the dimension changes of the samples were mainly driven by the illite and the contraction of the zeolite was suppressed. The start of the sintering (taken as the onset of the TDA curves) was shifted to lower temperatures with increasing zeolite content (inset figure in Figure 4) from 1020 °C (for illitic clay) to 1005 °C (for IZ50). This can be related to the good fluxing properties of the natural zeolite [33,34]. The overall shrinkage of the samples increased from 5.6% (for illitic clay) to 10.8% (for IZ50), as shown in Figure 4b. 3.5. Phase Composition The phase composition of the fired illite-zeolite samples (Figure 6 and Table 3) manifested significant differences. Quartz and Al2O3 were identified as dominant mineral phases in the fired illitic clay sample supported by orthoclase, mullite and amorphous phase. On the other hand, the fired zeolite sample contained cristobalite and albite as dominant phases supported by quartz and amorphous phase. The amorphous content in both samples is comparable. XRD analysis (Figure 6 and Table 3) of the samples revealed a decreasing quartz content with an increasing amount of zeolite in the samples. On the other hand, the amount of cristobalite gradually increased from 3 wt.% (sample IZ10) to 11 wt.% (sample IZ50). Orthoclase (was forming due to the high potassium content in the illitic clay), KAlSi3O8, disappeared when the amount of zeolite in the samples exceeded 30 wt.%, being replaced by albite (NaAlSi3O8). As zeolite contains a higher amount of Na, if this exceeds a certain value, albite is formed instead of orthoclase. The amorphous content of all the samples is similar, almost within the experimental error. 3.6. Bulk Density Temperature dependence of the bulk density (Figure 7) of the illitic sample was influenced by the physicochemical processes running in the illite. The removal of the physically bound water led to a smooth step-like decrease in the bulk density up to the temperature of 200 °C. After this process was finished, a continuous decrease in the bulk density was observed until the dehydroxylation started. As water molecules possess a higher density than clay, their removal leads to a decrease in the bulk density. After the dehydroxylation, a minimum of the bulk density was reached, around the temperature of 900 °C. As the sintering started, significant densification could be observed. The bulk density of the sample increased by ~10%. Compared with the green illitic sample density (~1800 kg/m3) the density of the pure zeolite sample was considerably lower (~1200 kg/m3). The dehydration of the zeolite led to a continuous decrease in the density of the sample up to ~400 °C, where a plateau was observed. The bulk density of the zeolite sample exhibited a significant increase as the sintering started above 850 °C. The sintering led to a ~30% increase in the bulk density of the zeolite sample. Temperature dependence of the bulk density of the mixtures exhibited similar features as those of the illitic clay. However, differences were found in the degree of densification. Zeolite supported the densification; thus, with an increasing amount of zeolite in the samples, the relative increase in the bulk density between room temperature and the maximum sintering temperature (1100 °C) increased. Sample IZ10 exhibited only a 10% increase in the value of bulk density. However, this increased to 14% for IZ20, 16% for IZ30, 19% for IZ40, and 22% for IZ50. A similar trend was observed in [29] for the mixtures of kaolin with zeolite. Nevertheless, the final values of the bulk density remained lower, as kaolin exhibited lower bulk density and the densification of the illitic clay was more progressive than that of kaolin. 3.7. Porosity Initial values of the porosities (Figure 8) of the green samples were stretched from 36% (illitic clay and IZ10) to 49% (zeolite). Upon heating, the value of the porosity of the samples exhibited a gradual increase due to the removal of the physically and structurally bound water. As the water molecules were escaping, the sample voids were left behind. The increase stopped as the sintering of the samples started, which was observed to take place from 900 °C. The progressive sintering of the samples was evident—the values of the porosities of all samples decreased below 8%, except the zeolite, which exhibited the porosity values of 17%. The lowest value of porosity was observed in the case of the illitic clay sample, for which the final value reached 2.2%. However, sample IZ10 also exhibited excellent densification behavior, as its porosity remained similar to that of the illitic clay sample. All the other samples reached higher values than those of the illitic clay or IZ10. 3.8. Thermal Diffusivity Thermal diffusivity of the mixtures exhibited the highest values at room temperature (Figure 9a) due to the increased water content of the samples (the physically bound water has not been removed yet at this temperature). The highest value was found for sample IZ10 and with increasing zeolite content, a gradual increase in the diffusivity value was observed (Figure 6, right)—thermal diffusivity of sample IZ50 reached only 0.35 mm2/s, while the IZ10 sample had a thermal diffusivity of 0.54 mm2/s. With increasing temperature, the physically bound water was gradually removed, and the values of thermal diffusivity decreased. The decrease became less significant after the physically bound water was liberated. During dehydroxylation, the thermal diffusivity reached its minimum due to the creation of a highly defective structure of illite (octahedral layers losing their OH− groups). Once the dehydroxylation finished, the thermal diffusivity started to increase along with the increasing temperature. The measurements were carried out only up to 900 °C due to the progressive shrinkage of the samples during sintering (the samples could not remain in the sample holder). The highest decrease and the most pronounced dependence of the diffusivity values on the temperature was observed in the case of the IZ10 sample (the value of the diffusivity decreased by 21%). Zeolite exhibits almost constant values of thermal diffusivity over the whole studied temperature interval (0.21 mm2/s) [29]. With increasing zeolite content, the dependence of the thermal diffusivity on the temperature became less significant. The lowest values of thermal diffusivity were observed for the IZ50 sample almost in the whole studied temperature interval. Moreover, the thermal diffusivity of sample IZ50 changed only slightly during the heating. The differences in the thermal diffusivity values of the individual samples decreased with increasing temperature (Figure 9b). 3.9. Thermal Conductivity The thermal conductivity values follow the same trend as the thermal diffusivity values—with increasing zeolite content, the value of thermal conductivity decreases (Figure 10a). The effect of the physically bound water was pronounced in sample IZ10, whilst the other samples exhibited almost no changes in the thermal conductivity values up to 300–400 °C. In this temperature region, the thermal conductivities of all samples reached their minimal values. The plateau-like dependency of the thermal conductivities of the samples can be ascribed to the gradual evaporation of water from the zeolite in the samples, which prevents the decrease in the thermal conductivity after the evaporation of the physically bound water from the illite. As the dehydroxylation started the thermal conductivity began to increase and this lasted up to 900 °C. It should be noted that measurements were finished at the onset of the sintering to prevent the samples from falling from the holder due to their progressive shrinkage. Comparing the thermal conductivity values of individual samples showed that the zeolite addition led to a decrease at all temperatures (Figure 10b). This behavior can be explained by the increased porosity of the samples with higher zeolite content. In addition, the thermal conductivity of zeolite is only 0.37 W/(m·K) [29]. Thus, its increasing amount decreases the thermal conductivity. At room temperature, the IZ10 sample exhibited a conductivity value of 1.03 W/(m·K), while the sample containing 50 wt.% of zeolite reached only 0.50 W/(m·K), half of that of the IZ10 sample. At 900 °C, this difference decreased—the values of thermal conductivity were 1.90 W/(m·K) and 1.47 W/(m·K) for the IZ10 and IZ50 samples, respectively. Nevertheless, the difference still remained significant. On the other hand, it should be mentioned, that the uncertainty of the measurement method reaches 6%. This feature suggested that the mixture has potential in the building industry, as the thermal insulation properties are improving with an increasing zeolite addition. 3.10. Specific Heat Capacity Heat capacity (Figure 11) exhibited an increasing trend with rising temperature, as expected by the Debye model. The addition of zeolite did not lead to any significant difference in the specific heat capacity at room temperature. The values of the specific heat capacity fall within the range from 1.12 to 1.02 kJ/(kg·K), in decreasing order with increasing zeolite content. At higher temperatures, the trends were not that straightforward. The effect of the removal of the physically bound water, as well as the effect of dehydroxylation, were not observable on the temperature dependence of the specific heat capacity. Nevertheless, the differences became significant, as the temperature reached 800 °C, and remained similar at 900 °C, where the sintering started. An opposite behavior was observed in the case of the mixtures of kaolin with zeolite, where the specific heat capacity decreased with an increasing zeolite content [29]. At the temperature of 900 °C, the value of specific heat capacity reached 2.97 kJ/(kg·K) for the IZ10 sample and 3.76 kJ/(kg·K) for the IZ50 sample. 4. Conclusions The mixtures of illitic clay (originating from northeastern Hungary) with five different amounts of natural zeolite (Slovakia) were studied by thermal analyses. Differential thermal analysis, thermogravimetry, and differential compensating calorimetry showed that the addition of zeolite influences the amount of physically bound water in the samples. Moreover, the addition of zeolite decreased the peak temperatures of the illite dehydroxylation—from 609 °C to 575 °C in the first step and from 713 °C to 702 °C in the second step. The overall mass losses of the mixtures changed significantly with an increasing zeolite amount. The illitic clay exhibited 6.9% mass loss over the studied temperature region, while the mass loss of the IZ50 sample reached 9.5%. The zeolite addition decreased the onset temperature of the sintering process from 1021 °C (illitic clay) to 1005 °C (IZ50) and increased the sample shrinkage from 5.6% (illitic clay) to 10.8% (IZ50). The dominant mineralogical phase in the IZ10 sample was quartz. However, its amount gradually decreased by increasing the zeolite content. As the amount of zeolite exceeded 30 wt.%, albite started to form instead of orthoclase. This was explained by the sodium content of the zeolite, which supports the formation of albite. Thermal diffusivity and conductivity reached the highest values for the samples with the lowest amount of zeolite (0.54 mm2/s and 1.03 W/(m·K) for diffusivity and conductivity, respectively). The difference between the values of the diffusivity of the samples decreased with increasing temperature. The lowest changes in the thermal diffusivity were observed in the IZ50 sample. A minimum in the diffusivity values was achieved around the illite dehydroxylation temperature. The above-mentioned results confirmed that by adding even a low amount of zeolite to the illitic clay, its sintering starts at lower temperatures. Moreover, zeolite addition increased the sample porosity which, in turn, led to a decrease in the values of the thermal conductivity. Due to the lower thermal conductivity values of the samples, the prepared mixtures might find uses as building materials, with better insulating properties, than pure illitic clay. Acknowledgments Authors wish to thank the company ZEOCEM, a.s. (Bystré, Slovakia), for the supply of natural zeolite. Author Contributions Conceptualization, A.T. and Š.C.; methodology, A.T., Š.C., F.L. and I.S.; investigation, Š.C., F.L. and I.S.; writing—original draft preparation, Š.C. and I.S.; writing—review and editing, Š.C., A.T. and G.Ł.; visualization, Š.C. and A.T.; supervision, A.T.; project administration, A.T.; funding acquisition, A.T. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Czech Science Foundation, Grant No. 20-01536S. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Differential thermal analysis of the samples (a). Peak temperatures of the illite dehydroxylation (1st and 2nd step) (b). Figure 2 DSC analysis of the mixtures and initial materials. Figure 3 The mass change of the prepared samples and initial materials (a). Comparison of the total mass losses (b). Figure 4 Dilatometry of the prepared mixtures and initial materials. Inset graph: Onset of the sintering (a). Relative expansion of the samples at different temperatures (b). Figure 5 Coefficient of linear thermal expansion of the samples. Figure 6 XRD analysis of the prepared samples. Figure 7 Bulk density of the samples. Figure 8 Porosity of the samples fired at different temperatures. Figure 9 Thermal diffusivity of the mixtures (a). Comparison of thermal diffusivities at different temperatures (b). Figure 10 Thermal conductivity of the mixtures (a). Comparison of thermal conductivities at different temperatures (b). Figure 11 Specific heat capacity of the samples. materials-15-03029-t001_Table 1 Table 1 Chemical composition of illitic clay and natural zeolite (in wt.%). Oxides SiO2 Al2O3 Fe2O3 TiO2 CaO MgO K2O Na2O L.O.I Illitic clay 58.4 23.9 0.6 - 0.4 1.7 7.7 0.1 7.2 Zeolite 68.2 12.3 1.3 0.2 3.9 0.9 2.8 0.7 11.35 materials-15-03029-t002_Table 2 Table 2 The compositions of the samples made from Sedlec kaolin and natural zeolite (in mass%). Sample ILB IZ10 IZ20 IZ30 IZ40 IZ50 ZEO Illitic clay 100 90 80 70 60 50 - Zeolite - 10 20 30 40 50 100 materials-15-03029-t003_Table 3 Table 3 Phase composition of the fired samples (in wt.%). Mineral Phase Illitic Clay IZ10 IZ20 IZ30 IZ40 IZ50 ZEO Quartz 34 32 28 25 24 22 14 Al2O3 31 26 27 25 20 21 - Orthoclase 13 15 17 16 - - - Mullite 22 24 21 26 25 21 - Cristobalite - 3 7 8 10 11 52 Albite - - - - 21 25 34 Amorphous 56 53 47 47 43 47 45 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ferrari S. Gualtieri A.F. The use of illitic clays in the production of stoneware tile ceramics Appl. Clay Sci. 2006 32 73 81 10.1016/j.clay.2005.10.001 2. Gualtieri A.F. Ferrari S. Leoni M. Grathoff G. Hugo R. Shatnawi M. Paglia G. Billinge S. Structural characterization of the clay mineral illite-1M J. Appl. Crystallogr. 2008 41 402 415 10.1107/S0021889808004202 3. Drits V.A. McCarty D.K. The nature of structure-bonded H2O in illite and leucophyllite from dehydration and dehydroxylation experiments Clays Clay Miner. 2007 55 45 58 10.1346/CCMN.2007.0550104 4. Gualtieri A.F. Ferrari S. Kinetics of illite dehydroxylation Phys. Chem. Miner. 2006 33 490 501 10.1007/s00269-006-0092-z 5. Viczián I. Hungarian investigation on the “Zempleni” illite Clays Clay Miner. 1997 45 114 115 10.1346/CCMN.1997.0450114 6. De Araújo J.H. da Silva N.F. Acchar W. Gomes U.U. Thermal decomposition of illite Mater. Res. 2004 7 359 361 Available online: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392004000200024&nrm=iso (accessed on 21 March 2022) 10.1590/S1516-14392004000200024 7. Wang G. Wang H. Zhang N. In situ high temperature X-ray diffraction study of illite Appl. Clay Sci. 2017 146 254 263 10.1016/j.clay.2017.06.006 8. Čejka J. Zilkova N. Syntéza a struktura zeolitu Chem. List. 2000 94 278 287 9. Bogdanov B. Georgiev D. Angelova K. Yaneva K. Natural Zeolites: Clinoptilolite Review Econ. Soc. Dev. Base Knowl. 2009 4 6 11 Available online: https://www.yumpu.com/en/document/read/15593360/natural-zeolites-clinoptilolite (accessed on 23 March 2017) 10. Roque-Malherbe R. Chapter 12 Applications of natural zeolites in pollution abatement and industry Handb. Surfaces Interfaces Mater. 2001 5 495 522 10.1016/B978-0-12-513910-6.50069-4 11. Favvas E.P. Tsanaktsidis C.G. Sapalidis A.A. Tzilantonis G.T. Papageorgiou S.K. Ch Mitropoulos A. Mitropoulos A.C. Clinoptilolite, a natural zeolite material: Structural characterization and performance evaluation on its dehydration properties of hydrocarbon-based fuels Microporous Mesoporous Mater. 2016 225 385 391 10.1016/j.micromeso.2016.01.021 12. Polat E. Karaca M. Demir H. Onus N. Use of natural zeolite (clinoptilolite) in agriculture J. Fruit Ornam. Plant Res. 2004 12 183 189 13. Mansouri N. Rikhtegar N. Panahi H.A.H.A. Atabi F. Shahraki B.K.B.K.B.K. Porosity, characterization and structural properties of natural zeolite-clinoptilolite-As a Sorbent Environ. Prot. Eng. 2013 39 139 152 10.5277/EPE130111 14. Kocak Y. Tascı E. Kaya U. The effect of using natural zeolite on the properties and hydration characteristics of blended cements Constr. Build. Mater. 2013 47 720 727 10.1016/j.conbuildmat.2013.05.033 15. Inglezakis V.J. The concept of “capacity” in zeolite ion-exchange systems J. Colloid Interface Sci. 2005 281 68 79 10.1016/j.jcis.2004.08.082 15567382 16. Bıyık R. Tapramaz R. An EPR study of clinoptilolite from Bigadiç in Turkey Microporous Mesoporous Mater. 2016 219 38 41 10.1016/j.micromeso.2015.07.030 17. Cieśla J. Franus W. Franus M. Kedziora K. Gluszczyk J. Szerement J. Jozefaciuk G. Environmental-Friendly Modifications of Zeolite to Increase Its Sorption and Anion Exchange Properties, Physicochemical Studies of the Modified Materials Materials 2019 12 3213 10.3390/ma12193213 18. Bandura L. Franus M. Madej J. Kołodyńska D. Hubicki Z. Zeolites in Phenol Removal in the Presence of Cu(II) Ions—Comparison of Sorption Properties after Chitosan Modification Materials 2020 13 643 10.3390/ma13030643 19. Lamprecht M. Bogner S. Steinbauer K. Schuetz B. Greilberger J.F. Leber B. Wagner B. Zinser E. Petek T. Wallner-Liebmann S. Effects of zeolite supplementation on parameters of intestinal barrier integrity, inflammation, redoxbiology and performance in aerobically trained subjects J. Int. Soc. Sports Nutr. 2015 12 40 10.1186/s12970-015-0101-z 26500463 20. Laurino C. Palmieri B. Zeolite: “the magic stone”; main nutritional, environmental, experimental and clinical fields of application Nutr. Hosp. 2015 32 573 581 26268084 21. Trník A. Scheinherrová L. Medveď I. Černý R. Simultaneous DSC and TG analysis of high-performance concrete containing natural zeolite as a supplementary cementitious material J. Therm. Anal. Calorim. 2015 121 67 73 10.1007/s10973-015-4546-8 22. Vejmelková E. Koňáková D. Kulovaná T. Keppert M. Žumár J. Rovnaníková P. Keršner Z. Sedlmajer M. Černý R. Engineering properties of concrete containing natural zeolite as supplementary cementitious material: Strength, toughness, durability, and hygrothermal performance Cem. Concr. Compos. 2015 55 259 267 10.1016/j.cemconcomp.2014.09.013 23. Franus W. Jozefaciuk G. Bandura L. Franus M. Use of Spent Zeolite Sorbents for the Preparation of Lightweight Aggregates Differing in Microstructure Minerals 2017 7 25 10.3390/min7020025 24. Barnat-Hunek D. Siddique R. Klimek B. Franus M. The use of zeolite, lightweight aggregate and boiler slag in restoration renders Constr. Build. Mater. 2017 142 162 174 10.1016/j.conbuildmat.2017.03.079 25. Húlan T. Trník A. Kaljuvee T. Uibu M. Štubňa I. Kallavus U. Traksmaa R. The study of firing of a ceramic body made from illite and fluidized bed combustion fly ash J. Therm. Anal. Calorim. 2017 127 79 89 10.1007/s10973-016-5477-8 26. Knapek M. Húlan T. Dobroň P. Chmelík F. Trník A. Štubňa I. Acoustic Emission During Firing of the Illite-Based Ceramics with Fly Ash Addition Acta Phys. Pol. A 2015 128 783 786 10.12693/APhysPolA.128.783 27. Kaljuvee T. Štubňa I. Somelar P. Mikli V. Kuusik R. Thermal behavior of some Estonian clays and their mixtures with oil shale ash additives J. Therm. Anal. Calorim. 2014 118 891 899 10.1007/s10973-014-3797-0 28. Csáki Š. Húlan T. Ondruška J. Štubňa I. Trnovcová V. Lukáč F. Dobroň P. Electrical conductivity and thermal analyses studies of phase evolution in the illite–CaCO3 system Appl. Clay Sci. 2019 178 105140 10.1016/j.clay.2019.105140 29. Ondruška J. Húlan T. Sunitrová I. Csáki Š. Łagód G. Struhárová A. Trník A. Thermophysical Properties of Kaolin–Zeolite Blends up to 1100 °C Crystals 2021 11 165 10.3390/cryst11020165 30. Húlan T. Štubňa I. Ondruška J. Csáki Š. Lukáč F. Mánik M. Vozár L. Ozolins J. Kaljuvee T. Trník A. Young’s modulus of different illitic clays during heating and cooling stage of firing Materials 2020 13 4968 10.3390/ma13214968 31. Zeolite Data Sheet Available online: Http://zeocem.sk/wp-content/uploads/2013/10/Zeolite_Data_Sheet-SJ.pdf (accessed on 14 March 2017) 32. Podoba R. Podobník Ľ. Upgrading of TGA/DTA analyzer derivatograph Epa. J. Silic. Based Compos. Mater. 2012 64 28 29 10.14382/epitoanyag-jsbcm.2012.5 33. Rietveld H.M. Line profiles of neutron powder-diffraction peaks for structure refinement Acta Crystallogr. 1967 22 151 152 10.1107/S0365110X67000234 34. Hill R.J. Howard C.J. Quantitative phase analysis from neutron powder diffraction data using the Rietveld method J. Appl. Crystallogr. 1987 20 467 474 10.1107/S0021889887086199 35. Dollase W.A. Correction of intensities for preferred orientation in powder diffractometry: Application of the March model J. Appl. Crystallogr. 1986 19 267 272 10.1107/S0021889886089458 36. Tagliente M.A. Massaro M. Strain-driven (002) preferred orientation of ZnO nanoparticles in ion-implanted silica Nucl. Instrum. Methods Phys. Res. Sect. B Beam Interact. Mater. Atoms 2008 266 1055 1061 10.1016/j.nimb.2008.02.036 37. Alver B.E. Sakizci M. Yörükoğullari E. Investigation of clinoptilolite rich natural zeolites from Turkey: A combined XRF, TG/DTG, DTA and DSC study J. Therm. Anal. Calorim. 2010 100 19 26 10.1007/s10973-009-0118-0 38. Csáki Š. Ondruška J. Trnovcová V. Štubňa I. Dobroň P. Vozár L. Temperature dependence of the AC conductivity of illitic clay Appl. Clay Sci. 2018 157 19 23 10.1016/j.clay.2018.02.026 39. Saarenketo T. Electrical properties of water in clay and silty soils J. Appl. Geophys. 1998 40 73 88 10.1016/S0926-9851(98)00017-2 40. Foldesova M. Hudec P. Dillinger P. Chemically modified zeolites: Surfaces and interaction with Cs and Co Inst. Pet. Coal 2007 49 60 63 41. Che C. Glotch T.D. Bish D.L. Michalski J.R. Xu W. Spectroscopic study of the dehydration and/or dehydroxylation of phyllosilicate and zeolite minerals J. Geophys. Res. 2011 116 E05007 10.1029/2010JE003740 42. Knapek M. Húlan T. Minárik P. Dobroň P. Stubňa I. Stráská J. Chmelík F. Study of microcracking in illite-based ceramics during firing J. Eur. Ceram. Soc. 2016 36 221 226 10.1016/j.jeurceramsoc.2015.09.004

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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093106 materials-15-03106 Article Analysis of a Pure Magnesium Membrane Degradation Process and Its Functionality When Used in a Guided Bone Regeneration Model in Beagle Dogs https://orcid.org/0000-0002-3620-7199 Rider Patrick 12† https://orcid.org/0000-0002-8250-723X Kačarević Željka Perić 123† Elad Akiva 2 Rothamel Daniel 4 Sauer Gerrit 4 Bornert Fabien 5 Windisch Peter 6 Hangyási Dávid 6 https://orcid.org/0000-0001-6307-4873 Molnar Balint 6 Hesse Bernhard 7 Witte Frank 1* Schierano Gianmario Academic Editor Muzio Giuliana Academic Editor 1 Department of Prosthodontics, Geriatric Dentistry and Craniomandibular Disorders, Charité—Universitätsmedizin Berlin, Aßmannshauser Straße 4–6, 14197 Berlin, Germany; patrick.rider@botiss.com (P.R.); zpkacarevic@fdmz.hr (Ž.P.K.) 2 Botiss Biomaterials AG, Ullsteinstrasse 108, 12109 Berlin, Germany; a.elad@hotmail.com 3 Department of Anatomy Histology, Embryology, Pathology Anatomy and Pathology Histology, Faculty of Dental Medicine and Health, University of Osijek, 31000 Osijek, Croatia 4 CMF Surgery, Johannes BLA Hospital, 41239 Mönchengladbach, Germany; daniel.rothamel@mg.johanniter-kliniken.de (D.R.); gerritsauer@me.com (G.S.) 5 Faculté de Chirurgie Dentaire de Strasbourg, Université de Strasbourg, 8 rue Sainte-Elisabeth, 67000 Strasbourg, France; bornertfabien@gmail.com 6 Department of Periodontology, Semmelweis University, 1769 Budapest, Hungary; peter.windisch@gmail.com (P.W.); sosefelejtemel@gmail.com (D.H.); molbal81@gmail.com (B.M.) 7 Xploraytion GmbH, Bismarkstrasse 11, 10625 Berlin, Germany; hesse@xploraytion.com * Correspondence: frank.witte@charite.de † These authors contributed equally to this work. 25 4 2022 5 2022 15 9 310621 3 2022 22 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). For the surgical technique of guided bone regeneration (GBR), the choice of available barrier membranes has until recently not included an option that is mechanically strong, durable, synthetic and resorbable. The most commonly used resorbable membranes are made from collagen, which are restricted in their mechanical strength. The purpose of this study is to evaluate the degradation and regeneration potential of a magnesium membrane compared to a collagen membrane. In eighteen beagle dogs, experimental bone defects were filled with bovine xenograft and covered with either a magnesium membrane or collagen membrane. The health status of the animals was regularly monitored and recorded. Following sacrifice, the hemimandibles were prepared for micro-CT (μ-CT) analysis. Complications during healing were observed in both groups, but ultimately, the regenerative outcome was similar between groups. The μ-CT parameters showed comparable results in both groups in terms of new bone formation at all four time points. In addition, the μ-CT analysis showed that the greatest degradation of the magnesium membranes occurred between 1 and 8 weeks and continued until week 16. The proportion of new bone within the defect site was similar for both treatment groups, indicating the potential for the magnesium membrane to be used as a viable alternative to collagen membranes. Overall, the new magnesium membrane is a functional and safe membrane for the treatment of defects according to the principles of GBR. NOVAMag membrane resorbable membrane GBR healing magnesium degradation micro-CT ==== Body pmc1. Introduction The concept of guided bone regeneration (GBR) is based on the placement of a barrier membrane to exclude unwanted tissues and cells from a secluded bony defect. The membrane provides space for slowly proliferating bone cells to populate the defect space, which would otherwise be occupied by faster proliferating soft tissue cells [1,2]. In addition to the exclusion of unwanted tissues, the membrane creates space for undisturbed bone regeneration, protects the underlying blood clot and stabilizes the wound. Collagen barrier membranes are currently one of the most commonly used resorbable membranes for GBR surgeries [3,4], and they demonstrate an excellent biocompatibility [5]. Due to their structure, collagen nanofibers have a good bioactive potential in bioregeneration [6]. Yet a relatively low mechanical strength means that they are susceptible to tearing or collapse into the defect void [7], which has been reported as the main drawback for using collagen membranes [8], because it does not provide sufficient volume stability at the time of bone formation [9]. In order to better control the degradation and improve the mechanical and chemical properties of collagen, new synthetic approaches have emerged that improve the properties of the collagen membrane [10,11]. There is also the potential issue of conflicting patient views, who may opt for synthetic materials. To address these issues, a new pure magnesium barrier membrane has been developed for GBR applications (Figure 1) and has previously been reported on [12]. The membrane is intended to function similarly to other degradable barrier membranes; however, due to its metallic structure, it provides better mechanical properties (than e.g., collagen) and has an initial form stability to protect the defect void from collapse. Magnesium is a biodegradable metal that has been used for medical applications for over 100 years [13], owing to its excellent biocompatibility, bioabsorbability and biomechanical properties [14]. As it degrades, its metallic structure is converted into magnesium salts that are then resorbed by the body [15,16,17]. As a fully biodegradable metal membrane, no removal surgery is necessary, resulting in fewer surgical interventions. During its degradation under physiological conditions, hydrogen gas is released [18,19]. The release of hydrogen gas has previously been reported to form gas cavities around magnesium metal implants; however, these gas cavities are also reported to spontaneously resolve and not have a negative effect on bone regeneration [15,16,17,20]. As with other degradable membranes, it is important that the resorption rate enables a sufficient barrier between the soft and the hard tissues during the initial healing phase, but also for it to be fully removed from the site once it is no longer needed. The resorption time should not exceed 6–12 months; otherwise, the benefits provided by using a resorbable material might be lost [21]. Studies performed using collagen membranes give an indication for the optimal functional lifespan of a barrier membrane. An in vivo study using rat calvarial defects performed by Kim et al. reported that the collagen membrane, Bio-Gide®, remained intact after 2 weeks, but after 4 weeks, it had lost its barrier function [22]. A study by von Arx et al. performed in rabbit tibias showed that the collagen membrane was intact after 2 weeks but reduced in size after 6 weeks healing. After 12 weeks, no differentiation to the host collagen could be made [23]. In a GBR canine model, collagen membrane degradation has been reported with more varied rates, even when using the same type of collagen membrane. Ivanovic et al. used a double layer technique to prolong functionality and reported the presence of residual membrane material at 12 weeks post-implantation [24]. Rothamel et al. reported that the membrane was resorbed between 4 and 8 weeks post-implantation [25], whilst Zubery et al. reported complete degradation of the membrane at different stages of the study, ranging from the first (8 weeks) to the last (24 weeks) time point [26]. Based on these studies reporting the degradation of a collagen membrane, it can be assumed that the barrier membrane must function for a minimum period of 2–4 weeks. After this point, some of these studies have reported differing degrees of degradation and loss of barrier function; however, all resulted with a successful regenerative outcome. The magnesium membrane and all the ideal qualities for a barrier membrane were previously reported on [12]. In this article, the application of a pure magnesium barrier membrane to treat GBR defects in a canine model is reported on. The success of the membrane is determined by comparison to a standard collagen membrane. Magnesium membrane degradation and regenerative outcome are assessed using µCT. 2. Results 2.1. Post-Surgical Follow-Up As expected, for the 2 week period post-surgery (preparatory and implantation), the dogs showed signs of acute inflammation and pain. For the duration of the study, weight variations of the animals occurred as expected and remained within the anticipated ranges for beagle dogs under the conditions of this kind of study. All animals survived until their scheduled sacrifice. Following the teeth extraction surgery (preparatory phase), some dogs required additional antimicrobial treatment or bone sequestrum removal; however, all sites ended up with a good healing result. Post-implantation (experimental phase), eight animals required an additional intervention, such as additional chlorhexidine rinsing or re-suturing; however, all sites ended up healing well. Additional interventions were mainly caused by swelling associated with magnesium membrane treated sites; however, in two of the eight animals, additional intervention was also required for collagen membrane treated sites. Most observations of swelling or lesions present at the magnesium membrane treated sites were reported during the scheduled surgical wound re-evaluation at 28 ± 2 days. Around this timepoint, 13 magnesium membrane treated sites in a total of 7 dogs reported observations of swelling. Two of these sites also reported the presence of lesions. After an additional treatment of chlorhexidine rinsing (for 3 dogs) and a varying healing period between 3 and 10 days, there were no abnormal findings reported by the veterinarian. At the next scheduled re-evaluation (42 ± 2 days), one additional magnesium membrane-treated site was reported to have swelling and a lesion, both of which resolved after 10 days. Another surgical site in another dog was also observed to be open, however without the presence of swelling, and it resolved itself after 10 days. The redness of the surgical site was reported for four dogs and did not occur in conjunction with any swelling. Of these dogs, two were observed to have one site treated with magnesium membrane that had a slight redness. The slight redness was reported at only one timepoint for each dog (at day 36 and 43, respectively). Another dog was reported to have a slight redness for both magnesium membrane-treated sites. This was reported over a prolonged period of time, which was mentioned at day 36 and 52 for both sites; however, no abnormal findings were reported at day 57. The last animal with reported redness was observed to have a small red spot (3 mm in diameter) at a collagen membrane-treated site. The small red spot was reported after the healing of a lesion at the same site. 2.2. Micro-CT The results of the measured µCT parameters are shown in Table 1 and visually compared in Figure 2. One week post-implantation, the measured µCT parameters of new bone and soft tissue appear similar between the magnesium and collagen membrane groups. At this timepoint, the only significantly different value was the volume of the void space (p < 0.001). This developed in the magnesium membrane group due to the release of hydrogen gas during the magnesium corrosive process. At 8 weeks post-implantation, the void space for the magnesium membrane had been resorbed and was no longer significantly different to that measured for the collagen membrane. There was no significant difference between the new bone volume between each group; however, there was more soft tissue present in the collagen membrane group (p ≤ 0.05) than in the defects treated with the magnesium membrane. The ratio of bone volume to total defect volume was comparable between the two groups (0.30 ± 0.07 for the magnesium membrane-implanted defects compared to 0.26 ± 0.05 for the collagen membrane-implanted defects). By 16 weeks, there were no significant differences between either of the groups for any of the measured parameters. The average soft tissue volume remained slightly higher in the collagen membrane treated defect sites (30.15 ± 8.75 mm3 for the collagen group compared to 25.74 ± 6.49 mm3 for the magnesium group), although it was non-significant. The bone volume to total volume ratio appears to be slightly higher for the magnesium membrane-treated defects (0.41 ± 0.09 mm3) compared to (0.34 ± 0.10 mm3) for the collagen group, but again, it was non-significant. For the 52-week timepoint, the new bone volume and soft tissue volume appear to be slightly lower for the magnesium membrane-treated defects, although this is related to the measured total defect volume being slightly lower than that of the collagen membrane-treated defects. Similarly, for the 16 week timepoint, the bone volume to total volume ratio appears to be slightly higher for the magnesium membrane defects, 0.62 ± 0.17 mm3 compared to 0.57 ± 0.05 mm3 for the collagen membrane-treated group. The implanted magnesium membranes were successfully detected and segmented. The magnesium metal was denser than the surrounding tissue, thus enabling it to be identified. Remnants of the metallic magnesium membrane could be identified and separated from other objects in the 3D gray-scale images. Representative images of the segmented magnesium membranes and the surrounding bone tissue at each timepoint are shown in Figure 3. In only one of the samples from the 16-week timepoint (n = 12) could remnant magnesium metal and salty phase still be detected. At the 52-week timepoint, there was no metallic magnesium present at any of the defect sites (n = 4). At the one week timepoint, metallic magnesium, magnesium salts and small gas cavities are shown to seclude the overlying soft tissue from the bony defect. Measurements of the residual magnesium are shown in Figure 4. These measurements indicated an average total volume of residual magnesium metal at 1 week to be 7 ± 2 mm3. This average decreases significantly by week 8 to 0 ± 1 mm3 (p < 0.001) and then further to 0 ± 0 mm3 at week 16 (p < 0.05). Surface area measurements of the magnesium metal measured an average area of 198 ± 38 mm2 at week 1. This significantly dropped to 17 ± 22 mm2 at week 8 (p < 0.05) and then further to 0 ± 0 mm2 by week 16 (p < 0.05). All of the magnesium membranes appeared to have completely degraded at the 52-week timepoint, with both surface area and total volume measured at 0 ± 0 mm2 and 0 ± 0 mm3, respectively. Although not indicated by the surface area and volume measurements, small remnants of the magnesium membrane were still visible in one of the samples at 16 weeks. Gas pockets formed as the magnesium metal degraded, which are visible around the membrane at the 1 week timepoint (Figure 3). The gas pockets were predominantly situated between the overlying soft tissue and the magnesium membrane upper surface, although some gas pockets were visible under the membrane as well. After 8 weeks, the majority of the gas pockets have been resorbed by the tissue, and at 16 weeks post-implantation, there are no remaining gas pockets in the vicinity of the defect site. 3. Discussion A magnesium membrane has been investigated for its use in GBR surgeries. Applied to GBR defects in beagle dogs, the membrane has shown a comparable efficiency to that of a standard collagen membrane. The first important outcome of this study was that the animals had a satisfactory general condition for the duration of the study when a magnesium membrane was applied in a GBR setting. Post-implantation monitoring showed a limited number of healing irregularities, such as swelling and lesions that were more frequently occurring in the magnesium membrane group. Although additional intervention was required for some of these animals, in all cases, the conditions stabilized or healed well without affecting the regenerative outcome. Both the magnesium membrane and the collagen membrane treatment groups did not present signs of a chronic inflammation reaction such as prolonged redness, swelling, pain and loss of function. Over the course of the study, the dogs maintained a healthy weight, which demonstrates a lack of pain and the preservation of function. Signs of acute inflammation such as redness and swelling during healing are an expected potential outcome of GBR surgery. This was observed at both magnesium membrane-treated sites and collagen membrane-treated sites. In the sites treated with magnesium membrane, this phenomenon can be explained by the perfusion of magnesium ions into the soft tissue after the degradation of the magnesium membrane [27]. In a retrospective study of the clinical outcomes and complications of biodegradable magnesium screws in humans, similar observations were made for soft tissue complications [28]. However, this was also shown to be a short-term tissue reaction, as was the case in the current study. Overall, soft tissue complications were expected in both the magnesium membrane group and the collagen membrane group, but they did not affect the success of regeneration. In this study, degradation of the magnesium membrane and its influence on the regenerative outcome have been evaluated using µCT. The µCT data show that the magnesium membrane was initially stable and remained largely intact 1 week post-implantation. Between 1 week and 8 weeks, the membrane underwent significant degradation that continued until week 16, when all but one of the membranes had completely degraded (Figure 3 and Figure 4). As magnesium metal degrades, it produces hydrogen gas [19], the presence of which has been linked to a moderate inflammation reaction [28,29]. During the period between 1 and 8 weeks, the magnesium membrane experienced its largest change in volume; hence, it produced the largest volume of hydrogen, which correlates with instances of swelling that were primarily reported by the veterinarian at a 28 ± 2 days (4 weeks) post-implantation evaluation. After a maximum period of 10 days, the reported swellings had resolved, which could indicate a reduction in hydrogen gas production. Hydrogen gas released by the degrading magnesium can lead to the formation of gas cavities around magnesium implants. These were visible around the magnesium membrane at the 1 week and 8 week timepoints (Figure 3). Nevertheless, previous studies have also reported that gas cavity formation has been followed by their spontaneous regression, and that new bone formation had not been negatively affected [15,16,17,20]. This is supported by the current study, as at the first timepoint (1 week), there was significantly more void space measured within the magnesium membrane group compared to the collagen membrane group. As the magnesium continued to degrade, the void space disappeared and remained non-significantly different to that of the collagen membrane in the subsequent timepoints (8, 16 and 52 weeks). Despite the formation of gas cavities around the magnesium membrane during the early timepoints of the study, the relative volume of new bone within the defect space consistently remained non-significantly different between defects treated with either the magnesium membrane or the collagen membrane. The ideal degradation rate for a resorbable GBR membrane should support the regeneration of the periodontium by secluding the defect site from unwanted tissues, but it could also fully and rapidly remove the membrane once its function is no longer required. To establish an ideal degradation rate, it is possible to compare the magnesium membrane to collagen membranes, which are a popular choice for GBR surgeries [3]. There are very few studies available that directly include the degradation of collagen membranes in vivo as a specific outcome; however, three studies were found where the degradation and integration of a collagen membrane were evaluated for a similar canine defect model that was used in this study [24,25,26]. In the current study, the degradation of the magnesium membrane was monitored using µCT, whilst for the other studies, collagen membrane degradation was evaluated histologically. Although different timepoints were chosen, these studies give an indication of a comparable degradation rate. Using a study by Rothamel et al. as a reference for collagen membrane degradation, both the magnesium and collagen membranes had an early onset of degradation that was noted at the first post-implantation timepoint; 1 week in this study for the magnesium membrane and 4 weeks for the collagen [25]. After 8 weeks, both membranes had undergone extensive degradation, with few remnants remaining. At the next sequential time point, which was 16 weeks in this study and 12 weeks for the collagen membrane, neither membrane had any visible remnants remaining. This would indicate that the degradation rates of both membranes were similar. µCT analysis of the magnesium membrane indicated that at one week post-implantation, the metallic structure had begun to develop corrosion pits and holes, although the majority of the membrane remained intact. By week 8, even though the metallic structure of magnesium had almost completely corroded away, the bone grafting material remained in place. This is shown, as no bone substitute material can be observed outside the initially drilled bone defect. A potential reason for this is the formation of magnesium salts and hydrogen gas development during the magnesium metal degradation process, which could maintain a seclusion of the defect site [19]. This phenomenon has previously been reported on for the magnesium membrane, where its degradation kinetics were studied in a minipig model [12]. It was shown that as the membrane degraded, the resultant magnesium salt layers and gas cavities provided a secondary phase to the barrier functionality of the barrier membrane. This affect can be clearly seen at the 1 week timepoint of the segmented µCT scans (Figure 3). 4. Materials and methods 4.1. Test Item The Test Article to be evaluated in this study is a magnesium membrane (NOVAMag® membrane, botiss biomaterials GmbH, Berlin, Germany) that is produced at biotrics bioimplants AG (Berlin, Germany) from pure magnesium (99.95%). The final dimensions of the membrane are 30 × 40 mm with rounded corners that have a 4 mm radius, a thickness of 140 µm, and a weight between 245 and 330 mg. The membrane can be cut using a pair of scissors before being bent to shape and placed over the defect. It is required that the membrane be fixed into position from both the buccal and oral sides. 4.2. Animals and Anesthesia In total, 20 adult male beagle dogs (Canis familiaris) were used in this study, which was performed at the Charles River Laboratories, Montreal, ULC. The investigatory study was approved by the Testing Facility’s Institutional Animal Care and Use Committee (IACUC). The testing facility is also accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care (AAALAC) and the Canadian Council on Animal Care (CCAC). Cohorts of six animals were assigned to 1 week, 8 weeks and 16 weeks timepoints. The remaining two animals were available as spares should there be any morbidity or mortality associated with the investigation. As these spare animals were not needed, they were transferred to a 52-weeks cohort. Two surgeries were performed as part of this study: a preparatory tooth extraction surgery and the experimental implantation surgery. Prior to both surgeries, the animals underwent general anesthesia using an injection composed of a mix of Buprenorphine, Acepromazine and Glycopyrrolate administered intramuscularly. Anesthesia induction for tracheal intubation was achieved with Propofol injected intravenously via a catheter in a vessel of the left or right cephalic or saphenous vein. Upon induction of anesthesia, the subject animal was intubated and supported with mechanical ventilation. Isoflurane in oxygen was administered to maintain a surgical plane of anesthesia, and Propofol was injected intravenously as needed to improve the efficacy of the anesthesia. To achieve local anesthesia for teeth extraction and implantation procedures, as well as manage pain after surgery, 0.8–1.2 mL of Lidocaine mixed with Epinephrine 1:50.000 was administered in each side of the lower jaw. For teeth extraction surgeries, local anesthesia was also administered in each side of the upper jaw. 4.3. Surgery The procedure was performed in two phases: a preparatory and an experimental phase. The preparatory phase involved the surgical extraction of four teeth on each side of the jaw, from the mandibular second premolar to the first molar. The corresponding teeth on the upper jaw were also extracted. Teeth extraction was followed by wound closure and suturing of the upper jaw, whilst the lower jaw remained open during a healing period of 12 ± 2 weeks. Daily oral cavity flushing was performed for 13–14 days post extraction. Sutures were removed from the upper jaw after 2 ± 1 weeks. For the experimental phase surgery, two independent bone defects were created on each side of the lower jaw. The defects were filled with a bone substitute material (Bio-Oss®, Geistlich, Wolhusen, Switzerland) and covered with either a magnesium membrane or a control collagen membrane (Bio-Gide®, Geistlich). Membranes were not allocated randomly; however, an even distribution across the different sides of the lower mandible was a control of bias. Each membrane was fixed with 4 titanium screws (1.5 mm × 3 mm ProFix titanium screws, Osteogenics); 2 on the buccal side and 2 on the lingual side, followed by wound closure with sutures. Representative photos of the magnesium membrane and collagen membrane after implantation are displayed in Figure 5. Daily oral cavity flushing was performed for 6 days post-implantation for the 1 week cohort and for 14 days post-implantation for the 8, 16 and 52-week cohorts. Sutures were removed 2 ± 1 weeks post-implantation. Upon euthanasia, hemimandibles were extracted and stored individually in 100% ethanol and kept refrigerated between 4 and 8 °C. 4.4. Veterinary Intervention and Care For the duration of the study, the animals were monitored and observed (cage side observation) at least twice a day by a trained professional. The animals’ health status was followed up by a veterinarian team, as necessary. Post-operative examinations carried out by the veterinarian team were performed under anesthesia using Propofol. Scheduled examinations post-implantation occurred three times in the first week (day 1, 3, and 7), once a week for the following three weeks (approximately day 14, 21, and 28), and thereafter once every 2 weeks (approximately day 42, 56, 70, 84, and 90), or until the day of scheduled sacrifice. The animals were weighed prior to the teeth extraction surgery, the implantation surgery and sacrifice, as wells as during veterinarian follow-ups. 4.5. Micro-CT Collection and Reconstruction Prior to histological processing, each explanted hemimandible was scanned using a Nikon XTH 225 ST Micro CT scanner (Nikon, Chiyoda, Tokyo, Japan). Images were then used to reconstruct a 3D image of each implanted site. The reconstructed µCT data had a 16-bit volume and a 10 μm isotropic voxel size. Each scan contained 4 titanium screws that held the membrane in place. Where possible, each scan was used to calculate: the new bone volume/ total defect volume (BV/TV), soft tissue volume, void volume, and residual magnesium metal. Further analysis was performed to determine the surface area and volume of the magnesium metal. To quantify the morphology of the magnesium membrane, the membrane had to be segmented within the CT scan volume. The data were loaded into AVIZO software (Thermo Fisher Scientific, Waltham, MA, USA), and metallic remnants of the magnesium membrane were segmented using the Segmentation toolbox of AVIZO. Segmentation was achieved by combining manual segmentation steps together with region-growing approaches. The results of the obtained mask for the metallic magnesium membrane and its comparison to the original gray-scale images are demonstrated in Figure 6. This approach was used to differentiate between the remaining magnesium metal and the magnesium salts which retain the shape and position of the magnesium membrane. The segmented volumes were loaded into MatLab (MATLAB and Statistics Toolbox Release 2018b, The MathWorks, Inc., Natick, MA, USA), and every dataset was analyzed toward its volume and surface, its surface to volume ratio as well as the number of magnesium membrane fragments. Furthermore, the number of magnesium fragments within each scan was analyzed in terms of fragment size by performing a connected component analysis. 4.6. Statistical Analysis Statistical analysis was performed by grouping the implants according to their material and implant duration. The regeneration of the defect was analyzed using unpaired t-tests to identify statistically significant differences for the parameters BV/BT, soft tissue volume, and void space volume between the tested groups at each timepoint. Standard deviation and statistical significance are shown. p ≤ 0.05 is represented by “*” and p ≤ 0.001 is represented by “***”. To evaluate the degradation of the magnesium membrane, unpaired t-tests were used to identify statistically significant differences between the magnesium remnant surface area and volume between each sequential time point. Statistical analysis was performed using GraphPad Prism 8.1.2 Software. 5. Conclusions A pure magnesium barrier membrane has been investigated as an alternative barrier membrane to be used in GBR treatment. Applied to GBR defects created in beagle dogs, veterinarian reporting and µCT analysis showed that the magnesium membrane produced a normal healing response, had a good regenerative outcome, and degraded at a rate similar to that of a collagen membrane. Although more swelling was reported for magnesium membrane-treated sites, this did not affect the regenerative outcome, and overall, there were no indications of a chronic inflammation reaction. Bone volume within the defect site remained similar to that of defects treated with a collagen membrane throughout the duration of this study. In conclusion, the results of this study indicate that the pure magnesium membrane is an effective barrier membrane suitable for GBR treatments. Author Contributions Conceptualization, P.R. and Ž.P.K.; methodology, A.E., D.R., G.S., P.W., D.H., B.M., B.H., F.B.; writing—original draft preparation, P.R., Ž.P.K., F.W. and A.E.; writing—review and editing, D.R., G.S., F.B., P.W., D.H., B.M., B.H.; supervision, P.W., D.H.; project administration, F.W.; funding acquisition, D.R. All authors have read and agreed to the published version of the manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Institutional Review Board Statement The investigatory study was approved of by the Testing Facility’s Institutional Animal Care and Use Committee (IACUC). The testing facility is also accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care (AAALAC) and the Canadian Council on Animal Care (CCAC). Informed Consent Statement Not applicable. Data Availability Statement The data presented in this article are available on request from the corresponding author. Conflicts of Interest P.R. and Ž.P.K. are employees of botiss biomaterials GmbH. Figure 1 (a) Pure magnesium membrane (NOVAMag® membrane, botiss biomaterials GmbH, Germany) used for GBR. (b) the magnesium membrane is positioned over the bony defect during the GBR procedure to provide a mechanical barrier between the soft and the hard tissues. Figure 2 Volumetric measurements of GBR defects treated with either a magnesium membrane (blue) or collagen membrane (red): (a) New Bone Volume/Total Defect Volume; (b) Soft Tissue Volume; (c) Void Space Volume. Standard deviation and statistical significance are shown. p ≤ 0.05 is represented by “*” and p ≤ 0.001 is represented by “***”. Figure 3 Reconstructed µCT images showing the residual metallic magnesium membrane (indicated in pink and blue magnesium salts). Only a minor amount of the metallic magnesium is left after 8 weeks and is completely corroded at 16 weeks (in 11/12 samples). At 52 weeks after implantation, no residual of the remaining magnesium membrane could be observed, whilst the surrounding bone of the defect has fully integrated bone substitute material. Figure 4 Box and whisker diagrams of (a) volume and (b) surface area measurements of the magnesium membrane remnants after implantation. Range and mean values are shown. Statistical significance is shown as p ≤ 0.05 represented by “*” and p ≤ 0.001 represented by “***”. Figure 5 Surgical placement of (a) magnesium membrane and (b) collagen membrane in a GBR model in the lower left jaw of beagle dogs. In both images, two treatment sites are visible. Figure 6 Representative images of the segmented magnesium metal membrane (pink) and virtual slices (gray) at the 1-week timepoint to illustrate the allocation of remnant metallic magnesium to gray values and image properties. Small gas cavities can be seen around the membrane, which are resultant from hydrogen gas development during the degradation process. Magnesium salts can also be seen retaining the shape and position of the membrane and are distinguished from the metallic magnesium using the employed segmentation technique within the AVIZO software (Thermo Fisher Scientific, USA). materials-15-03106-t001_Table 1 Table 1 µCT volume measurements for GBR defects treated with either a magnesium membrane or collagen membrane. Week Membrane No. of Treated Defects Volume Total Defect (TV) New Bone (BV) Soft Tissue Void BV/TV (mm3) (mm3) (mm3) (mm3) 1 Magnesium 12 76.92 ± 9.41 0.34 ± 0.30 46.21 ± 10.47 4.51 ± 3.19 0.00 ± 0.00 Collagen 12 80.15 ± 11.16 0.40 ± 0.30 51.20 ± 8.31 0.07 ± 0.07 0.00 ± 0.00 8 Magnesium 12 59.93 ± 10.89 17.71 ± 4.34 30.02 ± 6.92 0.06 ± 0.10 0.30 ± 0.07 Collagen 12 74.73 ±9.73 19.65 ± 4.72 37.72 ± 6.62 0.08 ± 0.13 0.26 ± 0.05 16 Magnesium 12 64.14 ± 8.85 25.93 ± 5.02 25.74 ± 6.49 0.05 ± 0.05 0.41 ± 0.09 Collagen 12 65.97 ± 7.57 22.63 ± 6.72 30.15 ± 8.75 0.06 ± 0.06 0.34 ± 0.10 52 Magnesium 4 47.89 ± 5.94 29.17 ± 5.81 11.32 ± 6.63 0.01 ± 0.01 0.62 ± 0.17 Collagen 4 62.31 ± 2.35 35.37 ± 2.88 15.42 ± 3.90 0.00 ± 0.00 0.57 ± 0.05 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ricci L. Perrotti V. Ravera L. Scarano A. Piattelli A. Iezzi G. Rehabilitation of deficient alveolar ridges using titanium grids before and simultaneously with implant placement: A systematic review J Periodontol. 2013 84 1234 1242 10.1902/jop.2012.120314 23205918 2. Sheikh Z. Qureshi J. Alshahrani A.M. Nassar H. Ikeda Y. Glogauer M. Ganss B. Collagen based barrier membranes for periodontal guided bone regeneration applications Odontology 2017 105 1 12 10.1007/s10266-016-0267-0 27613193 3. Khojasteh A. Kheiri L. Motamedian S. Khoshkam V. Guided Bone Regeneration for the Reconstruction of Alveolar Bone Defects Ann. Maxillofac. Surg. 2017 7 263 10.4103/ams.ams_76_17 29264297 4. Liang H. Yin J. Man K. Yang X.B. Calciolari E. Donos N. Russell S.J. Wood D.J. Tronci G. A long-lasting guided bone regeneration membrane from sequentially functionalised photoactive atelocollagen Acta Biomater. 2022 140 190 205 10.1016/j.actbio.2021.12.004 34896269 5. Sbricoli L. Guazzo R. Annunziata M. Gobbato L. Bressan E. Nastri L. Selection of Collagen Membranes for Bone Regeneration: A Literature Review Materials 2020 13 786 10.3390/ma13030786 32050433 6. Hussain Z. Ullah I. Liu X. Shen W. Ding P. Zhang Y. Gao T. Mansoorianfar M. Gao T. Pei R. Tannin-reinforced iron substituted hydroxyapatite nanorods functionalized collagen-based composite nanofibrous coating as a cell-instructive bone-implant interface scaffold Chem Eng J. 2022 438 135611 10.1016/j.cej.2022.135611 7. Naenni N. Schneider D. Jung R.E. Hüsler J. Hämmerle C.H.F. Thoma D.S. Randomized clinical study assessing two membranes for guided bone regeneration of peri-implant bone defects: Clinical and histological outcomes at 6 months Clin. Oral Implant. Res. 2017 28 1309 1317 10.1111/clr.12977 27659296 8. Mir-Mari J. Wui H. Jung R.E. Hämmerle C.H.F. Benic G.I. Influence of blinded wound closure on the volume stability of different GBR materials: An in vitro cone-beam computed tomographic examination Clin. Oral Implant. Res. 2016 27 258 265 10.1111/clr.12590 25856209 9. Guo H. Xia D. Zheng Y. Zhu Y. Liu Y. Zhou Y. A pure zinc membrane with degradability and osteogenesis promotion for guided bone regeneration: In vitro and in vivo studies Acta Biomater. 2020 106 396 409 10.1016/j.actbio.2020.02.024 32092431 10. Rahighi R. Panahi M. Akhavan O. Mansoorianfar M. Pressure-engineered electrophoretic deposition for gentamicin loading within osteoblast-specific cellulose nanofiber scaffolds Mater Chem Phys. 2021 272 125018 10.1016/j.matchemphys.2021.125018 11. Liu Y. Zhang Y. An Z. Zhao H. Zhang L. Cao Y. Mansoorianfar M. Liu X. Pei R. Slide-Ring Structure-Based Double-Network Hydrogel with Enhanced Stretchability and Toughness for 3D-Bio-Printing and Its Potential Application as Artificial Small-Diameter Blood Vessels ACS Appl. Bio Mater. 2021 4 8597 8606 10.1021/acsabm.1c01052 12. Rider P. Kačarević Ž.P. Elad A. Tadic D. Rothamel D. Sauer G. Bornert F. Windisch P. Hangyási D.B. Molnar B. Biodegradable magnesium barrier membrane used for guided bone regeneration in dental surgery Bioact. Mater. 2021 14 152 168 10.1016/j.bioactmat.2021.11.018 35310351 13. Witte F. The history of biodegradable magnesium implants: A review Acta Biomater. 2010 6 1680 1692 10.1016/j.actbio.2010.02.028 20172057 14. Wu S. Jang Y.S. Lee M.H. Enhancement of Bone Regeneration on Calcium-Phosphate-Coated Magnesium Mesh: Using the Rat Calvarial Model Front. Bioeng. Biotechnol. 2021 9 277 10.3389/fbioe.2021.652334 33996780 15. Biber R. Pauser J. Brem M. Bail H.J. Bioabsorbable metal screws in traumatology: A promising innovation Trauma Case Reports. 2017 8 11 15 10.1016/j.tcr.2017.01.012 29644307 16. Atkinson H.D. Khan S. Lashgari Y. Ziegler A. Hallux valgus correction utilising a modified short scarf osteotomy with a magnesium biodegradable or titanium compression screws-a comparative study of clinical outcomes BMC Musculoskelet Disord. 2019 20 334 10.1186/s12891-019-2717-7 31319832 17. Acar B. Kose O. Turan A. Unal M. Kati Y.A. Guler F. Comparison of Bioabsorbable Magnesium versus Titanium Screw Fixation for Modified Distal Chevron Osteotomy in Hallux Valgus Biomed. Res. Int. 2018 2018 5242806 10.1155/2018/5242806 30581858 18. Gonzalez J. Hou R.Q. Nidadavolu E.P.S. Willumeit-Römer R. Feyerabend F. Magnesium degradation under physiological conditions-Best practice Bioact. Mater. 2018 3 174 185 10.1016/j.bioactmat.2018.01.003 29744455 19. Atrens A. Song G.L. Liu M. Shi Z. Cao F. Dargusch M.S. Review of Recent Developments in the Field of Magnesium Corrosion Adv. Eng. Mater. 2015 17 400 453 10.1002/adem.201400434 20. Kim B.J. Piao Y. Wufuer M. Son W.C. Choi T.H. Biocompatibility and Efficiency of Biodegradable Magnesium-Based Plates and Screws in the Facial Fracture Model of Beagles J. Oral Maxillofac. Surg. 2018 76 1055.e1 1055.e9 10.1016/j.joms.2018.01.015 29438657 21. Hämmerle C.H.F. Jung R.E. Bone augmentation by means of barrier membranes Periodontol 2003 33 36 53 10.1046/j.0906-6713.2003.03304.x 12950840 22. Kim J.Y. Yang B.E. Ahn J.H. Park S.O. Shim H.W. Comparable efficacy of silk fibroin with the collagen membranes for guided bone regeneration in rat calvarial defects J. Adv. Prosthodont. 2014 6 539 546 10.4047/jap.2014.6.6.539 25551015 23. Jensen S.S. Broggini N. Hjørting-Hansen E. Schenk R. Buser D. Bone healing and graft resorption of autograft, anorganic bovine bone and β-tricalcium phosphate. A histologic and histomorphometric study in the mandibles of minipigs Clin. Oral Implant. Res. 2006 17 237 243 10.1111/j.1600-0501.2005.01257.x 24. Ivanovic A. Bosshardt D.D. Mihatovic I. Schwarz F. Gruber R. Sculean A. Effect of pulverized natural bone mineral on regeneration of three-wall intrabony defects. A preclinical study Clin. Oral Investig. 2014 18 1319 1328 10.1007/s00784-013-1089-x 25. Rothamel D. Schwarz F. Fienitz T. Smeets R. Dreiseidler T. Ritter L. Happe A. Zöller J. Biocompatibility and biodegradation of a native porcine pericardium membrane: Results of in vitro and in vivo examinations-PubMed Int. J. Oral Maxillofac. Implant. 2012 27 146 154 26. Zubery Y. Goldlust A. Alves A. Nir E. Ossification of a novel cross-linked porcine collagen barrier in guided bone regeneration in dogs J. Periodontol. 2007 78 112 121 10.1902/jop.2007.060055 17199547 27. Witte F. Hort N. Vogt C. Cohen S. Kainer K.U. Willumeit R. Feyerabend F. Degradable biomaterials based on magnesium corrosion Curr. Opin. Solid State Mater. Sci. 2008 12 63 72 10.1016/j.cossms.2009.04.001 28. Kim Y.K. Lee K.B. Kim S.Y. Bode K. Jang Y.S. Kwon T.Y. Jeon M.H. Lee M.H. Gas formation and biological effects of biodegradable magnesium in a preclinical and clinical observation Sci. Technol. Adv. Mater. 2018 19 324 335 10.1080/14686996.2018.1451717 29707071 29. Walker J. Shadanbaz S. Woodfield T.B.F. Staiger M.P. Dias G.J. The in vitro and in vivo evaluation of the biocompatibility of Mg alloys Biomed. Mater. 2014 9 015006 10.1088/1748-6041/9/1/015006 24343544

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094503 ijms-23-04503 Review Multiple Roles of SMC5/6 Complex during Plant Sexual Reproduction https://orcid.org/0000-0002-3048-4259 Yang Fen 12 https://orcid.org/0000-0001-9277-1766 Pecinka Ales 12* Tattini Massimiliano Academic Editor 1 Centre of the Region Haná for Biotechnological and Agricultural Research (CRH), Institute of Experimental Botany (IEB), Czech Academy of Sciences, 77900 Olomouc, Czech Republic; yang@ueb.cas.cz 2 Department of Cell Biology and Genetics, Faculty of Science, Palacký University, 77900 Olomouc, Czech Republic * Correspondence: pecinka@ueb.cas.cz 19 4 2022 5 2022 23 9 450328 2 2022 13 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Chromatin-based processes are essential for cellular functions. Structural maintenance of chromosomes (SMCs) are evolutionarily conserved molecular machines that organize chromosomes throughout the cell cycle, mediate chromosome compaction, promote DNA repair, or control sister chromatid attachment. The SMC5/6 complex is known for its pivotal role during the maintenance of genome stability. However, a dozen recent plant studies expanded the repertoire of SMC5/6 complex functions to the entire plant sexual reproductive phase. The SMC5/6 complex is essential in meiosis, where its activity must be precisely regulated to allow for normal meiocyte development. Initially, it is attenuated by the recombinase RAD51 to allow for efficient strand invasion by the meiosis-specific recombinase DMC1. At later stages, it is essential for the normal ratio of interfering and non-interfering crossovers, detoxifying aberrant joint molecules, preventing chromosome fragmentation, and ensuring normal chromosome/sister chromatid segregation. The latter meiotic defects lead to the production of diploid male gametes in Arabidopsis SMC5/6 complex mutants, increased seed abortion, and production of triploid offspring. The SMC5/6 complex is directly involved in controlling normal embryo and endosperm cell divisions, and pioneer studies show that the SMC5/6 complex is also important for seed development and normal plant growth in cereals. SMC5/6 complex genome stability meiosis seed reproductive development fertility polyploidy ==== Body pmc1. Introduction Recent studies revealed extensive dynamics in plant nuclear and chromosomal organization [1,2,3]. Plant chromosome and chromatin are very dynamic during sexual reproduction, where different stages are quickly substituted for one another and many events occur in a small number of highly specialized cells [4,5,6]. The process starts with meiosis, continues through gametogenesis and fertilization, and finally seed development. Sexual reproduction is crowned by precisely controlled nuclear divisions, the regulated repair of programmed DNA double-strand breaks, and a reduction in chromosome number. Many of these steps are orchestrated and surveilled by the family of evolutionarily conserved large-scale chromatin-processing molecular machines called structural maintenance of chromosomes (SMCs), along with other factors [7,8]. Whereas the functional role of cohesin and condensin SMC complexes during plant reproductive development has long been known [9], the functions of the SMC5/6 complex emerged only recently and are quickly accumulating [10]. The SMC5/6 complex is known mainly for its role during DNA damage repair across eukaryotic kingdoms [11,12,13]. In plants, it has been identified as a factor required for normal levels of somatic homologous recombination (HR) and resistance to various types of DNA-damaging agents [10,14]. However, recent papers on plant reproduction revealed many new fascinating phenotypes of SMC5/6 complex mutants. Furthermore, these studies also contributed strong evidence suggesting that this complex affects multiple processes within one developmental stage, sometimes via unknown or previously unanticipated pathways. Therefore, our review focuses mostly on the new findings concerning SMC5/6 functions in plant sexual reproductive development. The basic subunits and structure of the SMC5/6 complex have been described [13,15,16]. Briefly, it consists of two SMC proteins and up to six (organism-dependent) additional subunits, commonly termed Non-SMC elements (NSEs). The SMC5 and SMC6 proteins are ATPases that form a heterodimer via their hinge domains. At the opposite end, the SMC heads are bridged via the kleisin-type protein NSE4. The NSE1 and NSE3 subunits bind the NSE4 and are important for the complex’s attachment to DNA and processivity. The targets of ubiquitin ligase NSE1 [17] remain unknown, but a recent study revealed that it can ubiquitinate NSE4 in Schizosaccharomyces pombe [18]. The NSE2 (a.k.a. Methyl methanesulfonate-sensitive 21-MMS21, HIGH PLOIDY 2-HPY2) is an E3 small ubiquitin modifier (SUMO) ligase attached to the coiled-coil of SMC5 [19,20,21,22]. Its SUMOylation targets likely differ between organisms and include DNA repair proteins, as well as some SMC5/6 complex subunits [19,23,24]. The only identified NSE2 target in Arabidopsis is NSE4A [25]. In addition, there are two to three evolutionarily non-conserved subunits, generally thought to facilitate the complex’s binding to a specific chromatin context. In yeasts, Nse5 and Nse6 t interact with BRCT domain-containing factors Rtt107 or Brc1 [26,27,28]. In humans, there are SMC5-SMC6 complex localization factors 1 and 2 (SLF1 and SLF2) [29]. In plants, the functional homologs of NSE5 and NSE6 are ARABIDOPSIS SNI1-ASSOCIATED PROTEIN 1 (ASAP1) and SUPPRESSOR OF NPR1; INDUCIBLE (SNI1), respectively [30,31]. 2. Essential Functions in Meiosis Meiosis is a specialized division that occurs in sexually reproducing eukaryotes and fulfills two important tasks [32]. First, it facilitates a controlled exchange of segments of homologous chromosomes, leading to new combinations of genetic information. Second, with the two subsequent rounds of cell division, it produces four haploid gametes from one meiocyte. The most complex part of meiosis is prophase I, which starts with the leptotene stage, when numerous DNA double-strand breaks (DSBs) are introduced along the chromosomes by SPORULATION 11 (SPO11). Single-stranded DNA overhangs produced by MRN (MRE11-RAD50-NBS1) complex [33] are bound by two DNA recombinases, RAD51 and DMC1, invade appropriate regions on the homologous chromosomes, and form D-loop intermediates. Several repair pathways processing D-loop intermediates have been described in plants (Figure 1). The intermediates forming double Holliday junctions (dHJs) can either be removed via RTR (RECQ4A-TOP3A-RMI1) pathway, forming non-crossovers (NCOs) by dissolution [32,34,35], or processed into the Class I crossovers (COs) via ZMM (ZYP-MER3-MSH) pathway by dHJ resolution [32,36]. In contrast, the intermediates forming single Holliday junctions (sHJ) are processed either as the Class II crossovers by the MMS AND UV SENSITIVE 81 (MUS81) pathway or as NCOs by synthesis-dependent strand annealing (SDSA) HR pathway [32,34]. Subsequently, the physical connection formed by COs (chiasmata) keeps bivalents together to ensure proper orientation and segregation of chromosomes during the first meiotic division. During meiosis II, sister chromatids segregate, and four haploid spores are formed. All four male products survive, whereas three of the female products are eliminated. Figure 1 Simplified model of the functions of SMC5/6 complex during male meiosis in Arabidopsis. The meiotic double-strand breaks (DSBs) are initiated by SPO11. Recombinases RAD51 and DMC1, are required to repair the breaks by homology search and strand invasion, respectively. RAD51 supports the action of DMC1 by attenuating the SMC5/6 complex during this step [37]. The invasion of the homologous duplex DNA gives rise to a D-loop intermediate, which can be repaired by (i) non-crossovers (NCOs) via double Holliday junction (dHJ) dissolution by the RTR complex; (ii) by the ZMM pathway, forming Class I crossovers (COs) via dHJ resolution; (iii) by the MUS81-dependent pathway, forming Class II Cos; or (iv) by synthesis-dependent strand annealing (SDSA), generating NCOs. SMC5/6 is required to prevent the accumulation of aberrant and unresolved intermediates that arise outside the ZMM pathway [38]. The absence of SMC5/6 complex functions leads to the accumulation of abnormal joint molecules (aJMs), which are either repaired by MUS81, promoting Class II COs [39], or result in different abnormal phenotypes: either chromosome fragmentation and microspore abortion or lack of chromosome segregation, which results in the formation of diploid gametes and, finally, triploid offspring [40]. The involvement of the SMC5/6 complex in meiosis has been reported across kingdoms. Studies based on yeast and animal models suggested its role in the removal of unregulated (abnormal) joint molecules (aJMs) that may appear among sHJs [38,41,42,43]. This is also supported by observations in plants. Analysis of Arabidopsis natural variation in CO frequencies revealed a higher degree of recombination in Ler compared to Col-0 accession [39]. Subsequent quantitative trait locus (QTL) mapping led to the identification of the natural allele of SNI1 as the causal gene. Natural variation in SNI1 might fit well with its putative function as a loader to chromatin [31], and such a natural allele could modulate binding to slightly different substrates and/or under different conditions. The database of >1000 Arabidopsis genomes displays considerable variation in SNI1, with more than 30 alleles and 59 amino acid substitutions throughout the entire protein. The most likely causal mutation in SNI1Ler is I235V. Currently, it is unknown how this substitution changes SNI1 function, but valine represents only a minor change in chemical properties compared to isoleucine. Phenotypes similar to SNI1Ler (although stronger) were observed in loss-of-function SMC5/6 complex mutants sni1-2, nse4a-2, and asap1 (Table 1). When looking at the COs, it became obvious that Arabidopsis SMC5/6 complex mutants show less CO interference, and the relative amount of Class I COs decreased compared to Class II COs. Collectively, this suggests that the SMC5/6 complex is involved in aJM resolution during meiotic prophase I in Arabidopsis. An absence of this activity leads to the formation of anaphase bridges, chromosome fragmentation, unequal segregation, and chromatin loss. The SMC5/6 complex could eliminate aJMs by least two (mutually non-exclusive) mean. First, it might stabilize the HR structure and provide operational space for the other repair factors, including RMR complex, MUS81, and/or cohesin. This has been experimentally proven in yeast and mammals [38,41,44]. In Arabidopsis, there are, so far, only data from somatic nuclei, where the homologous chromosome regions are significantly less associated upon DNA damage in SMC5/6 complex mutants [45]. Secondly, the dynamics of aJM repair might be affected by the SUMOylation activity of the SMC5/6 complex. However, this has not been explored in plants. Although the activity of the SMC5/6 complex is important for aJM resolution, it needs to be correctly timed during meiosis. A recent study in Arabidopsis revealed that the SMC5/6 complex has to be suppressed during the early stages of prophase I to allow for the efficient formation of dHJs [37]. This was found by a forward-directed screen for suppressors of sni1-induced sterility. The screen yielded sni1 rad51 double mutant, suggesting that SMC5/6 complex and RAD51 might have antagonistic roles during meiosis. RAD51 is a homolog of bacterial RecA, which is protein known to bind single-stranded DNA (ssDNA) and is essential for sequence homology search. In meiosis, RAD51 cooperates with another recA homolog, DISRUPTION OF MEIOTIC CONTROL 1 (DMC1). Although RAD51 performs homology search, the DMC1 is specialized in strand invasion. Loss of function from each of these factors causes full sterility, but they differ in chromosomal phenotypes. The meiotic chromosomes of rad51 plants are highly fragmented, and those of dmc1 plants appear intact but do not form bivalents due to a lack of COs. A recent study in Arabidopsis found physical interaction between RAD51, DMC1, SNI1, and ASAP1 [37]. However, in vitro competition experiments revealed that RAD51 attenuates the interaction of DMC1 with the two SMC5/6 complex subunits. Based on this and other experiments, the authors proposed that RAD51 inhibits SMC5/6 during the early meiotic prophase and thus allows for DMC1-mediated strand invasion. Such interaction could occur at ssDNA around the DSBs because all three factors, RAD51, DMC1, and SMC5/6 complex, have ssDNA binding affinity [46,47,48]. So far, the most attention has been paid to SMC5/6 complex activity in processing meiotic DSBs and aJMs. However, it seems important for successful chromosome segregation during meiosis. We found that Arabidopsis nse2 plants produce approximately one-third of unreduced (diploid) microspores [40]. In some nse2 meiocytes, all chromosomes remain in one pole. This phenotype is independent of SPO11-induced DSBs, as suggested by the analysis of nse2 spo11 plants. Furthermore, the analysis of nse2 osd1 meiotic products revealed 80% dyads and 20% monads. Because mutants in OMISSION OF SECOND DIVISION 1 (OSD1) skip the second meiotic division and produce dyads instead of tetrads [49], this nse2 osd1 phenotype demonstrates that the non-reduction occurs mostly in meiosis I. However, meiosis II or both meiotic segregations can be omitted in a single nse2 meiocyte, as suggested by the analysis of meiotic products from nse2 qrt plants (qrt mutation prevents separation of meiotic products), which included all classes, from tetrads to monads. The non-reduction in SMC5/6 complex mutants could be caused by several different defects. There could be an unnoticed population of SPO11-independent DSBs causing this problem. However, this option is less likely, as nse2 and sni1-1 plants do not show more RAD51 foci during the zygotene stage, and the phenotype is not linked with chromosome fragmentation [39,40]. Alternatively, we cannot exclude other DSB-independent types of DNA damage arising from, e.g., premeiotic replication or other chromatin-associated processes. In addition, some nse2 meiocytes showed a disorganized and/or multipolar microtubule network. This might be caused by irregular chromosome positioning and/or structure, which was also observed in nse2 meiocytes. Any of the above-described possibilities likely slow down cell division, which might not reach the meiotic checkpoint [50] on time, in which case, the cell with non-separated chromosomes moves to the next stage. ijms-23-04503-t001_Table 1 Table 1 The phenotypes of Arabidopsis SMC5/6 complex mutants. At—Arabidopsis thaliana, Zm—Zea mays, Os—Oryza sativa, *—under standard growth conditions. n.a.—not available, ins.—sequence insertion, del.—sequence deletion, ex—exon. Gene Name Gene ID Mutant Allele Stock ID/Mutation Somatic Phenotype * Meiotic Phenotype Seed Phenotype Reference AtSMC5 At5g15920 Atsmc5-1 SALK_107583 Not viable n.a. Early embryo lethal (Type 1) [31,45] Atsmc5-2 SALK_092081 Not viable n.a. AtSMC6A At5g07660 Atsmc6a-2 SALK_091553 WT-like n.a. WT-like [51] AtSMC6B At5g61460 Atsmc6b-4 SALK_124719 WT-like n.a. WT-like smc6b-2 SALK_135638 n.a. Increased COs n.a. [39] smc6a-2 smc6b-4 SALK_091553 SALK_124719 Not viable n.a. Early embryo lethal (Type 1) [51] smc6a-1 smc6b-2 SALK_009818 SALK_135638 n.a. Increased COs n.a. [39] AtNSE1 At5g21140 Atnse1-1 CS16151 Not viable n.a. Early embryo lethal (Type 1) [52,53] Atnse1-2 SALK_136483 Not viable n.a. Early embryo lethal (Type 1) AtNSE2/AtHPY2/AtMMS21 At3g15150 Atnse2-1/Athpy2-1/Atmms21-1 Q115STOP Short roots and stems, deformed leaves, stem fasciations, irregular branching, triploid individuals Increased COs, fragmented and lagging chromosomes, anaphase bridges, monads to tetrads Large seeds, cellularization defects, increased seed abortion (Type 2) [21,22,40,54,55] Atnse2-2/Athpy2-2/Atmms21-2 SAIL_77_G06 AtNSE3 At1g34770 Atnse3-1 GK-459F08 Not viable n.a. Early embryo lethal (Type 1) [52,53] Atnse3-2 GK-534A03 Not viable n.a. Early embryo lethal (Type 1) AtNSE4A At1g51130 Atnse4a-1 SALK_057130 Not viable n.a. Early embryo lethal (Type 1) [56] Atnse4a-2 GK-768H08 Weakly delayed, triploid individuals Increased COs, fragmented and lagging chromosomes, anaphase bridges and micronuclei Large seeds, cellularization defects, increased seed abortion (Type 2) AtNSE4B At3g20760 Atnse4b-1 SAIL_296_F02 WT-like n.a. WT-like Atnse4b-2 GK-175D10 WT-like n.a. WT-like AtASAP1 At2g28130 Atasap1 GK-218F01 Strongly reduced growth, short roots Fragmentated chromosomes Almost sterile [31,37] AtSNI1 At4g18470 Atsni1-1 11 bp del., premature stop Reduced growth, short roots Fragmented chromosomes, increased Class II COs, dyads Reduced fertility [30,31,37,39] Atsni1-2 SAIL_298_H07 n.a. Fragmented chromosomes Almost sterile [37] Atsni1-3 SAIL_34_D11 Short roots and stems, deformed leaves and triploid individuals n.a. Large seeds, cellularization defects, increased seed abortion (Type 2) [40] AtSNI1Ler I235V WT-like Recombination QTL, increased COs n.a. [39] Atsni1-4 (as Atsni1-2) 14 bp del., premature stop n.a. n.a. n.a. ZmMMS21 Zm00001d039007 Zmmms21-1 Mu ins., ex4 Slow growth, severely stunted plants, short roots, fewer leaves at maturity n.a. Small kernels, pitted surface, reduced embryo size and an underfilled endosperm, poor germination [57] Zmmms21-2 Mu ins., ex6 n.a. Zmmms21-CR7 33 bp del., 11 aa del. ex1 n.a. Zmmms21-CR1 1 bp del., ex2, premature stop Not viable to early somatic lethal n.a. Zmmms21-CR3 1 bp ins. ex2, new TSS producing a truncated protein Not viable to early somatic lethal n.a. Zmmms21-CR4 1bp ins., ex1; 2 bp del., ex2, premature stop Not viable to early somatic lethal n.a. Zmmms21-CR6 3 bp del., 1 aa del. ex1 Not viable to early somatic lethal n.a. Zmmms21-CR2 14 bp del., ex2, premature stop Not viable n.a. Early embryo lethal Zmmms21-CR5 6 bp del., 2 aa del. ex1; 8 bp del. ex2, premature stop Not viable n.a. Early embryo lethal OsMMS21 LOC_ Os05g48880 Osmms21 05Z11BH79 Short roots, dwarf plants n.a. n.a. [58] Little is known about the role of the SMC5/6 complex in female meiosis. Arabidopsis NSE4A was found to be strongly expressed in the megaspore mother cell [56]. Furthermore, the presence of ovules without embryo sacs in nse2 plants suggests occasional failure of female meiosis [40]. Another emerging role of the SMC5/6 complex might lie in securing chromosome stability in the meiosis of polyploid plants. This could be of high importance for plant breeding because many crops are extant polyploids. Polyploid meiosis differs in some respects from that of diploid meiosis [59,60]. A recent pioneer study on the reproductive development of autotetraploid (4×) Arabidopsis nse2 plants revealed combined effects of polyploidy and SMC5/6 complex loss of function on meiotic phenotypes [54]. The 4× nse2 plants showed greater tolerance to aneuploidy and its transmission through the male and (surprisingly) female meiosis. This is probably allowed by the presence of at least one full chromosome complement and a second chromosome complement with few either missing or excessive chromosomes. How the combination of tetraploidy and SMC5/6 complex loss of function affect the ratio of Class I and II COs or processing of aJMs is yet to be addressed. 3. Emerging Roles in Plant Gametophytic Development The female and male meiosis produce mega- and microspores that undergo a series of cell divisions and differentiation in plants to form megagametophyte (embryo sac) and microgametophyte (pollen), respectively. These stages have not been extensively investigated concerning SMC5/6 complex functions (Table 1). Several studies revealed shrunken pollen and reduced pollen viability in nse2, nse4a-2, asap1, and sni1 [37,39,40,55,61]. In addition, there is less pollen germination and reduced pollen tube growth for nse2 [55]. However, these defects seem to be relics of problems arising during meiosis [40]. At the bicellular and tricellular stages of Arabidopsis pollen development, an abnormal number of nuclei and chromatin loss were occasionally observed. Whether these are also meiosis-derived defects and/or are caused by problems in the pollen mitotic divisions is unknown. To the best of our knowledge, the morphology of the embryo sac has been analyzed only in nse2 mutants of Arabidopsis and revealed a wide range of defects [40,55]. In the most extreme cases, the embryo sac was absent, which could result from an aborted female meiocyte. In addition, there were embryo sacs with variable numbers of nuclei, equally sized egg and central cell nuclei, or incorrect positions of the cells within the embryo sac. The latter problems could result from megagametophyte mitotic divisions by unequal segregation and possibly incorrect orientation of the mitotic spindles. The last problem might again (compared to lack of chromosome reduction in meiosis) suggest an effect of the SMC5/6 complex on microtubule network organization. 4. Direct and Indirect Effects on Seed Development Seed formation starts with double fertilization, where one sperm nucleus fuses with the egg cell nucleus and the second sperm nucleus fuses with the central cell nucleus, giving rise to a diploid embryo and triploid endosperm, respectively [62]. Whereas the embryo represents a new plant generation, the functions of endosperm are manifold and include nourishing the embryo, sensing compatibility of the parental genomes, and, in some species, providing energy during germination. Endosperm development starts with several rounds of cell division without cell wall formation (syncytium). Several days after fertilization, endosperm cellularizes; this step is critical for successful seed development. Normal endosperm development and cellularization require a balanced dosage of maternal (m) and paternal (p) genomes, which is, by default, defined as a 2m:1p ratio [63]. Early studies in Arabidopsis revealed a class of mutants with unusually large seeds, disrupted endosperm cellularization, and arrested embryo development [64]. Genes underlying this phenotype were called TITAN, and some were mapped to subunits of cohesin and condensin complexes [9,65]. The presence of giant nuclei in their endosperm indicated problems in cell division. Recently, defects in seed development were described for the mutants in the SMC5/6 complex. Although there is a resemblance with the titan seeds, we propose that the SMC5/6 complex mutants display not one but at least two principal seed phenotypes (Type 1 and 2), differing as to their origin (Figure 2; Table 1). Type 1 defective seeds correspond to the originally described EMBRYO DEFECTIVE (EMB) phenotype for SMC5 (EMB2782) and NSE1 (EMB1379). These abnormal seeds are initially of normal size, contain early-aborting embryos, and shrink during desiccation (Figure 2). This phenotype is inherited as a Mendelian recessive trait and was found in nse4a-1, all smc5, nse1, and nse3 alleles, as well as in smc6a-2 smc6b-4 double mutant (Table 1). For Arabidopsis SMC6 paralogs, the Type 1 seed phenotype is observable only in the double-mutant background because of the partial functional redundancy between SMC6A and SMC6B. Although the cause of the Type 1 seed phenotype is unclear, it strongly correlates with the signatures of genome instability, and we propose that these defects are directly caused by the deficient SMC5/6 complex function in seeds. Several DNA damage repair and cell cycle genes were upregulated in nse1, nse3, and smc6a smc6b seeds [51,52,53]. Cells activate checkpoints to arrest cell cycle progression, allowing sufficient time for DNA damage repair. The deficient DNA damage repair in these mutants may delay the cell cycle progression, cause growth inhibition, and finally lethality. The appearance of giant and heteromorphic endosperm nuclei in nse1, nse3, and smc6a smc6b mutant seeds indicates elevated endoreduplication instead of normal nuclear division [51,52,53]. The additional rounds of endoreduplication may delay the transition from proliferation to cellularization in the endosperm, thus arresting embryo development. NSE2 and SNI1 have been reported to inhibit E2F transcription factors in somatic tissues [66], suggesting that the SMC5/6 complex may contribute to cell cycle control. This also seems to be connected with auxin hormonal disbalance during embryo development as found in nse1 and nse3 seeds. Furthermore, many genes related to auxin signaling were downregulated in nse1 and nse3, including members of INDOLEACETIC ACID-INDUCED PROTEIN (IAA), AUXIN RESPONSE FACTOR (ARF), and YUCCA (YUC) families [52]. This supports the role of the SMC5/6 complex in the regulation of normal auxin biogenesis, translocation, and transduction. However, the connection between the SMC5/6 complex and the auxin pathway might be rather indirect. Serious defects in DNA damage repair may lead to cell death. Both vacuolar programmed cell death (PCD) and necrotic PCD were observed in embryos of nse1, nse3, and smc6a smc6b seeds [51,53]. However, it is still not clear whether PCD occurs and is possibly initiated in the mutant endosperm. The second aberrant seed phenotype (Type 2) of SMC5/6 complex mutants is hallmarked by large seed size, glossy surface, liquid endosperm, and an embryo reaching the heart or even later stages (Figure 2; Table 1). Such seeds are found in homozygous nse2-1, nse2-2, nse4a-2, and sni1-3 plants [40,51,52,56]. Interestingly, Type 2 abnormal seeds are induced paternally [40], suggesting problems in the parental genome dosage. Whereas the double fertilization with reduced gametes produces a diploid embryo (1m:1p) and triploid endosperm (2m:1p), fertilization with unreduced sperm nuclei (as observed in nse2 plants) gives rise to a triploid embryo (1m:2p) and a tetraploid endosperm (2m:2p). Although direct evidence that the Type 2 seeds are the product of fertilization by unreduced sperm nuclei is missing, this hypothesis is indirectly supported by the improved seed viability in crosses of diploid nse2 maternal plants with tetraploid wild-type paternal plants [40]. Hence, the Type 2 abnormal seed phenotype is most likely a consequence of aberrant meiosis when chromosomes fail to divide, and a diploid male gamete is produced, which leads to an incorrect parental dosage in the endosperm. Finally, the majority of such seeds die, but the minority can germinate and give rise to triploid offspring, as found for nse2, nse4a-2, and sni1-3 plants [40]. This is the first observation of triploids among smc5/6 complex mutants, possibly because plants tolerate triploidy and aneuploidies better than many other eukaryotic groups. Arabidopsis triploid plants exhibit various degrees of sterility but can function as a bridge towards karyotypically more stable tetraploids [59]. However, newly formed autotetraploid nse2 and nse4a-2 plants were almost sterile and produced hexaploid and aneuploid progeny with the extra genome copies or chromosomes from both parents [54], indicating that the SMC5/6 complex is also essential for stable tetraploid plant development. 5. Importance of Crop Fertility Current knowledge on the role of the SMC5/6 complex in plants is based on research on Arabidopsis thaliana, which is an excellent genetic model species representing plants with a small genome and low abundance of repetitive sequences [67]. However, most plants have larger genomes, which may be connected with a more complex genome organization and even greater necessity of activities performed by SMC complexes [68]. Therefore, it is exciting that the first studies on SMC5/6 complex functions in other plant species are emerging. Maize (Zea mays) represents a moderately sized grass genome (2.4 Gbp/1C) and a very important crop [69]. Knocking out maize MMS21/NSE2 revealed two principal phenotypes [57]. First, the more severe mutations caused lethality in the seed stage or soon after germination. Second, the less severe mutants had slightly smaller seeds with a pitted surface, reduced embryo size, and often underfilled endosperm. This indicates that the function of the SMC5/6 complex to control seed development is conserved in plants. Such seeds had lower germination, and the seedlings grew more slowly, ultimately developing into severely stunted plants with shorter roots and fewer, shorter, and narrower leaves at maturity [57]. Another study focused on the rice somatic phenotypes of OsMMS21, the ortholog of AtMMS21 [58]. The T-DNA insertion mutant had short roots and was dwarfish from the early tiller to the adult stages. These pioneer studies suggest that the functions of the SMC5/6 complex is also relevant for agriculturally important traits in cereal and possibly other crops. Acknowledgments We would like to thank Mónica Pradillo for her careful reading of the manuscript. Author Contributions F.Y. and A.P. participated in writing the manuscript. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by a Purkyně Fellowship from the Czech Academy of Sciences and GAČR grant 22-00871S (both to A.P.). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 2 Two types of abnormal seed phenotypes were found in the SMC5/6 complex mutants. The ovals represent schematically drawn seeds with embryos in green and endosperm in gray. Mutant seed Type 1 has normal ploidy with diploid (2×, 1m:1p) embryo and triploid (3×, 2m:1p) endosperm, embryo aborts in early stages due to cell cycle arrest, abnormal auxin signal, and programmed cell death (PCD). The image below shows Arabidopsis seeds 13 days after pollination (DAP), with Type 1 seed indicated by the arrow. The mutant seed Type 2 has abnormal ploidy with triploid embryo (1m:2p) and tetraploid (4×) endosperm containing two maternal and two paternal genomes (2m:2p). An excess of paternal genome delays endosperm cellularization, inhibits embryo development, and frequently leads to seed abortion. Examples of Type 2 seeds are shown below and indicated by arrows. Type 2 seeds usually appear larger than average seeds, with a smooth surface. Bars = 500 μm. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Rosa S. Shaw P. Insights into chromatin structure and dynamics in plants Biology 2013 2 1378 1410 10.3390/biology2041378 24833230 2. Doğan E.S. Liu C. Three-dimensional chromatin packing and positioning of plant genomes Nat. Plants 2018 4 521 529 10.1038/s41477-018-0199-5 30061747 3. Pecinka A. Chevalier C. Colas I. Kalantidis K. Varotto S. Krugman T. Michailidis C. Vallés M.-P. Muñoz A. Pradillo M. Chromatin dynamics during interphase and cell division: Similarities and differences between model and crop plants J. Exp. Bot. 2020 71 5205 5222 10.1093/jxb/erz457 31626285 4. Kawashima T. Berger F. Epigenetic reprogramming in plant sexual reproduction Nat. Rev. Genet. 2014 15 613 624 10.1038/nrg3685 25048170 5. She W. Baroux C. Chromatin dynamics during plant sexual reproduction Front. Plant Sci. 2014 5 354 10.3389/fpls.2014.00354 25104954 6. Baroux C. Autran D. Chromatin dynamics during cellular differentiation in the female reproductive lineage of flowering plants Plant J. 2015 83 160 176 10.1111/tpj.12890 26031902 7. Jeppsson K. Kanno T. Shirahige K. Sjögren C. The maintenance of chromosome structure: Positioning and functioning of SMC complexes Nat. Rev. Mol. Cell Biol. 2014 15 601 614 10.1038/nrm3857 25145851 8. Uhlmann F. SMC complexes: From DNA to chromosomes Nat. Rev. Mol. Cell Biol. 2016 17 399 412 10.1038/nrm.2016.30 27075410 9. Liu C.M. McElver J. Tzafrir I. Joosen R. Wittich P. Patton D. Van Lammeren A.A.M. Meinke D. Condensin and cohesin knockouts in Arabidopsis exhibit a titan seed phenotype Plant J. 2002 29 405 415 10.1046/j.1365-313x.2002.01224.x 11846874 10. Díaz M. Pecinka A. Scaffolding for repair: Understanding molecular functions of the SMC5/6 complex Genes 2018 9 36 10.3390/genes9010036 11. Kegel A. Sjögren C. The Smc5/6 complex: More than repair? Cold Spring Harb. Symp. Quant. Biol. 2010 75 179 187 10.1101/sqb.2010.75.047 21467147 12. Wu N. Yu H. The Smc complexes in DNA damage response Cell Biosci. 2012 2 5 10.1186/2045-3701-2-5 22369641 13. Aragón L. The Smc5/6 complex: New and old functions of the enigmatic long-distance relative Annu. Rev. Genet. 2018 52 89 107 10.1146/annurev-genet-120417-031353 30476445 14. Schubert V. SMC proteins and their multiple functions in higher plants Cytogenet. Genome Res. 2009 124 202 214 10.1159/000218126 19556774 15. Palecek J.J. Gruber S. Kite proteins: A superfamily of SMC/kleisin partners conserved across bacteria, archaea, and eukaryotes Structure 2015 23 2183 2190 10.1016/j.str.2015.10.004 26585514 16. Haering C.H. Gruber S. SnapShot: SMC protein complexes part i Cell 2016 164 326 326.e1 10.1016/j.cell.2015.12.026 26771499 17. Doyle J.M. Gao J. Wang J. Yang M. Potts P.R. MAGE-RING protein complexes comprise a family of E3 ubiquitin ligases Mol. Cell 2010 39 963 974 10.1016/j.molcel.2010.08.029 20864041 18. Kolesar P. Stejskal K. Potesil D. Murray J.M. Palecek J.J. Role of Nse1 subunit of SMC5/6 complex as a ubiquitin ligase Cells 2022 11 165 10.3390/cells11010165 35011726 19. Andrews E.A. Palecek J. Sergeant J. Taylor E. Lehmann A.R. Watts F.Z. Nse2, a component of the Smc5-6 complex, is a SUMO ligase required for the response to DNA damage Mol. Cell. Biol. 2005 25 185 196 10.1128/MCB.25.1.185-196.2005 15601841 20. Potts P.R. Yu H. Human MMS21/NSE2 is a SUMO ligase required for DNA repair Mol. Cell. Biol. 2005 25 7021 7032 10.1128/MCB.25.16.7021-7032.2005 16055714 21. Ishida T. Fujiwara S. Miura K. Stacey N. Yoshimura M. Schneider K. Adachi S. Minamisawa K. Umeda M. Sugimoto K. SUMO E3 ligase HIGH PLOIDY2 regulates endocycle onset and meristem maintenance in Arabidopsis Plant Cell 2009 21 2284 2297 10.1105/tpc.109.068072 19666737 22. Huang L. Yang S. Zhang S. Liu M. Lai J. Qi Y. Shi S. Wang J. Wang Y. Xie Q. The Arabidopsis SUMO E3 ligase AtMMS21, a homologue of NSE2/MMS21, regulates cell proliferation in the root Plant J. 2009 60 666 678 10.1111/j.1365-313X.2009.03992.x 19682286 23. García-Rodríguez N. Wong R.P. Ulrich H.D. Functions of Ubiquitin and SUMO in DNA replication and replication stress Front. Genet. 2016 7 87 10.3389/fgene.2016.00087 27242895 24. Meng X. Wei L. Peng X.P. Zhao X. Sumoylation of the DNA polymerase ε by the Smc5/6 complex contributes to DNA replication PLoS Genet. 2019 15 e1008426 10.1371/journal.pgen.1008426 31765372 25. Rytz T.C. Miller M.J. McLoughlin F. Augustine R.C. Marshall R.S. Juan Y. Charng Y. Scalf M. Smith L.M. Vierstra R.D. SUMOylome profiling reveals a diverse array of nuclear targets modified by the SUMO ligase SIZ1 during heat stress Plant Cell 2018 30 1077 1099 10.1105/tpc.17.00993 29588388 26. Pebernard S. Wohlschlegel J. McDonald W.H. Yates J.R. Boddy M.N. The Nse5-Nse6 dimer mediates DNA repair roles of the Smc5-Smc6 complex Mol. Cell. Biol. 2006 26 1617 1630 10.1128/MCB.26.8.3336.2006 16478984 27. Leung G.P. Lee L. Schmidt T.I. Shirahige K. Kobor M.S. Rtt107 is required for recruitment of the SMC5/6 complex to DNA double strand breaks J. Biol. Chem. 2011 286 26250 26257 10.1074/jbc.M111.235200 21642432 28. Oravcová M. Gadaleta M.C. Nie M. Reubens M.C. Limbo O. Russell P. Boddy M.N. Brc1 promotes the focal accumulation and SUMO ligase activity of Smc5-Smc6 during replication stress Mol. Cell. Biol. 2019 39 e00271-18 10.1128/MCB.00271-18 29. Räschle M. Smeenk G. Hansen R.K. Temu T. Oka Y. Hein M.Y. Nagaraj N. Long D.T. Walter J.C. Hofmann K. Proteomics reveals dynamic assembly of repair complexes during bypass of DNA cross-links Science 2015 348 1253671 10.1126/science.1253671 25931565 30. Li X. Zhang Y. Clarke J.D. Li Y. Dong X. Identification and cloning of a negative regulator of systemic acquired resistance, SNI1, through a screen for suppressors of npr1-1 Cell 1999 98 329 339 10.1016/S0092-8674(00)81962-5 10458608 31. Yan S. Wang W. Marqués J. Mohan R. Saleh A. Durrant W.E. Song J. Dong X. Salicylic acid activates DNA damage responses to potentiate plant immunity Mol. Cell 2013 52 602 610 10.1016/j.molcel.2013.09.019 24207055 32. Mercier R. Mézard C. Jenczewski E. Macaisne N. Grelon M. The molecular biology of meiosis in plants Annu. Rev. Plant Biol. 2015 66 297 327 10.1146/annurev-arplant-050213-035923 25494464 33. Borde V. The multiple roles of the Mre11 complex for meiotic recombination Chromosom. Res. 2007 15 551 563 10.1007/s10577-007-1147-9 17674145 34. Mercier R. Jolivet S. Vezon D. Huppe E. Chelysheva L. Giovanni M. Nogué F. Doutriaux M.-P. Horlow C. Grelon M. Two Meiotic Crossover Classes Cohabit in Arabidopsis: One Is Dependent on MER3, whereas the Other One Is Not Curr. Biol. 2005 15 692 701 10.1016/j.cub.2005.02.056 15854901 35. Knoll A. Schröpfer S. Puchta H. The RTR complex as caretaker of genome stability and its unique meiotic function in plants Front. Plant Sci. 2014 5 33 10.3389/fpls.2014.00033 24575106 36. Lynn A. Soucek R. Börner G.V. ZMM proteins during meiosis: Crossover artists at work Chromosom. Res. 2007 15 591 605 10.1007/s10577-007-1150-1 37. Chen H. He C. Wang C. Wang X. Ruan F. Yan J. Yin P. Wang Y. Yan S. RAD51 supports DMC1 by inhibiting the SMC5/6 complex during meiosis Plant Cell 2021 33 2869 2882 10.1093/plcell/koab136 34009315 38. Xaver M. Huang L. Chen D. Klein F. Smc5/6-Mms21 prevents and eliminates inappropriate recombination intermediates in meiosis PLoS Genet. 2013 9 e1004067 10.1371/journal.pgen.1004067 24385936 39. Zhu L. Fernández-Jiménez N. Szymanska-Lejman M. Pelé A. Underwood C.J. Serra H. Lambing C. Dluzewska J. Bieluszewski T. Pradillo M. Natural variation identifies SNI1, the SMC5/6 component, as a modifier of meiotic crossover in Arabidopsis Proc. Natl. Acad. Sci. USA 2021 118 e2021970118 10.1073/pnas.2021970118 34385313 40. Yang F. Fernández-Jiménez N. Tučková M. Vrána J. Cápal P. Díaz M. Pradillo M. Pecinka A. Defects in meiotic chromosome segregation lead to unreduced male gametes in Arabidopsis SMC5/6 complex mutants Plant Cell 2021 33 3104 3119 10.1093/plcell/koab178 34240187 41. Copsey A. Tang S. Jordan P.W. Blitzblau H.G. Newcombe S. Chan A.C. Newnham L. Li Z. Gray S. Herbert A.D. Smc5/6 coordinates formation and resolution of joint molecules with chromosome morphology to ensure meiotic divisions PLoS Genet. 2013 9 e1004071 10.1371/journal.pgen.1004071 24385939 42. Lilienthal I. Kanno T. Sjögren C. Inhibition of the Smc5/6 complex during meiosis perturbs joint molecule formation and resolution without significantly changing crossover or non-crossover levels PLoS Genet. 2013 9 e1003898 10.1371/journal.pgen.1003898 24244180 43. Verver D.E. Langedijk N.S.M. Jordan P.W. Repping S. Hamer G. The SMC5/6 complex is involved in crucial processes during human spermatogenesis Biol. Reprod. 2014 91 22 10.1095/biolreprod.114.118596 24855106 44. Potts P.R. Porteus M.H. Yu H. Human SMC5/6 complex promotes sister chromatid homologous recombination by recruiting the SMC1/3 cohesin complex to double-strand breaks EMBO J. 2006 25 3377 3388 10.1038/sj.emboj.7601218 16810316 45. Watanabe K. Pacher M. Dukowic S. Schubert V. Puchta H. Schubert I. The STRUCTURAL MAINTENANCE of CHROMOSOMES 5/6 complex promotes sister chromatid alignment and homologous recombination after DNA damage in Arabidopsis thaliana Plant Cell 2009 21 2688 2699 10.1105/tpc.108.060525 19737979 46. Masson J.-Y. West S.C. The Rad51 and Dmc1 recombinases: A non-identical twin relationship Trends Biochem. Sci. 2001 26 131 136 10.1016/S0968-0004(00)01742-4 11166572 47. Roy M.-A. D’Amours D. DNA-binding properties of Smc6, a core component of the Smc5–6 DNA repair complex Biochem. Biophys. Res. Commun. 2011 416 80 85 10.1016/j.bbrc.2011.10.149 22086171 48. Roy M.-A. Siddiqui N. D’Amours D. Dynamic and selective DNA-binding activity of Smc5, a core component of the Smc5-Smc6 complex Cell Cycle 2011 10 690 700 10.4161/cc.10.4.14860 21293191 49. Cromer L. Heyman J. Touati S. Harashima H. Araou E. Girard C. Horlow C. Wassmann K. Schnittger A. De Veylder L. OSD1 promotes meiotic progression via APC/C inhibition and forms a regulatory network with TDM and CYCA1;2/TAM PLoS Genet. 2012 8 e1002865 10.1371/journal.pgen.1002865 22844260 50. De Jaeger-Braet J. Krause L. Buchholz A. Schnittger A. Heat stress reveals a specialized variant of the pachytene checkpoint in meiosis of Arabidopsis thaliana Plant Cell 2022 34 433 454 10.1093/plcell/koab257 34718750 51. Zou W. Li G. Jian L. Qian J. Liu Y. Zhao J. Arabidopsis SMC6A and SMC6B have redundant function in seed and gametophyte development J. Exp. Bot. 2021 72 4871 4887 10.1093/jxb/erab181 33909904 52. Li G. Zou W. Jian L. Qian J. Deng Y. Zhao J. Non-SMC elements 1 and 3 are required for early embryo and seedling development in Arabidopsis J. Exp. Bot. 2017 68 1039 1054 10.1093/jxb/erx016 28207059 53. Li G. Zou W. Jian L. Qian J. Zhao J. AtNSE1 and AtNSE3 are required for embryo pattern formation and maintenance of cell viability during Arabidopsis embryogenesis J. Exp. Bot. 2019 70 6229 6244 10.1093/jxb/erz373 31408172 54. Yang F. Fernández Jiménez N. Majka J. Pradillo M. Pecinka A. Structural maintenance of chromosomes 5/6 complex is necessary for tetraploid genome stability in Arabidopsis thaliana Front. Plant Sci. 2021 12 2139 10.3389/fpls.2021.748252 34675953 55. Liu M. Shi S. Zhang S. Xu P. Lai J. Liu Y. Yuan D. Wang Y. Du J. Yang C. SUMO E3 ligase AtMMS21 is required for normal meiosis and gametophyte development in Arabidopsis BMC Plant Biol. 2014 14 153 10.1186/1471-2229-14-153 24893774 56. Díaz M. Pečinková P. Nowicka A. Baroux C. Sakamoto T. Yuliani Gandha P. Jeřábková H. Matsunaga S. Grossniklaus U. Pecinka A. The SMC5/6 complex subunit NSE4A is involved in DNA damage repair and seed development in Arabidopsis Plant Cell 2019 31 1579 1597 10.1105/tpc.18.00043 31036599 57. Zhang J. Augustine R.C. Suzuki M. Feng J. Char S.N. Yang B. McCarty D.R. Vierstra R.D. The SUMO ligase MMS21 profoundly influences maize development through its impact on genome activity and stability PLoS Genet. 2021 17 e1009830 10.1371/journal.pgen.1009830 34695110 58. Jiang J. Xie Y. Du J. Yang C. Lai J. A SUMO ligase OsMMS21 regulates rice development and auxin response J. Plant Physiol. 2021 263 153447 10.1016/j.jplph.2021.153447 34098413 59. Comai L. The advantages and disadvantages of being polyploid Nat. Rev. Genet. 2005 6 836 846 10.1038/nrg1711 16304599 60. Grandont L. Jenczewski E. Lloyd A. Meiosis and Its Deviations in Polyploid Plants Cytogenet. Genome Res. 2013 140 171 184 10.1159/000351730 23817089 61. Zelkowski M. Zelkowska K. Conrad U. Hesse S. Lermontova I. Marzec M. Meister A. Houben A. Schubert V. Arabidopsis NSE4 proteins act in somatic nuclei and meiosis to ensure plant viability and fertility Front. Plant Sci. 2019 10 774 10.3389/fpls.2019.00774 31281325 62. Chaudhury A.M. Koltunow A. Payne T. Luo M. Tucker M.R. Dennis E.S. Peacock W.J. Control of early seed development Annu. Rev. Cell Dev. Biol. 2001 17 677 699 10.1146/annurev.cellbio.17.1.677 11687501 63. Adams S. Vinkenoog R. Spielman M. Dickinson H.G. Scott R.J. Parent-of-origin effects on seed development in Arabidopsis thaliana require DNA methylation Development 2000 127 2493 2502 10.1242/dev.127.11.2493 10804189 64. Liu C.M. Meinke D.W. The titan mutants of Arabidopsis are disrupted in mitosis and cell cycle control during seed development Plant J. 1998 16 21 31 10.1046/j.1365-313x.1998.00268.x 9807824 65. Tzafrir I. Mcelver J.A. Liu C. Yang L.J. Wu J.Q. Martinez A. Patton D.A. Meinke D.W. Oklahoma I.T. Diversity of TITAN functions in Arabidopsis seed development Plant Physiol. 2002 74078 38 51 10.1104/pp.010911 66. Wang L. Chen H. Wang C. Hu Z. Yan S. Negative regulator of E2F transcription factors links cell cycle checkpoint and DNA damage repair Proc. Natl. Acad. Sci. USA 2018 115 E3837 E3845 10.1073/pnas.1720094115 29610335 67. The Arabidopsis Genome Initiative Arabidopsis Genome Initiative Analysis of the genome sequence of the flowering plant Arabidopsis thaliana Nature 2000 408 796 815 10.1038/35048692 11130711 68. Hoencamp C. Dudchenko O. Elbatsh A.M.O. Brahmachari S. Raaijmakers J.A. van Schaik T. Cacciatore Á.S. Contessoto V.G. van Heesbeen R.G. van den Broek B. 3D genomics across the tree of life reveals condensin II as a determinant of architecture type Science 2021 372 984 989 10.1126/science.abe2218 34045355 69. Schnable P.S. Ware D.H. Fulton R.S. Stein J.C. Wei F. Pasternak S. Liang C. Zhang J. Fulton L.L. Graves T. The B73 maize genome: Complexity, diversity, and dynamics Science 2009 326 1112 1115 10.1126/science.1178534 19965430

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095489 ijerph-19-05489 Article Alcohol Use of German Adults during Different Pandemic Phases: Repeated Cross-Sectional Analyses in the COVID-19 Snapshot Monitoring Study (COSMO) Koeger Melanie 12 https://orcid.org/0000-0001-6160-2847 Schillok Hannah 12 Voss Stephan 12 https://orcid.org/0000-0001-7492-7907 Coenen Michaela 12 Merkel Christina 3 Jung-Sievers Caroline 12* on behalf of the COSMO Study Team† Tchounwou Paul B. Academic Editor Feinn Richard S. Academic Editor 1 Institute for Medical Information Processing, Biometry, and Epidemiology—IBE, Chair of Public Health and Health Services Research, LMU Munich, Elisabeth-Winterhalter-Weg 6, 81377 Munich, Germany; mkoeger@ibe.med.uni-muenchen.de (M.K.); hannah.schillok@ibe.med.uni-muenchen.de (H.S.); svoss@ibe.med.uni-muenchen.de (S.V.); coenen@ibe.med.uni-muenchen.de (M.C.) 2 Pettenkofer School of Public Health, Elisabeth-Winterhalter-Weg 6, 81377 Munich, Germany 3 Federal Centre for Health Education (BZgA), Maarweg 149-161, 50825 Cologne, Germany; christina.merkel@bzga.de * Correspondence: cjungsievers@ibe.med.uni-muenchen.de † COSMO Study Team are listed in the acknowledgments. 01 5 2022 5 2022 19 9 548927 12 2021 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). There is little evidence on how different COVID-19 pandemic phases influence the alcohol use behaviour of adults. The objective of this study is to investigate alcohol use frequency over different COVID-19 pandemic phases and to identify vulnerable subgroups for risky use behaviour in the German adult population. Survey waves of 14/15 April 2020 (n = 1032), 23/24 June 2020 (n = 993), and 26/27 January 2021 (n = 1001) from the COVID-19 Snapshot Monitoring (COSMO) were analysed. The mean age was 46 ± 15.3 years in April, 46 ± 15.5 years in June, and 45 ± 15.5 years in January. The gender ratio was mostly equal in each survey wave. Descriptive analyses and univariate and multivariate logistic regression analyses for individuals with increased alcohol use frequency (AUF) were performed. 13.2% in April (lockdown), 11.3% in June (easement), and 8.6% in January (lockdown) of participants showed an increased AUF. Individuals with perceived burden, high frustration levels due to protective measures, and young to middle-aged adults were more likely to increase their AUF during different pandemic phases. In conclusion, unfavourable alcohol behaviour might occur as a potentially maladaptive coping strategy in pandemics. Because of potential negative long-term consequences of problematic alcohol use behaviour on health, public health strategies should consider mental health consequences and target addictive behaviour, while also guiding risk groups towards healthy coping strategies such as physical activities during pandemics/crises. COVID-19 alcohol use lockdown health behaviours coping strategies substance use University of ErfurtLeibniz Institute for Psychology Information (ZPID)Robert-Koch-Institute (RKI)Federal Centre for Health Education (BZgA)The COVID-19 Snapshot Monitoring (COSMO) Germany study is funded by the University of Erfurt, the Leibniz Institute for Psychology Information (ZPID), the Robert-Koch-Institute (RKI), and the Federal Centre for Health Education (BZgA). The substudy presented in this manuscript received no funding. ==== Body pmc1. Introduction Since the SARS-CoV-2 virus outbreak in Wuhan (China) in December 2019, it has spread all over the world and was declared a global pandemic by the World Health Organization (WHO) on 12 March 2020 [1]. As a result, many countries, including Germany, imposed strict social distancing and domestic quarantine measures to contain the spread of SARS-CoV-2 [2]. Not only did the virus cause severe respiratory infections, but first studies suggested that the pandemic also had an impact on the mental health and substance use behaviour in many individuals [3,4,5]. Previous crises such as the 2008 great recession, the 2001 terrorist attacks on 11 September, and the tsunami in Southeast Asia in 2004 had shown a relationship between an increased alcohol use (AU) and stressors induced by stressful life events, crises, or natural disasters [6,7,8]. In the context of the SARS outbreak in 2003, being exposed to the virus or being quarantined was associated with subsequent alcohol abuse and dependence symptoms among health care workers [9]. There is evidence of a connotation between alcohol use disorders (AUD) and stress [10]. Moreover, constitutive symptoms of depression are related to constitutive motives for AU as a coping strategy [11]. First studies about the mental health of the German population indicated an increase in symptoms of generalized anxiety, depression, psychological distress, and COVID-19-related anxiety during the pandemic [12,13]. Furthermore, loss of control, social isolation, and negative effects on the occupational/financial situation occurred in the German population [14,15]. Therefore, these stressors triggered by the COVID-19 pandemic might have led to maladaptive substance use patterns like an increased alcohol use frequency (AUF) [16]. Increasing the frequency of AU enhances the likelihood that the AUDIT (Alcohol Use Disorders Identification Test) score will rise, increasing the likelihood of heavy drinking or alcohol dependence [17]. Moreover, since alcohol use can impair the immune system, deteriorate mental health issues and the propensity for violent behaviour, and enhance the risk of acute respiratory distress syndrome, AU poses a particular health risk [18,19,20]. With the implementation of lockdowns, the WHO expressed concerns about enhanced AU during social isolation and the onset of AUDs, especially in Europe [21]. Studies by Manthey et al. and Koopmann et al. indicated that this assumption might not be unfounded for the German population in lockdown times [3,15,22]. In a European cross-sectional online survey, 32.7% of German individuals reported an increased AUF (n = 1517) [3]. An online survey assessing changes in alcohol and tobacco use behaviour during lockdown with 3245 German adults showed that 35.5% of the individuals consumed more alcohol compared to before the lockdown [22]. Although studies, as mentioned above, have already investigated the effects of crises and the pandemic on substance use behaviour such as alcohol and tobacco use, more surveys are needed to strengthen the empirical evidence and to identify risk groups for maladaptive AU behaviour. Therefore, the aim of this study was to investigate the AU pattern over different COVID-19 pandemic phases as well as to identify vulnerable subgroups for an increased AUF in the German adult population. Additionally, psychosocial factors such as mental burden, worries, and negative effects induced by the pandemic and pandemic measures were analysed as risk factors concerning unfavourable AU behaviour under this extreme situation. We hypothesised that pandemic-associated stress levels led to an increased AUF during the lockdown in the general German adult population. This could affect vulnerable population groups more than others. In addition, we evaluated various time points as we expected a lower proportion of Germans to increase their AUF in times of easement. 2. Materials and Methods 2.1. Study Design/Sample The COVID-19 Snapshot Monitoring (COSMO) study was a joint project of the University of Erfurt (Erfurt, Germany), the Robert Koch-Institute (Berlin, Germany), the Federal Centre for Health Education (Cologne, Germany), the Leibniz Institute for Psychology (Frankfurt, Germany), the Science Media Centre (Cologne, Germany), the Bernhard Nocht Institute for Tropical Medicine (Hamburg GER), and the Yale Institute for Global Health (New Haven, CT, USA) [23]. The aim of the project was to record the mental state and perception of the German population during the COVID-19 pandemic. The project consisted of repeated cross-sectional surveys (waves) conducted at first weekly, later biweekly from 3 March 2020. Approximately 1000 individuals aged 18 to 74 years from the general German population took part in each survey wave. Study participants were recruited by an ISO 26362:2009-compliant online panel (respondi.de) to represent the distribution of the German population by age, gender, and federal state in terms of the German census at each wave. Participation was based on voluntariness and anonymity. The study followed the European Data Protection Regulation. Each participant agreed to the terms of the study and provided informed consent before being able to answer the questionnaire. All general information regarding the COSMO study design, population, and recruitment, including inclusion and exclusion criteria and processes are described in the study protocol [23]. Ethical approval was granted by the ethics committee of the University of Erfurt (#20200501). In this manuscript, the COSMO survey waves of 14/15 April 2020, 23/24 June 2020, and 26/27 January 2021 were analysed. On 14/15 April 2020 (survey wave 7), the German population was in the first so-called lockdown, which was imposed by the German government on 22 March [24,25]. To examine AU behaviour during the period without a lockdown, fewer restrictions, and low incidence values, the survey of 23/24 June 2020 (survey wave 15) was included in the analyses. During the second, larger wave of infections and second strict lockdown in Germany, the ACF was conducted on 26/27 January 2021 (survey wave 34). Thus alcohol behaviour during renewed strict restrictions could be considered (see Figure 1). 2.2. Description of Variables and Measures 2.2.1. Demographic Variables Age was assessed as a continuous variable. For this study, we transformed the data into a categorical variable with the age groups 18–29, 30–44, 45–65, and ≥65 based on the GEDA (German Health Update) study [26]. In addition, gender (i.e., male, female), relationship status (i.e., yes, no), and migration background (i.e., yes, no, I don’t’ know) were used in this report. The respondents were asked in the COSMO survey whether they had children under the age of 18 with several age groups as well as “no” as possible response formats. Response options were collapsed to a binary variable (i.e., yes, no). 2.2.2. Socioeconomic Variables The net income of the participants was assessed with the income classes < €1250, €1250–1749, €1750–2249, €2250–2999, €3000–3999, €4000–4999, and ≥ €5000 by COSMO. We performed a recoding as follows: (a) <€1250 to capture individuals living near or below the poverty line [27], (b) €1250–2249 to mark the middle-class population including the average income of €1950, (c) €2250–3999 to represent the upper-middle class, and (d) >€4000 to capture the population with a high monthly income [28]. The number of household members (i.e., only me, 2 persons, 3–4 persons, >4 persons, no specification), the status of employment (i.e., yes, no), educational level (<9 years of schooling, >10 years of schooling without A-level, >10 years of schooling with A-level), and federal state of residence (Baden-Württemberg, Bavaria, Berlin, Brandenburg, Bremen, Hamburg, Hesse, Mecklenburg-Western Pomerania, Lower Saxony, North Rhine-Westphalia, Rhineland-Palatinate, Saarland, Saxony, Saxony-Anhalt, Schleswig-Holstein, Thuringia) was assessed by COSMO. For this manuscript, the federal state of residence was recoded into two local regions (i.e., east and west). 2.2.3. Main Outcome: Alcohol Use Frequency In the COSMO study, AUF was assessed as an indicator for AU behaviour with two variables in the survey waves of 14/15 April 2020, 19/20 May 2020, 23/24 June 2020, 27/28 October 2020, and 26/27 January 2021. The first variable records AUF during the last twelve months. The second refers to AUF during the last four weeks before the survey wave. The study participants were asked how often they drank alcohol such as beer, wine, sparkling wine, spirits, schnapps, cocktails, alcoholic mixed drinks, liqueurs, homemade, or home-distilled alcohol on a weekly basis. Possible answers were “On all days a week“, “On 5 or 6 days a week“, “On 3 or 4 days a week“, “On 2 days a week“, “On 1 day a week“, “On no day”, “I rarely drink alcohol”, and “I never drink alcohol”. In this work, a new variable was created by comparing the reported AUF during the last four weeks to the AUF during the last twelve months before the survey wave, with the categories “reduced AUF”, “unmodified AUF”, and “increased AUF”. For this purpose, auxiliary variables were formed first in which the answer options “I never drink alcohol”, “I rarely drink alcohol”, and “On no day” were combined since they describe very similar user behaviour. By aggregating the groups “reduced AUF” and “unmodified AUF”, a binary variable was created to analyse the subgroups and factors influencing an increased AUF using univariate and multivariate logistic regression. The DHS (German Head Office for Addiction Issues) recommends no AU on two days per week as well as a maximum intake of 10–12 g alcohol/day for healthy females and 20–24 g alcohol/day for healthy male adults as low-risk use [29,30]. Adherence to this recommendation was used as an additional outcome measure. For this purpose, we created a binary variable in which the response options “On 5 or 6 days a week” and “On all days of a week” were collapsed, representing no compliance to the recommendation (i.e., AU on ≥5 days/week). The remaining response options were aggregated as reference category “AU on <5 days/week”. 2.2.4. Health-Related Variables The variable to capture the presence of chronic disease and affiliation to the risk group for SARS-CoV-2 (i.e., yes, no, I don’t know) were conducted by COSMO. For this report, we modelled an item assessing awareness of a personal corona infection with the response formats “yes (current/convalesced)” (originally: yes, confirmed; yes, but not yet confirmed; yes, convalesced), and “no” (originally: no, I don’t know). To elicit physical activity, subjects were asked how much time they spent on sports, fitness, or physical activity in their free time during a typical week in the current pandemic. The WHO recommends at least 2.5 h of moderate-intensity endurance exercise per week [31]. Based on this recommendation, we created a binary variable that included the categories “<2.5 h/week” and “≥2.5 h/week”. 2.2.5. Variables Assessing Psychosocial Aspects, Reactance to Pandemic Measures and Mental Health Perceived burden by the pandemic was queried in COSMO (i.e., yes, no). Additionally, study participants were asked how much they worried about (a) losing their job, (b) widening of the gap between rich and poor, (c) getting infected by SARS-CoV-2, and (d) long-term restriction of social life. These questions could be answered on a 7-point Likert scale ranging from very little concern (1) to very much concern (7). For our analyses, the items were recoded into binary variables describing high levels of worries with response formats of “yes” (5–7) and “no” (1–4). Similarly, the variables assessing the frequency of obtaining information about SARS-CoV-2 (1: never, 7: very often) and frustration due to pandemic measures (1: not at all, 7: very much) were converted to analyse increased information seeking and frustration, respectively (5–7: yes, 1–4: no). Furthermore, two 7-point Likert scale variables about SARS-CoV-2 perception (i.e., the SARS-CoV-2 is something) were conducted by COSMO: One with “I feel helpless about” (1) to “I can actively do something about” (7) and another with “I think a lot about” (1) to “I almost never think about” (7) as response options. For our study, these items were recoded to perceived helplessness regarding SARS-CoV-2 (1–3: yes, 4–7: no) and high levels of rumination about SARS-CoV-2 (1–3: yes, 4–7: no). 2.3. Statistical Analysis The absolute and relative frequencies of all participants and those with an increased AUF were calculated to analyse AUF over different COVID-19 pandemic phases descriptively. For longitudinal comparison, odds ratios (OR), including 95% confidence intervals (CI), were computed by univariate analysis. In addition, proportions of non-drinkers were compared to historical data from the cross-sectional German Health Update (GEDA) study 2014/2015 for age groups and gender using relative frequencies [26]. The GEDA study took place from November 2014 to July 2015 and represented a national health survey. Data was collected by online or paper questionnaire from individuals aged 18 years and older randomly selected from 301 municipalities in Germany. To assess vulnerable subgroups for an increased AUF in our study, univariate logistic regressions were conducted, and results were reported as OR with corresponding 95% CIs. The influence of COVID-19 associated factors on an increased AUF was analysed respectively. Multivariate logistic regression analysis for an increased AUF was performed, including gender, education, awareness of migration, relationship status, household income, and burden based on previous studies [15,26,32,33,34]. We reported ORs, 95% CIs as well as Nagelkerke’s R2. Since COSMO was designed as an explanatory approach, adjustments for multiple testing were not performed. As an additional analysis, a univariate logistic regression for individuals exceeding the DHS recommendation of AU on a maximum of five days a week was estimated [35]. For all logistic regression analyses, determinants with the response options “yes”, “no”, and “I don’t know” (migration background, chronic disease, affiliation to risk group) were collapsed into “no/don’t know” and “yes”. The number of household members (i.e., only me, 2 persons, 3–4 persons, >4 persons, no specification) was recoded to “only me”, “2 persons”, and “≥3 persons” for the statistical analyses. Educational background was collapsed to a binary variable (i.e., no A-level, A-level) due to a small sample size of the category “<9 years of schooling”. In the case of missing data (household size, net household income, worry employment), these cases were excluded from estimations. To test the significance of variables, p values ≤ 0.05 were used (Wald’s test). All analyses were performed using the statistical software R (version 4.0.4) and RStudio (version 1.4.1716) [36]. 3. Results 3.1. Sample Characteristics In Table 1, study sample characteristics in each survey wave for the total study population and for the subsamples with an increased AUF are presented. The general study population included 1032, 993, and 1001 participants in the survey wave 7 (14/15 April 2020), wave 15 (23/24 June 2020), and wave 34 (26/27 January 2021), respectively. 136 (13.2%), 112 (11.3%), and 86 (8.6%) individuals showed an increased AUF in wave 7 (W7), wave 15 (W15), and wave 34 (W34), respectively. Gender distribution was mostly equal in each wave. The mean age was 46 ± 15.3 years in W7, 46 ± 15.5 years in W15, and 45 ± 15.5 years in W34, with the age group 45 to 64 representing the largest share in the three survey waves. Slightly more than half of the study sample had the highest educational level (A-level). The most common household size was two persons and amounted to approximately 40% in each survey wave. Participants with perceived burden accounted for 40.1% (W7), 36.8% (W15), and 57.1% (W34). For detailed information about general and subsamples, see Table 1. 3.2. Alcohol Use Frequency in Different Phases of the Pandemic Across the different pandemic phases, there was a decrease in the number of individuals who drank alcohol several times a week (W7: 30.2%; W15: 28.7%; W34: 25.6). Daily use was documented by 5.9% (W7) and 4.3% (W34) of study participants, with the lowest proportion at times of easement in W15 amounting to 3.7%. With 13.2% (W7), 11.3% (W15), and 8.6% (W34) of respondents, a decreasing trend across the different pandemic phases is indicated for an increased AUF (see Figure 2). The univariate logistic analysis (see Table S1 in the Supplementary file) showed a significant difference for results between W34 vs. W7 (0.62; 95% CI: 0.47–0.82) and W34 vs. W15 (0.74 [0.55–0.99]). The proportion of subjects with reduced AUF was 8.0% (W7), 6.8% (W15), and 7.5% (W34). In terms of non-drinkers, the proportions showed marginally higher values for males compared to GEDA data from 2014/2015 (W7: 12.7%, W15: 13.5%, W34: 13.5% vs. 10.3%) [26]. A greater positive deviation from the GEDA data was found for women (W7: 17.0%, W15: 17.8%, W34: 16.4% vs. 13.7%). Further information can be found in Table S2 in the Supplementary file). 3.3. Increased Alcohol Use Frequency in Different Subgroups: Univariate Logistic Regression Table 2 illustrates relative frequencies as well as the corresponding OR with 95% CIs of those who consumed alcohol more frequently during the last four weeks. Men showed an increased AUF more often than women in W7 and W15, though the OR was only significant in W15 (0.65 [0.44–0.97]). With increasing age, the chances of an increased AUF decreased slightly in every survey wave (W7: 0.98 [0.97–0.99]; W15: 0.98 [0.97–1.00]; W34: 0.99 [0.97–1.00]. Especially the age group 18–29 years (W7: 2.35 [1.26–4.37]; W15: 2.47 [CI: 1.06–5.76], W34: 1.41 [0.65–3.02] and 30–44 years (W7: 2.06 [1.13–3.74]; W15: 2.99 [1.37–6.53]; W34: 1.26 [0.61–2.58]) showed higher ORs for an increased AUF. However, the comparator group of those over 65 was relatively small (W7: n = 16, W15: n = 8, W34: n = 11). The odds for an increased AUF were higher for participants in a relationship (significant in W15: 1.73 [1.08–2.75]) or respondents who didn’t live alone. Though, the OR was only significant for the household size of three people in W15 (1.82 [1.06–3.12]) and two people in W34 (2.51 [1.27–4.95]). The odds for an increased AUF were higher among participants with children in W7 and W15, the latter being significant (1.77 [1.18–2.65]). Regarding socioeconomic status, upper-middle class individuals showed the highest odds for an increased AUF with a significant result in W15 (2.15 [1.02–4.52]) and non-significant results in W34 (23.3%). In W15, there was a positive association between increased AUF and employment (1.68 [1.07–2.65]). Chronic illness was negatively related to an increased AUF in W34 (0.55 [0.32–0.92]). More participants with an increased AUF performed the recommended amount of physical activity in W7 (1.57 [1.09–2.25]). Considering pandemic-related variables, a positive association between perceived burden and an increased AUF was evident in W7 (1.59 [1.11–2.28]) and W15 (1.73 [1.16–2.57]) (see also Figure 3). High levels of frustration due to pandemic measures were positively associated with an increased AUF in June (1.61 [1.10–2.36]) and April (2.17 [1.45–3.24]). With ORs of 1.51 [1.05–2.16], high levels of rumination about SARS-CoV-2 were positively linked to an increased AUF in W7. A positive association between an increased AUF and perceived helplessness regarding SARS-CoV-2 was observed in W7 (1.51 [1.05–2.17]). Enhanced worries did not show homogeneous patterns of association with an increased AUF: i.e., high levels of worries about getting ill by SARS-CoV-2 and worries about long-time restrictions of social life were not related to an increased AUF, high levels of worries about losing employment were positively associated with an increased AUF in W7 (1.56 [1.03–2.34]). 3.4. Multivariate Logistic Regression Table 3 shows our results of the multivariate logistic regression analysis. Age was positively associated with an increased AUF in W7 (0.98 [0.96–0.99]) and W15 (0.98 [0.97–1.00]), and being in a relationship resulted in a higher OR for an increased AUF in W34 (1.77 [1.01–3.09]). The perceived burden was associated with an increased AUF in W7 (1.53 [1.06–2.20]) and W15 (1.72 [1.14–2.58]) but not in W34. 3.5. Adherence to DHS Recommendation for Alcohol Use: Univariate Logistic Regression Regarding gender, relationship status, household size of two persons, and household net income, the results exceeding the maximum number of days for AC recommended by the DHS were similar to those for an increased AUF. In contrast to the results of the increased AUF analysis, the age groups 18–29 and 30–44 showed low odds of drinking alcohol more than five times per week (see Table S4 in the Supplementary file). With an OR of 1.60 [1.09–2.37] in W7, the perceived burden was positively associated with not complying with the recommendation for AUF, which was comparable to the results for an increased AUF. However, the OR of 1.21 [0.75–1.94] in W15 was not significant, and in W34, it was just below one at 0.95 [0.61–1.51]. Enhanced information frequency was positively related to exceeding the recommendation in W7 (2.08 [1.20–3.61]). All other pandemic-related variables showed an inhomogeneous and non-significant picture across all waves as well as compared to the analysis of an increased AUF. Data is shown in Table S4 in the Supplementary file. 4. Discussion For this work, we analysed COSMO data on AU behaviour at three time points during the COVID-19 pandemic in Germany. An increased AUF was observed during times of lockdown and easement of the pandemic. Taking a public health view, and with regard to possible prevention strategies, we focused on the vulnerable subgroups for an increased AUF in every pandemic phase and how to possibly target them. Our main results suggest that individuals with perceived burden, high frustration levels due to protective measures, and young to middle-aged adults were more likely to increase AUF over all pandemic phases, regardless of actual context factors. Other factors influencing an increased AUF varied between the different pandemic phases. First of all, our findings indicate that some increased while some decreased their AUF in different pandemic phases, with slightly more respondents showing an increased AUF. This result was supported by a cross-sectional European online survey with 32.7% increased AUF vs. 24.4% decreased AUF for German individuals (N = 1517) [3]. Furthermore, an online survey of 3245 German adults assessing changes in alcohol use behaviour during the lockdown found a higher proportion of individuals consuming more alcohol than less (35.5% vs. 21.3%) [22]. In other European countries, a higher proportion of an increased AUF was reported for France, Ireland, Poland, and the United Kingdom. In contrast, most European countries had a higher proportion of decreased AUF during the pandemic [3]. The decrease in AUF in Germany was significantly lower compared to other European countries [15]. These results imply that Germany is more vulnerable to an increased AUF than other countries in Europe. Fewer occasions for AU are given due to the closure of restaurants, bars, and clubs, as well as the cancellation of (large) events in (stricter) lockdown times [37]. Moreover, time restrictions on alcohol sales and night-time curfews might have led to a decreased AUF as well [2]. Since social motives are an important reason for AU, limiting the number of people allowed to meet in private might also have led to a reduction in AUF [16]. However, access to alcohol in supermarkets, gas stations, kiosks, as well as from to-go offerings in restaurants was constant during all pandemic periods with minor restrictions [37]. Additionally, people found new methods to gather for drinking, such as online pub quizzes or online parties [38]. As a second main result, our findings indicated that individuals with perceived burden or high levels of frustration due to protective measures, as well as young to middle-aged adults, were vulnerable to an increased AUF in all pandemic phases. Our multivariate and univariate analysis showed an association between perceived burden and an increased AUF, which was confirmed by another study in Germany in terms of a general increased AU [22]. It has been reported that the German population showed increased symptoms of generalized anxiety, depression, psychological distress, and COVID-19-related fears relatively stable over the different phases of the pandemic [12,13]. As noted in previous studies, these psychological stressors might be important triggers for an increased AUF, implying that alcohol was used as a maladaptive coping strategy [8,33,39]. Moreover, there might be a reciprocal interaction between an increased AUF and heightened levels of perceived burden [40,41]. Recent research suggests that women were more affected by pandemic distress, which is also mainly confirmed by our gender-stratified analysis (data not shown) [13,42]. Nevertheless, AU on ≥5 days/week was still significantly associated with being male in our analysis. In terms of the temporal dynamics and considering AU as a coping strategy, we expected a lower proportion of an increased AUF in W15 than in W7 and W34 since the pandemic measures were more lenient in W15. Hence, stress levels, and therefore AUF, might have been lower. However, Skoda et al. noted that the high burden levels persisted even when pandemic-induced fears declined and an easement of the pandemic measures was given [13]. On the other hand, there were more occasions for AU in June due to loosened pandemic regulations, and thus, an increased AUF might also have been caused by social drinking motives [16]. High frustration levels due to pandemic measures were positively related to an increased AUF, which can be confirmed by the literature [8,16]. The management of internal emotional stress through AU can be attributed to the inhibitory effect of alcohol on the nervous system [43]. Young adults showed high odds for an increased AUF in our analysis. Studies in the USA and Germany substantiate this result [4,44]. Young adults are in a stage of life where crucial decisions for their future have to be made, e.g., regarding career and relationships [45]. Phases of lockdown and social stagnation might have restricted them in these processes, which can increase the burden and thus AUF [46]. In addition, they are particularly reliant on marginal employment such as waitressing to make a living, which was lost due to the pandemic measures. This might have led to economic difficulties and potential risk factors for an increased AU [34]. As the early onset of AU is related to an enhanced risk of alcohol abuse and dependence, there might be a higher prevalence of AUD in the future [47]. However, Manthey et al. reported that decreased AU was mainly found in younger German individuals [15]. Additionally, recent studies indicated that young adults were more likely to experience not only an increase but also a decrease in AU during the pandemic [44,48]. Therefore, further research is needed to investigate the AU behaviour of young adults during a pandemic. The association between being in a relationship and an increased AUF (W15) could be potentially explained by increased peer pressure, relationship problems, or a maladaptive coping strategy of boredom and/or stress. Consistent with the existing literature, our work also identified middle-aged individuals as a vulnerable subgroup for an increased AUF [22,49]. Our work and a recent study have shown an association between parenting, which is often linked to middle age, and an increased AUF [50]. Furthermore, middle-aged individuals might be most at risk of financial dependence, as they are likely to have only been employed for a few years, have to provide for a family, and might have a loan to repay [49]. Besides, our analysis implied that individuals with perceived helplessness and high levels of rumination were at risk for an increased AUF in W7. Wolitzky-Taylor et al. reported a link between ruminative thinking and AUD [51]. Since worries are related to burden, we assumed that analyses of the effects of worries on AUF would have yielded a higher degree of correlation. However, an increase in worries showed different probabilities of an increased AUF, which might be explained by various personality traits [34]. Regarding socioeconomic status (income, employment, migration background, and education), our analyses showed high variability. An underrepresentation of individuals with low socioeconomic status in this snapshot survey might have led to distorted results in our study. Nevertheless, previous research has reviewed that unemployment and financial stressors are positively and negatively associated with adverse AU behaviour, respectively [8,34]. Interestingly, performing the recommended amount of physical activity was positively associated with an increased AUF in W7 (1.57 [1.09–2.25]). This could imply that individuals also engage in good coping strategies besides maladaptive ones [52]. Further research is needed to clarify the relationship between physical activity and AU behaviour and possible mediators. As there is no safe level of AU and a previous SARS outbreak has shown the occurrence of later alcohol abuse and dependence symptoms, it is important to inform the population about the risks of AU/an increased AUF [9,10,18]. Besides addictive concerns, social dangers can also arise from adverse alcohol behaviour, e.g., domestic violence, accidents, and crime [18,19,53]. Regarding future pandemics, more stringent public health strategies aimed at limiting AU/access to alcoholic beverages are needed (i.e., stricter time restrictions on the sale of alcohol in retail outlets, restrictions on alcohol marketing, or higher taxes/prices on alcoholic beverages) [53,54]. Additionally, more information about maladaptive coping strategies and their negative impact on health should be made available to the general population (e.g., easily accessible online fact sheets and various digital apps). Regarding burden as a risk factor for maladaptive alcohol behaviour, more psychosocial supports and services should be offered in times of pandemics or crises. Additionally, incentives for physical activity and other healthy coping strategies should be created by policymakers, especially for young to middle-aged adults during pandemics. Strengths and Limitations In terms of strengths, this repeated cross-sectional study design allows good insights into different pandemic phases. With about 1000 participants in each survey wave, a sufficient study population is given. Gender and age distribution are representative due to COSMO study recruitment. However, small sub-samples for given sub-questions might have distorted results in some sub-analyses. Still, study limitations also need to be considered. Due to the repeated cross-sectional study design, no conclusions can be drawn about the causality of the results. Although a cross-sectional design was chosen for this snapshot study, a prospective longitudinal study with the same individuals would have provided better insights into the trajectories of individual AU behaviour in relation to changing contextual factors. Considering bias, recall bias and social desirability bias might have occurred since COSMO collects self-reported data. In our sample, W34 was conducted nine months after the onset of the pandemic. Hence, the results of W34 might be distorted due to recall bias, habituation effect, or holidays that ended between 2 and 10 January 2021, respectively, to the federal state. In addition, pre-pandemic data on individual AU behaviour was unavailable in this study design. It should be noted that the variables of COSMO applied to survey AU are not validated instruments and only assess the frequency of AU. Valid statements about hazardous AU or alcohol dependency can only be made by assessing the consumed quantity, heavy drinking, and items assessing dependence symptoms [17]. Nevertheless, frequency represents an easier variable to remember than the exact amount consumed. Regarding DHS recommendation, using five days a week would still be acceptable. However, since use five days a week was assessed in a category together with six days a week, we had to consider five days a week as exceeding the recommendation. After all, some contextual factors that could be determinants for an increased (e.g., job loss, boredom, or quarantine) or decreased (e.g., earlier closing times for on-use outlets or alcohol restrictions in public areas) AUF during the COVID-19 pandemic were not collected by the COSMO survey. Due to the snapshot design of the study, no profound conclusions can be drawn for individual topics. 5. Conclusions In conclusion, an increased AUF was present over different phases of the COVID-19 pandemic. Individuals showing perceived burden, high levels of frustration due to protective measures, and young to middle-aged adults were identified as most vulnerable to an increased AUF. Because of the potential negative long-term consequences on health, public health strategies should target addictive behaviour during pandemics/crises while considering the aforementioned vulnerable groups. In addition, general preventive measures such as access to alcoholic beverages should be more strictly limited. The public should be guided towards healthy coping strategies such as physical activities instead of AU. Moreover, further research is needed to examine the extent and the motives for an increased AUF, binge drinking, and heavy drinking, as well as the impact of the COVID-19 pandemic on future AU behaviour and AUDs. Acknowledgments Germany’s COVID-19 Snapshot Monitoring (COSMO) is a joint project of the University of Erfurt (Cornelia Betsch [PI], Lars Korn, Philipp Sprengholz, Philipp Schmid, Lisa Felgendreff, Sarah Eitze), the Robert Koch Institute (RKI; Lothar H. Wieler, Patrick Schmich, Nora Katharina Schmid-Küpke), the Federal Centre for Health Education (BZgA; Heidrun Thaiss, Freia De Bock, Ursula von Rüden, Christina Merkel, Boris Orth), the Leibniz Centre for Psychological Information and Documentation (ZPID; Michael Bosnjak), the Science Media Center (SMC; Volker Stollorz), the Bernhard Nocht Institute for Tropical Medicine (BNITM; Michael Ramharter), and the Yale Institute for Global Health (Saad Omer). Review: Robert Böhm (University of Copenhagen), Britta Renner (University of Constance), Tobias Rothmund (University of Jena), Petra Dickmann (University Hospital Jena). Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095489/s1, Supplementary Table S1. Univariate analysis for modification of AUF (last four weeks vs. last 12 months) between different pandemic phases: ORs and 95% CIs. Supplementary Table S2. Comparison of relative proportions of non-drinkers during the pandemic (AUF in the last four weeks: category “never”) to pre-pandemic data (GEDA 14/15). Supplementary Table S3. Univariate analysis for pandemic-related variables: relative frequencies, ORs, and 95% CIs of individuals with increased AUF compared to those with reduced/unmodified AUF between different subgroups. Supplementary Table S4. Univariate analysis: relative frequencies, ORs, and 95% CIs of individuals exceeding (AU on ≥5 days/week) compared with those who adhere to the DHS recommendation (AU on <5 days/week). Click here for additional data file. Author Contributions Conceptualisation Subproject, M.K. and C.J.-S.; Conceptualisation: COSMO Consortium represented by C.M.; Methodology, M.K., C.J.-S., C.M., H.S. and S.V.; Software, M.K. and S.V.; Formal Analysis, M.K., C.J.-S. and S.V.; Writing—Original Draft Preparation, M.K., Supervision C.J.-S.; Writing—Review and Editing, M.K., C.J.-S., M.C., H.S., C.M. and S.V.; Supervision, C.J.-S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the University of Erfurt (#20200501). Informed Consent Statement Informed consent was obtained from all subjects included in the study. Data Availability Statement Data are not publicly available, but interested parties may contact the authors for more information. The data are not publicly available due to ethical restrictions. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Development of daily incidences (n) of SARS-CoV-2 infections in Germany from March 2020 to February 2021. Important changes in pandemic measures for the public are marked. Own illustration based on incidence data from the dashboard of the Robert-Koch Institute https://experience.arcgis.com/experience/478220a4c454480e823b17327b2bf1d4/page/page_1/ (accessed on 28 June 2021). Figure 2 Relative proportions (%) of individuals with reduced, unmodified, and increased AUF in different pandemic phases. Figure 3 ORs and 95% CIs of univariate analysis for pandemic-related variables of individuals with an increased AUF compared to those with reduced/unmodified AUF (see Table S3 in the Supplementary file). ijerph-19-05489-t001_Table 1 Table 1 Sample characteristics. Characteristics Wave 7 (14/15 April 2020) Wave 15 (23/24 June 2020) Wave 34 (26/27 January 2021) Total Increased AUF Total Increased AUF Total Increased AUF n/mean %/SD n/mean %/SD n/mean %/SD n/mean %/SD n/mean %/SD n/mean %/SD Total 1032 - 136 13.2 993 - 112 11.3 1001 - 86 8.6 Gender Male 503 48.7 75 55.1 483 48.6 65 58.0 504 50.3 44 51.2 Female 529 51.3 61 44.9 510 51.4 47 42.0 497 49.7 42 48.8 Age (continuous) 46 15.7 41 15.3 46 15.5 43 14.3 45 15.5 41 15.7 Age group 18–29 207 20.1 39 28.7 178 17.9 21 18.8 192 19.2 21 24.4 30–44 296 28.7 50 36.8 309 31.1 43 38.4 313 31.3 31 36.0 45–64 351 34.0 31 22.8 350 35.2 40 35.7 359 35.9 23 26.7 ≥65 178 17.2 16 11.8 156 15.7 8 7.1 137 13.7 11 12.8 Education level <9 years 127 12.3 13 10.2 112 11.3 11 9.8 119 11.9 9 7.6 >10 years (no A-level) 326 31.6 41 12.6 340 34.2 45 13.2 309 30.9 23 7.4 >10 years (A-level) 579 56.1 82 14.2 541 54.5 56 10.4 573 57.2 54 9.4 Migration background No 894 86.6 119 12.0 839 84.5 88 16.0 811 81.0 69 9.1 Yes 133 12.9 16 13.3 150 15.1 24 1.5 187 18.7 17 8.5 I don’t know 5 0.5 1 20.0 4 0.4 0 0 3 0.3 0 0.0 Local region East 168 16.3 19 14.0 165 16.6 17 15.2 161 16.1 11 12.8 West 864 83.7 117 86.0 828 83.4 95 84.8 840 83.9 75 87.2 Relationship No 316 30.6 41 30.1 317 31.9 25 22.3 309 30.9 20 23.3 Yes 716 69.4 95 69.9 676 68.1 87 77.7 692 69.1 66 76.7 Children No Children 725 70.3 88 64.7 698 70.3 66 58.9 716 71.5 62 72.1 Children 307 29.7 48 35.3 295 29.7 46 41.1 285 28.5 24 27.9 Household size Just me 236 22.9 29 12.3 262 26.4 21 8.0 231 23.1 11 5.6 2 persons 441 42.7 53 12.0 387 39.0 44 11.4 404 40.4 45 11.1 3–4 persons 308 29.8 50 16.2 293 29.5 37 12.6 302 30.2 25 6.3 >4 persons 47 4.6 4 8.5 51 5.1 10 19.6 61 6.1 5 8.2 No specification 0 0 0 0 0 0 0 0.0 3 0.3 0 0.0 Household net income <€1250 NA NA NA NA 142 14.3 11 9.8 115 11.5 10 11.6 €1250–2249 NA NA NA NA 249 25.1 24 21.4 245 24.5 21 24.4 €2250–3999 NA NA NA NA 352 35.4 47 42.0 367 36.7 27 31.4 >€4000 NA NA NA NA 170 17.1 26 23.2 199 19.9 20 23.3 No specification NA NA NA NA 80 8.1 4 3.6 75 7.5 8 9.3 Employment No NA NA NA NA 334 33.6 27 24.1 309 30.9 28 32.6 Yes NA NA NA NA 659 66.4 85 75.9 692 69.1 58 67.4 Chronic disease No 641 62.1 92 10.7 632 63.6 71 10.9 634 63.3 64 8.0 Yes 345 33.4 37 14.4 338 34.0 37 11.2 332 33.2 19 9.0 I don’t know 46 4.5 7 15.2 23 2.3 4 17.4 35 3.5 3 2.9 Personal infection with SARS-CoV-2 No 1013 98.2 99 72.8 966 97.3 109 97.3 945 94.4 80 93.0 Yes (current/convalesced) 19 1.8 37 27.2 27 2.7 3 2.7 56 5.6 6 7.0 Affiliation to risk group for SARS-CoV-2 No NA NA NA NA 475 47.8 64 9.3 572 57.1 57 6.1 Yes NA NA NA NA 518 52.2 48 13.5 349 34.9 21 11.2 Don’t know NA NA NA NA 0 0 0 0 80 8 8 10.0 Perceived burden No 618 59.9 68 50.0 639 64.4 59 52.7 429 42.9 31 36.0 Yes 414 40.1 68 50.0 354 35.6 53 47.3 572 57.1 55 64.0 AUF during the last four weeks Never 175 17.0 0 0.0 177 17.8 0 0.0 164 16.4 0 0.0 Rarely 319 30.9 0 0.0 332 33.4 0 0.0 371 37.1 0 0.0 Once a week 165 16.0 39 28.7 162 16.3 34 30.4 167 16.7 28 32.6 Several times per week 312 30.2 86 63.2 285 28.7 74 66.1 256 25.6 51 59.3 On all days of the week 61 5.9 11 8.1 37 3.7 4 3.6 43 4.3 7 8.1 Abbreviations: AUF: alcohol use frequency, N: number of cases in the total sample, n: number of cases in the subsamples with an increased AUF, SD: standard deviation, NA: not available (not collected in this wave). ijerph-19-05489-t002_Table 2 Table 2 Univariate analysis: relative frequencies, ORs, and 95% CIs of individuals with an increased AUF compared to those with reduced/unmodified AUF between different subgroups. Characteristics Wave 7 (14/15 April 2020) Wave 15 (23/24 June 2020) Wave 34 (26/27 January 2021) Increased 95% CI Increased 95% CI Increased 95% CI AUF (%) OR AUF (%) OR AUF (%) OR Gender Male (reference) 14.9 13.5 8.7 Female 11.5 0.74 [0.52–1.07] 9.2 0.65 [0.44–0.97] * 8.5 0.97 [0.62–1.50] Age (continuous) 0.98 [0.97–0.99] *** 0.98 [0.97–1.00] * 0.99 [0.97–1.00] Age group ≥65 (reference) 9.0 5.1 8.0 18–29 18.8 2.35 [1.26–4.37] ** 11.8 2.47 [1.06–5.76] * 10.9 1.41 [0.65–3.02] 30–44 16.9 2.06 [1.13–3.74] * 13.9 2.99 [1.37–6.53] ** 9.9 1.26 [0.61–2.58] 45–64 8.8 0.98 [0.52–1.85] 11.4 2.39 [1.09–5.23] * 6.4 0.78 [0.37–1.66] Educational level No A-Level (reference) 11.9 12.4 7.5 A-Level 14.2 1.22 [0.84–1.76] 10.4 0.82 [0.55–1.21] 9.4 1.29 [0.82–2.03] Migration background No/Don’t know (reference) 13.3 10.4 8.5 Yes 12.0 0.89 [0.51–1.55] 16.0 1.63 [1.00–2.65] * 9.1 1.08 [0.62–1.88] Local region East 11.3 10.3 6.8 West 13.5 1.23 [0.73–2.06] 11.5 1.13 [0.65–1.95] 8.9 1.34 [0.69–2.58] Relationship No (reference) 13.0 7.9 6.5 Yes 13.3 1.03 [0.69–1.52] 12.9 1.73 [1.08–2.75] * 9.5 1.52 [0.91–2.56] Children No (reference) 12.1 9.5 8.7 Yes 15.6 1.34 [0.92–1.96] 15.6 1.77 [1.18–2.65] ** 8.4 0.97 [0.59–1.59] Household size Just me (reference) 12.3 8.0 4.8 2 people 12.0 0.98 [0.60–1.58] 11.4 1.47 [0.85–2.54] 11.1 2.51 [1.27–4.95] ** ≥3 people 15.2 1.38 [0.85–2.26] 13.7 1.82 [1.06–3.12] * 8.3 1.81 [0.87–3.75] Household net income <€1250 (reference) NA NA NA 7.7 8.7 €1250–2249 NA NA NA 9.6 1.27 [0.60–2.68] 8.6 0.98 [0.45–2.16] €2250–3999 NA NA NA 13.4 1.84 [0.92–3.65] 7.4 0.83 [0.39–1.78] >€4000 NA NA NA 15.3 2.15 [1.02–4.52] * 10.1 1.17 [0.53–2.60] No specification NA NA NA 5.0 0.63 [0.19–2.04] 10.7 1.25 [0.47–3.34] Employment No (reference) NA NA NA 8.1 9.1 Yes NA NA NA 12.9 1.68 [1.07–2.65] * 8.4 0.92 [0.57–1.47] Chronic disease No/Don’t know (reference) 14.4 11.5 10.0 Yes 10.7 0.71 [0.48–1.07] 10.9 0.97 [0.64–1.48] 5.7 0.55 [0.32–0.92] * Physical activity <2.5 h/week (reference) 11.0 10.8 NA NA NA ≥2.5 h/week 16.2 1.57 [1.09–2.25] ** 12.1 1.13 [0.75–1.69] NA NA NA To view the n of the subgroups, refer to Table 1. * p < 0.05; ** p < 0.01, *** p < 0.001; marked in bold. Abbreviations: AUF: alcohol use frequency, OR: odds ratio, CI: confidence interval, NA: not available (not collected in this wave). Non-respondents for household size were not included in the analysis. ijerph-19-05489-t003_Table 3 Table 3 Multivariate analysis: adjusted ORs and 95% CIs of individuals with an increased AUF compared to those with reduced/unmodified AUF between different subgroups. Characteristics Wave 7 (14/15 April 2020) Wave 15 (23/24 June 2020) Wave 34 (26/27 January 2021) OR 95% CI OR 95% CI OR 95% CI Gender Male (reference) Female 0.69 [0.48–1.00] 0.62 [0.42–1.04] 0.95 [0.60–1.48] Age (continuous) 0.98 [0.96–0.99] *** 0.98 [0.97–1.00] * 0.99 [0.97–1.00] Educational level No A-Level (reference) A-Level 0.98 [0.66–1.45] 0.68 [0.45–1.04] 1.22 [0.75–1.99] Migration background No/Don’t know (reference) Yes 0.73 [0.41–1.30] 1.52 [0.91–2.53] 0.98 [0.55–1.73] Relationship No (reference) Yes 1.11 [0.75–1.66] 1.50 [0.89–2.52] 1.77 [1.01–3.09] * Household net income <€1250 (reference) NA NA €1250–2249 NA NA 1.16 [0.54–2.48] 0.91 [0.41–2.03] €2250–3999 NA NA 1.63 [0.78–3.40] 0.64 [0.29–1.43] >€4000 NA NA 1.93 [0.85–4.36] 0.87 [0.37–2.03] No specification NA NA 0.56 [0.17–1.88] 1.08 [0.40–2.93] Perceived burden No (reference) Yes 1.53 [1.06–2.20] * 1.72 [1.14–2.58] * 1.33 [0.83–2.13] Nagelkerke Pseudo R2 0.0434 0.0707 0.0251 To view the n of the subgroups, refer to Table 1. * p < 0.05; ** p < 0.01, *** p < 0.001; marked in bold. Abbreviations: AUF: alcohol use frequency, OR: odds ratio, CI: confidence interval, NA: not available (not collected in this wave). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. World Health Organization WHO Announces COVID-19 Outbreak a Pandemic Available online: https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/news/news/2020/3/who-announces-covid-19-outbreak-a-pandemic (accessed on 6 June 2021) 2. Bundesregierung 22. März 2020: Regeln Zum Corona-Virus Available online: https://www.bundesregierung.de/breg-de/leichte-sprache/22-maerz-2020-regeln-zum-corona-virus-1733310 (accessed on 21 February 2021) 3. Manthey J. Kilian C. Carr S. Bartak M. Bloomfield K. Braddick F. Gual A. Neufeld M. O’Donnell A. Petruzelka B. Use of alcohol, tobacco, cannabis, and other substances during the first wave of the SARS-CoV-2 pandemic in Europe: A survey on 36,000 European substance users Subst. Abus. Treat. Prev. Policy 2021 16 36 10.1186/s13011-021-00373-y 33902668 4. Knell G. Robertson M.C. Dooley E.E. Burford K. Mendez K.S. Health Behavior Changes During COVID-19 Pandemic and Subsequent “Stay-at-Home” Orders Int. J. Environ. Res. Public Health 2020 17 6268 10.3390/ijerph17176268 32872179 5. Xiong J. Lipsitz O. Nasri F. Lui L.M.W. Gill H. Phan L. Chen-Li D. Iacobucci M. Ho R. Majeed A. Impact of COVID-19 pandemic on mental health in the general population: A systematic review J. Affect. Disord. 2020 277 55 64 10.1016/j.jad.2020.08.001 32799105 6. Vlahov D. Galea S. Resnick H. Ahern J. Boscarino J.A. Bucuvalas M. Gold J. Kilpatrick D. Increased use of cigarettes, alcohol, and marijuana among Manhattan, New York, residents after the September 11th terrorist attacks Am. J. Epidemiol. 2002 155 988 996 10.1093/aje/155.11.988 12034577 7. Nordløkken A. Pape H. Wentzel-Larsen T. Heir T. Changes in alcohol consumption after a natural disaster: A study of Norwegian survivors after the 2004 Southeast Asia tsunami BMC Public Health 2013 13 58 10.1186/1471-2458-13-58 23336627 8. de Goeij M.C.M. Suhrcke M. Toffolutti V. van de Mheen D. Schoenmakers T.M. Kunst A.E. How economic crises affect alcohol consumption and alcohol-related health problems: A realist systematic review Soc. Sci. Med. 2015 131 131 146 10.1016/j.socscimed.2015.02.025 25771482 9. Wu P. Liu X. Fang Y. Fan B. Fuller C.J. Guan Z. Yao Z. Kong J. Lu J. Litvak I.J. Alcohol abuse/dependence symptoms among hospital employees exposed to a SARS outbreak Alcohol Alcohol. 2008 43 706 712 10.1093/alcalc/agn073 18790829 10. Ramchandani V.A. Stangl B.L. Blaine S.K. Plawecki M.H. Schwandt M.L. Kwako L.E. Sinha R. Cyders M.A. O’Connor S. Zakhari S. Stress vulnerability and alcohol use and consequences: From human laboratory studies to clinical outcomes Alcohol 2018 72 75 88 10.1016/j.alcohol.2018.06.001 30322482 11. Grazioli V.S. Bagge C.L. Studer J. Bertholet N. Rougemont-Bücking A. Mohler-Kuo M. Daeppen J.-B. Gmel G. Depressive symptoms, alcohol use and coping drinking motives: Examining various pathways to suicide attempts among young men J. Affect. Disord. 2018 232 243 251 10.1016/j.jad.2018.02.028 29499507 12. Bäuerle A. Teufel M. Musche V. Weismüller B. Kohler H. Hetkamp M. Dörrie N. Schweda A. Skoda E.-M. Increased generalized anxiety, depression and distress during the COVID-19 pandemic: A cross-sectional study in Germany J. Public Health 2020 42 672 678 10.1093/pubmed/fdaa106 13. Skoda E.-M. Spura A. de Bock F. Schweda A. Dörrie N. Fink M. Musche V. Weismüller B. Benecke A. Kohler H. Veränderung der psychischen Belastung in der COVID-19-Pandemie in Deutschland: Ängste, individuelles Verhalten und die Relevanz von Information sowie Vertrauen in Behörden Bundesgesundheitsbl 2021 64 322 333 10.1007/s00103-021-03278-0 33481055 14. Brooks S.K. Webster R.K. Smith L.E. Woodland L. Wessely S. Greenberg N. Rubin G.J. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence Lancet 2020 395 912 920 10.1016/S0140-6736(20)30460-8 32112714 15. Manthey J. Kilian C. Schomerus G. Kraus L. Rehm J. Schulte B. Alkoholkonsum in Deutschland und Europa während der SARS-CoV-2 Pandemie SUCHT 2020 66 247 258 10.1024/0939-5911/a000686 16. Cooper M.L. Kuntsche E. Levitt A. Barber L.L. Wolf S. Motivational Models of Substance Use: A Review of Theory and Research on Motives for Using Alcohol, Marijuana, and Tobacco Available online: https://www.researchgate.net/publication/275650480_Motivational_Models_of_Substance_Use_A_Review_of_Theory_and_Research_on_Motives_for_Using_Alcohol_Marijuana_and_Tobacco (accessed on 22 April 2021) 17. Babor T.F. Higgins-Biddle J.C. Saunders J.B. Monteiro M.G. The Alcohol Use Disorders Identification Test—Guidelines for Use in Primary Care Available online: https://apps.who.int/iris/bitstream/handle/10665/67205/WHO_MSD_MSB_01.6a.pdf?sequence=1 (accessed on 7 April 2021) 18. World Health Organization Alcohol and COVID-19: What You Need to Know Available online: https://www.euro.who.int/__data/assets/pdf_file/0010/437608/Alcohol-and-COVID-19-what-you-need-to-know.pdf (accessed on 7 April 2021) 19. Beck A. Heinz A. Alcohol-related aggression-social and neurobiological factors Dtsch. Arztebl. Int. 2013 110 711 715 10.3238/arztebl.2013.0711 24223671 20. Molina P.E. Happel K.I. Zhang P. Kolls J.K. Nelson S. Focus on: Alcohol and the immune system Alcohol Res. Health 2010 33 97 108 23579940 21. World Health Organization Alcohol Does Not Protect against COVID-19; Access Should Be Restricted during Lockdown Available online: https://www.euro.who.int/en/health-topics/disease-prevention/alcohol-use/news/news/2020/04/alcohol-does-not-protect-against-covid-19-access-should-be-restricted-during-lockdown (accessed on 9 June 2021) 22. Koopmann A. Georgiadou E. Reinhard I. Müller A. Lemenager T. Kiefer F. Hillemacher T. The Effects of the Lockdown during the COVID-19 Pandemic on Alcohol and Tobacco Consumption Behavior in Germany Eur. Addict. Res. 2021 27 242 256 10.1159/000515438 33902030 23. Betsch C. Wieler L. Bosnjak M. Ramharter M. Stollorz V. Omer S. Korn L. Sprengholz P. Felgendreff L. Eitze S. Germany COVID-19 Snapshot Monitoring (Cosmo Germany): Monitoring Knowledge, Risk Perceptions, Preventive Behaviours, and Public Trust in the Current Coronavirus Outbreak in Germany Available online: https://www.psycharchives.org/handle/20.500.12034/2386 (accessed on 9 June 2021) 24. Robert Koch-Institute Nationaler Pandemieplan Teil I Robert Koch-Institute Berlin, Germany 2017 10.25646/112 25. Robert Koch-Institute Ergänzung Zum Nationalen Pandemieplan—COVID-19—Neuartige Coronaviruserkrankung Robert Koch-Institute Berlin, Germany 2020 26. Lange C. Manz K. Kuntz B. Alkoholkonsum bei Erwachsenen in Deutschland: Riskante Trinkmengen J. Health Monit. 2017 2 66 73 10.17886/RKI-GBE-2017-031 27. Statistisches Bundesamt Armutsgefährdungsschwelle und Armutsgefährdung (Monetäre Armut) in Deutschland Available online: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Einkommen-Konsum-Lebensbedingungen/Lebensbedingungen-Armutsgefaehrdung/Tabellen/armutsschwelle-gefaehrdung-silc.html (accessed on 11 June 2021) 28. Niehues J. Stockhausen M. Wer Zur Oberschicht Gehört Available online: https://www.iwkoeln.de/presse/pressemitteilungen/beitrag/judith-niehues-maximilian-stockhausen-wer-zur-oberschicht-gehoert.html (accessed on 11 June 2021) 29. Seitz K.H. Bühringer G. Mann K. Grenzwerte für den Konsum alkoholischer Getränke. Empfehlungen des wissenschaftlichen Kuratoriums der DHS Deutsche Hauptstelle für Suchtfragen (Hrsg) Jahrbuch Sucht Pabst Science Publishers Lengerich, Germany 2008 205 209 30. Deutsche Hauptstelle für Suchfragen e.V. Wie Sollten Menschen mit Alkohol Umgehen, um Gesundheitsrisiken zu Verringern? Stellungsnahme der Deutschen Hauptstelle für Suchtfragen e.V. (DHS) 2019 Available online: https://www.dhs.de/fileadmin/user_upload/pdf/dhs-stellungnahmen/DHS_Stellungnahme_Umgang_mit_Alkohol.pdf (accessed on 17 December 2021) 31. World Health Organization Global Recommendations on Physical Activity for Health World Health Organization Geneva, Switzerland 2010 32. Orth B. Merkel C. Die Drogenaffinität Jugendlicher in der Bundesrepublik Deutschland 2019 Rauchen, Alkoholkonsum und Konsum Illegaler Drogen: Aktuelle Verbreitung und Trends BZgA Köln, Germany 2020 Available online: https://www.bzga.de/fileadmin/user_upload/PDF/studien/Drogenaffinitaet_Jugendlicher_2019_Basisbericht.pdf (accessed on 10 May 2021) 33. Clay J.M. Parker M.O. The role of stress-reactivity, stress-recovery and risky decision-making in psychosocial stress-induced alcohol consumption in social drinkers Psychopharmacology 2018 235 3243 3257 10.1007/s00213-018-5027-0 30209533 34. José B.S. van Oers H.A. van de Mheen H.D. Garretsen H.F. Mackenbach J.P. Stressors and alcohol consumption Alcohol Alcohol. 2000 35 307 312 10.1093/alcalc/35.3.307 10869253 35. Bundeszentrale für Gesundheitliche Aufklärung Alkoholgrenzwerte in Europa—Eine langjährige Diskussion: EU-Mitgliedsstaaten tauschen sich über Empfehlungen aus Alkoholspiegel 2015 Available online: https://shop.bzga.de/alkoholspiegel-ausgabe-juni-2015-32250012/ (accessed on 26 April 2021) 36. R: The R Project for Statistical Computing Available online: https://www.r-project.org/ (accessed on 4 June 2021) 37. akzept e.V. Bundesverband für Akzeptierende Drogenarbeit und Humane Drogenpolitik, Deutsche Aidshilfe Alternativer Drogen Suchtbericht 2020 7th ed. Pabst Science Publishers Lengerich, Germany 2020 Available online: https://alternativer-drogenbericht.de/wp-content/uploads/2020/10/akzeptADSB2020web.pdf (accessed on 22 February 2021) 978-3-95853-636-4 38. Meier P.S. Warde A. Holmes J. All drinking is not equal: How a social practice theory lens could enhance public health research on alcohol and other health behaviours Addiction 2018 113 206 213 10.1111/add.13895 28695705 39. Keyes K.M. Hatzenbuehler M.L. Grant B.F. Hasin D.S. Stress and alcohol: Epidemiologic evidence Alcohol Res. 2012 34 391 400 23584105 40. Cooper M.L. Frone M.R. Russell M. Mudar P. Drinking to regulate positive and negative emotions: A motivational model of alcohol use J. Personal. Soc. Psychol. 1995 69 990 1005 10.1037/0022-3514.69.5.990 41. Bendau A. Plag J. Kunas S. Wyka S. Ströhle A. Petzold M.B. Longitudinal changes in anxiety and psychological distress, and associated risk and protective factors during the first three months of the COVID-19 pandemic in Germany Brain Behav. 2021 11 e01964 10.1002/brb3.1964 33230969 42. Mohler-Kuo M. Dzemaili S. Foster S. Werlen L. Walitza S. Stress and Mental Health among Children/Adolescents, Their Parents, and Young Adults during the First COVID-19 Lockdown in Switzerland Int. J. Environ. Res. Public Health 2021 18 4668 10.3390/ijerph18094668 33925743 43. Abrahao K.P. Salinas A.G. Lovinger D.M. Alcohol and the Brain: Neuronal Molecular Targets, Synapses, and Circuits Neuron 2017 96 1223 1238 10.1016/j.neuron.2017.10.032 29268093 44. Bramness J.G. Bye E.K. Moan I.S. Rossow I. Alcohol Use during the COVID-19 Pandemic: Self-Reported Changes and Motives for Change Eur. Addict. Res. 2021 27 257 262 10.1159/000515102 33839730 45. Shanahan M.J. Pathways to Adulthood in Changing Societies: Variability and Mechanisms in Life Course Perspective Annu. Rev. Sociol. 2000 26 667 692 10.1146/annurev.soc.26.1.667 46. Shanahan L. Steinhoff A. Bechtiger L. Murray A.L. Nivette A. Hepp U. Ribeaud D. Eisner M. Emotional distress in young adults during the COVID-19 pandemic: Evidence of risk and resilience from a longitudinal cohort study Psychol. Med. 2020 52 824 833 10.1017/S003329172000241X 32571438 47. Grant B.F. Stinson F.S. Harford T.C. Age at onset of alcohol use and DSM-IV alcohol abuse and dependence: A 12-year follow-up J. Subst. Abus. 2001 13 493 504 10.1016/S0899-3289(01)00096-7 48. Steffen J. Schlichtiger J. Huber B.C. Brunner S. Altered alcohol consumption during COVID-19 pandemic lockdown Nutr. J. 2021 20 1 6 10.1186/s12937-021-00699-0 33388067 49. Alpers S.E. Skogen J.C. Mæland S. Pallesen S. Rabben Å.K. Lunde L.-H. Fadnes L.T. Alcohol Consumption during a Pandemic Lockdown Period and Change in Alcohol Consumption Related to Worries and Pandemic Measures Int. J. Environ. Res. Public Health 2021 18 1220 10.3390/ijerph18031220 33572994 50. Rodriguez L.M. Litt D.M. Stewart S.H. Drinking to cope with the pandemic: The unique associations of COVID-19-related perceived threat and psychological distress to drinking behaviors in American men and women Addict. Behav. 2020 110 106532 10.1016/j.addbeh.2020.106532 32652385 51. Wolitzky-Taylor K. Sewart A. Zinbarg R. Mineka S. Craske M.G. Rumination and worry as putative mediators explaining the association between emotional disorders and alcohol use disorder in a longitudinal study Addict. Behav. 2021 119 106915 10.1016/j.addbeh.2021.106915 33770722 52. Maertl T. de Bock F. Huebl L. Oberhauser C. Coenen M. Jung-Sievers C. COSMO Study Team Physical Activity during COVID-19 in German Adults: Analyses in the COVID-19 Snapshot Monitoring Study (COSMO) Int. J. Environ. Res. Public Health 2021 18 507 10.3390/ijerph18020507 53. Rehm J. Manthey J. Lange S. Badaras R. Zurlyte I. Passmore J. Breda J. Ferreira-Borges C. Štelemėkas M. Alcohol control policy and changes in alcohol-related traffic harm Addiction 2020 115 655 665 10.1111/add.14796 31475395 54. Chisholm D. Moro D. Bertram M. Pretorius C. Gmel G. Shield K. Rehm J. Are the “Best Buys” for Alcohol Control Still Valid? An Update on the Comparative Cost-Effectiveness of Alcohol Control Strategies at the Global Level J. Stud. Alcohol Drugs 2018 79 514 522 10.15288/jsad.2018.79.514 30079865

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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091235 plants-11-01235 Article Genome Insights into Autopolyploid Evolution: A Case Study in Senecio doronicum (Asteraceae) from the Southern Alps https://orcid.org/0000-0002-4317-7004 Fernández Pol 1* https://orcid.org/0000-0002-1547-8627 Hidalgo Oriane 12 https://orcid.org/0000-0002-2929-3818 Juan Ana 3 https://orcid.org/0000-0002-3837-8186 Leitch Ilia J. 2 Leitch Andrew R. 4 Palazzesi Luis 5 https://orcid.org/0000-0001-6219-1285 Pegoraro Luca 6 https://orcid.org/0000-0001-5658-8411 Viruel Juan 2 https://orcid.org/0000-0001-7632-9775 Pellicer Jaume 12* Troitsky Alex Academic Editor 1 Institut Botànic de Barcelona (IBB, CSIC-Ajuntament de Barcelona), Passeig del Migdia s.n., Parc de Montjuïc, 08038 Barcelona, Spain; oriane.hidalgo@ibb.csic.es 2 Royal Botanic Gardens, Kew, Kew Green, Richmond TW9 3AE, UK; i.leitch@kew.org (I.J.L.); j.viruel@kew.org (J.V.) 3 Departamento de Ciencias Ambientales y Recursos Naturales, Universidad de Alicante, 03080 Alicante, Spain; ana.juan@ua.es 4 School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK; a.r.leitch@qmul.ac.uk 5 Museo Argentino de Ciencias Naturales, CONICET, División Paleobotánica, Buenos Aires C1405DJR, Argentina; lpalazzesi@macn.gov.ar 6 Biodiversity and Conservation Biology Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Bimensdorf, Switzerland; luca.pegoraro90@gmail.com * Correspondence: pol.fernandez@csic.es (P.F.); jaume.pellicer@ibb.csic.es (J.P.); Tel.: +34-932890611 (P.F. & J.P.) 02 5 2022 5 2022 11 9 123509 4 2022 29 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Polyploidy is a widespread phenomenon across angiosperms, and one of the main drivers of diversification. Whilst it frequently involves hybridisation, autopolyploidy is also an important feature of plant evolution. Minority cytotypes are frequently overlooked due to their lower frequency in populations, but the development of techniques such as flow cytometry, which enable the rapid screening of cytotype diversity across large numbers of individuals, is now providing a more comprehensive understanding of cytotype diversity within species. Senecio doronicum is a relatively common daisy found throughout European mountain grasslands from subalpine to almost nival elevations. We have carried out a population-level cytotype screening of 500 individuals from Tête Grosse (Alpes-de-Haute-Provence, France), confirming the coexistence of tetraploid (28.2%) and octoploid cytotypes (71.2%), but also uncovering a small number of hexaploid individuals (0.6%). The analysis of repetitive elements from short-read genome-skimming data combined with nuclear (ITS) and whole plastid DNA sequences support an autopolyploid origin of the polyploid S. doronicum individuals and provide molecular evidence regarding the sole contribution of tetraploids in the formation of hexaploid individuals. The evolutionary impact and resilience of the new cytotype have yet to be determined, although the coexistence of different cytotypes may indicate nascent speciation. Asteraceae cytotype genome size repetitive DNA polyploidy transposable elements Winton (Harding) Alpine Plant Conservation & Research ProgrammeSpanish Research CouncilPID2019-108173GA-I00 PID2020-116480GB-I00 MCIN/AEI/10.13039/501100011033 Ramón y CajalRYC-2017-2274 “ESF Investing in your future”Winton (Harding) Alpine Plant Conservation & Research Programme (https://www.winton.com/philanthropy, accessed on 1 April 2022). Spanish Research Council (Refs: PID2019-108173GA-I00 and PID2020-116480GB-I00) funded by MCIN/AEI/ 10.13039/501100011033. J.P. benefited from a Ramón y Cajal grant Ref: RYC-2017-2274 funded by MCIN/AEI/ 10.13039/501100011033 and by “ESF Investing in your future”. ==== Body pmc1. Introduction Polyploidy (or whole-genome multiplication—WGM) refers to the coexistence of more than two copies of the genome in a nucleus. It arises from dysfunctional meiotic or mitotic division that results in the formation of unreduced gametes [1], generating polyploid individuals. Polyploidy is widespread across plants, and it is considered to be a major driver of evolutionary change in angiosperms [2,3]. Through the analysis of chromosome data, it is estimated that about 15% of speciation events in angiosperms involve polyploidy [4], generating similar frequencies of autopolyploid and allopolyploid species [5]. Chromosome counts and flow cytometry can efficiently identify recent polyploidisation events; however, they are limited to detect ancient polyploidisation events whose chromosomal signature might have been eroded over time by diploidising processes [6]. Nevertheless, the advent of new sequencing technologies has resulted in significant progress in our understanding of ancient polyploidy and diploidisation, revealing that WGMs have been more frequent than previously thought. For example, we currently know that the common ancestor of all angiosperms has undergone at least one ancient WGM event, predating their origin and subsequent diversification [7,8]. Since then, multiple episodes of WGM have been estimated along the major plant taxonomic lineages, supporting the role of polyploidy as one of the main engines of plant evolution [9]. Certainly, autopolyploidy results in changes in gene dosage and in levels of gene expression, which can in turn influence tolerance to environmental stress and therefore promote adaptation (e.g., [10,11,12]). Examples of autopolyploid speciation have been reported in several species, such as Tolmiea menziesii (Pursh) Torr. & A.Gray [13], Heuchera micrantha Douglas [14] and Centaurea tentudaica (Rivas Goday) Rivas Goday & Rivas Mart. [15] (see also a review on the topic by Parisod et al. [16] for further examples). One of the consequences of autopolyploidy is the reduction, or loss, of gene flow between ploidy levels, especially from higher to lower ploidy levels, although recurrent polyploidy formation may facilitate gene flow to higher ploidy levels. Nevertheless, the barriers to gene flow generated by polyploidy facilitate divergence within ploidy levels, increasing the potential for speciation. Current understanding of the occurrence of autopolyploid complexes has made unprecedented progress through the application of fast and cost-effective tools such as flow cytometry, which enables reliable screening of hundreds of individuals (e.g., [17,18,19,20]) in a relatively short period of time. Indeed, large-scale analyses have facilitated the discovery of hidden minority cytotypes (e.g., Elymus L. [21]), which might have otherwise remained hidden using solely chromosome-based approaches. In parallel, High-Throughput Sequencing (HTS) technologies have contributed significantly to our understanding of polyploid evolution, polyploid complexes and to polyploid genome dynamics [22,23]. For example, repetitive DNA sequences, including transposable elements (TE) and tandemly arranged elements (e.g., satellite DNA), which form a substantial component of plant genomes [24,25], have been shown to diverge independently in polyploid lineages compared with their diploid progenitors [26,27]. Repeat dynamics is not only of interest to study genome organisation, function and evolution [28,29], but is shown to harbour phylogenetic signal among closely related species, based on their abundance and sequence similarity recovered from HTS analysis [30,31]. The question now arises as to whether intraspecific (and intrapopulation) repeat variation can also be identified, and how is it influenced by mechanisms such as polyploidy. Senecio doronicum L. (Asteraceae) is a relatively common species of herbaceous perennial found throughout European mountain ranges between 1000–2400 m of elevation, exceptionally up to 3000 m [32]. Its habitat spans from alpine meadows to rocky screes (Figure 1). Even though diploids (2n = 20) have been described in the genus, chromosome numbers for the species have been frequently reported as 2n = 40, 80 (i.e., 2n = 4x and 8x). Additionally, higher ploidy levels (e.g., 12x) have also been found anecdotally on gametophytic records according to the Chromosome Counts Database (CCD) [33]. Aiming at evaluating and testing the existence of minority cytotypes in this species, we conducted a cytotype-screening analysis focusing on a population of the southern Alps (Tête Grosse, Alpes-de-Haute-Provence, France, Figure 2A). This analysis was combined with genome skimming approaches to characterise repetitive DNA across multiple individuals and cytotypes. Specifically, our goals were to assess: (i) the impact of polyploidy on the composition of the repetitive fraction of the genome in S. doronicum, (ii) investigate if there is intra- and intercytotype variation in the repetitive DNA content, and (iii) determine to what extent TEs can be used to unravel evolutionary pathways leading to polyploid complexes at the population level, beyond what can be interpreted from traditional nuclear and chloroplast markers. 2. Results 2.1. Cytotype Screening of Senecio doronicum Identifies Three Ploidies in Tête Grosse Our flow-cytometry DNA ploidy screening confirmed the coexistence of tetraploid and octoploid cytotypes in the population (Supplementary Table S1), with the latter being over 2.5x more abundant (i.e., 141 tetraploid individuals versus 356 octoploid individuals), and with very little overlap in the distribution of each cytotype across the population (Figure 2B,C). Additionally, the analyses uncovered three hexaploid individuals growing close together (<5 cm apart), which displayed intermediate DNA ratios (i.e., genome sizes) compared to those of tetraploids and octoploids (Figure 2C). Genome sizes (Mb/1C) estimated for each ploidy level were as follows: 4x (4205.4 ± 19.56), 6x (6357 ± 29.34), 8x (8097.84 ± 48.9). The survey conducted on 36 accessions from outside Tête Grosse, in neighbouring mountain valleys, also reported a high incidence of octoploid individuals (32 out of 36; Supplementary Table S2). 2.2. Repetitive DNA Content in S. doronicum A representative summary of the results of one individual per ploidy level is illustrated in Figure 3 and given in Table 1. The proportion of the genome containing repetitive elements was almost identical for the three cytotypes (i.e., mean: 85.54% (±0.32%)). Around 19–20% of the repetitive genome were unclassified elements. Ty3/Gypsy-like Long Terminal Repeats (LTR) elements dominate the repetitive landscape of each ploidy level, with genomic proportions (GP) of 46.86% in 4x, 42.02% in 8x and 44.06% in 6x, followed by Ty1/Copia LTRs (see Table 1 for detailed composition of the different repeat lineages comprising these LTR repeat superfamilies). Among four lineages of Ty3/Gypsy LTR elements identified, the chromovirus-type Tekay element was by far the most abundant (ranging between 39.08% to 43.85%). The Ty1/Copia superfamily was represented by seven lineages, with SIRE elements being the most abundant (GP: 13.08–13.60%, Table 1). Non-LTR retrotransposons were only represented by Pararetrovirus repeats, occurring in very low abundance (i.e., ≤0.22% GP). DNA transposons included Mutator, haT and Harbinger lineages, with Mutator being the most prevalent in all three cytotype accessions (GP: 0.34–0.49%, Table 1). (N.B. Details on the number of reads analysed for the 12 individuals comprising five tetraploids, three hexaploids and four octoploids and the classification and GP of the highly repetitive elements identified in their genomes are available in Tables S3 and S4 and Figure S1). Despite some variation observed in the GP of DNA repeats between the individuals analysed (Table S4), we did not find significant differences in the composition of the repetitive genomes between the three cytotypes (permanova p = 0.41). Moreover, linear regressions of the number of reads of each repeat type between all cytotype combinations, had an R2 around 0.99, with a high level of statistical significance (Figure 4 and Table 2, see also Figure S2 for regressions focusing on Ty1/Copia and Ty3/Gypsy elements). The variation in TE composition between individuals with the same cytotype were also small; in all cases differences were not significant (paired Wilcoxon tests p = 0.3–0.89) (Table S5), confirming high levels of similarity in the repetitive DNA content regardless of the ploidy level. The same trend was observed when comparing samples from Tête Grosse population with those analysed from outside the population (Table S5). 2.3. Phylogenetic Implications of Cytotype Diversity in S. doronicum To confirm that all recovered cytotypes belong to the same species, and to discard any individuals which showed evidence of hybridisation with closely related species, we conducted a phylogenetic analysis using the internal transcribed spacer (ITS) on a dataset comprising all 4x, 6x and 8x individuals analysed here and the extended sampling of the European clade of Senecio section Crociseris (Rchb.) Boiss. by Calvo et al. [34]. Both Neighbour-Net (NN) and Neighbour-Joining (NJ) trees confirmed that all analysed samples fell within S. doronicum (Figure 5A,B), but were embedded in different subclades, supporting an autopolyploid scenario, whilst indicating that octoploids most likely arose from tetraploids outside Tête Grosse. In contrast, we found that tetraploid and hexaploid individuals were grouped together in the same subclade, mixed with closely related accessions from the Alpes Maritimes. Octoploid individuals were clustered together in a separate subclade with accessions of Jacobaea kirghisica (DC.) E.Wiebe and S. doronicum from other populations of the Alps and Jura. The splitstree NN also supported these relationships between Tête Grosse individuals (i.e., octoploids belonging to a separate clade from the tetraploids and hexaploids, Figure 5B). Additionally, nuclear evidence was complemented by the analysis of conserved regions in a satellite DNA repeat (207 bp) shared between all analysed individuals from Tête Grosse. From the alignment matrix, we found that all tetra- and hexaploid individuals shared exactly the same sequence while octoploids shared five unique SNPs. Plastid DNA reconstruction was carried out on all 12 individuals, generating plastid genome sequences ranging between 151,196 and 151,222 bp. The comparison of plastid sequences between tetraploid and hexaploid individuals from Tête Grosse revealed 0–15 SNPs between the eight individuals analysed, with individual TG370 being the most divergent, although it still grouped with the other seven individuals analysed. In contrast, among octoploid individuals, 14–30 SNPs were found. Further, when comparing the plastid sequences of hexaploids and tetraploids, to octoploids from Tête Grosse, 66–87 variants were found. The plastid sequences of individuals outside Tête Grosse [FR626 and FR627 (4x), FR475 (8x)] were more similar to each other, regardless of ploidy level, than to the individuals of the same cytotype from the Tête Grosse site (Figure 5C). The NN reconstruction also supported the very close relationship between tetraploid and hexaploid individuals from Tête Grosse, while octoploids from this population appeared clustered in a different lineage (Figure 5C). Phylogenetic analyses carried out using TE outputs from RepeatExplorer2 failed to produce any systematic signal at the population level (data not shown), given the high similarity of the repetitive DNA elements between individuals and ploidy levels. 3. Discussion 3.1. Flow Cytometry Uncovers the Existence of Minority Cytotypes in S. doronicum Our flow-cytometry-based cytotype screening not only confirmed the coexistence of tetraploids and octoploids in Tête Grosse, but also uncovered the existence of a novel minority hexaploid cytotype, illustrating the utility of this kind of approach in detecting rare cytotypes. Both auto- and allopolyploid speciation in the genus Senecio has been frequently reported, and the consequences at chromosome and gene levels investigated (see review [35]). Whilst diploid species are reported to occur in the genus, S. doronicum has so far only been reported to exist at higher ploidy levels [33]. To a large extent, and based on our field observations across the southwestern Alps, the results reported here in Tête Grosse mimic the dynamics observed more broadly for the species, where octoploids are more abundant and widely distributed than tetraploids (Figure 2A,B). Indeed, 70% of the individuals surveyed in the Tête Grosse population were octoploids. Each cytotype showed evidence of distinct habitat preference in the population studied (Figure 1), which is illustrated by the little overlap in distribution of tetraploids and octoploids across the site (Figure 2B). Whether tetraploids are, in general, being outcompeted by octoploids is still an open question, and requires future extensive samplings across the Alps. One possible explanation for such a scenario could be that octoploids have more efficient dispersal mechanisms than tetraploids. Increased rates of self-pollination and efficient local dispersal of polyploid Ranunculus adoneus A. Gray have been key for increased persistence and long-term expansion compared to diploids [36]. Despite both cytotypes being reported to reproduce sexually by seeds [37], clonal reproduction cannot be ruled out given the high frequency of individuals that we observed growing together (in clumps). Based on such observations, it is possible that differential rates of sexual versus asexual reproduction between cytotypes may be an important factor contributing to the contrasting evolutionary successes of the cytotypes, which in the long term may contribute to the higher frequency of the octoploids over tetraploids in the genus. To our knowledge, the summit of Tête Grosse is one of the very few sites where both ploidy levels coexist, with other populations consisting mostly of scattered and isolated tetraploid individuals among octoploids (Figure 2A). The higher abundance of tetraploids at Tête Grosse means that opportunities for inter-cytotype hybridisation are more likely. Indeed, we observed that despite each cytotype having relatively different flowering periods, there was some overlap (c. 10 days) in flowering time between them (Pegoraro et al., unpublished), thus a window of opportunity for potential pollen exchange between cytotypes exists. Based on these observations, two main scenarios for the rise of the hexaploid individuals in the population can be considered, including a single cytotype origin or intercytotype crossing (discussed below). The very low number of hexaploid individuals found (3 out of 500 in the population) could represent the early stages of the establishment of hexaploids, but future surveys will be needed to confirm whether this is the case or just an isolated event, and potentially an evolutionary dead end. 3.2. Correlation of TE Amounts among Ploidy Levels Supports the Autopolyploid Evolution in S. doronicum Among the repeat clusters identified using RepeatExplorer2, the majority were classified as Ty3/Gypsy and Ty1/Copia superfamilies, supporting the dominance of LTR retrotransposons across land-plant genomes. An overall dominance of Ty3/Gypsy-like elements has been reported in many plant genomes, including species of Asteraceae [38], but there are exceptions such as in Urospermum Scop. (in a different tribe from Senecio), where Ty1/Copia elements are the major contributors [39]. In S. doronicum, by far the most abundant repeats were Ty3/Gypsy-Tekay elements, with a GP of c. 43%. Indeed, these repeats comprised more than double the GP of the second most abundant repeat lineage which was the Ty1/Copia SIRE elements (GP c. 13%, Table 1). Such analyses highlight the important role of Tekay repeats in shaping the genome of S. doronicum. At the population scale, the repetitive landscape of the individuals analysed was highly conserved, both within cytotypes and between accessions of different ploidy levels (Figure 3, Figure S1, Tables S4 and S5). This was evidenced by the significant correlations observed, either when ‘all repeats’ were analysed (Figure 4, Table 2) or when the Ty3/Gypsy and Ty1/Copia repeat classes were analysed separately (Table 2, Figure S2). Together, these data provide support for an autopolyploid origin of both hexa- and octoploid S. doronicum. One of the many outcomes of autopolyploidy is an increase in the amount of TEs due to the increased number of genome copies within the cell. However, mechanisms driving TE dynamics following WGM and their impact at evolutionary scales are diverse, and vary between auto- and allopolyploids and between species (reviewed in [16,40]). For example, whilst here we observed the above-mentioned significant—and almost linear—correlation between DNA repeats across ploidy levels, this is not necessarily the case in other plant species following autopolyploidy (although studies are limited). For example, a study of 300 autopolyploid Arabidopsis arenosa (L.) Lawalrée showed evidence of differential accumulation of TEs in different individuals, potentially influencing patters of gene expression and providing opportunities for local adaptations [41]. However, no such changes in repeat dynamics associated with cytotype was observed in S. doronicum, perhaps because they are recently formed cytotype variants. Although most studies of how repeat dynamics change in response to WGM come from the study of allopolyploids [40], which have increased complexity due to the associated interspecific hybridisation, the data are highlighting that genome upsizing and downsizing associated with changes in repetitive DNA activity can change over time [41]. These results therefore emphasise the importance of considering how the tempo of polyploidisation will impact the overall composition and organisation of a polyploid genome, rather than the actual polyploidisation process itself [42]. Evidence from population-wide comparative approaches is now needed to more fully evaluate the changes in the composition and organisation of repetitive elements following polyploidy over time, particularly in autopolyploids, which are very limited. 3.3. Unreduced Gamete Formation in Tetraploid Individuals as the Most Likely Origin of the Hexaploid Cytotype As indicated above, two potential yet exclusive evolutionary scenarios can be invoked to explain the origin of hexaploid individuals of S. doronicum in Tête Grosse: Scenario 1-they have arisen from an inter-cytotype cross involving reduced gametes from both the tetraploid and octoploid, and Scenario 2-their origin solely involves tetraploid individuals, arising from a cross between reduced and unreduced gametes (which have been reported in CCD). To distinguish between these two pathways we note the following: (i) The NN splitstree analysis of the whole plastid sequence data (Figure 5C) and the SNP counting from both the satellite and plastid DNA suggest an extremely close relationship between tetraploid and hexaploid individuals; (ii) Bearing in mind that the plastid genome is maternally inherited without meiosis [43], we assume that at least, the maternal contribution to the hexaploids came from the original tetraploid gene pool at Tête Grosse; (iii) The nuclear data (ITS) also support a close relationship between tetraploids and hexaploids based on the reduced number of SNPs from the satellite analysis, and from the phylogenetic inferences depicted in Figure 5A where no ITS variants were found in hexaploids. In summary, and taking all these observations together, we propose that hexaploid individuals on Tete Grôsse most likely arose via Scenario 2. Given the small number of SNPs, together with the low number of hexaploid individuals found in this population (just three out of 500 analysed), the data also suggest that these hexaploid individuals may have arisen very recently. Many of the examples of autopolyploid evolution reported in the literature involve diploid individuals that produce unreduced gametes leading to polyploid cytotypes (see review [16]). In contrast, our analysis suggests an origin arising from the tetraploid level. Minority cytotypes must overcome competition disadvantage and stochastic effects prior to becoming established, a process that can be favoured if recurrent WGM takes place. Certainly, the very low number of hexaploid individuals observed suggest that their long-term survival may be limited unless the production of unreduced gametes is high and/or there is the potential for vegetative growth or reproduction via apomictic pathways [44], although the latter does not seem to be present in the species [37]. In contrast, phylogenetic analyses (Figure 5A–C) indicate that octoploids have arisen from different populations of S. doronicum. Thus, their occurrence in sympatry suggests that long-distance dispersal has brought the populations together. The linear boundary between tetraploids and octoploids at Tête Grosse (Figure 2B) suggests expansion of one cytotype, perhaps to the detriment of the other. 4. Materials and Methods 4.1. Sampling of Senecio doronicum For this study, we selected a population site in Tête Grosse (Alpes-de Haute-Provence, France), at an elevation of about 2000 m, where preliminary analysis of individuals had previously identified the coexistence of both tetraploid and octoploid cytotypes. Sampling of 500 individuals from this site was carried out. Thirty-six specimens from outside the population in neighbouring mountain valleys (Figure 2A) were also collected. Fresh leaf samples of 536 individuals were collected and stored in Ziploc bags at 4 °C until processed for cytotype screening using flow cytometry. Representative herbarium vouchers of each cytotype were prepared and are deposited in Royal Botanic Gardens, Kew (K). 4.2. Cytotype Screening by Flow Cytometry Prior to our cytotype screening, initial analyses on individual plants involving both chromosome counts and estimations of nuclear DNA contents were carried out to enable subsequent DNA estimates to be used directly to infer DNA ploidy levels. The relative fluorescence intensities of nuclei from leaf samples were estimated by propidium iodide flow cytometry following the protocol described in Pellicer et al. [17] using a CyFlow Space flow cytometer (Sysmex-Partec, Norderstedt, Germany), fitted with a 100-mW green solid-state laser (Cobolt Samba, Solna, Sweden). Pools of five individuals were processed together. Each sample was reanalysed separately when cases of mixed-ploidy samples were detected, or in the presence of undetermined fluorescence peaks. We used Petroselinum crispum (Mill.) Fuss. ‘Champion Moss Curled’ [45] as calibration standard (4.5 pg/2C), and the general-purpose isolation buffer by Loureiro et al. [46] supplemented with 3% PVP-40 [47]. Resulting output histograms were analysed using the FlowMax software (v. 2.9, Sysmex-Partec GmbH, Norderstedt, Germany) for statistical calculations. 4.3. Genomic DNA Extraction and Illumina Sequencing Based on the ploidy screening, five tetraploid [(TG370, TG422, TG444–Tête Grosse), (FR626, FR627-Allos)], four octoploid [(TG84, TG137, TG237–Tête Grosse), (FR475-Orciéres)] and three hexaploid individuals (TG337R, TG506, TG507–Tête Grosse) were selected for HTS analyses. Genomic DNA extraction was carried out following the CTAB method with minor modifications [48]. Samples were further processed with NucleoSpin column cleanup following the manufacturer’s protocol. DNA products were run on an agarose 1% gel and quality-control-assessed using a Qubit 3 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). NEBNext® UltraTM II DNA Library Prep Kit for Illumina® (New England Biolabs, Ipswich, MA, USA) with an average insert size of 350–500 bp were prepared and sequenced on a MiSeq v.3 platform (Illumina, San Diego, CA, USA), generating 150 nt paired-end reads (0.45–1 × genome coverage) at Queen Mary University of London Genome Centre. 4.4. Flow-Graph-Based Clustering in RepeatExplorer2 Raw Illumina reads were inspected using FASTQC v.0.11.9, available through the web (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/, accessed on 10 January 2021), to check for low-quality reads or adapter sequences. Trimmomatic v.0.39 [49] was used to trim low-quality bases and reads were reduced to a minimum length of 100 nt (settings: AVGQUAL:20 MINLEN:100 LEADING:20 TRAILING:20 SLIDINGWINDOW:4:20). A map to reference to the complete Senecio vulgaris L. (GenBank Acc.: MH746728.1) plastid sequence was performed using Geneious Prime v.2021.2.2, and matching reads were excluded from further analyses. Paired reads were analysed using the RepeatExplorer2 pipeline [50,51], which performs the classification and quantification of repetitive elements using the REXdb database, which includes all known repeat elements in plants [52]. First, a preliminary analysis with one individual of each ploidy (i.e., 4x, 6x and 8x) was run to evaluate the number of reads that the server could analyse due to memory limitations. Next, a clustering analysis was performed for each of the individuals using the same number of reads, based on the maximum number of accepted reads (1.2 M reads), as advised by the pipeline developers. The annotation of the different clusters from the output directories for each individual was manually revised. Prior to performing comparative analyses, the results of the individual clustering within each ploidy level were compared to evaluate if there were significant differences in TE composition using paired Wilcoxon tests (calculated with wilcox.test function in R [53]). Since no significant differences were found between individuals of the same ploidy (p > 0.05), one individual of each ploidy was randomly chosen for the comparative analysis (i.e., 4x: TG422, 6x: TG507, 8x: TG84). Summary tables and a barplot showing the composition of the repetitive genome in the three individuals was constructed using ggplot2 [54] in R. The comparative analysis in RepeatExplorer2 included proportional amounts of reads of each individual according to their ploidy level (4x: 0.6 M, 6x: 0.9 M and 8x: 1.2 M reads). The annotation of repeats was carried out as described above. Comparison of the proportion of different types of repetitive elements was carried out by plotting pairwise scatterplots comparing the number of shared reads of each DNA repeat class between the different cytotypes as in Pellicer et al. [55], where the slope of the plot represents the genome size ratio between cytotypes. Linear regressions were performed using the lm function in R and differences between genome compositions were checked by performing a permanova test using the adonis function in the vegan package in R. Finally, the three most abundant shared nuclear satellites (identified by RepeatExplorer2) were checked for conserved domains. Cleaned reads were mapped to the three satellites using a map to reference approach in Geneious Prime v.2021.2.2. A single conserved region was identified at a 90% identity threshold for the three cytotypes in the most abundant satellite, and this region was reconstructed using a map-to-reference approach for all individuals in Tête Grosse. A matrix with all 12 individuals was created and aligned with MAFFT v.7.450 [56]. 4.5. Phylogenetic Analyses and Plastid Reconstruction The nuclear region of Senecio specimens belonging to Senecio section Crociseris containing the ITS1, 5.8S and ITS2 sequences in the 45S ribosomal DNA unit from the study by Calvo et al. [34] were downloaded from GenBank. To recover the same region from our individuals, the RepeatExplorer2 outputs annotated as ribosomal DNA clusters were identified, and the largest contig produced was retrieved. We double-checked the validity of these contigs by mapping all reads at a 90% similarity threshold and we did not find variants. These sequences were added to the matrix and aligned using MAFFT v.7.450. The alignment was manually trimmed and inspected for inconsistencies. The resulting nexus file was analysed with Splitstree v.4.17.1 under a Neighbour-Net (NN) approach with a bootstrap of 10,000 replicates [57]. Additionally, a Neighbour Joining (NJ) tree was produced in Geneious Prime v.2021.2.2 assigning Senecio umbrosus Waldst. & Kit. as the outgroup based on the results of the above-mentioned study. For the plastid reconstruction, adapter-free reads were analysed with NOVOPlasty v.4.3.1 [58] using default parameters. Several contigs were retrieved from each individual, which were mapped to a complete plastid sequence of Senecio vulgaris in Geneious Prime v.2021.2.2. The contigs covered 100% of the reference and a consensus for each individual was retrieved. Moreover, the cleaned and paired reads with Trimmomatic v.0.39 [49] were then mapped to the same Senecio vulgaris reference in Geneious Prime v.2021.2.2. From this analysis a consensus1 with a similarity threshold of 90% was extracted. In addition, a de novo assembly with SPAdes v.3.15.2 [59] was performed using the cleaned reads, producing several scaffolds. Those were mapped to consensus1 to check for possible insertions/deletions that could have been missed and a consensus2 was extracted. We aligned the consensus2 of each individual with the consensus obtained with the NOVOplasty method and found no differences. From the complete plastid sequences, a phylogenetic tree was produced using Splitstree v.4.17.1 [60] under a Neighbour-Net approach with a bootstrap of 10,000 replicates. Finally, following the methodology described in Vitales et al. [30], we explored phylogenetic signal in the most abundant TEs of our dataset. For that, we ran a test in which we used the top 25 most abundant repetitive elements from each cytotype. 5. Conclusions This study evidences how population surveys can be helpful to uncover hidden genomic diversity, in this case illustrated by minority cytotypes, which provide fundamental information necessary to interpret the evolutionary implications of polyploidy in plant evolution. In addition, despite the limitations of using TEs as phylogenetic markers at the population level, we find compelling evidence for an autopolyploid origin of hexaploid and octoploid S. doronicum based on TE content. This is further supported through the analysis of nuclear and plastid markers. Future work involving hypervariable markers across populations, such as nuclear microsatellite analysis or RAD sequencing, will be an ideal complement to confirm the results presented in this work. In addition, insights into the activity of the repetitive sequences through analysis of transcriptome and epigenome data will further enhance our understanding of how autopolyploidy impacts genome dynamics and contributes to their long-term survival. Acknowledgments We thank Robyn Powell and Esther Michalková for their help during flow cytometry, and Sonia Vigolo, Michel Rey, Diana Rey and Richard Nichols for their assistance during fieldwork. We also thank Jiří Macas and P. Nóvak for their advice on the analyses of repetitive DNA. We are grateful to the following National Parks and regional authorities are for allowing us to collect plants: Parc National du Mercantour (Collection Permits numbers 490/2017 and 186/2018), Parc National des Ecrins (Collection Permit number 184/2018). Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants11091235/s1, Supplementary Table S1: Cytotype screening of Senecio doronicum individuals from Tête Grosse (Alps du Aute Provence. Internal standard used in flow cytometry: Petroselinum crispum ‘Champion Curler Moss’ (2C = 4.45 pg); Supplementary Table S2: Cytotype screening of Senecio doronicum individuals from outside Tête Grosse (Alps du Aute Provence). Internal standard used in flow cytometry: Petroselinum crispum ‘Champion Curler Moss’ (2C = 4.45 pg); Supplementary Table S3: Details per individual of genome skimming and individual clustering analysis of specimens analysed from Tête Grosse (TG) and outside this population (FR); Supplementary Table S4: Repetitive DNA composition estimated in individuals of Senecio doronicum across cytotypes; Supplementary Table S5: Comparison of genome compositions between individuals of the same cytotype using paired Wilcoxon tests. All samples were from Tete Grosse with the exception of individuals FR626/FR627 and FR475, which were from Allos and Orciéres respectively; Supplementary Figure S1: Genomic composition of all Senecio doronicum accessions across cytotypes (4x, 6x and 8x). Estimates of the genomic abundances (in Mb/1C) of different repeats are indicated and colored by repeat class [GP = Genome proportion (%), LTR = Long Terminal Repeat]; Supplementary Figure S2: Pairwise scatterplot comparisons of the number of reads included in repeat clusters from each cytotype. The slope indicates the genome size ratio between each cytotype. (A–C) Ty1/Copia. (D–F) Ty3/Gypsy. Click here for additional data file. Author Contributions Conceptualization, J.P. and P.F., with the assistance of the remaining authors; fieldwork, J.P., L.P. (Luca Pegoraro), L.P. (Luis Palazzesi), O.H., I.J.L. and A.R.L.; genome size assessments and ploidy screening, O.H., J.P., L.P. (Luca Pegoraro) and L.P. (Luis Palazzesi); data analysis, J.P., P.F., J.V. and A.J.; writing—original draft preparation, J.P. and P.F.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The sequencing datasets presented in this study can be found in online repositories. The names of the repository and bioproject link can be found below: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA802320/ (accessed on 1 April 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Habitat preferences and morphology of tetraploid (A–C) and octoploid (D–F) cytotypes observed in Senecio doronicum from the population of Tête Grosse (Alpes-de-Haute-Provence, France). Figure 2 (A) Geographical distribution of the population of Senecio doronicum from Tête Grosse (). Additional sites sampled in the Southwestern French Alps are also indicated in the map and the cytotypes recovered indicated (4x = , 8x = ). (B) Distribution of individuals in the population of Tête Grosse, colored according to their cytotype. (C) Boxplots depicting the DNA ploidy levels assigned on the basis of relative fluorescence ratios of nuclei. Data Maps from Google Earth: Google Landsat/Copernicus Data SIO, NOAA, U.S. Navy, NGA, GEBCO. GeoBasis-DE/BKG (©2009) Inst. Geogr. Nacional. Figure 3 Genomic composition of Senecio doronicum representative of each cytotype (4x, 6x and 8x). Estimates of the genomic abundances (in Mb/1C) of different repeats are indicated and colored by repeat class [GP = Genome proportion (%), LTR = Long Terminal Repeat]. Figure 4 Pairwise scatterplot comparisons of the number of reads included in repeat clusters from each cytotype. The slope indicates the genome size ratio between each cytotype. (A) 4x vs. 6x. (B) 4x vs. 8x. (C) 8x vs. 6x. Figure 5 Neighbour joining tree (A) and Neighbour net analysis (B) based on ITS sequences of European clade of Senecio sect. Crociseris from Calvo et al. [34], and including 4x, 6x and 8x individuals of Senecio doronicum from the present study. (C) Neighbour net analysis of whole plastid sequences among those same individuals sequenced in our study. Dashed line separates individuals of Tête Grosse from other populations in the area. Capital letters indicate genetic clusters. plants-11-01235-t001_Table 1 Table 1 Repetitive DNA composition estimated in individuals TG422 (4x), TG507 (6x) and TG84 (8x) as illustrative of the overall dynamics reported across cytotypes. Genome Proportion (GP) 4x 6x 8x Repeat Type Lineage [%] [Mb] [%] [Mb] [%] [Mb] Ty1/Copia 14.51 610.40 14.86 944.78 15.28 1237.56 SIRE 13.08 550.07 13.34 848.01 13.60 1101.70 Angela 0.97 40.96 1.11 70.64 0.95 76.83 TAR 0.11 4.64 0.10 6.43 0.14 11.51 Bianca 0.06 2.44 0.06 3.99 0.31 24.73 Ale 0.03 1.24 0.01 0.82 0.03 2.81 Tork 0.06 2.37 0.04 2.48 0.06 4.60 Ikeros 0.21 8.68 0.20 12.42 0.19 15.39 Ty3/Gypsy 46.86 1970.85 44.02 2798.58 42.06 3406.09 Tekay 43.85 1843.88 40.61 2581.82 39.08 3164.91 Athila 1.67 70.09 1.60 101.55 1.56 126.28 CRM 0.39 16.41 0.42 26.46 0.36 29.44 Retand 0.96 40.47 1.40 88.76 1.06 85.47 LTR-unclassified 3.39 142.61 5.49 348.91 6.42 519.65 Other repeats Pararetrovirus 0.01 0.46 0.22 13.93 0.22 17.71 DNA transposons 0.61 25.54 0.71 44.93 0.56 45.12 TIR/Enspm-CACTA 0.00 0.00 0.00 0.00 0.00 0.00 TIR/MuDR-Mutator 0.40 16.71 0.49 31.33 0.34 27.15 TIR/haT 0.18 7.59 0.16 10.00 0.17 13.62 TIR/PIF-Harbinger 0.03 1.24 0.06 3.60 0.05 4.35 Tandem repeats Ribosomal DNA 0.28 11.76 0.40 25.35 0.25 19.97 Satellite 0.37 15.64 0.62 39.16 0.45 36.71 Unclassified repeat clusters (GP ≥ 0.01%) 5.92 249.17 5.64 358.81 5.94 480.84 Small unclassified clusters (GP < 0.01%) 13.49 567.21 13.95 886.71 14.10 1141.67 Total repeats 85.45 3593.65 85.91 5461.17 85.27 6905.31 Single copy 14.55 611.75 14.09 895.83 14.73 1192.53 plants-11-01235-t002_Table 2 Table 2 Statistics for the linear regression analyses carried out between cytotype pairs based on an analysis of the number of reads of Ty1/Copia-like elements, Ty3/Gypsy-like elements, and all repetitive elements (All). (SE: Standard error, Sig.: *** p-value < 0.0001). 8x–6x 6x–4x 8x–4x Slope SE R2 Sig. Slope SE R2 Sig. Slope SE R2 Sig. Ty1/Copia 1.37 0.01 0.996 *** 1.5 0.01 0.999 *** 2.06 0.02 0.996 *** Ty3/Gypsy 1.3 0.01 0.999 *** 1.5 0 0.999 *** 1.95 0.01 0.998 *** All 1.31 0 0.997 *** 1.5 0 0.999 *** 1.97 0.01 0.997 *** Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Brownfield L. Köhler C. Unreduced gamete formation in plants: Mechanisms and prospects J. Exp. Bot. 2011 62 1659 1668 10.1093/jxb/erq371 21109579 2. Soltis P.S. Marchant D.B. Van de Peer Y. Soltis D.E. Polyploidy and genome evolution in plants Curr. Opin. Genet. Dev. 2015 35 119 125 10.1016/j.gde.2015.11.003 26656231 3. Clark J.W. Donoghue P.C.J. Whole-genome duplication and plant macroevolution Trends Plant Sci. 2018 23 933 945 10.1016/j.tplants.2018.07.006 30122372 4. Wood T.E. Takebayashi N. Barker M.S. Mayrose I. Greenspoon P.B. Rieseberg L.H. The frequency of polyploid speciation in vascular plants Proc. Natl. Acad. Sci. USA 2009 106 13875 13879 10.1073/pnas.0811575106 19667210 5. Barker M.S. Arrigo N. Baniaga A.E. Li Z. Levin D.A. On the relative abundance of autopolyploids and allopolyploids New Phytol. 2016 210 391 398 10.1111/nph.13698 26439879 6. Dodsworth S. Chase M.W. Leitch A.R. Is post-polyploidization diploidization the key to the evolutionary success of angiosperms? Bot. J. Linn. Soc. 2016 180 1 5 10.1111/boj.12357 7. Jiao Y. Wickett N.J. Ayyampalayam S. Chanderbali A.S. Landherr L. Ralph P.E. Tomsho L.P. Hu Y. Liang H. Soltis P.S. Ancestral polyploidy in seed plants and angiosperms Nature 2011 473 97 100 10.1038/nature09916 21478875 8. DePamphilis C.W. Palmer J.D. Rounsley S. Sankoff D. Schuster S.C. Ammiraju J.S.S. Barbazuk W.B. Chamala S. Chanderbali A.S. Determann R. The Amborella genome and the evolution of flowering plants Science 2013 342 1241089 10.1126/science.1241089 24357323 9. Leebens-Mack J.H. Barker M.S. Carpenter E.J. Deyholos M.K. Gitzendanner M.A. Graham S.W. Grosse I. Li Z. Melkonian M. Mirarab S. One thousand plant transcriptomes and the phylogenomics of green plants Nature 2019 574 679 685 10.1038/s41586-019-1693-2 31645766 10. Bomblies K. Madlung A. Polyploidy in the Arabidopsis genus Chromosom. Res. 2014 22 117 134 10.1007/s10577-014-9416-x 11. Kolář F. Čertner M. Suda J. Schönswetter P. Husband B.C. Mixed-ploidy species: Progress and opportunities in polyploid research Trends Plant Sci. 2017 22 1041 1055 10.1016/j.tplants.2017.09.011 29054346 12. Baduel P. Bray S. Vallejo-Marin M. Kolář F. Yant L. The “Polyploid Hop”: Shifting challenges and opportunities over the evolutionary lifespan of genome duplications Front. Ecol. Evol. 2018 6 117 10.3389/fevo.2018.00117 13. Soltis D.E. Rieseberg L.H. Autopolyploidy in Tolmiea menziesii (Saxifragaceae): Genetic insights from enzyme electrophoresis Am. J. Bot. 1986 73 310 318 10.1002/j.1537-2197.1986.tb08534.x 14. Ness B. Soltis D. Soltis P. Autopolyploidy in Heuchera micranta (Saxifragaceae) Am. J. Bot. 1989 76 614 626 10.1002/j.1537-2197.1989.tb11354.x 15. Moreyra L.D. Márquez F. Susanna A. Garcia-Jacas N. Vázquez F.M. López-Pujol J. Genesis, evolution, and genetic diversity of the hexaploid, narrow endemic Centaurea tentudaica Diversity 2021 13 72 10.3390/d13020072 16. Parisod C. Holderegger R. Brochmann C. Evolutionary consequences of autopolyploidy New Phytol. 2010 186 5 17 10.1111/j.1469-8137.2009.03142.x 20070540 17. Pellicer J. Clermont S. Houston L. Rich T.C.G. Fay M.F. Cytotype diversity in the Sorbus complex (Rosaceae) in Britain: Sorting out the puzzle Ann. Bot. 2012 110 1185 1193 10.1093/aob/mcs185 22922587 18. Trávníček P. Kubátová B. Čurn V. Rauchová J. Krajníková E. Jersáková J. Suda J. Remarkable coexistence of multiple cytotypes of the Gymnadenia conopsea aggregate (the fragrant orchid): Evidence from flow cytometry Ann. Bot. 2011 107 77 87 10.1093/aob/mcq217 21059612 19. Kiedrzyński M. Zielińska K.M. Jedrzejczyk I. Kiedrzyńska E. Tomczyk P.P. Rewicz A. Rewers M. Indreica A. Bednarska I. Stupar V. Tetraploids expanded beyond the mountain niche of their diploid ancestors in the mixed-ploidy grass Festuca amethystina L. Sci. Rep. 2021 11 18735 10.1038/s41598-021-97767-6 34548532 20. Rojas-Andrés B.M. Padilla-García N. de Pedro M. López-González N. Delgado L. Albach D.C. Castro M. Castro S. Loureiro J. Martínez-Ortega M.M. Environmental differences are correlated with the distribution pattern of cytotypes in Veronica subsection Pentasepalae at a broad scale Ann. Bot. 2020 125 471 484 10.1093/aob/mcz182 31677387 21. Urfusová R. Mahelka V. Krahulec F. Urfus T. Evidence of widespread hybridization among couch grasses (Elymus, Poaceae) J. Syst. Evol. 2021 59 113 124 10.1111/jse.12563 22. McCann J. Jang T.-S. Macas J. Schneeweiss G.M. Matzke N.J. Novák P. Stuessy T.F. Villaseñor J.L. Weiss-Schneeweiss H. Dating the species network: Allopolyploidy and repetitive DNA evolution in american daisies (Melampodium sect. Melampodium, Asteraceae) Syst. Biol. 2018 67 1010 1024 10.1093/sysbio/syy024 29562303 23. Viruel J. Conejero M. Hidalgo O. Pokorny L. Powell R.F. Forest F. Kantar M.B. Soto Gomez M. Graham S.W. Gravendeel B. A target capture-based method to estimate ploidy from herbarium specimens Front. Plant Sci. 2019 10 937 10.3389/fpls.2019.00937 31396248 24. Bennetzen J.L. Wang H. The contributions of transposable elements to the structure, function, and evolution of plant genomes Annu. Rev. Plant Biol. 2014 65 505 530 10.1146/annurev-arplant-050213-035811 24579996 25. Wang D. Zheng Z. Li Y. Hu H. Wang Z. Du X. Zhang S. Zhu M. Dong L. Ren G. Which factors contribute most to genome size variation within angiosperms? Ecol. Evol. 2021 11 2660 2668 10.1002/ece3.7222 33767827 26. Renny-Byfield S. Kovařík A. Chester M. Nichols R.A. Macas J. Novák P. Leitch A.R. Independent, rapid and targeted loss of highly repetitive DNA in natural and synthetic allopolyploids of Nicotiana tabacum PLoS ONE 2012 7 e36963 10.1371/journal.pone.0036963 22606317 27. Weiss-Schneeweiss H. Leitch A.R. McCann J. Jang T.-S. Macas J. Chapter 5—Employing next generation sequencing to explore the repeat landscape of the plant genome BT—Next-Generation Sequencing in Plant Systematics Proceedings of the Next-Generation Sequencing in Plant Systematics Koeltz Botanical Books Hessen, German 2015 1 26 28. Novák P. Guignard M.S. Neumann P. Kelly L.J. Mlinarec J. Koblížková A. Dodsworth S. Kovařík A. Pellicer J. Wang W. Repeat-sequence turnover shifts fundamentally in species with large genomes Nat. Plants 2020 6 1325 1329 10.1038/s41477-020-00785-x 33077876 29. Serrato-Capuchina A. Matute D.R. The role of transposable elements in speciation Genes 2018 9 254 10.3390/genes9050254 30. Vitales D. Garcia S. Dodsworth S. Reconstructing phylogenetic relationships based on repeat sequence similarities Mol. Phylogenet. Evol. 2020 147 106766 10.1016/j.ympev.2020.106766 32119996 31. Dodsworth S. Chase M.W. Kelly L.J. Leitch I.J. Macas J. Novák P. Piednoël M. Weiss-Schneeweiss H. Leitch A.R. Genomic repeat abundances contain phylogenetic signal Syst. Biol. 2015 64 112 126 10.1093/sysbio/syu080 25261464 32. Aeschimann D. Lauber K. Martin D. Theurillat J.-P. Flora Alpina Belin Paris, France 2004 33. Rice A. Glick L. Abadi S. Einhorn M. Kopelman N.M. Salman-Minkov A. Mayzel J. Chay O. Mayrose I. The Chromosome Counts Database (CCDB)—A community resource of plant chromosome numbers New Phytol. 2015 206 19 26 10.1111/nph.13191 25423910 34. Calvo J. Álvarez I. Aedo C. Pelser P.B. A phylogenetic analysis and new delimitation of Senecio sect. Crociseris (Compositae: Senecioneae), with evidence of intergeneric hybridization Taxon 2013 62 127 140 10.1002/tax.621011 35. Walter G.M. Abbott R.J. Brennan A.C. Bridle J.R. Chapman M. Clark J. Filatov D. Nevado B. Ortiz-Barrientos D. Hiscock S.J. Senecio as a model system for integrating studies of genotype, phenotype and fitness New Phytol. 2020 226 326 344 10.1111/nph.16434 31951018 36. Baack E.J. To succeed globally, disperse locally: Effects of local pollen and seed dispersal on tetraploid establishment Heredity 2005 94 538 546 10.1038/sj.hdy.6800656 15770232 37. Pegoraro L. Baker E.C. Aeschimann D. Balant M. Douzet R. Garnatje T. Guignard M.S. Leitch I.J. Leitch A.R. Palazzesi L. The correlation of phylogenetics, elevation and ploidy on the incidence of apomixis in Asteraceae in the European Alps Bot. J. Linn. Soc. 2020 194 410 422 10.1093/botlinnean/boaa058 38. Staton S.E. Burke J.M. Evolutionary transitions in the Asteraceae coincide with marked shifts in transposable element abundance BMC Genom. 2015 16 623 10.1186/s12864-015-1830-8 39. Pellicer J. Balant M. Fernández P. Rodríguez González R. Hidalgo O. Morphological and genome-wide evidence of homoploid hybridisation in Urospermum (Asteraceae) Plants 2022 11 182 10.3390/plants11020182 35050070 40. Vicient C.M. Casacuberta J.M. Impact of transposable elements on polyploid plant genomes Ann. Bot. 2017 120 195 207 10.1093/aob/mcx078 28854566 41. Baduel P. Quadrana L. Hunter B. Bomblies K. Colot V. Relaxed purifying selection in autopolyploids drives transposable element over-accumulation which provides variants for local adaptation Nat. Commun. 2019 10 5818 10.1038/s41467-019-13730-0 31862875 42. Giraud D. Lima O. Huteau V. Coriton O. Boutte J. Kovarik A. Leitch A.R. Leitch I.J. Aïnouche M. Salmon A. Evolutionary dynamics of transposable elements and satellite DNAs in polyploid Spartina species Plant Sci. 2021 302 110671 10.1016/j.plantsci.2020.110671 33288000 43. Arroyo-García R. Lefort F. De Andrés M.T. Ibáñez J. Borrego J. Jouve N. Cabello F. Martínez-Zapater J.M. Chloroplast microsatellite polymorphisms in Vitis species Genome 2002 45 1142 1149 10.1139/g02-087 12502260 44. Hojsgaard D. Hörandl E. The rise of apomixis in natural plant populations Front. Plant Sci. 2019 10 358 10.3389/fpls.2019.00358 31001296 45. Obermayer R. Leitch I.J. HansonN L. Bennett M.D. Nuclear DNA C-values in 30 species double the familial representation in pteridophytes Ann. Bot. 2002 90 209 217 10.1093/aob/mcf167 12197518 46. Loureiro J. Rodriguez E. Doležel J. Santos C. Two new nuclear isolation buffers for plant DNA flow cytometry: A test with 37 species Ann. Bot. 2007 100 875 888 10.1093/aob/mcm152 17684025 47. Pellicer J. Powell R.F. Leitch I.J. The Application of flow cytometry for estimating genome size, ploidy level, endopolyploidy, and reproductive modes in plants BT Molecular Plant Taxonomy: Methods and Protocols Besse P. Springer New York, NY, USA 2021 325 361 978-1-0716-0997-2 48. Doyle J.J. Doyle J.L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue Phytochem. Bull. 1987 19 11 15 49. Bolger A.M. Lohse M. Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data Bioinformatics 2014 30 2114 2120 10.1093/bioinformatics/btu170 24695404 50. Novák P. Neumann P. Pech J. Steinhaisl J. Macas J. RepeatExplorer: A Galaxy-based web server for genome-wide characterization of eukaryotic repetitive elements from next-generation sequence reads Bioinformatics 2013 29 792 793 10.1093/bioinformatics/btt054 23376349 51. Novák P. Neumann P. Macas J. Global analysis of repetitive DNA from unassembled sequence reads using RepeatExplorer2 Nat. Protoc. 2020 15 3745 3776 10.1038/s41596-020-0400-y 33097925 52. Neumann P. Novák P. Hoštáková N. Macas J. Systematic survey of plant LTR-retrotransposons elucidates phylogenetic relationships of their polyprotein domains and provides a reference for element classification Mob. DNA 2019 10 1 10.1186/s13100-018-0144-1 30622655 53. R Core Team R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing Vienna, Austria 2019 54. Wickham H. ggplot2: Elegant Graphics for Data Analysis 2nd ed. Springer New York, NY, USA 2016 978-3-319-24277-4 55. Pellicer J. Fernández P. Fay M.F. Michálková E. Leitch I.J. Genome size doubling arises from the differential repetitive DNA dynamics in the genus Heloniopsis (Melanthiaceae) Front. Genet. 2021 12 1685 10.3389/fgene.2021.726211 56. Katoh K. Standley D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability Mol. Biol. Evol. 2013 30 772 780 10.1093/molbev/mst010 23329690 57. Bryant D. Moulton V. Neighbor-Net: An agglomerative method for the construction of phylogenetic networks Mol. Biol. Evol. 2004 21 255 265 10.1093/molbev/msh018 14660700 58. Dierckxsens N. Mardulyn P. Smits G. NOVOPlasty: De novo assembly of organelle genomes from whole genome data Nucleic Acids Res. 2017 45 e18 10.1093/nar/gkw955 28204566 59. Prjibelski A. Antipov D. Meleshko D. Lapidus A. Korobeynikov A. Using SPAdes De Novo Assembler Curr. Protoc. Bioinforma. 2020 70 e102 10.1002/cpbi.102 32559359 60. Huson D.H. Bryant D. Application of phylogenetic networks in evolutionary studies Mol. Biol. Evol. 2006 23 254 267 10.1093/molbev/msj030 16221896

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==== Front Nanomaterials (Basel) Nanomaterials (Basel) nanomaterials Nanomaterials 2079-4991 MDPI 10.3390/nano12091529 nanomaterials-12-01529 Article Responsivity of Fractal Nanoparticle Assemblies to Multiple Stimuli: Structural Insights on the Modulation of the Optical Properties https://orcid.org/0000-0001-7005-3309 Capocefalo Angela 12* https://orcid.org/0000-0002-8779-7897 Bizien Thomas 3 https://orcid.org/0000-0003-4793-5359 Sennato Simona 1 https://orcid.org/0000-0002-4049-8187 Ghofraniha Neda 1 https://orcid.org/0000-0001-6373-5176 Bordi Federico 12 https://orcid.org/0000-0002-3284-5054 Brasili Francesco 12* Guerrero-Martínez Andrés Academic Editor 1 Institute for Complex Systems (ISC-CNR), National Research Council, 00185 Rome, Italy; simona.sennato@roma1.infn.it (S.S.); neda.ghofraniha@roma1.infn.it (N.G.); federico.bordi@roma1.infn.it (F.B.) 2 Department of Physics, Sapienza University of Rome, 00185 Rome, Italy 3 Synchrotron SOLEIL, L’Orme des Merisiers, Saint-Aubin, BP 48, CEDEX, 91192 Gif-sur-Yvette, France; thomas.bizien@synchrotron-soleil.fr * Correspondence: angela.capocefalo@uniroma1.it (A.C.); francesco.brasili@gmail.com (F.B.) 01 5 2022 5 2022 12 9 152930 3 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Multi-responsive nanomaterials based on the self-limited assembly of plasmonic nanoparticles are of great interest due to their widespread employment in sensing applications. We present a thorough investigation of a hybrid nanomaterial based on the protein-mediated aggregation of gold nanoparticles at varying protein concentration, pH and temperature. By combining Small Angle X-ray Scattering with extinction spectroscopy, we are able to frame the morphological features of the formed fractal aggregates in a theoretical model based on patchy interactions. Based on this, we established the main factors that determine the assembly process and their strong correlation with the optical properties of the assemblies. Moreover, the calibration curves that we obtained for each parameter investigated based on the extinction spectra point out to the notable flexibility of this nanomaterial, enabling the selection of different working ranges with high sensitivity. Our study opens for the rational tuning of the morphology and the optical properties of plasmonic assemblies to design colorimetric sensors with improved performances. gold nanoparticles proteins patchy colloids self-assembly nanosensor hybrid nanomaterials biosensing Small Angle X-ray Scattering (SAXS) plasmonic resonance EU Framework Programme for Research and Innovation730872 Sapienza University of Romen.AR11715C821B8F01 The research leading to SAXS results has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Programme for Research and Innovation Horizon 2020. A.C. acknowledges Sapienza University of Rome for the grant “Progetti per Avvio alla Ricerca”, prot. n.AR11715C821B8F01. ==== Body pmc1. Introduction The controlled assembly of gold nanoparticles (AuNPs) has proved to be a promising route for the fabrication of novel bottom-up plasmonic nanomaterials with selectable features to be employed in diverse applications, ranging from electronics to medicine [1]. Particularly attractive are the optical properties of these systems, that can be finely tuned in a broad spectral range by acting on the clustering process. These properties stem from the excitation of localized surface plasmons, that results in the confinement of enhanced electromagnetic fields at the particle surface and leads to strong extinction at the resonant wavelength (Localised Surface Plasmon Resonance, LSPR) [2]. The LSPR of AuNPs-based systems can be tailored by the morphology of the assemblies, by the number of constituent AuNPs and by the distribution of the interparticle distances within the aggregates [3,4]. In fact, from dimers to more complex nanoarchitectures, when AuNPs are in close proximity, the single localized plasmonic modes hybridize into new coupling bands shifted at higher wavelengths, visually resulting in a color change of the colloidal dispersion [5]. The spectral weights of these coupled modes is determined by the structure and size of the clusters. Owing to these flexible optical properties, AuNPs assemblies are increasingly employed as versatile platforms for advanced applications in optical and chemical sensing [6], especially for colorimetric assays [7] and spectroscopic detection [8,9]. On top of that, a further peculiarity of gold is its chemical stability, that results in low toxicity of AuNPs thus enabling their application in biosensing [10] and nanomedicine [11,12]. In this context, the toxic side effects of AuNPs related to concentration, size and molecular capping have been extensively evaluated [13]. It has been reported that the toxicity of citrate-capped AuNPs is strongly reduced if their diameter exceeds 40 nm [14,15]; therefore, in the present study, we focused on citrate-capped AuNPs with diameter of 60 nm, that show a high biocompatibility [16]. The main strategy for tuning the optical properties of plasmonic aggregates through the clustering process is to decorate the surface of the AuNPs with stimuli-responsive moieties [17]. In this way, the self-assembly can be controlled relying on changes of the interaction potential between the colloidal particles induced by environmental parameters such as pH, ionic strength and temperature. Among the available stimuli-responsive compounds, proteins and DNA, that are characterized by programmable inter-molecular interactions and responsiveness to external stimuli, allow for realizing self-assembled hybrid systems with the desired features [18,19,20]. In addition, biological macromolecules have the huge advantage of being intrinsically biocompatible and biodegradable, allowing their use even for in vivo biosensing [21,22,23]. Protein- and DNA- mediated aggregation of AuNPs has been successfully employed in the realization of colorimetric assays for the recognition of biomolecular processes such as DNA hybridisation [24] and detection of target molecules such as exosomal proteins [4] and heparin [25]. To take advantage of this potential, a detailed analysis aimed at establishing the exact correspondence between the optical response and the structural modification of the plasmonic aggregates is mandatory. Here, we propose an in-depth investigation of the structural and optical properties of a self-assembled hybrid plasmonic material by combining Small Angle X-ray Scattering (SAXS) and extinction spectroscopy. We adopt an electrostatic approach for the realization of protein-decorated colloidal particles by employing anionic AuNPs. In a previous study, we demonstrated that the resulting nanomaterial shows effective antibacterial activity [19], however, as a further advantage, the responsivity to external stimuli provided by the protein makes this system promising to be employed as nanosensor. In this work, we provide a detailed analysis of the protein-mediated aggregation process by relating the morphology of the complexes—in terms of their fractal dimension and interparticle distance—with their optical response at varying protein concentration, pH and temperature. Based on extinction spectra, we build a calibration curve for each one of these parameters, in order to gain the full control on these external stimuli which is pivotal for the realization of effective sensors. 2. Materials and Methods 2.1. Materials Citrate-stabilised AuNPs with nominal diameter of 60 nm and number density of 2.6×1010 mL−1 were provided by Ted Pella (Redding, CA, USA). Chicken egg white lysozyme powder (MW 14.4 kDa, purity > 90%) was provided by Sigma-Aldrich. Sodium citrate buffer at pH 6.5 was provided by Merck Millipore (Burlington, MA, USA). All the chemicals employed in sample preparation were purchased from Sigma-Aldrich (St. Louis, MO, USA) and used without further purification. 2.2. Sample Preparation A stock solution was prepared by dissolving the lysozyme powder in 20 mM sodium citrate buffer to keep the pH at 6.5. Protein solutions at different concentrations were prepared by diluting the initial protein solution in a proper volume of the same buffer. Lysozyme-AuNPs samples at different protein-AuNP number ratios ξ were therefore obtained by adding to each protein solution an equal volume of the AuNPs stock solution. In the analysed samples lysozyme concentration ranges between 17 nM and 215 nM, to obtain ξ values between 800 and 10,000. After mixing the two components, we set an incubation time to left AuNPs clusters grow up to their equilibrium size. The analysis aimed at identify the growth times of samples prepared at different ξ are reported in Section S1 of the Supplementary Materials. Measurements as a function of pH were performed by adjusting the pH of the solutions of lysozyme-AuNPs samples by adding aliquots of hydrochloric acid (HCl) or sodium hydroxide (NaOH) for obtaining solutions at acidic and basic pH, respectively. An equilibration time of at least 5 min was scheduled before measuring the samples. 2.3. Dynamic Light Scattering The size of AuNPs clusters was characterized in terms of their hydrodynamic diameter 2RH by Dynamic Light Scattering (DLS) measurements. Experiments were performed using a NanoZetaSizer apparatus (Malvern Instruments LTD, Worcester, UK), equipped with a 5 mW He-Ne laser emitting at 633 nm. The scattered light was collected at an angle of 173°. Decay times were extrapolated from the acquired intensity autocorrelation functions using the CONTIN algorithm. Decay times were used to determine the distribution of the diffusion coefficients D, which are converted in the intensity-weighted distributions of the hydrodynamic diameter using the Stokes–Einstein relationship RH=kBT/6πηD, where kBT is the thermal energy and η the water viscosity. The collected data were analyzed using the Zetasizer software provided with the instrument. The reported results are obtained on measurements performed after the incubation time, of at least 5 min, scheduled for samples preparation or pH adjustment. The minimum time needed to reach the equilibrium size of clusters, which depends on the lysozyme-AuNPs molar ratio, was evaluated as described in Section S1 of Supplementary Materials. For experiments at different temperatures, after every temperature change the samples were kept thermalizing for 5 min before acquisition. In any case, we considered samples as stabilized when we could perform at least three consecutive measurements that yielded comparable hydrodynamic diameter distributions. The reported values and the associated errors are obtained by averaging the center values of these distributions and by the corresponding standard deviation. 2.4. Extinction Spectroscopy Extinction spectra were acquired in the range of wavelengths from 200 to 1100 nm using a double ray spectrophotometer V-570 (Jasco, Tokyo, Japan), equipped with a Peltier thermostatted holder EHC-505 (Jasco). The spectral resolution of the instrument is of 0.1 nm in the UV–Visible and 0.5 nm in the near-infrared. Experiments at different protein concentrations and pH were performed at 25 °C, after an equilibration time, of at least 5 min and evaluated for each lysozyme-AuNPs molar ratio, from samples preparation or pH adjustment. For experiments at different temperatures, after every temperature change the samples were kept thermalizing for 5 min before acquisition. In any case, we considered samples as stabilized when we could perform at least three consecutive measurements that yielded the same spectrum. The spectra here reported are normalized to the extinction at 400 nm, where the absorption coefficient is proportional to the molar concentration of Au(0) in the sample [26]. 2.5. Scanning Electron Microscopy SEM images were acquired using an Auriga 405 microscope (Zeiss, Jena, Germany), with an extracting voltage of 15 kV and 350× magnification. For sample deposition, silicon substrates were functionalized by incubating a 3% ethanol solution of (3-Aminopropyl)triethoxysilane (APTES) for 3 h. Subsequently, 50 µL of the sample solution was incubated for 5 min on the substrate and then removed by gently rinsing with MilliQ water. The samples were finally dried under gentle nitrogen flow. 2.6. Small Angle X-ray Scattering The structure of the AuNPs clusters in solution was investigated by Small Angle X-ray Scattering (SAXS). Experiments were performed at Synchrotron SOLEIL (Saint Aubin, France), SWING beamline. For measurements, samples were filled in capillaries (1.5 mm diameter) and placed at the sample-to-detector distance of 6.5 m. The exposure time for acquisitions was set to 1 s and 30 scattering patterns were acquired for each sample. Scattering patterns were recorded using a two-dimensional EigerX 4-M detector (Dectris, Baden, Switzerland) at 12 keV, allowing measurements in the range of q-vector—defined as q=(4π/λ)sinθ, where 2θ is the scattering angle—from 0.001 to 0.18 Å−1. For intensity background subtraction, scattering patterns of an empty capillary and of a capillary filled with Milli-Q water were recorded. Experiments at different protein concentrations and pH were performed at 25 °C, after an equilibration time of about 20 min from samples preparation or pH adjustment. For measurements as a function of temperature, a Huber Ministat 125 thermostat was employed and experiments were conducted at selected temperatures from 25 °C to 80 °C. For each temperature, a thermalization time of 5 min was scheduled before acquisition. The processing and averaging of the scattering patterns were performed by the software Foxtrot (SOLEIL software group and SWING beamline). When averaging, any scattering curve not perfectly superimposed with the overall set acquired, due to possible residual equilibration or other experimental perturbations, was discarded. For a collection of particles, the scattered intensity I(q) can be expressed in terms of the form factor P(q) of single particles and of the structure factor S(q) of the system: (1) I(q)=nv2Δρ2P(q)S(q), where n and v are the number density and the volume of the scattering particles, and Δρ is the contrast in electron density between particles and solvent. Here, P(q) describes the ensemble averaged shape of scattering objects in solution, whereas S(q) accounts for the interference introduced by interparticle correlations. For a dilute system of non-interacting scatterers, S(q)=1 [27]. In our experiments, the form factor is directly measured on the stock solution of AuNPs. To derive the radius R0 of AuNPs, the obtained curve was fitted to a spherical form factor model [27], assuming a log-normal particle size distribution. To derive the structure factor of AuNPs clusters, we divided the scattered intensity measured on each sample by the form factor P(q). The obtained S(q) curves were fitted to a sticky hard spheres model [28], defined by a Percus–Yevick approximation with an attractive square well potential [29,30], to extrapolate the effective radius R of the interacting colloids. Data analysis was performed by the software SasView, version 5.04 [31]. 3. Results For clarity of presentation, in this section we report the investigation of the morphological and optical properties of AuNPs clusters obtained by protein-mediated aggregation separately for each parameter investigated: protein concentration, temperature and pH of the solution. 3.1. Aggregates at Different Protein Concentrations We studied the protein-mediated aggregation of AuNPs at varying the number ratio ξ between the two species in the colloidal dispersion at 25 °C and pH 6.5. To this aim, we kept the AuNPs number density fixed at 1.3×1010 mL−1 and varied the lysozyme concentration between 17 and 215 nM, corresponding to ξ values ranging from 800 to 10,000. The characterization of the formed clusters by DLS, extinction spectroscopy and SEM is reported in Figure 1. DLS experiments reported in Figure 1a show the self-limited aggregation of AuNPs into assemblies whose average size varies in dependence on ξ. We also analyzed the temporal evolution of the size distributions over a period of 100 min (Section S1 of Supplementary Materials), assessing the self-limited nature of the aggregation process. At low number ratios (ξ<1100), the value of the hydrodynamic diameter is almost constant around 60 nm, thus indicating that the sparsely protein-decorated AuNPs do not aggregate. Upon increasing the number ratio, as the adsorption of the protein to AuNPs increases, the steep variation in the hydrodynamic diameter trend for ξ≥1100 highlights the formation of AuNPs aggregates, that reach a maximum size of ∼500 nm for the highest number ratio investigated. Extinction spectra of the complexes at varying ξ are reported in Figure 1b. The optical properties showed excellent stability for 1 h after sample preparation, coherently with DLS measurements; afterwards weak sedimentation effects are observed for ξ≥2500 (Section S1 of Supplementary Materials). At the lowest number ratio (ξ=800), the shape of the extinction spectrum of the sample is comparable to that of the AuNPs stock solution, confirming that the aggregates are not yet formed in solution. Starting from ξ=1100, a shoulder at higher wavelengths appears in the extinction spectra, accompanied by a progressive broadening and shift of the LSPR. These spectral modifications are indicative of plasmon coupling. In fact, when AuNPs are in close proximity (few nanometers), their extinction spectrum acquires a new band, red-shifted significantly from that of isolated nanoparticles, whose intensity increases with the number of interacting AuNPs [5]. The position and width of this band depend on the average interparticle distance and on its statisical distribution within clusters [32]. Such spectral modifications are more pronounced with increasing number ratio, with the extinction spectra widened in the near infrared region. This is consistent with the clusters growth highlighted by DLS. At the highest number ratios, extinction spectra do not evolve anymore, as expected for large clusters, in which the extinction is dominated by the contribution of long chains of nanoparticles [33,34]. DLS and extinction spectroscopy experiments evidence the close correspondence between the progressive aggregation of the colloids and their optical properties [19]. To have an experimental parameter that allows us to monitor the aggregation process and the subsequent variations of the morphology of the clusters through the spectral changes, we define the ratio between the extinction intensities at 800 and 536 nm, that weights the contributions to the spectra of interacting and non-interacting plasmon modes. The intensity at 800 nm, that increases when AuNPs assemble and the coupling of plasmonic modes becomes more relevant, is the marker parameter for AuNPs aggregation, while the intensity at 536 nm corresponds to the maximum of the extinction peak of single AuNPs (see the spectrum reported in gray in Figure 1b). The analysis of the time evolution of this parameter is reported in Section S1 of the Supplementary Materials, revealing excellent stability even in the case of the larger clusters when a hint of sedimentation is observed. The obtained curve as a function of the protein concentration is reported in Figure 1c, highlighting the onset of the aggregation at ξ=1100, corresponding to a protein concentration of 24 nM. Representative SEM images of the samples are reported in Figure 1d. We accurately chose and optimized the procedure used for depositing samples onto silicon substrates reported in Section 2.5 in order to minimize possible alterations of the clusters structure during the adhesion to the silicon surface and to avoid undesired aggregation [35]. SEM micrographs show the formation of assemblies where the average number of AuNPs per cluster increases with ξ. Small clusters (ξ=1100 and ξ=1200) appear compact, while larger ones are less regular and some protruding branches appear. Moving from the results provided by DLS and SEM and with the aim of establishing a connection between the structure of AuNPs clusters and the observed modulation of the optical properties, we performed a detailed SAXS analysis of the clusters in solution, as reported in Figure 2. We acquired SAXS curves on samples prepared at the same number ratios considered for extinction spectroscopy (Figure 2a). The shape of the scattered intensity curves in the low-q region (q<5×10−3Å−1) allows us to easily recognize AuNPs aggregation. In fact, the scattering curves of non-aggregated AuNPs show a clear plateau in this region and the overall shape overlaps quite well the typical scattered intensity of non-interacting spheres (Figure 2b). The presence of larger objects in solution, namely AuNPs aggregates, is identified by a steeper negative slope in the same low-q region. In our case, for ξ=800 the amount of protein that adsorbs to AuNPs is not sufficient to perturb the stability of the colloidal dispersion. For ξ=1100, the plateau is no more clearly reached and, starting from ξ=1200, AuNPs aggregation is clearly observed, consistently with DLS and with the appearance of coupled plasmon modes in the extinction spectra. We analyzed SAXS curves focusing on the mass fractal dimension Df of clusters and on the interparticle distance d. The first parameter is commonly used to describe the geometry of complex and disordered structures, characterized by recursive patterns at different length scales [36,37]. It measures the scaling of the mass M with the size of the aggregate and is defined by the expression M∝RDf, where R is any linear measure of the size [36]. In this respect, the fractal dimension is strictly linked to the global topology of plasmonic nanoparticles’ aggregates and therefore it determines their optical properties [38,39,40]. The linear decrease of I(q) in the log-log plot, observed for ξ≥1200 in the q-range from 3×10−3 to 8×10−3 Å−1, is typical of mass fractal objects [36]. We therefore fitted the scattered intensity to a power law decay I(q)∝q−Df in the selected q-range [41] to derive the fractal dimension. The obtained fractal dimension values, plotted as a function of ξ in Figure 2c, are always lower than 2 and slightly decrease with ξ, indicating non-compact clusters that become more branched at increasing the lysozyme concentration and therefore the amount of protein adsorbed to AuNPs. In fact, when deposited on silicon substrates (SEM images of Figure 1d) AuNPs aggregates appear mainly disposed as single layers while superimposed AuNPs can be rarely found, as expected for loose and branched three-dimensional structures. More insights on the short-range interparticle correlations are obtained by analyzing the structure factors S(q) of the samples with ξ≥1200, where the formation of fractal objects is clearly observed. To derive S(q), we divided the scattered intensity curves of samples by the form factor of single AuNPs, measured on the stock solution [30,42]. The resulting curves are reported in Figure 2d. The structure factors were fitted to a sticky hard spheres model [28] to extrapolate the effective radius R of the interacting colloids (Figure 2e). This parameter indicates the distance at which particles start to repel each other and it is assumed to describe the halved average center-to-center distance between nearest-neighbor AuNPs [30]. We then estimated the interparticle distance, i.e., the average distance between the gold surfaces of adjacent particles, by: (2) d=2(R−R0). where R0 is the radius of the bare AuNPs colloids, obtained by fitting the SAXS curves measured on the AuNPs stock solution to a spherical form factor [27] (Figure 2b). The obtained values of interparticle distance are reported as a function of ξ in Figure 2f. The distance between adjacent AuNPs is of few nanometers, consistent with the size of ∼3 nm of folded lysozyme proteins [19], and increases for the highest ξ values, when the largest amount of protein adsorbs to AuNPs and larger, more branched aggregates are formed. Based on the analyses as a function of the protein concentration here reported, we identified the threshold number ratio ξ=1100, at which the aggregation of AuNPs is activated. At this number ratio, ∼50 protein molecules adsorb to each AuNPs [19] and the average distance between them can be estimated to ∼14 nm, by approximating the unoccupied regions of the AuNPs surface around each molecule with equivalent circles. For the following part of our investigation, aimed at studying the influence of pH and temperature on the clusters morphology and optical properties, we selected three number ratios: ξ=800, just before the threshold, ξ=1200, at the very beginning of the aggregation, when small AuNPs clusters are formed, and ξ=2500, corresponding to the formation of larger and branched aggregates that are stable in solution for the whole duration of the experiments. 3.2. Aggregates at Different pH Here, we investigate the structure of the AuNPs clusters obtained by protein-mediated aggregation at varying the pH of the solution. To this aim we changed the pH both towards acid and basic pH values, by selecting for each range the number ratios at which we expect significant variations in the assemblies morphology. At first, we consider ξ=800 and ξ=1200, that at pH 6.5 are the number ratios right before and right after the aggregation threshold (Figure 1a), for which we analyzed the acidic range, down to pH 2.0. The corresponding scattering curves and structure factors, together with the plots of the fractal dimension and interparticle distance as a function of pH are reported in Figure 3. In the case of ξ=800, at pH 6.5 the SAXS curve (Figure 3a) shows the classical plateau in the low-q region, indicating non-interacting AuNPs. Upon lowering the pH, the shape of the scattering curve in the low-q region changes, highlighting the formation of fractal aggregates. The extrapolated fractal dimensions, reported in Figure 3b, rise with pH up to the maximum value Df∼2 at pH 2, suggesting the increasing density of the clusters. The structure factors, reported in Figure 3c, exhibit consistent variations with pH. At pH 6.5, S(q)∼1, while by lowering the pH the peak corresponding to short-range interparticle correlation appears and its maximum progressively shifts towards higher q. The significant decrease of the interparticle distance at lowering pH (Figure 3d) corroborates this observation. In the case of ξ=1200, AuNPs are already organized in small clusters at pH 6.5, as reported in SEM images (Figure 1d). The scattering curves as a function of pH of Figure 3e show an increasing slope in the low-q region of the log-log plot, that becomes particularly pronounced at pH 2. From the trend of the fractal dimension (Figure 3f) it is evident indeed an abrupt increase of Df at the lowest pH. Concerning the structure factor (Figure 3g), also in this case we observe a shift of the peak towards high q values with decreasing pH and a decrease of the interparticle distance (Figure 3h). We also investigate the structure of AuNPs aggregates when pH is changed to basic values, ranging from 6.5 and 10. In this case we select ξ=2500, that corresponds at pH 6.5 to the formation of clusters with average hydrodynamic diameter of ∼ 270 nm. The SAXS data and analysis are reported in Figure 4. The scattering curves (Figure 4a) do not display evident variations of the slope in the low-q region. Consistently, the fractal dimension (Figure 4b) remains quite stable in the overall range of pH, with slightly lower values at pH 9 and 10. The analysis of the structure factors (Figure 4c,d) shows that the average interparticle distance increases with pH, unlike the case of acidic pH. The optical properties of the samples in the different pH analyzed are reported in Figure 5, together with the corresponding plots of the ratio between the extinction intensities at 800 and 536 mm as a function of pH. For ξ = 800 (Figure 5a), the shape of the extinction spectra change from the typical plasmonic profile of single AuNPs, at pH 6.5, to the broader two-bands shape of nanoparticle aggregates, at lower pH. The plasmonic band increasingly spreads towards higher wavelength by lowering pH suggesting the increased weight of coupled plasmons in acidic environment, similarly to what occurs at increasing number ratios (see the plasmonic profiles at ξ=5000 and ξ = 10,000 in Figure 1b). However, along with the increased size of clusters, the higher density of AuNPs (increased fractal dimension, Figure 3b) contributes in this case. In the case of ξ=1200 (Figure 5b), the intensity of the peak of the extinction spectrum corresponding to the interparticle plasmonic modes, at ∼800 nm, increases with decreasing pH. This indicates the enhanced plasmon coupling induced by the closer proximity of AuNPs, consistently with the increasing of the fractal dimension (Figure 3f) and with the reduction of the interparticle distance (Figure 3h). For ξ=2500 (Figure 5c), studied in basic pH conditions, the intensity of the extinction band of the interparticle modes decreases with increasing pH and its maximum shifts towards smaller wavelegths. This behavior is opposite to that observed for ξ=1200. At the same time, the intensity of the peak at ∼536 nm, corresponding to the LSPR of single AuNPs, increases. These spectral changes indicate the reduction of the plasmon coupling between AuNPs composing the assemblies and therefore suggest a possible detachment of some AuNPs from the clusters when pH is increased. The three calibration curves of Figure 5d–f reveal that it is possible to select different working regions, intended as the range of pH where the sensitivity of the extinction ratio is maximum, depending on the number ratio. In the case of ξ=2500, the calibration curve shows a non-monotonic trend in the range of pH between 6.5 and 8.0, outside the working range. This is due to the weak dependence of spectra on pH, making significant other fluctuations in the spectra that could affect the value of the extinction ratio. However, this aspect does not limit the feasibility of pH measurements, since the sample at ξ=2500 would be employed in the pH range between 8.0 and 10.0. 3.3. Aggregates at Different Temperatures In this section, we analyse the effects of temperature on the structure and optical properties of the nanomaterial for the three selected protein-AuNP number ratios. Starting from 25 °C, we increase the temperature of the samples up to 80 °C. In the case of ξ=800, the temperature increase has no effect on the stability of the colloidal dispersion, as reported in Section S2 of the Supplementary Materials. SAXS data and extinction spectra demonstrate indeed that AuNPs do not aggregate for all the temperatures analyzed. In the case of aggregates already formed in the solution, for ξ=1200 and ξ=2500, the SAXS analyses at varying temperature are reported in Figure 6. The low-q range of the scattering curves of the sample with ξ=1200, containing the smallest assemblies, reveals a decrease of the fractal dimension with increasing temperature that is more pronounced starting from from 50 °C onward (Figure 6a,b). The corresponding structure factors (Figure 6c) show a progressive shift of the peak toward high q values, pointing to a decrease of the average distance between AuNPs (Figure 6d). A similar behaviour of the structural and morphological properties is observed in SAXS data for ξ=2500 (Figure 6e–h). Also in this case, the fractal dimension lowers with temperature down to the minimum value Df∼1.75 and the interparticle distance displays a clear reduction at 60 °C. This marked reduction of the fractal dimension is confirmed by the branched and open structure of the assemblies at high temperature, as evidenced by the representative SEM image of Figure 6i, acquired on the sample deposited on a silicon substrate after increasing the temperature to 80 °C. The analysis of the optical properties of samples with ξ=1200 and ξ=2500 as a function of temperature are reported in Figure 7 in terms of extinction spectra and corresponding plots of the ratio between the extinction values at 800 and 356 mm. In both cases, in the extinction spectra the LSPR of single AuNPS (peak at ∼536 nm) slightly decreases at increasing temperature. At the same time, the interparticle plasmonic band, at ∼800 nm, broadens towards higher wavelengths, more markedly for ξ=2500. The redshift and slight widening of this band at ξ=1200 suggests the enhanced coupling between AuNPs, as evidenced by the concomitant reduction of the interparticle distance (Figure 6d). For ξ=2500 instead, the more pronounced broadening might indicate an increased size of the AuNPs clusters promoted by the temperature. 4. Discussion In this work, we performed a detailed structural investigation on a self-assembled plasmonic nanomaterial with the purpose of clarifying the effects of the assembly morphology on its optical properties. We considered three external stimuli—analyte concentration, pH and temperature—of pivotal interest for possible sensing applications. To this aim, we focused on the case-study of the electrostatic, protein-mediated assembly of AuNPs. The peculiar characteristic of our system is the formation of long-lived clusters with finite size. This can occur only in the presence of competing interaction forces that result in a limiting mechanism for the assembly process [43]. In our specific case, the aggregation is triggered by the adsorption of a positively charged protein, lysozyme, to the oppositely charged surface of anionic AuNPs [19]. This gives rise to the formation of colloidal particles with inhomogeneous surface charge, i.e., with surface patches that are oppositely charged with respect to the net charge of the particle. The interaction between such patchy colloidal particles may show a significant attractive component—arising from short-range, local interaction between oppositely charged patches on the approaching particles—even if the net charges on the two particles have the same sign. This results in a complex aggregation phenomenology that leads to the formation of clusters with finite-size, as pointed out by several experimental studies on the self-assembly of charged colloidal particles, when mixed with oppositely charged polymers, macromolecules or nanoparticles in an aqueous solvent [19,44,45,46]. The final size of the formed aggregates for given values of pH, temperature, ionic strength and concentration is controlled by the charge ratio between the adsorbing species and the colloids, and therefore by the amount of adsorbate present in the solution. By increasing the adsorbate content, the progressive reduction of the net charge of the primary colloids induces the formation of growing clusters. Close to the isoelectric point, where the charge of the adsorbed layer neutralises the original charge of the colloids, the aggregates reach their maximum size. For higher adsorbate content, the sign of net charge of the colloids can be reversed, leading to a reentrant condensation that results in the gradual decrease of the cluster size [47]. This phenomenology and the mechanisms that drive the self-limited aggregation can be described by the “charge-patch” interaction potential [47], originally proposed by Velegol and Thwar to describe the interaction between two inhomogeneously charged (patchy) colloidal particles in the Derjaguin approximation, i.e., when their size is larger than the electrostatic screening length of the colloidal suspension [48]. The two main parameters of the model are the average electrostatic surface potential ζ of two identical approaching particles with radius a and the corresponding standard deviation σ, that accounts for the charge inhomogeneity. The expression for the potential combines an attractive contribution, depending on σ, and a repulsive one, depending on ζ. Since the two components have different interaction ranges, they give rise to a potential barrier that two approaching particles must overcome to stick together. The height of the barrier is given, in units of the thermal energy kBT, by: (3) Vmax=πεaσ2ln1−ζ2ζ2+σ22+2ζ2ln1+ζ2ζ2+σ2, where ε is the permittivity of the dispersing medium. Here the term proportional to σ2 is negative and the one proportional to ζ2 is positive; therefore, aggregation is induced when the surface charge inhomogeneity increases or the total absolute charge on the colloids surface diminishes. Moreover, Vmax is proportional to the radius of the approaching particles, indicating that aggregation is more favored when the curvature of the approaching surfaces is higher. This charge-patch interaction model adequately decribes the protein-mediated aggregation of AuNPs exploited in the present work [19]. In fact, in our case, the colloidal particle are represented by AuNPs, whose citrate capping provides a homogeneous negative surface charge. The charge patches are formed when lysozyme, that is positively charged in the overall experimental condition explored, adsorbs to AuNPs. Due to the small portion of the AuNPs surface area covered by each protein molecule (full coverage is obtained with ∼1800 molecules) we could finely tune the charge inhomogeneity by the lysozyme-AuNPs number ratio. Notably, this theoretical model introduces a limiting mechanism in the aggregation process even if accounting only for local interactions. In this respect, charge-patch interactions can not be framed within the two main mechanisms commonly identified to describe self limited aggregation, namely reaction limited aggregation (RLA) and diffusion limited aggregation (DLA) [49,50]. In fact, in RLA the final size of clusters is determined by the balance between attractive and repulsive interactions that depends on the size of the forming aggregates. This is excluded when the Derjaguin approximation holds. In the case of DLA, the limiting factor is the lowered probability for two particles to collide, which decreases when colloids aggregate. This mechanism does not account for reentrant condensation, that instead occurs in our case [19]. The formation of assemblies with increasing size as a function of protein concentration is evident from DLS and SAXS measurements of Figure 1 and Figure 2. Notably, at increasing the protein amount we observed an higher spacing between AuNPs in the cluster, from 3.5 up to 5.3 nm. The values of the interparticle distances are comparable with the size of lysozyme and consistent with a progressive accumulation of proteins on the colloids surface. The fractal dimension of the assemblies falls between 1.85 and 1.87, depending on the number ratio ξ. These values do not lie in the ranges associated to RLA (1.9≤Df≤2.1) and DLA (1.7≤Df≤1.8) models, witnessing the different mechanism that arrests the growth of clusters. The low density of such fractal aggregates can be explained if considering the dependence of the potential barrier between approaching particles on the surface curvature (Equation (3)). When aggregates are growing, the effective radius of curvature involved in the interactions is the local radius of curvature of the cluster. Hence, one approaching AuNPs sticks more likely to a sharp region of the cluster surface, where the barrier is lower, than to a flat one. Proceeding on this line, we analyze the experiments on the cluster morphology at varying pH and temperature in the framework of the charge-patch interactions. For these investigations we selected three protein-AuNPs number ratios: 800, 1200 and 2500. The pH of the solution affects the protonation/deprotonation degree of the chemical groups that confer electrostatic charge to the proteins and to the AuNPs, namely amines and carboxyl groups. Therefore, this parameter directly affects the interaction strength between particles through their surface potential and surface charge inhomogeneity. The surface charge of AuNPs is owed to a capping of citrate molecules that include three carboxyl groups, whose pKa values occur at pH 3.1, 4.7, and 6.4, respectively [51]. This implies that the negative surface charge of AuNPs is gradually shielded with decreasing pH until it is completely neutralized at pH values lower than 3.1. Lysozyme, on the contrary, has one of the highest isoelectric points among proteins, occurring at pH 10.0 [52,53], due to the presence of a large number of positive amino acidic residues containing amino groups. Therefore its overall charge, that remains positive in the full range of pH employed in our experiments, is markedly positive in acidic environment and is almost neutralized in basic solutions [52,53]. On this basis, it is possible to frame the results obtained on the AuNPs clusters morphology at varying the pH of the solution in the charge-patch interaction model. In acidic environment, the surface charge inhomogeneity σ increases (higher charge of the positive patches) and the surface potential ζ of the primary colloids diminishes (lowering of the negative charge of the citrate capping). As a consequence, the lowering of the potential barrier (Equation (3)) enables the onset of the clustering in samples with small amount of protein (ξ=800, Figure 3). Coherently, the interparticle distance progressively lowers, down to 2.9 nm (ξ=1200, Figure 3). It is worth mentioning that lysozyme is a robust protein that retains its globular folding down to pH 3.0 [54]. Therefore, here we exclude a contribution of protein denaturation in the reduced spacing between AuNPs with decreasing pH, that is instead owed to the strengthening of the interaction between nearest-neighbor AuNPs. Moreover, at low pH values the fractal dimension of the clusters increases up to Df≃2.0. The lowering of the potential barrier, increases the probability for AuNPs to stick also to regions of the forming clusters with higher radius of curvature, making them more compact. This is particularly evident at the lowest pH, for which the negative charges on the AuNPs surface are almost completely neutralized. In basic solutions the behavior is opposite. The negative charge of AuNPs is preserved and actually increased, while the net charge of the protein is reduced, leading to a decrease of the inhomogeneity of the surface charge. Therefore, the attractive contribution to the pair interaction potential diminishes and the height of the potential barrier raises. This weakening of the interaction strength is reflected in the augmented interparticle distance due to the higher repulsion between colloids that could eventually lead to the detachment of some AuNPs from the clusters, but is not sufficient to induce the complete disaggregation. The corresponding fractal dimension diminishes significantly at pH 9 and 10, indicating loosen structures. All the discussed structural modification of the assemblies induced by pH variations are reflected by their optical properties (Figure 5). The aggregation of AuNPs at acidic pH leads to a redshift and broadening of the band at ∼800 nm, more pronounced for ξ=800, indicating the presence of a higher number of coupled plasmons as a consequence of the formation of larger and denser aggregates promoted by the drop of the energy potential barrier. This implies the superposition of several interparticle plasmonic modes corresponding to different coupling strengths between plasmons [33]. In the case of ξ=1200, the increased intensity of the band at ∼800 nm, corresponding to coupled plasmons, is not accompanied by a marked widening beyond 900 nm. This implies that the size of the assemblies does not increase significantly, and the observed modification in the plasmon coupling is mainly due to the reduced interparticle distance and increased fractal dimension. On the contrary, in basic environment we observe a re-entrant behaviour of the plasmon coupling represented by the blueshift of the band at high wavelengths, due to the weakened interactions between colloids. The role of temperature mainly consists in enhancing the diffusivity of the single AuNPs and of the clusters in the dispersion; therefore, the fraction of particles that have sufficient energy to overcome the potential barrier increases [55,56]. In fact, SAXS and SEM experiments performed on the assemblies point out that AuNPs remain aggregated (Figure 6) and reveal the presence of assemblies with an average size that is larger with respect to that of the original clusters formed at 25 °C. Moreover, by increasing temperature, the increase of the height of the potential barrier determines the opening and loosening of the aggregates structure, as witnessed by both SEM (Figure 6i) and by the marked reduction of the fractal dimension down to 1.76 in the case of ξ=2500. The observed decrease of the interparticle distance with increasing temperatures might appear to be contradictory in this framework. Nevertheless, an important aspect that must be taken into account is the effect of temperature on the protein structure. In fact, the protein unfolding, occurring starting above 50 °C [57], determines the reduction of the lysozyme thickness that results in a reduced interparticle spacing. Furthermore, the onset of other types of interactions between the colloids following protein denaturation—such as hydrophobic or covalent interactions as a result of the exposure of hydrophobic residues to the solvent or the rupture of disulfide bridges [15]—could contribute to the decreased interparticle distance. Even in this case the optical features of the assemblies strictly follow the colloidal aggregation dynamics. The enhancement of the plasmon coupling due to the lowered distance between the AuNPs and the increase of the average cluster dimension are highlighted by the redshift and broadening of the extinction band at 800 nm, particularly evident for ξ=2500 (Figure 7). A scheme of the properties of the fractal assemblies as function of the different experimental parameters analyzed in this work is reported in Figure 8. In summary, at fixed temperature, if the attractive component of the potential (σ) is increased (acidic pH), aggregation is prompted, AuNPs can stick also to regions with high radius of curvature (resulting in increased fractal dimension), and the interparticle distance is lowered. Instead, at fixed interaction potential, when temperature is increased the aggregate results more banched due to the higher energy of interacting particles that stick immediately to the outer AuNPs of the clusters and do not fill the inner voids. These considerations about the influence of the external parameters on the fractal dimension of aggregates enable to interpret the near-field microscopy results previously reported on the aggregation of soft colloids mediated by charge-patch interactions [19,58,59,60]. The detailed analysis of the response to environmental stimuli proposed in the present work leads the way to develop plasmonic sensors based on the protein-mediated colloidal aggregation of AuNPs. To this aim, we derived from the extinction spectra different calibration curves for protein concentration (Figure 1c), pH (Figure 5d–f) and temperature (Figure 7c,d) by defining an experimental parameter, that is the ratio between the contribution of coupled plasmons at 800 nm and that of the single particle LSPR at 536 nm. In the case of protein concentration, we observe a strong sensitivity at extremely low amount of protein, between 17.2 and 25.8 nM. The potentiality of our approach becomes particularly evident when looking at the calibration curves as a function of pH and temperature. We can evaluate the sensitivity of the sensor from the steepness of the calibration curve as a function of the measured parameter. Given the different behavior of the assemblies depending on their initial morphology, it is possible to obtain various sensors with different dynamic range of sensitivity for the quantity of interest only by changing the number ratio ξ between protein and AuNPs. In the case of pH, we have maximum sensitivity in the pH range between 4 and 6.5 for ξ=800, between 2 and 6.5 for ξ=1200 and between 8 and 10 for ξ=2500. In the case of temperature, we found maximum sensitivities in the ranges 25 ÷ 60 °C and 25 ÷ 50 °C for ξ=1200 and ξ=2500, respectively. Notably, both pH and temperature ranges includes physiological conditions, important for sensing applications in the biomedical field. These findings highlight the flexibility of our system that allow to design sensing devices selecting “a priori” the working point more suited for specific applications. 5. Conclusions The aggregation of plasmonic nanoparticles is a widely exploited phenomenon in the development of novel and highly performing sensing devices. In particular, the realization of colorimetric sensors relying on the controlled aggregation of plasmonic nanoparticles has been employed in the detection of various analytes such as viruses [61], hormones [62], food contaminants [63], opioids [64] as well as for the determination of variations in environmental parameters as temperature [65]. In this work, we focused on the effects on the optical properties of the plasmonic aggregates structure rearrangement upon variation of external parameters such as analyte concentration, pH and temperature. Compared to the other systems, the peculiarity of the proposed nanosensor lies in its high versatility. In fact, the same sensing platform can be exploited for measuring three different parameters. Moreover, by acting on the protein-AuNPs number ratio, and thus on the assembly of the original system, it is possible to move the working point and sensitivity of the sensor in different regions of interest. In addition to these assets, our approach can be transferred to other biologically relevant macromolecules with responsiveness in different ranges of pH and temperature, leading to a considerable widening of the possible applications. In more detail, we analyzed the morphology of clusters in terms of fractal dimension and interparticle distance and its dependence on the external stimuli by framing the experimental results in the charge-patch interaction theoretical model. We then interpreted the optical properties of the system on the basis of the studied morphological modifications. Experiments allowed us to build calibration curves as a function of the three parameters examined. The system demonstrated to be promising and highly flexible, allowing for selecting different working ranges, depending on the application of interest. Our results represent an important step towards the rational design of plasmonic sensors based on the self-assembly of nanoparticles. Acknowledgments Authors acknowledge SOLEIL for providing synchrotron radiation facilities under proposal n. 20180833 at the SWING beamline. Authors acknowledge the Physics Department of Sapienza University of Rome for providing access to the Nanoscience & Nanotechnology Laboratories (SNN-Lab) of the Research Center on Nanotechnology Applied to Engineering of Sapienza University (CNIS) for SEM measurements and F. Mura for the technical support in SEM imaging. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/nano12091529/s1, Figure S1: Study of the time evolution and stability of the plasmonic aggregates, Figure S2: Analysis of the AuNPs clusters as a function of temperature for the number ratio ξ=800. Click here for additional data file. Author Contributions Conceptualization, A.C. and F.B. (Francesco Brasili); formal analysis, A.C. and F.B. (Francesco Brasili); investigation, A.C., T.B. and F.B. (Francesco Brasili); resources, A.C., T.B. and F.B. (Federico Bordi); data curation, A.C., T.B. and F.B. (Francesco Brasili); writing—original draft preparation, A.C. and F.B. (Francesco Brasili); writing—review and editing, T.B., S.S., N.G. and F.B. (Federico Bordi); visualization, A.C.; supervision, S.S., N.G. and F.B. (Federico Bordi); project administration, A.C. and F.B. (Francesco Brasili); funding acquisition, A.C. and F.B. (Francesco Brasili) All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available from the corresponding authors upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Figure 1 Characterization of AuNPs clusters obtained for different protein concentrations (the lysozyme-AuNPs number ratio ξ is represented by the colorbar), performed at 25 °C and pH 6.5: morphology and optical properties. (a) hydrodynamic diameter 2RH, values and errors are the mean and the standard deviation of at least 3 measurements; (b) extinction spectra, the spectrum of bare AuNPs is shown by dashed gray line for comparison; (c) calibration curve obtained for protein concentration: the experimental parameter employed for quantifying the aggregation of AuNPs, namely the ratio between the extinction values measured at 800 and 536 nm, is reported as a function of protein concentration. The vertical dashed lines in panels a and c indicate the onset of the aggregation. (d) Representative SEM images of clusters for ξ=1100, ξ=1200, ξ=2500 and ξ = 10,000. Figure 2 SAXS analysis of the AuNPs clusters morphology as a function of the protein concentration (the lysozyme-AuNPs number ratio ξ is represented by the colorbar), performed at 25 °C and pH 6.5: (a) SAXS curves (circles, the curve in gray is acquired on the AuNPs stock solution) and power-law decay fitting curves (black lines, only for curves at ξ≥1200 that show a clear power-low decay in the q-range from 0.002 to 0.0072 Å−1); (b) fit of the SAXS curve of the AuNPs stock solution (gray circles) to a spherical form factor (blue line); (c) fractal dimension as a function of ξ; (d) structure factors at varying ξ; (e) representative fit of a structure factor S(q) (gray circles, sample at ξ = 10,000) to a sticky hard spheres model (blue line); (f) interparticle distance as a function of ξ. SAXS curves and structure factors are shifted vertically for clarity. Figure 3 SAXS analysis of the AuNPs clusters morphology as a function of pH in acidic conditions (pH between 2 and 6.5), performed at 25 °C for two different lysozyme-AuNPs number ratios, ξ=800 and ξ=1200. (a,e) SAXS curves (circles) and power-law decay fitting curves (black lines); (b,f) fractal dimension as a function of pH; (c,g) structure factors; (d,h) interparticle distance as a function of pH. SAXS curves and structure factors are shifted vertically for clarity. Figure 4 SAXS analysis of the AuNPs clusters morphology as a function of pH in basic conditions (pH between 6.5 and 10), performed at 25 °C for ξ=2500. (a) SAXS curves (circles) and power-law decay fitting curves (black lines); (b) fractal dimension as a function of pH; (c) structure factors; (d) interparticle distance as a function of pH. SAXS curves and structure factors are shifted vertically for clarity. Figure 5 Optical properties of the AuNPs clusters at varying the pH of the solution for the three lysozyme-AuNPs number ratios analyzed, ξ=800, ξ=1200 and ξ=2500. (a–c) Extinction spectra at varying pH; (d–f) calibration curves as a function of pH, derived from the extinction spectra by the ratio between the extinction values at 800 and 536 nm. The temperature was kept at 25 °C during experiments. Figure 6 SAXS analysis of the AuNPs clusters morphology as a function of temperature (from 25 °C to 80 °C), performed at pH 6.5 for two different lysozyme-AuNPs number ratios, ξ=1200 and ξ=2500. (a,e) SAXS curves (circles) and power-law decay fitting curves (black lines); (b,f) fractal dimension as a function of temperature; (c,g) structure factors; (d,h) interparticle distance as a function of temperature; (i) representative SEM image of the assemblies obtained for ξ=2500 and deposited at 80 °C. SAXS curves and structure factors are vertically shifted for clarity. Figure 7 Optical properties of AuNPs clusters at varying the temperature of the solution for the two lysozyme-AuNPs number ratios analyzed, ξ=1200 and ξ=2500. (a,b) Extinction spectra at varying temperature; (c,d) calibration curves as a function of temperature, derived from the extinction spectra by the ratio between the extinction values at 800 and 536 nm. The pH of the solutions was 6.5 during experiments. Figure 8 Schematic illustration of the observed structural variation of the protein-AuNPs assemblies in response to the different external stimuli analyzed: protein concentration, pH and temperature. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Stockman M.I. Kneipp K. Bozhevolnyi S.I. Saha S. Dutta A. Ndukaife J. Kinsey N. Reddy H. Guler U. Shalaev V.M. Roadmap on plasmonics J. Opt. 2018 20 43001 10.1088/2040-8986/aaa114 2. Eustis S. El-Sayed M.A. Why gold nanoparticles are more precious than pretty gold: Noble metal surface plasmon resonance and its enhancement of the radiative and nonradiative properties of nanocrystals of different shapes Chem. Soc. Rev. 2006 35 209 217 10.1039/B514191E 16505915 3. Kelly K.L. Coronado E. Zhao L.L. Schatz G.C. The optical properties of metal nanoparticles: The influence of size, shape, and dielectric environment J. Phys. Chem. B 2003 107 668 677 10.1021/jp026731y 4. Jiang Y. Shi M. Liu Y. Wan S. Cui C. Zhang L. Tan W. Aptamer/AuNP biosensor for colorimetric profiling of exosomal proteins Angew. Chem. Int. Ed. 2017 56 11916 11920 10.1002/anie.201703807 28834063 5. Halas N.J. Lal S. Chang W.S. Link S. Nordlander P. Plasmons in strongly coupled metallic nanostructures Chem. Rev. 2011 111 3913 3961 10.1021/cr200061k 21542636 6. Oliverio M. Perotto S. Messina G.C. Lovato L. De Angelis F. Chemical functionalization of plasmonic surface biosensors: A tutorial review on issues, strategies, and costs ACS Appl. Mater. Interfaces 2017 9 29394 29411 10.1021/acsami.7b01583 28796479 7. Li Z. Wang W. Yin Y. Colloidal assembly and active tuning of coupled plasmonic nanospheres Trends Chem. 2020 2 593 608 10.1016/j.trechm.2020.03.008 8. Spedalieri C. Szekeres G.P. Werner S. Guttmann P. Kneipp J. Probing the Intracellular Bio-Nano Interface in Different Cell Lines with Gold Nanostars Nanomaterials 2021 11 1183 10.3390/nano11051183 33946192 9. Domenici F. Fasolato C. Mazzi E. De Angelis L. Brasili F. Mura F. Postorino P. Bordi F. Engineering microscale two-dimensional gold nanoparticle cluster arrays for advanced Raman sensing: An AFM study Colloids Surf. A Physicochem. Eng. Asp. 2016 498 168 175 10.1016/j.colsurfa.2016.03.043 10. Hou S. Zhang A. Su M. Nanomaterials for biosensing applications Nanomaterials 2016 6 58 10.3390/nano6040058 11. Gerosa C. Crisponi G. Nurchi V.M. Saba L. Cappai R. Cau F. Faa G. Van Eyken P. Scartozzi M. Floris G. Gold nanoparticles: A new golden era in oncology? Pharmaceuticals 2020 13 192 10.3390/ph13080192 32806755 12. Domenici F. Capocefalo A. Brasili F. Bedini A. Giliberti C. Palomba R. Silvestri I. Scarpa S. Morrone S. Paradossi G. Ultrasound delivery of Surface Enhanced InfraRed Absorption active gold-nanoprobes into fibroblast cells: A biological study via Synchrotron-based InfraRed microanalysis at single cell level Sci. Rep. 2019 9 1 13 10.1038/s41598-019-48292-0 30626917 13. Gerber A. Bundschuh M. Klingelhofer D. Groneberg D.A. Gold nanoparticles: Recent aspects for human toxicology J. Occup. Med. Toxicol. 2013 8 1 6 10.1186/1745-6673-8-32 23356875 14. Lasagna-Reeves C. Gonzalez-Romero D. Barria M. Olmedo I. Clos A. Ramanujam V.S. Urayama A. Vergara L. Kogan M.J. Soto C. Bioaccumulation and toxicity of gold nanoparticles after repeated administration in mice Biochem. Biophys. Res. Commun. 2010 393 649 655 10.1016/j.bbrc.2010.02.046 20153731 15. Capocefalo A. Deckert-Gaudig T. Brasili F. Postorino P. Deckert V. Unveiling the interaction of protein fibrils with gold nanoparticles by plasmon enhanced nano-spectroscopy Nanoscale 2021 13 14469 14479 10.1039/D1NR03190B 34473176 16. Chen Y.S. Hung Y.C. Liau I. Huang G.S. Assessment of the in vivo toxicity of gold nanoparticles Nanoscale Res. Lett. 2009 4 858 864 10.1007/s11671-009-9334-6 20596373 17. Johnson L. Gray D.M. Niezabitowska E. McDonald T.O. Multi-stimuli-responsive aggregation of nanoparticles driven by the manipulation of colloidal stability Nanoscale 2021 13 7879 7896 10.1039/D1NR01190A 33881098 18. Caprara D. Ripanti F. Capocefalo A. Sarra A. Brasili F. Petrillo C. Fasolato C. Postorino P. DNA-functionalized gold nanoparticle assemblies for Surface Enhanced Raman Scattering Colloids Surf. A Physicochem. Eng. Asp. 2020 589 124399 10.1016/j.colsurfa.2019.124399 19. Brasili F. Capocefalo A. Palmieri D. Capitani F. Chiessi E. Paradossi G. Bordi F. Domenici F. Assembling patchy plasmonic nanoparticles with aggregation-dependent antibacterial activity J. Colloid Interface Sci. 2020 580 419 428 10.1016/j.jcis.2020.07.006 32698085 20. Ofir Y. Samanta B. Rotello V.M. Polymer and biopolymer mediated self-assembly of gold nanoparticles Chem. Soc. Rev. 2008 37 1814 1825 10.1039/b712689c 18762831 21. Zeng S. Yong K.T. Roy I. Dinh X.Q. Yu X. Luan F. A review on functionalized gold nanoparticles for biosensing applications Plasmonics 2011 6 491 506 10.1007/s11468-011-9228-1 22. Graczyk A. Pawlowska R. Jedrzejczyk D. Chworos A. Gold nanoparticles in conjunction with nucleic acids as a modern molecular system for cellular delivery Molecules 2020 25 204 10.3390/molecules25010204 31947834 23. Kaefer K. Krüger K. Schlapp F. Uzun H. Celiksoy S. Flietel B. Heimann A. Schroeder T. Kempski O. Sönnichsen C. Implantable sensors based on gold nanoparticles for continuous long-term concentration monitoring in the body Nano Lett. 2021 21 3325 3330 10.1021/acs.nanolett.1c00887 33784105 24. Xing S. Xu X. Fu P. Xu M. Gao T. Zhang X. Zhao C. Colorimetric detection of single base-pair mismatches based on the interactions of PNA and PNA/DNA complexes with unmodified gold nanoparticles Colloids Surf. B Biointerfaces 2019 181 333 340 10.1016/j.colsurfb.2019.05.069 31154144 25. Ma X. Kou X. Xu Y. Yang D. Miao P. Colorimetric sensing strategy for heparin assay based on PDDA-induced aggregation of gold nanoparticles Nanoscale Adv. 2019 1 486 489 10.1039/C8NA00162F 26. Höller R.P. Dulle M. Thomä S. Mayer M. Steiner A.M. Foörster S. Fery A. Kuttner C. Chanana M. Protein-assisted assembly of modular 3D plasmonic raspberry-like core/satellite nanoclusters: Correlation of structure and optical properties ACS Nano 2016 10 5740 5750 10.1021/acsnano.5b07533 26982386 27. Guinier A. Fournet G. Yudowitch K.L. Small-Angle Scattering of X-rays John Wiley & Sons New York, NY, USA 1955 28. Menon S. Manohar C. Rao K.S. A new interpretation of the sticky hard sphere model J. Chem. Phys. 1991 95 9186 9190 10.1063/1.461199 29. Baxter R. Percus–Yevick equation for hard spheres with surface adhesion J. Chem. Phys. 1968 49 2770 2774 10.1063/1.1670482 30. Aili D. Gryko P. Sepulveda B. Dick J.A. Kirby N. Heenan R. Baltzer L. Liedberg B. Ryan M.P. Stevens M.M. Polypeptide folding-mediated tuning of the optical and structural properties of gold nanoparticle assemblies Nano Lett. 2011 11 5564 5573 10.1021/nl203559s 22047629 31. Doucet M. Cho J.H. Alina G. Attala Z. Bakker J. Bouwman W. Butler P. Campbell K. Cooper-Benun T. Durniak C. SasView version 5.0.4 Zenodo Genève, Switzerland 2021 10.5281/zenodo.4467703 32. Loumaigne M. Midelet C. Doussineau T. Dugourd P. Antoine R. Stamboul M. Débarre A. Werts M.H. Optical extinction and scattering cross sections of plasmonic nanoparticle dimers in aqueous suspension Nanoscale 2016 8 6555 6570 10.1039/C6NR00918B 26935710 33. Esteban R. Taylor R.W. Baumberg J.J. Aizpurua J. How chain plasmons govern the optical response in strongly interacting self-assembled metallic clusters of nanoparticles Langmuir 2012 28 8881 8890 10.1021/la300198r 22364608 34. Herrmann L.O. Valev V.K. Aizpurua J. Baumberg J.J. Self-sifting of chain plasmons: The complex optics of Au nanoparticle clusters Opt. Express 2013 21 32377 32385 10.1364/OE.21.032377 24514830 35. Japaridze A. Vobornik D. Lipiec E. Cerreta A. Szczerbinski J. Zenobi R. Dietler G. Toward an effective control of DNA’s submolecular conformation on a surface Macromolecules 2016 49 643 652 10.1021/acs.macromol.5b01827 36. Bushell G. Yan Y. Woodfield D. Raper J. Amal R. On techniques for the measurement of the mass fractal dimension of aggregates Adv. Colloid Interface Sci. 2002 95 1 50 10.1016/S0001-8686(00)00078-6 11843188 37. Lattuada M. Wu H. Morbidelli M. Hydrodynamic radius of fractal clusters J. Colloid Interface Sci. 2003 268 96 105 10.1016/j.jcis.2003.07.028 14611778 38. Balfourier A. Mulens-Arias V. Gazeau F. Carn F. Rational Design of Fractal Gold Nanosphere Assemblies with Optimized Photothermal Conversion Using a Quantitative Structure Property Relationship (QSPR) Approach J. Phys. Chem. C 2020 124 8938 8948 10.1021/acs.jpcc.0c00384 39. Wallace G.Q. Lagugné-Labarthet F. Advancements in fractal plasmonics: Structures, optical properties, and applications Analyst 2019 144 13 30 10.1039/C8AN01667D 40. Fusco Z. Tran-Phu T. Cembran A. Kiy A. Kluth P. Nisbet D. Tricoli A. Engineering Fractal Photonic Metamaterials by Stochastic Self-Assembly of Nanoparticles Adv. Photon. Res. 2021 2 2100020 10.1002/adpr.202100020 41. Teixeira J. Small-angle scattering by fractal systems J. Appl. Crystallogr. 1988 21 781 785 10.1107/S0021889888000263 42. Verma A. Srivastava S. Rotello V.M. Modulation of the interparticle spacing and optical behavior of nanoparticle ensembles using a single protein spacer Chem. Mater. 2005 17 6317 6322 10.1021/cm051483e 43. Piccinini E. Pallarola D. Battaglini F. Azzaroni O. Self-limited self-assembly of nanoparticles into supraparticles: Towards supramolecular colloidal materials by design Mol. Syst. Des. Eng. 2016 1 155 162 10.1039/C6ME00016A 44. Sennato S. Chauveau E. Casciardi S. Bordi F. Truzzolillo D. The double-faced electrostatic behavior of PNIPAm microgels Polymers 2021 13 1153 10.3390/polym13071153 33916554 45. Truzzolillo D. Sennato S. Sarti S. Casciardi S. Bazzoni C. Bordi F. Overcharging and reentrant condensation of thermoresponsive ionic microgels Soft Matter 2018 14 4110 4125 10.1039/C7SM02357J 29664092 46. Hierrezuelo J. Sadeghpour A. Szilagyi I. Vaccaro A. Borkovec M. Electrostatic stabilization of charged colloidal particles with adsorbed polyelectrolytes of opposite charge Langmuir 2010 26 15109 15111 10.1021/la102912u 20822122 47. Bordi F. Sennato S. Truzzolillo D. Polyelectrolyte-induced aggregation of liposomes: A new cluster phase with interesting applications J. Phys. Condens. Matter 2009 21 203102 10.1088/0953-8984/21/20/203102 21825508 48. Velegol D. Thwar P.K. Analytical model for the effect of surface charge nonuniformity on colloidal interactions Langmuir 2001 17 7687 7693 10.1021/la010634z 49. Lin M. Lindsay H. Weitz D. Ball R. Klein R. Meakin P. Universality in colloid aggregation Nature 1989 339 360 362 10.1038/339360a0 50. Jungblut S. Joswig J.O. Eychmüller A. Diffusion-and reaction-limited cluster aggregation revisited Phys. Chem. Chem. Phys. 2019 21 5723 5729 10.1039/C9CP00549H 30801102 51. Papagianni M. Advances in citric acid fermentation by Aspergillus niger: Biochemical aspects, membrane transport and modeling Biotechnol. Adv. 2007 25 244 263 10.1016/j.biotechadv.2007.01.002 17337335 52. Kubiak-Ossowska K. Cwieka M. Kaczynska A. Jachimska B. Mulheran P.A. Lysozyme adsorption at a silica surface using simulation and experiment: Effects of pH on protein layer structure Phys. Chem. Chem. Phys. 2015 17 24070 24077 10.1039/C5CP03910J 26315945 53. Komorek P. Wałek M. Jachimska B. Mechanism of lysozyme adsorption onto gold surface determined by quartz crystal microbalance and surface plasmon resonance Bioelectrochemistry 2020 135 107582 10.1016/j.bioelechem.2020.107582 32535493 54. Komorek P. Jachimska B. Brand I. Adsorption of lysozyme on gold surfaces in the presence of an external electric potential Bioelectrochemistry 2021 142 107946 10.1016/j.bioelechem.2021.107946 34507162 55. Tang P. Colflesh D.E. Chu B. Temperature effect on fractal structure of silica aggregates J. Colloid Interface Sci. 1988 126 304 313 10.1016/0021-9797(88)90124-5 56. Sennato S. Truzzolillo D. Bordi F. Cametti C. Effect of Temperature on the Reentrant Condensation in Polyelectrolyte- Liposome Complexation Langmuir 2008 24 12181 12188 10.1021/la8021563 18831566 57. Czeslik C. Winter R. Effect of temperature on the conformation of lysozyme adsorbed to silica particles Phys. Chem. Chem. Phys. 2001 3 235 239 10.1039/b005900p 58. Bordi F. Cametti C. Sennato S. Diociaiuti M. Direct evidence of multicompartment aggregates in polyelectrolyte-charged liposome complexes Biophys. J. 2006 91 1513 1520 10.1529/biophysj.106.085142 16731565 59. Sciortino F. Mossa S. Zaccarelli E. Tartaglia P. Equilibrium cluster phases and low-density arrested disordered states: The role of short-range attraction and long-range repulsion Phys. Rev. Lett. 2004 93 055701 10.1103/PhysRevLett.93.055701 15323710 60. Sciortino F. Tartaglia P. Zaccarelli E. One-dimensional cluster growth and branching gels in colloidal systems with short-range depletion attraction and screened electrostatic repulsion J. Phys. Chem. B 2005 109 21942 21953 10.1021/jp052683g 16853852 61. Retout M. Mantri Y. Jin Z. Zhou J. Noël G. Donovan B. Yim W. Jokerst J.V. Peptide-Induced Fractal Assembly of Silver Nanoparticles for Visual Detection of Disease Biomarkers ACS Nano 2022 16 6165 6175 10.1021/acsnano.1c11643 62. Siddiqui S. Shawuti S. Sirajuddin Niazi J.H. Qureshi A. l-Cysteine-Mediated Self-Assembled Ag–Au Nanoparticles As Fractal Patterns with Bowling-Alley-like Hollow Arrays for Electrochemical Sensing of Dopamine Ind. Eng. Chem. Res. 2019 58 8035 8043 10.1021/acs.iecr.9b00016 63. Liu G. Lu M. Huang X. Li T. Xu D. Application of gold-nanoparticle colorimetric sensing to rapid food safety screening Sensors 2018 18 4166 10.3390/s18124166 30486466 64. Mohseni N. Bahram M. Baheri T. Chemical nose for discrimination of opioids based on unmodified gold nanoparticles Sens. Actuators B Chem. 2017 250 509 517 10.1016/j.snb.2017.04.145 65. Choe A. Yeom J. Shanker R. Kim M.P. Kang S. Ko H. Stretchable and wearable colorimetric patches based on thermoresponsive plasmonic microgels embedded in a hydrogel film NPG Asia Mater. 2018 10 912 922 10.1038/s41427-018-0086-6

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093450 sensors-22-03450 Article The Design of a Low Noise, Multi-Channel Recording System for Use in Implanted Peripheral Nerve Interfaces https://orcid.org/0000-0003-3048-6219 Sadrafshari Shamin 1* https://orcid.org/0000-0003-4279-8930 Metcalfe Benjamin 1 Donaldson Nick 2 https://orcid.org/0000-0002-3036-3908 Granger Nicolas 3 Prager Jon 3 Taylor John 1 Kim Sung-Phil Academic Editor 1 Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK; bwm23@bath.ac.uk (B.M.); eesjtt@bath.ac.uk (J.T.) 2 Department of Medical Physics and Bioengineering, University College London, London WC1E 6BT, UK; n.donaldson@ucl.ac.uk 3 Department of Clinical Science and Services, The Royal Veterinary College, Hawkshead Lane, Brookmans Park, Hatfield AL9 7TA, UK; nicolasgranger@rvc.ac.uk (N.G.); jon.prager@bristol.ac.uk (J.P.) * Correspondence: ss3231@bath.ac.uk 30 4 2022 5 2022 22 9 345001 4 2022 23 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). In the development of implantable neural interfaces, the recording of signals from the peripheral nerves is a major challenge. Since the interference from outside the body, other biopotentials, and even random noise can be orders of magnitude larger than the neural signals, a filter network to attenuate the noise and interference is necessary. However, these networks may drastically affect the system performance, especially in recording systems with multiple electrode cuffs (MECs), where a higher number of electrodes leads to complicated circuits. This paper introduces formal analyses of the performance of two commonly used filter networks. To achieve a manageable set of design equations, the state equations of the complete system are simplified. The derived equations help the designer in the task of creating an interface network for specific applications. The noise, crosstalk and common-mode rejection ratio (CMRR) of the recording system are computed as a function of electrode impedance, filter component values and amplifier specifications. The effect of electrode mismatches as an inherent part of any multi-electrode system is also discussed, using measured data taken from a MEC implanted in a sheep. The accuracy of these analyses is then verified by simulations of the complete system. The results indicate good agreement between analytic equations and simulations. This work highlights the critical importance of understanding the effect of interface circuits on the performance of neural recording systems. neural recording multiple electrode cuff (MEC) interface filter network common-mode rejection ratio (CMRR) noise performance crosstalk electrode mismatch EPSRCEP/P018947/1 This research was funded by EPSRC grant number EP/P018947/1, and the APC is not applicable. ==== Body pmc1. Introduction 1.1. Neural Recording The recording of signals from the peripheral nervous system (PNS) (the electroneurogram—ENG) using chronically implanted electrodes is one of the major challenges in current neuroprosthetic research. Several types of implantable interfaces have been proposed, but very few have been validated with long-term chronic studies. One of the most well-established types, both for stimulation and recording, is the extraneural nerve cuff [1]. Cuffs are widely used for the electrical stimulation of the peripheral nerves, including in commercial devices, such as the LivaNova vagus nerve stimulator for intractable epilepsy [2,3]. Likewise, there have been several demonstrations of recording from the PNS using cuffs, albeit predominantly in acute studies [4]. Tripolar stimulation cuffs, in which a current is driven between the centre electrode and the outer pair of electrodes (which are usually connected together) are also frequently employed [5]. For recording purposes, a monopole, dipole or tripole electrode structure is connected to a differential amplifier or a double-differential amplifier. The dipole recording configuration is most common, although it has been shown that the tripole arrangement can reduce interference by improving common-mode (CM) rejection [6]. The neural signals within the PNS may be classified as afferent or efferent, corresponding to the direction of propagation. Most peripheral nerves (especially when interfaced using an extraneural approach) are mixed and contain many afferent and efferent axons. In order to record selectively from specific axons, it is necessary to perform some form of signal processing to separate the propagating signals. There are many approaches to this problem, such as the use of spatio-temporal filters [7], source localisation [8], electrical impedance tomography [9], or discrimination based on conduction velocity [10]. Velocity Selective Recording (VSR) uses multi-electrode cuffs (MECs) to detect and classify neural signals based on the different velocities present, exploiting the correspondence between conduction velocity and fibre diameter, at least for myelinated nerves [11,12]. 1.2. Recording Challenges of MECs To implement VSR, the electrodes of the MEC must be connected to a bank of differential amplifiers [11] and this increases the complexity of the amplifier design task. As for the dipoles and tripoles, the amplitudes of spontaneous (i.e., naturally occurring) neural signals recorded are very small (generally less than 1 µV [13]). Therefore, the differential voltage gain must be high (typically 60–100 dB) with an adequate signal-to-noise ratio (SNR), requiring very low noise front-end amplifiers, i.e., the noise floor of the amplifier must be less than a few nV/√Hz [14]. The outline schematic of an example recording system is shown in Figure 1, where N (typically about 10) electrodes are fitted to an insulating nerve cuff forming a MEC. The electrodes are shown connected directly to an amplifier array as dipoles. For the MEC, in addition to the exacting differential specification required of each amplifier, in order to mitigate the effects of undesired interfering signal sources, CM gain and crosstalk between the individual channels must be minimised. In the recording of spontaneous neural signals, interference comes from nearby muscles, AC mains and radio frequency (RF) pick-up [15]. Singly or in combination, such interference can saturate high-gain amplifiers. Therefore, a bandpass filter interface network, placed between the recording electrodes and the front-end amplifiers, is essential to limit the effects of high- and low-frequency interfering signals. Unfortunately, the presence of such a filter network conflicts with the noise and CM rejection behaviour of the amplifiers and so the interface between the two requires careful design. Moreover, the impedance mismatch between channels in a multi-electrode recording system is inevitable and will also affect the system’s performance. In this paper, two interface circuits suitable for a multi-electrode recording system are examined for cuff electrodes. Analyses of noise, common-mode rejection ratio (CMRR) and crosstalk are presented for two input networks (‘Type 1’ and ‘Type 2’) (these correspond to the networks called ‘Type 1’ and ‘Type 2’ in [15]). The two networks were originally introduced and analysed for the case of a single tripole (one differential amplifier) in [16], and it was found that the ‘Type 2’ arrangement was superior to the ‘Type 1’ network in terms of both CMRR and noise performance. In this paper, we extend and enlarge the results of [16] and demonstrate that the single-amplifier results do not extend to a multi-electrode system. The two networks are shown in Figure 2. The overall intention of this work is to aid and inform the designer of such a system and provide the theory that simulation alone cannot. Having said that, the validation study presented is based mostly on simulation. The justification for this approach is discussed in Section 4 and relates to the inherently low sensitivity of the circuits employed to component tolerances (including the electrode impedances) and the reliability of simulation models in the bandwidth under consideration. Equations are derived symbolically using MATLAB and simplified for practical component values, reflecting how the various parameters affect the design criteria. Although the equations are derived for a 10-channel recording system, they can be extended and generalised for an N electrode system. SPICE simulations and some measured data are used to validate the accuracy of the procedure and indicate good agreement between the detailed analytic equations and the simplified versions. The outline of this paper is as follows. CMRR, crosstalk and noise performance of a 10-channel multi-electrode system with two types of filters are discussed, and corresponding approximate equations are derived in Section 2. Section 4 investigates the accuracy of the approximate equations derived in Section 2 using SPICE simulation. Section 5 discusses how these analyses can help designers to achieve the desired specifications in a multi-electrode recording system and, finally, conclusions are drawn in Section 6. 2. Interface Circuits Figure 2a,b show the two candidate front-end circuits that are referred to as ‘Type 1’ and ‘Type 2’ [16]. Both circuits place an RC bandpass filter between the cuff electrodes and the input terminals of the amplifiers, realised by first-order high pass and low pass sections connected in cascade, the time constants being realised by the series and parallel capacitors (Cs, Cp), respectively, and associated resistances, including the two impedances Rd and Re, (see below). The cut-off frequencies are chosen to be about 100 Hz and 100 kHz [14], respectively, attenuating both low- and high-frequency interfering signals while satisfying the bandwidth requirements of a 10-channel VSR system for neural recording [7]. Note, also, that the sensitivities of the circuit transfer functions to the various component values (including those associated with the electrodes) will be low. In all cases, the electrodes, which are grouped as dipoles, are represented by an equivalent circuit consisting of a voltage source (Vd) in series with an impedance (Rd) representing the axial component of the section of the tissue inside the cuff. This combination of voltage generator and impedance appears to be a generic Thévenin source, but actually, it is more complicated than that. The source will be the superposition of voltages from all the separate axons, and each axon produces action potentials at the dipole electrodes which is the product of Rd and its action current—the action current is being determined by the travelling transmembrane (TMAP) potential and the high axon resistance [11]. The action currents are therefore a property of the nerve and only Rd can be altered by the design of the cuff. It follows that Vd and Rd are not independent but, in fact, Vd is proportional to Rd. Rd is resistive and has a typical value of about 0.5 kΩ [9]. By contrast, the impedances of the electrodes connecting the tissue to the front-end amplifier circuits (Re) are complex, with typical values (moduli) of about 1 kΩ at a frequency of 1 kHz. These element values and assumptions have been employed in assessing the performances of the two candidate circuits discussed in the paper and to simplify the design equations. The only difference between the two circuits in Figure 2 is that in the Type 1 circuit of Figure 2a the bias current path to ground for each amplifier input is provided by individual resistors (Ra) while in the Type 2 configuration of Figure 2b, a centre tapped pair of resistors (R1) is employed [8]. The two resistors’ Rcm represents the impedances between the reference electrode (normally placed far away from the cuff) and the end electrodes of the cuff. Vcm is the CM input voltage (i.e., the interfering source in this case). At passband (mid-band) frequencies, it is assumed that the shunt capacitors become open circuits and the series capacitors short circuit. In the following sub-sections, expressions for CMRR, crosstalk and noise are derived for both versions of the circuit, for passband operation in all cases. Finally, it is worth noting that all the circuits employed are based on simple first-order RC circuits and, since no overall feedback is employed, the poles of the transfer functions lie on the negative real axis of the complex plane. This has the advantage that Q values are low in the frequency domain and hence sensitivity to component tolerances is also low. 2.1. Common-Mode Rejection Ratio (CMRR) Using an amplifier with high CMRR does not guarantee that the entire system will operate with high CMRR. A front-end filter network of the type shown in Figure 2 (either version) can generate differential signals from common-mode inputs, reducing the overall CMRR of the system. It can be shown that the CMRR of the entire system is related to the CMRR of the individual amplifiers by the following expression [8]: (1) 1CMRR≈1CMRRa+VaiVcm where CMRRa is the amplifier’s common-mode rejection ratio and Vai/Vcm represents the differential gain from the common-mode input (see Figure 2—both forms) to the i′th differential input of the amplifier array. Therefore, an inappropriately designed front-end filter can degrade the performance of the entire system, irrespective of the quality of the amplifiers. To investigate the effect of the front-end network on the overall CMRR, the common-mode gain at the differential input of each amplifier Vai was calculated for both candidate structures, for N = 10. 2.1.1. ‘Type 1’ Biasing Structure To calculate the effect of a common-mode signal at the inputs of the amplifiers, all differential input voltage sources Vdi are set to zero, and the KCL equations for nodes V1, …, V10, V′1, …, V′10 are written in the form:(2) A×[V1:V10V′1:V′10]=B×Vcm where A is the (20 × 20) connection matrix shown in Table 1 and B is a (20 × 1) column vector. In B, all elements are zero except for the 11th and 20th, which are Gcm1 and Gcm2, respectively. (3) B=[00:0Gcm100:Gcm2] In the analysis, the conductances Gcm, Gd, etc., are the inverses of the resistances Rcm, Rd in Figure 2. Assuming that the amplifiers are ideal, V1, …, V10, V′1, …, V′10 can be calculated as:(4) [V1:V10V′1:V′10]=A−1×B×Vcm The nodal equations for V1–V10 were solved symbolically using MATLAB (see Appendix A for an example equation). The input impedance (Rai) should be larger than the electrode impedances in order to maximise the voltage drop across the input. Therefore, making the reasonable assumptions that:Rai >> Rei; Rai >> Rcmi and Rai >> Rdi; all i and all the Ra are equal, all the Re are equal, and the Rcm are equal, the additional CM gain in the i’th channel due to the filter network can be expressed as follows:(5) VaiVcm≈(N2−i)RdRa ;i=1,2, …,N/2 where Vai is the differential input voltage to the i’th amplifier and N, the number of electrodes is assumed to be even (similar arguments apply for N odd) and with a value of 10 in this case. Equation (5) shows that the outer channels have higher common-mode gain and therefore lower CMRR than those near the centre of the array, where the overall CMRR approaches that of the amplifiers. Note that the additional CM gain can be reduced by reducing the ratio Rd/Ra as far as possible. 2.1.2. ‘Type 2’ Biasing Structure Figure 2b shows the front-end network employing the ‘Type 2’ biasing circuit. As in the case of the ‘Type 1’ structure, KCL equations can be derived and the voltages V1–V10 calculated. Proceeding as in the ‘Type 1’ case, assuming this time that for all i, R2i >> Rcmi, Rdi and Rei and that, in addition, Rei << R1i, the CM gain at the differential input of the amplifier is approximated as:(6) VaiVcm≈(N2−i)(Rd||2R1)R2; i=1, 2,…,N/2 Equation (6) shows that increasing R2 and reducing R1 improves the CMRR. However, note that reducing R1 also decreases the differential gain of the channels in addition to possibly reducing the accuracy of the approximation, which requires, as already noted, that Rei << R1i. Therefore, some design trade-offs may be required in this case. 2.2. Crosstalk between the Channels The differential gain from each input source Vdi to the amplifier inputs Vaj can be discussed in two parts. Firstly, the gain from each source to its corresponding amplifier input should be as close to unity as possible and, secondly, the gain from each source to the inputs of the other amplifiers, which, for the purposes of this paper, we refer to as crosstalk, should ideally be zero. In this section, the differential gain at each amplifier input is calculated for both candidate structures. 2.2.1. ‘Type 1’ Biasing Structure To analyse the differential gain at each amplifier input Vaj, all the differential inputs Vdi except one are set to zero (the CM input voltage is also set to zero). For this calculation, it is convenient to use the Norton form of the equivalent circuit for each source, where:(7) Idi=VdiRdi The KCL equations for V1, …, V10, V′1, …, V′10 are as follows:(8) A×[V1:V10V′1:V′10]=Ci×Idi  where A is defined in Table 1 and the column vector Ci is: (9)  Ci=[c1:ck:c10]   , ck={1k=i−1k=i+10else  The voltages V1–V10 follow from:(10) [V1:V10]=A−1×Ci×Idi  and the differential gain from each source to each amplifier input is given by Equation (11):(11) VajVdi={1−Rd2Rcm+9Rdif i=j−Rd2Rcm+9Rdif i≠j  Equation (11) shows that crosstalk is reduced by reducing the ratio Rd/Rcm. 2.2.2. ‘Type 2’ Biasing Structure The analysis is very similar to that employed for the ‘Type 1’ structure and the differential gain in this case is:(12) VajVdi={Rd||2R1Rd(1−Rd||2R12Rcm+9(Rd||2R1))if i=j−Rd||2R1Rd(Rd||2R12Rcm+9(Rd||2R1))if i≠j  As in the case of the ‘Type 1’ structure, crosstalk in the ‘Type 2’ biasing arrangement is reduced by decreasing the ratio of Rd/Rcm. Note, in addition, that in this case, decreasing R1 reduces both crosstalk and differential gain, which may be unacceptable in some applications. 2.3. Noise Analysis In this section, the main sources of noise and their effect on the behaviour of the circuit, including the front-end filter networks (as shown in Figure 2) are described. The subject of noise in multi-channel VSR systems was dealt with comprehensively in [12]. In this paper, we present a simplified approach based on the earlier work, however, we intend to inform the designer of the main issues involved and their possible mitigation. The contributions of thermal noise, amplifier voltage noise and amplifier current noise are considered separately, and the individual sources are assumed to be Gaussian and uncorrelated in all cases. In both the Type 1 and Type 2 arrangements, the axial components of the electrode/tissue combination are denoted Rd, while the Re is the electrode impedances (see Figure 2). The two resistances Rcm are the common-mode elements connecting the ends of the cuff system to the reference (shown as ground in the figure). In the Type 1 circuit, the Ra are bias resistors, essentially used to define the DC bias point of the amplifier inputs, whereas, in the Type 2 circuit, a balanced-T network is used for this purpose. As already noted, one consequence of this arrangement is that a potential divider exists involving Re and R1, that influences both the signal and noise amplitudes. 2.3.1. Thermal Noise For noise modelling, as in other sections of the paper, all the resistors are assumed to be real (i.e., ohmic) except for Re, which are complex impedances. In the passband of the filter, the capacitors are chosen, so that those connected in series are short circuits while those in shunt are open circuits. The following assumptions amongst the impedances are made: Rai >>∣Rei∣; Rai >> Rcmi, R2i >> R1i and Rai >> Rdi; all i For noise calculations, it is helpful to redraw the filter circuit in the passband as a ladder network, where the impedances of each type are assumed to be equal. For the Type 1 circuit, it is as shown in Figure 3a. Noting the inequalities above, the Ra appear in parallel with much smaller resistances and so can be omitted from the noise calculations. The simplified circuit is redrawn, as shown in Figure 3b. If each Rd is removed from the circuit in turn, the Thévenin equivalent circuit of residual impedance at the port where the resistor was removed is [(N − 1)Rd + 2Rcm]. For N = 10 (i.e., large) and, given that Rcm is not negligible, this residue will be in excess of 10Rd. This resistance appears in parallel with the Rd removed and so it is reasonable to assume that the only significant contribution to thermal noise density at the input to an amplifier is given by one Rd and the associated pair of impedances Re. The thermal noise density contribution appearing at the input to this amplifier, expressed as an rms voltage, is, therefore:(13) Va1(rms)=4kT(Rd+2re(Re) where re(Re) represents the real part of Re. Similar expansion and simplification procedures can be applied to the Type 2 circuit, resulting in the equivalent circuit shown in Figure 4. As already noted in Section 2.1.2 of the paper, the presence of the resistors R1 places a potential divider (involving the impedances Re as the other element) in each signal path. Due to the small size of the recorded signals, it is highly desirable to make the gain of this divider as close to unity as possible and so we can add a further inequality to the previous list: R1i >> ∣Rei∣, all i Figure 4 Simplified passband equivalent circuit for thermal noise analysis for a Type 2 circuit. This is a ladder expansion of Figure 2b, to which the same simplifying procedures have been applied as were used in Figure 3a. In addition, as already noted, for maximum signal gain we require that R1 >> ∣Re∣ and so the circuit reduces to that of Figure 3b. A consequence of this is that the R1 will contribute little to the overall noise calculation since they also appear in parallel with many small resistances. The thermal noise equivalent circuits for both Type 1 and Type 2 circuits are therefore the same (Figure 3b) and the thermal noise density appearing at the input to each amplifier is given by Equation (1). 2.3.2. Amplifier Noise Figure 5 is the noise equivalent circuit of a single-ended output, differential voltage amplifier, where vn and in are rms noise sources (densities), respectively. Assuming the input resistance of the amplifiers is so large as to be effectively infinite, the voltage noise contribution of each amplifier appears only at the corresponding output, since no current flows into the other parts of the circuit as a result of the presence of vn. The equivalent circuit for the amplifier current noise is shown in Figure 6, where the simplified form of the circuit developed above has been used. It is clear from this circuit that each amplifier will cause noise current to flow around a primary loop consisting of one Rd and two Re and also around a secondary loop consisting of (N − 1) resistors Rd and two Rcm. Using the same arguments as for thermal noise, the current in the secondary loop will be significantly less than in the primary loop and can be ignored for practical purposes. Using the principle of superposition (i.e., taking each source individually, the others being removed from the circuit) and treating the various resistances and impedances as noiseless (since the noise contributions of these components have been considered separately), the contribution to the rms voltage Va1 due to ia1 is:Va11 = ia1|Rd1 + Re1 + Re2| Since Va1 appears across one of the pairs of electrodes at the end of the array, considering only currents flowing in the primary loops, the only other contribution comes from ia2: Va12 = ia2|Re2| Assuming that all the Rd are equal and all the Re are equal and that ia1 and ia2 are uncorrelated sources of the same statistics and of equal amplitude ia, the total rms value of Va1 is given by summing the two contributions, recalling that Re is a complex impedance:Van=ia|Rd+2Re|2+|Re|2 where n = 1 or N − 1, and, similarly, for the other inputs (i.e., those not placed at the ends of the array):Vam=ia|Rd+2Re|2+2|Re|2 In this section, in summary, expressions have been derived for the thermal noise and amplifier voltage and current noise appearing at the input of one of the amplifiers in the N channel system shown in Figure 2. The analysis is a simplified form of that given previously in [12] and, given certain assumptions, ensures the accuracy of the thermal and amplifier current noise calculations is better than approximately 1/N, where N is typically 10 (the amplifier voltage noise calculation is exact). Since all three sources are assumed to be white and uncorrelated, an expression for the total input-referred noise density for one amplifier can be written using superposition. This is valid for both Type 1 and Type 2 arrangements: (14) va(total)=4kT[Rd+2re(Re)]+vn2+ia2(|Rd+2Re|2+p|Re|2) where p = 1 at the end amplifiers, and p = 2 for the others. Table 2 summarizes the equations derived in this section. 3. Electrode Impedance Mismatch In Section 2, the calculation of CMRR, crosstalk and noise performance for the case of matched electrode impedances was discussed. However, in practice, impedance variation of the individual electrodes, as well as the mismatch between the electrodes, is inevitable. Typical reasons for this are fabrication process non-idealities and inconsistencies and the growth of encapsulation tissue around the electrodes. In addition, changes in electrode size and separation would affect the impedances of the electrodes (Rd and Re), and hence, both the gain and the upper cut-off frequency of the bandpass filter to some extent. However, the inherently low sensitivity design of the filter circuits ensures that the effect on the system parameters would be small. As an illustration of typical impedance variations, a 10 electrode MEC with stainless steel ring electrodes (diameter 1 mm, electrode pitch 1.5 mm) was fabricated and implanted on the second sacral spinal nerve root S2 (left) of a female sheep. Impedance measurements were taken using a two-wire configuration at 1 kHz with a 100 mV source voltage. The measurements are shown in Table 3 and indicate that the modulus of the impedance mismatch between pairs of electrodes may be as high as 200%, and therefore not negligible (note that the impedance values in Table 3 are illustrative only. This is because these values include contributions from both Re and Rd. At present we do not have estimates of these impedances separately). Clearly, then, it is critically important that the impedance mismatch is included in the design and analysis of the recording instrumentation. To illustrate the effect of impedance mismatch, the effect on CMRR and crosstalk are discussed for both types of interfaces. As in the case of the matched interface networks, analysed in Section 2, KCL equations are derived, and the CM gain and crosstalk are calculated for both interfaces with mismatched electrode impedances. Note, also, that the same assumptions are applied as in Section 2. As a result, only the axial component of the electrode impedance (Rd) appears in the equations in Table 4 and Table 5 and only variations of Rd and Rcm need to be considered. The effect of mismatch between two reference impedances (Rcm) on the gain is shown in Table 4, where Rcm and ΔRcm represent the average value of the reference impedance and its mismatch. For both circuits, the first term of the CM gain equations is the same as the gain of a network without mismatch. The second term is added to reflect the Rcm mismatch and therefore degrades the CMRR. However, it does not affect the differential gain and so crosstalk is not affected by Rcm mismatch. The effect of axial impedance mismatch on common-mode and differential gain is summarised in Table 4. In these equations, Rdi represents the axial impedance of the ith electrode. Therefore, the mismatch of each electrode affects the CMRR and crosstalk of its corresponding channel only in both types of structure. 4. Validation by Simulation 4.1. Accuracy of the Approximate Equations To verify the accuracy of the approximate equations derived in Section 2, a 10-channel interface was simulated (using SPICE) for both the ‘Type 1’ and ‘Type 2’ structures. The amplifier is assumed to have a high input impedance and not to interact with the interface, except for the amplifier’s current noise source. As already noted, this causes currents to flow in the interface circuit, resulting in differential voltages at the amplifier inputs. The effect of the amplifier current noise source is therefore expressed as an impedance. The other simulations considered are CMRR, crosstalk and thermal noise (note that the input-referred rms voltage noise does not depend on the design of the interface circuit and so is not considered). The comparison between the two sets of results for CMRR is shown in Figure 7 for different cases where some parameters are kept constant while others are swept over a practical range of interest (note that for compactness, only the curves describing the CMRR performance are shown). The variables chosen for this validation process are as shown in Table 6. In Figure 7, the x-axes show the swept parameters, the others being held at their nominal values. The CMRR variation as a function of Rd and Ra (‘Type 1’)/R2 (‘Type 2’) is shown in Figure 7a,b. The inaccuracies caused by the various approximations are less than 0.05 dB compared with the SPICE simulations. Similarly, for crosstalk, where Rd and Rcm are varied, the inaccuracies caused by the approximations are less than 0.1 dB. The errors in the calculation of thermal noise and amplifier current noise gain are less than 3.6% and 0.08%, respectively. 4.2. Simulation of the Complete System As an example of the characterisation of a complete recording system, a 10-channel ‘Type 1’ interface network (Figure 2a operating in the passband), connected to a low noise CMOS amplifier array, was simulated using SPICE. In this example, all the components in the interface network were matched (Ra = 10 MΩ, Rcm = Rd = 1 kΩ). The specifications of the ENG amplifier are summarised in Table 7. The simulated and calculated results are shown in Table 8. It should be noted that for the calculated CMRR value, the measured amplifier CMRR (77.5 dB) is included (Equation (1)), whereas neglecting the effect of the amplifier results in a CMRR of 67.96 dB. For the noise density, Equation (14) calculates the total noise density referred to as the input of the amplifier, which results in 8.5 nV/Hz and, in order to refer the noise to the voltage source Vdi, it should be divided by the corresponding gain from (Equations (11) and (12)). For both crosstalk and noise parameters, the calculated values and simulation results are in good agreement, as illustrated in Table 8. Unfortunately, as explained above, it is not possible at present to incorporate the measured results given in Table 4 into these simulations, as separate values for Rd and Re are not available. 5. Discussion 5.1. Validity of Assumptions 5.1.1. Use of a Simulation-Based Analytical Study As noted above, with few exceptions, the study presented in this paper is based on simulation. The justification for this is that: (a) the circuits employed to achieve a bandpass characteristic (first-order RC combinations) have inherently low sensitivity to parameter values; (b) that the bandwidth (centred around 1 kHz) is very low; (c) the circuits are fee-forward, i.e., no overall feedback is applied. Taken together, these aspects favour the use of simulation because (i) the use of RC circuits for frequency selection and the absence of overall feedback means that the transfer functions of the circuits have low Q in the frequency domain and, therefore, have low sensitivity to component tolerance. Furthermore, (ii) in the bandwidth of the systems discussed, the component models employed in commercial circuit simulators provide an adequate level of precision for most practical purposes. 5.1.2. The Use of Gaussian Noise Models This paper has presented a detailed analysis of the noise performance (in terms of thermal noise, amplifier voltage noise and amplifier current noise) of the Type 1 and Type 2 circuits, with a focus on the design guidelines that aim to maximise the SNR. Throughout this analysis, the noise sources have been modelled using independent Gaussian processes—a common approach for noise modelling. Interference has been assumed to arise predominantly from high-frequency radio transmissions (RF) and would be dealt with via the appropriate selection of the corner frequencies of the bandpass filter. This is made possible because the RF sources are significantly out-of-band when compared to ENG. However, other biological sources within the body will also contribute to the interference, and it is likely that some of these will produce impulsive noise that may be better represented by coloured noise (e.g., Brownian noise). These sources will most likely be in-band, and thus not readily removed by simple filtering in the frequency domain. These sources are not considered in this paper; however, they would most likely appear at the recording interface as correlated sources akin to the ECG artefact. Thus, the analysis of the common-mode rejection ratio considered in Section 2.1 would apply in this case. 5.2. Optimisation of Component Values A set of analytical design equations were derived in Section 2, linking the main system parameters (CMRR, crosstalk and noise) for two types (Types 1 and 2) of practical multi-channel interface networks to the underlying component values. These equations were validated (by simulation) in Section 3 and found to be accurate in all cases, at least when reasonable assumptions were made. In fact, it was noted that if R1 >> Rd, and R2 ~ Ra, the same design equations can be used for both types of interface networks, suggesting a unified graphical presentation to aid the designer. This is important, since the design of a multi-channel interface system, optimised to a particular specification, presents the designer with a very large set of design choices and possibilities. The four plots in Figure 8 show the design equations for CMRR, crosstalk, thermal noise and amplifier current noise derived in Section 2 for both interface structures in a compact, visually accessible form. Figure 8a (based on Equation (5)) shows that CMRR is increased by increasing the values of the grounded resistors (Ra) and/or reducing the cuff impedances (Rd), always recognising that the upper limit of CMRR is determined by the amplifier itself. Note that crosstalk (Figure 8b and Equation (11)) can be reduced by reducing the ratio of Rd to Rcm, but for practical values of these elements, crosstalk is fairly constant. In Figure 8c,d, the effects of thermal noise and gain of amplifier current noise at preamplifier input are plotted at constant temperature (37 °C) in terms of Rd and Rcm, assuming that Re is negligible in comparison with other impedance values. These plots demonstrate the effect of the interface network impedances on the components of the total input-referred noise that depends on them, i.e., neglecting the voltage noise contribution of the amplifier. Both these parameters can be reduced by decreasing the electrode impedance (Rd) but are both almost independent of the common-mode resistance, Rcm. Note, however, that since the total input-referred noise is the superposition of all three components (see Equation (14)), reducing any or all of them will reduce the total noise. In summary, ∣Re∣ should be small because this will reduce both thermal and amplifier current noise (Equations (13) and (14)) and avoid attenuation of the neural signal. Equations (13) and (14) are valid for the noise, however, they need to be considered carefully when optimising the design. The noise is minimised by reducing both Re and Rd, however, because the signal amplitude is proportional to Rd [11,17], in practice, to maximise signal/noise, the cuff should be designed to maximise Rd and the effect that has on noise is unavoidable. Rcm should be as large as possible in order to minimise crosstalk (Equations (11) and (12)), which will only have a small effect on noise. Increasing Ra (Type 1) or R2 (Type 2) reduces CMRR (Equations (5) and (6)); the analysis in Section 3 does not show any difference between the two biasing networks. Finally, note that the maximum value of Ra is limited by the input impedance of the amplifier (possible potential divider effects reducing the signal amplitude) and the effect on input filter design (time constants, etc.). The analysis in this paper is for networks operated in the passband. However, for a complete filter design, the capacitor sizes should be determined based on the resistor values chosen using the criteria discussed in this paper. The required lower and upper cut-off frequencies determine the Cs and Cp capacitor sizes, respectively. It should be noted that to have equal cut-off frequencies, all the Cs should be equal, and all the Cp should be equal as well. 6. Conclusions Bandpass filter networks are essential for interfacing arrays of electrodes (such as nerve cuff electrodes) to amplifier arrays for applications, such as velocity selective recording (VSR). However, the inclusion of these networks influences the CMRR, crosstalk, and noise performance of such systems. In this paper, an analysis has been provided relating the performance criteria of two commonly used front-end biasing networks to component values. The effect of electrode mismatches is also discussed for both networks. It is shown that the ‘Type 1’ and ‘Type 2’ biasing networks result in a similar performance, provided that certain assumptions are satisfied. The approach taken in the paper is to generalise the design problem as far as possible in order to aid the designer in the complex task of designing an interface network for a particular application. Using reasonable assumptions, the complicated state equations of the complete system are simplified into a manageable set of design equations, which are then verified for accuracy by comparison with the SPICE simulations of the complete system. Finally, a set of three-dimensional plots has been derived, which show how the main parameters of interest (CMRR, crosstalk and noise) depend in a very general way on the circuit component values. The knowledge thus provided to the designer will help in the construction of a first, probably approximate design, that can subsequently be refined by simulation. Author Contributions Conceptualization, S.S., B.M., N.D., N.G., J.P. and J.T.; Formal analysis, S.S. and J.T.; Funding acquisition, J.T.; Methodology, S.S., B.M. and J.T.; Supervision, J.T.; Validation, S.S.; Writing—original draft, S.S.; Writing—review & editing, B.M., N.D., N.G., J.P. and J.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Appendix A Example of the Symbolic Calculation of Common-Mode (CM) Gain Using Matlab The gain at the input of the first amplifier to the common-mode input voltage Vcm, for the ‘Type 1’ structure, is given by the ratio of two polynomials a and b:(A1) Va1Vcm=ab  where a and b are: a = (A2) 36Ga9Gcm2Gd7Ge2 + 210Ga9Gcm2Gd6Ge3 + 462Ga9Gcm2Gd5Ge4 + 495Ga9Gcm2Gd4Ge5 + 286Ga9Gcm2Gd3Ge6 + 91Ga9Gcm2Gd2Ge7 + 15Ga9Gcm2GdGe8 + Ga9Gcm2Ge9 + 8Ga9GcmGd8Ge2 + 120Ga9GcmGd7Ge3 + 462Ga9GcmGd6Ge4 + 792Ga9GcmGd5Ge5 + 715Ga9GcmGd4Ge6 + 364Ga9GcmGd3Ge7 + 105Ga9GcmGd2Ge8 + 16Ga9GcmGdGe9 + Ga9GcmGe10 + 288Ga8Gcm2Gd7Ge3 + 1470Ga8Gcm2Gd6Ge4 + 2772Ga8Gcm2Gd5Ge5 + 2475Ga8Gcm2Gd4Ge6 + 1144Ga8Gcm2Gd3Ge7 + 273Ga8Gcm2Gd2Ge8 + 30Ga8Gcm2GdGe9 + Ga8Gcm2Ge10 + 64Ga8GcmGd8Ge3 + 840Ga8GcmGd7Ge4 + 2772Ga8GcmGd6Ge5 + 3960Ga8GcmGd5Ge6 + 2860Ga8GcmGd4Ge7 + 1092Ga8GcmGd3Ge8 + 210Ga8GcmGd2Ge9 + 16Ga8GcmGdGe10 + 1008Ga7Gcm2Gd7Ge4 + 4410Ga7Gcm2Gd6Ge5 + 6930Ga7Gcm2Gd5Ge6 + 4950Ga7Gcm2Gd4Ge7 + 1716Ga7Gcm2Gd3Ge8 + 273Ga7Gcm2Gd2Ge9 + 15Ga7Gcm2GdGe10 + 224Ga7GcmGd8Ge4 + 2520Ga7GcmGd7Ge5 + 6930Ga7GcmGd6Ge6 + 7920Ga7GcmGd5Ge7 + 4290Ga7GcmGd4Ge8 + 1092Ga7GcmGd3Ge9 + 105Ga7GcmGd2Ge10 + 2016Ga6Gcm2Gd7Ge5 + 7350Ga6Gcm2Gd6Ge6 + 9240Ga6Gcm2Gd5Ge7 + 4950Ga6Gcm2Gd4Ge8 + 1144Ga6Gcm2Gd3Ge9 + 91Ga6Gcm2Gd2Ge10 + 448Ga6GcmGd8Ge5 + 4200Ga6GcmGd7Ge6 + 9240Ga6GcmGd6Ge7 + 7920Ga6GcmGd5Ge8 + 2860Ga6GcmGd4Ge9 + 364Ga6GcmGd3Ge10 + 2520Ga5Gcm2Gd7Ge6 + 7350Ga5Gcm2Gd6Ge7 + 6930Ga5Gcm2Gd5Ge8 + 2475Ga5Gcm2Gd4Ge9 + 286Ga5Gcm2Gd3Ge10 + 560Ga5GcmGd8Ge6 + 4200Ga5GcmGd7Ge7 + 6930Ga5GcmGd6Ge8 + 3960Ga5GcmGd5Ge9 + 715Ga5GcmGd4Ge10 + 2016Ga4Gcm2Gd7Ge7 + 4410Ga4Gcm2Gd6Ge8 + 2772Ga4Gcm2Gd5Ge9 + 495Ga4Gcm2Gd4Ge10 + 448Ga4GcmGd8Ge7 + 2520Ga4GcmGd7Ge8 + 2772Ga4GcmGd6Ge9 + 792Ga4GcmGd5Ge10 + 1008Ga3Gcm2Gd7Ge8 + 1470Ga3Gcm2Gd6Ge9 + 462Ga3Gcm2Gd5Ge10 + 224Ga3GcmGd8Ge8 + 840Ga3GcmGd7Ge9 + 462Ga3GcmGd6Ge10 + 288Ga2Gcm2Gd7Ge9 + 210Ga2Gcm2Gd6Ge10 + 64Ga2GcmGd8Ge9 + 120Ga2GcmGd7Ge10 + 36GaGcm2Gd7Ge10 + 8GaGcmGd8Ge10 b = (A3) 9Ga10Gcm2Gd8 + 120Ga10Gcm2Gd7Ge + 462Ga10Gcm2Gd6Ge2 + 792Ga10Gcm2Gd5Ge3 + 715Ga10Gcm2Gd4Ge4 + 364Ga10Gcm2Gd3Ge5 + 105Ga10Gcm2Gd2Ge6 + 16Ga10Gcm2GdGe7 + Ga10Gcm2Ge8 + 2Ga10GcmGd9 + 90Ga10GcmGd8Ge + 660Ga10GcmGd7Ge2 + 1848Ga10GcmGd6Ge3 + 2574Ga10GcmGd5Ge4 + 2002Ga10GcmGd4Ge5 + 910Ga10GcmGd3Ge6 + 240Ga10GcmGd2Ge7 + 34Ga10GcmGdGe8 + 2Ga10GcmGe9 + 10Ga10Gd9Ge + 165Ga10Gd8Ge2 + 792Ga10Gd7Ge3 + 1716Ga10Gd6Ge4 + 2002Ga10Gd5Ge5 + 1365Ga10Gd4Ge6 + 560Ga10Gd3Ge7 + 136Ga10Gd2Ge8 + 18Ga10GdGe9 + Ga10Ge10 + 90Ga9Gcm2Gd8Ge + 1080Ga9Gcm2Gd7Ge2 + 3696Ga9Gcm2Gd6Ge3 + 5544Ga9Gcm2Gd5Ge4 + 4290Ga9Gcm2Gd4Ge5 + 1820Ga9Gcm2Gd3Ge6 + 420Ga9Gcm2Gd2Ge7 + 48Ga9Gcm2GdGe8 + 2Ga9Gcm2Ge9 + 20Ga9GcmGd9Ge + 810Ga9GcmGd8Ge2 + 5280Ga9GcmGd7Ge3 + 12,936Ga9GcmGd6Ge4 + 15,444Ga9GcmGd5Ge5 + 10,010Ga9GcmGd4Ge6 + 3640Ga9GcmGd3Ge7 + 720Ga9GcmGd2Ge8 + 68Ga9GcmGdGe9 + 2Ga9GcmGe10 + 90Ga9Gd9Ge2 + 1320Ga9Gd8Ge3 + 5544Ga9Gd7Ge4 + 10,296Ga9Gd6Ge5 + 10,010Ga9Gd5Ge6 + 5460Ga9Gd4Ge7 + 1680Ga9Gd3Ge8 + 272Ga9Gd2Ge9 + 18Ga9GdGe10 + 405Ga8Gcm2Gd8Ge2 + 4320Ga8Gcm2Gd7Ge3 + 12,936Ga8Gcm2Gd6Ge4 + 16,632Ga8Gcm2Gd5Ge5 + 10,725Ga8Gcm2Gd4Ge6 + 3640Ga8Gcm2Gd3Ge7 + 630Ga8Gcm2Gd2Ge8 + 48Ga8Gcm2GdGe9 + Ga8Gcm2Ge10 + 90Ga8GcmGd9Ge2 + 3240Ga8GcmGd8Ge3 + 18,480Ga8GcmGd7Ge4 + 38,808Ga8GcmGd6Ge5 + 38,610Ga8GcmGd5Ge6 + 20,020Ga8GcmGd4Ge7 + 5460Ga8GcmGd3Ge8 + 720Ga8GcmGd2Ge9 + 34Ga8GcmGdGe10 + 360Ga8Gd9Ge3 + 4620Ga8Gd8Ge4 + 16,632Ga8Gd7Ge5 + 25,740Ga8Gd6Ge6 + 20,020Ga8Gd5Ge7 + 8190Ga8Gd4Ge8 + 1680Ga8Gd3Ge9 + 136Ga8Gd2Ge10 + 1080Ga7Gcm2Gd8Ge3 + 10,080Ga7Gcm2Gd7Ge4 + 25,872Ga7Gcm2Gd6Ge5 + 27,720Ga7Gcm2Gd5Ge6 + 14,300Ga7Gcm2Gd4Ge7 + 3640Ga7Gcm2Gd3Ge8 + 420Ga7Gcm2Gd2Ge9 + 16Ga7Gcm2GdGe10 + 240Ga7GcmGd9Ge3 + 7560Ga7GcmGd8Ge4 + 36,960Ga7GcmGd7Ge5 + 64,680Ga7GcmGd6Ge6 + 51,480Ga7GcmGd5Ge7 + 20,020Ga7GcmGd4Ge8 + 3640Ga7GcmGd3Ge9 + 240Ga7GcmGd2Ge10 + 840Ga7Gd9Ge4 + 9240Ga7Gd8Ge5 + 27,720Ga7Gd7Ge6 + 34,320Ga7Gd6Ge7 + 20,020Ga7Gd5Ge8 + 5460Ga7Gd4Ge9 + 560Ga7Gd3Ge10 + 1890Ga6Gcm2Gd8Ge4 + 15,120Ga6Gcm2Gd7Ge5 + 32,340Ga6Gcm2Gd6Ge6 + 27,720Ga6Gcm2Gd5Ge7 + 10,725Ga6Gcm2Gd4Ge8 + 1820Ga6Gcm2Gd3Ge9 + 105Ga6Gcm2Gd2Ge10 + 420Ga6GcmGd9Ge4 + 11,340Ga6GcmGd8Ge5 + 46,200Ga6GcmGd7Ge6 + 64,680Ga6GcmGd6Ge7 + 38,610Ga6GcmGd5Ge8 + 10,010Ga6GcmGd4Ge9 + 910Ga6GcmGd3Ge10 + 1260Ga6Gd9Ge5 + 11,550Ga6Gd8Ge6 + 27,720Ga6Gd7Ge7 + 25,740Ga6Gd6Ge8 + 10,010Ga6Gd5Ge9 + 1365Ga6Gd4Ge10 + 2268Ga5Gcm2Gd8Ge5 + 15,120Ga5Gcm2Gd7Ge6 + 25,872Ga5Gcm2Gd6Ge7 + 16,632Ga5Gcm2Gd5Ge8 + 4290Ga5Gcm2Gd4Ge9 + 364Ga5Gcm2Gd3Ge10 + 504Ga5GcmGd9Ge5 + 11,340Ga5GcmGd8Ge6 + 36,960Ga5GcmGd7Ge7 + 38,808Ga5GcmGd6Ge8 + 15,444Ga5GcmGd5Ge9 + 2002Ga5GcmGd4Ge10 + 1260Ga5Gd9Ge6 + 9240Ga5Gd8Ge7 + 16,632Ga5Gd7Ge8 + 10,296Ga5Gd6Ge9 + 2002Ga5Gd5Ge10 + 1890Ga4Gcm2Gd8Ge6 + 10,080Ga4Gcm2Gd7Ge7 + 12,936Ga4Gcm2Gd6Ge8 + 5544Ga4Gcm2Gd5Ge9 + 715Ga4Gcm2Gd4Ge10 + 420Ga4GcmGd9Ge6 + 7560Ga4GcmGd8Ge7 + 18,480Ga4GcmGd7Ge8 + 12,936Ga4GcmGd6Ge9 + 2574Ga4GcmGd5Ge10 + 840Ga4Gd9Ge7 + 4620Ga4Gd8Ge8 + 5544Ga4Gd7Ge9 + 1716Ga4Gd6Ge10 + 1080Ga3Gcm2Gd8Ge7 + 4320Ga3Gcm2Gd7Ge8 + 3696Ga3Gcm2Gd6Ge9 + 792Ga3Gcm2Gd5Ge10 + 240Ga3GcmGd9Ge7 + 3240Ga3GcmGd8Ge8 + 5280Ga3GcmGd7Ge9 + 1848Ga3GcmGd6Ge10 + 360Ga3Gd9Ge8 + 1320Ga3Gd8Ge9 + 792Ga3Gd7Ge10 + 405Ga2Gcm2Gd8Ge8 + 1080Ga2Gcm2Gd7Ge9 + 462Ga2Gcm2Gd6Ge10 + 90Ga2GcmGd9Ge8 + 810Ga2GcmGd8Ge9 + 660Ga2GcmGd7Ge10 + 90Ga2Gd9Ge9 + 165Ga2Gd8Ge10 + 90GaGcm2Gd8Ge9 + 120GaGcm2Gd7Ge10 + 20GaGcmGd9Ge9 + 90GaGcmGd8Ge10 + 10GaGd9Ge10 + 9Gcm2Gd8Ge10 + 2GcmGd9Ge10 where Gx = 1/Rx Due to their complexity, these equations do not provide useful insight into the effects of the various parameters. Consider the effect of the following (reasonable) assumptions: Rai >> Rcmi and Rai >> Rei; Rai >> Rdi; all i(A4) a≈36GaGcm2Gd7Ge10+8GaGcmGd88Ge10  (A5) b≈9Gcm2Gd8Ge10+2GcmGd9Ge10  Hence, the CM gain for the first channel can be expressed as follows:(A6) Va1Vcm≈36GaGcm2Gd7Ge10+8GaGcmGd88Ge109Gcm2Gd8Ge10+2GcmGd9Ge10≈4GaGd=4RdRa  In general, for N = 10, this can be written as:(A7) VaiVcm≈(5−i)(Rd||2R1)R2  Figure 1 Simplified schematic of a typical recording configuration using a MEC fitted to a peripheral nerve. There may be one or more ranks of amplification after the front-end network. Figure 2 Front-end network with (a) ‘Type 1’ biasing arrangement and (b) ‘Type 2’ biasing arrangement. Figure 3 (a) Passband equivalent circuit for thermal noise analysis. This is a ladder expansion of the circuit of Figure 2a, i.e., for a Type 1 circuit. (b) The circuit of (a) with the resistors Ra is removed to reflect the fact that they appear in parallel with much smaller resistors and therefore contribute little to the thermal noise calculation. Figure 5 Noise equivalent circuit of the amplifiers. The input impedance of the amplifiers is assumed to be infinite. Figure 6 Simplified passband equivalent circuit for amplifier current noise analysis applicable to both Type 1 and Type 2 circuits. Figure 7 Examples comparing the approximate equations and simulation results for the ‘Type 1’ and ‘Type 2’ interface networks. Minimum CMRR versus (a) Rd and (b) Ra (for Type 1)/R2 (for Type 2). The nominal component values are: R2 = Ra = 10 MΩ, R1 = 10 kΩ, Rcm = Rd = 1 kΩ. Note that the comparisons between calculation and simulation for the other parameters (i.e., crosstalk, thermal noise and amplifier current noise are not plotted, but the limiting values are quoted in the text). Figure 8 The effect of design parameters on (a) CMRR; (b) crosstalk; (c) thermal noise and (d) current noise gain. This 3D presentation of the material from Section 2 and Section 4 is discussed in Section 5. sensors-22-03450-t001_Table 1 Table 1 Connection matrix A for ‘Type 1’ front-end network. 1 2 … 10 11 12 13 14 20 1 Ge1 + Ga1 0 … 0 −Ge 1 0 0 0 0 2 0 Ge2 + Ga2 … 0 0 −Ge 2 0 0 0 : : : : : : : : : : 10 0 0 … Ge10 + Ga10 0 0 0 0 −Ge 10 11 −Ge 1 0 … 0 Gcm1 + Ge1 + Gd1 −Gd 1 0 0 0 12 0 −Ge 2 … 0 −Gd 1 Ge2 + Gd1 + Gd2 −Gd 2 0 0 13 0 0 … 0 0 −Gd 2 Ge3 + Gd2 + Gd3 −Gd 3 0 : : : : : : : : : : 20 0 0 … −Ge 10 0 0 0 0 Gcm2 + Ge10 + Gd9 sensors-22-03450-t002_Table 2 Table 2 Summary of the equations derived in this section (all Re, Ra, Rd are equal). Description ‘Type 1’ Circuit ‘Type 2’ Circuit Equations No. Common-Mode Gain VaiVcm≈(5−i)RdRa VaiVcm≈(5−i)(Rd||2R1)R2 (5), (6) Crosstalk Between Channels VajVdi={1−Rd2Rcm+9Rdif i=j−Rd2Rcm+9Rdif i≠j VajVdi={Rd||2R1Rd(1−Rd||2R12Rcm+9(Rd||2R1))if i=j−Rd||2R1Rd(Rd||2R12Rcm+9(Rd||2R1))if i≠j (11), (12) Total Thermal Noise Density Va1(rms)=4kT(Rd+2re(Re) (13) Total Input-Referred rms Noise Density va(total)=4kT[Rd+2re(Re)]+vn2+ia2(|Rd+2Re|2+p|Re|2)  (14) sensors-22-03450-t003_Table 3 Table 3 Two-wire impedance measurements of the electrodes as dipoles for an implanted cuff in sheep. Electrodes 2—Wire Impedance Measurements (100 mV, 1 kHz) 1–2 2.4 kΩ/−59° 2–3 2.0 kΩ/−58° 3–4 2.6 kΩ/−59° 4–5 3.3 kΩ/−60° 5–6 3.9 kΩ/−51° 6–7 2.5 kΩ/−47° 7–8 1.7 kΩ/−61° 8–9 1.4 kΩ/−59° 9–10 1.3 kΩ/−60° Reference-1 1.1 kΩ/−48° Reference-10 1.1 kΩ/−48° sensors-22-03450-t004_Table 4 Table 4 Common-mode and differential gain for mismatched common-mode impedances (only Rcms not equal). Structure Common-Mode Gain Differential Mode Gain ‘Type 1’ VaiVcm=(5−i)RdRa+(2.5RdRa(1+4.5RdRcm))(ΔRcmRcm) VaiVdj={1−Rd2Rcm+10Rdif i=j−Rd2Rcm+10Rdif i≠j ‘Type 2’ VaiVcm=(5−i)RdR2+Rd||2R1(4R29)(1+4.5Rd||2R1Rcm)(ΔRcmRcm) VajVdi={Rd||2R1Rd(1−Rd||2R12Rcm+9(Rd||2R1))if i=j−Rd||2R1Rd(Rd||2R12Rcm+9(Rd||2R1))if i≠j sensors-22-03450-t005_Table 5 Table 5 Common-mode and differential gain for mismatched electrode impedances (Rds are not equal but Ras, Rcms are equal). Structure Common-Mode Gain Differential Mode Gain ‘Type 1’ VaiVcm=(5−i)RdiRa VaiVdj={1−Rdi2Rcm+∑x=110Rdxif i=j−Rdi2Rcm+∑x=110Rdxif i≠j ‘Type 2’ VaiVcm=(5−i)RdiR2 sensors-22-03450-t006_Table 6 Table 6 Variables chosen for validation. Parameter Variables Held Constant Swept Variables both circuits CMRR R2 = Ra = 10 MΩ Rd, Ra (or R2 for Type 2) Crosstalk R1 = 10 kΩ Rd, Rcm Thermal noise Rcm = Rd = 1 kΩ Rd Amplifier current noise Rd, Rcm sensors-22-03450-t007_Table 7 Table 7 Summary of amplifier specifications [14]. Parameter Specifications Technology 0.35 µm 4-metal 2-poly CMOS Power supply ±1.5 V Midband Gain 79.7 dB −3 dB frequencies Lower 258 Hz Upper 24.1 kHz CMRR (@3 KHz) 77.5 dB (AV,CM = 1.29) PSRR(@3KHz) VDD 50.57 dB VSS 40.2 dB Adjacent channel interference(crosstalk) <−100.1 dB Total input-referred voltage noise density@3 kHz 7.5 nV/Hz Total input-referred current noise density@3 kHz 0.55 pA/Hz Total input-referred rms voltage noise 1 Hz–31 kHz for a source resistance of 1 kΩ 1.82 uV sensors-22-03450-t008_Table 8 Table 8 Summary of a complete system with Type 1 interface (Ra = 10 MΩ, Rcm = Rd = 1 kΩ, Re = 0). Parameter Calculation Simulation Min(CMRR) (@3 KHz) 65.29 dB 65.08 dB Adjacent channel interference (crosstalk) −20.83 dB −20.81 dB Total input-referred voltage noise density@3 kHz 9.35 nV/Hz 9.32 nV/Hz Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Haugland M. A flexible method for fabrication of nerve cuff electrodes Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Amsterdam, The Netherlands 31 October–3 November 1996 Volume 1 359 360 2. Kawai K. Tanaka T. Baba H. Bunker M. Ikeda A. Inoue Y. Kameyama S. Kaneko S. Kato A. Nozawa T. Outcome of vagus nerve stimulation for drug-resistant epilepsy: The first three years of a prospective Japanese registry Epileptic Disord. 2017 19 327 338 10.1684/epd.2017.0929 28832004 3. Purser M.F. Mladsi D.M. Beckman A. Barion F. Forsey J. Expected budget impact and health outcomes of expanded use of vagus nerve stimulation therapy for drug-resistant epilepsy Adv. Ther. 2018 35 1686 1696 10.1007/s12325-018-0775-0 30143957 4. Metcalfe B.W. Nielsen T.N. de N Donaldson N. Hunter A.J. Taylor J. First demonstration of velocity selective recording from the pig vagus using a nerve cuff shows respiration afferents Biomed. Eng. Lett. 2018 8 127 136 10.1007/s13534-017-0054-z 30603197 5. Metcalfe B.W. Nielsen T. Taylor J. Velocity selective recording: A demonstration of effectiveness on the vagus nerve in pig Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Honolulu, HI, USA 18–21 July 2018 1 4 6. Pflaum C. Riso R.R. Wiesspeiner G. Performance of alternative amplifier configurations for tripolar nerve cuff recorded ENG Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Amsterdam, The Netherlands 31 October–3 November 1996 Volume 1 375 376 7. Koh R.G. Nachman A.I. Zariffa J. Use of spatiotemporal templates for pathway discrimination in peripheral nerve recordings: A simulation study J. Neural Eng. 2016 14 016013 10.1088/1741-2552/14/1/016013 28000616 8. Silveira C. Brunton E. Spendiff S. Nazarpour K. Influence of nerve cuff channel count and implantation site on the separability of afferent ENG J. Neural Eng. 2018 15 046004 10.1088/1741-2552/aabca0 29629880 9. Aristovich K. Donegá M. Blochet C. Avery J. Hannan S. Chew D.J. Holder D. Imaging fast neural traffic at fascicular level with electrical impedance tomography: Proof of principle in rat sciatic nerve J. Neural Eng. 2018 15 056025 10.1088/1741-2552/aad78e 30070261 10. Yoshida K. Kurstjens G. Hennings K. Experimental validation of the nerve conduction velocity selective recording technique using a multi-contact cuff electrode Med. Eng. Phys. 2009 31 1261 1270 10.1016/j.medengphy.2009.08.005 19762269 11. Taylor J. Donaldson N. Winter J. Multiple-electrode nerve cuffs for low-velocity and velocity-selective neural recording Med. Biol. Eng. Comput. 2004 42 634 643 10.1007/BF02347545 15503964 12. Donaldson N. Rieger R. Schuettler M. Taylor J. Noise and selectivity of velocity-selective multi-electrode nerve cuffs Med. Biol. Eng. Comput. 2008 46 1005 1018 10.1007/s11517-008-0365-4 18696136 13. Metcalfe B.W. Chew D.J. Clarke C.T. Donaldson N.D.N. Taylor J.T. A new method for spike extraction using velocity selective recording demonstrated with physiological ENG in Rat J. Neurosci. Methods 2015 251 47 55 10.1016/j.jneumeth.2015.05.003 25983203 14. Rieger R. Taylor J. Demosthenous A. Donaldson N. Langlois P.J. Design of a low-noise preamplifier for nerve cuff electrode recording IEEE J. Solid-State Circuits 2003 38 1373 1379 10.1109/JSSC.2003.814437 15. Rahal M. Winter J. Taylor J. Donaldson N. An improved configuration for the reduction of EMG in electrode cuff recordings: A theoretical approach IEEE Trans. Biomed. Eng. 2000 47 1281 1284 10.1109/10.867963 11008430 16. Casas O. Pallas-Areny R. Optimal bias circuit for instrumentation amplifiers Proceedings of the 14th Imeko World Congress Tampere, Finland 2–6 June 1997 143 148 17. Stein R. Pearson K. Predicted amplitude and form of action potentials recorded from unmyelinated nerve fibres J. Theor. Biol. 1971 32 539 558 10.1016/0022-5193(71)90155-X 5571123

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==== Front Int J Environ Res Public Health Int J Environ Res Public Health ijerph International Journal of Environmental Research and Public Health 1661-7827 1660-4601 MDPI 10.3390/ijerph19095292 ijerph-19-05292 Article Focused-Attention Meditation Improves Flow, Communication Skills, and Safety Attitudes of Surgeons Chen Hao 12† https://orcid.org/0000-0001-9257-4519 Liu Chao 23† Zhou Fang 4† Cao Xin-Yi 5 Wu Kan 26 https://orcid.org/0000-0002-1292-0758 Chen Yi-Lang 7 Liu Chia-Yih 8 Huang Ding-Hau 9 Chiou Wen-Ko 7810* Tchounwou Paul B. Academic Editor 1 School of Film and Communication, Xiamen University of Technology, Xiamen 361021, China; haochen19606@163.com 2 Business Analytics Research Center, Chang Gung University, Taoyuan 33302, Taiwan; victory666666@126.com (C.L.); kan@gap.cgu.edu.tw (K.W.) 3 School of Journalism and Communication, Hua Qiao University, Xiamen 361021, China 4 Department of Economic and Management, Suzhou Vocational Institute of Industrial Technology, Suzhou 215000, China; zhouf@siit.edu.cn 5 Clinical Neurocognitive Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; rekixinyicao@163.com 6 Department of Orthopaedic Surgery, Chang Gung Memorial Hospital, Taoyuan 33302, Taiwan 7 Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 24301, Taiwan; ylchen@mail.mcut.edu.tw 8 Department of Psychiatry, Chang Gung Memorial Hospital, Taipei 10507, Taiwan; liucy752@cgmh.org.tw 9 Institute of Creative Design and Management, National Taipei University of Business, Taoyuan 22058, Taiwan; hau1012@gmail.com 10 Department of Industrial Design, Chang Gung University, Taoyuan 33302, Taiwan * Correspondence: wkchiu@mail.cgu.edu.tw † These authors contributed equally to this work. 27 4 2022 5 2022 19 9 529231 3 2022 24 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Objective: Patient safety is a worldwide problem and a focus of academic research. Human factors and ergonomics (HFE) is an approach to improving healthcare work systems and processes. From the perspective of the cognitive ergonomics of HFE, the aim of this study is to improve the flow level, communication skills, and safety attitudes of surgeons through focused-attention meditation (FAM) training, thus helping to reduce adverse clinical events. Methods: In total, 140 surgeons were recruited from three hospitals in China and randomly divided into two groups (FAM group and control group). The FAM group received 8 weeks of FAM training, while the control group was on the waiting list and did not receive any interventions. Three scales (WOLF, LCSAS, and SAQ-C) were used to measure the data of three variables (flow, communication skills, and safety attitude), respectively, at two times, before and after the intervention (pre-test and post-test). The incidence of adverse events during the intervention was also collected for both groups. Results: The ANOVA results showed that all three variables had a significant main effect of time and significant interactions between time and group. The independent-sample T-test results showed that the incidence of adverse events during the intervention was significantly lower in the FAM group than in the control group. Conclusions: The intervention of FAM could significantly improve surgeons’ flow levels, communication skills, and safety attitudes, potentially helping to reduce adverse clinical events. focused-attention meditation flow communication skills safety attitude clinical adverse events patient safety Ministry of Science and Technology (MOST)109-2221-E-182-033-MY3 This study was supported by the Ministry of Science and Technology (MOST) of Taiwan (Grant MOST 109-2221-E-182-033-MY3). ==== Body pmc1. Introduction Patient safety and medical errors have become a worldwide issue and a focus of academic research. The focus and scope of research is broad, ranging from analyzing the causes of medical errors and shortcomings in the clinical process to testing strategies or measures for improvements in patient care and management [1]. Over the past decade, significant effort and resources have been devoted to preventing medical errors and improving patient safety. Human factors and ergonomics (HFE) are key systems for improving the quality of patient care and patient safety [2]. Past studies have shown that many patient safety incidents are related to a lack of attention to human factors and ergonomics (HFE) in the design and implementation of technology, processes, workflows, jobs, teams, and socio-technical systems [3]. Experts and scholars have also designed and developed a series of products, standards, and systems for HFE in healthcare [4]. However, there are still many phenomena that endanger patient safety; medical accidents also occur occasionally, and increasing evidence shows that human factors are the key features of adverse events [4]. In complex healthcare systems, it is inevitable that even experienced, motivated, skilled, and reliable individuals make mistakes because, due to the human factor, mistakes usually occur when systems and technologies do not match the characteristics of the person [5]. Therefore, from the perspective of the cognitive ergonomics of HFE, this study conducted psychological interventions to find a simple and easy method to train surgeons to better match their own characteristics and skills with external challenges, improve their concentration and engagement at work, and enhance their communication skills and safety attitudes. 1.1. Focused-Attention Meditation Meditation consists of a set of mental exercises used to develop a cognitively and emotionally balanced mind, and its development and practice date back 4000 years [6]. Over the past 50 years, there has been increasing interest in meditation, largely because of its effectiveness in improving emotional regulation [7]. Meditation is often conceptualized as a series of attentional and emotional regulation exercises [8]. There are many ways to practice meditation, and a common way to classify this large family of practices is based on what meditators do from their first-person perspective: focused-attention meditation (FAM) and open-monitoring meditation (OMM) [9]. While FAM has a clear focus on objects such as breathing, OMM practice (e.g., mindfulness meditation) has no clear focus, and the task is to be constantly aware of what is happening and to return to this monitoring state when drawn to something else [10]. The purpose of FAM is to resist the outside world and no longer receive external information, while that of OMM is to be inside, to treat and restore the current self-state [9]. FAM emphasizes attention maintenance and aims to consciously induce a state of relaxation, while OMM focuses on monitoring attention and emphasizes acceptance without judgment [9,11]. In this study, FAM was chosen as the intervention method because FAM simply focuses on the improvement of attention, while OMM maintains the awareness and monitoring of internal and external stimuli while maintaining attention. During FAM, the meditator brings her/his attention to an object, such as breathing, and then uses this attention to monitor whether the attention is still there; once the meditator realizes that attention has strayed, he or she returns to the object in focus, minimizing any further mental elaboration [12]. It is worth noting that this is in contrast to our habitual reactions, in which we tend to feel frustrated by our inability to stay focused, leading to feelings of disgust [13]. By aversive, we refer to emotional states experienced as aversive, while pleasant refers to the opposite. In other words, meditation can reduce aversive feelings by developing mental habits that reduce this amplification and catastrophizing process, and this in itself may be one of the most important beneficial mechanisms through which FAM relieves mood and stress [14,15]. Moye and van Vugt [16] found that the ability to maintain attention was significantly improved after FAM practice than before, and speculated that the improvement in mood regulation observed after meditation was due to the ability to maintain focus. A series of studies by Chan et al. has confirmed that FAM affects a series of attention-related learning and cognitive processes. FAM establishes a state of enhanced cognitive control, and enhances the effect of top-down control on sequence-learning based on the control characteristics of attention [12]. FAM may be associated with enhanced cognitive control to facilitate the development of a more efficient stimulus–response process compared to other forms of attentional task induction [8,10]. Many studies have explained the mechanism through which FAM enhances attention from a neurological perspective. Irrmischer et al. [17] found that the effect of FAM on attention was associated with greater control, and FAM strongly suppressed the long-range temporal correlations (LRTC) of neuronal oscillations relative to eyes-closed rest. The ability to reduce LRTC during meditation increased, which was associated with maintaining focus [17]. Manna et al. [18] found that the functional reorganization of brain activity patterns for attention and cognitive monitoring occurred during FAM practice. In a study by Yoshida et al. [14], the FAM group showed significantly higher P3 amplitude and shorter response time to target T stimulus during the task; by contrast, no such correlations were observed in the control group. These findings provide direct evidence of the effectiveness of FAM training. Surgeons need to maintain a high level of concentration while performing surgery, and they also need channels to relieve the intense stress and negative emotions involved in such a high-intensity job; therefore, FAM practice may help them. 1.2. Flow and Focused-Attention Meditation Flow refers to a mental state experienced by being fully engaged and deeply immersed in the task or activity at hand, in which people are fully engaged in the activity and gain many positive experiences [19]. Csikszentmihalyi [20] believed that flow is a positive emotion and experience related to a task. Flow refers to the mental state in which an individual uses his or her skills to complete a series of challenges and achieve a goal. In this process, individuals constantly receive positive feedback and adjust their behavior according to this feedback [21]. Flow can prompt an individual to show a strong interest in an activity or thing and motivate them to participate in it [22]. What FAM and flow have in common is a high degree of concentration. FAM is an effective training method for concentration. Individuals with higher levels of concentration are more likely to enter the flow state [23]. Bakker [24] applies flow to work situations. According to flow’s attribute description, flow is most likely to occur when the challenge of a situation is balanced with a person’s ability to cope with this challenge [20]. Analogously, in work situations, employees experience work-related flow when their work needs are matched with their skills [25]. Work-related flow is a peak experience generated by individuals at work, characterized by clear goals, focus, and matching of skills with challenges [24]. The nature of surgeons’ work makes it easier for them to experience flow. First, the goal of the surgeon’s job is clear: to treat patients and remove and repair diseased tissue. Secondly, surgeons need to maintain a high degree of concentration in their work. Thirdly, the complexity of surgery poses significant challenges, requiring surgeons to constantly improve their skills. 1.3. Communication Skills and Focused Attention Communication and teamwork can be complex skills to apply in the operating room, as the members of operating-room teams vary by type of surgery [26]. Communication is the process of information exchange between people. Surgery is an important means of eradicating or effectively treating some diseases, and it is the embodiment of medical technology and medical skill [27]. Effective communication between surgeons and other medical workers and between surgeons and patients is the basis for improving medical quality and achieving the expected results of surgery [28,29]. Therefore, surgeons need to have good communication skills. Surgery requires the surgeon to work with nurses and anesthesiologists. Different medical specialties have different working styles, and surgeons must have a high degree of responsibility, respect, and understanding of the nature and characteristics of the work of other medical staff [30]. Surgeons should establish a harmonious working environment, in which all colleagues display a positive working attitude, support and cooperate with each other, do not shirk responsibility, and analyze and solve problems directly, so as to ensure smooth operation and better embody the idea of patient-centered medicine [31]. When people communicate, they mobilize an ability to coordinate their attention with that of others, which is called joint attention [32]. Joint attention is usually based on visual attention to define social coordination following another person’s gaze, adopting common reference points to operate, and on using the direction of one’s own gaze or position to determine, with another person, the potential of common reference points [33]. According to the theory of joint attention, as visual attention ability improves, visual attention develops into the ability to coordinate mental attention with others [32]. Increased focus helps to promote joint attention, which, in turn, helps to improve communication [34]. Many previous studies have also confirmed the effect of attention on communication skills. Karnieli-Miller et al. [35] found that the higher the concentration levels of medical students, the better their clinical communication skills. The reason is that in communication, we must always pay attention to the facial expression, voice, intonation, and emotional changes of the communication object, and focus on practice involves awareness of the moment [36]. People with high levels of focus are more effective at capturing details and have keen insight into emotions and affect, so highly focused people are more effective at clinical communication [37]. 1.4. Patient Safety and Safety Attitude The World Health Organization (WHO)’s World Alliance for Patient Safety and the International Patient Safety Goals (IPSG) recognize patient safety as part of a global strategy aimed at minimizing adverse events and eliminating preventable harm in healthcare systems [38]. Patient safety is defined as “the avoidance and prevention of patient injury or adverse events resulting from medical services” [39]. Patient safety should be guaranteed in everyday practice because it improves the quality of care, ensures correct diagnosis, prevents nosocomial infections and medication errors, and ultimately provides correct management [40,41]. The growing recognition that patient safety is a key to the quality of healthcare products has contributed to the importance of a patient safety culture in healthcare organizations [42]. An organization’s safety culture is the product of individual and group values, including attitudes, perceptions, competencies, and behavior patterns that determine commitment to the organization’s health and safety management [43]. Safety attitudes include six major patient safety factors, namely, teamwork atmosphere, safety atmosphere, job satisfaction, management perception, working conditions, and stress perception [44]. Safety attitudes help to identify weaknesses that may exist in clinical settings and facilitate quality improvement interventions and reductions in medical errors [45]. In summary, communication, work stress, and job satisfaction are important factors influencing safety attitudes [44]. FAM can help relieve stress, regulate mood, and reduce work stress [14,15]. Improved concentration makes surgeons more focused on the work at hand, less likely to be distracted, more likely to enter the state of flow, experience pleasure, and, thus, improve job satisfaction. Increased focus also improves communication skills, which in turn helps achieve effective teamwork [37]. Therefore, FAM practice may be a simple and effective intervention to help improve the safety attitudes of surgeons. 1.5. Research Purpose and Hypotheses The purpose of this study is to improve flow levels, communication skills, and safety attitudes among surgeons through FAM intervention. Based on the above literature, this study proposes the following hypotheses: Hypothesis 1 (H1). FAM practice will significantly improve the flow level, communication skills, and safety attitudes of subjects in the experimental group. Hypothesis 2 (H2). Through the intervention of FAM practice, the experimental group will show better patient safety performance than the control group. 2. Method 2.1. Participants Subjects in this study were recruited from the surgical departments of three hospitals in China, and a total of 140 qualified subjects participated in and completed the study. The subjects were randomly divided into two equal groups, the FAM group and the control group, with 70 participants in each group. Table 1 shows the demographic information of the subjects. To avoid the effect of gender on the results, we matched the gender composition between the two groups, and there was no significant difference between the two groups in age composition, sex ratio, or other demographic factors. 2.2. Instruments Work-related Flow Inventory (WOLF). This is a 12-item self-report scale developed by Bakker [24]. Based on the conceptual characteristics of work-related flow, this scale consists of three dimensions (each dimension contains four items): concentration on task, clear goals, and challenge–skill balance. A five-point Likert scale was used to measure the levels of flow characteristics experienced, ranging from 1 (never) to 5 (always), with higher scores indicating higher work-related flow levels. The Chinese version of WOLF used in this study was translated by Gu et al. [46]. The Cronbach’s alpha of WOLF in this study was 0.84. Liverpool Communication Skills Assessment Scale (LCSAS). This scale was developed by Humphris and Kaney [47] to measure the communication skills of doctors. The scale has 12 items in total, including five dimensions: introduction, nonverbal behavior, respect and empathy, questioning, and giving information. A four-point scale was used: 1 = unacceptable, 2 = poor, 3 = acceptable, and 4 = good. The scale is widely used in clinical practice to assess physicians’ communication skills, and the literature supports LCSAS as a reliable tool with acceptable reliability and validity [48]. The Chinese version of LCSAS used in this study was translated by Liu et al. [49]. The Cronbach’s alpha of LCSAS in this study was 0.89. Safety Attitudes Questionnaire-C (SAQ-C). The scale was developed by the University of Texas and has a reliability of 0.9 [50]. SAQ has 32 items across five dimensions: teamwork climate, safety climate, job satisfaction, perception of management, and working conditions. The questions were answered on a five-point Likert scale (1 = strongly disagree, 2 = slightly disagree, 3 = neutral, 4 = slightly agree, and 5 = strongly agree). SAQ-C is a reliable tool for eliciting provider attitudes about medical safety [51]. The Chinese version of SAQ-C used in this study was translated by Lee et al. [52]. The Cronbach’s alpha of SAQ-C in this study was 0.91. Clinical Adverse Events (CAE). We examined the following five kinds of higher-frequency adverse event in clinical operation: surgical site infection, urinary tract infection, ventilator-associated pneumonia, medication errors, and dressing mistakes [53]. This was a self-report scale; the participating surgeons rated the frequency of all adverse events that occurred during the trial. The frequency of adverse events was described using a six-point Likert scale from 1 (daily) to 6 (never), with a higher score indicating a lower incidence of adverse events. 2.3. FMA Practice Subjects in the FAM group underwent 55 min of FAM practice intervention three times a week for a total duration of 8 weeks. The practice site was located in a meditation yoga practice room, which was spacious, quiet, and easily accessible. Due to the busy work schedule of surgeons, the FAM meditation practice was conducted every night on weekdays and all day on weekends. Subjects chose to participate three times a week according to their own schedule. The meditation practice was conducted by two instructors with more than 3 years of experience in FAM instruction each. The instructors did not know the purpose of the study, the specific arrangement of the experiment, and which participants were involved in the study in each activity. Each meditation practice was observed and recorded by a researcher who did not interfere with the practice. Each 55-min meditation practice included the following procedures: A 10-min period of instructor guidance, 35 min FAM practice (with a 5-min break), and 10 min exchanging experiences and discussion. The instructor taught meditation techniques in the 10 min guidance session prior to meditation, and helped participants relax and ease into the meditation state. The specific operation methods of FAM for 30 min are as follows: (1) Adjust to a comfortable sitting position to relax the body and mood; (2) choose a point of focus, which can be breathing or chanting mantras, or anything else; (3) focus all your attention on the point, feel and observe it, and let go of other thoughts and feelings; (4) if there is a distraction, when you notice it, transfer your attention to the point and continue to observe and feel it. After completing the 15-min meditation, take a 5-min break and meditate for the next 15 min. The 10-min discussion time after the meditation was used for participants to communicate about the meditation, so that the instructor could understand the participants’ experience of meditation and answer their questions accordingly. 2.4. Procedue A 2 (group) × 2 (time) parallel randomized controlled trial design was used in this study, in which the intervention condition was FAM practice and the control condition was waiting. The first test time node was the baseline before the experiment, and the second test time node was the level after the intervention. We advertised for FAM practice on the internal network of three hospitals in China. The recruiting advertisement said that there was a study on meditation to improve concentration and offered a free meditation-training program to help improve concentration, regulate emotions, and reduce work stress. Interested surgeons were invited to sign up. FAM training was free for 8 weeks and aimed to improve concentration, mood and relaxation. The sample size was determined by G*Power. Two groups of four scales were used for the measurements, at α = 0.05 and 80% power, f = 0.3, which was the medium effect size of ANOVA with repeated measures. The recommended sample size was 100, and we expected an attrition rate of 20% from pre-test to post-test, so we attempted to recruit at least 120 participants. After screening, our pre-test sample included 154 participants, of whom 140 completed the post-test. Figure 1 depicts the experimental process and the flow chart of the study. The inclusion criteria of subjects were: (1) Doctors in surgical departments; (2) at least 2 years of related working experience; (3) aged between 25 and 55; (4) agreed to participate in this study and signed informed consent. Exclusion criteria were: (1) History of mental illness or mental disorder; (2) have taken psychotropic drugs in the past 2 years, or are currently using psychotropic drugs; (3) have received any form of psychological intervention in the past 2 years; (4) have any form of meditation training experience. In this study, random sequence codes generated by SPASS 22 software were used for random grouping. A list of codes labeled “Group A” and “Group B” was given to participants who were randomly assigned to either group A or group B in a 1:1 allocation ratio. Group A was the experimental group and immediately started FAM practice, while group B was the control group waiting to participate in the next practice. Subjects, data analysis staff, and other researchers participating in the study were not informed of the details of the grouping and the corresponding relationships before the completion of the experimental procedure and data analysis. The study was therefore double-blind. Each participant signed a subject consent form to ensure they understood and agreed to participate in the study before proceeding. Participants were informed that they had the right to terminate their participation in the study without any reason, at any time, without prejudice against their legal rights and interests. Researchers could also pause the study if necessary. The purpose of the pre-test was to establish a baseline for the experiment. Prior to the start of the entire intervention program, the subjects signed the subject consent and conducted the scale evaluation of the pre-test. The pre-test included demographic information and three scales, WOLF, LCSAS, and SAQ-C, which took approximately 40 min to answer. The total duration of the intervention was 8 weeks. There was a post-test at the end of the entire intervention, at which point the participants completed three scales (WOLF, LCSAS, and SAQ-C) again. Furthermore, since participants were asked to recall the approximate frequency of adverse events during the 8-week intervention period based on their memory, CAE data were collected. To encourage participants to truthfully report their rate of adverse events, they were allowed to use nicknames instead of their real names. The time to answer the post-test questionnaire was also approximately 40 min. Finally, the researchers explained to the participants the real purpose of the study and thanked them. This study was approved by the Ethics Committee of Chang Gung University and in accordance with the ethical guidelines. 2.5. Data Analysis In this study, IBM SPSS 22 software was used for statistical analysis. Descriptive statistics were used to describe the characteristics and distribution of subjects’ demographic data and experimental data. ANOVA with repeated measures was used to compare the differences before and after intervention and the differences between groups. Independent-sample T test was used to compare the differences in the rate of adverse events between the two groups. The significance level was set at 0.05. 3. Result This study consisted of three 2 (group type: FAM, control) × 2 (time: pre-test, post-test) ANOVAs with repeated measures. The results of descriptive statistics and paired-sample T tests are shown in Table 2, and the ANOVA results are shown in Table 3 and Figure 2. The p-values of the Box’s test, Mauchly’s test, and Levene’s test were all greater than 0.05, indicating that these data were suitable for ANOVA. In terms of flow, communication skills, and safety attitudes, there were a significant main effect of time and significant interactions between time and group, but no significant main effect of group (see Table 3). These results indicate that the FAM intervention significantly improved participants’ flow levels, communication skills, and safety attitudes, so Hypothesis 1 was supported. The incidence of CAE during FAM intervention was reported post-test (see Table 1). The independent-sample T-test results showed a significant difference in CAE scores between the two groups (p = 0.003, Std. error = 0.067). The CAE score of the FAM group was significantly higher than that of the control group, indicating that the incidence of adverse events within 8 weeks of the experimental intervention was lower in the FAM group than in the control group, thus supporting Hypothesis 2. 4. Discussion 4.1. FAM Improves Flow Levels The results of this study found that the intervention of FAM significantly improved the flow level of the subjects. FAM and flow experience have some common characteristics, in that they both emphasize the importance of being present [54]. Flow requires a very concentrated moment of attention and unintentionally focuses on a specific task [55]. FAM may create the basic conditions for flow experience. For this reason, many scholars suggest that focusing on the present is an effective strategy for achieving flow. Csikszentmihalyi [20] explained that flow experience is due to exceptionally strong concentration within a limited stimulus area, and present consciousness is the common feature of focused meditation and flow experience. Turnbull et al. [56] found that subjects with higher concentration levels were more likely to experience flow. Their study suggests that concentration may be a catalyst for flow, that the changes in attention experienced by participants are positively correlated with changes in flow, and that FAM interventions can effectively promote flow experiences. Some evidence of causality in the attention–flow relationship was obtained in studies of athletes, which found that FAM interventions may increase flow experiences [57]. Athletes in the FAM training program experienced higher levels of flow than before, as well as higher flow levels than athletes who did not take part in meditation training [58]. Some scholars explain this phenomenon from the perspective of neurocognitive function. Weber et al. [59] argued that flow experience is related to the synchronization of the attention network and the reward network. In flow experience, the attention network associated with flow experience discharges synchronously with the reward network. Klasen et al. [60] also found, in a fMRI (functional magnetic resonance imaging) study of flow experience, that as flow experience decreased in video game players, the synchronization between the attention network and the reward network also weakened, further confirming that flow experiences are related to the synchronization between the attention network and the reward network. 4.2. FAM Improves Communication Skills The results of this study suggested that the FAM intervention significantly improved the subjects’ communication skills. First, attention can indirectly influence clinical communication skills through cognitive reappraisal. Attention is the awareness of the body’s feelings, emotions, mental representations, perceptual experiences, and cognitive reappraisal [37]. This awareness enhances concentration and cognitive functions, reduces automated responses, relieves stress, and reduces redundant and negative thinking modes, thus reducing the difficulty of emotional adjustment and increasing the use of cognitive reappraisal strategies [37]. Secondly, according to the theory of social emotional choice, when individuals are aware of the time limitations, their emotional goals take precedence, that is, they focus their attention on the present and have positive cognitive preferences, so as to produce positive cognitive processing [61]. Emotional self-regulation and control is the foundation of communication with patients, and surgeons may encounter in the process of clinical operation all kinds of problems and frustrations, such as puncture failure or medication errors and other adverse clinical events [62]. When doctors with high concentration skills show negative emotions, they can flexibly use emotion regulation strategies to adjust their psychological state through cognitive reappraisal, so as to fundamentally improve their ability to communicate with patients [63,64]. 4.3. FAM Improves Safety Attitudes This study found that FAM intervention significantly improved the safety attitudes of surgeons. At present, society places increasing demands on the professional and personal ability of surgeons [65]. Surgeons have to face increasing pressure and challenges. If they are in this pressured working state for a long time, they are prone to negative emotions, which make them unable to devote themselves to their work in the best state and increase the risk of medical safety issues [66]. Studies have shown that FAM can help surgeons focus on the needs of patients, improve practical problem-solving and awareness of their own state, help reduce stress, and reduce adverse medical events [67]. First, training helps improve surgeons’ concentration and emotional regulation, enabling them to focus on the work at hand, effectively deal with various disturbances and efficiently complete tasks. When surgeons face patient complaints, accusations can be dealt with in a peaceful state of mind and with an optimistic attitude to solve the problem [68]. Second, awareness training can reduce the pressure surgeons place on themselves, which can enable surgeons to discover their inner sense of time-pressure, release their dissatisfaction, maintain a peaceful mindset, and improve their sense of professional interest and reduce job burnout at work, so as to help them to develop a more positive, healthy attitude to work and improve their perceptions of and attitudes towards stressful events [69]. In addition, training improves subjects’ communication skills, which, in turn, enhances teamwork among healthcare professionals and facilitates the formation of supportive relationships among team members. Through mutual assistance, mutual support and reminders among team members, professionals identify problems at work in a timely manner and deal with them with the strength of their team [70]. Effective communication and assistance between team members can effectively improve work efficiency and safety, create a positive safety culture, and improve safety attitudes [71]. 4.4. FAM May Help Reduce Adverse Events Errors in surgeons’ work involve perceptual errors, judgment errors, and action errors, which are the direct causes of adverse clinical events [72]. Perceptual errors are usually caused by inadequate psychological preparation, excessive emotional tension and paralysis, low perceptual level, distraction, and slow reactions, among others. Perception errors, lack of experience, and poor resilience often lead to errors in judgment [73]. Perception errors and judgment errors further lead to operational errors, resulting in adverse events [74]. During a long operation, as the workload increases, the surgeon’s perception process undergoes a series of changes. Attention is a mental state that always accompanies the cognitive process [75]. It seems to be a kind of selective filter for concentration, which enables people to input information selectively and focus their attention on the information to be input, processed, extracted, and output [75]. However, people’s ability to process information at the same time is limited. If the input information is too large, people’s thinking enters a state of chaos, and, if coupled with low quality of information or interference by objective conditions, concentrated attention is reduced [75]. In specific stages of surgery, due to surges of information, attention capacity is limited, so that surgeons experience difficulties in their distribution and transfer of attention [76]. The narrow scope of attention and the interference of irrelevant stimuli place information beyond the attentional capacity of surgeons [53]. Obviously, in such a state, surgeons’ cognitive processes are disrupted. Working under high load can make surgeons nervous and anxious, which makes it difficult for them to carry out operations as normal [12]. When emergent, unexpected, complex, urgent, and dangerous emergency situations appear, they not only increase the workload of surgeons, but also increase their psychological load [77]. At this point, the surgeon’s mind is often too tense, and their mood can become extremely unstable [78]. When an emergency exceeds the surgeon’s ability to respond, it can lead to a sharp decline in their ability to work, often in the form of decreased perception, reduced attention span, undesired omissions, and even the inability to determine what to do and to “turn a blind eye” [79]. Mind-wandering is the act of diverting attention from work tasks to unrelated things. Spontaneous mind-wandering is often associated with self-reflective states that lead to negative processing of the past, worries and fantasies about the future, and the disruption of primary task performance [80]. While the key of FAM is concentration, FAM can help surgeons to learn to monitor when mind-wandering occurs, which can improve the performance of tasks that require sustained attention and intense focus [10]. FAM can reduce mind-wandering, improve cognitive performance, improve participants’ ability to maintain attention in the presence of external distractions, help improve concentration on tasks, and reduce performance degradation due to task-unrelated distractions [81]. Meditation training increases awareness and decreases mind-wandering, which results in optimal actions and fewer adverse events only when the subject is fully engaged in the present moment [82]. 4.5. Research Limitations and Future Studies This study explores the positive effects of interventions on improving flow, communication skills, and safety attitudes among surgeons, and draws some innovative and practical conclusions. However, due to reasons of manpower, material resources, and time, there are also the following limitations: (1) The subjects of this study were all surgeons. Whether the results of this study can be extended to other medical and health practitioners needs further investigation and verification; and (2) in this study, self-reported questionnaires were used, and the frequency of reported adverse events may be reduced when surgeons perform self-evaluation. Based on the limitations of this study, the following suggestions are put forward for future research: (1) Future studies should improve and enrich data collection and measurement tools and integrate multiple evaluation methods, such as third-party evaluation and behavioral observation. Furthermore, future research should ensure that the data reflect the situations of subjects more truly and effectively, and include the performance of a more comprehensive evaluation of various variables to better meet the research needs; and (2) the structural equation model and other investigation and research methods should be used to further explore the relationships between variables and clarify the deep influence mechanisms acting on each variable. 5. Conclusions This study found the following. (1) FAM intervention can significantly improve flow, communication skills, and safety attitudes among surgeons. (2) FAM intervention may help to reduce the rate of adverse clinical events. The specific mechanism observed in this study was as follows: (1) FAM enhanced the ability of surgeons to control their own attention; and (2) FAM can help relieve negative emotions, such as stress and anxiety. (3) FAM improved the flow level of the subjects and made them more likely to experience flow at work. The pleasant experiences generated by flow further offset the negative emotions of the subjects, and stimulated work motivation. (4) FAM improves subjects’ communication skills and safety attitudes, improves teamwork, and contributes to a safe working atmosphere. The above points may help surgeons reduce errors in perception, judgment, and action in their work, thus reducing the incidence of adverse clinical events. Acknowledgments The authors thank all the participants in this study. The participants in the psychology experiment understood the purpose and content of the experiment and participated in the experiment with voluntary consent. Participants could discontinue their participation in the experiment at any time without penalty. Author Contributions H.C.’s main contributions were in the research design and the writing of the manuscript’s Methods and Discussion sections; C.L. contributed to the collection and analysis of the literature and the writing of the manuscript’s Introduction; F.Z. contributed to the statistical analysis of the data and the writing of manuscript’s Results; the data results were explained by K.W. and Y.-L.C.; C.-Y.L. and X.-Y.C. were responsible for the data collection; D.-H.H. participated in the discussion and conception of the study; W.-K.C. conceived and designed the study. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the Ethics Committee of Chang Gung University (IRB No: 202001014B0D001), and all subjects signed informed consent. Informed Consent Statement The subject voluntarily agrees to participate in the study and has the right to terminate or withdraw from the study without any reason at any point during the study period, without affecting his/her legal rights. Data Availability Statement The data in the research are not publicly available. If there is a reasonable request for data viewing and use, the corresponding author can be contacted. Conflicts of Interest There is no other conflict of interest of this study. Figure 1 Procedure flow chart of the study. Figure 2 Comparison between FAM group and control group. Errors bars: 95% confidence interval; CAE: clinical adverse events; FAM: focused-attention meditation; LCSAS: Liverpool Communication Skills Assessment Scale; SAQ-C: Safety Attitudes Questionnaire-C; WOLF: work-related flow inventory. ijerph-19-05292-t001_Table 1 Table 1 Demographic characteristics of participants. Characteristic Total FAM Group Control Group Age (SD) 40.56 (7.26) 39.19 (7.78) 41.94 (7.62) Male (%) 103 (73.6%) 50 (71.4%) 53 (75.7%) Female (%) 37 (26.4%) 20 (28.6%) 17 (24.3%) Note. No demographic characteristic was significantly different among the two groups. FAM: Focused-attention meditation. ijerph-19-05292-t002_Table 2 Table 2 Results of descriptive statistics. Group Measure Mean (SD) Pre Post FAM WOLF 3.166 (0.709) 3.590 (0.652) LCSAS 2.121 (0.670) 2.523 (0.713) SAQ-C 3.049 (0.648) 3.454 (0.751) CAE 5.155 (0.383) Control WOLF 3.247 (0.602) 3.310 (0.688) LCSAS 2.264 (0.688) 2.203 (0.631) SAQ-C 3.127 (0.681) 3.205 (0.682) CAE 4.957 (0.402) Note. CAE: clinical adverse events; FAM: focused-attention meditation; LCSAS: Liverpool Communication Skills Assessment Scale; SAQ-C: Safety Attitudes Questionnaire-C; WOLF: work-related flow inventory. ijerph-19-05292-t003_Table 3 Table 3 Results of ANOVA. Measure Variable F p η2 WOLF Time ** 9.691 0.002 0.066 Group 1.539 0.217 0.011 Time × Group * 5.332 0.022 0.037 LCSAS Time * 4.249 0.041 0.030 Group 1.233 0.269 0.009 Time × Group ** 7.833 0.006 0.054 SAQ-C Time ** 10.013 0.002 0.068 Group 1.053 0.307 0.008 Time × Group * 4.545 0.035 0.032 Note. * p < 0.05; ** p < 0.01. LCSAS: Liverpool Communication Skills Assessment Scale; SAQ-C: Safety Attitudes Questionnaire-C; WOLF: work-related flow inventory. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Duffy V.G. Improving efficiencies and patient safety in healthcare through human factors and ergonomics J. Intell. Manuf. 2011 22 57 64 10.1007/s10845-009-0276-8 2. Xie A.P. Carayon P. A systematic review of human factors and ergonomics (hfe)-based healthcare system redesign for quality of care and patient safety Ergonomics 2015 58 33 49 10.1080/00140139.2014.959070 25323570 3. Bion J.F. Abrusci T. Hibbert P. Human factors in the management of the critically ill patient Br. J. Anaesth. 2010 105 26 33 10.1093/bja/aeq126 20511333 4. Keebler J.R. Rosen M.A. Sittig D.F. Thomas E. Salas E. Human factors and ergonomics in healthcare: Industry demands and a path forward Hum. Factors 2022 64 250 258 10.1177/00187208211073623 35000407 5. Cohen T.N. Gewertz B.L. Shouhed D. A human factors approach to surgical patient safety Surg. Clin. N. Am. 2021 101 1 13 10.1016/j.suc.2020.09.006 33212071 6. Liu C. Chen H. Liu C.Y. Lin R.T. Chiou W.K. The effect of loving-kindness meditation on flight attendants’ spirituality, mindfulness and subjective well-being Healthcare 2020 8 174 10.3390/healthcare8020174 7. Liu C. Chen H. Liu C.Y. Lin R.T. Chiou W.K. Cooperative and individual mandala drawing have different effects on mindfulness, spirituality, and subjective well-being Front. Psychol. 2020 11 2629 8. Chan R.W. Lushington K. Immink M.A. States of focused attention and sequential action: A comparison of single session meditation and computerised attention task influences on top-down control during sequence learning Acta Psychol. 2018 191 87 100 10.1016/j.actpsy.2018.09.003 9. Lippelt D.P. Hommel B. Colzato L.S. Focused attention, open monitoring and loving kindness meditation: Effects on attention, conflict monitoring, and creativity—A review Front. Psychol. 2014 5 1083 10.3389/fpsyg.2014.01083 25295025 10. Chan R.W. Alday P.M. Zou-Williams L. Lushington K. Schlesewsky M. Bornkessel-Schlesewsky I. Immink M.A. Focused-attention meditation increases cognitive control during motor sequence performance: Evidence from the n2 cortical evoked potential Behav. Brain Res. 2020 384 112536 10.1016/j.bbr.2020.112536 32032740 11. Fucci E. Abdoun O. Caclin A. Francis A. Dunne J.D. Ricard M. Davidson R.J. Lutz A. Differential effects of non-dual and focused attention meditations on the formation of automatic perceptual habits in expert practitioners Neuropsychologia 2018 119 92 100 10.1016/j.neuropsychologia.2018.07.025 30040956 12. Chan R.W. Immink M.A. Lushington K. The influence of focused-attention meditation states on the cognitive control of sequence learning Conscious. Cogn. 2017 55 11 25 10.1016/j.concog.2017.07.004 28750361 13. Ullrich S. Colzato L.S. Wolff N. Beste C. Short-term focused attention meditation restricts the retrieval of stimulus-response bindings to relevant information Mindfulness 2021 12 1272 1281 10.1007/s12671-021-01599-4 14. Yoshida K. Takeda K. Kasai T. Makinae S. Murakami Y. Hasegawa A. Sakai S. Focused attention meditation training modifies neural activity and attention: Longitudinal eeg data in non-meditators Soc. Cogn. Affect. Neurosci. 2020 15 215 223 10.1093/scan/nsaa020 32064537 15. Dobrakowski P. Blaszkiewicz M. Skalski S. Changes in the electrical activity of the brain in the alpha and theta bands during prayer and meditation Int. J. Environ. Res. Public Health 2020 17 9567 10.3390/ijerph17249567 33371283 16. Moye A.J. van Vugt M.K. A computational model of focused attention meditation and its transfer to a sustained attention task IEEE Trans. Affect. Comput. 2021 12 329 339 10.1109/TAFFC.2019.2908172 17. Irrmischer M. Houtman S.J. Mansvelder H.D. Tremmel M. Ott U. Linkenkaer-Hansen K. Controlling the temporal structure of brain oscillations by focused attention meditation Hum. Brain Mapp. 2018 39 1825 1838 10.1002/hbm.23971 29331064 18. Manna A. Raffone A. Perrucci M.G. Nardo D. Ferretti A. Tartaro A. Londei A. Del Gratta C. Belardinelli M.O. Romani G.L. Neural correlates of focused attention and cognitive monitoring in meditation Brain Res. Bull. 2010 82 46 56 10.1016/j.brainresbull.2010.03.001 20223285 19. Seligman M.E.P. Csikszentmihalyi M. Positive psychology—An introduction Am. Psychol. 2000 55 5 14 10.1037/0003-066X.55.1.5 11392865 20. Csikszentmihalyi M. Happiness, flow, and economic equality Am. Psychol. 2000 55 1163 1164 10.1037/0003-066X.55.10.1163 11080848 21. Abuhamdeh S. Csikszentmihalyi M. The importance of challenge for the enjoyment of intrinsically motivated, goal-directed activities Personal. Soc. Psychol. Bull. 2012 38 317 330 10.1177/0146167211427147 22067510 22. Lambert J. Csikszentmihalyi M. Facilitating or foiling flow: The role of momentary perceptions of feedback J. Posit. Psychol. 2020 15 208 219 10.1080/17439760.2019.1578893 23. Tse D.C.K. Nakamura J. Csikszentmihalyi M. Living well by “flowing” well: The indirect effect of autotelic personality on well-being through flow experience J. Posit. Psychol. 2021 16 310 321 10.1080/17439760.2020.1716055 24. Bakker A.B. The work-related flow inventory: Construction and initial validation of the wolf J. Vocat. Behav. 2008 72 400 414 10.1016/j.jvb.2007.11.007 25. Debus M.E. Sonnentag S. Deutsch W. Nussbeck F.W. Making flow happen: The effects of being recovered on work-related flow between and within days J. Appl. Psychol. 2014 99 713 722 10.1037/a0035881 24512028 26. Skramm S.H. Jacobsen I.L.S. Hanssen I. Communication as a non-technical skill in the operating room: A qualitative study Nurs. Open 2021 8 1822 1828 10.1002/nop2.830 33631059 27. Gutierrez-Puertas L. Marquez-Hernandez V.V. Gutierrez-Puertas V. Granados-Gamez G. Aguilera-Manrique G. Educational interventions for nursing students to develop communication skills with patients: A systematic review Int. J. Environ. Res. Public Health 2020 17 2241 10.3390/ijerph17072241 28. Chen H. Liu C. Cao X.Y. Hong B. Huang D.H. Liu C.Y. Chiou W.K. Effects of loving-kindness meditation on doctors’ mindfulness, empathy, and communication skills Int. J. Environ. Res. Public Health 2021 18 4033 10.3390/ijerph18084033 33921271 29. Julia-Sanchis R. Cabanero-Martinez M.J. Leal-Costa C. Fernandez-Alcantara M. Escribano S. Psychometric properties of the health professionals communication skills scale in university students of health sciences Int. J. Environ. Res. Public Health 2020 17 7565 10.3390/ijerph17207565 30. Taylor L.J. Nabozny M.J. Steffens N.M. Tucholka J.L. Brasel K.J. Johnson S.K. Zelenski A. Rathouz P.J. Zhao Q.Q. Kwekkeboom K.L. A framework to improve surgeon communication in high-stakes surgical decisions best case/worst case JAMA Surg. 2017 152 531 538 10.1001/jamasurg.2016.5674 28146230 31. Manser T. Foster S. Flin R. Patey R. Team communication during patient handover from the operating room: More than facts and figures Hum. Factors 2013 55 138 156 10.1177/0018720812451594 23516799 32. Mundy P. Newell L. Attention, joint attention, and social cognition Curr. Dir. Psychol. Sci. 2007 16 269 274 10.1111/j.1467-8721.2007.00518.x 19343102 33. Kim K. Mundy P. Joint attention, social-cognition, and recognition memory in adults Front. Hum. Neurosci. 2012 6 172 10.3389/fnhum.2012.00172 22712011 34. Kaur M. Eigsti I.M. Bhat A. Effects of a creative yoga intervention on the joint attention and social communication skills, as well as affective states of children with autism spectrum disorder Res. Autism Spectr. Disord. 2021 88 101860 10.1016/j.rasd.2021.101860 34552663 35. Karnieli-Miller O. Michael K. Segal O. Steinberger A. Assessing an intervention focused on enhancing interpersonal communication skills and humor: A multi-method quasi-experiential study among medical students Health Commun. 2018 33 1560 1572 10.1080/10410236.2017.1384347 29058509 36. Bernard M. Favre N. Ya D. Despland J.N. Stiefel F. Should communication skills training increase the focus on psychodynamic aspects of the patient-clinician relationship? J. Psychosom. Res. 2008 64 640 641 37. Bickel J. Focus on improving relational communication skills and discussing what matters most Acad. Med. 2012 87 1471 1472 10.1097/ACM.0b013e31826cdd10 23111261 38. El Shafei A.M.H. Zayed M.A. Patient safety attitude in primary health care settings in giza, egypt: Cross-sectional study Int. J. Health Plan. Manag. 2019 34 851 861 10.1002/hpm.2743 39. Brasaite I. Kaunonen M. Suominen T. Healthcare professionals’ knowledge, attitudes and skills regarding patient safety: A systematic literature review Scand. J. Caring Sci. 2015 29 30 50 10.1111/scs.12136 24708205 40. Unver S. Yenigun S.C. Patient safety attitude of nurses working in surgical units: A cross-sectional study in turkey J. Perianesthesia Nurs. 2020 35 671 675 10.1016/j.jopan.2020.03.012 41. Cantero-Lopez N. Gonzalez-Chorda V.M. Valero-Chilleron M.J. Mena-Tudela D. Andreu-Pejo L. Vila-Candel R. Cervera-Gasch A. Attitudes of undergraduate nursing students towards patient safety: A quasi-experimental study Int. J. Environ. Res. Public Health 2021 18 1429 10.3390/ijerph18041429 33546501 42. Liu C. Chen H. Cao X.Y. Sun Y.N. Liu C.Y. Wu K. Liang Y.C. Hsu S.E. Huang D.H. Chiou W.K. Effects of mindfulness meditation on doctors’ mindfulness, patient safety culture, patient safety competency and adverse event Int. J. Environ. Res. Public Health 2022 19 3282 10.3390/ijerph19063282 35328968 43. Kong L.N. Zhu W.F. He S. Chen S.Z. Yang L. Qi L. Peng X. Attitudes towards patient safety culture among postgraduate nursing students in china: A cross-sectional study Nurse Educ. Pract. 2019 38 1 6 10.1016/j.nepr.2019.05.014 31163311 44. Elfering A. Semmer N.K. Grebner S. Work stress and patient safety: Observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses Ergonomics 2006 49 457 469 10.1080/00140130600568451 16717004 45. Ellis L.A. Tran Y. Pomare C. Long J.C. Churruca K. Mahmoud Z. Liauw W. Braithwaite J. “Time is of the essence”: Relationship between hospital staff perceptions of time, safety attitudes and staff wellbeing BMC Health Serv. Res. 2021 21 1 11 10.1186/s12913-021-07275-6 33388053 46. Gu H.L. Wen Z.L. Fan X.T. Investigating the multidimensionality of the work-related flow inventory (wolf): A bifactor exploratory structural equation modeling framework Front. Psychol. 2020 11 740 10.3389/fpsyg.2020.00740 32435216 47. Humphris G.M. Kaney S. The liverpool brief assessment system for communication skills in the making of doctors Adv. Health Sci. Educ. 2001 6 69 80 10.1023/A:1009879220949 11486140 48. Qureshi A.A. Zehra T. Simulated patient’s feedback to improve communication skills of clerkship students BMC Med. Educ. 2020 20 1 10 10.1186/s12909-019-1914-2 49. Liu X.C. Rohrer W. Luo A.J. Fang Z. He T.H. Xie W.Z. Doctor-patient communication skills training in mainland china: A systematic review of the literature Patient Educ. Couns. 2015 98 3 14 10.1016/j.pec.2014.09.012 25308954 50. Sexton J.B. Helmreich R.L. Neilands T.B. Rowan K. Vella K. Boyden J. Roberts P.R. Thomas E.J. The safety attitudes questionnaire: Psychometric properties, benchmarking data, and emerging research BMC Health Serv. Res. 2006 6 1 10 10.1186/1472-6963-6-44 16403235 51. Modak I. Sexton J.B. Lux T.R. Helmreich R.L. Thomas E.J. Measuring safety culture in the ambulatory setting: The safety attitudes questionnaire-ambulatory version J. Gen. Intern. Med. 2007 22 1 5 10.1007/s11606-007-0114-7 52. Lee W.C. Wung H.Y. Liao H.H. Lo C.M. Chang F.L. Wang P.C. Fan A. Chen H.H. Yang H.C. Hou S.M. Hospital safety culture in taiwan: A nationwide survey using chinese version safety attitude questionnaire BMC Health Serv. Res. 2010 10 1 8 10.1186/1472-6963-10-234 20044945 53. Elwy A.R. Itani K.M.F. Bokhour B.G. Mueller N.M. Glickman M.E. Zhao S.B. Rosen A.K. Lynge D. Perkal M. Brotschi E.A. Surgeons’ disclosures of clinical adverse events JAMA Surg. 2016 151 1015 1021 10.1001/jamasurg.2016.1787 27438083 54. Yoshida K. Ogawa K. Mototani T. Inagaki Y. Sawamura D. Ikoma K. Sakai S. Flow experience enhances the effectiveness of attentional training: A pilot randomized controlled trial of patients with attention deficits after traumatic brain injury Neurorehabilitation 2018 43 183 193 10.3233/NRE-172396 30040757 55. Marty-Dugas J. Howes L. Smilek D. Sustained attention and the experience of flow Psychol. Res.-Psychol. Forsch. 2021 85 2682 2696 10.1007/s00426-020-01433-x 33225384 56. Turnbull A. Wang H.T. Schooler J.W. Jefferies E. Margulies D.S. Smallwood J. The ebb and flow of attention: Between-subject variation in intrinsic connectivity and cognition associated with the dynamics of ongoing experience Neuroimage 2019 185 286 299 10.1016/j.neuroimage.2018.09.069 30266263 57. Stavrou N.A.M. Psychountaki M. Georgiadis E. Karteroliotis K. Zervas Y. Flow theory—Goal orientation theory: Positive experience is related to athlete’s goal orientation Front. Psychol. 2015 6 1499 10.3389/fpsyg.2015.01499 26500577 58. Stavrou N.A. Jackson S.A. Zervas Y. Karteroliotis K. Flow experience and athletes’ performance with reference to the orthogonal model of flow Sport Psychol. 2007 21 438 457 10.1123/tsp.21.4.438 59. Weber R. Tamborini R. Westcott-Baker A. Kantor B. Theorizing flow and media enjoyment as cognitive synchronization of attentional and reward networks Commun. Theory 2009 19 397 422 10.1111/j.1468-2885.2009.01352.x 60. Klasen M. Weber R. Kircher T.T.J. Mathiak K.A. Mathiak K. Neural contributions to flow experience during video game playing Soc. Cogn. Affect. Neurosci. 2012 7 485 495 10.1093/scan/nsr021 21596764 61. VanLangen K.M. Sahr M.J. Salvati L.A. Meny L.M. Bright D.R. Sohn M. Viability of virtual skills-based assessments focused on communication Am. J. Pharm. Educ. 2021 85 564 570 10.5688/ajpe8378 34544738 62. Weiland A. Blankenstein A.H. Willems M.H.A. Van Saase J. Van der Molen H.T. Van Dulmen A.M. Arends L.R. Post-graduate education for medical specialists focused on patients with medically unexplained physical symptoms; development of a communication skills training programme Patient Educ. Couns. 2013 92 355 360 10.1016/j.pec.2013.06.027 23906652 63. Neipp M.C. Perez-Jover V. Guilabert M. Martinez-Gonzalez M.C. Pons N. Nunez R. Evaluating nurses and patients communication skills: A focus group study Psychol. Health 2012 27 288 64. Piattelli A. Cazzaniga E. Colistra E. Iuvaro M.D. Palazzo S. Responding empathically to patients and colleagues: Focus on working group for implementing an effective communication skills. The experience of the team of oncology department in cosenza hospital Psycho-Oncology 2017 26 114 65. Arora S. Sevdalis N. Ahmed M. Wong H. Moorthy K. Vincent C. Safety skills, training for surgeons: A half-day intervention improves knowledge, attitudes and awareness of patient safety Surgery 2012 152 26 31 10.1016/j.surg.2012.02.006 22503321 66. Bain C.J. Wang T. McArthur G. Williams G. Atkins J. Jones I. Safety and efficacy of excision and direct closure in acute burns surgery: Outcome analysis in a prospective series of 100 patients and a survey of uk burns surgeons’ attitudes Burns 2014 40 1635 1641 10.1016/j.burns.2014.02.021 24685067 67. Wordsworth H. Wickham A. Bellew B. Gilfillan N. Attitudes towards safety of regional anaesthesia in trauma patients: A survey of surgeons and anaesthetists in a major trauma centre and a specialist hand unit Anaesthesia 2015 70 100 68. Berman L. Rangel S. Goldin A. Skarda D. Ottosen M. Bliss D. Valusek P. Fallat M. Tsao K. Comm A.Q.S. Safety culture among pediatric surgeons: A national survey of attitudes and perceptions of patient safety J. Pediatric Surg. 2018 53 381 395 10.1016/j.jpedsurg.2017.09.011 69. Day R.W. Conrad C. Vauthey J.N. Aloia T.A. Evaluating surgeon attitudes towards the safety and efficacy of portal vein occlusion and associating liver partition and portal vein ligation: A report of the malinsa survey Hpb 2015 17 936 941 10.1111/hpb.12439 26255813 70. Prati G. Pietrantoni L. Attitudes to teamwork and safety among italian surgeons and operating room nurses Work 2014 49 669 677 10.3233/WOR-131702 24004761 71. Tussardi I.T. Benoni R. Moretti F. Tardivo S. Poli A. Wu A.W. Rimondini M. Busch I.M. Patient safety in the eyes of aspiring healthcare professionals: A systematic review of their attitudes Int. J. Environ. Res. Public Health 2021 18 7524 10.3390/ijerph18147524 34299975 72. Anderson J.E. Utter G.H. Romano P.S. Jurkovich G.J. Surgeon-reported complications vs ahrq patient safety indicators: A comparison of two approaches to identifying adverse events J. Am. Coll. Surg. 2018 227 313 320 10.1016/j.jamcollsurg.2018.06.008 29981918 73. Cohen M.X. van Gaal S. Dynamic interactions between large-scale brain networks predict behavioral adaptation after perceptual errors Cereb. Cortex 2013 23 1061 1072 10.1093/cercor/bhs069 22514250 74. Zacks J.M. Kurby C.A. Eisenberg M.L. Haroutunian N. Prediction error associated with the perceptual segmentation of naturalistic events J. Cogn. Neurosci. 2011 23 4057 4066 10.1162/jocn_a_00078 21671745 75. Lo S.Y. Howard C.J. Holcombe A.O. Feature-based attentional interference revealed in perceptual errors and lags Vis. Res. 2012 63 20 33 10.1016/j.visres.2012.04.021 22579792 76. Berman L. Rialon K.L. Mueller C.M. Ottosen M. Weintraub A. Coakley B. Brandt M.L. Heiss K. Supporting recovery after adverse events: An essential component of surgeon well-being J. Pediatric Surg. 2021 56 833 838 10.1016/j.jpedsurg.2020.12.031 33454081 77. Luu S. Patel P. St-Martin L. Leung A.S.O. Regehr G. Murnaghan M.L. Gallinger S. Moulton C.A. Waking up the next morning: Surgeons’ emotional reactions to adverse events Med. Educ. 2012 46 1179 1188 10.1111/medu.12058 23171260 78. Skevington S.M. Langdon J.E. Giddins G. ‘Skating on thin ice?’ Consultant surgeon’s contemporary experience of adverse surgical events Psychol. Health Med. 2012 17 1 16 10.1080/13548506.2011.592841 22191491 79. Sligter L.M. van Steijn M.E. Scheepstra K.W.F. Dijksman L.M. Koot H.W.J. van Pampus M.G. Mental-health, coping and support following adverse events on the work-floor: A cross-sectional study among dutch orthopaedic surgeons Acta Orthop. Belg. 2020 86 349 362 33581017 80. Vago D.R. Zeidan F. The brain on silent: Mind wandering, mindful awareness, and states of mental tranquility Ann. N. Y. Acad. Sci. 2016 1373 96 113 10.1111/nyas.13171 27398642 81. Kajimura S. Masuda N. Lau J.K.L. Murayama K. Focused attention meditation changes the boundary and configuration of functional networks in the brain Sci. Rep. 2020 10 1 11 10.1038/s41598-020-75396-9 31913322 82. Hussain D. Bhushan B. Psychology of meditation and health: Present status and future directions Int. J. Psychol. Psychol. Ther. 2010 10 439 451

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094492 ijms-23-04492 Review Novel Multifaceted Roles for RNF213 Protein https://orcid.org/0000-0002-0256-9706 Pollaci Giuliana 1 https://orcid.org/0000-0001-8483-3509 Gorla Gemma 1 https://orcid.org/0000-0001-6811-6112 Potenza Antonella 1 https://orcid.org/0000-0001-5752-1374 Carrozzini Tatiana 1 https://orcid.org/0000-0002-0141-0437 Canavero Isabella 2 https://orcid.org/0000-0002-2493-628X Bersano Anna 2 https://orcid.org/0000-0001-6751-5031 Gatti Laura 1* Borlongan Cesar Academic Editor 1 Laboratory of Neurobiology, Neurology IX Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; giuliana.pollaci@istituto-besta.it (G.P.); gemma.gorla@istituto-besta.it (G.G.); antonella.potenza@istituto-besta.it (A.P.); tatiana.carrozzini@istituto-besta.it (T.C.) 2 Cerebrovascular Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; isabella.canavero@istituto-besta.it (I.C.); anna.bersano@istituto-besta.it (A.B.) * Correspondence: laura.gatti@istituto-besta.it; Tel.: +39-02-23942389 19 4 2022 5 2022 23 9 449218 3 2022 17 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Ring Finger Protein 213 (RNF213), also known as Mysterin, is the major susceptibility factor for Moyamoya Arteriopathy (MA), a progressive cerebrovascular disorder that often leads to brain stroke in adults and children. Although several rare RNF213 polymorphisms have been reported, no major susceptibility variant has been identified to date in Caucasian patients, thus frustrating the attempts to identify putative therapeutic targets for MA treatment. For these reasons, the investigation of novel biochemical functions, substrates and unknown partners of RNF213 will help to unravel the pathogenic mechanisms of MA and will facilitate variant interpretations in a diagnostic context in the future. The aim of the present review is to discuss novel perspectives regarding emerging RNF213 roles in light of recent literature updates and dissect their relevance for understanding MA and for the design of future research studies. Since its identification, RNF213 involvement in angiogenesis and vasculogenesis has strengthened, together with its role in inflammatory signals and proliferation pathways. Most recent studies have been increasingly focused on its relevance in antimicrobial activity and lipid metabolism, highlighting new intriguing perspectives. The last area could suggest the main role of RNF213 in the proteasome pathway, thus reinforcing the hypotheses already previously formulated that depict the protein as an important regulator of the stability of client proteins involved in angiogenesis. We believe that the novel evidence reviewed here may contribute to untangling the complex and still obscure pathogenesis of MA that is reflected in the lack of therapies able to slow down or halt disease progression and severity. RNF213 Moyamoya arteriopathy E3 ubiquitin ligase angiogenesis inflammation PTP1b lipid metabolism antimicrobial activity ==== Body pmc1. Introduction Ring Finger Protein 213 (RNF213), also known as Mysterin (Moyamoya steno-occlusive disease-associated AAA+ and RING finger protein), is a E3 ubiquitin protein ligase of 591 kDa consisting of 5207 amino acids encoded by locus 15,624 bp ORF and 5431 bp 5′ and 3′ UTRs on chromosome 17q25.3. The RNF213 gene is the major susceptibility factor for Moyamoya Arteriopathy (MA), a progressive cerebrovascular disorder that often leads to brain stroke in adults and children [1]. RNF213 is an atypical susceptibility gene, because its p.R4810K variant has been associated with MA mainly in East Asian patients [2]. Moreover, the pattern of inheritance in MA familial cases is unclear and most likely heterogeneous. Although several rare and nondisruptive RNF213 variants, distinct from p.R4810K, have been reported in MA patients of European ancestry, no major susceptibility variant has been identified to date in Caucasian MA patients [3]. In addition, the RNF213 variants that have been reported so far in Caucasian cases did not lead to conclusions useful for identifying putative therapeutic targets for MA patient treatments. The difficulty in drawing a clear conclusion about causality when RNF213 variants were considered individually in patient cohorts and the low penetrance observed in most families has rendered genetic counseling quite difficult so far. For these reasons, the investigation of novel biochemical functions, substrates and unknown partners of RNF213 will help to unravel the pathogenic mechanisms of MA and will facilitate variant interpretations in a diagnostic context in the future. The incomplete disease knowledge on pathogenic drivers is reflected in the lack of therapies able to slow or halt the disease progression and severity. The aim of the present review is to discuss novel perspectives regarding emerging RNF213 roles in light of the recent literature updates and dissect their relevance for understanding MA and for the design of future research studies. 2. RNF213 from Gene to Molecular Structure The RNF213 gene is conserved in protochordates and vertebrates, and it is ubiquitously expressed, with the higher expression rate in immune tissue [2,4]. The encoded protein exists in two isoforms [4]. RNF213 is a cytosolic protein with a perinuclear space localization. It is a huge unique protein that encompasses both ubiquitin ligase activity and ATPase activity; its functional domains are divided as follows: − Six ATPase domains, each containing a Walker A and a Walker B domain, peculiar to ATP-binding proteins; the A motif is the main ‘P-loop’ responsible for binding phosphate, while the B motif is a magnesium-binding motif [5]. − One RING finger domain with an E3 ubiquitin ligase domain that is able to covalently modify the substrate with the addition of ubiquitin molecules and stimulate the intracellular biological processes, such as proteasomal protein degradation [4]. Morito and colleagues identified the presence of two tandem ATPase domains and demonstrated that RNF213 is capable of forming a ring-shaped homo-oligomer in the cell approximately comparable with macromolecular complexes such as the ribosome. They also observed that a relatively large amount of protein diffuses as a monomer in the cell, suggesting that Mysterin exists in a balanced condition between the monomeric and oligomeric states [6]. A recent cryo-EM analysis by Ahel and colleagues showed a detailed structure of the full-length murin RNF213 (584 kDa, 5184 residues), possibly resembling the human homolog protein [1]. The murine protein is depicted by 20 subdomains divided into three structural components: the N-arm, AAA and E3 module. The first one (residues 1–1290) is connected by a linker domain (1291–1774) to the second module, the AAA core, made up of six AAA units (1775–3405). The central region consists of a hinge domain (3406–3588) that connects the AAA core to the E3 domain (3598–4926). The last is composed of a four-domain scaffold that locates the E3 RING (3940–3999) at the edge of the molecule at the opposite site of the AAA domain. They demonstrated the presence of a six-membered AAA ring, with two catalytically competent units (AAA3 and AAA4), bearing all functional motifs (Walker A and Walker B) [1]. The RING finger domain is composed of a E3 module with ubiquitinase activity. Post-translational protein modifications by mono- or polyubiquitin chains are involved in several signaling pathways and are tightly regulated to ensure the cellular processes. Ubiquitin molecules are conjugated at the ε-amino group of lysyl residues of the target proteins through isopeptide bonds. The nature of the ubiquitin–ubiquitin isopeptide bond appears to determine the subsequent fate of ubiquitinated proteins [7]. Several studies have proposed that Mysterin exerts ubiquitylation activity toward a variety of substrate proteins, including itself, with a mechanism of autoubiquitylation [4,8]. The ubiquitin ligase activity of RNF213 is cysteine-dependent, capable of promoting the ubiquitin transfer by a trans-thiolation mechanism rather than by activating the E2–Ub conjugate, as Ubiquitin E3 ligases conventionally do. RNF213 employs a E3 scaffold to perform its ubiquitin ligase function in a RING-independent manner [1]. To date, Mysterin is the only known protein that exerts both AAA+ ATPase and ubiquitin ligase activities, but how it coordinates the unique combination of enzymatic activities to perform specific functions in a cell remains elusive. 3. RNF213 Genetic Background Despite the growing and detailed information that recently was brought to light about its structure, the exact function of this huge protein still remains unclear. Since RNF213 has a critical role in MA, its correlation in vascular development/angiogenesis was the first to be defined. In a locus-specific GWAS, RNF213 was identified for the first time as a susceptibility gene for MA. Due to the unusually high prevalence of MA patients in Japan (6 per 100,000 population), the presence of a founder mutation among the Japanese population was hypothesized. A GWA study demonstrated that 19 of the 20 MA families shared the same single-base substitution in exon 60 of RNF213: c.14576G>A, causing an amino acid substitution from Arg to Lys in the 4810 position (R4810K). It was identified in 95% of MA familial cases, 73% of non-familial MA cases, including 45 heterozygotes and a single homozygote, and 1.4% of controls. Additional missense mutations were detected in three non-familial MA cases without the R4810K mutation, suggesting that such mutations greatly increase the risk of MA, with an odd ratio (OR) of 190.8 [2]. Studies based on a large-scale sequencing analysis tried to extend the correlation to all East Asian populations, identifying this genetic variant as common in 42 families [4,9]. A different genetic background in Caucasian patients was found through the positive association of MA with rare heterozygous RNF213 missense variants, particularly in early onset and/or familial cases. These ‘Caucasian’ variants significantly clustered in a C-terminal ‘hotspot’ encompassing the RING finger domain [3]. RNF213 rare pathogenic missense variants were also detected in all affected members of some MA European families also carrying mutations in PALD 1 (Phosphatase Domain Containing Paladin 1), a gene probably involved in peptidyl-tyrosine dephosphorylation. Nonetheless, three carriers were unaffected, and one of them presented a steno-occlusive angiopathy without fulfilling the criteria for MA, similar to the known incomplete penetrance of RNF213 variants [10]. In addition, a WES study on European MA led to the identification of de novo germline heterozygous CBL mutations in unrelated cases, presenting a bilateral severe early onset MA. Likewise, RNF213, the CBL gene, encodes a huge E3 ubiquitin protein ligase containing a RING finger domain and is involved in proteasome modulation. This finding strongly reinforces and supports the involvement of a defective proteasome signaling pathway in MA pathophysiology [11]. 4. RNF213 and Inflammation-Related Angiogenesis Kobayashi and colleagues in 2015 obtained biochemical and functional characterizations of the RNF213 R4180K mutation in angiogenesis through in vitro and in vivo studies. They showed that the upregulation of RNF213 could be produced by inflammatory signals. IFN-B was able to increase RNF213 gene expression through the STAT-x-binding site in the promoter region. The upregulation mediated by IFN-B was associated with lower angiogenesis, and RNF213 R4810K polymorphism led to a decreased tube-forming ability in response to environmental stimuli [12]. Accordingly, Ohkubo and colleagues demonstrated that RNF213 is transcriptionally induced by the administration of TNF-A and co-stimulation with other proinflammatory cytokines, thus connecting the environmental factors to the RNF213 response. RNF213 was also involved in the cell proliferation of endothelial cells through decreasing AKT phosphorylation and inducing matrix metalloproteinase-1 (MMP1) [13]. These findings support the importance of the inflammatory environment in MA. In particular, MA-involved vessels are depicted by a concentric fibrocellular hyperplasia of the intima [14,15], caused by the proliferation of vascular smooth muscle cells (VSMC) and extracellular matrix (ECM), resulting in a progressive intimal fibrous thickening [16,17,18]. Since little is known about fibrosis in MA, the cross-talk between endothelial cells (EC) and VSMC in MA is under investigation. Some evidence suggested that chemokines derived from defective colony-forming EC could be responsible for the aberrant recruitment and proliferation of VSMC progenitors in MA patients [19]. Recently, it has been demonstrated that ECM receptor-related genes are significantly downregulated in iPS-derived ECs from patients carrying the p.R4810K mutation [20]. The latter cells produced less ECM components than the controls, suggesting that RNF213 variants may be directly involved in changes in the ECM [21]. Thus, it is likely that VSMC are implicated in fibrosis and EC in the fibrillogenesis process through chemokine secretion in an inflammatory context. Ubc13/Uev1A (Ubiquitin-conjugating enzyme) is an E2 enzyme that cooperates with the RNF213 RING domain, promoting K63-linked polyubiquitination but not K48-linked polyubiquitination of the substrates [22]. K48 ubiquitination implies subsequent proteolytic degradation of the target protein [23]. Conversely, K63 linkages are known to regulate critical cellular processes such as DNA repair, innate immune response, the clearance of damaged mitochondria and protein sorting [24]. Moreover, K63 ubiquitination plays a pivotal role in the regulation of both canonical and noncanonical NF-κB activation pathways that negatively regulate apoptosis. The Ubc13/RNF213 interaction may contribute to the selective ubiquitination of the target protein through a mechanism in which Ubc13 forms heterodimers with other E2 enzymes and catalyzes the synthesis of K63-polyubiquitin chains [22]. Ahel et al. evaluated the R4753K mutation in the murine protein homologous to RNF213 R4810K and demonstrated that it does not significantly alter the enzymatic properties of RNF213 in vitro. MA mutations strongly cluster and alter the overall conformation and dynamics of the composite E3 module and, thus, its ubiquitination activity [1]. The R4810K variant undoubtedly afflicts the ubiquitin ligase domain of RNF213, leading to either mechanistic inhibition or altered substrate binding. Bahn and colleagues in 2016 proposed RNF213 as a promoter of angiogenesis in an in vitro tumor model through the stabilization of the master angiogenesis regulator HIF-1 (hypoxia inducible factor 1). They demonstrated for the first time that RNF213 is a putative substrate of PTP1b, and it is a major regulator of the ubiquityloma—in particular, in HER2+BC cells [25]. They implicated RNF213 in vascular development through its direct/indirect effect in the angiogenic pathway, thus conferring it a leading role in the pathophysiology of MA. Inflammation is extensively studied in correlation with obesity and metabolic disorders. In the presence of obesity, the recruitment of adipokines and chemokines causes the infiltration of macrophages into the adipose tissues, where they secrete proinflammatory molecules that lead to insulin resistance [26]. Inflammation triggers the induction of TNFα in adipocytes, which further induces the expression of PTP1B [27]. Interestingly, the RNF213 interactome included a cluster belonging to TNFα and PTP1B [8]. PTP1B is also a negative regulator of insulin [28], while TNFα causes insulin resistance [29] and acts as an antiadipogenic factor by altering PTP1B [28]. PPARγ has been suggested to be one of the main adipogenic regulators [8]. To identify a possible correlation between TNFα/PTP1B and RNF213 in adipogenesis, a PPARγ activator and anti-inflammatory molecule was used [30]. The insulin-resistant TNFα/PTP1B pathway enhances RNF213 expression, while PPARγ-mediated insulin sensitization suppresses its expression. Thus, it was hypothesized that PTP1B could inactivate PPARγ to induce RNF213 [8]. The RNF213 expression appears linked to inflammation and the insulin pathway. Probably, TNFα induces the expression of PTP1B, increasing its activity [31,32], which blocks PPARγ [27]. PPARγ can suppress the transcription of RNF213; therefore, the suppression of PPARγ induces RNF213. RNF213 emerged as a link between obesity, inflammation and insulin resistance. 5. RNF213 Key Interactors The ‘mystery’ of RNF213 also wraps around its interactors. As mentioned above, Banh and colleagues, studying the tumor hypoxia microenvironment, stumbled onto RNF213. They investigated the factors involved in nonmitochondrial oxygen consumption (NMOC), a mechanism aimed at limiting oxygen consumption and promoting tumor survival in the hypoxia microenvironment. PTP1B is required for Her2/Neu-driven breast cancer in mice. PTP1B deficiency sensitizes HER2+ breast cancer cell lines to hypoxia by increasing NMOC by α-KG-dependent dioxygenases (α-KGDDs). α-KGDDs probably acts by catalyzing the prolyl hydroxylation of HIF1α and determining its destabilization and the consequent potential failure of the hypoxic response [33]. PTP1B probably acts via RNF213 to suppress α-KGDD activity and NMOC. It was suggested that PTP1B negatively regulated RNF213 E3 ligase activity and that some RNF213 substrates globally regulate α-KGDDs by altering the level of co-substrates/metabolites, such as ascorbate and/or iron [25]. It could be possible that this pathway, allowing tumor growth in the hypoxia microenvironment, can be compromised in MA patients. Recently, a new antimicrobial activity of RNF213 as an interferon-induced ISG15 interactor/ISG15-binding protein and cellular sensor of ISGylated proteins was discovered (see below, Section 7) [34]. ISG15 was reported to interact in a noncovalent manner with HIF1α, preventing its dimerization and downstream signaling [35]. The PTP1B-negative regulation of RNF213 was associated with the mechanism involving the IFN-I-induced oligomerization of RNF213. It would be worthwhile to test whether PTPB1 also regulates RNF213 oligomerization in response to interferon, since PTP1B also affects JAK-STAT signaling [34]. 6. RNF213 and Lipid Metabolism The lipid accumulation interferes with normal cellular and tissue functions, causing lipotoxicity, which seems to be one of the causes of many metabolic diseases [36,37]. Saturated fatty acids are implicated in several mechanisms, including incorporation into membrane lipids and storage in lipid droplets, by acting as protein modifiers or mitochondrial oxidation. Palmitate (C16: 0) is particularly toxic for cells, since high concentrations of palmitate induce apoptosis [38]. More recently, Piccolis et al., conducted studies on palmitate-induced toxicity. An excess of palmitate is incorporated into a wide variety of lipids, and the accumulation of saturated glycerolipids in the ER triggers the prolonged activation of the IRE1 pathway of the UPR [39,40]. The depletion of RNF213 was identified as a protection mechanism against palmitate-induced lipotoxicity, reducing the cellular toxicity by 50%. Furthermore, RNF213 knockdown also lessened palmitate-induced cell death in different cell types. The most surprising finding is that the depletion of RNF213 almost normalized the cellular lipidome during exposure to palmitate, abrogating the accumulation of di-saturated glycerophospholipids. Measuring the incorporation of radiolabeled palmitate into lipids, it seems that RNF213 knockdown did not alter the total palmitate incorporation but promoted the partitioning of the substrate toward triglycerides. Although the mechanism remains to be determined, RNF213 is clearly a modulator of lipotoxicity from saturated fatty acids through a mechanism that has an important effect on a cell’s ability to store lipids in droplets, ubiquitous organelles specialized for neutral lipid storage (LDs) (Figure 1). The first evidence that RNF213 is targeted at LDs was reported by Sugihara and colleagues [41]. To dissect the subcellular distribution of RNF213, they performed high-resolution fluorescence microscopy with RNF213 harboring mCherry (mCherry-mst). They found that cells transiently overexpressing mCherry-mst formed LDs more extensively than intact (non-transfected) cells. A quantitative analysis of those LDs revealed that the number of LDs and the area occupied by LDs are markedly increased in RNF213-overexpressing cells. Conversely, the depletion of RNF213 by CRISPR/Cas9 or siRNA resulted in a significant reduction of LDs. The authors reported that RNF213 is targeted at LDs and markedly increases their abundance in cells. This effect was exerted primarily through specific elimination of adipose triglyceride lipase (ATGL) from LDs. However, no physical interaction between RNF213 and ATGL was found. A plausible scenario is that RNF213 and ATGL compete for binding to a common anchoring protein facilitating LD localization. RNF213 may affect the putative anchoring protein with its AAA+ activity and prevent the ATGL influx to LDs [41] (Figure 2). Previous epidemiological studies did not find any correlation between MA and obesity/dyslipidemia, as the condition is characterized by the hyperplasia of vascular smooth muscle cells (VSMC) and by luminal thrombosis to the injury, while, generally, no atherosclerotic changes were found [42]. Therefore, MA was not considered closely related to the lipid metabolism. However, very recently, it was suggested that lipid metabolism may be involved in the pathogenesis of MA, although neither study showed a direct association between the RNF213 mutations and dyslipidemia [43]. In fact, the untargeted gas chromatography mass spectrometry (MS) approach identified 25 discriminating serum metabolic biomarkers in MA patients. A panel of fatty acids (myristic acid, pelargonic acid, palmitic acid, palmitoleic acid and stearic acid) could be used to distinguish between MA patients and healthy donors (HD). The level of succinic acid, an intermediate of the TCA cycle, was significantly decreased in the MA patient serum, indicating an alteration in the cycle that would lead to an altered level in the fatty acid. A defective respiratory machinery in the mitochondria could be associated with the mitochondrial abnormalities observed in MA patients [44,45], and with a decrease of the ‘building blocks’ of cellular membrane and defective signal transduction [46]. An untargeted lipidomic approach was recently performed on the plasma of MA patients [47], confirming what was previously observed in the serum [46]. Indeed, MA patients showed a surprisingly lower plasma content of lipids as compared to HD, particularly in lipids belonging to the glycosphingolipid and phospholipid classes. Through a discriminant analysis (PLS-DA), the lipidomic profile showed a separation of 23.1% of the principal component (PC1). The authors supposed that, since glycosphingolipids and phospholipids are plasma-membrane components, their reduced level could correlate with a decrease of the cellular debris due to a reduction of peripherally circulating progenitor cells [48] as an effect of the major cerebral recruitment of circulating cells [49]. An increase of cardiolipin, a typical mitochondrial lipid, could confirm the frequently reported abnormalities of MA patients. A quantitative targeted MS analysis showed a free spingoid base level increase in the plasma of MA patients in comparison to HD. Specifically, Sph, DHSph, S1P and DHS1P concentrations were augmented in MA patients. Of note, S1P and DHS1P are pro-angiogenic/proliferative factors, again in agreement with MA pathogenesis. All studies focused on novel unreleased and unexpected RNF213 roles in lipid metabolism, thus widening the scenario of the putative functions of Mysterin. 7. RNF213 and Antimicrobial Activity The RNF213 gene may also impact the resistance to infectious diseases such as Rift Valley Fever (RVF), an emerging viral zoonosis affecting ruminants and humans [50]. Evidence from experimental models has demonstrated the importance of genetic host factors in determining the RVF severity in mice. The authors narrowed down the critical interval to a 530 kb region containing five protein-coding genes, among which RNF213 emerged as a potential candidate. They generated Rnf213-deficient mice by CRISPR/CAS9 and showed that they were significantly more susceptible to RVF than the control mice. The STRING Mus musculus database analysis revealed that murine RNF213 formed a highly interconnected network with UBA7, USP18, PARP14, IFIT3, IRF7, RSAD2, STAT1, IGTP, MX2, RTP4, OASL2, IRGM2, LGALS3BP and OAS2 proteins. Seven of these proteins were associated with the Gene Ontology (GO) categories ’innate immune response’, six with the ’immune effector process’ and/or ’response to other organism’, five with ’defense response to virus’, three with ’negative regulation of viral process’ and two with ’response to type I interferon’. These numerous interactions with innate immunity genes suggested a role of RNF213 in response to infection [50]. Homozygous Rnf213-deficient mice (referred to as Rnf213tm3/tm3) did not show any visible phenotype under a conventional environment. After intraperitoneal injection of the RVF virus (RVFV), the survival time in lethally infected mice was significantly shorter in Rnf213tm3/tm3 than in Rnf213+/+. These results indicated that RNF213 gene delays the fatal outcome of RVFV infection. In humans, the primary site of RVFV replication is in the liver, together with LD accumulation [51]. A major consequence of RVFV infection in mice is the overwhelming infection of hepatocytes resulting in early-onset death for severe hepatitis [52,53]. It has been observed that the hepatocytes store up cytoplasmic LDs persisting during liver regeneration in the surviving mice [54]. It is therefore possible that RNF213 influences the resistance to RVFV infection through a major role in lipid metabolism [50] (Figure 3). An in silico assessment of the RNF213 expression profile in a large collection of human tissues confirmed the high correlation between the RNF213 and GO categories of ‘immune response to virus’ [13]. A few years later, emerging data pointed out the identification of RNF213 as a novel immune sensor, unveiling the link between MA and infection [55]. In particular, the ubiquitin coat, which marks cytosol-invading bacteria as the cargo for antibacterial autophagy [56,57,58], is likely to be the result of the unprecedented ubiquitylation of a minimal substrate, such as the lipid A of bacterial lipopolysaccharide (LPS), mediated by the RNF213 ubiquitin ligase [55]. This intriguing result has been obtained by the RNAi approach and CRISPR technology used to test whether RNF213 is required for the ubiquitylation of LPS. Indeed, cells lacking RNF213 failed to ubiquilate LPS upon infection. In particular, this study demonstrated that RNF213-mediated LPS ubiquitylation requires a catalytically active AAA+ module, independent of the RING domain. Through the creation of a bacterial ubiquitin coat, RNF213 was able to restrict the proliferation of cytosolic Salmonella, suggesting an extension of the scope of ubiquitylation more than a simple and basic post-translational protein modification [55] (Figure 4). Overall, bacterial/viral infections could contribute to MA development in genetically susceptible subjects, although no RNF213 variant predisposed to MA was impaired during the LPS ubiquitylation ability [55]. RNF213 has been described as an ISG15 interactor and cellular sensor of ISGylated proteins [34]. ISG15 is an interferon-stimulated and Ub-like protein that, in a process known as ISGylation, conjugates an immunity-related modification, counteracting microbial infection [59,60,61,62,63]. Once upregulated by type I and III interferons, viral nucleic acids, bacterial DNA and LPS, ISG15 is able to exert potent antiviral effects both in vitro and in vivo [64,65,66]. It has also been described as an ISG15 antibacterial activity against intracellular bacterial and eukaryotic pathogens [64,67,68]. Currently, the mechanisms by which ISG15 modification is perceived and how it protects against microbial infections have not yet been clarified. A supposed model is based on the localization of the ISG15 E3 ligase (HERC5) at the ribosome site where the proteins are co-translationally modified by ISG15 during infection, thus hampering with the function of newly translated viral proteins [69]. Differently from ubiquitin, ISG15 exerts an antimicrobial role by also conjugating to target substrates through noncovalent interactions or acting as a secreted cytokine. For instance, free ISG15 is referred to interact in a noncovalent way with HIF1α, avoiding its dimerization and downstream signaling [35]. For this reason, in order to identify and map the noncovalent ISG15 protein–protein interactions, Thery et al. developed the MS-based approach named Virotrap, a virus-like particle trapping technology that allows the capture of protein complexes within virus-like particles (VLPs) budding from mammalian cells. Thanks to this technology, they mapped the noncovalent interactome of ISG15 in human cells. RNF213 has been identified as the most enriched protein in the ISG15 VLPs, requiring both the N- and C-terminal domains to selectively interact with ISG15. This evidence highlighted the capability of RNF213 to interact with and bind ISGylated proteins, recruiting them to LDs. Monomeric RNF213 is directly recruited from the cytosol on the surface of LDs, where its oligomerization in a hexamer is driven by ATP binding. RNF213 oligomerization and translocation to LDs may serve for the creation of a binding platform for ISG15 and, potentially, multiple ISGylated proteins [34]. Thery et al. demonstrated that the increasing expression of RNF213 is strictly associated with lower viral infection levels in cultured cells. Conversely, the reduced RNF213 expression levels promoted in vitro infection with different viruses. Compared to the antiviral activity, the antimicrobial effect of RNF213 was more marked and subjected to ISG15. Taken together, these results emphasized the role of RNF213 in the innate cellular immune response and pointed out a functional association between ISG15 and RNF213. As far as the antimicrobial activity reported in vivo, it is likely that the overexpression of RNF213 prior to infection gives rise to the innate defense response (Figure 5). 8. Conclusions Our literature review resumes and summarizes the multiplicity of the RNF213 roles, including novel unexpected functions. The RNF213 gene was first discovered in 2011, and since then, the scientific setting has been filled with subsequent in vitro and in vivo studies, expanding the knowledge of such a mysterious and peculiar protein. Since its identification as a susceptibility gene in MA, its involvement in angiogenesis and vasculogenesis has strengthened together with a role in inflammatory signals and proliferation pathways. Several previous studies have shown that RNF213 may also be involved in other vascular phenotypes, such as premature coronary artery disease, renal or aortic artery disease [70], hypertension [71], cerebral cavernous malformation [72], fibromuscular dysplasia [73], stenosis/major intracranial artery occlusion [74] and intracranial aneurysm [75]. Therefore, it is clear that RNF213 has a relevant role in many vascular diseases, although the specific molecular mechanisms in which it is involved have not always been clarified. Interestingly, most recent studies have been more focused on its relevance in antimicrobial activity and lipid metabolism, highlighting new, intriguing perspectives. This novel research field may corroborate a major role of RNF213 protein in the proteasome pathway by representing the protein as an important regulator of the stability of the client proteins involved in angiogenesis. (i.e., HIF1α [25]). All these studies underlined that RNF213 acts as an antimicrobial host defense effector in MA patients, possibly triggered by autoimmune responses, prior infection and/or inflammatory processes. It is reasonable to speculate that MA patients carrying RNF213 polymorphisms may exhibit a defective immune response to infections or may be more predisposed to autoimmune reactions. Therefore, autoimmune diseases and infections, which are MA-associated conditions, could trigger the disease in genetically susceptible individuals [76]. We believe that the novel evidence reviewed here may contribute to untangling the complex and still obscure pathogenesis of MA that is reflected in the lack of therapies able to slow or halt disease progression and severity. Author Contributions Conceptualization and writing—original draft preparation, G.P., G.G., A.P. and T.C.; review and editing, I.C., A.B. and L.G. and supervision and funding acquisition, A.B. and L.G. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by two grants from the Italian Ministry of Health (Ricerca Corrente 2018-2021 to L.G. and Ricerca Finalizzata RF-2019-12369247 to A.B.). Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of the data; in the writing of the manuscript or in the decision to publish the results. Abbreviations RFN213 Ring Finger Protein 213, MA Moyamoya arteriopathy, Hsp104 Heat Shock Protein 104, NFS N-Ethylmaleimide Sensitive Fusion Protein, STAT Signal Transducer And Activator Of Transcription, AKT Protein Kinase B, EC endothelial cells, Ubc13/ Uev1A Ubiquitin Conjugating Enzyme E2 13, Ubiquitin Conjugating Enzyme E2 Variant 1 A, PTP1B Protein Tyrosine Phosphatase 1B, PPARγ Proliferator-Activated Receptor γ, NF-κB Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells, NMOC Non-mitochondrial Oxygen Consumption, α-KGDDs α-KG-Dependent Dioxygenases, HIF1α Hypoxia-Inducible-Factor-1α, ISG15 Interferon-Stimulated Gene 15, JAK Janus Kinase, ER Endoplasmic Reticulum, IRE1 Inositol-Requiring Enzyme 1, UPR Unfolded Protein Response, LDs Lipid Droplets, ATGL Adipose Triglyceride Lipase, cVSMC Circulating Vascular Smooth Muscle Cells, cEPCs Endothelial Peripherally Circulating Progenitor Cells, Sph Sphingosine, DHSph Dihydrosphingosine, S1P Sphingosine 1-Phosphate, DHS1P Dihydrosphingosine 1-Phosphate, RVF Rift Valley Fever, UBA7 Ubiquitin-like Modifier-Activating Enzyme 7, USP18 Ubiquitin Specific Peptidase 18, PARP14 Protein Mono-ADP-Ribosyltransferase, IFIT3 Interferon Induced Protein With Tetratricopeptide Repeats 3, IRF 7 Interferon Regulatory Factor 7, RSAD2 Radical S-Adenosyl Methionine Domain Containing 2, IGTP Interferon gamma-Induced GTPase, MX2 MX Dynamin Like GTPase 2, RTP4 Receptor Transporter Protein 4, OASL2 2’-5’-Oligoadenylate Synthase-like Protein 2, IRGM2 Immunity-related GTPase Family M member 2, LGALS3BP Galectin 3 Binding Protein, OAS2 2’-5’-Oligoadenylate Synthetase 2, RVFV Rift Valley Fever Virus, VLPs Virus-like Particles. Figure 1 A protective mechanism mediated by the RNF213 protein against palmitate-induced lipotoxicity (ER, endoplasmic reticulum). Figure 2 A possible link between RNF213 and lipid droplet (LD) stability. An overexpression of RNF213 increases the number and the covered area of LDs, while RNF213 depletion significantly reduced the abundance of LDs (siRNA, small interfering RNA; ATGL, adipose triglyceride lipase). Figure 3 RNF213 protects against RVFV (Rift Valley Fever Virus) infection by increasing the level of LDs (lipid droplets). Figure 4 The RNF213 ubiquitin (Ub) E3 ligase domain mediates the ubiquitylation of Lipid A of bacterial lipopolysaccharide (LPS). Figure 5 RNF213 oligomerization and translocation to lipid droplets (LDs) may serve for the creation of a binding platform for Interferon-Stimulated Gene 15 (ISG15) and multiple ISGylated proteins (IFN I, interferon I; IFN II, interferon II). Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ahel J. Lehner A. Vogel A. Schleiffer A. Meinhart A. Haselbach D. Clausen T. Moyamoya disease factor RNF213 is a giant E3 ligase with a dynein-like core and a distinct ubiquitin-transfer mechanism eLife 2020 9 1 23 10.7554/eLife.56185 2. Kamada F. Aoki Y. Narisawa A. Abe Y. Komatsuzaki S. Kikuchi A. Kanno J. Niihori T. Ono M. Ishii N. A genome-wide association study identifies RNF213 as the first Moyamoya disease gene J. Hum. Genet. 2011 56 34 40 10.1038/jhg.2010.132 21048783 3. Guey S. Kraemer M. Hervé D. Ludwig T. Kossorotoff M. Bergametti F. Schwitalla J.C. Choi S. Broseus L. Callebaut L. Rare RNF213 variants in the C-terminal region encompassing the RING-finger domain are associated with moyamoya angiopathy in Caucasians Eur. J. Hum. Genet. 2017 25 995 1003 10.1038/ejhg.2017.92 28635953 4. Liu W. Morito D. Takashima S. Mineharu Y. Kobayashi H. Hitomi T. Hashikata H. Matsuura N. Yamazaki S. Toyoda A. Identification of RNF213 as a susceptibility gene for moyamoya disease and its possible role in vascular development PLoS ONE 2011 6 e22542 10.1371/journal.pone.0022542 21799892 5. Walker J.E. Saraste M. Runswick M.J. Gay N.J. Distantly related sequences in the alpha- and beta-subunits of ATP synthase, myosin, kinases and other ATP-requiring enzymes and a common nucleotide binding fold EMBO J. 1982 1 945 951 10.1002/j.1460-2075.1982.tb01276.x 6329717 6. Morito D. Nishikawa K. Hoseki J. Kitamura A. Kotani Y. Kiso K. Kinjo M. Fujiyoshi Y. Nagata K. Moyamoya disease-associated protein mysterin/RNF213 is a novel AAA+ ATPase, which dynamically changes its oligomeric state Sci. Rep. 2014 4 4442 10.1038/srep04442 24658080 7. Romero-Barrios N. Vert G. Proteasome-independent functions of lysine-63 polyubiquitination in plants New Phytol. 2018 217 995 1011 10.1111/nph.14915 29194634 8. Sarkar P. Thirumurugan K. New insights into TNFα/PTP1B and PPARγ pathway through RNF213- a link between inflammation, obesity, insulin resistance, and Moyamoya disease Gene 2021 771 145340 10.1016/j.gene.2020.145340 33333224 9. Liu W. Senevirathna S.T. Hitomi T. Kobayashi H. Roder C. Herzig R. Kraemer M. Voormolen M.H. Cahová P. Krischek B. Genomewide association study identifies no major founder variant in Caucasian moyamoya disease J. Genet. 2013 92 605 609 10.1007/s12041-013-0304-5 24371184 10. Grangeon L. Guey S. Schwitalla J.C. Bergametti F. Arnould M. Corpechot M. Hadjadj J. Riant F. Aloui C. Drunat S. Clinical and Molecular Features of 5 European Multigenerational Families with Moyamoya Angiopathy Stroke 2019 50 789 796 10.1161/STROKEAHA.118.023972 30908154 11. Guey S. Grangeon L. Brunelle F. Bergametti F. Amiel J. Lyonnet S. Delaforge A. Arnould M. Desnous B. Bellesme C. De novo mutations in CBL causing early-onset paediatric moyamoya angiopathy J. Med. Genet. 2017 54 550 557 10.1136/jmedgenet-2016-104432 28343148 12. Kobayashi H. Matsuda Y. Hitomi T. Okuda H. Shioi H. Matsuda T. Imai H. Sone M. Taura D. Harada K.H. Biochemical and Functional Characterization of RNF213 (Mysterin) R4810K, a Susceptibility Mutation of Moyamoya Disease, in Angiogenesis In Vitro and In Vivo J. Am. Heart Assoc. 2015 4 e002146 10.1161/JAHA.115.002146 26126547 13. Ohkubo K. Sakai Y. Inoue H. Akamine S. Ishizaki Y. Matsushita Y. Sanefuji M. Torisu H. Ihara K. Sardiello M. Moyamoya disease susceptibility gene RNF213 links inflammatory and angiogenic signals in endothelial cells Sci. Rep. 2015 5 13191 10.1038/srep13191 26278786 14. Takagi Y. Kikuta K. Nozaki K. Fujimoto M. Hayashi J. Imamura H. Hashimoto N. Expression of hypoxia-inducing factor-1 alpha and endoglin in intimal hyperplasia of the middle cerebral artery of patients with moyamoya disease Neurosurgery 2007 60 338 345 10.1227/01.NEU.0000249275.87310.FF 17290185 15. Takekawa Y. Umezawa T. Ueno Y. Sawada T. Kobayashi M. Pathological and immunohistochemical findings of an autopsy case of adult moyamoya disease Neuropathology 2004 24 236 242 10.1111/j.1440-1789.2004.00550.x 15484702 16. Takagi Y. Kikuta K. Nozaki K. Hashimoto N. Histological features of middle cerebral arteries from patients treated for moyamoya disease Neurol. Med. Chir. 2007 47 1 4 10.2176/nmc.47.1 17. Reid A.J. Bhattacharjee M.B. Regalado E.S. Milewicz A. El-Hakam L.M. Dauser R.C. Milewicz D.M. Diffuse and uncontrolled vascular smooth muscle cell proliferation in rapidly progressing pediatric moyamoya disease J. Neurosurg. Pediatr. 2010 6 244 249 10.3171/2010.5.PEDS09505 20809708 18. Achrol A.S. Guzman R. Lee M. Steinberg G.K. Pathophysiology and genetic factors in moyamoya disease Neurosurg. Focus. 2009 26 E4 10.3171/2009.1.FOCUS08302 19. Phi J.H. Suzuki N. Moon Y.J. Park A.K. Wang K.C. Lee J.Y. Choi S.A. Chong S. Shirane R. Kim S.K. Chemokine Ligand 5 (CCL5) Derived from Endothelial Colony-Forming Cells (ECFCs) Mediates Recruitment of Smooth Muscle Progenitor Cells (SPCs) toward Critical Vascular Locations in Moyamoya Disease PLoS ONE 2017 12 e0169714 10.1371/journal.pone.0169714 28072843 20. Hamauchi S. Shichinohe H. Uchino H. Yamaguchi S. Nakayama N. Kazumata K. Osanai T. Abumiya T. Houkin K. Era T. Cellular functions and gene and protein expression profiles in endothelial cells derived from Moyamoya disease-specific iPS cells PLoS ONE 2016 11 e163561 10.1371/journal.pone.0163561 21. Matsuo M. Nadanaka S. Soga M. Sugiyama T. Serigano S. Shimano K. Ichinose F. Nakamura T. Maeda T. Houkin K. Vulnerability to shear stress caused by altered peri—Endothelial matrix is a key feature of Moyamoya disease Sci. Rep. 2021 11 1552 10.1038/s41598-021-81282-9 33452387 22. Habu T. Harada K.H. UBC13 is an RNF213-associated E2 ubiquitin-conjugating enzyme, and Lysine 63-linked ubiquitination by the RNF213-UBC13 axis is responsible for angiogenic activity FASEB Bio. Adv. 2021 3 243 258 10.1096/fba.2019-00092 33842849 23. Wang G. Gao Y. Li L. Jin G. Cai Z. Chao J.I. Lin H.K. K63-linked ubiquitination in kinase activation and cancer Front. Oncol. 2012 2 5 10.3389/fonc.2012.00005 22649774 24. Pickart C.M. Fushman D. Polyubiquitin chains: Polymeric protein signals Curr. Opin. Chem. Biol. 2004 8 610 616 10.1016/j.cbpa.2004.09.009 15556404 25. Banh R.S. Iorio C. Marcotte R. Xu Y. Cojocari D. Rahman A.A. Pawling J. Zhang W. Sinha A. Rose C.M. PTP1B controls non-mitochondrial oxygen consumption by regulating RNF213 to promote tumour survival during hypoxia Nat. Cell Biol. 2016 18 803 813 10.1038/ncb3376 27323329 26. Bai Y. Sun Q. Macrophage recruitment in obese adipose tissue Obes. Rev. 2015 16 127 136 10.1111/obr.12242 27. Song D.D. Chen Y. Li Z.Y. Guan Y.F. Zou D.J. Miao C.Y. Protein tyrosine phosphatase 1B inhibits adipocyte differentiation and mediates TNFα action in obesity Biochim. Biophys. Acta. 2013 1831 1368 1376 10.1016/j.bbalip.2013.05.006 23711960 28. Bansal S. Mahendiratta S. Agrawal M. Kumar S. Sharma A.R. Garg N. Joshi R. Sarma P. Prakash A. Chopra K. Role of protein tyrosine phosphatase 1B inhibitor in central insulin resistance and associated cognitive deficits Brain Res. Bull. 2021 171 113 125 10.1016/j.brainresbull.2021.02.026 33684458 29. Lorenzo M. Fernández-Veledo S. Vila-Bedmar R. Garcia-Guerra L. De Alvaro C. Nieto-Vazquez I. Insulin resistance induced by tumor necrosis factor-alpha in myocytes and brown adipocytes J. Anim. Sci. 2008 86 (Suppl. S14) E94 E104 10.2527/jas.2007-0462 17940160 30. Ao C. Huo Y. Qi L. Xiong Z. Xue L. Qi Y. Pioglitazone suppresses the lipopolysaccharide-induced production of inflammatory factors in mouse macrophages by inactivating NF-kappaB Cell Biol. Int. 2010 34 723 730 10.1042/CBI20090005 19947950 31. Dadke S.S. Li H.C. Kusari A.B. Begum N. Kusari J. Elevated expression and activity of protein-tyrosine phosphatase 1B in skeletal muscle of insulin-resistant type II diabetic Goto-Kakizaki rats Biochem. Biophys. Res. Commun. 2000 274 583 589 10.1006/bbrc.2000.3188 10924321 32. Lam N.T. Covey S.D. Lewis J.T. Oosman S. Webber T. Hsu E.C. Cheung A.T. Kieffer T.J. Leptin resistance following over-expression of protein tyrosine phosphatase 1B in liver J. Mol. Endocrinol. 2006 36 163 174 10.1677/jme.1.01937 16461936 33. Epstein A.C. Gleadle J.M. McNeill L.A. Hewitson K.S. O’Rourke J. Mole D.R. Mukherji M. Metzen E. Wilson M.I. Dhanda A. elegans EGL-9 and mammalian homologs define a family of dioxygenases that regulate HIF by prolyl hydroxylation Cell 2001 107 43 54 10.1016/S0092-8674(01)00507-4 11595184 34. Thery F. Martina L. Asselman C. Zhang Y. Vessely M. Repo H. Sedeyn K. Moschonas G.D. Bredow C. Teo Q.W. Ring finger protein 213 assembles into a sensor for ISGylated proteins with antimicrobial activity Nat. Commun. 2021 12 5772 10.1038/s41467-021-26061-w 34599178 35. Yeh Y.H. Yang Y.C. Hsieh M.Y. Yeh Y.C. Li T.K. A negative feedback of the HIF-1α pathway via interferon-stimulated gene 15 and ISGylation Clin. Cancer Res. 2013 19 5927 5939 10.1158/1078-0432.CCR-13-0018 24056783 36. Brookheart R.T. Michel C.I. Schaffer J.E. As a matter of fat Cell Metab. 2009 10 9 12 10.1016/j.cmet.2009.03.011 19583949 37. Shimabukuro M. Zhou Y.T. Levi M. Unger R.H. Fatty acid-induced beta cell apoptosis: A link between obesity and diabetes Proc. Natl. Acad. Sci. USA 1998 95 2498 2502 10.1073/pnas.95.5.2498 9482914 38. Paumen M.B. Ishida Y. Muramatsu M. Yamamoto M. Honjo T. Inhibition of carnitine palmitoyltransferase I augments sphingolipid synthesis and palmitate-induced apoptosis J. Biol. Chem. 1997 272 3324 3329 10.1074/jbc.272.6.3324 9013572 39. Piccolis M. Bond L.M. Kampmann M. Pulimeno P. Chitraju C. Jayson C. Vaites L.P. Boland S. Lai Z.W. Gabriel K.R. Probing the Global Cellular Responses to Lipotoxicity Caused by Saturated Fatty Acids Mol. Cell 2019 74 32 44.e8 10.1016/j.molcel.2019.01.036 30846318 40. Kitai Y. Ariyama H. Kono N. Oikawa D. Iwawaki T. Arai H. Membrane lipid saturation activates IRE1α without inducing clustering Genes Cells 2013 18 798 809 10.1111/gtc.12074 23803178 41. Sugihara M. Morito D. Ainuki S. Hirano Y. Ogino K. Kitamura A. Hirata H. Nagata K. The AAA+ ATPase/ubiquitin ligase mysterin stabilizes cytoplasmic lipid droplets J. Cell Biol. 2019 218 949 960 10.1083/jcb.201712120 30705059 42. Scott R.M. Smith E.R. Moyamoya disease and moyamoya syndrome N. Engl. J. Med. 2009 360 1226 1237 10.1056/NEJMra0804622 19297575 43. Mineharu Y. Miyamoto S. RNF213 and GUCY1A3 in Moyamoya Disease: Key Regulators of Metabolism, Inflammation, and Vascular Stability Front. Neurol. 2021 12 687088 10.3389/fneur.2021.687088 34381413 44. Choi J.W. Son S.M. Mook-Jung I. Moon Y.J. Lee J.Y. Wang K.C. Kang H.S. Phi J.H. Choi S.A. Chong S. Mitochondrial abnormalities related to the dysfunction of circulating endothelial colony-forming cells in moyamoya disease J. Neurosurg. 2018 129 1151 1159 10.3171/2017.5.JNS17147 29219755 45. Wang X. Han C. Jia Y. Wang J. Ge W. Duan L. Proteomic Profiling of Exosomes from Hemorrhagic Moyamoya Disease and Dysfunction of Mitochondria in Endothelial Cells Stroke 2021 52 3351 3361 10.1161/STROKEAHA.120.032297 34334053 46. Geng C. Cui C. Guo Y. Wang C. Zhang J. Han W. Jin F. Chen D. Jiang P. Metabolomic Profiling Revealed Potential Biomarkers in Patients with Moyamoya Disease Front. Neurosci. 2020 14 308 10.3389/fnins.2020.00308 32372905 47. Dei Cas M. Carrozzini T. Pollaci G. Potenza A. Nava S. Canavero I. Tinelli F. Gorla G. Vetrano I.G. Acerbi F. Plasma Lipid Profiling Contributes to Untangle the Complexity of Moyamoya Arteriopathy Int. J. Mol. Sci. 2021 22 13410 10.3390/ijms222413410 34948203 48. Tinelli F. Nava S. Arioli F. Bedini G. Scelzo E. Lisini D. Faragò G. Gioppo A. Ciceri E.F. Acerbi F. Vascular Remodeling in Moyamoya Angiopathy: From Peripheral Blood Mononuclear Cells to Endothelial Cells Int. J. Mol. Sci. 2020 21 5763 10.3390/ijms21165763 49. Hill J.M. Zalos G. Halcox J.P. Schenke W.H. Waclawiw M.A. Quyyumi A.A. Finkel T. Circulating endothelial progenitor cells, vascular function, and cardiovascular risk N. Engl. J. Med. 2003 348 593 600 10.1056/NEJMoa022287 12584367 50. Houzelstein D. Simon-Chazottes D. Batista L. Tokuda S. Langa Vives F. Flamand M. Montagutelli X. Panthier J.J. The ring finger protein 213 gene (Rnf213) contributes to Rift Valley fever resistance in mice Mamm. Genome 2021 32 30 37 10.1007/s00335-020-09856-y 33420513 51. Shraim M.A. Eid R. Radad K. Saeed N. Ultrastructural pathology of human liver in Rift Valley fever BMJ Case Rep. 2016 2016 bcr2016216054 10.1136/bcr-2016-216054 52. Batista L. Jouvion G. Simon-Chazottes D. Houzelstein D. Burlen-Defranoux O. Boissière M. Tokuda S. do Valle T.Z. Cumano A. Flamand M. Genetic dissection of Rift Valley fever pathogenesis: Rvfs2 locus on mouse chromosome 11 enables survival to early-onset hepatitis Sci. Rep. 2020 10 8734 10.1038/s41598-020-65683-w 32457349 53. Smith D.R. Steele K.E. Shamblin J. Honko A. Johnson J. Reed C. Kennedy M. Chapman J.L. Hensley L.E. The pathogenesis of Rift Valley fever virus in the mouse model Virology 2010 407 256 267 10.1016/j.virol.2010.08.016 20850165 54. Reed C. Steele K.E. Honko A. Shamblin J. Hensley L.E. Smith D.R. Ultrastructural study of Rift Valley fever virus in the mouse model Virology 2012 431 58 70 10.1016/j.virol.2012.05.012 22687428 55. Otten E.G. Werner E. Crespillo-Casado A. Boyle K.B. Dharamdasani V. Pathe C. Santhanam B. Randow F. Ubiquitylation of lipopolysaccharide by RNF213 during bacterial infection Nature 2021 594 111 116 10.1038/s41586-021-03566-4 34012115 56. Huang J. Brumell J.H. Bacteria-autophagy interplay: A battle for survival Nat. Rev. Microbiol. 2014 12 101 114 10.1038/nrmicro3160 24384599 57. Perrin A.J. Jiang X. Birmingham C.L. So N.S. Brumell J.H. Recognition of bacteria in the cytosol of Mammalian cells by the ubiquitin system Curr. Biol. 2004 14 806 811 10.1016/j.cub.2004.04.033 15120074 58. Deretic V. Saitoh T. Akira S. Autophagy in infection, inflammation and immunity Nat. Rev. Immunol. 2013 13 722 737 10.1038/nri3532 24064518 59. Yuan W. Krug R.M. Influenza B virus NS1 protein inhibits conjugation of the interferon (IFN)-induced ubiquitin-like ISG15 protein EMBO J. 2001 20 362 371 10.1093/emboj/20.3.362 11157743 60. Zhao C. Beaudenon S.L. Kelley M.L. Waddell M.B. Yuan W. Schulman B.A. Huibregtse J.M. Krug R.M. The UbcH8 ubiquitin E2 enzyme is also the E2 enzyme for ISG15, an IFN-alpha/beta-induced ubiquitin-like protein Proc. Natl. Acad. Sci. USA 2004 101 7578 7582 10.1073/pnas.0402528101 15131269 61. Dastur A. Beaudenon S. Kelley M. Krug R.M. Huibregtse J.M. Herc5, an interferon-induced HECT E3 enzyme, is required for conjugation of ISG15 in human cells J. Biol. Chem. 2006 281 4334 4338 10.1074/jbc.M512830200 16407192 62. Zou W. Zhang D.E. The interferon-inducible ubiquitin-protein isopeptide ligase (E3) EFP also functions as an ISG15 E3 ligase J. Biol. Chem. 2006 281 3989 3994 10.1074/jbc.M510787200 16352599 63. Okumura F. Zou W. Zhang D.E. ISG15 modification of the eIF4E cognate 4EHP enhances cap structure-binding activity of 4EHP Genes Dev. 2007 21 255 260 10.1101/gad.1521607 17289916 64. Radoshevich L. Impens F. Ribet D. Quereda J.J. Nam Tham T. Nahori M.A. Bierne H. Dussurget O. Pizarro-Cerdá J. Knobeloch K.P. ISG15 counteracts Listeria monocytogenes infection eLife 2015 4 e06848 10.7554/eLife.06848 26259872 65. Malakhova O. Malakhov M. Hetherington C. Zhang D.E. Lipopolysaccharide activates the expression of ISG15-specific protease UBP43 via interferon regulatory factor 3 J. Biol. Chem. 2002 277 14703 14711 10.1074/jbc.M111527200 11854279 66. Bazzigher L. Pavlovic J. Haller O. Staeheli P. Mx genes show weaker primary response to virus than other interferon-regulated genes Virology 1992 186 154 160 10.1016/0042-6822(92)90069-2 1370126 67. Kimmey J.M. Campbell J.A. Weiss L.A. Monte K.J. Lenschow D.J. Stallings C.L. The impact of ISGylation during Mycobacterium tuberculosis infection in mice Microbes Infect. 2017 19 249 258 10.1016/j.micinf.2016.12.006 28087453 68. Napolitano A. van der Veen A.G. Bunyan M. Borg A. Frith D. Howell S. Kjaer S. Beling A. Snijders A.P. Knobeloch K.-P. Cysteine-Reactive Free ISG15 Generates IL-1β-Producing CD8α+ Dendritic Cells at the Site of Infection J. Immunol. 2018 201 604 614 10.4049/jimmunol.1701322 29891555 69. Durfee L.A. Lyon N. Seo K. Huibregtse J.M. The ISG15 conjugation system broadly targets newly synthesized proteins: Implications for the antiviral function of ISG15 Mol. Cell 2010 38 722 732 10.1016/j.molcel.2010.05.002 20542004 70. Cecchi A.C. Guo D. Ren Z. Flynn K. Santos-Cortez R.L. Leal S.M. Wang G.T. Regalado E.S. Steinberg G.K. Shendure J. RNF213 rare variants in an ethnically diverse population with Moyamoya disease Stroke 2014 45 3200 3207 10.1161/STROKEAHA.114.006244 25278557 71. Koizumi A. Kobayashi H. Liu W. Fujii Y. Senevirathna S.T. Nanayakkara S. Okuda H. Hitomi T. Harada K.H. Takenaka K. R4810K, a polymorphism of RNF213, the susceptibility gene for moyamoya disease, is associated with blood pressure Environ. Health Prev. Med. 2013 18 121 129 10.1007/s12199-012-0299-1 22878964 72. Lin J. Liang J. Wen J. Luo M. Li J. Sun X. Xu X. Li J. Wang D. Wang J. Mutations of RNF213 are responsible for sporadic cerebral cavernous malformation and lead to a mulberry-like cluster in zebrafish J. Cereb. Blood Flow. Metab. 2021 41 1251 1263 10.1177/0271678X20914996 32248732 73. Kiando S.R. Barlassina C. Cusi D. Galan P. Lathrop M. Plouin P.F. Jeunemaitre X. Bouatia-Naji N. Exome sequencing in seven families and gene-based association studies indicate genetic heterogeneity and suggest possible candidates for fibromuscular dysplasia J. Hypertens. 2015 33 1802 1810 10.1097/HJH.0000000000000625 26147384 74. Miyawaki S. Imai H. Shimizu M. Yagi S. Ono H. Mukasa A. Nakatomi H. Shimizu T. Saito N. Genetic variant RNF213 c.14576G>A in various phenotypes of intracranial major artery stenosis/occlusion Stroke 2013 44 2894 2897 10.1161/STROKEAHA.113.002477 23970789 75. Zhou S. Ambalavanan A. Rochefort D. Xie P. Bourassa C.V. Hince P. Dionne-Laporte A. Spiegelman D. Gan-Or Z. Mirarchi C. RNF213 Is Associated with Intracranial Aneurysms in the French-Canadian Population Am. J. Hum. Genet. 2016 99 1072 1085 10.1016/j.ajhg.2016.09.001 27745834 76. Sigdel T.K. Shoemaker L.D. Chen R. Li L. Butte A.J. Sarwal M.M. Steinberg G.K. Immune response profiling identifies autoantibodies specific to Moyamoya patients Orphanet. J. Rare Dis. 2013 8 45 10.1186/1750-1172-8-45 23518061

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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092458 jcm-11-02458 Article Effects of High-Resolution CT Changes on Prognosis Predictability in Acute Respiratory Distress Syndrome with Diffuse Alveolar Damage Huang Ching-Ying 1 https://orcid.org/0000-0002-7453-0368 Wu Patricia Wanping 1 https://orcid.org/0000-0001-8831-3295 Wong Yon-Cheong 1 https://orcid.org/0000-0002-8777-1638 Kao Kuo-Chin 234 https://orcid.org/0000-0003-1746-6782 Huang Chung-Chi 234* Chiumello Davide Academic Editor Windisch Wolfram Academic Editor 1 Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, Taoyuan 33353, Taiwan; noctis.huang@gmail.com (C.-Y.H.); pwwu@cgmh.org.tw (P.W.W.); ycwong@cgmh.org.tw (Y.-C.W.) 2 Department of Respiratory Therapy, College of Medicine, Chang Gung University, Taoyuan 33353, Taiwan; kck0502@cgmh.org.tw 3 Department of Pulmonary and Critical Care Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 33353, Taiwan 4 Department of Respiratory Therapy, Linkou Chang Gung Memorial Hospital, Taoyuan 33353, Taiwan * Correspondence: cch4848@cgmh.org.tw; Tel.: +886-3-3281200 (ext. 8467); Fax: +886-3-3287787 27 4 2022 5 2022 11 9 245805 3 2022 22 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Diffuse alveolar damage (DAD) is the pathological hallmark of acute respiratory distress syndrome (ARDS). DAD is independently correlated with higher mortality compared with the absence of DAD. Traction bronchiectasis in areas of ground-glass opacity or consolidation is associated with the late fibroproliferative or fibrotic phase of DAD. This study examined whether the 60-day mortality related to DAD could be predicted using high-resolution computed tomography (HRCT) findings and HRCT scores. A total of 34 patients with DAD who received HRCT within 7 days of ARDS diagnosis were enrolled; they were divided into a 60-day survival group and a nonsurvival group, with 17 patients in each group. Univariate and multivariate binary regression analyses and the receiver operating characteristic curve revealed that only the total percentage of the area with traction bronchiectasis or bronchiolectasis was an independent predictor of 60-day mortality (odds ratio, 1.067; 95% confidence interval (CI), 1.011–1.126) and had favorable predictive performance (area under the curve (AUC): 0.784; 95% CI, 0.621–0.946; cutoff, 21.7). Physiological variables, including age, days from ARDS to HRCT, the sequential organ failure assessment (SOFA) score, the PaO2/fraction of inspired oxygen (FiO2) ratio, dynamic driving pressure, and dynamic mechanical power, were not discriminative between 60-day survival and nonsurvival. In conclusion, the extent of fibroproliferation on HRCT in early ARDS, presented as the total percentage of area with bronchiectasis or bronchiolectasis, is an independent positive predictor with a favorable predictive ability for the 60-day mortality of DAD. acute respiratory distress syndrome diffuse alveolar damage high-resolution computed tomography traction bronchiectasis mechanical power This research received no external funding. ==== Body pmc1. Introduction Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury in the ICU. The LUNG SAFE study revealed that the incidence of ARDS among ICU admissions was 10.4% [1]. ARDS-related mortality was over 40% in two large cohorts and has remained high in the past 10 years [2,3]. Regarding the mortality for different severities, the recent LUNG SAFE study disclosed that hospital mortality was 34.9% for those with mild, 40.3% for those with moderate, and 46.1% for those with severe ARDS [1]. Diffuse alveolar damage (DAD), characterized by interstitial edema, type II cell hyperplasia, acute inflammation, and hyaline membranes, is the pathological hallmark of the acute exudative phase of ARDS [3]. ARDS patients tend to progress to the fibroproliferative phase and then the fibrotic phase if they survive after the initial exudative phase [4]. However, several autopsy [5] and open lung biopsy (OLB) [6,7,8] studies have revealed that only approximately half of patients with ARDS have DAD. Compared with the absence of DAD, DAD is associated with greater disease severity and is an independent risk factor for higher mortality [5,6,7,8]. However, the PREDATOR study concluded that DAD cannot be predicted merely on the basis of clinical parameters and that tissue biopsy is required for the histopathological diagnosis of DAD [9]. OLB, a routine procedure, is complex and presents various risks; therefore, the authors proposed that developing alternate methods, such as biomarkers and lung imaging techniques, for diagnosing DAD is necessary. High-resolution computed tomography (HRCT) findings have substantial value in ARDS diagnosis [10,11,12,13] and correspond to the pathological phases of DAD [14,15,16]. The absence of traction bronchiectasis or bronchiolectasis in areas of ground-glass opacity (GGO) or consolidation corresponds to the exudative and early proliferative phases of DAD, whereas the presence of traction bronchiectasis or bronchiolectasis in areas of GGO or consolidation is associated with the late proliferative and fibrotic phases of such damage. Ichikado et al. [17] assigned different weights to HRCT findings, including normal attenuation, GGO, consolidation, traction bronchiectasis, and honeycombing, and established a scoring system to evaluate the severity of fibroproliferative changes in the lung parenchyma. They reported that extensive fibroproliferative changes on HRCT were an independent predictor of poor prognosis in the clinical early stage of ARDS. They also revealed that HRCT scores <230 could predict 28-day survival after ARDS onset (area under the receiver operating characteristic curve (AUROC), 0.808; sensitivity, 73%; specificity, 75%) and were associated with a lower incidence of barotrauma and a greater number of ventilator-free days. They also proposed that in patients with early ARDS, the extent of pulmonary fibroproliferation assessed using HRCT and an HRCT score of >210 could predict an increase in 60-day mortality (AUROC, 0.71; 95% confidence interval (CI), 0.61–0.82; sensitivity, 71%; specificity, 72%), with a greater susceptibility of these patients to multiple organ failure and ventilator dependency and their associated outcomes [18]. The risk of hospital mortality related to cases with DAD has been reported to be approximately two times higher than that related to cases without DAD [6,9]. Because of the poorer prognosis of DAD, this study examined whether changes in and scores of HRCT performed within 7 days of ARDS diagnosis could predict the 60-day mortality of patients with ARDS with pathologically confirmed DAD. 2. Materials and Methods 2.1. Patient Enrollment We retrospectively reviewed the medical charts of all ARDS cases that fulfilled the Berlin definition criteria [3] and received lung biopsies at the Linkou Chang Gung Memorial Hospital after 2003. A total of 126 cases with lung biopsies were collected, including 105 patients that received open lung biopsy (OLB) and 21 patients that received cryobiopsy. In most of these cases, lung biopsy was indicated when ARDS was suspected to be noninfectious and the patient did not exhibit clear risk factors. The clinical and radiological manifestations progressed rapidly. The infiltrations, GGO, or consolidation revealed on chest X-ray or HRCT were bilateral, with a relatively symmetrical distribution. Informed consent for OLB or cryobiopsy was obtained from the patients’ families. A flowchart for patient enrollment and exclusion is presented in Figure 1. Of the 126 patients with lung biopsies, 68 had a pathological diagnosis of DAD. The remaining 51 did not have DAD; 7 cases with usual interstitial pneumonia were excluded. Of the 68 DAD cases, 21 cases with a time from HRCT to ARDS diagnosis of more than 7 days, 6 cases with no available HRCT data, and 5 cases of chronic lung disease according to the clinical history or previous radiological findings were also excluded. Because this study was retrospective, it was difficult to have HRCT performed at the time of diagnosis of ARDS in every case. For the first week after ARDS onset, the main histopathology is the acute exudative phase, followed by the fibroproliferative and fibrotic phases from the second week onward. We wanted to know whether the ARDS patients had entered into the fibroproliferative or fibrotic phases in the clinical early stage at the time of ARDS diagnosis. If the HRCT was performed over 7 days after ARDS diagnosis, it was reasonable that the HRCT would reveal fibroproliferative changes because of disease progression. Therefore, only DAD patients with HRCT performed within 7 days of ARDS diagnosis were enrolled. Finally, 34 patients with DAD were enrolled and divided into two groups, the 60-day survival group and the nonsurvival group, with 17 patients in each group. In this study, we defined 60-day survival as either (1) patients who remained admitted or (2) patients who were discharged but whose OPD follow-up record could be found over 60 days after admission. The Institutional Review Board (IRB) of Chang Gung Memorial Hospital approved the study protocol (IRB number 202200184B0), and the study was performed in compliance with the tenets of the Declaration of Helsinki. The IRB waived the need for written informed consent because this study was retrospective and had no bearing on modifications to patient management. All personal information in the database were encrypted and deidentified. The pathological criteria for DAD diagnosis included the presence of hyaline membranes, pulmonary inflammatory infiltrates, intra-alveolar and interstitial edema, alveolar type II cell hyperplasia, interstitial proliferation of fibroblasts and myofibroblasts, and organizing interstitial fibrosis. 2.2. Clinical Data The following clinical data were retrieved from the patients’ medical charts: age, sex, body weight, underlying diseases, ARDS diagnosis, the time from HRCT and lung biopsy to ARDS diagnosis, the time from lung biopsy to HRCT, the duration of mechanical ventilation until ventilator weaning or patient death, the sequential organ failure assessment (SOFA) score, the PaO2/FiO2 (P/F) ratio, tidal volume, the positive end-expiratory pressure (PEEP) level, peak airway pressure, dynamic driving pressure, dynamic mechanical power (MP), and the severity of ARDS according to the Berlin definition criteria [3]. The clinical data, Coma scale, and SOFA score were recorded at the time of diagnosis of ARDS before sedation and paralysis. 2.3. Examination, Assessment, and Scoring of HRCT Whole-lung volumetric HRCT scans were performed using multidetector-row computed tomography (CT) at full inspiration from the lung apex to the base. All multidetector-row CT scans were obtained with a 2.5 mm section thickness and a table speed per rotation of 15 mm. Abutting CT slices were reconstructed using a high-spatial frequency algorithm. The sections were displayed at 10 mm intervals throughout the chest with the patient in a supine position. According to the recommendations of the Nomenclature Committee of the Fleischner Society [19], the HRCT abnormalities were defined as follows: GGO—hazy areas denoting increased lung attenuation, but with preservation of bronchial and vascular margins; consolidation—homogeneous increase in pulmonary parenchymal attenuation that obscures the margins of vessels and airway walls; traction bronchiectasis—bronchial dilatation, which is commonly irregular, in association with juxtabronchial opacification that is interpreted as representing retractile pulmonary fibrosis; traction bronchiolectasis—bronchiolar dilatation in association with peribronchiolar opacification that is interpreted as representing retractile pulmonary fibrosis; honeycombing—clustered cystic air spaces (between 0.3 and 1.0 cm in diameter, but occasionally as large as 2.5 cm), which are usually subpleural and characterized by well-defined, often thick, walls. The chest radiography and HRCT scans of a case in the survival group and a case in the nonsurvival group are illustrated in Figure 2. We adopted the HRCT scoring system proposed by Ichikado et al. to evaluate the severity of parenchyma abnormalities. The scoring system was previously used in the evaluation of HRCT findings of patients with acute interstitial pneumonia (AIP) [16], ARDS [17,18], and idiopathic pulmonary fibrosis (IPF) [20]. The HRCT findings were ranked on a scale of 1–6 on the basis of the classification system, with the scores indicating the following: 1—normal attenuation, 2—GGO, 3—consolidation, 4—GGO with traction bronchiectasis or bronchiolectasis, 5—consolidation with traction bronchiectasis or bronchiolectasis, and 6—honeycombing. The left and right lungs were divided into an upper zone (the area above the level of the carina), a middle zone (the area between the carina and infrapulmonary vein), and a lower zone (the area below the level of the infrapulmonary vein). The extent of each of these six abnormalities was assessed independently in each of the six zones (i.e., the upper, middle, and lower zones of the left and right lungs). The proportion of each HRCT abnormality in the affected lung parenchyma in each zone was assessed through a visual estimation of the percentage (to the nearest 10%). The abnormality score for each zone was calculated by multiplying the percentage area by the ranking score obtained (1–6). The total score for each abnormality was calculated as the average of the scores of the six zones for each patient. The final CT score for each patient was obtained through the summation of the six averaged scores. The HRCT scores were independently evaluated by one pulmonologist and one radiologist. The assessment scores assigned by these two observers were averaged. Because our study was retrospective, and because data on plateau pressure and static measurements were not available for all cases, the dynamic driving pressure and dynamic MP were applied in this cohort. The dynamic driving pressure was calculated by subtracting the PEEP from the peak inspiratory pressure. The dynamic MP was calculated as follows: 0.098 × respiratory rate × tidal volume × [peak inspiratory pressure—(0.5 × dynamic driving pressure)] [21]. 2.4. Statistical Analysis All variables are expressed as means ± standard deviation. The Kolmogorov–Smirnov test was used to verify the normality of the distributions of continuous variables. Differences in the continuous variables between the survival and nonsurvival groups were analyzed using Student’s t-test or Mann–Whitney U test. Differences in categorical variables between the survival and nonsurvival groups were compared using the chi-square test or Fisher’s exact test. Univariate binary logistic regression model analyses were applied to evaluate the association between the 60-day mortality and the selected variables. The variables significantly associated with the outcome of 60-day mortality were input into the multivariate logistic regression model to assess their independent contribution to the outcome. The ability of the studied variables to predict 60-day mortality was tested using the receiver operating characteristic (ROC) curve. The area under each ROC curve (AUC) was calculated, with a value of <0.5 indicating the inability of the indicator to accurately predict 60-day mortality. The cutoff value for the data was based on the maximum value of Youden’s index (J = sensitivity + specificity − 1). Linear regression and correlation analysis were used to analyze the association of the HRCT scores and total percentage of the area with traction bronchiectasis with ARDS severity (P/F ratio) and lung mechanics (dynamic MP). All statistical analyses were conducted using SPSS for Windows (version 22, Chicago, IL, USA), and a p-value of < 0.05 was considered significant. 3. Results The data of 126 patients with ARDS who received lung biopsies after 2003 were collected; of these patients, 68 had DAD, 51 did not have DAD, and 7 had IPF. Among the 68 patients with DAD, we excluded 21 cases with a time from HRCT to ARDS diagnosis of more than 7 days, 6 cases with no available HRCT, and 5 patients with chronic lung disease to avoid false increases in the HRCT score. The remaining 34 patients with a time from HRCT to ARDS diagnosis of <7 days were enrolled (Figure 1), with 17 categorized in the 60-day survival group and 17 in the 60-day nonsurvival group. The main clinical characteristics of these 34 cases are summarized in Table 1. No significant differences were noted in the clinical parameters except the HRCT score between the survival and nonsurvival groups. The HRCT abnormalities and HRCT scores are listed in Table 2. No significant differences in any of the six HRCT findings were observed between the survival and nonsurvival groups. However, the mean HRCT score and the mean total percentage of the area with traction bronchiectasis or bronchiolectasis were significantly higher in the nonsurvival group (272.7 ± 49.4; 34.0 ± 16.6) than in the survival group (241.9 ± 47.2; 19.6 ± 17.3), indicating more fibroproliferative change in the nonsurvival group than in the survival group at an early stage of diagnosis. The binary logistic regression model was applied to investigate whether the severity of illness (SOFA score), the severity of ARDS (PaO2/FiO2 ratio), impairment of pulmonary mechanics (dynamic driving pressure and dynamic MP), and the severity of parenchyma HRCT abnormality (HRCT score and total percentage of area with traction bronchiectasis) were independently associated with 60-day mortality. The dynamic MP (odds ratio (OR), 1.325; 95% CI, 1.018–1.723) and the total percentage of the area with traction bronchiectasis or bronchiolectasis (OR, 1.174; 95% CI, 1.011–1.326) positively predicted 60-day mortality (Table 3). Both these variables were input into the multiple logistic regression model, and only the total percentage of the area with traction bronchiectasis or bronchiolectasis remained an independent positive predictor of 60-day mortality (OR, 1.067; 95% CI, 1.011–1.126). The ROC curve and the corresponding AUC were used to assess the performance of the aforementioned severity variables in predicting 60-day mortality and to determine the cutoff values of the statistically significant variables (Figure 3). The total percentage of the area with traction bronchiectasis or bronchiolectasis had a favorable predictive value [22] and the highest AUC (AUC, 0.784; cutoff, 21.7) among the five tested severity variables. The AUC for the HRCT score was 0.727, with a cutoff value of 263.3. The predictive abilities of the SOFA score, P/F ratio, and dynamic MP were no better than chance. The results of the linear regression and correlation analysis revealed no significant correlation between the HRCT score and the dynamic MP (p = 0.29; R = −0.18) or P/F ratio (p = 0.927; R = 0.163) or between the total percentage of the area with traction bronchiectasis and the MP (p = 0.148; R = −0.25) or P/F ratio (p = 0.36; R = 0.16). 4. Discussion The main study findings are as follows. (1) The HRCT score and the total percentage of the area with traction bronchiectasis or bronchiolectasis were significantly higher in the 60-day nonsurvival group than in the survival group. (2) As an alternative to the HRCT score, the total percentage of the area with traction bronchiectasis or bronchiolectasis was an independent predictor of 60-day mortality and exhibited a favorable predictive value (AUC, 0.784; 95% CI, 0.621–0.946). (3) Physiologic variables, including age, days from ARDS to HRCT, SOFA score, P/F ratio, dynamic driving pressure, and dynamic MP, were not discriminative between the 60-day survival and nonsurvival groups. (4) The HRCT findings, including both the HRCT score and the total percentage of the area with traction bronchiectasis or bronchiolectasis, were not correlated with ARDS severity (P/F ratio) or the impairment of pulmonary mechanics (dynamic MP). DAD has been proposed to be the histological hallmark of acute-phase ARDS [3]. However, recent OLB [6,7,8] and autopsy [5,23,24,25] studies have consistently reported that only approximately half of ARDS cases diagnosed on the basis of the Berlin definition had DAD. Both the meta-analysis (n = 350) [6] and the PREDATOR study (n = 258) [9] by Cardinal-Fernandez et al. similarly demonstrated that those with DAD had a poorer prognosis than those without DAD, with the risk of hospital mortality approximately two times higher for those with DAD than that for those without DAD. Most of the aforementioned studies aimed to investigate the differences between cases with DAD and those without DAD and determine which of the physiological variables (e.g., SOFA score and P/F ratio) might be independently associated with DAD-related mortality. However, the results were inconsistent because of the differences in the enrolled patient population and sample size among the studies. Moreover, a model for distinguishing cases with DAD from those without DAD could not be established [6,9]. The PREDATOR [9] study concluded that histological DAD could not be predicted on the basis of clinical variables. By contrast, our study focused on the prediction of pathologically confirmed DAD. However, we found no significant difference in physiological variables between the survival and nonsurvival groups (Table 1). The acute exudative phase of DAD occurs mainly in the first week after ARDS onset, followed by the fibroproliferative and fibrotic phases from the second week onward [4]. However, with the heterogeneity and different progression speeds of the disease, the time from the onset of the disease to progression to severity levels adequate to meet the ARDS Berlin definition criteria (e.g., P/F ratio < 300 mmHg and PEEP > 5 cmH2O) is variable and unpredictable. In a study of 159 autopsies of cases of ARDS with DAD, Thille et al. [26] reported that the prevalence of exudative change was 90% in 82 cases with an ARDS duration of less than 1 week. However, up to 54% (44/82) of the cases already exhibited fibroproliferative change, and 4% (3/82) had fibrosis. Regarding HRCT manifestations, the study series of Ichikado et al. [14,15,16] demonstrated an association between the presence of traction bronchiectasis or bronchiolectasis in areas of GGO or consolidation and the late fibroproliferative or fibrotic phases. Fibroproliferation with traction bronchiectasis was observed in 64% (28/44) of patients who received HRCT within 7 days of ARDS diagnosis [17] and in 47% (40/85) of patients who received HRCT on the day of ARDS diagnosis [18]. These results emphasize that a clinically early phase of ARDS does not correspond to a pathologically early phase. However, through the HRCT changes, we could clearly estimate the pathological stage the patient was in at the time of ARDS diagnosis. Lamy et al. [27] applied pathological findings to predict the prognosis of 45 OLB- or autopsy-confirmed ARDS cases and demonstrated that patients who exhibited histological acute exudative changes had a more favorable prognosis than patients in the fibroproliferative or fibrotic stages. Progression from the early exudative phase to the late fibroproliferative and fibrotic stages led to an impairment of lung mechanics and oxygen diffusion capacity, resulting in patients with ARDS being dependent on ventilators and susceptible to subsequent ventilator-associated pneumonia. Sepsis and multiple system organ failure during long-term ICU stays have been suggested to be the main causes of death in patients with ARDS [28,29], which may partly account for those with DAD having a poorer prognosis than those without DAD. In the Ichikado HRCT scoring system, the score for traction bronchiectasis is weighted by multiplying the percent area of GGO with traction bronchiectasis by 4 and multiplying the percent area of consolidation with traction bronchiectasis by 5. Ichikado et al. [15,18] concluded that the HRCT score for pulmonary fibroproliferation assessment was the only independent predictor of susceptibility to multiple organ failure and ARDS outcomes. However, they did not test the original unweighted total percentage of area with traction bronchiectasis or bronchiolectasis. In our study, the Ichikado score of HRCT performed within 7 days of ARDS diagnosis failed to predict the outcomes, and only the total percentage of the area with traction bronchiectasis or bronchiolectasis was independently associated with 60-day mortality in patients with pathologically confirmed DAD. Ichikado et al. enrolled all relevant patients with ARDS in their cohort, whereas we only focused on ARDS patients with DAD. This difference in the enrolled populations might have contributed to the difference in the predictive values between the Ichikado HRCT score and the unweighted total percentage of the area with traction bronchiectasis. Nonetheless, our results confirmed the findings of Lamy et al. [27] and Ichikado et al. [15] showing that progression into the fibroproliferative or fibrotic stages early at the time of ARDS diagnosis was an independent predictor of poor prognosis. In the present study, the ROC curve revealed that the values of the parameters of the severity of illness (SOFA score), the severity of ARDS (P/F ratio), and lung mechanics (dynamic MP) in the prediction of 60-day mortality related to DAD were not better than chance. Only the HRCT findings significantly predicted 60-day mortality. The total percentage of the area with traction bronchiectasis demonstrated a favorable predictive value. with the highest AUC of 0.784 (95% CI, 0.621–0.946; sensitivity, 70.6%; specificity, 82.4%) and a cutoff of 21.7. The mortality for the subgroup with a total percentage of the area with traction bronchiectasis of >21.7 was 74% (14/19), and that for the subgroup with a value of ≤21.7% was 20% (3/15). Roughly, in patients with DAD with a total area of fibroproliferation of >22% at the time of ARDS diagnosis, the mortality rate was approximately 3.7 times higher than that in patients with <22% fibroproliferation. The AUC for the HRCT score was 0.727 (95% CI, 0.551–0.902; sensitivity, 88.2%; specificity, 58.5%), and the cutoff was 263.3. This was higher than the cutoff of 210 in Ichikado’s study [18], which may imply that those with DAD have more severe fibroproliferation than those without DAD at the time of ARDS diagnosis. Notably, the AUC of the HRCT score for predicting 60-day survival in Ichikado’s whole ARDS cohort (0.71) was similar to the AUC of the HRCT score in our DAD cohort (0.72). Our results highlight the consistency of the Ichikado HRCT scoring system in predicting ARDS survival and underscore the superior predictive value of the total percentage of the area with traction bronchiectasis or bronchiolectasis. Amato et al. proposed that driving pressure was the factor most associated with mortality in ARDS and that decreasing the driving pressure through the adjustment of ventilatory settings was strongly associated with increased survival [30]. The driving pressure of the respiratory system is defined as the ratio of the tidal volume to respiratory system compliance or the difference between the plateau pressure and PEEP. A meta-analysis [31] comprising 3252 patients also confirmed the association between high driving pressure and high mortality (OR, 1.44; 95% CI, 0.11–1.18). Thille et al. [25], in their study of 159 autopsies of cases of ARDS with DAD, also demonstrated that increased dynamic driving pressure was independently associated with DAD. In addition to driving pressure, MP incorporates the tidal volume, pressure, flow, and respiratory rate to calculate the amount of energy delivered to the respiratory system by the ventilator per unit of time. MP is superior to other ventilator parameters in estimating the risk of ventilator-associated lung injury [32] and can enable risk estimation using factors other than driving pressure alone. MP has been shown to predict mortality in critically ill [33] and ARDS patients [34,35]. A study that applied dynamic variables and a registry-based prospective cohort containing 13,939 patients, including those with ARDS, also revealed that increases in the dynamic driving pressure and dynamic MP were associated with an increased risk of ICU mortality [21]. On the contrary, the dynamic driving pressure was correlated with neither DAD nor mortality in the PREDATOR study [9] and was also not associated with mortality related to ARDS with DAD in our cohort (Table 3). In our study, although MP was significant in the univariate regression analysis, the multivariate logistic regression analysis failed to confirm that dynamic MP was an independent predictor of 60-day mortality related to DAD (Table 3). Our study has some limitations. First, the results may have been influenced by selection bias. OLB was performed only for ARDS patients presenting bilateral GGO or consolidation with rapid progression and who did not exhibit clear etiology of ARDS. Therefore, AIP cases accounted for a large proportion of our cohort. However, Parambil et al. [36] reported that infections and AIP were the most common causes of DAD diagnosed using OLB. Therefore, our results might still be applicable to DAD with other underlying etiologies. Second, this study is retrospective in nature and has a relatively small sample size because only a small proportion of ARDS patients were selected for OLB. Furthermore, the patients were required to have received HRCT within 7 days of ARDS diagnosis to assess the severity of fibroproliferation. Approximately 40% (27/68) of the pathologically confirmed DAD cases in our cohort were excluded because of the lack of HRCT within 7 days of ARDS diagnosis (Figure 1). The results might have been more conclusive if these 27 cases were enrolled. 5. Conclusions As an alternative to the HRCT score, the extent of fibroproliferation on HRCT performed within 7 days of ARDS diagnosis, denoted as the total percentage of the area with traction bronchiectasis or bronchiolectasis, was an independent predictor and had a favorable predictive value for the 60-day mortality of patients with pathologically confirmed ARDS with DAD. A total fibroproliferation percentage greater than the cutoff of 22% signified poor prognosis and a 3.7 times higher 60-day mortality. Physiological variables could not adequately discriminate between survival and nonsurvival cases. Acknowledgments The authors would like to express their appreciation for the patients and staff in the ICUs at Chang Gung Memorial Hospital. Author Contributions Conceptualization, Y.-C.W. and C.-C.H.; data curation, C.-Y.H., P.W.W. and K.-C.K.; writing—original draft, C.-Y.H. and P.W.W.; writing—review and editing, K.-C.K. and C.-C.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The Institution Review Board of CGMH approved this study in accordance with the Declaration of Helsinki (IRB Number: 202200184B0). Informed Consent Statement The IRB waived the need for written informed consent because this study was retrospective and had no bearing on modifications to patient management. All personal information in the database was encrypted and deidentified. Data Availability Statement The data sets analyzed in the study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow chart for patient enrollment. DAD: diffuse alveolar damage; UIP: usual interstitial pneumonia. Figure 2 (A,B) Chest radiography and HRCT scan at the level below carina of a 35-year-old male patient with psoriasis with ARDS caused by methotrexate-induced pneumonitis who survived and was discharged. (C,D) Chest radiography and HRCT scan at the level below the carina of a 75-year-old female with left parotid gland lymphoepithelial carcinoma with liver and bone metastasis and ARDS caused by pneumonia who expired in ICU. Both chest X-rays (A,C) show bilateral dense consolidation, more severe in (A) the survival case. (B) HRCT findings of the survival case show extensive GGO and consolidation with a smooth bronchial wall. (D) HRCT findings in the non-survival case show bilateral GGO, reticulation, and prominent traction bronchiectasis (red arrows). Figure 3 Receiver operator characteristic (ROC) curve of the HRCT score, traction bronchiectasis, SOFA score, PaO2/FiO2 ratio, and MP. jcm-11-02458-t001_Table 1 Table 1 Clinical Characteristics of ARDS Patients with DAD. Charteristics Total (n = 34) Survivors (n = 17) Non-Survivors (n = 17) p Value Age (years) 58.9 ± 16 56.5 ± 13.8 61.4 ± 18 0.255 Sex (male/female) 20/14 9/8 11/6 0.21 Cause of ARDS   AIP 17 7 10   Pneumonia 9 3 6   Sepsis induced ARDS 3 2 1   Methotrexate induced DAD 2 2   Autoimmune interstitial lung disease 1 1   Amphetamine induced ARDS 1 1   Cytomegalovirus pneumonitis 1 1 Severity of ARDS   mild 26.5% (9/34) 35.3% (6/17) 17.6% (3/17)   moderate 61.8% (2/34) 52.9% (9/17) 64.7% (11/17)   severe 14.7% (5/34) 11.8% (2/17) 17.6% (3/17) Days from ARDS to HRCT (days) 1.9 ± 1.8 1.9 ± 2.0 1.9 ± 1.6 0.206 Days from ARDS to lung biopsy (days) 8.5 ± 8.7 9.0 ± 11.6 7.1 ± 4.5 0.308 Days from HRCT to lung biopsy (days) 7.2 ± 8.9 9.9± 11.4 5.4 ± 4.8 0.467 Duration of mechanical duration (days) 29.9 ± 34.1 35 ± 46.8 24.8 ± 12.3 0.563 SOFA score 5.2 ± 2.2 4.9 ± 1.9 5.6 ± 2.4 0.443 HRCT score 257.3 ± 49.3 241.9 ± 47.2 272.7 ± 51.9 * 0.024 PaO2/FiO2 154.8 ± 61.1 169.1 ± 69.5 140.5 ± 49.2 0.361 Ventilator variables   Tidal Volume (mL/kg predicted) 7.7 ± 2.3 7.4 ± 2.2 8.0 ± 2.4 0.836   PEEP (cmH2O) 11.9 ± 2.6 11.8 ± 2.6 12.1 ± 2.6 0.644   Dynamic driving pressure (cmH2O) 19.6 ± 5.0 20.7 ± 5.1 18.5 ± 4.8 0.161   Mechanical Power (J/min) 22.7 ± 5.1 22.1 ± 5.2 23.4 ± 5.1 0.391 Abbreviation: AIP: acute interstitial pneumonia; DAD: diffuse alveolar damage; SOFA: sequential organ failure assessment; PEEP positive end-expiratory pressure. * p value < 0.05 between survival and nonsurvival. jcm-11-02458-t002_Table 2 Table 2 HRCT score and HRCT findings of survivors and non-survivors. All Patients (n = 34) Survivals (n = 17) Non-Survivals (n = 17) p Value HRCT score 257.3 ± 49.3 241.9 ± 47.2 272.7 ± 49.4 * 0.024 Percentage of area without traction bronchiectasis 73.2 ± 18.2 80.4 ± 17.3 66.1 ± 16.6 * 0.005 Percentage of area with traction bronchiectasis 26.8 ± 18.2 19.6 ± 17.3 34.0 ± 16.6 * 0.005 Normal Attenuation 22.5 ± 18.2 20.7 ± 18.3 24.2 ± 18.5 0.523 Ground-Glass opacity 36.1 ± 20.7 43.1 ± 20.6 29.1 ± 18.9 0.108 Consolidation 14.7 ± 15.6 16.6 ± 19.6 12.7 ± 10.5 0.809 Ground-Glass opacity with traction bronchiectasis or bronchiolectasis 16.1 ± 12.9 12.8 ± 12.2 19.4 ± 13.1 0.097 Consolidation with traction bronchiectasis or bronchiolectasis 10 ± 9.6 6.8 ± 7.3 13.2 ± 10.8 0.054 Honeycombing 0.7 ± 2.9 0 ± 0 1.4 ± 4.1 0.074 * p value < 0.05 between survival and nonsurvival. jcm-11-02458-t003_Table 3 Table 3 Univariate and multivariate logistic regression for analyzing independent risk factors for 60-day mortality. Variables Univariate OR (95% CI) p Value Multivariate OR (95% CI) p Value SOFA 0.901 (0.506–1.602) 0.722 PaO2/FiO2 ratio 1.018 (0.999–1.037) 0.069 0.984 (0.969–1.000) 0.054 Driving pressure 1.275 (0.96–1.694) 0.093 Mechanical Power 0.755 (0.58–0.982) 0.036 1.162 (0.971–1.391) 0.102 HRCT score 1.038 (0.985–1.093) 0.162 % of total area with traction bronchiectasis or bronchiolectasis 0.852 (0.734–0.989) 0.035 1.082 (1.021–1.148) 0.008 Abbreviations: OR: odds ratio; CI: confidence interval. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Bellani G. Laffey J.G. Pham T. Fan E. Brochard L. Esteban A. Gattinoni L. Van Haren F. Larsson A. McAuley D.F. Epidemiology, Patterns of Care, and Mortality for Patients with Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries JAMA 2016 315 788 800 10.1001/jama.2016.0291 26903337 2. Phua J. Badia J.R. Adhikari N.K. Friedrich J.O. Fowler R.A. Singh J.M. Scales D.C. Stather D.R. Li A. Jones A. Has mortality from acute respiratory distress syndrome decreased over time? A systematic review Am. J. Respir. Crit. Care Med. 2009 179 220 227 10.1164/rccm.200805-722OC 19011152 3. Ranieri V.M. Rubenfeld G.D. Thompson B.T. Ferguson N.D. Caldwell E. Fan E. Camporota L. Slutsky A.S. ARDS Definition Task Force Acute respiratory distress syndrome: The Berlin definition JAMA 2012 307 2526 2533 22797452 4. Tomashefski J.F. Jr. Pulmonary pathology of acute respiratory distress syndrome Clin. Chest Med. 2000 21 435 466 10.1016/S0272-5231(05)70158-1 11019719 5. Lorente J.A. Cardinal-Fernandez P. Munoz D. Frutos-Vivar F. Thille A.W. Jaramillo C. Ballen-Barragan A. Rodriguez J.M. Penuelas O. Ortiz G. Acute respiratory distress syndrome in patients with and without diffuse alveolar damage: An autopsy study Intensive Care Med. 2015 41 1921 1930 10.1007/s00134-015-4046-0 26385863 6. Cardinal-Fernandez P. Bajwa E.K. Dominguez-Calvo A. Menendez J.M. Papazian L. Thompson B.T. The Presence of Diffuse Alveolar Damage on Open Lung Biopsy Is Associated with Mortality in Patients with Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis Chest 2016 149 1155 1164 10.1016/j.chest.2016.02.635 26896701 7. Kao K.C. Hu H.C. Chang C.H. Hung C.Y. Chiu L.C. Li S.H. Lin S.W. Chuang L.P. Wang C.W. Li L.F. Diffuse alveolar damage associated mortality in selected acute respiratory distress syndrome patients with open lung biopsy Crit. Care 2015 19 228 10.1186/s13054-015-0949-y 25981598 8. Guerin C. Bayle F. Leray V. Debord S. Stoian A. Yonis H. Roudaut J.B. Bourdin G. Devouassoux-Shisheboran M. Bucher E. Open lung biopsy in nonresolving ARDS frequently identifies diffuse alveolar damage regardless of the severity stage and may have implications for patient management Intensive Care Med. 2015 41 222 230 10.1007/s00134-014-3583-2 25476984 9. Cardinal-Fernandez P. Ortiz G. Chang C.H. Kao K.C. Bertreau E. Philipponnet C. Casero-Alonso V.M. Souweine B. Charbonney E. Guérin C. Predicting the Impact of Diffuse Alveolar Damage through Open Lung Biopsy in Acute Respiratory Distress Syndrome—The PREDATOR Study J. Clin. Med. 2019 8 829 844 10.3390/jcm8060829 10. Kamo T. Tasaka S. Suzuki T. Asakura T. Suzuki S. Yagi K. Namkoong H. Ishii M. Morisaki H. Betsuyaku T. Prognostic values of the Berlin definition criteria, blood lactate level, and fibroproliferative changes on high-resolution computed tomography in ARDS patients BMC Pulm. Med. 2019 19 37 10.1186/s12890-019-0803-0 30744598 11. Imai R. Nishimura N. Takahashi O. Tamura T. High-resolution computed tomography for the prediction of mortality in acute respiratory distress syndrome: A retrospective cohort study Health Sci. Rep. 2021 4 e418 10.1002/hsr2.418 34646945 12. Tomiyama N. Müller N.L. Johkoh T. Cleverley J.R. Ellis S.J. Akira M. Ichikado K. Honda O. Mihara N. Kozuka T. Acute respiratory distress syndrome and acute interstitial pneumonia: Comparison of thin-section CT findings J. Comput. Assist. Tomogr. 2001 25 28 33 10.1097/00004728-200101000-00005 11176289 13. Joynt G.M. Antonio G.E. Lam P. Wong K.T. Li T. Gomersall C.D. Ahuja A.T. Late stage adult respiratory distress syndrome caused by severe acute respiratory syndrome: Abnormal findings at thin-section CT Radiology 2004 230 339 346 10.1148/radiol.2303030894 14752179 14. Ichikado K. Johkoh T. Ikezoe J. Takeuchi N. Kohno N. Arisawa J. Nakamura H. Nagareda T. Itoh H. Ando M. Acute interstitial pneumonia: High-resolution CT findings correlated with pathology Am. J. Roentgenol. 1997 168 333 338 10.2214/ajr.168.2.9016201 9016201 15. Ichikado K. Suga M. Gushima Y. Johkoh T. Iyonaga K. Yokoyama T. Honda O. Shigeto Y. Tomiguchi S. Takahashi M. Hyperoxia-induced diffuse alveolar damage in pigs: Correlation between thin-section CT and histopathologic findings Radiology 2000 216 531 538 10.1148/radiology.216.2.r00jl05531 10924582 16. Ichikado K. Suga M. Müller N.L. Taniguchi H. Kondoh Y. Akira M. Johkoh T. Mihara N. Nakamura H. Takahashi M. Acute interstitial pneumonia: Comparison of high-resolution computed tomography findings between survivors and non-survivors Am. J. Respir. Crit. Care Med. 2002 165 1551 1556 10.1164/rccm.2106157 12045132 17. Ichikado K. Suga M. Muranaka H. Prediction of prognosis for acute respiratory distress syndrome with thin-section CT: Validation in 44 cases Radiology 2006 238 321 329 10.1148/radiol.2373041515 16293804 18. Ichikado K. Muranaka H. Gushima Y. Kotani T. Nader H.M. Fujimoto K. Johkoh T. Iwamoto N. Kawamura K. Nagano J. Fibroproliferative changes on high resolution CT in the acute respiratory distress syndrome predict mortality and ventilator dependency: A prospective observational cohort study BMJ Open 2012 2 e000545 10.1136/bmjopen-2011-000545 19. Austin J.H.M. Muller N.L. Friedman P.J. Hansell D.M. Naidich D.P. Remy-Jardin M. Webb W.R. Zerhouni E. Glossary of Terms for CT of the Lungs: Recommendations of the Nomenclature Committee of the Fleischner Society Radiology 1996 200 327 331 10.1148/radiology.200.2.8685321 8685321 20. Fujimoto K. Taniguchi H. Johkoh T. Kondoh Y. Ichikado K. Sumikawa H. Ogura T. Kataoka K. Endo T. Kawaguchi A. Acute exacerbation of idiopathic pulmonary fibrosis: High-resolution CT scores predict mortality Eur. Radiol. 2012 22 83 92 10.1007/s00330-011-2211-6 21822949 21. Urner M. Juni P. Hansen B. Wettstein M.S. Ferguson N.D. Fan E. Time-varying intensity of mechanical ventilation and mortality in patients with acute respiratory failure: A registry-based, prospective cohort study Lancet Respir. Med. 2020 8 905 913 10.1016/S2213-2600(20)30325-8 32735841 22. Ray P. Le Manach Y. Riou B. Houle T.T. Statistical evaluation of a biomarker Anesthesiology 2010 112 1023 1040 10.1097/ALN.0b013e3181d47604 20234303 23. Thille A.W. Esteban A. Fernández-Segoviano P. Rodriguez J.M. Aramburu J.A. Peñuelas O. Cortés-Puch I. Cardinal-Fernández P. Lorente J.A. Frutos-Vivar F. Comparison of the Berlin definition for acute respiratory distress syndrome with autopsy Am. J. Respir. Crit. Care Med. 2013 187 761 767 10.1164/rccm.201211-1981OC 23370917 24. Thompson B.T. Matthay M.A. The Berlin definition of ARDS versus pathological evidence of diffuse alveolar damage Am. J. Respir. Crit. Care Med. 2013 187 675 677 10.1164/rccm.201302-0385ED 23540876 25. Thille A.W. Penuelas O. Lorente J.A. Fernandez-Segoviano P. Rodriguez J.M. Aramburu J.A. Panizo J. Esteban A. Frutos-Vivar F. Predictors of diffuse alveolar damage in patients with acute respiratory distress syndrome: A retrospective analysis of clinical autopsies Crit. Care 2017 21 254 10.1186/s13054-017-1852-5 29052522 26. Thille A.W. Esteban A. Fernández-Segoviano P. Rodriguez J.M. Aramburu J.A. Vargas-Errázuriz P. Martín-Pellicer A. Lorente J.A. Frutos-Vivar F. Chronology of histological lesions in acute respiratory distress syndrome with diffuse alveolar damage: A prospective cohort study of clinical autopsies Lancet Respir. Med. 2013 1 395 401 10.1016/S2213-2600(13)70053-5 24429204 27. Lamy M. Fallat R.J. Koeniger E. Dietrich H.P. Ratliff J.L. Eberhart R.C. Tucker H.J. Hill J.D. Pathologic features and mechanisms of hypoxemia in adult respiratory distress syndrome Am. Rev. Respir. Dis. 1976 114 267 287 788563 28. Montgomery A.B. Stager M.A. Carrico C.J. Hudson L.D. Causes of mortality in patients with the adult respiratory distress syndrome Am. Rev. Respir. Dis. 1985 132 485 489 10.1097/00132586-198608000-00056 4037521 29. Stapleton R.D. Wang B.M. Hudson L.D. Rubenfeld G.D. Caldwell E.S. Steinberg K.P. Causes and timing of death in patients with ARDS Chest 2005 128 525 532 10.1378/chest.128.2.525 16100134 30. Amato M.B. Meade M.O. Slutsky A.S. Brochard L. Costa E.L. Schoenfeld D.A. Stewart T.E. Briel M. Talmor D. Mercat A. Driving pressure and survival in the acute respiratory distress syndrome N. Engl. J. Med. 2015 372 747 755 10.1056/NEJMsa1410639 25693014 31. Aoyama H. Pettenuzzo T. Aoyama K. Pinto R. Englesakes M. Fan E. Association of Driving Pressure with Mortality Among Ventilated Patients With Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis Crit. Care Med. 2018 46 300 306 10.1097/CCM.0000000000002838 29135500 32. Gattinoni L. Tonetti T. Cressoni M. Cadringher P. Herrmann P. Moerer O. Protti A. Gotti M. Chiurazzi C. Carlesso E. Ventilator-related causes of lung injury: The mechanical power Intensive Care Med. 2016 42 1567 1575 10.1007/s00134-016-4505-2 27620287 33. Serpa Neto A. Deliberato R.O. Johnson A.E.W. Bos L.D. Amorim P. Pereira S.M. Cazati D.C. Cordioli R.L. Correa T.D. Pollard T.J. Mechanical power of ventilation is associated with mortality in critically ill patients: An analysis of patients in two observational cohorts Intensive Care Med. 2018 44 1914 1922 10.1007/s00134-018-5375-6 30291378 34. Zhang Z. Zheng B. Liu N. Ge H. Hong Y. Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome Intensive Care Med. 2019 45 856 864 10.1007/s00134-019-05627-9 31062050 35. Parhar K.K.S. Zjadewicz K. Soo A. Sutton A. Zjadewicz M. Doig L. Lam C. Ferland A. Niven D.J. Fiest K. Epidemiology, mechanical power, and 3-year outcomes in ARDS patients using standardized screening: An observational cohort study Ann. Am. Thorac. Soc. 2019 16 1263 1272 10.1513/AnnalsATS.201812-910OC 31247145 36. Parambil J.G. Myers J.L. Aubry M.C. Ryu J.H. Causes and Prognosis of Diffuse Alveolar Damage Diagnosed on Surgical Lung Biopsy Chest 2007 132 50 57 10.1378/chest.07-0104 17475632

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091908 nutrients-14-01908 Article Relationship between Serum 25-Hydroxyvitamin D Level and Risk of Recurrent Stroke https://orcid.org/0000-0002-1184-1791 Li Guowei 12* Li Likang 1 https://orcid.org/0000-0001-9142-2767 Adachi Jonathan D. 3 Wang Ruoting 1 Ye Zebing 4 Liu Xintong 5 Thabane Lehana 26 https://orcid.org/0000-0002-7566-1626 Lip Gregory Y. H. 78 Gropper Sareen Academic Editor 1 Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou 510317, China; lilikangccem@hotmail.com (L.L.); wangruoting1996@163.com (R.W.) 2 Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON L8S 4L8, Canada; thabanl@mcmaster.ca 3 Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada; jd.adachi@sympatico.ca 4 Department of Cardiology, Guangdong Second Provincial General Hospital, Guangzhou 510317, China; tgccem@hotmail.com 5 Department of Neurology, Guangdong Second Provincial General Hospital, Guangzhou 510317, China; jzhzang@163.com 6 Centre for Evaluation of Medicines, St. Joseph’s Healthcare, Hamilton, ON L8N 4A6, Canada 7 Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool L69 3BX, UK; gregory.lip@liverpool.ac.uk 8 Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, 9000 Aalborg, Denmark * Correspondence: lig28@mcmaster.ca; Tel.: 86-020-3264-0264; Fax: 86-020-8916-9025 02 5 2022 5 2022 14 9 190815 4 2022 30 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Evidence for the association between vitamin D and risk of recurrent stroke remains sparse and limited. We aimed to assess the relationship between serum circulating 25-hydroxyvitamin D (25(OH)D) level and risk of recurrent stroke in patients with a stroke history, and to identify the optimal 25(OH)D level in relation to lowest recurrent stroke risk. Data from the nationwide prospective United Kingdom Biobank were used for analyses. Primary outcome was time to first stroke recurrence requiring a hospital visit during follow-up. We used Cox proportional hazards regression model with restricted cubic splines to explore 25(OH)D level in relation to recurrent stroke. The dose-response relationship between 25(OH)D and recurrent stroke risk was also estimated, taking the level of 10 nmol/L as reference. A total of 6824 participants (mean age: 60.6 years, 40.8% females) with a baseline stroke were included for analyses. There were 388 (5.7%) recurrent stroke events documented during a mean follow-up of 7.6 years. Using Cox proportional hazards regression model with restricted cubic splines, a quasi J-shaped relationship between 25(OH)D and risk of recurrent stroke was found, where the lowest recurrent stroke risk lay at the 25(OH)D level of approximate 60 nmol/L. When compared with 10 nmol/L, a 25(OH)D level of 60 nmol/L was related with a 48% reduction in the recurrent stroke risk (hazard ratio = 0.52, 95% confidence interval: 0.33–0.83). Based on data from a large-scale prospective cohort, we found a quasi J-shaped relationship between 25(OH)D and risk of recurrent stroke in patients with a stroke history. Given a lack of exploring the cause–effect relationship in this observational study, more high-quality evidence is needed to further clarify the vitamin D status in relation to recurrent stroke risk. vitamin D recurrent stroke 25-hydroxyvitamin stroke prevention Science Foundation of Guangdong Second Provincial General Hospitalgrant number: YY2018-002, recipient: GL Medical Scientific Research Foundation of Guangdong Province of Chinagrant number: A2020453, recipient: GL This work was supported by the Science Foundation of Guangdong Second Provincial General Hospital (grant number: YY2018-002, recipient: GL) and the Medical Scientific Research Foundation of Guangdong Province of China (grant number: A2020453, recipient: GL). ==== Body pmc1. Introduction Stroke is a serious public health concern, especially with the aging population, ranking as the second leading cause of death worldwide [1]. A previous stroke is substantially related with increased risk of subsequent stroke, with a recurrent rate ranging from 5% to 40% within five years [2,3,4]. Hence, there has been a move towards a more holistic and integrated care approach to stroke management, including attention to lifestyle and comorbidities [5]. Recently, vitamin D has been widely found to associate with risk of stroke, based on data from observational studies. Several meta-analyses consistently reported that low level of circulating 25-hydroxyvitamin D (25(OH)D) was significantly related with the onset of stroke [6,7,8,9]. Nevertheless, evidence for the association between vitamin D and risk of recurrent stroke remains sparse and limited. Some studies reported that among patients with a previous stroke, those with the first quartile of 25(OD)D level had a significantly highest risk of recurrent stroke [10,11]. However, their small sample sizes and short-term follow-up precluded further investigation of adequate vitamin D levels in relation to stroke recurrence. Furthermore, the optimal level of 25(OH)D associated with the lowest risk of recurrent stroke remains largely unknown, especially given the non-linear relationship between 25(OH)D level and stroke risk. Therefore, in this study, we aimed to assess the association between serum 25(OH)D level and risk of recurrent stroke in patients with a prior stroke history, and second, to identify the optimal 25(OH)D level in relation to lowest recurrent stroke risk. Data from the nationwide prospective United Kingdom (UK) Biobank were used for analyses. 2. Methods 2.1. Participants and Setting Descriptions about the UK Biobank have been published in the literature and on the website (www.ukbiobank.ac.uk, accessed on 10 December 2021) [12]. In brief, the UK Biobank is a nationwide prospective cohort study that recruited >500,000 community dwellers between year 2006 and 2010, with the goals of improving diagnosis, prevention, treatment, and prognosis of diseases for the middle-aged and older adults. The study collected data from participant self-reports, interview with trained staff and physical measures, and used multiple data sources for linkage. The UK Biobank was approved by the Northwest Multicenter Research Ethics committee (11/NW/0382). The Guangdong Second General Provincial Hospital Research Ethics Committee approved the current analysis (2022-KY-KZ-119-01). All participants provided written informed consent. For our current study, we limited eligible participants to those with a history of stroke at baseline. Information on history of stroke was identified from patient self-reports, the ICD-10 and ICD-9 code at baseline. The patient selection process is displayed in Supplemental Figure S1 for this study. 2.2. Outcome Measures Our primary outcome was time to first stroke recurrence requiring a hospital visit during follow-up. The ICD-10 codes were used to determine the recurrent stroke events and their corresponding survival time (Supplemental Table S1 shows the codes used for stroke identification). Secondary outcomes included ischemic and hemorrhagic stroke. Patients were followed up to stroke recurrence, 31 March 2017, or death, whichever came first. 2.3. Serum 25(OH)D Levels and Other Independent Variables Serum 25(OH)D level (in nmol/L) was measured from the non-fasted blood sample drawn at the time of study enrollment, using the Liaison XL 25(OH)D assay. Data on other independent variables at baseline included age, sex, smoking and drinking, ethnicity, education, body mass index (BMI), physical activity, atrial fibrillation, hypertension, heart failure, hypercholesterolemia, and diabetes. We also collected information on intake of statins, non-steroidal anti-inflammatory drugs (NSAIDs), anticoagulants, antihypertensive and antidiabetic medications, and mineral and vitamin supplementation. To enhance the under-recognition of data on comorbidities and medication intake at baseline, we used the information from patient’s self-reports, interviews with trained staff regarding medications and treatment that patients received, and ICD codes. We documented the existence of a variable if the patient had a positive response to any of the aforementioned data fields. 3. Statistical Analysis Continuous and categorical variables were depicted with mean (standard deviation, SD) and frequency (percentage), respectively. Comparisons of baseline information between patients with and without recurrent stroke were performed by t-test for continuous variables and chi-square test for categorical variables. We used the Kaplan–Meier method to graph failure curve for recurrent stroke. Kernel density estimation was used to estimate the probability density of participants’ serum 25(OH)D level. To illustrate the relationship between 25(OH)D level and risk of recurrent stroke, we conducted a Cox proportional hazards regression model that was adjusted for the baseline characteristics as listed in Table 1 including age, sex, BMI, smoking and drinking, physical activity, comorbidities, medications, and supplementation. Results were presented with hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). To explore the optimal of 25(OH)D level, we employed the restricted cubic splines with knots at 5th, 35th, 65th, and 95th percentiles to smooth the non-linear association between 25(OH)D level and recurrent stroke risk. We also showed the dose-response relationship between 25(OH)D level and recurrent stroke risk to estimate the HRs for pre-determined levels at 20, 30, 40, 50, 60, 70, and 80 nmol/L, taking the 25(OH)D of 10 nmol/L as reference. Similar analyses were also conducted for secondary outcomes of ischemic and hemorrhagic stroke. We performed two post hoc sensitivity analyses to assess the robustness of the main findings. A competing risk analysis using the Fine and Gray model was conducted for the relationship between 25(OH)D levels and risk of recurrent stroke, by treating all-cause death as competing events for recurrent stroke. Recognizing that the 25(OH)D levels may have oscillation by months and the length between the onset of stroke and blood sampling date may be different, we performed another sensitivity analysis in the multivariable Cox model after further adjusted for these two variables (the month for 25(OH)D measures, and the length between the stroke onset and blood sampling date). Two pre-defined subgroups were conducted by sex (males and females) and age (<65 and ≥65 years) to explore whether there existed potential effect modifications. Furthermore, to directly compare with results from previous studies, we estimated the associations between different quartiles of 25(OH)D level and recurrent stroke risk, with the first quartile as reference value. Likewise, we assessed different 25(OH)D levels in relation to recurrent stroke risk using the recognized cut-off points for vitamin D sufficiency (>50 nmol/L), insufficiency (25–50), and deficiency (<25), taking vitamin D deficiency as reference. All tests were two-sided, and the significance level was set as 0.05. Stata version 17 (StataCorp, College Station, TX, USA) and R version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria) were used for analyses. 4. Results There were 6824 participants (mean age: 60.6 years, 40.8% females) with a baseline stroke included in this analysis. There were approximately 40% and 7% of participants who never smoked and consumed alcohol, respectively. The majority of participants was physically active (73%) and with hypertension (62%). Other information on comorbidities, medication, and supplementation intake was also presented in Table 1. The mean 25(OH)D level was 46.5 nmol/L. During a mean follow-up of 7.6 (SD = 1.8) years, there were 388 (5.7%) recurrent stroke events documented including 250 ischemic, 87 hemorrhagic, and 51 unspecified stroke (Supplemental Figure S2 displays the Kaplan–Meier failure curve for recurrent stroke). Table 1 displays comparisons of baseline characteristics between participants with and without recurrent stroke. Participants with recurrent stroke were older, and less likely to be females and physically active when compared with controls (all p-values < 0.05). Significantly higher percentages of hypertension and diabetes were found in patients with recurrent stroke. Participants in the recurrent stroke group were more likely to consume statins, anticoagulants, antihypertensive, and antidiabetic medications. Supplemental Figure S3 shows the probability density function of serum 25(OH)D level stratified by participants with and without recurrent stroke. A lower 25(OH)D level was found in patients with recurrent stroke (45.6 vs. 46.5); however, the difference was not statistically significant (p-value = 0.48; Table 1). A quasi J-shaped relationship between 25(OH)D and risk of recurrent stroke was found in this study (Figure 1), where the lowest recurrent stroke risk lay at the 25(OH)D level of 58.2 nmol/L. As Table 2 presents, when taking the 25(OH)D of 10 nmol/L as reference, a 25(OH)D level of 60 nmol/L was related with a 48% reduction in the recurrent stroke risk (HR = 0.52, 95% CI: 0.33–0.83). A total of 658 (9.6%) deaths occurred before recurrent stroke; therefore, these deaths were the competing events for stroke recurrence. The competing risk analysis by treating deaths as competing events yielded similar findings to the main results, with the potential lowest recurrent stroke risk at the 25(OH)D level of approximate 60 nmol/L (subhazards ratio = 0.66, 95% CI: 0.40–1.12; Supplemental Table S2). Another sensitivity analysis by further adjusted for the month for 25(OH)D measures, the length between the onset of stroke and blood sampling date, and these two variables, showed similar results to the main findings, with the smallest HR of 0.51, 0.51, and 0.50 correspondingly at the 25(OH)D level of 60 nmol/L (Supplemental Table S2). Analyses for secondary outcomes and by subgroup yielded in general similar results to the main findings, with the lowest smallest recurrent stroke risk at 25(OH)D of about 60 nmol/L (HRs ranging from 0.43 to 0.70); however, the potentially lowest risks of hemorrhagic stroke (HR = 0.38) and for females (HR = 0.29) were observed at approximately 40 nmol/L (Table 2; Supplemental Figures S4–S9). Table 3 shows results from additional analyses for the relationship between 25 (OH)D and recurrent stroke risk. When compared with the first quartile, the third quartile of 25(OH)D level (ranging from 43.5 to 61.3 nmol/L) was found to significantly associate with a 32% reduction in recurrent stroke risk (HR = 0.68, 95% CI: 0.48–0.96). Participants with insufficient (HR = 0.60) or sufficient 25(OH)D levels (HR = 0.59) had a significantly and similarly reduced risk of recurrent stroke, when taking 25(OH)D deficiency as reference. 5. Discussion In this nationwide prospective cohort study, we explored what was the optimal vitamin D level in relation to risk of recurrent stroke in patients with a prior stroke history. There was a quasi J-shaped relationship between 25(OH)D and risk of recurrent stroke observed, with the lowest risk found at 25(OH)D level of approximate 60 nmol/L. When compared with 10 nmol/L, a 25(OH)D level of 60 nmol/L was significantly associated with a 48% reduction in recurrent stroke risk. The majority of literature had consistently found that low 25(OH)D levels were linearly or non-linearly associated with risk of first-ever stroke, although the relationship remained controversial. In this study, we found the optimal 25(OH)D level lay at approximate 60 nmol/L regarding the risk of recurrent stroke, which was in line with the quasi J-shaped association found from a recent meta-analysis that reported the 25(OH)D level of 50 nmol/L was related with the lowest stroke risk [8]. Even though with a different inflection, our study again confirmed that either a low or high level of 25(OH)D was related with elevated risk of recurrent stroke. Our different optimal 25(OH)D value from the published meta-analysis may be due to different population (with stroke history versus free from stroke) and outcome (stroke recurrence versus onset of stroke), data sources (individual patient data versus published summary data) and study settings (single country versus multi-country). Nevertheless, our results may provide some evidence about the vitamin D status in relation to risk of recurrent stroke. The role of 25(OH)D level in stroke recurrence was largely remained uninvestigated. Vitamin D status may be associated with stroke size and disease severity, which could subsequently impact the propensity towards stroke recurrence [13,14]. Unfortunately, there were no data on NIHSS (National Institutes of Health Stroke Scale) to evaluate the stroke severity and size between patients with and without recurrent stroke. However, our additional analyses showed similar results to previous studies that further adjusted for NIHSS (Table 3) [10,11]. Vitamin D deficiency had been linked with cardiovascular risk including hypertension, diabetes mellitus, and arterial stiffness, thereby contributing to enhanced stroke risk [15,16,17]. Moreover, vitamin D may own neuroprotective effects, while vitamin D deficiency could promote inflammation and vascular remodelling to increase the risk of stroke [18]. Indeed, in this study, when compared with low level of 25(OH)D or vitamin D deficiency, a decreased risk of recurrent stroke was consistently found. Moreover, high dosages of vitamin D administration in animal experiments could result in widespread arterial calcification, especially when with co-existing diabetes, atherosclerosis, and kidney disease [19]. This also in part supported the elevated risk of recurrent stroke with high 25(OH)D levels (Figure 1). Nevertheless, given the non-randomization design, whether the observed 25(OH)D level was a surrogate for healthy lifestyle and/or frailty status, and whether there was residual biases and confounding effect existed in this study, remained uncertain. Therefore, our findings regarding the relationship between 25(OH)D level and recurrent stroke risk should be interpreted with caution, requiring further high-quality evidence and ideally from randomized controlled trials for clarification and verification. There have been four studies evaluating the association between 25(OH)D level and risk of recurrent stroke in the literature, three from China [10,11,20] and one from the US [21]. All these studies categorized 25(OH)D level as either four quartiles [10,11] or binary for analyses [20,21]. These studies failed to comprehensively assess vitamin D status in relation to recurrent stroke. Importantly, they did not consider the potential association between high 25(OH)D levels and increased recurrent stroke risk, which would mislead the audience about the incremental beneficial effect of high vitamin D status. Their various cut-off points for 25(OH)D categorization used for analyses could also make their findings difficult to interpret, as it may not be appropriate to use quartiles or dichotomization for primary analyses regarding the J-shaped relationship given the substantial heterogeneity in the defined subgroups. For instance, Huang et al. used the fourth quartile (>22.8 ng/mL, i.e., >57 nmol/L) as a reference group [11], while our results demonstrated a slight decrease followed by continuous increase in recurrent stroke risk with elevated 25(OH)D levels in the group of >57 nmol/L (Figure 1). Moreover, their small sample sizes (ranging from 220 to 946) prohibited further attempts at exploring stroke subtypes and subgroup effects. By contrast, our study used data from a large-scale prospective cohort with a follow-up of approximate eight years for analyses. The relationship between 25(OH)D and recurrent stroke risk was depicted by graphs from restricted cubic splines in combination with estimates of multiple individual 25(OH)D points, generating a detailed non-linear association between 25(OH)D in relation to recurrent stroke. Furthermore, we performed analyses for stroke subtypes and stratified by age and sex to test the potential effect modifications. Of note, the relationship for hemorrhagic stroke and females seemed to demonstrate a different pattern from the main analysis (Supplemental Figures S5 and S7). Part of the interpretation may be due to the relatively small sample size of recurrent stroke events in females and for hemorrhagic stroke (Table 2). Nonetheless, these exploratory results for different subgroups required further adequately powered and well-designed studies for further investigation and clarification. 6. Strength and Limitations This study used data from a nationwide cohort to comprehensively assess serum 25(OH)D level in relation to recurrent stroke, with results shown as illustrations and estimates from specific 25(OH)D values. Rigorous methodology and robust analyses also supported the study findings. The high risk of stroke recurrence and its substantial impact on mortality remained a severe public health concern [22,23]. While there was an evidence gap in the existing guidelines regarding 25(OH)D level in relation to recurrent stroke, our findings might highlight the importance of adequate vitamin D status in relation to recurrent stroke risk, although we had limited data to explore the causal mechanisms. Several limitations exited in this study. First, we could not fully preclude confounding effects especially of those unmeasured variables in this observational study, which may compromise the validity and strength of our results [24]. For instance, due to lack of data on NIHSS, whether and to what extent the relationship between vitamin D status and recurrent stroke risk could be influenced by stroke severity and size, remained unknown. Likewise, the relationship between 25(OH)D and recurrent stroke risk may be driven by some unmeasured factors associated with lifestyle and frailty, which would impair our observed findings. Some baseline comorbidities (hypertension, diabetes, and heart failure) and medications (NSAIDs, antihypertensive, and antidiabetic drugs) were significantly associated with serum 25(OH)D levels. Even though we adjusted for all the comorbidities and medications in the multivariable model, unquantified moderator and confounding effects would remain. It was reported that the use of Liaison assay would systematically underestimate the values of 25(OH)D, which may lead to study populations being misclassified as vitamin D deficiency [25]. Therefore, our results should be interpreted with caution, especially regarding the absolute 25(OH)D values and the inflection points found from the quasi J-shaped relationship curves. We only had data on baseline 25(OH)D measures; thus, no analysis for the change in vitamin D status in relation to recurrent stroke could be performed. It would be a worthwhile endeavor to further explore the change in vitamin D status and its potential usefulness for stroke prognosis and risk evaluation. Furthermore, it was uncertain about whether the splines for hemorrhagic stroke and in females were because of either insufficient statistical power or the true absence of a shaped relationship with 25(OH)D. Collectively, our findings from an observational study were primarily hypothesis generating with an exploratory nature, which warranted further exploration to clarify the vitamin D status in relation to risk of recurrent stroke. 7. Conclusions Based on data from a large-scale prospective cohort, we found a quasi J-shaped relationship between 25(OH)D and risk of recurrent stroke in patients with a stroke history, which might provide some insights into the vitamin D status for recurrent stroke prevention. Given a lack of exploring the cause–effect relationship in this observational study, more high-quality evidence is needed to further clarify the vitamin D status in relation to recurrent stroke risk. Acknowledgments We would like to thank the participants and staff of the UK Biobank study for their valuable contributions. This research has been conducted using the UK Biobank Resource under Application Number 63844. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14091908/s1, Table S1: Codes used for ascertainment of stroke events at baseline and during follow-up; Table S2. Sensitivity analysis results for the relationship between 25(OH)D and risk of recurrent ischemic stroke; Figure S1: Flow diagram showing the selection of participants in this study; Figure S2: Kaplan–Meier failure curve for incident recurrent stroke; Figure S3: Kernel density estimate for probability density function of 25(OH)D stratified by participants with and without recurrent stroke; Figure S4: Restricted cubic splines showing 25(OH)D in relation to recurrent ischemic stroke with the lowest risk laying at 56.3 nmol/L; Figure S5: Restricted cubic splines showing 25(OH)D in relation to recurrent hemorrhagic stroke with the potentially lowest risk laying at 41.2 nmol/L; Figure S6: Restricted cubic splines showing 25(OH)D in relation to recurrent stroke in males with the lowest risk laying at 58.7 nmol/L; Figure S7: Restricted cubic splines showing 25(OH)D in relation to recurrent stroke in females with the potentially lowest risk laying at 38.7 nmol/L; Figure S8: Restricted cubic splines showing 25(OH)D in relation to recurrent stroke in patients <65 years with the lowest risk laying at 58.4 nmol/L; Figure S9: Restricted cubic splines showing 25(OH)D in relation to recurrent stroke in patients ≥65 years with the lowest risk laying at 53.3 nmol/L. Click here for additional data file. Author Contributions G.L., L.L., Z.Y. and X.L. contributed equally to this study. G.L., L.L., Z.Y., X.L. and G.Y.H.L.: conceived and designed the study. G.L., L.L., Z.Y. and X.L.: obtained data, performed analyses and interpretation, and drafted the manuscript. G.L., J.D.A., R.W., L.T. and G.Y.H.L.: provided professional and statistical support, and made critical revisions. G.L. and G.Y.H.L. acted as the guarantors of this work. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The UK Biobank study was approved by the North West Multicenter Research Ethics Committee (11/NW/0382). The Guangdong Second General Provincial Hospital Research Ethics Committee approved the current analysis (2022-KY-KZ-119-01). Informed Consent Statement All participants provided written consent before enrolment. Data Availability Statement The data can be available on application to the UK Biobank (www.ukbiobank.ac.uk/). Data described for the analyses and in the manuscript will be made available upon request. Conflicts of Interest G.Y.H.L. has served as a consultant for Novartis, Bayer/Janssen, Biotronik, BMS/Pfizer, Medtronic, Boehringer Ingelheim, Verseon, and Daiichi-Sankyo and as a speaker for Medtronic, Bayer, BMS/Pfizer, Boehringer Ingelheim, and Daiichi-Sankyo. No fees have been received directly or personally. All other authors have declared no conflicts of interest. Figure 1 Restricted cubic spline showing the 25(OH)D levels in relation to risk of recurrent stroke (shadow indicating the 95% confidence intervals). nutrients-14-01908-t001_Table 1 Table 1 Patients’ baseline characteristics and comparisons between patients with and without recurrent stroke. Characteristics Total Participants (n = 6824) Stroke Recurrence during Follow-Up Yes (n = 388) No (n = 6436) p-Value Age: mean (SD), years 60.6 (6.9) 61.9 (6.4) 60.6 (6.9) <0.01 Female sex: n (%) 2783 (40.8) 136 (35.1) 2647 (41.1) 0.02 BMI: mean (SD), kg/m2 28.8 (5.1) 28.5 (4.9) 28.9 (5.1) 0.13 Smoking: n (%)    Never 2747 (40.6) 140 (36.4) 2607 (40.9) 0.05    Former 2915 (43.1) 167 (43.4) 2748 (43.1)    Current 1097 (16.2) 78 (20.3) 1019 (16.0) Alcohol drinking: n (%)    Never 446 (6.6) 28 (7.3) 418 (6.5) 0.83    Former 588 (8.7) 32 (8.3) 556 (8.7)    Current 5761 (84.8) 326 (84.5) 5435 (84.8) White ethnicity: n (%) 6465 (95.3) 367 (94.8) 6098 (95.3) 0.68 With college or university degree: n (%) 567 (8.5) 31 (8.2) 536 (8.5) 0.83 Physical activity (≥600 MET min per week): n (%) 3792 (73.1) 196 (66.9) 3596 (73.5) 0.01 Comorbidity: n (%)    Atrial fibrillation 535 (7.8) 39 (10.1) 496 (7.7) 0.10    Hypertension 4222 (61.9) 269 (69.3) 3953 (61.4) <0.01    Hypercholesterolemia 2996 (43.9) 188 (48.5) 2808 (43.6) 0.06    Diabetes 1003 (14.7) 92 (23.7) 911 (14.2) <0.01    Heart failure 206 (3.0) 17 (4.4) 189 (2.9) 0.11 Medication and supplementation intake: n (%)    NSAIDs 694 (10.2) 38 (9.8) 656 (10.2) 0.80    Antihypertensive drugs 4075 (59.8) 259 (66.8) 3816 (59.4) <0.01    Antidiabetic drugs 763 (11.2) 76 (19.6) 687 (10.7) <0.01    Statins 4462 (65.4) 274 (70.6) 4188 (65.1) 0.03    Anticoagulants 631 (9.2) 51 (13.1) 580 (9.0) <0.01    Vitamins 1934 (28.7) 110 (28.6) 1824 (28.7) 0.99    Minerals and other dietary supplementation 2685 (39.6) 144 (37.5) 2541 (39.7) 0.39 Serum 25(OH)D: mean (SD), nmol/L 46.5 (22.4) 45.6 (25.9) 46.5 (22.1) 0.48 SD = standard deviation; BMI = body mass index; NSAIDs = non-steroidal anti-inflammatory drugs. nutrients-14-01908-t002_Table 2 Table 2 Results for the relationship between serum 25(OH)D level and recurrent stroke risk. Outcome/Analysis No. of Events/No. of Patients 25(OH)D Level, in nmol/L 1 10 20 30 40 50 60 70 80 Main analysis Primary outcome Total recurrent stroke 388/6824 Ref 0.85 (0.65–1.12) 0.72 (0.44–1.18) 0.62 (0.36–1.06) 0.54 (0.33–0.89) 0.52 (0.33–0.84) 0.56 (0.35–0.88) 0.63 (0.39–1.01) Secondary outcome Ischemic stroke 250/6824 Ref 0.91 (0.64–1.28) 0.82 (0.44–1.54) 0.75 (0.37–1.51) 0.70 (0.37–1.32) 0.69 (0.38–1.26) 0.72 (0.40–1.31) 0.79 (0.43–1.44) Hemorrhagic stroke 87/6824 Ref 0.64 (0.36–1.13) 0.44 (0.16–1.21) 0.38 (0.12–1.16) 0.40 (0.15–1.09) 0.42 (0.16–1.06) 0.40 (0.16–1.02) 0.38 (0.14–1.02) Subgroup analysis By sex Males 252/4041 Ref 1.01 (0.73–1.41) 0.99 (0.54–1.80) 0.88 (0.45–1.72) 0.74 (0.40–1.37) 0.70 (0.39–1.25) 0.76 (0.43–1.35) 0.91 (0.51–1.63) Females 136/2783 Ref 0.54 (0.33–0.88) 0.33 (0.14–0.78) 0.29 (0.11–0.72) 0.32 (0.14–0.74) 0.34 (0.16–0.74) 0.31 (0.14–0.67) 0.25 (0.11–0.60) By age <65 years 205/4355 Ref 0.85 (0.58–1.24) 0.71 (0.36–1.37) 0.56 (0.28–1.12) 0.45 (0.24–0.85) 0.43 (0.23–0.79) 0.47 (0.25–0.86) 0.56 (0.30–1.04) ≥65 years 183/2469 Ref 0.86 (0.58–1.28) 0.75 (0.36–1.57) 0.68 (0.28–1.64) 0.66 (0.29–1.48) 0.66 (0.31–1.39) 0.68 (0.33–1.41) 0.72 (0.34–1.52) Ref = reference; 1 Results shown as hazard ratios (95% confidence intervals) from the models that used restricted cubic splines and were adjusted for age, sex, BMI, smoking and drinking, physical activity, comorbidities, medications, and supplementation. nutrients-14-01908-t003_Table 3 Table 3 Result from additional analyses for the relationship between 25 (OH)D and recurrent stroke risk. Serum 25(OH)D Level Recurrent Stroke No. of Events/No. of Patients HR (95% CI) 1 p-Value Defined by quartile 2 1st quartile 117/1719 Ref - 2nd quartile 92/1707 0.77 (0.56–1.07) 0.12 3rd quartile 86/1693 0.68 (0.48–0.96) 0.03 4th quartile 93/1705 0.77 (0.55–1.08) 0.13 Defined by status Deficiency (<25 nmol/L) 97/1239 Ref - Insufficiency (25–50 nmol/L) 149/2906 0.60 (0.44–0.81) < 0.01 Sufficiency (>50 nmol/L) 142/2679 0.59 (0.43–0.82) < 0.01 HR = hazard ratio; CI = confidence interval; Ref = reference; 1 Results from the models that used restricted cubic splines and were adjusted for age, sex, BMI, smoking and drinking, physical activity, comorbidities, medications, and supplementation. 2 The cut-off points to define quartiles were 28.9, 43.5, and 61.3 nmol/L. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Virani S.S. Alonso A. Aparicio H.J. Benjamin E.J. Bittencourt M.S. Callaway C.W. Carson A.P. Chamberlain A.M. Cheng S. Delling F.N. Heart Disease and Stroke Statistics—2021 Update: A Report From the American Heart Association Circulation 2021 143 e254 e743 10.1161/CIR.0000000000000950 33501848 2. Khanevski A.N. Bjerkreim A.T. Novotny V. Næss H. Thomassen L. Logallo N. Kvistad C.E. The NOR-STROKE Study Group Recurrent ischemic stroke: Incidence, predictors, and impact on mortality Acta Neurol. Scand. 2019 140 3 8 10.1111/ane.13093 30929256 3. Flach C. Muruet W. Wolfe C.D. Bhalla A. Douiri A. Risk and Secondary Prevention of Stroke Recurrence: A Population-Base Cohort Study Stroke 2020 51 2435 2444 10.1161/STROKEAHA.120.028992 32646337 4. Donkor E.S. Stroke in the21stCentury: A Snapshot of the Burden, Epidemiology, and Quality of Life Stroke Res. Treat. 2018 2018 3238165 10.1155/2018/3238165 30598741 5. Lip G.Y.H. Ntaios G. “Novel Clinical Concepts in Thrombosis”: Integrated Care for Stroke Management—Easy as ABC Thromb. Haemost. 2021 122 316 319 10.1055/a-1632-1777 34474499 6. Zhou R. Wang M. Huang H. Li W. Hu Y. Wu T. Lower Vitamin D Status Is Associated with an Increased Risk of Ischemic Stroke: A Systematic Review and Meta-Analysis Nutrition 2018 10 277 10.3390/nu10030277 29495586 7. Jani R. Mhaskar K. Tsiampalis T. Kassaw N.A. González M. Ángel M. Panagiotakos D.B. Circulating 25-hydroxy-vitamin D and the risk of cardiovascular diseases. Systematic review and meta-analysis of prospective cohort studies Nutr. Metab. Cardiovasc. Dis. 2021 31 3282 3304 10.1016/j.numecd.2021.09.003 34656382 8. Shi H. Chen H. Zhang Y. Li J. Fu K. Xue W. Teng W. Tian L. 25-Hydroxyvitamin D level, vitamin D intake, and risk of stroke: A dose-response meta-analysis Clin. Nutr. 2020 39 2025 2034 10.1016/j.clnu.2019.08.029 31530422 9. Su C. Jin B. Xia H. Zhao K. Association between Vitamin D and Risk of Stroke: A PRISMA-Compliant Systematic Review and Meta-Analysis Eur. Neurol. 2021 84 399 408 10.1159/000517584 34325429 10. Qiu H. Wang M. Mi D. Zhao J. Tu W. Liu Q. Vitamin D status and the risk of recurrent stroke and mortality in ischemic stroke patients: Data from a 24-month follow-up study in China J. Nutr. Health Aging 2017 21 766 771 10.1007/s12603-016-0821-z 28717806 11. Huang H. Zheng T. Wang S. Wei L. Wang Q. Sun Z. Serum 25-hydroxyvitamin D predicts early recurrent stroke in ischemic stroke patients Nutr. Metab. Cardiovasc. Dis. 2016 26 908 914 10.1016/j.numecd.2016.06.009 27461862 12. Sudlow C. Gallacher J. Allen N. Beral V. Burton P. Danesh J. Downey P. Elliott P. Green J. Landray M. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age PLoS Med. 2015 12 e1001779 10.1371/journal.pmed.1001779 25826379 13. Siniscalchi A. Lochner P. Anticoli S. Chirchiglia D. De Sarro G. Gallelli L. What is the Current Role for Vitamin D and the Risk of Stroke? Curr. Neurovascular Res. 2019 16 178 183 10.2174/1567202616666190412152948 30977444 14. Yarlagadda K. Ma N. Doré S. Vitamin D and Stroke: Effects on Incidence, Severity, and Outcome and the Potential Benefits of Supplementation Front. Neurol. 2020 11 384 10.3389/fneur.2020.00384 32587562 15. Michos E.D. Carson K.A. Schneider A.L.C. Lutsey P.L. Xing L. Sharrett A.R. Alonso A. Coker L.H. Gross M. Post W. Vitamin D and Subclinical Cerebrovascular Disease: The Atherosclerosis Risk in Communities brain magnetic resonance imaging study JAMA Neurol. 2014 71 863 10.1001/jamaneurol.2014.755 24861877 16. Berridge M.J. Vitamin D deficiency and diabetes Biochem. J. 2017 474 1321 1332 10.1042/BCJ20170042 28341729 17. Kheiri B. Abdalla A. Osman M. Ahmed S. Hassan M. Bachuwa G. Vitamin D deficiency and risk of cardiovascular diseases: A narrative review Clin. Hypertens. 2018 24 9 10.1186/s40885-018-0094-4 29977597 18. Makariou S. Michel P. Tzoufi M. Challa A. Milionis H. Vitamin D and Stroke: Promise for Prevention and Better Outcome Curr. Vasc. Pharmacol. 2014 12 117 124 10.2174/15701611113119990119 22724468 19. Drüeke T.B. Massy Z.A. Role of vitamin D in vascular calcification: Bad guy or good guy? Nephrol. Dial. Transplant. 2012 27 1704 1707 10.1093/ndt/gfs046 22431706 20. Ji W. Zhou H. Wang S. Cheng L. Fang Y. Low serum levels of 25-hydroxyvitamin D are associated with stroke recurrence and poor functional outcomes in patients with ischemic stroke J. Nutr. Health Aging 2016 21 892 896 10.1007/s12603-016-0846-3 21. Welles C.C. Whooley M.A. Karumanchi S.A. Hod T. Thadhani R. Berg A.H. Ix J.H. Mukamal K.J. Vitamin D deficiency and cardiovascular events in patients with coronary heart disease: Data from the Heart and Soul Study Am. J. Epidemiol. 2014 179 1279 1287 10.1093/aje/kwu059 24699783 22. Kolmos M. Christoffersen L. Kruuse C. Recurrent Ischemic Stroke—A Systematic Review and Meta-Analysis J. Stroke Cerebrovasc. Dis. 2021 30 105935 10.1016/j.jstrokecerebrovasdis.2021.105935 34153594 23. Talelli P. Greenwood R.J. Review: Recurrent stroke: Where do we stand with the secondary prevention of noncardioembolic ischaemic strokes? Ther. Adv. Cardiovasc. Dis. 2008 2 387 405 10.1177/1753944708093411 19124436 24. Fewell Z. Smith G.D. Sterne J.A.C. The Impact of Residual and Unmeasured Confounding in Epidemiologic Studies: A Simulation Study Am. J. Epidemiol. 2007 166 646 655 10.1093/aje/kwm165 17615092 25. Fraser W.D. Tang J.C.Y. Dutton J.J. Schoenmakers I. Vitamin D Measurement, the Debates Continue, New Analytes Have Emerged, Developments Have Variable Outcomes Calcif. Tissue Res. 2019 106 3 13 10.1007/s00223-019-00620-2

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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094595 ijms-23-04595 Article Biocompatibility and Mechanical Stability of Nanopatterned Titanium Films on Stainless Steel Vascular Stents https://orcid.org/0000-0003-2398-8261 Yelkarasi Cagatay 1 https://orcid.org/0000-0001-5389-8262 Recek Nina 2 Kazmanli Kursat 1 Kovač Janez 2 https://orcid.org/0000-0002-3529-3371 Mozetič Miran 2 https://orcid.org/0000-0003-3549-0049 Urgen Mustafa 1* https://orcid.org/0000-0002-1145-9883 Junkar Ita 2* Armentano Ilaria Academic Editor Díez-Pascual Ana María Academic Editor 1 Department of Metallurgical and Materials Engineering, Istanbul Technical University, 34469 Istanbul, Turkey; yelkarasi@itu.edu.tr (C.Y.); kursat@itu.edu.tr (K.K.) 2 Jozef Stefan Institute, Jamova Cesta 39, Sl-1000 Ljubljana, Slovenia; nina.recek@ijs.si (N.R.); janez.kovac@ijs.si (J.K.); miran.mozetic@ijs.si (M.M.) * Correspondence: urgen@itu.edu.tr (M.U.); ita.junkar@ijs.si (I.J.) 21 4 2022 5 2022 23 9 459517 3 2022 18 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Nanoporous ceramic coatings such as titania are promoted to produce drug-free cardiovascular stents with a low risk of in-stent restenosis (ISR) because of their selectivity towards vascular cell proliferation. The brittle coatings applied on stents are prone to cracking because they are subjected to plastic deformation during implantation. This study aims to overcome this problem by using a unique process without refraining from biocompatibility. Accordingly, a titanium film with 1 µm thickness was deposited on 316 LVM stainless-steel sheets using magnetron sputtering. Then, the samples were anodized to produce nanoporous oxide. The nanoporous oxide was removed by ultrasonication, leaving an approximately 500 nm metallic titanium layer with a nanopatterned surface. XPS studies revealed the presence of a 5 nm-thick TiO2 surface layer with a trace amount of fluorinated titanium on nanopatterned surfaces. Oxygen plasma treatment of the nanopatterned surface produced an additional 5 nm-thick fluoride-free oxide layer. The samples did not exhibit any cracking or spallation during plastic deformation. Cell viability studies showed that nanopatterned surfaces stimulate endothelial cell proliferation while reducing the proliferation of smooth muscle cells. Plasma treatment further accelerated the proliferation of endothelial cells. Activation of blood platelets did not occur on oxygen plasma-treated, fluoride-free nanopatterned surfaces. The presented surface treatment method can also be applied to other stent materials such as CoCr, nitinol, and orthopedic implants. cardiovascular stents nanopatterning plasma treatment endothelium cells smooth muscle cells cell viability hemocompatibility restenosis ==== Body pmc1. Introduction According to the World Health Organization [1,2], cardiovascular diseases represent the number one cause of death globally, accounting for almost one-third of all cases. The number of coronary bypass surgeries, a radical way of treating cardiovascular diseases (CVD), decreased dramatically with the invention and application of coronary stents. Today, the most widely used cardiovascular stent materials are 316 LVM stainless-steels, CoCr alloys, and nitinol [3]. In the early decades, bare metallic stents (BMS) were successfully used for the treatment of more than 2 million people each year [4], even if they may cause other complications such as re-blockage of the vessels, also known as in-stent restenosis (ISR). ISR is widely observed in 20–30% of the patients six months after the stent implantation [5]. This post-implantation complication is caused by vascular smooth cell migration, proliferation, and growth of the arterial inner wall, and can be described as “an exaggerated healing process” because of the insufficient biocompatibility of the stent material [6]. In order to decrease the ISR rate, drug-eluting stents (DES) were developed by coating the bare metal stents with immunosuppressive or cancer treatment agent-containing polymeric materials to inhibit vascular smooth cell growth [7]. However, long-term research showed that the risk of stent-induced thrombosis rate of DES is much higher than BMS [8,9,10]. Additionally, there was always a risk of peeling off the polymer coating during stent deployment [11]. The new generation of DES with a bioabsorbable polymeric coating showed promising results compared to the first-generation DES [12,13]. However, it is still quite challenging to significantly reduce the restenosis rate without using drugs such as sirolimus or paclitaxel. Biocompatibility of the implant surfaces can also be improved with chemically stable inorganic material coatings [8,14]. Metal oxides such as TiO2 are extensively used for this purpose [15,16], as they exhibit good biocompatibility and can be produced in various morphologies, including nanostructures. Many studies have already shown that nanostructured surface features significantly influence biological responses and can even be selective for specific cell types [17,18,19,20,21]. Nanostructures can be fabricated by various methods, such as sandblasting [22], hydrothermal processes [23,24,25,26], anodization [27,28], or surface-alloying followed by selective etching [10]. Karpagavalli et al. [29] reported that nano-topography produced by deposition of nanostructured TiO2 onto Ti-alloy surfaces enhanced biocompatibility by decreasing the human aortic smooth muscle cells’ integration. Nasakina et al. [30] studied the biocompatibility of nanostructured nitinol (NiTi: 55.91 wt.% Ni–44.03 wt.% Ti) coated with titanium or tantalum layers produced with magnetron sputtering. They have found that coated samples exhibited higher mitotic activity than the NiTi reference sample with the formation of a merged-cell monolayer of the myofibroblasts and the mesenchymal stromal cells. Another study by Chen et al. [31] showed that mesenchymal stem cells (MSCs) proliferated better on the nano-hydroxyapatite (HAp) coating compared to bare titanium or micron-sized hydroxyapatite-coated surface, indicating that the HAp/Ti nanocomposite has good biocompatibility and bioactivity for orthopedic and dental implant applications. For implants in contact with blood, such as vascular stents, inhibiting or decreasing the potential of thrombosis, associated with high platelet adhesion and its activation on the implant surface, is a primary concern. The adhesion of platelets is an indicator of surface hemocompatibility: the lower the platelet adhesion and their activation on the surface, the higher the material biocompatibility with blood [32]. It has already been shown that appropriately nanostructured surfaces could influence platelet adhesion [33,34]. This improvement was ascribed to altered conformation of adsorbed proteins on the surface, mainly fibrinogen, which was recognized as an essential factor determining platelet adhesion and activation. It was shown in a recent study by Firkowska-Boden et al. that confirmation of fibrinogen molecules changes due to the altered surface nano-topography, which further dictates platelet interactions [33]. However, it should be emphasized that other physicochemical properties of the material’s surface, such as chemical composition and wettability, play an essential role in blood platelet interactions [34,35]. Thus, plasma treatment may also be used for fine-tuning the nanostructured surface properties to improve biocompatibility. This treatment can be performed using various gaseous discharges to make surfaces either hydrophilic or hydrophobic and induce different chemical surface compositions, surface charge, roughness, and crystallinity [36]. These factors have an essential role in immobilizing proteins and cells [37,38,39]. An excellent review of plasma treatment and cell adhesion is provided in a paper by Griesser et al. [40]. In the studies aiming to investigate the contribution of brittle oxide-based nanostructures such as anodic oxides to the biocompatibility of coronary stents, the nature and integrity of the treated surface and its performance during implantation are not afforded sufficient consideration. The stents are plastically deformed during implantation, which increases the brittle top layer’s cracking and delamination risk. Thus, ceramic coatings on stents, such as titanium oxide, have risks because of the high plastic deformation during their expansion. As a result, cracked or delaminated coating layers may detach from the surface under mechanical stresses, including forces accompanied by blood flow or cyclic expansion of the blood veins. This phenomenon not only damages the desired surface chemistry and nano-topography, but may also increase the risk of restenosis and other complications arising from particle debris [41]. In an ideal case, a coating on a BMS should be as flexible as the metallic substrate itself, and at the same time as biocompatible as a nanostructured film. Fabricating such coatings or surface modifications that exhibit these properties still presents a scientific and technological challenge. In this work, a unique surface modification method is reported for producing a highly biocompatible nanopatterned surface that is expected to preserve its integrity during plastic deformation of the stents. The method briefly consists of deposition of titanium on AISI 316 LVM stainless-steel stent materials, followed by anodization and removal of the nanoporous anodic oxide from the substrates by ultrasonic cavitation, leaving behind a nanopatterned metallic titanium layer on the SS. The samples are also subjected to an additional treatment with non-equilibrium gaseous oxygen plasma for improving biocompatibility. The mechanical integrity of nanoporous anodic oxide and nanopatterned metallic titanium-covered surface layers during plastic deformation was also investigated. Furthermore, in vitro studies with human coronary artery endothelial cells (HCAEC) and human coronary artery smooth muscle cells (HCASMC) and whole blood were performed to evaluate the influence of surface modification on the biological response. The innovative, nanopatterned, metallic titanium-coated stainless-steel surfaces have shown superior biocompatible properties and, at the same time, good coating stability, which is of primary importance for its application for vascular stents. 2. Results A schematic illustration of procedures used to prepare the nanopatterned surfaces is presented in Figure 1. Accordingly, after surface polishing of stainless-steel (SS), a four-step procedure was applied:Step #1: Titanium coating on SS (pTi). Step #2: Partial anodization of titanium-coated SS (aTiO2). Step #3: Removal of anodic porous anodic oxide with ultrasonication, leaving behind a thin nanopatterned Ti layer on SS (cTi). Step #4: Brief oxygen plasma treatment (cTi+P). In addition to the steps above, pTi and its plasma-treated version (pTi+P) were used as a reference in the biological tests. 2.1. Optimization of Anodization Duration During the anodization of pTi, the thickness of the metallic titanium that will remain on the SS after ultrasonication is directly related to the anodization time. Therefore, we first anodized the entire titanium film on SS and recorded the anodization current versus time. With the initiation of anodization, the current sharply decreased, indicating the formation of a barrier titanium oxide layer, followed by a slight increase in current with the formation of pores. After the pore formation, the current decreased monotonously with the increasing thickness of the oxide film. With a further increase of anodization time, the current started to increase, with the beginning of the anodic dissolution of the SS surface (Figure 2). Accordingly, the time needed for anodization of the entire titanium film was determined as 500 s. Thus, for the anodization of approximately 500 nm of the metallic titanium on the SS substrate, we anodized the sample for 250 s. The validity of the method was verified by measuring the remained titanium layer thickness by XRF after removal of the anodic oxide with ultrasonication. These measurements showed that the thickness of the remnant metallic titanium film was in the range of 500 ± 40 nm. We used this validated methodology to prepare the samples for further testing. 2.2. Morphological Characterizations Morphological changes after accomplishing each step were examined by scanning electron microscope (SEM) (Figure 3). The SEM image of the 316 LVM stainless-steel sample after titanium film deposition (Step #1) is presented in Figure 3a. A relatively smooth surface was observed (pTi). Such a surface is typical for deposition processes using magnetron sputtering with moderate biasing of the substrate. Figure 3b shows the SEM image after the anodization process (Step #2). The titanium layer was transformed into a nanoporous oxide structure (aTiO2). The lateral dimensions of the pores were about 100 nm. The ultrasonication (Step #3) enabled the removal of the nanoporous oxide film and revealed the nanopatterned titanium layer with a hemispherical nanostructure (cTi) (Figure 3c). The SEM image of the boundary line of the ultrasonicated area clearly shows that the process successfully removed the brittle, weakly adhered nanoporous TiO2 without causing a significant modification of the remnant nanopatterned metallic titanium layer (Figure 4). The depth and diameter of the nanopatterns were measured with AFM. Figure 5a,b show the AFM images of the cTi surface. Accordingly, the nanosized hemispherical patterns have a depth and diameter of 20 ± 5 and 100 ± 20 nm, respectively (Figure 5c). 2.3. Response of aTiO2 and cTi Surfaces to Plastic Deformation Stents are subjected to considerable plastic deformation during application. This aspect is not generally considered in the studies aiming to modify the surfaces of the stents by different methods. Understanding the changes that may be induced on the structure and morphology of the surface-treated stents is very important for the proper functioning of the stents. We have applied a three-point bending test (for two different angles: 45° and 90°) to compare the mechanical stability of anodized samples before (aTiO2) and after (cTi) removal of the nanoporous oxide structure. After the bending test, SEM images of the aTiO2 surface indicated the formation of microcracks in the nanoporous structure (Figure 6a,b). However, the cTi surface survived well under both deformation conditions (Figure 6c,d). These results indicated that the samples with a nanoporous anodic oxide layer (aTiO2) tend to crack and delaminate. This effect may create debris during the functioning of the stents and increase the risk of increased augmented vascular inflammation. On the other hand, the nanopatterned surfaces (cTi) did not exhibit cracking or delamination under the bending conditions used in this study. Additionally, they preserved their nanopatterned morphology, making them more favorable for stent applications. Bending tests of plasma-treated cTi surfaces also afforded similar results. The potential of these samples to be used as stent materials is investigated in detail in the further sections of the study. 2.4. Surface Analysis by XPS XPS characterization of cTi samples before and after the plasma treatment was performed to reveal surface chemistry (Figure 7). The wide spectrum obtained from sample surfaces before plasma treatment consisted of mainly titanium and oxygen, typical for a metallic titanium surface exposed to the atmosphere. In addition to carbon, nitrogen, and calcium probably originating from surface contamination, the peak corresponding to F1s was also present in the spectrum due to the electrochemical process used for fabrication of nanostructures. The spectrum acquired after plasma treatment was similar to the one obtained before plasma treatment except for the F1s peak, which was no longer present on the surface. High-resolution XPS spectra of Ti2p, O1s, and F1s were also acquired to detail the surface’s chemistry and the effect of the oxygen plasma treatment. The deconvoluted spectrum of the Ti2p peak before oxygen plasma consisted of two doublets (Figure 8). The primary compound of the film was Ti4+ bound to oxygen in the form of TiO2, as expected (Ti2p3/2 = 458.7 eV, Δ = 5.8 eV). The minor compound in the film is attributed to fluorinated titanium [42] (Ti2p3/2 = 460.1 eV, Δ = 5 eV). The presence of the fluorinated compound was further verified with the F1s peak (Figure 9a). The deconvoluted O1s spectrum, which is the other principal constituent of the surface layer, consists of two compounds at 530.2 eV (O1s for TiO2) and 531.6 eV (O1s for adsorbed O–H or O–C molecules) [43] (Figure 9b). Thus, the surface layer of the sample before plasma treatment consists of TiO2-, fluorinated-Ti-, O–H-, and O–C-based compounds. After oxygen plasma treatment, the fluorinated-Ti in the Ti2p spectrum was no longer observed, leaving behind TiO2 as the main titanium compound (Figure 8). The F1s peak was also no longer detectable in the spectral region of F1s (Figure 9a). The O1s intensity that corresponds to the Ti4+ bond to oxygen increased (Figure 9b) along with the substantial decrease of O1s peaks corresponding to O–H and O–C bonds. For further evaluation of the concentration variation of Ti, O, F, and C within the surface layer, we performed XPS depth profiling on cTi samples before and after plasma treatment. According to the XPS depth profiles shown in Figure 10, plasma treatment caused an increase in the thickness of the oxide layer, from about 5 to 10 nm (orange and green arrows). In addition, the appearance of a fluorine peak in the depth profile after sputtering 5 nm of the surface layer indicates that the film grew above the existing oxide-fluoride mixture layer during oxygen plasma treatment (Figure 10b). Additionally, the calcium contamination observed in the wide spectrum was also diminished after a few cycles of sputtering. 2.5. Surface Wettability Evaluation of surface wettability is one of the surface characteristics of biomaterial surfaces, as it may play an essential role in the biological response. Water contact angles (WCA) were measured on pTi and cTi samples before and after plasma treatment to determine the contribution of both nanopatterning and plasma treatment to wetting properties (Table 1). Results show that the pTi and cTi are relatively hydrophobic. Plasma treatment increased the wettability of both samples due to the removal of surface contaminants and the oxidation of titanium, which was also confirmed by XPS analysis conducted on cTi (Figure 7, Figure 8 and Figure 9). However, plasma treatment induced a more prominent effect on pTi. Increased wetting properties of the surface do not necessarily indicate a better biological response [44], which also depends on surface texture, chemistry, and the nature of the cells that interact with the surface. Thus, measured WCA values should be considered together with other surface features for its final application in the body (desired cell interaction). 2.6. Biological Response of the Nanopatterned Surfaces For the description of the nanopatterned surfaces that will be subjected to biocompatibility tests, the results of XPS, SEM, and surface wettability data for cTi and cTi+P are compiled and presented in this section. The structure of the nanoporous/nanotubular titanium layer formed during anodization in fluoride-containing electrolytes is very well-known [45]. During anodization, a fluorinated-Ti layer forms below the barrier layer and between the pore walls (Figure 11a) [46]. As expressed by XPS measurements (Figure 6, Figure 7, Figure 8 and Figure 9), the remnants of this fluorinated-Ti layer were still present on the surface even after removing the anodic oxide with ultrasonication. Thus, the morphology and chemistry of the sample described as cTi is equivalent to the schematic picture presented in Figure 11b and consists of a mixture of fluorinated-Ti and oxides with a surface wetting angle of 80 ± 4°. Oxygen plasma treatment increases the oxide layer thickness on metallic titanium. As determined from XPS depth profiles (Figure 10a,b), this oxide film grows on the mixture of fluorinated-Ti and oxides. Thus, on the cTi+P samples, the fluorinated-Ti layer was not present, and their wetting angles were lower than those of cTi (Figure 11c). 2.6.1. In Vitro Cell Viability Studies To reveal the influence of nanopatterning on the biological response, we performed in vitro studies with HCAEC and HCASMC. These two cell lines are often used in in vitro studies of cardiovascular functions, such as angiogenesis and atherosclerosis. HCAEC form a layer on the inner side of the blood vessels and have a main role in the formation of the vessels. HCASMC form the media layer of arteries and maintain the integrity of the arterial wall. In the case of atherosclerosis and restenosis, these cells play an important role in arterial wall remodeling. In case of vascular stents, it is desired that endothelial cells grow well on the surface, as they present ideal antithrombogenic material, while smooth muscle cell growth should be inhibited to prevent the risk of restenosis (narrowing of blood vessels). In vitro tests were performed on pTi and cTi surfaces before and after plasma treatment to determine the metabolic activity of cells adhered to these substrates. pTi samples were used as a reference. The HCAEC viability on the cTi samples was significantly improved compared to pTi reference samples (Figure 12a). The nanopatterned surface cTi covered with a mixture of titanium dioxide and fluorinated-Ti was shown to improve HCAEC viability, while even higher metabolic activity of adhered cells was observed on the plasma-treated nanopatterned surface (cTi+P) (Figure 11c). On the other hand, HCASMC (Figure 12b) adhered and proliferated best on pTi, whereas on cTi samples, their viability was significantly lower, indicating unfavorable surface conditions for their attachment and viability. In the initial stage, plasma-treated nanopatterned surfaces (cTi+P) showed improved viability of HCASMC compared to nanostructured surfaces (cTi); however, after 24 h of incubation, no significant difference in viability was observed between these two surfaces. It should also be emphasized that HCASMC viability was the lowest for nanopatterned surfaces (with or without plasma treatment) compared to the control (pTi), which indicates that such nano-topography significantly influences the adhesion and viability of HCASMC. Interestingly, the opposite was observed for the HCAEC, where nanopatterned surfaces were shown to improve cell viability. After plasma treatment of nanopatterned surfaces and longer incubation times, the viability of HCAEC was improved. 2.6.2. Platelet Adhesion Platelet adhesion tests were utilized to determine the hemocompatibility of the cTi and cTi+P samples that exhibited good biocompatibility, using pTi as a reference. After incubation with whole blood, SEM analyses were used to determine the number and morphology of adhered platelets on the samples. The morphological forms of platelets from the least activated to the most activated were as follows: round (R) > dendritic (D) > spread dendritic (SD) > spread (S) > fully spread (FS) [47]. Figure 13 presents the interaction of whole blood with different samples. It was observed that on the pTi surface, platelets adhered mainly in fully spread form, which indicates their high activation on the surface and thus the high risk for undesired thrombotic reactions. Some erythrocytes were also present on the surface, as seen in Figure 13. In the case of plasma-treated Ti (pTi+P), platelets were mostly in the dendritic (D) and spread dendritic (SD) form. In this case, a lower number of platelets on the surface was observed, and some erythrocytes were also detected as well as leukocytes. In the case of cTi, a high number of platelets was observed, and their morphology indicated high activation and adhesion, as platelets were mainly in the S and FS form. While in the case of cTi+P, platelet adhesion was significantly reduced, and practically no platelets were detected on these surfaces, only a few erythrocytes were present, as seen in Figure 13. This result pointed out the benefit of oxygen plasma treatment on hemocompatibility. 3. Discussion The beneficial role of nano-topographic features on the biocompatibility of biomaterials is very well-known and has already been the subject of intensive research [5,48,49,50,51,52,53,54,55,56]. Most of the studies deal with osseointegration properties of orthopedic implants, while some also involve the interaction of endothelial cells with the surface used for cardiovascular stent applications [48,50,51]. It was shown that surface geometry plays an important role in biological responses, as different interactions of cells and proteins with surfaces having similar chemistry but altered nanotopography were observed [17,18,19,34,50]. Accordingly, the biocompatibility of an implant with appropriate surface chemistry can be further increased with nano-structuring. The proposed mechanisms that lead to increased biocompatibility are: (1) electronic modifications of the topmost surface, (2) increased surface area (edges/corner sites, particle boundaries), and (3) mimicking the natural architecture of vascular walls [52]. These mechanisms potentially affect protein adhesion (their conformation) and the cell response, which further influences its integration with the surrounding tissues and the lifespan of the medical device in the body. The nanopatterned surfaces obtained in this study were shown to provide selective cell adhesion, as improved proliferation of HCAEC and reduced proliferation of HCASMC were observed. In addition, these types of surfaces seem to reduce platelet adhesion and activation, which reduces the risk of thrombosis. Other studies show that the viability of both HCAEC and HCASMC increases without selectivity for nanopore diameters below 35 nm [15]. However, for those between 70 and 100 nm, selectivity toward HCAEC was obtained [15,57]. We have observed similar vascular cell responses using our nanopatterned surfaces with 100 ± 10 nm pore diameters. The higher cell viability of HCAEC compared to HCASMC (Figure 12) can be attributed to the morphology of the obtained nanopattern that resembles the natural nanoarchitecture of the internal vessel wall where endothelial cells attach [58], as well as to altered surface chemistry obtained by oxygen plasma treatment. Fluorinated titanium compounds were detected on nanopatterned surfaces after removing nanoporous TiO2 with ultrasonication (Figure 8, Figure 9 and Figure 10). However, further improvement of cell viability with oxygen plasma treatment was achieved for HCAEC, while no significant difference in cell viability was observed for HCASMC. It could be proposed that HCAEC are more sensitive to the change in surface chemistry, as after plasma treatment fluorine is removed from the surface and the oxide layer is formed. However, our results also show that the fluorinated-Ti-containing nanopatterned (cTi) surface exhibits better cell viability for HCAEC than flat (pTi) and (pTi+P), indicating the dominant role of nanopatterning on cell viability even in the presence of a fluorinated layer. The nanofeatures obtained in this study have significantly lower thicknesses than nanotubes described in the literature. These results indicate that the main morphological parameter to cell viability is the diameter of the nanofeatures rather than its thickness/length. Thus, the use of poorly adherent thick coatings, such as TiO2 nanotubes/nanopores, to improve the cell viability of implants is not mandatory. As proposed, nanopatterned metallic titanium with similar diameters covered by a very thin oxide layer can function similarly. Attaining the desired biocompatibility of stents is not sufficient, as stents should also have good hemocompatibility. Primarily, they should prevent adhesion and activation of platelets on the surface, as this would significantly reduce the risk for thrombotic reactions [32]. Among the samples investigated in this study, the desired hemocompatibility properties were only attained for oxygen plasma-treated nanopatterned samples (cTi+P) (Figure 13). It is well-known that titanium can act as a thrombogenic material depending on its surface properties [59]. Several studies in the literature indicate the positive role of fluorination on the osseointegration and thrombogenic properties of titanium-based orthopedic and dental implants [60]. Therefore, fluorides may induce thrombogenic reactions on the surface, while oxygen plasma treatment can overcome this issue as it removes the fluoride from the surface as well as increases the concentration of oxygen on the surface. We have not come across any studies on the possible role of fluorides on hemocompatibility and cell viability for stent applications, and further work is needed to clarify these effects. To maintain a healthy blood vessel and avoid ISR, the endothelization of the inner layer of the vessel is very important for cardiovascular stent applications. As the preferred proliferation of HCASMC is one of the main reasons for ISR, providing a surface feature that offers improved cell selectivity towards HCAEC is desired. The proposed nanopatterning method obtained promising results in this regard. However, hemocompatibility is also crucial for the proper functioning of the stent material; thus, appropriate surface chemistry is also needed (restricting the contact with fluorinated-Ti, increasing oxygen content, etc.). Oxygen plasma treatment used in this study was successful for this purpose. An additional benefit of the proposed method is the mechanical integrity of the nanopatterned layer on the stent material under plastic deformation, as cracking and spallation of the oxide layer may lead to undesired biological responses after implantation of the stent and its long-term use in the human body. 4. Materials and Methods 4.1. Sample Preparation The sample preparation procedure schematically presented in Figure 1 is detailed in the following sections. 4.1.1. (STEP #1) Ti Coating The 0.30 mm-thick 316 LVM stainless-steel samples were cut to rectangular pieces of 20 × 10 mm dimensions and mirror-polished. They were placed in a vacuum chamber after surface cleaning with acetone, ethanol, and distilled water. After evacuation to a base pressure of 10−3 Pa, 900 sccm Ar gas was introduced into the chamber to reach 1.5 Pa. Argon ions first etched the samples. The ion etching process was started by applying −600 V bias voltage against the grounded chamber for 4 min, followed by −800 V for 2 min and −1000 V for 1 min. After ion etching, samples were coated with titanium using a dual-rotating magnetron sputtering source operating at 40 kHz, 550 V, and 18 A at a pressure of 0.5 Pa Argon (200 sccm) in the same experimental system, without breaking the vacuum conditions. During the deposition, a DC voltage of −150 V was applied to the substrates to ensure the appropriate properties of the titanium film. The deposition was accomplished in 500 s. The thickness of the titanium film on the stainless-steel substrate was 1 µm. These samples are referred to as plain-titanium-coated stainless-steel (pTi). 4.1.2. (STEP #2) Anodization The plain-titanium-coated SS samples (pTi) were anodized in ethylene glycol solution containing 0.6 wt.% NH4F and 1% v/v H2O at 27 ± 1 °C. A water-jacketed 100 mL cell was used to precisely control the temperature of the anodization solution. The distance between the stainless-steel cathode and the sample was kept constant at 20 mm. The anodization voltage was 40 V. The duration of anodization was optimized by following the time-dependent current variation (Figure 2). After accomplishing the anodization, samples are washed with distilled water and dried. These samples are named as anodized titanium oxide (aTiO2). 4.1.3. (STEP #3) Ultrasonication (US) We have benefited from the low adhesion of anodized titanium oxide (aTiO2) to metallic titanium to remove the aTiO2 layer from the titanium surface. For this purpose, we have subjected the aTiO2 to ultrasonication using a horn-tip ultrasonicator in a distilled water bath, with a peak-to-peak amplitude of 25 µm (transversal mechanical oscillation) and a frequency of 20 kHz. Details of the device are presented elsewhere [61]. The samples subjected to US to produce the nanopatterned metallic titanium layer are named as cTi. 4.1.4. (STEP #4) Plasma Treatment After the ultrasonication, a series of samples were treated in oxygen plasma to observe the contribution to surface chemistry and biocompatibility. This step aims to activate the sample surface and remove any organic impurities that might have persisted on the sample’s surface after accomplishing the ultrasonication. We used a radiofrequency (RF) generator operating at 13.56 MHz and a peak-to-peak voltage of 600 V. The generator was connected to a coil via a matching network. The nominal power was fixed at 400 W, and the plasma was ignited in the capacitive mode (E-mode). Samples were treated in oxygen plasma under 50 Pa pressure for 10 s. Plasma-treated, nanopatterned, metallic titanium and plasma-treated plain titanium are named as cTi+P and pTi+P, respectively. 4.2. Sample Characterization 4.2.1. Surface Morphology and Coating Thickness Determination The surface morphology of the coatings after each step was investigated with FEG-SEM (JEOL JSM 7000F and Thermo Scientific Quattro S Field Emission Scanning Electron Microscope). Topographic features of the surfaces after removal of the oxide layer were examined by Atomic Force Microscopy (Nanomagnetics Instruments, Ankara, Turkey) in tapping mode in the air using Si cantilever at a constant force of 30 N/m and resonance frequency of 160 kHz (<10 nm tip radius, 10 µm tip height). The thickness of the metallic titanium coatings on the 316 LVM substrates was measured with an XRF thickness measurement system (Fischerscope X-ray System XDL 662). The device was calibrated for titanium coatings on 316 LVM stainless-steel. 4.2.2. XPS Analysis X-ray photoelectron spectroscopy (XPS) analyses were performed with the PHI-TFA XPS spectrometer (Physical Electronics Inc., Chanhassen, MN, USA) equipped with an Al-Kα monochromatic source. The analyzed area was about 0.4 mm in diameter. The high-energy resolution spectra were acquired with an energy analyzer operating at the resolution of 0.6 eV and pass energy of 29 eV. XPS depth profiles were obtained by sputtering the sample surface with a 4 keV beam of Ar ions rastered over 3 × 3 mm. The sputtering rate was determined using standards and was about 1 nm/min. Quantification of surface composition was performed from XPS peak intensities considering relative sensitivity factors provided by the instrument manufacturer [62]. 4.2.3. Bending Tests We applied a three-point bending test to determine the SS samples’ response to plastic deformation covered with aTiO2 and cTi. The samples were bent at 45° and 90°. After bending tests, the surfaces of all samples were investigated with SEM. 4.2.4. Surface Wettability The surface wettability was performed with the Drop Shape Analyzer DSA-100 (Krüss GmbH, Hannover, Germany) by the sessile drop method to measure the static contact angle. The contact angle on the surface was analyzed immediately after plasma treatment by adding a 2.5 µL drop of deionized water on 8 different surface areas. The relative humidity was around 45%, and the operating temperature was 21 °C, which did not vary significantly during continuous measurements. 4.3. In Vitro Biological Response Human coronary artery endothelial cells (HCAEC) and human coronary artery smooth muscle cells (HCASMC) were used to evaluate the interaction of cells with the surface. Cell viability was determined via the MTT assay. The blood compatibility was assessed by the adhesion and activation of platelets on the surface after incubation with whole blood. All the samples were incubated with biological material immediately after plasma treatment because of the instability of the WCA of plasma-treated samples after exposure to atmosphere [63]. 4.3.1. Cell Viability Studies—MTT Assay HCAEC were purchased from Lifeline Cell Technology (Frederick, MD, USA), and HCASMC were purchased from ProVitro AG (Berlin, Germany). HCAEC were grown in the VascuLife EnGS endothelial medium complete kit (Frederick, MD, USA) and HCASMC in the smooth muscle cell growth medium FCS-kit (ProVitro AG, Berlin, Germany) at 37 °C in a humidified atmosphere at 5% CO2. Cells were seeded at a density of 2 × 104 cells in 100 μL drops of the medium on the upper side of the samples (concentration: 2.55 × 104 cells/cm2) and left for 3, 24, and 72 h to attach. Experiments were performed in triplicates for each sample and incubation time. After 3, 24, and 72 h of the HCASMC and HCAEC incubation process, the medium was removed, and the samples were washed to remove all the unattached cells from the surface. Then, 200 μL of fresh Hanks’ Balanced Salt Solution (HBSS) mixed with the tetrazolium agent was added to each well with the sample, mixed, and the OD at 492 nm was measured with a microplate reader (Tecan Infinite M1000). Blank (medium without the cells) was measured at 690 nm, and all the experiments were performed in triplicates. JASP 0.9.2 open-source software (University of Amsterdam, Amsterdam, The Netherlands) was used to statistically analyze MTT data. Group means were calculated and compared using ANOVA followed by the post hoc Tukey’s range test. Differences in the means were considered statistically significant at p < 0.05. Error bars in charts represent standard error. 4.3.2. Platelet Adhesion Incubation with whole blood was performed to study the adhesion and activation of platelets on the nanopatterned Ti surface (cTi) and nanopatterned plasma-treated surface (cTi+P) using pTi and pTi+P as reference samples. Whole blood was obtained from healthy donors by vein puncture. Samples were cut to 7 × 7 mm pieces and incubated with 250 μL of whole blood for 45 min at room temperature. Afterward, 250 μL of PBS was added and rinsed 3 times with PBS to remove weakly adherent platelets. The adherent cells were fixed by 400 μL of 0.5 vol% glutaraldehyde for 1 h at room temperature. For SEM analysis, the surfaces were again rinsed with PBS and dehydrated by using a graded ethanol series (50, 70, 80, 90, 100 vol%), and again 100 vol% of ethanol for 5 min, and in the last stage, 100 vol% of ethanol for 10 min. Afterward, the samples were dried with liquid nitrogen, left in a vacuum for 3 h, and coated with gold/palladium before SEM characterization. 5. Conclusions A method for synthesizing titanium coatings on stainless-steel surfaces with desired morphology and chemistry for stent applications was presented. The method enables the formation of periodical, nanopatterned, thin titanium film on smooth stainless-steel substrates. The unique morphology and chemistry were obtained by the four-step procedure, where titanium film was first deposited on the stainless-steel surface, followed by anodization, ultrasonication, and oxygen plasma treatment. The anodization enabled the formation of nanoporous/nanotubular anodic oxide consisting of titanium oxide and fluorinated titanium. After removing this fragile oxide layer by ultrasonication, a nanopatterned titanium surface with periodical structures of about 20 nm in depth and about 100 nm in diameter was obtained. The diameter of the nanopatterns is in accordance with the sizes of biocompatible nanoporous titanium oxides reported in the literature. When subjected to plastic deformation, these structures retained their shape and integrity compared to the nanoporous oxide-covered surfaces. The results indicate that our unique surface preparation process substantially decreased the cracking and spalling tendency of the surface layer during the implantation of stents. Such a surface morphology in combination with altered surface chemistry and wettability was also beneficial for the adhesion and proliferation of HCAEC. On the other hand, the adhesion and proliferation of HCASMC were suppressed mainly due to the altered surface nano-topography. The rapid endothelialization and suppressing the proliferation of smooth muscle cells are crucial for the performance of vascular stents since they prevent thrombosis and restenosis. Furthermore, the activation of blood platelets on the nanopatterned surface was significantly suppressed after oxygen plasma treatment. This effect indicated the role of additional surface features (chemistry and wettability) induced by oxygen plasma as the nanopatterned surface alone did not show a reduction in the number of adhered platelets. Acknowledgments We acknowledge the work performed by Metka Benčina and Eva Levičnik who helped with in vitro tests and SEM analysis. Author Contributions Conceptualization, C.Y., M.U., I.J., K.K. and M.M.; methodology, C.Y., M.U., N.R. and I.J.; software, C.Y., N.R. and J.K.; validation, M.U. and I.J.; formal analysis, C.Y. and N.R.; investigation, C.Y. and N.R.; resources, M.U. and M.M.; data curation, C.Y. and N.R.; writing—original draft preparation, C.Y. and N.R.; writing—review and editing, M.U., I.J. and M.M.; visualization, C.Y., N.R. and J.K.; supervision, M.U., K.K. and M.M.; project administration, M.U. and M.M.; funding acquisition, M.U. and M.M. All authors have read and agreed to the published version of the manuscript. Funding This study has been realized within the scope of a bilateral project between TUBITAK and ARRS (Slovenian Research Agency), project No. TUBITAK- 216M520. The authors acknowledge the financial support given by TUBITAK and ARRS. We also acknowledge ARRS for P2-0082 (Thin film structures and plasma surface engineering) and Project J3-2533. Institutional Review Board Statement The study was conducted following the Helsinki Declaration and approved by the Ethics Committee of Slovenia (approval number: 56/03/10). Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Surface preparation steps: #1 titanium coating on stainless-steel, #2 anodization of titanium, #3 ultrasonication of nanoporous TiO2, and #4 O2-plasma treatment of cTi. Figure 2 Time dependence of the anodization current. Figure 3 Surface morphology from SEM images of samples after each step: (a) as-deposited (pTi), (b) as-anodized (aTiO2), and (c) as-ultrasonicated (cTi). Figure 4 Surface morphology of nanoporous (aTiO2) and ultrasonicated (cTi) areas from SEM analysis. The sample was tilted at 30°. Figure 5 AFM images of the nanopatterned titanium surface (cTi): (a) 3D image of 1 × 1 µm area, (b) 2D image of 600 × 600 nm area, and (c) line profile taken from the region marked with red line on (b). Figure 6 SEM images of the surface after the three-point bending tests: (a) 45° bending of aTiO2, (b) 90° bending of aTiO2, (c) 45° bending of cTi, and (d) 90° bending of cTi. Figure 7 Wide XPS spectra of cTi before and after oxygen plasma treatment. Figure 8 XPS spectra of Ti2p of cTi before and after oxygen plasma treatment. Figure 9 XPS spectra of (a) F1s and (b) O1s regions of cTi before and after oxygen plasma treatment. Figure 10 XPS depth profile of cTi (a) before and (b) after oxygen plasma treatment (orange and green arrows represent oxide layer thickness before and after the plasma treatment, respectively). Figure 11 Schematic representation of the surface chemistry and morphology of (a) aTiO2, (b) cTi, and (c) cTi+P surfaces. Figure 12 Results of the MTT assay for: (a) HCAEC and (b) HCASMC cell proliferation on pTi, cTi, pTi+P, and cTi+P surfaces. The error bars represents standard error. Symbols * represent a statistically significant change in viability after 3, 24, and 72 h (represents statistical significance at * p < 0.05, ** p < 0.01, and *** p < 0.001 compared with the pTi). Mean values (±SE) for the respective triplicates are presented. Figure 13 Platelets interacting with plain titanium (pTi), plain titanium plasma-treated (pTi+P), nanopatterned Ti surface (cTi), and nanopatterned plasma-treated surface (cTi+P) at different magnifications (left-hand side 2 kX, right-hand side 5 kX). Images were obtained from SEM analysis of samples incubated with whole blood. ijms-23-04595-t001_Table 1 Table 1 WCA values before and after plasma treatment. pTi cTi pTi+P cTi+P 85 ± 3° 80 ± 4° 28 ± 2° 44 ± 3° Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. World Health Organization Global Action Plan for the Prevention and Control of Noncommunicable Diseases 2013–2020 World Health Organization Geneva, Switzerland 2013 2. Santos M. Waterhouse A. Lee B.S.L. Chan A.H.P. Tan R.P. Michael P.L. Filipe E.C. Hung J. Wise S.G. Bilek M.M.M. Simple one-step covalent immobilization of bioactive agents without use of chemicals on plasma-activated low thrombogenic stent coatings Functionalised Cardiovascular Stents Elsevier Amsterdam, The Netherlands 2018 211 228 3. Beshchasna N. Saqib M. Kraskiewicz H. Wasyluk Ł. Kuzmin O. Duta O.C. Ficai D. Ghizdavet Z. Marin A. Ficai A. Recent advances in manufacturing innovative stents Pharmaceutics 2020 12 349 10.3390/pharmaceutics12040349 32294908 4. Walimbe S. Innovations in Cardiovascular Disease Treatment and the Rising Demand for Stents Available online: https://www.dicardiology.com/article/innovations-cardiovascular-disease-treatment-and-rising-demand-stents (accessed on 19 April 2021) 5. Saleh Y.E. Gepreel M.A. Allam N.K. Functional Nanoarchitectures For Enhanced Drug Eluting Stents Sci. Rep. 2017 7 40291 10.1038/srep40291 28079127 6. Zain M. Jamil R. Siddiqui W. Neointimal hyperplasia Curr. Opin. Lipidol. 2019 30 377 382 10.1097/MOL.0000000000000627 31348024 7. Kiramijyan S. Liu M. The benefits of drug-eluting stents in the treatment of coronary artery disease Res. Rep. Clin. Cardiol. 2016 9 9 25 10.2147/RRCC.S54203 8. Sojitra P. Chemical vapor deposition of cardiac stents Functionalised Cardiovascular Stents Elsevier Amsterdam, The Netherlands 2018 149 154 9. Soares J.S. Moore J.E. Biomechanical Challenges to Polymeric Biodegradable Stents Ann. Biomed. Eng. 2016 44 560 579 10.1007/s10439-015-1477-2 26464270 10. Tsujino I. Ako J. Honda Y. Fitzgerald P.J. Drug delivery via nano-, micro and macroporous coronary stent surfaces Expert Opin. Drug Deliv. 2007 4 287 295 10.1517/17425247.4.3.287 17489655 11. Wiemer M. Butz T. Schmidt W. Schmitz K.P. Horstkotte D. Langer C. Scanning electron microscopic analysis of different drug eluting stents after failed implantation: From nearly undamaged to major damaged polymers Catheter. Cardiovasc. Interv. 2010 75 905 911 10.1002/ccd.22347 20088011 12. Cassese S. Byrne R.A. Tada T. Pinieck S. Joner M. Ibrahim T. King L.A. Fusaro M. Laugwitz K.L. Kastrati A. Incidence and predictors of restenosis after coronary stenting in 10,004 patients with surveillance angiography Heart 2014 100 153 159 10.1136/heartjnl-2013-304933 24270744 13. Torii S. Jinnouchi H. Sakamoto A. Kutyna M. Cornelissen A. Kuntz S. Guo L. Mori H. Harari E. Paek K.H. Drug-eluting coronary stents: Insights from preclinical and pathology studies Nat. Rev. Cardiol. 2020 17 37 51 10.1038/s41569-019-0234-x 31346257 14. Borhani S. Hassanajili S. Ahmadi Tafti S.H. Rabbani S. Cardiovascular stents: Overview, evolution, and next generation Prog. Biomater. 2018 7 175 205 10.1007/s40204-018-0097-y 30203125 15. Nuhn H. Blanco C.E. Desai T.A. Nanoengineered Stent Surface to Reduce In-Stent Restenosis In Vivo ACS Appl. Mater. Interfaces 2017 9 19677 19686 10.1021/acsami.7b04626 28574242 16. Rani V.V.D. Manzoor K. Menon D. Selvamurugan N. Nair S.V. The design of novel nanostructures on titanium by solution chemistry for an improved osteoblast response Nanotechnology 2009 20 195101 10.1088/0957-4484/20/19/195101 19420629 17. Choudhary S. Haberstroh K.M. Webster T.J. Enhanced functions of vascular cells on nanostructured Ti for improved stent applications Tissue Eng. 2007 13 1421 1430 10.1089/ten.2006.0376 17518735 18. Das K. Bose S. Bandyopadhyay A. TiO2 nanotubes on Ti: Influence of nanoscale morphology on bone cell-materials interaction J. Biomed. Mater. Res.-Part A 2009 90 225 237 10.1002/jbm.a.32088 18496867 19. Flašker A. Kulkarni M. Mrak-Poljšak K. Junkar I. Čučnik S. Žigon P. Mazare A. Schmuki P. Iglič A. Sodin-Semrl S. Binding of human coronary artery endothelial cells to plasma-treated titanium dioxide nanotubes of different diameters J. Biomed. Mater. Res.-Part A 2016 104 1113 1120 10.1002/jbm.a.35646 20. Kshitiz Afzal J. Kim S.-Y. Kim D.-H. A nanotopography approach for studying the structure-function relationships of cells and tissues Cell Adh. Migr. 2014 9 300 307 10.4161/cam.29359 21. Goriainov V. Hulsart-Billstrom G. Sjostrom T. Dunlop D.G. Su B. Oreffo R.O.C. Harnessing Nanotopography to Enhance Osseointegration of Clinical Orthopedic Titanium Implants—An In Vitro and In Vivo Analysis Front. Bioeng. Biotechnol. 2018 6 44 10.3389/fbioe.2018.00044 29696140 22. Dibra A. Kastrati A. Mehilli J. Pache J. von Oepen R. Dirschinger J. Schömig A. Influence of stent surface topography on the outcomes of patients undergoing coronary stenting: A randomized double-blind controlled trial Catheter. Cardiovasc. Interv. 2005 65 374 380 10.1002/ccd.20400 15926182 23. Mohan C.C. Cherian A.M. Kurup S. Joseph J. Nair M.B. Vijayakumar M. Nair S.V. Menon D. Stable Titania Nanostructures on Stainless Steel Coronary Stent Surface for Enhanced Corrosion Resistance and Endothelialization Adv. Healthc. Mater. 2017 6 1 11 10.1002/adhm.201601353 24. Lorenzetti M. Dogša I. Stošicki T. Stopar D. Kalin M. Kobe S. Novak S. The influence of surface modification on bacterial adhesion to titanium-based substrates ACS Appl. Mater. Interfaces 2015 7 1644 1651 10.1021/am507148n 25543452 25. Jaggessar A. Mathew A. Tesfamichael T. Wang H. Yan C. Yarlagadda P.K.D.V. Bacteria death and osteoblast metabolic activity correlated to hydrothermally synthesised TiO2 surface properties Molecules 2019 24 1201 10.3390/molecules24071201 30934764 26. Jaggessar A. Mathew A. Wang H. Tesfamichael T. Yan C. Yarlagadda P.K. Mechanical, bactericidal and osteogenic behaviours of hydrothermally synthesised TiO2 nanowire arrays J. Mech. Behav. Biomed. Mater. 2018 80 311 319 10.1016/j.jmbbm.2018.02.011 29459290 27. Junkar I. Kulkarni M. Drašler B. Rugelj N. Recek N. Drobne D. Kovač J. Humpolicek P. Iglič A. Mozetič M. Enhanced biocompatibility of TiO 2 surfaces by highly reactive plasma J. Phys. D Appl. Phys. 2016 49 244002 10.1088/0022-3727/49/24/244002 28. Kulkarni M. Mazare A. Gongadze E. Perutkova S. Kralj-Iglic V. Milosev I. Schmuki P. Iglic A. Mozetic M. Titanium nanostructures for biomedical applications Nanotechnology 2015 26 62002 10.1088/0957-4484/26/6/062002 29. Karpagavalli R. Zhou A. Chellamuthu P. Nguyen K. Corrosion behavior and biocompatibility of nanostructured TiO2 film on Ti6Al4V J. Biomed. Mater. Res. Part A 2007 83 1087 1095 10.1002/jbm.a.31447 17584904 30. Nasakina E.O. Baikin A.S. Sergienko K.V. Sevost’yanov M.A. Kolmakov A.G. Goncharenko B.A. Zabolotnyi V.T. Fadeev R.S. Fadeeva I.S. Gudkov S.V. Biocompatibility of nanostructured nitinol with titanium or tantalum surface composite layers formed by magnetron sputtering Dokl. Chem. 2015 461 86 88 10.1134/S0012500815030027 31. Chen F. Lam W.M. Lin C.J. Qiu G.X. Wu Z.H. Luk K.D.K. Lu W.W. Biocompatibility of electrophoretical deposition of nanostructured hydroxyapatite coating on roughen titanium surface: In vitro evaluation using mesenchymal stem cells J. Biomed. Mater. Res.-Part B Appl. Biomater. 2007 82 183 191 10.1002/jbm.b.30720 32. Schettini N. Jaroszeski M.J. West L. Saddow S.E. Hemocompatibility Assessment of 3C-SiC for Cardiovascular Applications Silicon Carbide Biotechnology Elsevier Inc. Amsterdam, The Netherlands 2012 153 208 9780123859068 33. Firkowska-Boden I. Jandt K.D. Helbing C. Dauben T.J. Pieper M. How nanotopography-induced conformational changes of fibrinogen affect platelet adhesion and activation Langmuir 2020 36 11573 11580 10.1021/acs.langmuir.0c02094 32921061 34. Junkar I. Kulkarni M. Benčina M. Kovač J. Mrak-Poljšak K. Lakota K. Sodin-Šemrl S. Mozetič M. Iglič A. Titanium Dioxide Nanotube Arrays for Cardiovascular Stent Applications ACS Omega 2020 5 7280 7289 10.1021/acsomega.9b04118 32280869 35. Vesel A. Junkar I. Cvelbar U. Kovac J. Mozetic M. Surface modification of polyester by oxygen- And nitrogen-plasma treatment Surf. Interface Anal. 2008 40 1444 1453 10.1002/sia.2923 36. Ishizaki T. Saito N. Takai O. Correlation of cell adhesive behaviors on superhydrophobic, superhydrophilic, and micropatterned superhydrophobic/superhydrophilic surfaces to their surface chemistry Langmuir 2010 26 8147 8154 10.1021/la904447c 20131757 37. Ozaltin K. Lehocký M. Kuceková Z. Humpolíček P. Sáha P. A novel multistep method for chondroitin sulphate immobilization and its interaction with fibroblast cells Mater. Sci. Eng. C 2017 70 94 100 10.1016/j.msec.2016.08.065 27770972 38. Kunrath M.F. Vargas A.L.M. Sesterheim P. Teixeira E.R. Hubler R. Extension of hydrophilicity stability by reactive plasma treatment and wet storage on TiO2 nanotube surfaces for biomedical implant applications J. R. Soc. Interface 2020 17 20200650 10.1098/rsif.2020.0650 32993437 39. Benčina M. Iglič A. Mozetič M. Junkar I. Crystallized TiO2 Nanosurfaces in Biomedical Applications Nanomaterials 2020 10 1121 10.3390/nano10061121 40. Griesser H.J. Chatelier R.C. Gengenbach T.R. Johnson G. Steele J.G. Growth of Human Cells on Plasma Polymers: Putative Role of Amine and Amide Groups J. Biomater. Sci. Polym. Ed. 1994 5 531 554 10.1163/156856294X00194 8086382 41. Kollum M. Farb A. Schreiber R. Terfera K. Arab A. Geist A. Haberstroh J.J. Wnendt S. Virmani R. Hehrlein C. Particle debris from a nanoporous stent coating obscures potential antiproliferative effects of tacrolimus-eluting stents in a porcine model of restenosis Catheter. Cardiovasc. Interv. 2005 64 85 90 10.1002/ccd.20213 15619311 42. Wang S. Liu X. Wang L. Wen Q. Du N. Huang J. Formation mechanism and properties of fluoride-phosphate conversion coating on titanium alloy RSC Adv. 2017 7 16078 16086 10.1039/C6RA27199E 43. Biesinger M.C. Lau L.W.M.W. Gerson A.R. StC Smart R. Smart R.S.C. Resolving surface chemical states in XPS analysis of first row transition metals, oxides and hydroxides: Sc, Ti, V, Cu and Zn Appl. Surf. Sci. 2010 257 887 898 10.1016/j.apsusc.2010.07.086 44. Mani G. Feldman M.D. Patel D. Agrawal C.M. Coronary stents: A materials perspective Biomaterials 2007 28 1689 1710 10.1016/j.biomaterials.2006.11.042 17188349 45. Sulka G.D. Nanostructured Anodic Metal Oxides: Synthesis and Applications Elsevier Inc. Amsterdam, The Netherlands 2020 978-0-12-816706-9 46. Yoo H. Kim M. Kim Y.T. Lee K. Choi J. Catalyst-doped anodic TiO2 nanotubes: Binder-free electrodes for (photo)electrochemical reactions Catalysts 2018 8 555 10.3390/catal8110555 47. Goodman S.L. Sheep, pig, and human platelet-material interactions with model cardiovascular biomaterials J. Biomed. Mater. Res. 1999 45 240 250 10.1002/(SICI)1097-4636(19990605)45:3<240::AID-JBM12>3.0.CO;2-C 10397982 48. Lu J. Rao M.P. MacDonald N.C. Khang D. Webster T.J. Improved endothelial cell adhesion and proliferation on patterned titanium surfaces with rationally designed, micrometer to nanometer features Acta Biomater. 2008 4 192 201 10.1016/j.actbio.2007.07.008 17851147 49. Yao C. Slamovich E.B. Webster T.J. Enhanced osteoblast functions on anodized titanium with nanotube-like structures J. Biomed. Mater. Res.-Part A 2008 85 157 166 10.1002/jbm.a.31551 17688267 50. Choudhary S. Berhe M. Haberstroh K.M. Webster T.J. Increased endothelial and vascular smooth muscle cell adhesion on nanostructured titanium and CoCrMo Int. J. Nanomed. 2006 1 41 49 10.2147/nano.2006.1.1.41 51. Llopis-Grimalt M.A. Forteza-Genestra M.A. Alcolea-Rodriguez V. Ramis J.M. Monjo M. Nanostructured titanium for improved endothelial biocompatibility and reduced platelet adhesion in stent applications Coatings 2020 10 907 10.3390/coatings10090907 52. Webster T.J. Ejiofor J.U. Increased osteoblast adhesion on nanophase metals: Ti, Ti6Al4V, and CoCrMo Biomaterials 2004 25 4731 4739 10.1016/j.biomaterials.2003.12.002 15120519 53. Alpaslan E. Ercan B. Webster T.J. Anodized 20 nm diameter nanotubular titanium for improved bladder stent applications Int. J. Nanomed. 2011 6 219 225 10.2147/ijn.s15816 54. Su E.P. Justin D.F. Pratt C.R. Sarin V.K. Nguyen V.S. Oh S. Jin S. Effects of titanium nanotubes on the osseointegration, cell differentiation, mineralisation and antibacterial properties of orthopaedic implant surfaces Bone Jt. J. 2018 100B 9 16 10.1302/0301-620X.100B1.BJJ-2017-0551.R1 55. Wójciak-Stothard B. Curtis A. Monaghan W. Macdonald K. Wilkinson C. Guidance and activation of murine macrophages by nanometric scale topography Exp. Cell Res. 1996 223 426 435 10.1006/excr.1996.0098 8601420 56. De Oliveira P.T. Nanci A. Nanotexturing of titanium-based surfaces upregulates expression of bone sialoprotein and osteopontin by cultured osteogenic cells Biomaterials 2004 25 403 413 10.1016/S0142-9612(03)00539-8 14585688 57. Oh S. Brammer K.S. Li Y.S.J. Teng D. Engler A.J. Chien S. Jin S. Stem cell fate dictated solely by altered nanotube dimension Proc. Natl. Acad. Sci. USA 2009 106 2130 2135 10.1073/pnas.0813200106 19179282 58. Flemming R.G. Murphy C.J. Abrams G.A. Goodman S.L. Nealey P.F. Effects of synthetic micro- and nano-structured surfaces on cell behavior Biomaterials 1999 20 573 588 10.1016/S0142-9612(98)00209-9 10213360 59. Hong J. Andersson J. Ekdahl K.N. Elgue G. Axén N. Larsson R. Nilsson B. Titanium is a highly thrombogenic biomaterial: Possible implications for osteogenesis Thromb. Haemost. 1999 82 58 64 10.1055/s-0037-1614630 10456455 60. Pham M.H. Reseland H.J. Reseland J.E. Fluoride Modification of Titanium Surfaces Enhance Complement Activation Materials 2020 13 684 10.3390/ma13030684 32028745 61. Azar G.T.P. Yelkarasi C. Ürgen M. The role of droplets on the cavitation erosion damage of TiN coatings produced with cathodic arc physical vapor deposition Surf. Coat. Technol. 2017 322 211 217 10.1016/j.surfcoat.2017.05.050 62. Moulder J.F. Stickle W.F. Sobol P.E. Bomben K.D. Handbook of X-Ray Photoelectron Spectroscopy Chastain J. Perkin-Elmer Corporation, Physical Electronics Division Eden Prairie, MN, USA 1995 63. Kulkarni M. Junkar I. Puliyalil H. Iglic A. Wettability Switch of Anodic Titanium Dioxide Nanotubes with Various Diameters Biophys. J. 2016 110 339a 10.1016/j.bpj.2015.11.1823

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==== Front Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells11091416 cells-11-01416 Review Respiratory Viral and Bacterial Exacerbations of COPD—The Role of the Airway Epithelium Love Michelle E. https://orcid.org/0000-0001-9629-6595 Proud David * Simoes Davina C.M. Academic Editor Barreiro Esther Academic Editor Department of Physiology & Pharmacology, Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada; melove@ucalgary.ca * Correspondence: dproud@ucalgary.ca 22 4 2022 5 2022 11 9 141629 3 2022 19 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). COPD is a leading cause of death worldwide, with acute exacerbations being a major contributor to disease morbidity and mortality. Indeed, exacerbations are associated with loss of lung function, and exacerbation frequency predicts poor prognosis. Respiratory infections are important triggers of acute exacerbations of COPD. This review examines the role of bacterial and viral infections, along with co-infections, in the pathogenesis of COPD exacerbations. Because the airway epithelium is the initial site of exposure both to cigarette smoke (or other pollutants) and to inhaled pathogens, we will focus on the role of airway epithelial cell responses in regulating the pathophysiology of exacerbations of COPD. This will include an examination of the interactions of cigarette smoke alone, and in combination with viral and bacterial exposures in modulating epithelial function and inflammatory and host defense pathways in the airways during COPD. Finally, we will briefly examine current and potential medication approaches to treat acute exacerbations of COPD triggered by respiratory infections. airway epithelial cells rhinovirus bacteria innate immunity host defense inflammation ==== Body pmc1. Introduction Chronic obstructive pulmonary disease (COPD) is a multifaceted inflammatory disease of the lungs that is now one of the top three causes of death worldwide, with most deaths occurring in low- and middle-income countries [1,2]. The disease is characterized by chronic inflammation of the airways accompanied by persistent airflow limitation and dyspnea, with mucous hyper secretion, chronic cough and recurrent lower respiratory infections also being common features. While biomass smoke, environmental pollutants, occupational exposures and genetic factors can lead to the development of COPD, cigarette smoke is the leading risk factor in the developed world [1]. COPD manifests as periods of stable chronic symptoms interrupted by periods of acute exacerbations, defined as periods of worsening of symptoms requiring increased medication or hospitalization. Even a single COPD exacerbation can result in a significant increase in the rate of decline in lung function [3]. However, the severity and frequency of COPD exacerbations increases with disease progression [4], and frequent exacerbations are associated with a more rapid decline in lung function, poorer quality of life and increased mortality [5,6,7]. Patients can experience a range of symptoms during exacerbation but the most characteristic are increased dyspnea, increased sputum volume and increased sputum purulence [8]. In addition to their impact on disease outcomes, acute exacerbations of COPD leading to hospitalizations are major drivers of healthcare costs accounting for 50–80% of direct medical costs [9,10]. At the onset of exacerbations 35% of patients report cold-like symptoms [11], and it is clear that exacerbations of COPD are frequently associated with viral and/or bacterial infections [12,13,14,15]. Although the percentage varies in individual studies, it appears that approximately 20–30% of patients with acute exacerbations of COPD have a detectable bacterial infection, 20–50% have a viral infection and approximately 25% have a bacterial viral co-infection [16,17]. The primary viral pathogen detected in patients with exacerbation of COPD is rhinovirus [14], while Haemophilius influenzae is the most commonly observed bacterial pathogen [17,18]. The airway epithelium is the initial site of interactions of pathogens with the airway and is also the primary site of viral replication. As such, it is important to briefly consider the properties of airway epithelial cells that contribute to the maintenance of airway homeostasis and the response to pathogens. In the current article we will review the role of the epithelium in host defense and consider how the properties of the epithelium are modified by cigarette smoke, as well as by viral and bacterial infections. Co-infections will also be reviewed as will the current status of therapies for exacerbations of COPD. In this review we focus on general, broadly applicable concepts and do not focus on specific subgroups of patients. We also focus on common seasonal viruses and do not consider COVID-19 for several reasons. The relationship of the COVID-19 epidemic with exacerbations of COPD is complex and still evolving. Moreover, distinguishing the symptoms of a typical exacerbation from COVID-19 infection is difficult, and it is unclear whether management should target COVID-19 with antiviral agents or focus on typical management of COVID-19 exacerbations. 2. Role of the Epithelium in Host Defense A major function of the airway epithelium is to serve as a barrier to inhaled pathogens. The first line of this defense in the larger airways is mucociliary clearance, by which pathogens are trapped in a viscous surface layer and removed before they can act with surface-binding sites on airway epithelial cells. Mucociliary clearance involves coordinated beating of cilia through a watery periciliary layer to transport particulates and pathogens trapped in the upper mucus gel layer towards the trachea. The mucus layer is comprised of a mixture of aqueous fluid and high-molecular-weight mucin glycoproteins which contain binding sites for pathogens. In humans, MUC5AC and MUC5B are the dominant secreted gel-forming mucins [19,20], while MUC2 is only a minor constituent of the mucous layer [20]. By contrast, MUC1, MUC4 and MUC16, the dominant tethered mucins, remain attached to the epithelial surface, serving as an added layer of protection against penetration by noxious agents [20]. The structural diversity of mucin glycoproteins means they contain carbohydrate moieties that recognize adhesins and hemagglutinins from numerous pathogens including Haemophilius influenzae, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae, and influenza virus [21]. If pathogens penetrate the mucociliary layer, the airway epithelium forms a pseudostratified physical barrier to segregate the luminal contents of the airway from the lamina propria. A number of intercellular junctional complexes including tight junctions, adherens junctions, gap junctions, and desmosomes collectively contribute to maintaining cell polarity and a tight barrier. Epithelial barrier function is primarily controlled by the expression and organization of tight junctions, which are apically expressed intercellular adhesion complexes that selectively regulate the passage of macromolecules, water, and ions [22]. Tight junctions are comprised of three main types of transmembrane proteins: claudins, occludin, and junctional adhesion molecules (JAMs), which are connected to the actin cytoskeleton via junctional plaques that include members of the zonula occludens protein family, which help regulate junctional assembly [23]. In addition to a physical barrier function, epithelial cells express a range of pattern recognition molecules, including Toll-like receptors, NOD-like receptors and mannose-binding lectin, that recognize pathogens and subsequently initiate proinflammatory responses, including the release of chemokines to recruit phagocytes and other cells, as well as host defense responses that include the production of a wide array of antibacterial and antiviral molecules [24]. Peptides and proteins with direct antimicrobial activity include lysozyme, lactoferrin, secretory leukocyte protease inhibitor, members of the β-defensin family of peptides, cathelicidin and surfactant proteins [24]. These peptides and proteins are complemented by proteases and antiproteases, and by reactive oxygen species (ROS) and reactive nitrogen species (RNS). Although macrophages and leukocytes are usually considered to be the major sources of ROS and RNS in the lung, airway epithelial cells express NADPH oxidase, xanthine oxidase and dual oxidases (Duox) 1 and 2, all of which can contribute to ROS production. For example, epithelial cells generate superoxide in response to multiple stimuli, including mechanical strain [25]. In addition, epithelial cells generate hydrogen peroxide mainly via the activity of Duox enzymes. Levels of hydrogen peroxide produced at the airway surface from normal epithelial cells are sufficient to support the generation of bacteriocidal hypothiocyanate, a pathway that is inhibited in cystic fibrosis [26]. The generation of ROS can modify epithelial function by activating transcription factors to increase expression of cytokines, chemokines and adhesion molecules. To help mitigate the effects of excessive ROS generation in the airways, epithelial cells also express several antioxidant pathways. The potential of cigarette smoke to disrupt oxidant–antioxidant balance may be a contributing factor to the pathogenesis of COPD. The major RNS generated by the epithelium is nitric oxide (NO). This is generated from L-arginine, predominantly by the inducible, type 2 isoform (iNOS) of nitric oxide synthase (NOS), which is the major form expressed in the epithelium. It was initially suggested that NO was proinflammatory in the airways because it induces mucus secretion and prostanoid production, modulates ion transport, triggers vasodilation and, under some conditions, enhances vascular permeability. Moreover, it can induce tissue damage via generation of peroxynitrite [27]. On the other hand, NO is bronchodilatory and increases ciliary beat frequency, inhibits vascular permeability at inflammatory sites and inhibits adhesion processes involved in inflammatory cell recruitment [27,28]. NO can also exert antimicrobial and antiviral effects and has been shown to inhibit replication of human rhinovirus [29]. Thus, its role in disease processes is likely complex. There is evidence, however, for increased expression of iNOS and increased nitrositive stress in patients with COPD [30,31]. 3. Cigarette Smoke Impairs Mucociliary Clearance and Barrier Function Although the airway epithelium displays several lines of defense to inhaled pathogens (Figure 1), cigarette smoke can modify many of these epithelial functions. Cigarette smoke-induced injury to the airway epithelium promotes epithelial remodeling and pro-inflammatory signaling, resulting in impaired mucociliary clearance and disrupted barrier function. This creates an environment that is more favorable for microbial growth and persistence in the lungs. Cigarette smoke exposure causes several histological changes in the airway epithelium and associated structures including submucosal gland hypertrophy, goblet cell hyperplasia, reduced club cell numbers and increased inflammatory cell infiltrates [32,33,34,35]. In differentiated air–liquid interface cultures, exposure to cigarette smoke is associated with increased MUC5AC and reduced SCGB1A1 (a club cell marker) positive cells [36,37]. Consistent with these observations, bronchial sections of COPD patients show increased MUC5AC staining in the submucosal glands and epithelial surface compared to healthy controls [38]; moreover, the chronic mucus hypersecretion seen in COPD is associated with increased airflow limitation (FEV1) and risk of hospitalization [39]. Concentrations of MUC5AC have been reported to be a marker of chronic bronchitis [40]. In addition to hypersecretion of mucus and MUC proteins, sputum samples obtained from smokers with normal lung function and COPD patients have a higher viscosity (lower hydration) and percentage of solids compared to healthy controls, leading to impaired mucociliary transport [35]. Cigarette smoke reduces the hydration of airway secretions and alters the viscoelastic properties of mucus by altering the function of ion channels important for fluid balance. Kreindler et al. observed reduced chloride secretion in airway cells exposed to cigarette smoke extract [41], which is consistent with reports that the expression and function of the cystic fibrosis transmembrane conductance regulator (CFTR) are reduced upon cigarette smoke exposure [42]. In addition to the effects of cigarette smoke on ion channels, it has also been reported that nicotine can increase mucus viscosity by inhibiting the postexocytotic hydration of released mucins, likely via electrostatic and hydrophobic interactions [43]. In addition to the effects of cigarette smoking on mucus release and viscosity, smoking also has profound effects on ciliary function. Smoking decreases ciliogenesis [44], and reduces the number of ciliated cells [45,46], an effect that can be inhibited by use of an EGFR tyrosine kinase inhibitor [47]. Smoking is also associated with a shortening of airway cilia length, a phenomenon linked to smoking-induced downregulation of genes associated with intraflagellar transport, a key process in producing cilia of normal length [48,49]. Finally, smoking also reduces ciliary beat frequency [45,50,51]. It would obviously be expected that the combined effects of cigarette smoking on ciliogenesis, ciliary length, ciliary beat frequency, and mucus dehydration would lead to impaired mucociliary clearance. In confirmation of this, a study examining saccharin transit time in the nasal epithelium as a measure of mucociliary clearance found a significant reduction in mucociliary clearance in current smokers with or without COPD compared to patients with COPD who were ex-smokers or to healthy subjects [52]. Excess mucus production and impaired mucociliary clearance would be expected to contribute to the formation of mucus plugs in COPD. Subsequent infection with bacterial and viral pathogens could promote further mucus secretion and inflammatory signaling in the airways that may lead to additional airflow limitation and exacerbations in the COPD airways. As noted above, tight junctions in the airway epithelium play an important role in forming cell–cell contacts and maintaining a physical barrier to pathogens. Cigarette smoke exposure is associated with a reduction in barrier function and changes in junctional protein expression. In agreement with older animal studies where exposure to cigarette smoke led to increased levels of inhaled fluorescein isothiocyanate-dextran appearing in the bloodstream [53], Tatsuta and colleagues demonstrated a dose-dependent increase in the permeability of Calu-3 cell cultures with cigarette smoke extract [54]. Moreover, microarray analysis of bronchial brushings from smokers revealed a global downregulation of genes required for the maintenance of apical junctional complexes [55]. Consistent with this observation, increased permeability of epithelial cultures treated with cigarette smoke is associated with alteration of expression of genes linked to tight junction and adherens junction function [54,56,57,58]. Such losses in barrier function would be expected to enhance the ability of pathogens to penetrate the epithelial layer and may also allow increased passage of inflammatory mediators and fluid. 4. Bacteria and COPD Exacerbations Although the traditional dogma based on standard culture techniques was that the lungs of healthy individuals are sterile, the advent of more sensitive molecular diagnostic techniques has shown this not to be the case. While the bacterial burden is far less than in the gastrointestinal tract, the human respiratory tract nonetheless has a distinct endogenous bacterial profile (microbiome) that can be altered during disease [59]. In healthy individuals, the human lung microbiome is composed primarily of bacteria of the phyla Bacteroides and Firmicutes [59], with Prevotella, Veillonella and Streptococcus representing the predominant genera present. Unlike the gastrointestinal tract, which demonstrates considerable spatial variation in microbial diversity, samples taken from the upper and lower lobes are relatively consistent in microbial community composition [59,60]. However, not surprisingly, taxonomic diversity decreases with increased distance from the oral cavity [59]. Although it may seem intuitively obvious that cigarette smoking would alter the respiratory tract microbiome, the existing data do not fully support this concept. A study examining bronchoalveolar lavages from healthy non-smokers and smokers found no significant differences in the respiratory microbiome of the two groups [61]. Opron and colleagues compared healthy never-smokers to smokers with normal lung function and to patients with either mild-to-moderate COPD or with severe COPD [62]. They were unable to identify any microbiota variations that specifically associated with either current smoking or with COPD. Rather they found that differences in overall bacterial composition in the lung were more strongly linked to measures of airway dysfunction rather than to a diagnosis of COPD. These data may indicate that secondary factors in addition to cigarette smoking are needed before microbiome changes are seen. It may also be that disease severity and associated inflammatory and structural changes in the lung are required to support microbiome changes, as several studies have found microbiome changes in severe COPD compared to controls [63,64,65]. In general, in patients with severe COPD, the microbiome shows lower diversity, with a loss of part of the resident flora and an increase in pathogenic bacterial species [64,65]. Importantly, these changes in the microbiome were associated with changes in expression of multiple host genes [65]. Patients with COPD are frequently colonized with pathogenic bacterial species even when their disease is stable [66,67,68,69]. In several studies, commonly detected bacteria include Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, and Pseudomonas aeruginosa. The burden of such pathogenic bacteria is often associated with increased markers of airway inflammation [67,68,69]. Indeed, Singh and colleagues demonstrated a relationship between bacterial colonization and bacterial load with sputum inflammatory markers. Levels of CXCL8, interleukin 1β and myeloperoxidase were found to be elevated in COPD patients with lower airway bacterial colonization, and total bacterial load was associated with increasing airway inflammation [70]. There is controversy, however, as to whether dysbiosis of the microbiota in stable disease is predictive of exacerbation frequency. Patel and colleagues reported an increased exacerbation frequency associated with colonization by pathogenic bacteria [68], while other studies have found no relationship between baseline microbial patterns and exacerbation frequency [69], or have found that a subset of exacerbations may be associated with baseline microbial dysbiosis [71]. Longitudinal studies have shown that there appears to be a relationship between temporal variations in bacterial profiles and exacerbation frequency [71,72]. There is considerable overlap between the pathogenic bacterial species observed during exacerbations of COPD and those seen during stable disease. Thus, in patients hospitalized with acute exacerbations of COPD, Haemophilus influenzae followed by Pseudomonas aeruginosa, Moroxella catarrhalis, Streptococcus pneumoniae and Staphylycoccus aureus are commonly detected [17,73]. This led to the suggestion that exacerbations may be triggered by increases in the load of chronically colonizing bacteria, but a subsequent study demonstrated that concentrations of pre-existing bacterial strains were not higher during exacerbations [74]. Thus, it has now been established that acquisition of new virulent strains of pathogenic bacteria is strongly associated with occurrence of exacerbations [75,76,77,78]. Indeed, is has been shown that, after depletion of commensal bacteria with moxifloxacin treatment, only acquisition of a new pathogenic bacteria was associated with occurrence of an exacerbation [79]. Both pathogen virulence and interactions with the host immune system help to determine the outcome of the acquisition of a new bacterial strain. It has been shown that genomic differences between strains of nontypeable Haemophilus influenzae partially account for the outcome of an infection with this organism [80]. In addition, strains of Haemophilus influenzae that induce exacerbations show increased adherence to epithelial cells and induce more inflammation, such as production of CXCL8 and recruitment of neutrophils, when compared to chronic colonizing strains [78]. Increases in neutrophils, and in chemokines that recruit and activate these cells are strongly linked to acute exacerbations of COPD [81,82]. Cigarette smoking may be expected to enhance neutrophil recruitment as smoking has also been linked to epithelial production of chemokines, such as CXCL8, that can recruit neutrophils [83,84,85]. These effects may also be exaggerated by the ability of smoking to suppress some aspects of host defense [86]. Antibiotic studies provide further support for the role of bacteria in COPD exacerbations. A systematic review concluded that antibiotics are beneficial in the treatment of exacerbations, particularly in those subjects who produce purulent sputum [87]. The use of prophylactic antibiotics to prevent exacerbations is more controversial. It has been reported that some antibiotics, particularly macrolides, were associated with a reduction in exacerbations [88]. Macrolides have attracted particular attention as they are known to have antiinflammatory and immunomodulatory functions in addition to being antibacterial [89]. Studies using one-year treatment of exacerbation-prone patients with either erythromycin or azithromycin reduced the risk of exacerbations relative to usual care [90,91]. There are no studies, however, going beyond a one-year treatment period, and the benefits seen need to be balanced against the development of microbial resistance and side effects. The factors that underlie bacteria-associated exacerbations of COPD remain incompletely understood. It has recently been shown that glucose levels are increased in sputum samples from patients with COPD relative to healthy subjects [92]. This enriched glucose environment, along with the increased mucus production and reduced mucociliary clearance seen in COPD patients, would be expected to favor bacterial growth and may have the potential to alter the balance of the microbiome in the lungs [59,92]. In support of this concept, Pseudomonas aeruginosa inoculated into sputum obtained from COPD patients was associated with increased growth compared to sputum obtained from controls [92]. It is also likely that cigarette smoking decreases innate lung immune defenses to permit new bacterial infection of the lower airways. This could trigger airway inflammation and further changes to innate immune defense, causing exacerbation of disease and permitting chronic infection. This continuous cycle of infection driving chronic inflammation, acute exacerbations and ultimately progression of the disease has been referred to as the “vicious circle” hypothesis [73]. 5. Viruses and COPD Exacerbations Although bacterial infections have long been associated with COPD exacerbations, it was not until the beginning of this century that the use of molecular diagnostics revealed the association of respiratory viruses with exacerbations of COPD. In 2000, Seemungal and colleagues examined 33 patients with COPD both when stable and during subsequent exacerbations. In this small study, ten of 43 exacerbations were associated with rhinovirus infections [93]. Since that time, numerous studies have confirmed that multiple viruses, including rhinovirus, influenza, parainfluenza, coronavirus, and respiratory syncytial virus (RSV), can be detected during exacerbations of COPD [12,13,14,94,95,96]. In virtually all studies, human rhinoviruses were the predominant virus type associated with exacerbations accounting for approximately 40–60% of viruses detected, depending on the study [14,16,95,96]. This likely reflects the relative prevalence of rhinoviruses in circulation, rather than any unusual pathogenicity of rhinoviruses. Nonetheless, the predominance of rhinovirus during exacerbations has made it a common choice for further study. While detection of viruses during acute exacerbations of COPD confirms an association, it does not establish a causal role in the pathogenesis of exacerbations. To further examine the potential causal relationship between rhinovirus infection and COPD exacerbations, Mallia and colleagues performed experimental rhinovirus infections in patients with mild to moderate COPD [97]. Consistent with a role for viruses in exacerbations, they observed that subjects with COPD developed lower airway symptoms accompanied by airflow obstruction. These subjects also showed increased airway inflammation compared to healthy control subjects [97]. The COPD patients infected with rhinovirus also had an increased viral load, suggesting altered viral handling in COPD. The mechanisms by which rhinovirus can induce exacerbation of COPD, however, are not well understood. The airway epithelium is the primary site of respiratory viral infection and replication. Such infections lead to a modulation of epithelial phenotype, which includes the induction of a wide range of proinflammatory and host response molecules [98]. Production of type I and type III interferons (IFN), and the subsequent induction of multiple interferon-stimulated genes (ISGs) by the airway epithelium, plays a critical role in defense against respiratory viruses [99]. Mallia and colleagues reported that bronchial alveolar lavage cells obtained from COPD patients and infected ex vivo with rhinovirus showed reduced levels of type I and type III IFNs compared to cells from healthy controls [97]. They speculated that reduced production of IFNs may play a role in virus-induced COPD exacerbations. A second study reported a reduction in baseline mRNA expression of IFNβ as well as of IFNλ2/3, but not IFNλ1, in sputum cells from patients who experience frequent exacerbation compared to those who do not, while expression of all IFNs was reduced during virus-associated naturally occurring exacerbations [100]. In further support of this concept, García-Valero et al. reported reduced immunostaining and mRNA levels of IFNβ and interferon regulatory factor-7 (IRF-7) at baseline in COPD patients compared with healthy smokers and never-smokers [101]. The potential role of IFN deficiency is controversial, however, as other studies suggest no impairment of type I and type III IFN responses in COPD. Schneider and colleagues reported that airway epithelial cells isolated from patients with COPD and infected with rhinovirus showed increased rhinovirus replication compared to cells from healthy controls, despite increased interferon IFN-λ1 and IFN-λ2 levels in the COPD samples [102]. Baines and co-workers also observed increased expression of type I and type III IFNs in rhinovirus-infected epithelial cells from COPD patients compared to healthy controls but saw no difference in levels of rhinovirus replication between the two populations [103]. A study of sputum cells from COPD patients and healthy controls also found no differences in type I and type III IFNs between the two populations. In the population as a whole, data on ISGs were inconsistent, although a decrease was observed in the subgroup of patients with the most severe COPD [104]. Our own data also did not show any differences in levels of IFNβ and IFN-λ1, or of the antiviral protein viperin, upon rhinovirus infection of epithelial cells obtained from bronchial brushings from controls, healthy smokers and COPD patients (Figure 2). Interestingly, a recent study has proposed that any differences between COPD and healthy controls may be not due to a deficient airway epithelial IFN response but to one which is delayed, as they observed that maximal IFN production did not occur until significantly later in COPD patients [105]. Although a large number of antiviral genes are often referred to as ISGs because they can be induced by IFNs, these genes can also be induced independently of IFNs. Thus, Schmid and coworkers demonstrated that cells deficient in both type I and type III IFN receptors could still produce ISGs in response to viral infection [106]. Similarly, we have shown that cigarette smoke extract suppresses induction of numerous ISGs including viperin, ISG56 and ISG15 during rhinovirus infection in the absence of any significant changes in expression of type I or type III IFNs [107]. Evidence for a role of other respiratory viruses in exacerbations of COPD is more circumstantial. A review of multiple studies concluded that annual influenza vaccination is associated with reduced exacerbation and hospitalization in COPD [108]. Cigarette smoke exposure has been shown to reduce antiviral host defense in airway epithelial cells and to increase RSV replication [109,110]. RSV infections also exacerbate cigarette smoke-induced COPD in mice [111], and passive smoke exposure increases the severity of RSV induced airway disease in infants [112]. Substantially more work is needed, however, to definitively establish a direct mechanistic link between these viral infections and COPD exacerbations. 6. Viral–Bacterial Co-Infections Viral–bacterial co-infections are detected in approximately 25% of patients hospitalized with exacerbations of COPD, and subjects with such co-infections were found to have more marked impairment of lung function and were hospitalized for longer [16]. It has also been observed that patients with viral–bacterial co-infections had more severe exacerbations and were at greater risk for readmission after their exacerbation [17]. Although it is conceivable that some of these co-infections occur via spontaneous independent viral and bacterial infections, there is clear evidence that viral infections can serve as a trigger for a secondary bacterial infection. Experimental rhinovirus infection of patients with moderate COPD, as well as smokers with normal lung function and healthy non-smokers resulted in secondary bacterial infections in 60% of patients with COPD but in only 9.5% of smokers with normal lung function and 10% of non-smokers [113]. The most common bacterial species observed in COPD patients were Haemophilus influenzae and Streptococcus pneumoniae. It is not clear, however, how many of these secondary bacterial infections represent de novo infections with new bacterial strains, since it has also been shown that experimental rhinovirus infection can lead to outgrowth of the bacterial airway microbiome and an increase in bacterial burden, with Haemophilus influenzae being the primary bacteria showing outgrowth [114]. Such changes in the microbiome were not observed in health individuals after rhinovirus infection. It is unclear what predisposes patients with COPD to secondary bacterial infections, although it has been suggested that observed reductions in levels of the antibacterial peptides secretory leukocyte protease inhibitor (SLPI) and elafin in COPD patients may contribute [113]. However, interactions of rhinovirus and bacteria with the airway epithelium are complex, leading to altered barrier function, as well as to production of proinflammatory cytokines and a host of antimicrobial molecules (Figure 3). Thus, other mechanisms may also contribute to bacterial infection and growth. It has been reported that rhinovirus infection can stimulate release of planktonic bacteria from biofilm and can increase inflammatory chemokine production from epithelial cells of patients with cystic fibrosis [115], but parallel studies have not been performed in cells from COPD patients. Rhinovirus has also been shown to upregulate airway epithelial expression of the bacterial adhesion molecules fibronectin, platelet-activating factor receptor (PAF-r) and carcinoembryonic antigen-related cell adhesion molecule (CEACAM), leading to increased adhesion of bacterial species including Haemophilus influenzae, Staphylococcus aureus, and Streptococcus pneumoniae [116], although it is not known if this occurs to a greater extent in cells from COPD patients. It is also well established that rhinovirus can disrupt epithelial barrier function [117,118,119], and such rhinovirus-induced disruption has been associated with increased paracellular migration of Haemophilus influenzae [117]. Finally, rhinovirus infections may impair some epithelial antibacterial responses to enhance bacterial growth. Infection with rhinovirus has been shown to promote degradation of the signaling molecule interleukin 1 receptor associated kinase 1 (IRAK1), leading to reduced epithelial production of CXCL8 and impaired neutrophil chemotaxis in response to non-typeable Haemophilus influenzae [120]. Once both viruses and bacteria are present in the airway, they can interact to modify epithelial responses relative to those observed with each stimulus individually. It has been shown that rhinovirus and bacteria synergistically induce epithelial production of several molecules, including CCL20, human β-defensin-2 (HBD2) and IL-17C [121,122,123]. These molecules are induced by synergistic effects on several signaling pathways. Interestingly, the antibacterial molecule HBD2 is produced in significantly lower amounts in epithelial cells from patients with COPD compared to those from smokers with normal lung function or from healthy controls [122]. By contrast, IL-17C, which feeds back on epithelial cells to stimulate production of the proinflammatory chemokine CXCL1, inducing neutrophil chemotaxis, is produced in increased amounts in response to virus and bacteria in cells from COPD patients compared to other groups [123]. It is tempting to speculate that this change in the balance to a reduced antimicrobial production but enhanced proinflammatory response in the airways may contribute to the combined effects of viral–bacterial co-infection on symptoms during COPD exacerbations. 7. Current Treatment of COPD Exacerbations The current available pharmacological treatments for exacerbations of COPD have remained largely unchanged for some considerable time and rely on bronchodilators, corticosteroids and, when indicated, antibiotics. Despite the lack of strong evidence from randomized clinical trials, guidelines recommend that short-acting inhaled β2-adrenergic agonists, with or without short-acting anticholinergics be used as initial bronchodilators for treatment of acute exacerbations of COPD [1]. Although there are no clinical studies that have evaluated the use of long-acting bronchodilators during exacerbations, it is recommended that such treatments be continued during exacerbations. In addition, to bronchodilator therapy, the use of oral corticosteroids is recommended as there is evidence that these drugs shorten recovery time, improve oxygenation, improve lung function and shorten hospitalization times [124,125,126,127]. It is recommended, however, that corticosteroid treatment be limited to 5 days to reduce the risk of development of pneumonia that has been observed with longer courses [128]. Although the mechanisms by which corticosteroids increase the risk of pneumonia are unclear, similar increases in risk have also been observed in patients receiving inhaled corticosteroids for significant durations [129,130]. As noted above, the use of antibiotics remains somewhat controversial because exacerbations may be triggered by viral as well as by bacterial infections, but they are considered beneficial in patients with purulent sputum as an indicator of a bacterial infection [87]. A major gap in our arsenal to treat exacerbations of COPD is any effective approach to treat virus-induced exacerbations. It has recently been shown that the monoclonal antibody, nirsevimab, given before the RSV season protected infants from medically attended RSV-associated lower respiratory tract infections [131], but it remains to be seen if this approach will be effective in patients with COPD. Moreover, while influenza vaccination is associated with a reduction in COPD exacerbations and hospitalization rates [108], this approach is not currently applicable to exacerbations triggered by other virus types. For example, no vaccine is available for use against rhinovirus infections. Development of such a vaccine is complicated by the existence of over 160 strains of rhinovirus that fall into three main groups (A, B and C) based on genome sequence homology [132,133]. This broad diversity, together with a lack of specific information on the critical, important immune-protective responses required to reduce symptoms, has led to a failure thus far to develop a vaccine to induce broad protective effects [134]. Similar to the challenges with vaccines, approaches to modulate broad-ranging immune response to rhinovirus infections have been unsuccessful. Although neutralizing antibodies to any given strain of rhinovirus are induced, these are usually highly strain specific [135], although RV-C species can induce some cross-species neutralizing responses [136]. It is also apparent that neutralizing antibodies do not develop until after peak symptoms have already occurred [137], raising concerns about protection during an ongoing exacerbation. Similar issues arise with cell-mediated immunity, which also tends not to develop until after symptoms begin to resolve. Although there is evidence of some shared T-cell epitopes among some species, this is neither consistent nor universal [138]. The delayed immune responses raise some questions about their role in viral clearance, a point also raised by the observation that highly differentiated airway epithelial cells in culture are able to clear rhinovirus infection in the absence of immune cells [139]. The other pharmacological approaches that have been used to try to limit rhinovirus infections have tried to prevent viral binding using either antireceptor antibodies or capsid-binding drugs or to prevent viral replication using drugs that inhibit viral proteases essential for replication [140,141]. Thus far, none of these attempts have led to successful therapies. So, we currently remain without any broad-ranging treatment for virus-induced exacerbations of COPD and additional approaches and further research are still needed. Author Contributions Conceptualization, M.E.L. and D.P.; methodology, M.E.L. and D.P., formal analysis, M.E.L.; resources, D.P.; data curation, M.E.L.; writing—original draft preparation, M.E.L. and D.P., writing—review and editing, M.E.L. and D.P., supervision, D.P., funding acquistion, D.P. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the National Science and Engineering Research Council of Canada (grant number: RGPIN-2018-03861) and the Canadian Institutes of Health Research (grant number: PJT-159635). D.P. is the holder of a Tier 1 Canada Research Chair in Inflammatory Airway Diseases. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Barrier function, mucociliary clearance, and host defenses in the normal airway epithelium. Figure 2 Exposure of bronchial epithelial cells from COPD patients, healthy smokers and non-smokers to rhinovirus-1A lead to similar levels of IFNβ, IFN-λ1 and viperin induction (n = 6). Bronchial epithelial cells were obtained by bronchial brushings. Cells were infected with rhinovirus for 48 h or 72 h. Levels of mRNA were assessed by real-time PCR. Figure 3 Airway epithelial responses to infection with viruses and/or bacteria. Epithelial cells produce intracellular and secreted antivirals and antibacterial products. In addition, chemokines and cytokines can be synergistically produced upon co-infection. There is also increased mucus secretion and a reduction in barrier function. ISGs, interferon-stimulated genes. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Global Initiative for Chronic Obstructive Lung Disease, Report. Global Strategy for Prevention, Diagnosis and Management of COPD: 2022 Report Available online: https://goldcopd.org/2022-gold-reports-2/ (accessed on 28 March 2022) 2. Halpin D.M.G. Celli B.R. Criner G.J. Frith P. López Varela M.V. Salvi S. Vogelmeier C.F. Chen R. Mortimer K. Montes de Oca M. The GOLD summit on chronic obstructive pulmonary disease in low- and middle-income countries Int. J. Tuberc. Lung Dis. 2019 23 1131 1141 10.5588/ijtld.19.0397 31718748 3. Halpin D.M.G. Decramer M. Celli B.R. Mueller A. Metdorf N. Tashkin D.P. Effect of a single exacerbation on decline in lung function in COPD Respir. Med. 2017 128 85 91 10.1016/j.rmed.2017.04.013 28610675 4. Hurst J.R. Vestbo J. Anzueto A. Locantore N. Müllerova H. Tal-Singer R. Miller B. Lomas D.A. Agusti A. MacNee W. Susceptibility to exacerbation in chronic obstructive pulmonary disease N. Engl. J. Med. 2010 363 1128 1138 10.1056/NEJMoa0909883 20843247 5. Donaldson G.C. Seemungal T.A.R. Bhowmik A. Wedzicha J.A. Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease Thorax 2002 57 847 852 10.1136/thorax.57.10.847 12324669 6. Seemungal T.A.R. Donaldson C.G. Paul E.A. Bestall J.C. Jeffries D.J. Wedzicha J.A. Effect of exacerbation on quality of life in patients with chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 1998 157 1418 1422 10.1164/ajrccm.157.5.9709032 9603117 7. Soler-Cataluña J.J. Martinez-Garcia M.A. Román-Sánchez P. Salcedo E. Navarro M. Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease Thorax 2005 60 925 931 10.1136/thx.2005.040527 16055622 8. Donaldson G.C. Wedzicha J.A. COPD exacerbations, 1: Epidemiology Thorax 2006 61 164 168 10.1136/thx.2005.041806 16443707 9. Sullivan S.D. Ramsey S.D. Lee T.A. The economic burden of COPD Chest 2000 117 5S 9S 10.1378/chest.117.2_suppl.5S 10673466 10. Wouters E.F.M. Economic analysis of the Confronting COPD survey: An overview of results Respir. Med. 2003 97 S3 S14 10.1016/S0954-6111(03)80020-3 11. Seemungal T.A. Donaldson G.C. Bhowmik A. Jeffries D.J. Wedzicha J.A. Time course and recovery of exacerbations in patients with chronic obstructive pulmonary disease Am. J. Respir Crit. Care Med. 2000 161 1608 1613 10.1164/ajrccm.161.5.9908022 10806163 12. Cameron R.J. de Wit D. Welsh T.N. Ferguson J. Grissell T.V. Rye P.J. Virus infection in exacerbations of chronic obstructive pulmonary disease requiring ventilation Intensive Care Med. 2006 32 1022 1029 10.1007/s00134-006-0202-x 16791664 13. Bouquet J. Tabor D.E. Silver J.S. Nair V. Tovchigrechko A. Griffin M.P. Esser M.T. Sellman B.R. Jin H. Microbial burden and viral exacerbations in a longitudinal multicenter COPD cohort Respir. Res. 2020 21 77 10.1186/s12931-020-01340-0 32228581 14. Seemungal T. Harper-Owen R. Bhowmik A. Moric I. Sanderson G. Message S. Maccallum P. Meade T.W. Jeffries D.J. Johnston S.L. Respiratory viruses, symptoms and inflammatory markers in acute exacerbations and stable chronic obstructive pulmonary disease Am. J. Respir Crit. Care Med. 2001 164 1618 1623 10.1164/ajrccm.164.9.2105011 11719299 15. Zwaans W.A.R. Mallia P. van Winden M.E.C. Rohde G.G.U. The relevance of respiratory viral infections in the exacerbations of chronic obstructive pulmonary disease-a systematic review J. Clin. Virol. 2014 61 181 188 10.1016/j.jcv.2014.06.025 25066886 16. Papi A. Bellettato C.M. Braccioni F. Romagnoli M. Casolari P. Caramori G. Fabbri L.M. Johnston S.L. Infections and airway inflammation in chronic obstructive pulmonary disease severe exacerbations Am. J. Respir. Crit. Care Med. 2006 173 1114 1121 10.1164/rccm.200506-859OC 16484677 17. Wark P.A.B. Tooze M. Powell H. Parsons K. Viral and bacterial infection in acute asthma and chronic obstructive pulmonary disease increases the risk of readmission Respirology 2013 18 996 1002 10.1111/resp.12099 23600594 18. Wilkinson T.M.A. Hurst J.R. Perera W.R. Wilks M. Donaldson G.C. Wedzicha J.A. Effects of interactions between lower airway bacterial and rhinoviral infection in exacerbations of COPD Chest 2006 129 317 324 10.1378/chest.129.2.317 16478847 19. Fahy J.V. Dickey B.F. Airway mucus function and dysfunction N. Engl. J. Med. 2010 363 2233 2247 10.1056/NEJMra0910061 21121836 20. Lillehoj E.P. Kato K. Lu W. Kim K.C. Cellular and molecular biology of airway mucins Int. Rev. Cell Mol. Biol. 2013 303 139 202 23445810 21. Plotkowski M.C. Bajolet-Laudinet O. Puchelle E. Cellular and molecular mechanisms of bacterial adhesion to respiratory mucosa Eur. Respir. J. 1993 6 903 916 8339812 22. Zihni C. Mills C. Matter K. Balda M.S. Tight junctions: From simple barriers to multifunctional molecular gates Nat. Rev. Mol. Cell. Biol. 2016 17 564 580 10.1038/nrm.2016.80 27353478 23. Umeda K. Ikenouchi J. Katahira-Tayama S. Furuse K. Sasaki H. Nakayama M. Matsui T. Tsukita S. Furuse M. Tsukita S. ZO-1 and ZO-2 independently determine where claudins are polymerized in tight-junction strand formation Cell 2006 126 741 754 10.1016/j.cell.2006.06.043 16923393 24. Proud D. Leigh R. Epithelial cells and airway diseases Immunol. Rev. 2011 242 186 204 10.1111/j.1600-065X.2011.01033.x 21682746 25. Chapman K.E. Sinclair S.E. Zhuang D. Hassid A. Desai L.P. Waters C.M. Cyclic mechanical strain increases reactive oxygen species production in pulmonary epithelial cells Am. J. Physiol. Lung Cell. Mol. Physiol. 2005 289 L834 L841 10.1152/ajplung.00069.2005 15964900 26. Moskwa P. Lorentzen D. Excoffon K.J. Zabner J. McCray P.B. Jr. Nauseef W.M. Dupuy C. Bánfi B. A novel host defense system of airways is defective in cystic fibrosis Am. J. Respir. Crit. Care Med. 2007 175 174 183 10.1164/rccm.200607-1029OC 17082494 27. Bove P.F. van der Vliet A. Nitric oxide and reactive nitrogen species in airway epithelial cell signaling and inflammation Free Radic. Biol. Med. 2006 41 515 527 10.1016/j.freeradbiomed.2006.05.011 16863984 28. Granger D.N. Kubes P. Nitric oxide as an antiinflammatory agent Methods Enzymol. 1996 269 434 442 8791672 29. Sanders S.P. Siekierski E.S. Porter J.D. Richards S.M. Proud D. Nitric oxide inhibits rhinovirus-induced cytokine production and viral replication in a human respiratory epithelial cell line J. Virol. 1998 72 934 942 10.1128/JVI.72.2.934-942.1998 9444985 30. Ichinose M. Sugiura H. Yamagata S. Koarai A. Shirato K. Increase in reactive oxygen species production in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2000 162 701 706 10.1164/ajrccm.162.2.9908132 10934109 31. Ricciardolo F.L.M. Caramori G. Ito K. Capelli A. Brun P. Abatangelo G. Papi A. Chung K.F. Adcock I. Barnes P.J. Nitrosative stress in the bronchial mucosa of severe chronic obstructive pulmonary disease J. Allergy Clin. Immunol. 2005 116 1028 1035 10.1016/j.jaci.2005.06.034 16275371 32. Lumsden A.B. McLean A. Lamb D. Goblet and Clara cells of human distal airways: Evidence of smoking induced changes in their numbers Thorax 1984 39 844 849 10.1136/thx.39.11.844 6505991 33. Saetta M. Turato G. Baraldo S. Zanin A. Braccioni F. Mapp C.E. Maestrelli P. Cavallesco G. Papi A. Fabbri L.M. Goblet cell hyperplasia and epithelial inflammation in peripheral airways of smokers with both symptoms of chronic bronchitis and chronic airflow limitation Am. J. Respir. Crit. Care Med. 2000 161 1016 1021 10.1164/ajrccm.161.3.9907080 10712357 34. Kim V. Jeong S. Zhao H. Kesimer M. Boucher R.C. Wells J.M. Christenson S.A. Han M.K. Dransfield M. Paine R.R. Current smoking with or without chronic bronchitis is independently associated with goblet cell hyperplasia in healthy smokers and COPD subjects Sci. Rep. 2020 10 20133 10.1038/s41598-020-77229-1 33208859 35. Lin V.Y. Kaza N. Birket S.E. Kim H. Edwards L.J. LaFontaine J. Liu L. Mazur M. Byzek S.A. Hanes J. Excess mucus viscosity and airway hydration impact COPD airway clearance Eur. Respir. J. 2020 55 1900419 10.1183/13993003.00419-2019 31672759 36. Haswell L.E. Hewitt K. Thorne D. Richter A. Gaca M.D. Cigarette smoke total particulate matter increases mucous secreting cell numbers in vitro: A potential model of goblet cell hyperpasia Toxicol. In Vitro 2010 24 981 987 10.1016/j.tiv.2009.12.019 20060463 37. Gindele J.A. Kiechle T. Benediktus K. Birk G. Brendel M. Heinemann F. Wohnhaas C.T. LeBlanc M. Zhang H. Strulovici-Barel Y. Intermittent exposure to whole cigarette smoke alters the differentiation of primary small airway epithelial cells in the air-liquid interface culture Sci. Rep. 2020 10 6257 10.1038/s41598-020-63345-5 32277131 38. Caramori G. Casolari P. Di Gregorio C. Saetta M. Baraldo S. Boschetto P. Ito K. Fabbri L.M. Barnes P.J. Adcock I.M. MUC5AC expression is increased in bronchial submucosal glands of stable COPD patients Histopathology 2009 55 321 331 10.1111/j.1365-2559.2009.03377.x 19723147 39. Vestbo J. Prescott E. Lange P. Association of chronic mucus hypersecretion with FEV1 decine and chronic obstructive pulmonary disease morbidity. Copenhagen City Heart Study Group Am. J. Respir. Crit. Care Med. 1996 153 1530 1535 10.1164/ajrccm.153.5.8630597 8630597 40. Kesimer M. Ford A.A. Ceppe A. Radicioni G. Cao R. Davis C.W. Doerschuk C.M. Alexis N.E. Anderson W.H. Henderson A.G. Airway mucin concentration as a marker of chronic bronchitis N. Engl. J. Med. 2017 377 911 922 10.1056/NEJMoa1701632 28877023 41. Kreindler J.L. Jackson A.D. Kemp P.A. Bridges R.J. Danahay H. Inhibition of chloride secretion in human bronchial epithelial cells by cigarette smoke extract Am. J. Physiol. Lung Cell. Mol. Physiol. 2005 288 L894 L902 10.1152/ajplung.00376.2004 15626749 42. Cantin A.M. Hanrahan J.W. Bilodeau G. Ellis L. Dupuis A. Liao J. Zielenski J. Durie P. Cystic fibrosis transmembrane conductance regulator function is suppressed in cigarette smokers Am. J. Respir Crit. Care Med. 2006 173 1139 1144 10.1164/rccm.200508-1330OC 16497995 43. Chen E.Y. Sun A. Chen C.-S. Mintz A.J. Chin W.-C. Nicotine alters mucin rheological properties Am. J. Physiol. Lung Cell. Mol. Physiol. 2014 307 L149 L157 10.1152/ajplung.00396.2012 24838753 44. Tamashiro E. Xiong G. Anselmo-Lima W.T. Kreindler J.L. Palmer J.N. Cohen N.A. Cigarette smoke exposure impairs respiratory epithelial ciliogenesis Am. J. Rhinol. Allergy 2009 23 117 122 10.2500/ajra.2009.23.3280 19401033 45. Simet S.M. Sisson J.H. Pavlik J.A. Devasure J.M. Boyer C. Liu X. Kawasaki S. Sharp J.G. Rennard S.I. Wyatt T.A. Long-term cigarette smoke exposure in a mouse model of ciliated epithelial function Am. J. Respir. Cell Mol. Biol. 2010 43 635 640 10.1165/rcmb.2009-0297OC 20042711 46. Sisson J.H. Papi A. Beckmann J.D. Leise K.L. Wisecarver J. Broderson B.W. Kelling C.L. Spurzem J.R. Rennard S.I. Smoke and viral infection cause cilia loss detectable by bronchoalveolar lavage cytology and dynein ELISA Am. J. Respir. Crit. Care Med. 1994 149 205 213 10.1164/ajrccm.149.1.8111584 8111584 47. Valencia-Gattas M. Connor G.E. Fregien N.L. Gefitinib, an EGFR tyrosine kinase inhibitor, prevents smoke-mediated ciliated airway epithelial cell loss and promoted their recovery PLoS ONE 2016 11 e0160216 10.1371/journal.pone.0160216 27532261 48. Leopold P.L. O’Mahoney M.J. Lian X.J. Tilley A.E. Harvey B.-G. Crystal R.G. Smoking is associated with shortened airway cilia PLoS ONE 2009 4 e8157 10.1371/journal.pone.0008157 20016779 49. Hessel J. Heldrich J. Fuller J. Staudt M.R. Radisch S. Hollmann C. Harvey B.-G. Kaner R.J. Salit J. Yee-Levin J. Intraflagellar transport gene expression associated with short cilia in smoking and COPD PLoS ONE 2014 9 e85453 10.1371/journal.pone.0085453 24465567 50. Agius A.M. Smallman L.A. Pahor A.L. Age, smoking and nasal ciliary beat frequency Clin. Otolaryngol. Allied Sci. 1998 23 227 230 10.1046/j.1365-2273.1998.00141.x 9669071 51. Cohen N.A. Zhang S. Sharp D.B. Tamashiro E. Chen B. Sorscher E.J. Woodworth B.A. Cigarette smoke condensate inhibits transepithelial chloride transport and ciliary beat frequency Laryngoscope 2009 119 2269 2274 10.1002/lary.20223 19418539 52. Ito J.T. Ramos D. Lima F. Rodrigues F.M.M. Gomes P.R. Moreira G.L. Macchione M. Toledo A.C. Ramos E.M.C. Nasal mucociliary clearance in subjects with COPD after smoking cessation Respir. Care 2015 60 399 405 10.4187/respcare.03266 25389352 53. Burns A.R. Hosford S.P. Dunn L.A. Walker D.C. Hogg J.C. Respiratory epithelial permeability after cigarette smoke exposure in guinea pigs J. Appl. Physiol. 1989 66 2109 2116 10.1152/jappl.1989.66.5.2109 2473059 54. Tatsuta M. Kan-O K. Ishii Y. Yamamoto N. Ogawa T. Fukuyama S. Ogawa A. Fujita A. Nakanishi Y. Matsumoto K. Effects of cigarette smoke on barrier function and tight junction proteins in the bronchial epithelium: Protective role of cathelicidin LL-37 Respir. Res. 2019 20 251 10.1186/s12931-019-1226-4 31706310 55. Shaykhiev R. Otaki F. Bonsu P. Dang D.T. Teater M. Stukovici-Barel Y. Salit J. Harvey B.-G. Crystal R.G. Cigarette smoking reprograms apical junctional complex molecular architecture in the human airway epithelium in vivo Cell Mol. Life Sci. 2011 68 877 892 10.1007/s00018-010-0500-x 20820852 56. Heijink I.H. Brandenburg S.M. Postma D.S. van Oosterhout A.J.M. Cigarette smoke impairs airway epithelial barrier function and cell-cell contact recovery Eur. Respir. J. 2012 39 419 428 10.1183/09031936.00193810 21778164 57. Schamberger A.C. Mise N. Genoyer E. Yildirim A.O. Meiners S. Eickelberg O. Cigarette smoke-induced disruption of bronchial epithelial tight junctions is prevented by transforming growth factor-β Am. J. Respir. Cell Mol. Biol. 2014 50 1040 1052 10.1165/rcmb.2013-0090OC 24358952 58. Oldenburger A. Poppinga W.J. Kos F. de Bruin H.G. Rijks W.F. Heijink I.H. Timens W. Meurs H. Maarsingh H. Schmidt M. A-kinase anchoring proteins contribute to loss of E-cadherin and bronchial epithelial barrier by cigarette smoke Am. J. Physiol. Cell Physiol. 2014 306 C585 C597 10.1152/ajpcell.00183.2013 24452374 59. Dickson R.P. Erb-Downward J.R. Martinez F.J. Huffnagle G.B. The microbiome and the respiratory tract Annu Rev. Physiol. 2016 78 481 504 10.1146/annurev-physiol-021115-105238 26527186 60. Feng Z.-H. Li Q. Liu S.-R. Du X.-N. Wang C. Nie X.-H. Wang W. Ying S. Comparison of composition and diversity of bacterial microbiome in human upper and lower respiratory tract Chin. Med. J. 2017 130 1122 1124 10.4103/0366-6999.204934 28469109 61. Morris A. Beck J.M. Schloss P.D. Campbell T.B. Crothers K. Curtis J.L. Flores S.C. Fontenot A.P. Ghedin E. Huang L. Comparison of the respiratory microbiome in healthy nonsmokers and smokers Am. J. Respir. Crit. Care Med. 2013 187 1067 1075 10.1164/rccm.201210-1913OC 23491408 62. Opron K. Begley L.A. Erb-Downward J.R. Freeman C. Madapoosi S. Alexis N.E. Barjaktarevic I. Barr R.G. Bleecker E.R. Bowler R.P. Lung microbiota associations with clinical features of COPD in the SPIROMICS cohort NPJ Biofilms Microbiomes 2021 7 14 10.1038/s41522-021-00185-9 33547327 63. Pragman A.A. Kim H.B. Reilly C.S. Wendt C. Isaacson R.E. The lung microbiome in moderate and severe chronic obstructive pulmonary disease PLoS ONE 2012 7 e47305 10.1371/journal.pone.0047305 23071781 64. Garcia-Nuñez M. Millares L. Pomares X. Ferrari R. Pérez-Brocal V. Gallego M. Espasa M. Moya A. Monsó E. Severity-related changes of bronchial microbiome in chronic obstructive pulmonary disease J. Clin. Microbiol. 2014 52 4217 4223 10.1128/JCM.01967-14 25253795 65. Sze M.A. Dimitriu P.A. Suzuki M. McDonough J.E. Campbell J.D. Brothers J.F. Erb-Downward J.R. Huffnagle G.B. Hayashi S. Elliott W.M. Host response to the lung microbiome in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2015 192 438 445 10.1164/rccm.201502-0223OC 25945594 66. Zalacain R. Sobradillo V. Amilibia J. Barrón J. Achótegui V. Pijoan J.I. Llorente J.L. Predisposing factors to bacterial colonization in chronic obstructive pulmonary disease Eur. Respir. J. 1999 13 343 348 10.1034/j.1399-3003.1999.13b21.x 10065679 67. Hill A.T. Campbell E.J. Hill S.L. Bayley D.L. Stockley R.A. Association between airway bacterial load and markers of airway inflammation in patients with stable chronic bronchitis Am. J. Med. 2000 109 288 295 10.1016/S0002-9343(00)00507-6 10996579 68. Patel I.S. Seemungal T.A.R. Wilks M. Lloyd-Owen S.J. Donaldson G.C. Wedzicha J.A. Relationship between bacterial colonization and the frequency, character and severity of COPD exacerbations Thorax 2002 57 759 764 10.1136/thorax.57.9.759 12200518 69. Wang Z. Maschera B. Lea S. Kolsum U. Michalovich D. Van Horn S. Traini C. Brown J.R. Hessel E.M. Singh D. Airway-host microbiome interactions in chronic obstructive pulmonary disease Respir. Res. 2019 20 113 10.1186/s12931-019-1085-z 31170986 70. Singh R. Mackay A.J. Patel A.R.C. Garcha D.S. Kowlessar B.S. Brill S.E. Donnelly L.E. Barnes P.J. Donaldson G.C. Wedzicha J.A. Inflammatory thresholds and the species-specific effects of colonizing bacteria in stable chronic obstructive pulmonary disease Respir. Res. 2014 15 114 10.1186/s12931-014-0114-1 25218165 71. Wang Z. Singh R. Miller B.E. Tal-SInger R. Van Horn S. Tomsho L. Mackay A. Allinson J.P. Webb A.J. Brookes A.J. Sputum microbiome temporal variability and dysbiosis in chronic obstructive pulmonary disease exacerbations: An analysis of the COPDMAP study Thorax 2018 73 331 338 10.1136/thoraxjnl-2017-210741 29269441 72. Mayhew D. Devos N. Lambert C. Brown J.R. Clarke S.C. Kim V.L. Magid-Slav M. Miller B.E. Ostridge K.K. Patel R. Longitudinal profiling of the lung microbiome in the AERIS study demonstrates repeatability of bacterial and eosinophilic COPD exacerbations Thorax 2018 73 422 430 10.1136/thoraxjnl-2017-210408 29386298 73. Sethi S. Murphy T.F. Infection in the pathogenesis and course of chronic obstructive pulmonary disease N. Engl. J. Med. 2008 359 2355 2365 10.1056/NEJMra0800353 19038881 74. Sethi S. Sethi R. Eschberger K. Lobbins P. Cai X. Grant B.J.B. Murphy T.F. Airway bacterial concentrations and exacerbations of chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2007 176 356 361 10.1164/rccm.200703-417OC 17478618 75. Sethi S. Evans N. Grant B.J. Murphy T.F. New strains of bacteria and exacerbations of chronic obstructive pulmonary disease N. Engl. J. Med. 2002 347 465 471 10.1056/NEJMoa012561 12181400 76. Murphy T.F. Brauer A.L. Grant B.J. Sethi S. Morexella catarrhalis in chronic obstructive pulmonary disease: Burden of disease and immune response Am. J. Respir Crit. Care Med. 2005 172 195 199 10.1164/rccm.200412-1747OC 15805178 77. Murphy T.F. Brauer A.L. Eschberger K. Lobbins P. Grove L. Cai X. Sethi S. Pseudomonas aeruginosa in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2008 177 853 860 10.1164/rccm.200709-1413OC 18202344 78. Chin C.L. Manzel L.J. Lehman E.E. Humlicek A.L. Shi L. Starner T.D. Denning G.M. Murphy T.F. Sethi S. Look D.C. Haemophilus influenzae from patients with chronic obstructive pulmonary disease exacerbation induce more inflammation than colonizers Am. J. Respir. Crit. Care Med. 2005 172 85 91 10.1164/rccm.200412-1687OC 15805181 79. Miravitlles M. Marín A. Monsó E. Vilà S. de la Roza C. Hervás R. Esquinas C. García M. Millares L. Morera J. Efficacy of moxifloxacin in the treatment of bronchial colonization in COPD Eur. Respir. J. 2009 34 1066 1071 10.1183/09031936.00195608 19386683 80. Fernaays M.M. Lesse A.J. Sethi S. Cai X. Murphy T.F. Differential genome contents of nontypeable Haemophilus influenzae strains from adults with chronic obstructive pulmonary disease Infect. Immun. 2006 74 3366 3374 10.1128/IAI.01904-05 16714566 81. Qiu Y. Bandi V. Atmar R.L. Hattotuwa K. Guntupalli K.K. Jeffery P.K. Biopsy neutrophilia, neutrophil chemokine and receptor gene expression in severe exacerbations of chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2003 168 968 975 10.1164/rccm.200208-794OC 12857718 82. Quint J.K. Wedzicha J.A. The neutrophil in chronic obstructive pulmonary disease J. Allergy Clin. Immunol. 2007 119 1065 1071 10.1016/j.jaci.2006.12.640 17270263 83. Mio T. Romberger D.J. Thompson A.B. Robbins R.A. Heires A. Rennard S.I. Cigarette smoke induces interleukin-8 release from human bronchial epithelial cells Am. J. Respir. Crit. Care Med. 1997 155 1770 1776 10.1164/ajrccm.155.5.9154890 9154890 84. Hudy M.H. Traves S.L. Wiehler S. Proud D. Cigarette smoke modulates rhinovirus-induced airway epithelial chemokine production Eur. Respir. J. 2010 35 1256 1263 10.1183/09031936.00128809 19840959 85. Moretto N. Bertolini S. Iadicicco C. Marchini G. Kaur M. Volpi G. Patacchini R. Singh D. Facchinetti F. Cigarette smoke and its component acrolein augment IL-8/CXCL8 mRNA stability via p38 MAPK/MK2 signaling in human pulmonary cells Am. J. Physiol. Lung Cell. Mol. Biol. 2012 303 L929 L938 10.1152/ajplung.00046.2012 86. Herr C. Beisswenger C. Hess C. Kandler K. Suttorp N. Welte T. Schroeder J.M. Vogelmeier C. Bals R. Suppression of pulmonary innate host defence in smokers Thorax 2009 64 144 149 10.1136/thx.2008.102681 18852155 87. Ram F.S.F. Rodriguez-Roisin R. Granados-Navarrete A. Garcia-Aymerich J. Barnes N.C. Antibiotics for exacerbations of chronic obstructive pulmonary disease Cochrane Database Syst. Rev. 2006 2 CD004403 88. Herath S.C. Normansell R. Maisey S. Poole P. Prophylactic antibiotic therapy for chronic obstructive pulmonary disease (COPD) Cochrane Database Syst. Rev. 2018 10 CD009764 10.1002/14651858.CD009764.pub3 30376188 89. Martinez F.J. Curtis J.L. Albert R. Role of macrolide therapy. in chronic obstructive pulmonary disease Int. J. Chron. Obstruct, Pulmon. Dis. 2008 3 331 350 10.2147/COPD.S681 18990961 90. Seemungal T.A.R. Wilkinson T.M.A. Hurst J.R. Perera W.R. Sapsford R.J. Wedzicha J.A. Long-term erythromycin therapy is associated with decreased chronic obstructive pulmonary disease exacerbations Am. J. Respir. Crit. Care Med. 2008 178 1139 1147 10.1164/rccm.200801-145OC 18723437 91. Albert R.K. Connett J. Bailey W.C. Casaburi R. Cooper J.A.D. Criner G.J. Curtis J.L. Dransfield M.T. Han M.K. Lazarus S.C. Azithromycin for prevention of exacerbations of COPD N. Engl. J. Med. 2011 365 689 698 10.1056/NEJMoa1104623 21864166 92. Mallia P. Webber J. Gill S.K. Trujillo-Torralbo M.-B. Calderazzo M.A. Finney L. Bahksoliani E. Farne H. Singanayagam A. Footit J. Role of airway glucose on bacetrial infections in patients with chronic obstructive pulmonary disease J. Allergy Clin. Immunol. 2018 142 815 823.e6 10.1016/j.jaci.2017.10.017 29310905 93. Seemungal T.A.R. Harper-Owen R. Bhowmik A. Jeffries D.J. Wedzicha J.A. Detection of rhinovirus in induced sputum at exacerbation of chronic obstructive pulmonary disease Eur. Respir. J. 2000 16 677 683 10.1034/j.1399-3003.2000.16d19.x 11106212 94. Wedzicha J.A. Role of viruses in exacerbations of chronic obstructive pulmonary disease Proc. Am. Thorac. Soc. 2004 1 115 120 10.1513/pats.2306030 16113423 95. McManus T.E. Marley A.-M. Baxter N. Christie S.N. O’Neill H.J. Elborn J.S. Coyle P.V. Kidney J.C. Respiratory viral infection in exacerbations of COPD Respir. Med. 2008 102 1575 1580 10.1016/j.rmed.2008.06.006 18672353 96. Rohde G. Wiethege A. Borg I. Kauth M. Bauer T.T. Gillissen A. Bufe A. Schultze-Werninghaus G. Respiratory viruses in exacerbations of chronic obstructive pulmonary disease requiring hospitalisation: A case-control study Thorax 2003 58 37 42 10.1136/thorax.58.1.37 12511718 97. Mallia P. Message S.D. Gielen V. Contoli M. Gray K. Kebadze T. Aniscenko J. Laza-Stanca V. Edwards M.R. Slater L. Experimental rhinovirus infection as a human model of chronic obstructive pulmonary disease exacerbation Am. J. Respir. Crit. Care Med. 2011 183 734 742 10.1164/rccm.201006-0833OC 20889904 98. Michi A.N. Love M.E. Proud D. Rhinovirus-induced modulation of epithelial phenotype: Role in asthma Viruses 2020 12 1328 10.3390/v12111328 99. Vareille M. Kieninger E. Edwards M.R. Regamey N. The airway epithelium: Soldier in the fight against respiratory viruses Clin. Microbiol. Rev. 2011 24 210 229 10.1128/CMR.00014-10 21233513 100. Singanayagam A. Loo S.-L. Calderazzo M. Finney L.J. Trujillo Torralbo M.-B. Bakhsoliani E. Girkin J. Veerati P. Pathinayake P.S. Nichol K.S. Antiviral immunity is impaired in COPD patients with frequent exacerbations Am. J. Physiol. Lung Cell. Mol. Physiol. 2019 317 L893 L903 10.1152/ajplung.00253.2019 31513433 101. Garcia-Valero J. Olloquequi J. Montes J.F. Rodríguez E. Martin-Satué M. Texidó L. Sancho J.F. Deficient pulmonary IFN-β expression in COPD patients PLoS ONE 2019 14 e0217803 31170225 102. Schneider D. Ganesan S. Comstock A.T. Meldrum C.A. Mahidhara R. Goldsmith A.M. Curtis J.L. Martinez F.J. Hershenson M.B. Sajjan U.S. Increased cytokine response of rhinovirus-infected airway epithelial cells in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2010 182 332 340 10.1164/rccm.200911-1673OC 20395558 103. Baines K.J. Hsu A.C.-Y. Tooze M. Gunawardhana L.P. Gibson P.G. Wark P.A.B. Novel immune genes associated with excessive inflammatory and antiviral responses to rhinovirus in COPD Respir. Res. 2013 14 15 10.1186/1465-9921-14-15 23384071 104. Hilzendeger C. da Silva J. Henket M. Schleich F. Corhay J.L. Kebadze T. Edwards M.R. Mallia P. Johnston S.L. Louis R. Reduced sputum expression of interferon-stimulated genes in severe COPD Int. J. Chron. Obstruct Pulmon. Dis. 2016 11 1485 1494 10.2147/COPD.S105948 27418822 105. Veerati P.C. Troy N.M. Reid A.T. Li N.F. Nichol K.S. Kaur P. Maltby S. Wark P.A.B. Knight D.A. Bosco A. Airway epithelial cell immunity is delayed during rhinovirus infection in asthma and COPD Front. Immunol. 2020 11 974 10.3389/fimmu.2020.00974 32499788 106. Schmid S. Mordstein M. Kochs G. García-Sastre A. Transcription factor redundancy ensures induction of the antiviral state J. Biol. Chem. 2010 285 42013 42022 10.1074/jbc.M110.165936 20943654 107. Proud D. Hudy M.H. Wiehler S. Zaheer R.S. Amin M.A. Pelikan J.B. Tacon C.E. Tonsaker T.O. Walker B.L. Kooi C. Cigarette smoke modulates expression of human rhinovirus-induced airway epithelial host defense genes PLoS ONE 2012 7 e40762 10.1371/journal.pone.0040762 22808255 108. Beekat-Berkani R. Wilkinson T. Buchy P. Dos Santos G. Stefanidis D. Devaster J.-M. Meyer N. Seasonal influenza vaccination in patients with COPD: A systematic literature review BMC Pulm. Med. 2017 17 79 10.1186/s12890-017-0420-8 28468650 109. Modestou M.A. Manzel L.J. El-Mahdy S. Look D.C. Inhibition of IFN-γ-dependent antiviral airway epithelial defense by cigarette smoke Respir. Res. 2010 11 64 10.1186/1465-9921-11-64 20504369 110. Groskreutz D.J. Monick M.M. Babor E.C. Nyunoya T. Varga S.M. Look D.C. Hunninghake G.W. Cigarette smoke alters respiratory syncytial virus-induced apoptosis and replication Am. J. Respir. Cell Mol. Biol. 2009 41 189 198 10.1165/rcmb.2008-0131OC 19131644 111. Foronjy R.F. Dabo A.J. Taggart C.C. Weldon S. Geraghty P. Respiratory syncytial virus infections enhance cigarette smoke induced COPD in mice PLoS ONE 2014 9 e90567 10.1371/journal.pone.0090567 24587397 112. Maedel C. Kainz K. Frischer T. Reinweber M. Zacharasiewicz A. Increased severity of respiratory syncytial virus airway infection due to passive smoke exposure Pediatr. Pulmonol. 2018 53 1299 1306 10.1002/ppul.24137 30062859 113. Mallia P. Footitt J. Sotero R. Jepson A. Contoli M. Trujillo-Torralbo M.-B. Kebadze T. Aniscenko J. Oleszkiewicz G. Gray K. Rhinovirus infection induces degradation of antimicrobial peptides and secondary bacterial infection in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2012 186 1117 1124 10.1164/rccm.201205-0806OC 23024024 114. Molyneaux P.L. Mallia P. Cox M.J. Footitt J. Wiilis-Owen S.A.G. Homola D. Trujillo-Torralbo M.-B. Elkin S. Kon O.M. Cookson W.O.C. Outgrowth of the bacterial airway microbiome after rhinovirus exacerbation of chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2013 188 1224 1231 10.1164/rccm.201302-0341OC 23992479 115. Chattoraj S.S. Ganesan S. Jones A.M. Helm J.M. Comstock A.T. Bright-Thomas R. LiPuma J.J. Hershenson M.B. Sajjan U.S. Rhinovirus infection liberates planktonic bacteria from biofilm and increases chemokine responses in cystic fibrosis airway epithelial cells Thorax 2011 66 333 339 10.1136/thx.2010.151431 21289024 116. Wang J.H. Kwon H.J. Jang Y.J. Rhinovirus enhances various bacterial adhesions to nasal epithelial cells simultaneously Laryngoscope 2009 119 1406 1411 10.1002/lary.20498 19434681 117. Sajjan U. Wang Q. Zhao Y. Gruenert D.C. Hershenson M.B. Rhinovirus disrupts the barrier function of polarized airway epithelial cells Am. J. Respir. Crit. Care Med. 2008 178 1271 1281 10.1164/rccm.200801-136OC 18787220 118. Looi K. Buckley A.G. Rigby P.J. Garratt L.W. Iosifidis T. Zosky G.R. Larcombe A.N. Lannigan F.J. Ling K.-M. Martinovich K.M. Effects of human rhinovirus on epithelial barrier integrity and function in children with asthma Clin. Exp. Allergy 2018 48 513 524 10.1111/cea.13097 29350877 119. Michi A.N. Yipp B.G. Dufour A. Lopes F. Proud D. PGC-1α mediates a metabolic host defense response in human iarway epithelium during rhinovirus infections Nat. Commun. 2021 12 3669 10.1038/s41467-021-23925-z 34135327 120. Unger B.L. Faris A.N. Ganesan S. Comstock A.T. Hershenson M.B. Sajjan U.S. Rhinovirus attenuates non-typeable Haemophilus influenza-stimulated IL-8 responses via TLR2-dependent degradation of IRAK-1 PLoS Pathog. 2012 8 e1002969 10.1371/journal.ppat.1002969 23055935 121. Maciejewski B.A. Jamieson K.C. Arnason J.W. Kooi C. Wiehler S. Traves S.L. Leigh R. Proud D. Rhinovirus-bacteria coexposure synergistically induces CCL20 production from human bronchial epithelial cells Am. J. Physiol. Lung Cell. Mol. Physiol. 2017 312 L731 L740 10.1152/ajplung.00362.2016 28283475 122. Arnason J.W. Murphy J.C. Kooi C. Wiehler S. Traves S.L. Shelfoon C. Maciejewski B. Dumonceaux C.J. Lewenza W.S. Proud D. Human β-defensin-2 production upon viral and bacterial co-infection is attenuated in COPD PLoS ONE 2017 12 e-175963 10.1371/journal.pone.0175963 28489911 123. Jamieson K.C. Traves S.L. Kooi C. Wiehler S. Dumonceaux C.J. Maciejewski B.A. Arnason J.W. Michi A.N. Leigh R. Proud D. Rhinovirus and bacteria synergistically induce IL-17C release from human airway epithelial cells to promote neutrophil recruitment J. Immunol. 2019 202 160 170 10.4049/jimmunol.1800547 30504421 124. Thompson W.H. Nielson C.P. Carvalho P. Charan N.B. Crowley J.J. Controlled trial of oral prednisone in outparients with acute COPD exacerbations Am. J. Respir. Crit. Care Med. 1996 154 407 412 10.1164/ajrccm.154.2.8756814 8756814 125. Davies L. Angus R.M. Calverley P.M. Oral corticosteroids in patients admitted to hospital with exacerbations of chronic obstructive pulmonary disease: A propsective randomized controlled trial Lancet 1999 354 456 460 10.1016/S0140-6736(98)11326-0 10465169 126. Niewoehner D.E. Erbland M.L. Deupree R.H. Collins D. Gross N.J. Light R.W. Anderson P. Morgan N. Effect of systemic glucocorticoids on exacerbations of chronic obstructive pulmonary disease. Department of Veterans Affairs Cooperative Study Group N. Engl. J. Med. 1999 340 1941 1947 10.1056/NEJM199906243402502 10379017 127. Maltais F. Ostinelli J. Bourbeau J. Tonnal A.B. Jacquemet N. Haddon J. Rouleau M. Boukhana M. Martinot J.B. Duroux P. Comparison of nebulized budesonide and oral prednisone with placebo in the treatment of acute exacerbations of chronic obstructive pulmonary disease: A randomized control trial Am. J. Respir. Crit. Care Med. 2002 165 698 703 10.1164/ajrccm.165.5.2109093 11874817 128. Sivapalan P. Ingebrigtsen T.S. Rasmussen D.B. Sørensen R. Rasmussen C.M. Jensen C.B. Allin K.H. Eklöf J. Seersholm N. Vestbo J. COPD exacerbations: The impact of long versus short courses of oral corticosteroids on mortality and pneumonia: Nationwide data on 67,000 patients with COPD followed for 12 months BMJ Open Respir Res. 2019 6 e000407 10.1136/bmjresp-2019-000407 129. Calverley P.M. Anderson J.A. Celli B. Ferguson G.T. Jenkins C. Jones P.W. Yates J.C. Vestbo J. TORCH Investigators, Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease N. Engl. J. Med. 2007 356 775 789 10.1056/NEJMoa063070 17314337 130. Calverley P.M.A. Tetzlaff K. Vogelmeier C. Fabbri L.M. Magnussen H. Wouters E.F.M. Mezzanotte W. Disse B. Finnigan H. Asijee G. Eosinophilia, frequent exacerbations, and steroid response in chronic obstructive pulmonary disease Am. J. Respir. Crit. Care Med. 2017 196 1219 1221 10.1164/rccm.201612-2525LE 28306321 131. Hammitt L.L. Dagan R. Yuan Y. Cots M.B. Bosheva M. Madhi S.A. Muller W.J. Zar H.J. Brooks D. Grenham A. Nirsevimab for prevention of RSV in healthy late-preterm and term infants N. Engl. J. Med. 2022 386 837 846 10.1056/NEJMoa2110275 35235726 132. Palmenberg A.C. Rathe J.A. Liggett S.B. Analysis of the complete genome sequences of human rhinovirus J. Allergy Clin. Immunol. 2010 125 1190 1199 10.1016/j.jaci.2010.04.010 20471068 133. Royston L. Tapparel C. Rhinoviruses and respiratory enteroviruses: Not as simple as ABC Viruses 2016 8 16 10.3390/v8010016 26761027 134. McLean G.R. Vaccine strategies to induce broadly protective immunity to rhinovirus Hum. Vaccin. Immunother. 2020 16 684 686 10.1080/21645515.2019.1661207 31464554 135. Buscho R.F. Perkins J.C. Knopf H.L. Kapikian A.Z. Chanock R.M. Further characterization of the local respiratory tract antibody response induced by intranasal instillation of inactivated rhinovirus 13 vaccine J. Immunol. 1972 108 169 177 4334548 136. Choi T. Devries M. Bacharier L.B. Busse W. Carmargo C.A.J. Cohen R. Demuri G.P. Evans M.D. Fitzpatrick A.M. Gergen P.J. Enhanced neutralizing antibody responses to rhinovirus C and age-dependent patterns of infection Am. J. Respir. Crit. Care Med. 2021 203 822 830 10.1164/rccm.202010-3753OC 33357024 137. Barclay W.S. al-Nakib W. Higgins P.G. Tyrrell D.A. The time course of the humoral immune response to rhinovirus infection Epidemiol. Infect. 1989 103 659 669 10.1017/S095026880003106X 2558033 138. Gern J.E. Dick E.C. Kelley E.A.B. Vrtis R. Klein B. Rhinovirus-specific T cells recognize both shared and serotype-restricted viral epitopes J. Infect. Dis. 1997 175 1108 1114 10.1086/516449 9129073 139. Warner S.M. Wiehler S. Michi A.N. Proud D. Rhinovirus replication and innate immunity in highly differentiated human airway epithelial cells Respir. Res. 2019 20 150 10.1186/s12931-019-1120-0 31299975 140. Leigh R. Proud D. Virus-induced modulation of lower airway diseases: Pathogenesis and pharmacologic approaches to treatment Pharmacol. Ther. 2015 148 185 198 10.1016/j.pharmthera.2014.12.005 25550230 141. Casanova V. Sousa F.H. Stevens C. Barlow P.G. Antiviral therapeutic approaches for human rhinovirus infections Future Virol. 2018 13 505 518 10.2217/fvl-2018-0016 30245735

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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091747 nutrients-14-01747 Article The Administration of Panax Ginseng Berry Extract Attenuates High-Fat-Diet-Induced Sarcopenic Obesity in C57BL/6 Mice https://orcid.org/0000-0001-9237-4277 Shin Ji-Eun 1 Jeon So-Hyun 2 https://orcid.org/0000-0002-4231-3051 Lee Sang-Jun 3 Choung Se-Young 124* Salucci Sara Academic Editor 1 Department of Life and Nanopharmaceutical Sciences, Graduate School, Kyung Hee University, Seoul 02447, Korea; cindy@khu.ac.kr 2 Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea; yrs02223@daum.net 3 Holistic Bio Co., Seongnam 13494, Korea; leesjun@holistic-bio.com 4 Department of Preventive Pharmacy and Toxicology, College of Pharmacy, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea * Correspondence: sychoung@khu.ac.kr; Tel.: +82-2-961-9198; Fax: +82-2-961-0372 22 4 2022 5 2022 14 9 174720 2 2022 20 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Sarcopenia and obesity are serious health problems that are highly related to several metabolic diseases. Sarcopenic obesity, a combined state of sarcopenia and obesity, results in higher risks of metabolic diseases and even mortality than sarcopenia or obesity alone. Therefore, the development of therapeutic agents for sarcopenic obesity is crucial. C57BL/6 mice were fed with a high-fat diet (HFD) for 9 weeks. Then, mice were administered with Panax ginseng berry extract (GBE) for an additional 4 weeks, with continuous HFD intake. GBE significantly decreased the food efficiency ratio, serum lipid and insulin levels, adipose tissue weights, and adipocyte size. It significantly increased the grip strength, muscle masses, and myofiber cross-sectional area. It deactivated the protein kinase C (PKC) theta and zeta, resulting in activation of the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) pathway, which is known to regulate muscle synthesis and degradation. Furthermore, it inhibited the production of inflammatory cytokines in the muscle tissue. GBE attenuated both obesity and sarcopenia. Thus, GBE is a potential agent to prevent or treat sarcopenic obesity. ginseng berry extract sarcopenic obesity PI3K/Akt pathway protein synthesis degradation inflammation ==== Body pmc1. Introduction Sarcopenia, a decline in skeletal muscle mass and strength, is an important health problem, prevalent in elderly people [1]. Obesity is also a crucial health concern worldwide, and its prevalence has been continuously increasing [2]. Both obesity and sarcopenia are highly associated with metabolic disorders, disability, and even mortality [3]. Sarcopenic obesity, the combined state of sarcopenia and obesity, leads to higher risks of metabolic diseases, disability, and mortality rates than either sarcopenia or obesity alone [4]. However, the research on the molecular mechanism and therapeutic strategies of sarcopenic obesity are still lacking [5]. Therefore, the development of therapeutics or preventive medicine for sarcopenic obesity is necessary. The molecular mechanism of sarcopenic obesity is not well understood. In this study, we investigated how the obese state induces sarcopenia. The increased inflow of fatty acid due to the obese state accumulates intramyocellular lipids in muscle tissue [6,7]. These lipids consist of diacylglycerol (DAG), ceramides, triacylglycerol, etc. Increased DAG content activates protein kinase C theta (PKCθ), predominantly expressed in skeletal muscle [8,9]. PKCθ induces serine phosphorylation of insulin receptor substrate-1 (IRS1), resulting in the impairment of insulin signaling. Increased ceramide content activates protein kinase C zeta (PKCζ) and deactivates protein kinase B (Akt), involved in insulin signaling [10,11]. Among the insulin signaling pathways, the phosphoinositide 3-kinase (PI3K)/Akt pathway is known to regulate muscle protein synthesis and degradation [12,13]. Deactivation of the PI3K/Akt pathway inhibits protein synthesis and promotes protein degradation. It causes an imbalance in muscle mass maintenance and induces muscle loss. Further, the accumulation of intramyocellular lipids induces the secretion of inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β [14,15]. It induces low-level inflammation in the muscle tissue, resulting in a continuous muscle atrophic state. Taken together, increased fatty acid uptake and intramyocellular lipid accumulation in muscle tissue deactivate the PI3K/Akt pathway and induce low-level inflammation, resulting in muscle loss and, ultimately, sarcopenic obesity. The root of Panax ginseng has long been used as an herbal medicine in Asian counties. It has various pharmacological effects, such as anticancer, antidiabetic, anti-obesity, and anti-inflammation [16,17,18,19]. Its major active components are ginsenosides [20,21,22], and ginsenosides can be obtained from different parts of the plant. Several studies showed that Panax ginseng berry extract (GBE) has higher ginsenoside contents and a distinctive ginsenoside profile compared to Panax ginseng extract [23,24,25]. Therefore, GBE might have higher pharmacological effects than its root against several diseases, but the studies about GBE are insufficient. GBE has shown antidiabetic and anti-obesity effects in several studies [26,27,28,29]. However, the effect of GBE on muscle or sarcopenia has not been reported before. Since insulin resistance is highly associated with the cause of sarcopenic obesity and GBE has been reported to have anti-obesity effects, we thought that GBE might have a therapeutic effect on sarcopenic obesity. Therefore, in this study, we investigated the effect of GBE on sarcopenic obesity and aimed to determine its effect on the muscle that is damaged by the obese state. 2. Materials and Methods 2.1. Preparation of Panax Ginseng Berry Extract (GBE) and UHPLC-ESI-MS/MS Analysis of GBE Freshly harvested 4-year-old Korean ginseng berries (Panax ginseng Meyer) cultivated in the Gangwon-do province of South Korea were used. After fresh ginseng berries were water washed, the seeds were removed, and the remainder (pulp and juice) was collected. The remainder was then extracted with 5-times more water than the amount of the remainder at 80 ± 5 °C for 5 h. The extract was filtered and evaporated under a vacuum at 60 °C and spray dried to obtain standardized GBE powder. The production yield of GBE was about 2.5% and the GBE was standardized to contain 5% of the index component, ginsenoside Re. The concentration of seven major ginsenosides in GBE was analyzed by HPLC. Total ginsenoside concentrations (% w/w) were 15.19%. Individual ginsenoside concentrations were 0.45%, 0.90%, 1.11%, 0.75%, 6.06%, 1.16%, and 0.53% for the ginsenosides Rb1, Rb2, Rc, Rd, Re, Rg1, and Rg2, respectively (described in Supplementary Material, Figure S1). 2.2. Animals and Experimental Design Five-week-old male C57BL/6 mice were purchased from Raon bio. (Yongin, Korea) and housed in a standard animal facility maintained on 12 h:12 h light-dark cycle at 25 ± 1 °C. Mice freely accessed food and water. The animal experiment protocol was approved by the Institutional Animal Care and Use Committee guidelines of Kyung Hee University and the approval number was KHUASP(SE)-19-252. After acclimation, mice were randomly divided into a normal group (n = 8) which was fed with a low-fat diet containing 10% kcal fat (D12450B, Research Diets Inc., New Brunswick, NJ, USA) and CMC (Carboxymethyl cellulose) or a high-fat diet (HFD) feeding group (n = 32) which was fed with a high-fat diet containing 60% kcal fat (D12492, Research Diets Inc., New Brunswick, NJ, USA). The composition of low- and high-fat diets was shown in Supplementary Table S1. After HFD feeding for 9 weeks, the HFD feeding group was randomly divided into four groups as follows (n = 8); HFD: mice fed with a high-fat diet and administered CMC; GBE 50: mice fed with a high-fat diet and administered with GBE (50 mg/kg); GBE 100: mice fed with a high-fat diet and administered with GBE (100 mg/kg); GBE 200: mice fed with a high-fat diet and administered with GBE (200 mg/kg); GBE was dissolved in CMC according to the dose of each administration group. Oral administration was performed for 4 weeks. The body weight, food intake, and water intake were measured twice a week throughout the study period. 2.3. Measurement of Grip Strength Grip strength was measured twice a week during an animal experiment using a grip strength test (Bioseb, Chaville, France). Mice were lifted by the tail and placed on the grid connected with the grip-strength test. After the mice held the grid, we pulled them horizontally until the grip was broken. The maximum force of grip was measured and we used the average of five measurements for analysis. The grip strength was normalized to bodyweight [30]. 2.4. Biochemical Analysis of Serum Lipid and Insulin Levels At the end of the experiment, mice were anesthetized with isoflurane gas, and blood samples were collected from the inferior vena cava. The blood samples were incubated at room temperature for 30 min and then centrifuged at 3000 rpm for 15 min at 4 °C to obtain serum. Levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and triglyceride (TG) were measured using commercial kits purchased from Asan Diagnostics (Seoul, Korea). The low-density lipoprotein cholesterol (LDL-c) level was calculated using Friedewald formula: TC level—HDL-c level—TG level/5. Serum insulin level was analyzed using a commercial kit purchased from the Morinaga Institute of Biological Science (Yokohama, Japan). The serum lipid and insulin levels were measured following the manufacturer’s instructions. 2.5. Histological Analysis of Muscle Cross-Sectional Area (CSA) and Adipocyte Size After sacrifice, the gastrocnemius and epididymal fat were obtained. They were fixed with 4% paraformaldehyde and sliced into 4 μm-thick paraffin-embedded sections. Then, the sections were stained with hematoxylin and eosin (H&E) for 13 h. Stained sections were visualized using an optical microscope (Olympus, Tokyo, Japan). Ten muscle fibers and adipocyte were measured from each image, and the average value was used for quantification using image J software (64-bit Java 1.8.0_172) (n = 10/mice, six mice were measured in each group). 2.6. Quantitative Real Time-PCR (qRT-PCR) Assay Thirty milligrams of quadriceps were homogenized with a liquid nitrogen. A total RNA was extracted using easy-RED™ (iNtRON, Seongnam, Korea) according to the manufacturer’s protocol. Then cDNA was synthesized from the extracted RNA using a PrimeScript™ 1st strand cDNA Synthesis Kit (TaKaRa, Tokyo, Japan). qRT-PCR was performed using a Step One Plus™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) with TB Green™ Premix Ex Taq™ (TaKaRa, Tokyo, Japan). The mRNA levels were normalized to the Gapdh and calculated using the comparative method (2−ΔΔCt). 2.7. Western Blot Assay Fifty milligrams of gastrocnemius was homogenized with liquid nitrogen and lysed using a lysis buffer containing cOmplete™ Protease Inhibitor Cocktail and PhosSTOP™ (Roche Diagnostics, Indianapolis, IN, USA). Then the lysates were centrifuged (13,000 rpm, 15 min, 4 °C), and the supernatants were collected. The protein concentrations were measured using a Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific, Rockford, IL, USA). The same amount of protein was loaded on a 12% or 15% polyacrylamide gel and was transferred to a polyvinylidene fluoride membrane. The primary antibodies used purchased as follows, and diluted as 1:1000 with BSA in TBST. The primary antibodies used purchased as follows, and diluted as 1:1000 with BSA: Cell Signalling (Danvers, MA, USA) (p-IRS1 (#2385), IRS1 (#2382), p-PKCζ (#2060), PKC (#9368), p-PI3K (#4228), p-Mtor (#2971), mTOR (#2972), p-Akt (#9271), Akt (#9272), p-S6K1 (#9205), S6K1 (#9202), p-4E-BP1 (#2855), 4E-BP1 (#9452), p-FoxO3a (#9465), and FoxO3a (#12829)), Abcam (Cambridge, UK) (PI3K (ab191606)), Santa Cruz Biotechnology (Santa Cruz, CA, USA) (p-PKCθ (sc-271920), PKCθ (sc-1680), Atrogin-1 (sc-166806) and MurF1 (sc-398608)), and GeneTex (Irvine, CA, USA) (β-actin (GT5512)). The next day, it was incubated with a horseradish peroxidase-conjugated secondary antibody (GeneTex, Irvine, CA, USA) for 100 min. The secondary antibodies were diluted from 1:600 to 1: 2000 with 5% skim milk in TBST. Then it was visualized using a LAS3000 luminescent image analyzer (Fuji Film, Tokyo, Japan). The protein expression level was analyzed using the Image J software (National Institute of Health, Bethesda, MD, USA) and normalized to the β-actin. 2.8. Statistical Analysis The results were expressed as the mean ± SD. The Shapiro–Wilk normality test was conducted to verify the normality of the data. The normally distributed data were analyzed using one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance was determined by SPSS version 25 statistical software (Chicago, IL, USA) and it was expressed as follows: # p < 0.05, ## p < 0.01, and ### p < 0.001 compared to the normal group. * p < 0.05, ** p < 0.01, and *** p < 0.001 compared to the HFD group. 3. Results 3.1. GBE Administration Significantly Decreased Food Efficiency Ratio and Increased Grip Strength At the beginning of the experiment, the body weights of the normal and HFD group were similar. After two weeks of LFD or HFD intake, the body weight in the HFD feeding group was significantly increased compared to the normal group. After nine weeks, the HFD feeding group was divided into HFD, GBE 50, GBE 100, and GBE 200 groups. The body weight did not show significant differences as a result of GBE administration (Figure 1A). To investigate the effect of GBE administration, we measured the food efficiency ratio (FER). FER was calculated using the equation: (The final body weight—the initial body weight (g)/food intake (g) × 100). The initial and final body weight are shown in Supplementary Table S2 and old people and water intake are shown in Supplementary Figure S2. The FER was significantly increased in the HFD group compared to the normal group, and it was significantly decreased in the GBE 200 group compared to the HFD group (Figure 1B). The grip strength was significantly decreased in the HFD feeding group compared to the normal group, after three weeks of HFD intake. At the end of the experiment, the grip strength in the GBE 200 group significantly increased compared to the HFD group (Figure 1C). 3.2. GBE Administration Significantly Increased Muscle Mass and Decreased Adipose Tissue Weights After sacrifice, muscle and adipose tissues were collected and weighed. The muscle tissue weights (quadriceps, gastrocnemius, and soleus) were significantly decreased by HFD feeding and were significantly increased by GBE administration, in a dose-dependent manner (Figure 2A–C). The adipose tissue weights (epididymal, mesenteric, and perirenal fat) were significantly increased by HFD intake and were significantly decreased by GBE treatment, in a dose-dependent manner (Figure 2D–G). 3.3. GBE Administration Significantly Decreased Serum Lipid and Insulin Levels The serum TC level was significantly increased in the HFD group compared to the normal group and significantly decreased in the GBE 200 group compared to the HFD group. The HDL-c level in the serum showed no significant differences between groups. However, the HDL-c/TC ratio was significantly decreased in the HFD group compared to the normal group, and it was significantly increased by GBE administration, in a dose-dependent manner. The LDL-c level was significantly increased in the HFD group compared to the normal group and was significantly decreased in the GBE 200 group compared to the HFD group. The serum TG level was significantly increased in the HFD group compared to the normal group and significantly decreased in the GBE 200 group compared to the HFD group. The blood insulin level was significantly increased in the HFD group compared to the normal group and was significantly decreased in the GBE 200 group compared to the HFD group (Table 1). 3.4. GBE Administration Significantly Decreased Adipocyte Size and Significantly Increased Myofiber Cross-Sectional Area (CSA) The adipocyte size of epididymal fat and myofiber CSA of gastrocnemius were measured using captured images of H&E-stained sections. The mean adipocyte size was significantly increased in the HFD group compared to the normal group. It was significantly decreased in the GBE 100 and GBE 200 group compared to the HFD group (Figure 3A,B). The adipocyte size distribution graph showed an increase in adipocyte size from HFD feeding and a decrease from GBE treatment (Figure 3C). The average CSA was significantly lower in the HFD group than the normal group. It was significantly increased in the GBE 100 and GBE 200 group compared to the HFD group (Figure 4A,B). The CSA distribution of each myofiber in the HFD group was decreased compared to the normal group. The GBE treatment enlarged it in a dose-dependent manner (Figure 4C). 3.5. GBE Administration Up-Regulated the PI3K/Akt Pathway through Inactivation of PKCθ and PKCζ Increased lipid accumulation in muscle tissue due to HFD intake activates PKCθ and PKCζ. PKCθ and PKCζ down-regulate the PI3K/Akt pathway, which is known to regulate protein synthesis and degradation. The phosphorylation ratios of PKCθ, PKCζ, and IRS1 were significantly decreased in the HFD group compared to the normal group and significantly increased in the GBE 200 group compared to the HFD group. The phosphorylation ratios of PI3K and Akt were significantly decreased by HFD feeding and significantly increased by GBE 200mg/kg administration (Figure 5A). The activation of PI3K and Akt lead to significant increases in the phosphorylation ratios of the mammalian target of rapamycin (mTOR), ribosomal protein S6 kinase beta-1 (S6K1), and eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), which are known to activate protein synthesis. The phosphorylation ratio of forkhead box protein O3 (FoxO3a) was also significantly increased by GBE 200mg/kg administration, resulting in significant decreases in muscle atrophy F-box protein (Atrogin1) and muscle ring finger-1 (MuRF1) expression levels, known to induce protein degradation (Figure 5B). 3.6. GBE Administration Down-Regulated the Expression Levels of Inflammatory Cytokines To investigate the effect of GBE administration on inflammation, we measured the inflammatory cytokine expression levels. TNF-α, IL-6, and IL-1β mRNA levels were significantly increased by HFD feeding and decreased by GBE 200mg/kg administration (Figure 6). 4. Discussion Continuous HFD intake significantly increases body weight, adipose tissue weights, and adipose sizes [31,32], and decreases grip strength, muscle mass, and myofiber CSA [33,34]. In our study, those changes were similarly shown; thus, we confirmed the onset of sarcopenic obesity due to HFD consumption. GBE showed an attenuating effect on both sarcopenia and obesity. GBE administration significantly increased the grip strength, muscle mass, and myofiber CSA. It also significantly decreased the serum lipid levels, adipose tissue weights, and adipocyte size. Interestingly, the body weight showed no significant changes as a result of GBE administration. Considering changes in muscle mass and fat weight, it seems that muscle mass increased as the amount of fat decreased. GBE was previously studied for its anti-diabetic effect [26,27,28]. It lowered the serum insulin levels and insulin resistance scores (HOMA-IR). When we measured the blood insulin level in our study, it was significantly decreased by GBE administration. Among insulin signaling, the PI3K/Akt pathway is highly associated with the cause of sarcopenia [13,35]. In previous studies, ginsenoside Re reversed insulin resistance through regulating IRS1 and IRS1-bound PI3K [36], and ginsenoside Rg1 attenuated starvation-induced muscle degradation through regulating the Akt/FoxO signaling pathway [37]. Since ginsenoside Re and Rg1 are the major components of GBE, we thought that GBE might affect the PI3K/Akt pathway. Therefore, we investigated the changes in the PI3K/Akt pathway and its association with obesity. The continuous intake of a 6% HFD caused lipid accumulation in muscle tissue and it activated PKCθ and PKCζ [6]. Activated PKCθ and PKCζ deactivates IRS1 and Akt, respectively [7], resulting in deactivation of the PI3K/Akt pathway, which regulates protein synthesis and degradation [38]. GBE administration inactivated PKCθ and PKCζ and, thus, activated IRS1, PI3K, and Akt. When PI3K activates Akt, Akt phosphorylates mTOR and FoxO3a [39,40]. Activated mTOR phosphorylates S6K1 and 4E-BP1, which induce protein synthesis by promoting ribosomal protein S6 and releasing the translation initiation factor eIF4E. GBE administration increased the phosphorylation ratios of mTOR, S6K1, and 4E-BP1. FoxO3a, a transcription factor of two E3 ubiquitin ligases (Atrogin1 and MurF1), is deactivated by phosphorylation [41]. Atrogin1 and MurF1 promote protein degradation through the ubiquitin-proteasome system. Further, increased adipose tissue surrounding the muscle enhances FoxO and up-regulates Atrogin1 and MurF1 [42]. GBE administration deactivated FoxO3a and, thus, decreased Atrogin1 and MurF1 expression levels. In summary, GBE attenuated sarcopenic obesity through deactivation of PKCθ and PKCζ and activation of the PI3K/Akt pathway. It promoted protein synthesis by activating mTOR and inhibited protein degradation by deactivating FoxO3a. Obesity is a state of chronic inflammation with increased inflammatory cytokine levels in the blood [43]. It affects the muscle tissue and increases the production of inflammatory cytokines in the muscle tissue [44]. When we measured the inflammatory cytokine levels in muscle tissue, HFD intake significantly increased expression levels but GBE administration dose-dependently decreased expression levels. Therefore, GBE administration attenuated sarcopenic obesity by reducing inflammatory cytokine levels. 5. Conclusions Panax ginseng berry extract attenuates sarcopenic obesity. GBE increased muscle-function-related factors: grip strength, muscle mass, and muscle fiber CSA. It also decreased obesity-related factors: body weight, fat mass, and adipocyte CSA. These results are possible due to two main pathways. First, recovered protein synthesis and degradation imbalance by activating the PI3K/Akt pathway in skeletal muscle. Second, recovered serum lipid and insulin level. In addition, it inhibits the production of inflammatory cytokines in the muscle tissue. Collectively, GBE could be used as an effective natural treatment for sarcopenic obesity. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/nu14091747/s1, Supplementary Figure S1. UHPLC-ESI-MS/MS profile of GBE, Supplementary Figure S2. (A) The daily water intake and (B) the food intake per animal, Supplementary Table S1. The composition of low- and high-fat diets, Supplementary Table S2. Initial and final body weight. Click here for additional data file. Author Contributions Conceptualization, S.-J.L.; Investigation, J.-E.S.; Project administration, S.-Y.C.; Writing—original draft, J.-E.S., S.-H.J.; Writing—review & editing, S.-Y.C. All authors have read and agreed to the published version of the manuscript. Funding This research has no support or funding. Institutional Review Board Statement This research was approved by the Animal studies committee of Kyung Hee University (approval number: KHUASP(SE)-19-252). Informed Consent Statement Not applicable. Data Availability Statement Data is contained within the article and the Supplementary Materials. Conflicts of Interest The authors declare no conflict of interest. Figure 1 GBE administration significantly decreased food efficiency ratio and increased grip strength. (A) The body weight (g) during an animal experiment. (B) The food efficiency ratio (FER, %). (C) The grip strength (g/g) during an animal experiment. It was expressed as a ratio of grip strength to body weight. Data are expressed as mean ± SD. ## p < 0.01 and ### p < 0.001 versus the normal group. * p < 0.05 versus the HFD group. Figure 2 GBE administration significantly increased muscle mass and decreased adipose tissue weights. The muscle mass: (A) quadriceps, (B) gastrocnemius, and (C) soleus. They were expressed as a ratio of muscle tissue weight to body weight (mg/g). The adipose tissue weights: (D) epididymal fat, (E) mesenteric fat, (F) perirenal fat, and (G) total white fat. The total white fat was calculated, adding the three fat weights. They were shown as a ratio of fat weight to body weight (mg/g). Data are expressed as mean ± SD. ### p < 0.001 versus the normal group. * p < 0.05, ** p < 0.01, and *** p < 0.001 versus the HFD group. Figure 3 GBE administration significantly decreased adipocyte size. (A) H&E staining of epididymal fat. (B) The mean adipocyte size of epididymal fat. (C) The distribution graph of adipocyte size. Data are expressed as mean ± SD. ### p < 0.001 versus the normal group. ** p < 0.01 versus the HFD group. Figure 4 GBE administration significantly decreased significantly increased myofiber cross-sectional area (CSA). (A) H&E staining of gastrocnemius. (B) The mean adipocyte size of epididymal fat. (C) The distribution graph of adipocyte size. Data are expressed as mean ± SD. ### p < 0.001 versus the normal group. ** p < 0.01 and *** p < 0.001 versus the HFD group. Figure 5 GBE administration up-regulated the PI3K/Akt pathway through inactivation of PKCθ and PKCζ. (A) The changes in upstream factors of PI3K/Akt pathway. (B) The changes in downstream factors of PI3K/Akt pathway. The protein expression levels were normalized to the β-actin level. Data are expressed as mean ± SD. # p < 0.05, ## p < 0.01 and ### p < 0.001 versus the normal group. * p < 0.05, ** p < 0.01, and *** p < 0.001 versus the HFD group. Figure 6 GBE administration down-regulated the expression levels of inflammatory cytokines. The mRNA expression levels were normalized to the gapdh level. Data are expressed as mean ± SD. ## p < 0.01, and ### p < 0.001 versus the normal group. * p < 0.05, ** p < 0.01, versus the HFD group. nutrients-14-01747-t001_Table 1 Table 1 Data are expressed as mean ± SD. # p < 0.05 ## p < 0.01 and ### p < 0.001 versus the normal group. * p < 0.05 and ** p < 0.01 versus the HFD group. Group Normal HFD GBE 50 GBE 100 GBE 200 Factors TC (mg/dL) 105.59 ± 6.74 14.04 ± 14.19 ## 135.20 ± 13.04 125.33 ± 9.87 119.41 ± 11.79 * HDL-c (mg/dL) 66.74 ± 3.62 80.18 ± 11.06 82.38 ± 9.45 81.28 ± 1.05 79.63 ± 4.65 HDL-c/TC ratio(mg/dL) 0.66 ± 0.03 0.55 ± 0.04 ## 0.61 ± 0.03 0.65 ± 0.04 * 0.67 ± 0.04 ** LDL-c (mg/dL) 29.10 ± 3.80 49.88 ± 11.20 ## 42.37 ± 5.01 34.73 ± 11.01 33.41 ± 7.50 * TG (mg/dL) 44.00 ± 8.64 71.00 ± 16.77 # 64.00 ± 12.65 47.00 ± 8.87 44.50 ± 8.81 * Insulin (ng/mL) 0.30 ± 0.03 0.99 ± 0.01 ### 1.09 ± 0.15 0.96 ± 0.04 0.71 ± 0.16 * Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Kalinkovich A. Livshits G. Sarcopenic obesity or obese sarcopenia: A cross talk between age-associated adipose tissue and skeletal muscle inflammation as a main mechanism of the pathogenesis Ageing Res. Rev. 2017 35 200 221 10.1016/j.arr.2016.09.008 27702700 2. Blüher M. Obesity: Global epidemiology and pathogenesis Nat. Rev. Endocrinol. 2019 15 288 298 10.1038/s41574-019-0176-8 30814686 3. Wannamethee S.G. Atkins J.L. Muscle loss and obesity: The health implications of sarcopenia and sarcopenic obesity Proc. Nutr. Soc. 2015 74 405 412 10.1017/S002966511500169X 25913270 4. Choi K.M. Sarcopenia and sarcopenic obesity Korean J. Intern. Med. 2016 31 1054 10.3904/kjim.2016.193 27809450 5. Zamboni M. Rubele S. Rossi A.P. Sarcopenia and obesity Curr. Opin. Clin. Nutr. Metab. Care 2019 22 13 19 10.1097/MCO.0000000000000519 30461451 6. Tumova J. Andel M. Trnka J. Excess of free fatty acids as a cause of metabolic dysfunction in skeletal muscle Physiol. Res. 2016 65 193 10.33549/physiolres.932993 26447514 7. Kitessa S.M. Abeywardena M.Y. Lipid-induced insulin resistance in skeletal muscle: The chase for the culprit goes from total intramuscular fat to lipid intermediates, and finally to species of lipid intermediates Nutrients 2016 8 466 10.3390/nu8080466 8. Schmitz-Peiffer C. Biden T.J. Protein kinase C function in muscle, liver, and β-cells and its therapeutic implications for type 2 diabetes Diabetes 2008 57 1774 1783 10.2337/db07-1769 18586909 9. Morino K. Petersen K.F. Shulman G.I. Molecular mechanisms of insulin resistance in humans and their potential links with mitochondrial dysfunction Diabetes 2006 55 S9 S15 10.2337/db06-S002 17130651 10. Lipina C. Hundal H.S. Lipid modulation of skeletal muscle mass and function J. Cachexia Sarcopenia Muscle 2017 8 190 201 10.1002/jcsm.12144 27897400 11. Galadari S. Rahman A. Pallichankandy S. Galadari A. Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms Lipids Health Dis. 2013 12 98 10.1186/1476-511X-12-98 23835113 12. Glass D.J. Skeletal muscle hypertrophy and atrophy signaling pathways Int. J. Biochem. Cell Biol. 2005 37 1974 1984 10.1016/j.biocel.2005.04.018 16087388 13. Vainshtein A. Sandri M. Signaling pathways that control muscle mass Int. J. Mol. Sci. 2020 21 4759 10.3390/ijms21134759 32635462 14. Palomer X. Pizarro-Delgado J. Barroso E. Vázquez-Carrera M. Palmitic and oleic acid: The yin and yang of fatty acids in type 2 diabetes mellitus Trends Endocrinol. Metab. 2018 29 178 190 10.1016/j.tem.2017.11.009 29290500 15. Shou J. Chen P.-J. Xiao W.-H. Mechanism of increased risk of insulin resistance in aging skeletal muscle Diabetol. Metab. Syndr. 2020 12 14 10.1186/s13098-020-0523-x 32082422 16. Helms S. Cancer prevention and therapeutics: Panax ginseng Altern. Med. Rev. 2004 9 259 274 15387718 17. Lee H.J. Lee Y.-H. Park S.K. Kang E.S. Kim H.-J. Lee Y.C. Choi C.S. Park S.E. Ahn C.W. Cha B.-S. Korean red ginseng (Panax ginseng) improves insulin sensitivity and attenuates the development of diabetes in Otsuka Long-Evans Tokushima fatty rats Metabolism 2009 58 1170 1177 10.1016/j.metabol.2009.03.015 19477471 18. Kim D.Y. Yang W.M. Panax ginseng ameliorates airway inflammation in an ovalbumin-sensitized mouse allergic asthma model J. Ethnopharmacol. 2011 136 230 235 10.1016/j.jep.2011.04.048 21549818 19. Li Z. Ji G.E. Ginseng and obesity J. Ginseng Res. 2018 42 1 8 10.1016/j.jgr.2016.12.005 29348715 20. Sun S. Qi L.-W. Du G.-J. Mehendale S.R. Wang C.-Z. Yuan C.-S. Red notoginseng: Higher ginsenoside content and stronger anticancer potential than Asian and American ginseng Food Chem. 2011 125 1299 1305 10.1016/j.foodchem.2010.10.049 21344064 21. Cho W.C. Chung W.-S. Lee S.K. Leung A.W. Cheng C.H. Yue K.K. Ginsenoside Re of Panax ginseng possesses significant antioxidant and antihyperlipidemic efficacies in streptozotocin-induced diabetic rats Eur. J. Pharmacol. 2006 550 173 179 10.1016/j.ejphar.2006.08.056 17027742 22. Kim J.H. Yi Y.-S. Kim M.-Y. Cho J.Y. Role of ginsenosides, the main active components of Panax ginseng, in inflammatory responses and diseases J. Ginseng Res. 2017 41 435 443 10.1016/j.jgr.2016.08.004 29021688 23. Kim C.-K. Cho D.H. Lee K.-S. Lee D.-K. Park C.-W. Kim W.G. Lee S.J. Ha K.-S. Taeg O.G. Kwon Y.-G. Ginseng berry extract prevents atherogenesis via anti-inflammatory action by upregulating phase II gene expression Evid.-Based Complementary Altern. Med. 2012 2012 490301 10.1155/2012/490301 24. Kim Y.K. Yoo D.S. Xu H. Park N.I. Kim H.H. Choi J.E. Park S.U. Ginsenoside content of berries and roots of three typical Korean ginseng (Panax ginseng) cultivars Nat. Prod. Commun. 2009 4 1934578X0900400704 10.1177/1934578X0900400704 25. Cho K.S. Park C.W. Kim C.-K. Jeon H.Y. Kim W.G. Lee S.J. Kim Y. Lee J. Choi Y. Effects of Korean ginseng berry extract (GB0710) on penile erection: Evidence from in vitro and in vivo studies Asian J. Androl. 2013 15 503 10.1038/aja.2013.49 23708462 26. Xie J. Zhou Y.-P. Dey L. Attele A. Wu J. Gu M. Polonsky K. Yuan C.-S. Ginseng berry reduces blood glucose and body weight in db/db mice Phytomedicine 2002 9 254 258 10.1078/0944-7113-00106 12046868 27. Attele A.S. Zhou Y.-P. Xie J.-T. Wu J.A. Zhang L. Dey L. Pugh W. Rue P.A. Polonsky K.S. Yuan C.-S. Antidiabetic effects of Panax ginseng berry extract and the identification of an effective component Diabetes 2002 51 1851 1858 10.2337/diabetes.51.6.1851 12031973 28. Seo E. Kim S. Lee S.J. Oh B.-C. Jun H.-S. Ginseng berry extract supplementation improves age-related decline of insulin signaling in mice Nutrients 2015 7 3038 3053 10.3390/nu7043038 25912041 29. Chae H.-S. You B.H. Choi J. Chin Y.-W. Kim H. Choi H.S. Choi Y.H. Ginseng berry extract enhances metformin efficacy against obesity and hepatic steatosis in mice fed high-fat diet through increase of metformin uptake in liver J. Funct. Foods 2019 62 103551 10.1016/j.jff.2019.103551 30. Witteveen E. Hoogland I.C. Wieske L. Weber N.C. Verhamme C. Schultz M.J. Van Schaik I.N. Horn J. Assessment of intensive care unit-acquired weakness in young and old mice: An E. coli septic peritonitis model Muscle Nerve 2016 53 127 133 10.1002/mus.24711 26015329 31. Lee M.R. Kim J.E. Choi J.Y. Park J.J. Kim H.R. Song B.R. Choi Y.W. Kim K.M. Song H. Hwang D.Y. Anti-obesity effect in high-fat-diet-induced obese C57BL/6 mice: Study of a novel extract from mulberry (Morus alba) leaves fermented with Cordyceps militaris Exp. Ther. Med. 2019 17 2185 2193 10.3892/etm.2019.7191 30867704 32. Peng Y. Sun Q. Xu W. He Y. Jin W. Yuan L. Gao R. Vitexin ameliorates high fat diet-induced obesity in male C57BL/6J mice via the AMPKα-mediated pathway Food Funct. 2019 10 1940 1947 10.1039/C9FO00148D 30874277 33. Tong T. Kim M. Park T. α-Ionone attenuates high-fat diet-induced skeletal muscle wasting in mice via activation of cAMP signaling Food Funct. 2019 10 1167 1178 10.1039/C8FO01992D 30734800 34. Yoo A. Jang Y.J. Ahn J. Jung C.H. Seo H.D. Ha T.Y. Chrysanthemi Zawadskii var. Latilobum Attenuates Obesity-Induced Skeletal Muscle Atrophy via Regulation of PRMTs in Skeletal Muscle of Mice Int. J. Mol. Sci. 2020 21 2811 10.3390/ijms21082811 35. Gheibi S. Kashfi K. Ghasemi A. A practical guide for induction of type-2 diabetes in rat: Incorporating a high-fat diet and streptozotocin Biomed. Pharmacother. 2017 95 605 613 10.1016/j.biopha.2017.08.098 28881291 36. Han D.-H. Kim S.H. Higashida K. Jung S.-R. Polonsky K.S. Klein S. Holloszy J.O. Ginsenoside Re rapidly reverses insulin resistance in muscles of high-fat diet fed rats Metabolism 2012 61 1615 1621 10.1016/j.metabol.2012.04.008 22571876 37. Li F. Li X. Peng X. Sun L. Jia S. Wang P. Ma S. Zhao H. Yu Q. Huo H. Ginsenoside Rg1 prevents starvation-induced muscle protein degradation via regulation of AKT/mTOR/FoxO signaling in C2C12 myotubes Exp. Ther. Med. 2017 14 1241 1247 10.3892/etm.2017.4615 28781621 38. Kandarian S.C. Jackman R.W. Intracellular signaling during skeletal muscle atrophy Muscle Nerve 2006 33 155 165 10.1002/mus.20442 16228971 39. Argadine H.M. Mantilla C.B. Zhan W.-Z. Sieck G.C. Intracellular signaling pathways regulating net protein balance following diaphragm muscle denervation Am. J. Physiol.-Cell Physiol. 2011 300 C318 C327 10.1152/ajpcell.00172.2010 21084642 40. Schiaffino S. Mammucari C. Regulation of skeletal muscle growth by the IGF1-Akt/PKB pathway: Insights from genetic models Skelet. Muscle 2011 1 4 10.1186/2044-5040-1-4 21798082 41. Kang S.-H. Lee H.-A. Kim M. Lee E. Sohn U.D. Kim I. Forkhead box O3 plays a role in skeletal muscle atrophy through expression of E3 ubiquitin ligases MuRF-1 and atrogin-1 in Cushing’s syndrome Am. J. Physiol.-Endocrinol. Metab. 2017 312 E495 E507 10.1152/ajpendo.00389.2016 28246104 42. Zhu S. Tian Z. Torigoe D. Zhao J. Xie P. Sugizaki T. Sato M. Horiguchi H. Terada K. Kadomatsu T. Aging-and obesity-related peri-muscular adipose tissue accelerates muscle atrophy PLoS ONE 2019 14 0221366 10.1371/journal.pone.0221366 43. Gregor M.F. Hotamisligil G.S. Inflammatory mechanisms in obesity Annu. Rev. Immunol. 2011 29 415 445 10.1146/annurev-immunol-031210-101322 21219177 44. Pellegrinelli V. Rouault C. Rodriguez-Cuenca S. Albert V. Edom-Vovard F. Vidal-Puig A. Clément K. Butler-Browne G.S. Lacasa D. Human adipocytes induce inflammation and atrophy in muscle cells during obesity Diabetes 2015 64 3121 3134 10.2337/db14-0796 25695947

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093406 sensors-22-03406 Article Analysis of the Effect of Velocity on the Eddy Current Effect of Metal Particles of Different Materials in Inductive Bridges Li Wei 1 https://orcid.org/0000-0002-8081-8878 Yu Shuang 1 https://orcid.org/0000-0003-3172-600X Zhang Hongpeng 1* Zhang Xingming 12 https://orcid.org/0000-0001-8549-3382 Bai Chenzhao 1 Shi Haotian 1 Xie Yucai 1 Wang Chengjie 1 Xu Zhiwei 1 Zeng Lin 3 Sun Yuqing 1 Dao Phong B. Academic Editor Yu Liang Academic Editor Qiu Lei Academic Editor 1 School of Marine Engineering, Dalian Maritime University, Dalian 116026, China; dmuliwei@dlmu.edu.cn (W.L.); yush312@163.com (S.Y.); zhxm@hit.edu.cn (X.Z.); baichenz@163.com (C.B.); dmu6hao@163.com (H.S.); xyc86418332@163.com (Y.X.); wangcj@dlmu.edu.cn (C.W.); xuzhiwei201809@163.com (Z.X.); sunyq@dlmu.edu.cn (Y.S.) 2 School of Naval Architecture and Ocean Engineering, Harbin Institute of Technology, Weihai 264209, China 3 Laboratory of Biomedical Microsystems and Nano Devices, Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; lin.zeng@siat.ac.cn * Correspondence: zhppeter@dlmu.edu.cn 29 4 2022 5 2022 22 9 340627 3 2022 27 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). A method for analyzing the influence of velocity changes on metal signals of different materials in oil detection technology is proposed. The flow rate of metal contaminants in the oil will have a certain impact on the sensitivity of the output particle signal in terms of electromagnetic fields and circuits. The detection velocity is not only related to the sensitivity of the output particle signal, but also to the adaptability of high-speed and high-throughput in oil online monitoring. In this paper, based on a high-sensitivity inductive bridge, the eddy current effect of velocity in a time-harmonic magnetic field is theoretically analyzed and experimentally verified, the phenomenon of particle signal variation with velocity for different materials is analyzed and discussed, and finally the effect of velocity on the output signal of the processing circuit is also elaborated and experimentally verified. Experiments show that under the influence of the time-harmonic magnetic field, the increase of the velocity enhances the detection sensitivity of non-ferromagnetic metal particles and weakens the detection sensitivity of non-ferromagnetic particles. Under the influence of the processing circuit, different velocities will produce different signal gains, which will affect the stability of the signal at different velocities. inductance bridge particle material velocity eddy current effect oil detection National Natural Science Foundation of China51679022 Fundamental Research Funds for the Central Universities3132022219 Liaoning Revitalization Talents ProgramXLYC2002074 This present project is supported by the National Natural Science Foundation of China (Grant No. 51679022), the Fundamental Research Funds for the Central Universities (Grant No. 3132022219), and the Liaoning Revitalization Talents Program (XLYC2002074). ==== Body pmc1. Introduction The Real Economy is the foundation of a country’s economic development, involving industry, agriculture, construction, and other fields. The operation stability of various heavy machinery in the real economy determines the engineering efficiency and quality. Therefore, mechanical fault diagnosis is directly related to the economic cost of engineering and indirectly related to the development of the country’s real economy. In the context of such engineering needs, the fault diagnosis of mechanical equipment shows its criticality. Fault diagnosis is a state monitoring technology for mechanical equipment during operation. By grasping the noise [1], vibration [2], temperature [3], oil quality [4,5], and other information of mechanical equipment during operation, it is possible to realize the type judgment of mechanical faults, fault location, and early prediction of mechanical faults [6]. There are four main means of fault diagnosis techniques [7]: noise detection, vibration detection, temperature detection, and oil detection. Among them, the oil detection technology [8,9] is widely used in engineering because it can detect various information in the mechanical system, so as to obtain more comprehensive fault information such as mechanical wear degree, fault type, and fault location. The detected information includes oil viscosity [10], air bubbles [11], water content [12], and metal particle concentration [13,14], size [15], type [16] in the oil. However, there are still problems of the low sensitivity of large-throughput detection and low-throughput detection which is not conducive to online detection [17]. Solving the contradiction has become the research direction of researchers in related fields. In 2009, Murali S et al. [18] designed a microfluidic oil detection chip based on the principle of capacitive Coulter counting, which combined the microfluidic chip with the oil detection technology, greatly reducing the size of the microfluidic oil detection chip and improving the sensitivity of metal particle detection in oil. In 2011, Du L et al. [19] designed a microfluidic oil detection chip based on the inductance Coulter principle, which can realize the differentiated identification of ferrous metals and non-ferrous metals. Zhang X et al. [20] studied the detection mechanism of the inductive oil detection chip, established a system model between the detection coil and metal particles, and obtained the mathematical model between the number of turns, density, excitation frequency, metal particle size, and output inductance of the detection coil. Respectively, Ma L et al. [21], Li Y et al. [22] used the mutual inductance between double coils and the optimization of triple coil structure to improve the detection sensitivity of the sensor. Davis J P et al. [23] realized the high-sensitivity identification of metal particles under the condition of the simplified circuit by using Maxwell bridge and subsequent filtering, amplifying, and rectifying circuits. As mentioned above, many researchers have been working to achieve high-sensitivity differential detection from various aspects, including structural design [24], circuit design [25], magnetic material addition [26]. To further realize online monitoring of mechanical faults and expand the detection throughput with high detection sensitivity, a series of studies have been carried out by the researchers concerned. Zhu X et al. [27] adopted the time-division multiplexing method to collect the sensing data of 9 channels in sequence, and added series diodes to eliminate the crosstalk between each channel. Jagtiani A V et al. [28] adopted the frequency division multiplexing method to modulate and demodulate multiple signals with different frequency carriers, increasing the detection throughput by 4 times. Bai C et al. [29] designed a high-throughput sensor with an annular flow channel structure, expanding the flow to 16 times that of the original microchannel. Other related researchers started from the perspective of detection speed, explored the possibility of online monitoring of oil, and explored the impact of speed on detection sensitivity. Wang X et al. [30] explored the influence of particle velocity on the aliasing signal waveform, and put forward the conclusion that the aliasing induced voltage is proportional to the particle velocity. Wu Y et al. [31] deduced the analytical formula for the influence of the flow rate on the magnetic field, and proposed that the detection sensitivity of copper particles can be enhanced by increasing the oil detection flow rate. Liu E et al. [32] studied the influence of flow velocity on the detection signal, and proposed that the amplitude of the inductive signal of metal particles can be improved by appropriately reducing the flow velocity. The research results of the above researchers are valuable, but there is still controversy about the effect of flow rate on abrasive particles of different materials. In this study, based on an inductive bridge, we explore the effect of particle velocities of different materials on the eddy current effect. The influence of particle motion velocity on the output signal of detected particles is analyzed by using the angle difference between the direction of particle motion and the direction of magnetic field lines on both sides of the coil. The characteristics of high-speed and high throughput regard online monitoring are fitted under the premise of high detection sensitivity. Compared with previous analysis of velocity, this method can visually verify the trend of particle velocity to signal change without interference from electromagnetic and detection circuits. In this paper, an inductive bridge and a processing circuit are used to replace the impedance analyzer, so the sensor still has high detection sensitivity under the premise of portability and low cost. And the content explored in this paper is in line with the actual engineering, which is conducive to the development of online monitoring. On this basis, it is committed to the realization of online detection of oil, by exploring the influence of speed on the detection of metal particles of different materials. 2. Sensor Design and Theory Analysis 2.1. Inductance Detection Analysis The design of the sensor chip is shown in Figure 1. The inside of the sensing chip includes the particle inlet and outlet, the detection channel, and the inductive bridge. In the inductive bridge, one of the spiral coils wrapped around the outside of the detection channel is the induction coil and the other spiral coil is the balance coil. Fixed resistance, variable resistance and two solenoid coils form an electric bridge, and the inductive pulses generated by particles passing through the induction coils are converted into differential voltage pulses by the inductive bridge. As shown in Figure 1, the two nodes on the bridge were connected to the AC excitation, and the voltage signals output by the other two nodes were connected to the subsequent detection circuit. According to previous studies [33], the amount of inductance change produced by the particle at the central axis of the solenoid coil is:(1) ΔLx=Im(Δzmaxω)=4πμ0N2w2+d2Re(kp) where Δzmax is the impedance output by the coil detecting the particle, ω is the angular frequency of the AC excitation, μ0 is the vacuum permeability, N is the number of turns of the coil, w is the axial length of the coil, and d is the inner diameter of the coil. The magnetization factor kp of ferromagnetic metal particles is:(2) kp=(−r2k2+2μr+1)sin(rk)−rk(2μr+1)cos(rk)(r2k2+μr−1)sin(rk)−rk(μr−1)cos(rk)⋅r32 The magnetization factor kp of the non-ferromagnetic metal particles is:(3) kp=12⋅[r3+3r2kcot(rk)−3rk2] where r is the particle radius and μr is the relative magnetic permeability of the particle, which is assumed to be a real number in this paper and is not affected by frequency. (4) k=−jωμrμ0σ where σ is the electrical conductivity. When an AC excitation is applied to the coil, an alternating magnetic field is generated inside the coil. Since the relative permeability of ferromagnetic metal particles is much greater than 1, the magnetization effect generated when the ferromagnetic metal particles pass through the induction coil causes the magnetic flux in the coil to increase abruptly. However, the induced current is generated inside the ferromagnetic metal particles to obstruct the change of the original magnetic field, and the induced current generates magnetic flux in the opposite direction of the original magnetic field, which weakens the original magnetic field. That is, the particles produce eddy current effect in the time-harmonic magnetic field. For ferromagnetic particles, the magnetization effect is stronger than the eddy current effect, so the amount of change in coil inductance caused by ferromagnetic metal particles is positive. Since the relative permeability of non-ferromagnetic metal particles is slightly less than 1, the eddy current effect dominates when the non-ferromagnetic metal particles pass through the induction coil, causing the original magnetic field to be weakened, so the change in coil inductance caused by the non-ferromagnetic metal particles is negative. The sensor can differentiate and detect ferromagnetic and non-ferromagnetic metal particles in the oil, based on the Coulter principle. The tribological information reflected by the detected metal particle information (including the number of metal particles obtained by the number of inductance signals, and the particle size of the metal particles obtained by the amplitude of the inductance signal) can be used to predict the degree of failure of the system. 2.2. Design and Principle Analysis of Inductor Bridge Considering the bridge as an equivalent circuit, the equivalent circuit is shown in Figure 2 A, B, C, D are the endpoints on the bridge arms; Lx is the inductance of the induction coil; Rx is the internal resistance of the induction coil; Ln is the inductance of the reference coil; Rn is the internal resistance of the reference coil; Ra and Rb are the balance resistances on the two bridge arms, respectively. Simulate the equivalent circuit of the inductive bridge. The frequency of the AC excitation source was set to 1 MHz, and the voltage was set to 10 V. Explore the effect of resistance parameters on bridge sensitivity. First, change the resistance values of Ra and Rb at the same time; second, change the resistance values of the coil internal resistance Rx and Rn at the same time. Under the condition that the inductance base value of the two coils Lx, Ln was 1 μH and the inductance change ΔLx was 0.1 μH, the change of the coil internal resistance had a great influence on the voltage difference UBD between the two points B and D. As shown in Figure 3, the direction of the arrows shows the trend of bridge sensitivity as a function of internal resistance. As the coil internal resistance Rx decreased, the voltage value of UBD increased under the condition of the same inductance variation ΔLx, namely, the higher the quality factor of the coil, the higher the sensitivity of the bridge. Combined with the analysis of the simulation results, it is expected to select the coil with a smaller internal resistance Rx under the condition of similar base inductance Lx. As shown in Figure 4, w is the height of the coil; k is the number of layers of the coil; a is the wire diameter of the coil; d is the inner diameter of the coil. The expression for the amount of change in coil inductance ΔLx due to particles in Equation (1) shows that the amount of change in inductance ΔLx is related to the coil turns N, axial length w, coil inner diameter d, particle radius r, relative permeability of particles μr, particle conductivity σ, and the angular frequency ω of the AC excitation applied to the coil. Among them, the factors affected by the coil itself are: the number of turns of the coil N, the axial length w, and the inner diameter of the coil d. Let b=N2w2+d2. The larger b is, the larger the change in coil inductance ΔLx is, and the higher the sensitivity to detect particles as they pass through the coil. Since ∂b∂N>0, ∂b∂w<0, and ∂b∂d<0, it means that the larger the number of coil turns N, the smaller the coil axis length w and the inner diameter d, the higher the coil inductance variation ΔLx. In order to produce a large inductance variation ΔLx between the metal particles and the coil, it is desired to increase the number of turns N of the coil, while being able to reduce the coil axis length w and the inner diameter d. The expression for the estimated internal resistance of the spiral coil is:(5) Rx=ρ⋅lS=ρ⋅2π⋅Nk⋅∑i=0k=i+1{[a(2i+1)+d]/2}π⋅(a2)2 where ρ is the coil resistivity, l is the coil length, and S is the coil cross-sectional area. It can be seen from Equation (5) that the larger the wire diameter a that determines the cross-sectional area of the coil S, the smaller the number of turns N, the axial length w, and the inner diameter d that collectively reflect the coil length l, the smaller the coil internal resistance Rx. Therefore, increasing the wire diameter of the coil a can reduce the internal resistance of the coil Rx without affecting the variation of the coil inductance ΔLx. Since the microfluidic chip adopts tiny coils, the wire diameter a which is smaller than the number of coil turns N, axial length w and inner diameter d is regarded as a fixed value, and the part as the numerator is ignored in the calculation of the partial derivative between the axial length w and the number of coil turns N. Then there is ∂R∂w>0, ∂R∂d>0, ∂R∂N>0, that is, the coil resistance Rx decreases monotonically with the decrease of the number of turns N, axial length w, and inner diameter d. Since the wire diameter a is much smaller than the number of coil layers k, the axial length w and the inner diameter d, namely, ∂R∂N<∂R∂w and ∂R∂N<∂R∂d, which means the change rate of the coil resistance Rx with the number of turns N is smaller than the change rate of the resistance Rx with the axial length w and inner diameter d. Collectively, the coil resistance Rx can be reduced by decreasing the number of turns N, axial length w, and inner diameter d. The effect of a change in the number of turns N is less than the effect of a change in the axial length w and inner diameter d on the resistance Rx. Therefore, the number of turns N of the coil can be increased, while the resistance Rx can be appropriately sacrificed, and the coil inductance variation ΔLx can be increased at the same time. To summarize, in order to select a coil with smaller resistance Rx under the condition of larger inductance change ΔLx, a larger coil wire diameter a, smaller axial length w, inner diameter d, and appropriately larger number of turns N can be selected. Combined with the above theoretical analysis and debugging through experiments, the number of turns N = 230 turns, axial length w = 2.76 mm, inner diameter d = 0.54 mm, outer diameter D = 1.55 mm, wire diameter a = 0.07 mm, resistance Rx = 4 Ω of the solenoid coil were selected by the bridge sensing unit. When the particles pass through the coil to generate an inductive signal, the two arms of the bridge generate a voltage difference [34], the voltage of the two arms are rectified into two DC pulsating voltage signals, and then filtered by the filter circuit to remove the high frequency noise signal [35], interspersed in the particle signal, and finally differentially amplified by an amplifier circuit to generate the differential voltage caused by the particles. As shown in the block diagram of the detection circuit system in Figure 5, when the bridge is balanced:(6) ZAB⋅ZCD=ZAD⋅ZBC That is:(7) (jωLx+Rx)⋅Rb=(jωLn+Rn)⋅Ra (8) UBD=UAD−UAB=Ui⋅(ZADZAD+ZCD−ZABZAB+ZBC) (9) UBD=Ui{ω2[Lx2Rb(Rn+Rb)−Ln2Ra(Rx+Ra)]+(Rn+Rb)(Rx+Ra)(RxRb−RnRa)[ω2Lx2+(Rx+Ra)2][ω2Ln2+(Rn+Rb)2]+ωLxRa[ω2Ln2+(Rn+Rb)2]−ωLnRb[ω2Lx2+(Rx+Ra)2][ω2Lx2+(Rx+Ra)2][ω2Ln2+(Rn+Rb)2]⋅j} When ferromagnetic metal particles pass through an alternating time-harmonic magnetic field in the inductive bridge, the inductance value of the induction coil increases, resulting in an increase in UBD, and the differential voltage is positive; when the non-ferromagnetic metal particles pass through the inductive bridge, the inductance value of the induction coil decreases, resulting in a decrease in UBD, the differential voltage is negative. In Figure 5, a half-wave rectifier circuit module using diodes was used to rectify two AC voltage signals into pulsating DC voltage signals respectively. Since the amplitude and direction of the DC signal do not change with time, the rectified pulsating DC voltage signal can realize the differential detection of ferromagnetic and non-ferromagnetic metal particles by an inductive bridge, and can be better collected and compared. In the low-pass filter module using the two-stage wireless gain multiple feedback filter circuit, the cut-off frequency of the first-stage low-pass filter circuit was 16 kHz, and the cut-off frequency of the second-stage low-pass filter circuit was 1.6 kHz. The low-pass filter module can reduce the AC components in the two-channel pulsating DC voltage signals as much as possible, and filter out the high-frequency noise and harmonics mixed in the two-channel signals. The differential amplifier module made the voltage difference between the two signals affected by the sensing coil and the reference coil, and the differential voltage signal combined with the reverse amplifier circuit could be amplified by 20 to 400 times. In the previous experimental research in the laboratory, the DC signal generated by the AC voltage signal through the above-mentioned rectification, filtering and amplifying circuit still has relatively large noise. Therefore, the terminal filter circuit was adopted in the laboratory to further extract the particle signal with very low frequency. The terminal filter using the UAF42 active filter can adjust the cutoff frequency of the low-pass filter in the range of 0~5 kHz and the quality factor of the filter by changing the resistance value of the potentiometer. The high-sensitivity detection of ferromagnetic and non-ferromagnetic metal particles in oil detection and the portability of the detection device are realized through the processing of the inductive bridge and the detection circuit. 2.3. The Effect of Velocity on the Magnetic Field of a Solenoid The velocity of metal particles in the sensing coil is a non-negligible factor affecting the particle signal. The velocity of the metal particles passing through the sensing coil affects both the sensing signal [36] and the flux of the oil detection. According to Faraday’s law of electromagnetic induction:(10) ε=−dΦdt where ε is the induced electromotive force generated by the particle passing through the coil, and dΦdt is the rate of change of the magnetic flux with time. According to earlier research in our lab [21]:(11) ε=∮CE→in⋅dl=−dΦdt=−ddt∬SB→⋅dS→=−∬S(∂B→∂t⋅dS→+B→⋅∂∂tdS→) where E→in is the electric field strength of the metal particle induced by the magnetic field, dl is the length differential of the vortex ring inside the metal particle, B→ is the magnetic induction between the metal particle and the coil, S→ is the area of the vortex ring, −∬S∂B→∂t⋅dS→ is the induced electromotive force εt due to the change in the magnetic field, and −∬SB→∂∂t⋅dS→ is the kinetic electromotive force εm due to the movement of the metal particle in the magnetic field. When the metal particles pass through the alternating magnetic field in the coil, an eddy current ring is generated inside the metal, and the resulting motional electromotive force is:(12) εm=−dϕmdt=∮C(v→×B→)⋅dl where v→ is the moving velocity of the metal particles in the magnetic field. According to the definition of inductance:(13) dL=dΦdI=∮c(v→×B→)⋅dl dtI It can be seen from Equation (13) that in the alternating magnetic field, the coil inductance dL caused by the motional electromotive force εm increases with the increase of the velocity v→. That is, the greater the velocity, the greater the induced electromotive force containing the motional electromotive force, the stronger the obstruction of the original magnetic field by the induced electromotive force generated by the metal particles, and the more pronounced the eddy current effect inside the metal particles. This is reflected in the fact that, by increasing the velocity, the magnetization effect is weakened more by the eddy current effect in the detection of ferromagnetic metal particles, resulting in a weaker signal for ferromagnetic particles, while the eddy current effect is enhanced in the detection of non-ferromagnetic particles, resulting in a stronger signal for non-ferromagnetic particles. 3. Results and Discussion Experiments to explore the velocity often use a plane coil, so that the metal particles move on the surface of the plane coil, that is, in the direction perpendicular to the magnetic field lines of the plane coil. This method amplifies the proportion of the motional electromotive force in the induced electromotive force, which is ideal for the study of velocity effect. However, during the actual experiments, many uncontrollable factors arise at the same time as the velocity increases, such as the small sampling rate of the equipment, particle vibration and increased noise. These factors also affect the output of the signal. Using the angle difference θ between the movement direction of the metal particles on both sides of the solenoid coil and the magnetic field line inside the solenoid, as shown in Figure 6, the influence trend of the dynamic electromotive force can be clearly seen by comparison. In this experiment, the experimental system was set up as shown in Figure 7, with the metal particles adhering to a nylon rope and a stepper motor controlling the velocity past the detection chip. The particle inductance signal sensed by the sensing coil in the detection chip is converted into two voltage signals by the inductance bridge in the detection chip. When the metal particles on the nylon rope pass through the sensing coil, a voltage difference is generated between the two voltage signals. The inductive bridge in the detection chip was given a 1.3 MHz, 10 V sinusoidal AC excitation source by a waveform generator. The subsequent processing circuit rectifies, filters, differentiates and amplifies the two voltage signals generated at points B and D of the inductive bridge, and the processing circuit was powered by a DC power supply of ±15 V DC. The voltage signal processed by the processing circuit is converted by the data acquisition card to the computer through analog-digital conversion. To avoid distortion of the sampled signal when the sampling rate was insufficient, the sampling rate was chosen to be much greater than the signal frequency. The sampling rate chosen was 2000 samples/s, much greater than the frequency of the signal required by Nyquist-Shannon sampling theorem for this experiment. The experiment proved that the sampling signal at this sampling rate was stable, with a set of signals for 350 μm iron particles at a velocity of 5 mm/s as shown in Figure 8: The experimental data of the acquired noise signal is shown in Figure 9. The noise signal is collected at each velocity for 10 s under the condition of no-load nylon rope. It can be seen in Figure 9 that the collected noise signal does not change much with the change of velocity. Figure 10 shows a comparison of the signals of 350 µm ferromagnetic metal particles (350 µm Fe) at different velocities, capturing one signal from a set at each velocity, which was intercepted for 10 s. Figure 11 shows a comparison of the signals of non-ferromagnetic metal particles (350 μm Cu) at different velocities, capturing one signal from a set at each velocity, which was intercepted for 10 s. Figure 12 shows a comparison of the signals of non-ferromagnetic metal particles (350 μm Al) at different velocities, capturing one signal from a set at each velocity, which was intercepted for 10 s. As can be seen in Figure 10, Figure 11 and Figure 12, during the increase in velocity from 5 mm/s to 65 mm/s, the signal affected by the velocity of the cut magnetic induction lines before and after the spiral coil starts to increase significantly when the velocity increases to 35 mm/s. This phenomenon can be observed in the detection of iron particles, copper particles and aluminum particles. This phenomenon is caused by the angular difference θ between the moving direction of the particles and the direction of the alternating magnetic field. The change of velocity increases the induced electromotive force between the particles and the coil, and enhances the eddy current effect inside the particles. This phenomenon is consistent with the theoretical inference in 2.3. Figure 13a shows the changing trend of the voltage signal amplitude affected by the cutting magnetic field velocity for the iron, copper, and aluminum metal particles on both sides of the coil. Although the eddy current effect caused by the enhanced induced electromotive force increases as the particle velocity increases, the amplitude of the voltage change caused by the velocity increases, resulting in a weakening of the signal of ferromagnetic metal particles and an enhancement of the signal of non-ferromagnetic metal particles. However, in general, the trend of the signal change of metal particles is still weakened, and the signal amplitude of non-ferromagnetic metal particles is still weakened. The signal weakening trend is shown in Figure 13b. The analysis of this phenomenon is presented as follows. The increase of the detection velocity, on the one hand, for the time-harmonic magnetic field, changes the induced electromotive force between the metal particles and the coil in the magnetic field; on the other hand, for the detection circuit, it changes the frequency of the metal particle signal. That is, as the velocity of the metal particles increases, the signal frequency of the metal particles increases. It can be seen by using the solenoid that in the time-harmonic magnetic field, the increase of the velocity leads to the enhancement of the induced electromotive force, which weakens the original magnetic induction intensity. This phenomenon is manifested as an increase in the negative detection signal caused by the induced electromotive force, which gradually increases with the increase of the detection velocity on both sides of the sensing area of the solenoid. This is reflected in the weakening of the detection signal of the ferromagnetic metal particles and the enhancement of the detection signal of the non-ferromagnetic metal particles. This experimental result is consistent with the theoretical inference in Section 2.3. As for the non-magnetic factors during the experiment, that is, for the detection circuit, the change in the signal frequency of the metal particles causes a change in the signal output amplitude of the particles at the corresponding frequency components. According to the set stepper motor stroke, stepper motor acceleration time and the velocity of the particles passing through the sensing coil, it is known that when the particles pass through the sensing coil at a velocity of 5 mm/s, the particle signal frequency is 0.02 Hz; when the particle passes the sensing coil at a velocity of 15 mm/s, the frequency of the particle signal is 0.06 Hz; when the particle passes the sensing coil at a velocity of 25 mm/s, the frequency of the particle signal is 0.09 Hz; when the particle passes the sensing coil at a velocity of 35 mm/s, the frequency of the particle signal is 0.12 Hz; when the particle passes the sensing coil at a velocity of 45 mm/s, the frequency of the particle signal is 0.15 Hz; when the particle passes the sensing coil at a velocity of 55 mm/s, the frequency of the particle signal is 0.17 Hz; when the particle passes the sensing coil at a velocity of 65 mm/s, the frequency of the particle signal is 0.19 Hz. As can be seen, different detection velocities, will directly lead to changes in the frequency component of the acquired signal, and the change in frequency, which will further affect the effect of the processing of that frequency component in the detection circuit, namely, the change in the frequency component caused by the velocity enhancement, will directly lead to changes in the output signal of the detection circuit. As shown in Figure 14, the terminal filter selected in the detection circuit is taken as an example. For the selected terminal filter UAF42 low-pass filter, the cut-off frequency of the low-pass filter was adjusted to be very low at the beginning of the experiment, and the quality influence of the filter was not considered. The ripple attenuation in the passband of the low-pass filter was ignored, so the amplitude and frequency change of the particle signal when passing through the filtering and amplifying circuit in the detection circuit was not considered. As shown in Figure 15, the characteristic curves of Chebyshev-type low-pass filter vary in trend for different component parameters. The low-pass filter produces different amounts of equal ripple undulations d′, d″ in the low frequency passband. Low-pass filters designed with different component parameters have different characteristic curves. When the ripple in the passband of the filter is large, the amplitude gain of the output signal fluctuates greatly due to the change of the signal frequency, as shown in Figure 15a; When the ripple in the passband of the filter is small, the amplitude gain of the output signal fluctuates less due to the change of the signal frequency, as shown in Figure 15b. Therefore, it is considered that as the detection velocity increases, the signal frequency component changes, resulting in a change in the output signal gain amplitude of the detection circuit. Based on the above hypothesis, the experiment was further designed. By re-adjusting the parameters of the low-pass filter element, the amplitude-frequency characteristics [37] of the low-pass filter circuit were changed, and the response of the circuit to the signal frequency component that changes with the velocity was changed. The two potentiometers R4 and R8 resistors of the low-pass filter were adjusted appropriately to change its quality factor; the two potentiometers R6 and R9 resistors of the low-pass filter were adjusted appropriately to change its low-pass cut-off frequency. The experimental results for the detection of 350 μm iron particles and 350 μm copper particles are shown in Figure 16 and Figure 17, respectively. In Figure 16, A and B both represent 350 μm iron particles. Signal A is the voltage signal of 350 μm iron particles before adjusting the detection circuit, which is represented by the blue solid line; Trend A is the signal trend with increasing velocity, which is represented by the blue dashed line. Signal B is the voltage signal of 350 μm iron particles after adjusting the detection circuit, which is represented by the red solid line; Trend B is the signal trend with increasing velocity, which is represented by the red dashed line. In Figure 17, C and D both represent 350 μm copper particles. Signal C is the voltage signal of 350 μm copper particles before adjusting the detection circuit, which is represented by the blue solid line; Trend C is the signal trend with increasing velocity, which is represented by the blue dashed line; Signal D is the voltage signal of 350 μm copper particles after adjusting the detection circuit, which is represented by the red solid line; Trend D is the signal trend with increasing velocity, which is represented by the red dashed line. It can be observed through two sets of experiments that after adjusting the detection circuit, the attenuation of the signal becomes slower. Compared to the signal change amplitude of metal particles with velocity change before the adjustment of the detection circuit, the signal amplitude attenuation of iron particles was reduced from 2.6838 V to 1.8582 V, when the metal particle velocity was increased from 5 mm/s to 65 mm/s after a slight adjustment to the detection circuit, as shown in Figure 16, and the signal amplitude attenuation was reduced by 0.8256 V. As shown in Figure 17, the signal amplitude attenuation of copper particles was reduced from 0.7469 V to 0.5097 V, and the signal amplitude attenuation was reduced by 0.2372 V. This shows that the attenuation of the total signal is indeed affected by the filter circuit. Similarly, the amplifying ability of the amplifying circuit to each frequency component is also different. It is inferred that the attenuation of the total signal amplitude is indeed influenced by the amplitude-frequency characteristics in the filtering and amplifying circuits in the detection circuit. Another reason for the analysis of the total signal attenuation is that the experimental setup of the stepper motor itself has a high current, generating non-negligible electromagnetic interference, which leads to the enhancement of low-level noise and the weakening of high-level signals through radiation interference, ultimately leading to the attenuation of the detection signal amplitude, but the influencing factor is the effect on the overall frequency component, independent of the particle velocity. The experimental results show that in a time-harmonic magnetic field, an increase in particle velocity increases the eddy current effect in the magnetic field, resulting in a decrease in signal amplitude for ferromagnetic metal particles and an increase in signal amplitude for non-ferromagnetic metal particles. Simultaneously, the quality of the detection circuit has an impact on the signals of particles with different velocities, and the design of the detection circuit should be optimized to improve the stability of the output signal in the passband. 4. Conclusions We analyzed and summarized the theory and law of the electromagnetic field for inductance differential detection, deduced the formula that causes the voltage difference of the inductive bridge to change, and optimized the subsequent processing circuit. The designed sensor can achieve low cost and portability under the premise of ensuring higher sensitivity. Based on the inductive bridge, this paper draws the following conclusions by studying the effect of velocity on particles of different materials. In terms of the sensitive influence of the coil quality factor on the inductive bridge: Through the simulation and analysis of the equivalent circuit of the inductive bridge, it is concluded that the higher the quality factor of the coil, the higher the detection sensitivity of the inductive bridge. The quality factor of the coil is mainly affected by N, w, d. To improve the detection sensitivity of the inductive bridge, it is possible to increase the coil diameter a and reduce w and d, and appropriately increase N. Based on this method, suitable sensing and reference coils are selected for the inductive bridge. In terms of the effect of velocity on the electromagnetic field: In the alternating magnetic field, the general law that velocity affects the inductance signal was obtained, which was verified by theoretical analysis and experimental phenomena in the magnetic field. The increased velocity will enhance the eddy current effect of the particles in the magnetic field, which will further increase the signal of non-ferromagnetic metal particles and weaken the signal of ferromagnetic metal particles. In terms of the effect of velocity on the processing circuit: We assumed that the velocity also affects the output signal of the processing circuit, due to the abnormal weakening of the detected signal. The conclusion is that the optimized processing circuit can suppress the instability of the output signal, which arises due to the variation of the particle velocity. This research is helpful to the development of oil online monitoring technology, which starts from the characteristics of high flow rate and high flux of oil in the mechanical systems. Future work will concentrate on optimizing the design of the detection circuit to stabilize the particle output signal at different velocities in the circuit. In addition, combined with the effect of speed on magnetic fields and circuits, we will find a balance point in the contradiction between the effect of velocity on ferromagnetic and non-ferromagnetic metals. Acknowledgments The authors wish to thank the financial support. The authors would also like to thank Dalian Maritime University for their support of this research. Author Contributions Conceptualization, W.L. and S.Y.; Data curation, S.Y., X.Z. and Y.X.; Formal analysis, C.B. and H.S.; Funding acquisition, W.L. and H.Z.; Investigation, Z.X.; Methodology, W.L., H.Z. and X.Z.; Project administration, W.L.; Resources, L.Z. and Y.S.; Software, S.Y. and Y.X.; Supervision, H.Z. and Y.S.; Validation, W.L. and S.Y.; Visualization, C.W. and Z.X.; Writing—original draft, W.L.; Writing—review & editing, W.L. and S.Y. All authors will be informed about each step of manuscript processing including submission, revision, revision reminder, etc. via emails from our system or assigned Assistant Editor. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic diagram of microfluidic chip sensing unit. Figure 2 Inductive bridge equivalent circuit. Figure 3 Effect of coil quality factor on bridge sensitivity. Figure 4 Schematic diagram of coil parameters. Figure 5 Schematic diagram of detection circuit system. Figure 6 Schematic diagram of cutting magnetic field lines in the direction of movement of metal particles. Figure 7 Experimental system diagram. Figure 8 Steady sampling signal for 350 μm iron particles. Figure 9 Noise signals at different velocities under no load. Figure 10 Comparison of signals at different velocities for 350 μm iron. Figure 11 Comparison of signals at different velocities for 350 μm copper. Figure 12 Comparison of signals at different velocities for 350 μm aluminum. Figure 13 Diagram of signal variation with velocity: (a) Variation of metal particle voltage amplitude affected by velocity, (b) Variation of the total signal amplitude of the metal particles with varying velocity. Figure 14 Terminal UAF42 low pass filter. Figure 15 Characteristic curves of low-pass filter circuits with different design parameters: (a) Large passband ripple, (b) Small passband ripple. Figure 16 Signal change of ferromagnetic metal particles (350 μm Fe) with velocity change after adjusting the detection circuit. Figure 17 Signal change of non-ferromagnetic metal particles (350 μm Cu) with velocity change after adjusting the detection circuit. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Towsyfyan H. Gu F. Ball A.D. Liang B. Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements Friction 2019 7 572 586 10.1007/s40544-018-0244-4 2. Wang T. Han Q. Chu F. Feng Z. Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review Mech. Syst. Signal Process. 2019 126 662 685 10.1016/j.ymssp.2019.02.051 3. Mohammed A. Djurovic S. Electric Machine Bearing Health Monitoring and Ball Fault Detection by Simultaneous Thermo-Mechanical Fibre Optic Sensing IEEE Trans. Energy Convers. 2021 36 71 80 10.1109/TEC.2020.3003793 4. Muthuvel P. George B. Ramadass G.A. A Highly Sensitive In-Line Oil Wear Debris Sensor Based on Passive Wireless LC Sensing IEEE Sens. J. 2021 21 6888 6896 10.1109/JSEN.2020.3036154 5. Jia R. Ma B. Zheng C. Ba X. Wang L. Du Q. Wang K. Comprehensive Improvement of the Sensitivity and Detectability of a Large-Aperture Electromagnetic Wear Particle Detector Sensors 2019 19 3162 10.3390/s19143162 6. Wang C. Bai C. Yang Z. Zhang H. Li W. Wang X. Zheng Y. Ilerioluwa L. Sun Y. Research on High Sensitivity Oil Debris Detection Sensor Using High Magnetic Permeability Material and Coil Mutual Inductance Sensors 2022 22 1833 10.3390/s22051833 35270986 7. De Azevedo H.D.M. Araújo A.M. Bouchonneau N. A review of wind turbine bearing condition monitoring: State of the art and challenges Renew. Sustain. Energy Rev. 2016 56 368 379 10.1016/j.rser.2015.11.032 8. Shi H. Zhang H. Huo D. Yu S. Su J. Xie Y. Li W. Ma L. Chen H. Sun Y. An Ultrasensitive Microsensor Based on Impedance Analysis for Oil Condition Monitoring IEEE Trans. Ind. Electron. 2022 69 7441 7450 10.1109/TIE.2021.3100982 9. Li Y. Yu C. Xue B. Zhang H. Zhang X. A Double Lock-in Amplifier Circuit for Complex Domain Signal Detection of Particles in Oil IEEE Trans. Instrum. Meas. 2022 71 1 10 10.1109/TIM.2021.3130926 10. Jakoby B. Scherer M. Buskies M. Eisenschmid H. An automotive engine oil viscosity sensor IEEE Sens. J. 2003 3 562 568 10.1109/JSEN.2003.817164 11. Shi H. Zhang H. Ma L. Sun Y. Chen H. Zhao X. Bai C. Zhang Y. Inductive-Capacitive Coulter Counting: Detection and Differentiation of Multi-Contaminants in Hydraulic Oil Using a Microfluidic Sensor IEEE Sens. J. 2021 21 2067 2076 10.1109/JSEN.2020.3016000 12. Birkin P.R. Youngs J.J. Truscott T.T. Martini S. Development of an optical flow through detector for bubbles, crystals and particles in oils Phys. Chem. Chem. Phys. 2022 24 1544 1552 10.1039/D1CP03655F 34940769 13. Park J. Yoo S.J. Yoon J. Kim Y.J. Inductive particle detection system for real-time monitoring of metals in airborne particles Sens. Actuators-Phys. 2021 332 113153 10.1016/j.sna.2021.113153 14. Koo H. Ahn H.S. Monitoring Inductance Change to Quantitatively Analyze Magnetic Wear Debris in Lubricating Oil Tribol. Lubr. 2016 32 189 194 10.9725/KSTLE.2016.32.6.189 15. Haiden C. Wopelka T. Jech M. Keplinger F. Vellekoop M.J. A Microfluidic Chip and Dark-Field Imaging System for Size Measurement of Metal Wear Particles in Oil IEEE Sens. J. 2016 16 1182 1189 10.1109/JSEN.2015.2501355 16. Zhang H. Chon C.H. Pan X. Li D. Methods for counting particles in microfluidic applications Microfluid. Nanofluid. 2009 7 739 10.1007/s10404-009-0493-7 32214956 17. Shi H. Bai C. Xie Y. Li W. Zhang H. Liu Y. Zheng Y. Zhang S. Zhang Y. Lu H. Capacitive–Inductive Magnetic Plug Sensor with High Adaptability for Online Debris Monitoring IEEE Trans. Instrum. Meas. 2022 71 1 8 10.1109/TIM.2022.3156981 18. Murali S. Jagtiani A.V. Xia X. Carletta J. Zhe J. A microfluidic Coulter counting device for metal wear detection in lubrication oil Rev. Sci. Instrum. 2009 80 016105 10.1063/1.3072665 19191466 19. Du L. Zhe J. A microfluidic inductive pulse sensor for real time detection of machine wear Proceedings of the 2011 IEEE 24th International Conference on Micro Electro Mechanical Systems Cancun, Mexico 23–27 January 2011 1079 1082 10.1109/MEMSYS.2011.5734616 20. Zhang X. Zhang H. Sun Y. Chen H. Zhang Y. Research on the Output Characteristics of Microfluidic Inductive Sensor J. Nanomater. 2014 2014 725246 10.1155/2014/725246 21. Ma L. Shi H. Zhang H. Li G. Shen Y. Zeng N. High-sensitivity distinguishing and detection method for wear debris in oil of marine machinery Ocean Eng. 2020 215 107452 10.1016/j.oceaneng.2020.107452 22. Li Y. Wu J. Guo Q. Design on Electromagnetic Detection Sensor on Wear Debris in Lubricating Oil Proceedings of the 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Auckland, New Zealand 20–23 May 2019 1 5 10.1109/I2MTC.2019.8826904 23. Davis J.P. Carletta J.E. Veillette R.J. Du L. Zhe J. Instrumentation circuitry for an inductive wear debris sensor Proceedings of the 10th IEEE International NEWCAS Conference Montreal, QC, Canada 17–20 June 2012 501 504 10.1109/NEWCAS.2012.6329066 24. Wu X. Zhang Y. Li N. Qian Z. Liu D. Qian Z. Zhang C. A New Inductive Debris Sensor Based on Dual-Excitation Coils and Dual-Sensing Coils for Online Debris Monitoring Sensors 2021 21 7556 10.3390/s21227556 34833634 25. Chady T. Enokizono M. Todaka T. Tsuchida Y. Yasutake T. Identification of three-dimensional distribution of metal particles using electromagnetic tomography system J. Mater. Process. Technol. 2007 181 177 181 10.1016/j.jmatprotec.2006.03.022 26. Bai C. Zhang H. Wang W. Zhao X. Chen H. Zeng N. Inductive-Capacitive Dual-Mode Oil Detection Sensor Based on Magnetic Nanoparticle Material IEEE Sens. J. 2020 20 12274 12281 10.1109/JSEN.2020.2985021 27. Zhu X. Du L. Zhe J. A 3 × 3 wear debris sensor array for real time lubricant oil conditioning monitoring using synchronized sampling Mech. Syst. Signal Process. 2017 83 296 304 10.1016/j.ymssp.2016.06.014 28. Jagtiani A.V. Carletta J. Zhe J. A microfluidic multichannel resistive pulse sensor using frequency division multiplexing for high throughput counting of micro particles J. Micromech. Microeng. 2011 21 065004 10.1088/0960-1317/21/6/065004 29. Bai C. Zhang H. Zeng L. Zhao X. Yu Z. High-Throughput Sensor to Detect Hydraulic Oil Contamination Based on Microfluidics IEEE Sens. J. 2019 19 8590 8596 10.1109/JSEN.2019.2922319 30. Wang X. Chen P. Luo J. Yang L. Feng S. Characteristics and Superposition Regularity of Aliasing Signal of an Inductive Debris Sensor Based on a High-Gradient Magnetic Field IEEE Sens. J. 2020 20 10071 10078 10.1109/JSEN.2020.2992110 31. Wu Y. Zhang H. Research on the effect of relative movement on the output characteristic of inductive sensors Sens. Actuators Phys. 2017 267 485 490 10.1016/j.sna.2017.10.004 32. Liu E. Zhang H. Wu Y. Fu H. Sun Y. Chen H. Effect of oil velocity on sensitivity of micron metal particle detection by inductive sensor Opt. Precis Eng. 2016 24 533 539 10.3788/OPE.20162403.0533 33. Zhang X. Zeng L. Zhang H. Huang S. Magnetization Model and Detection Mechanism of a Microparticle in a Harmonic Magnetic Field IEEE ASME Trans. Mechatron. 2019 24 1882 1892 10.1109/TMECH.2019.2928704 34. Xie Y. Zhang H. Shi H. Zhang Y. Frequency Research of Microfluidic Wear Debris Detection Chip Based on Inductive Wheatstone Bridge Proceedings of the 2021 IEEE 16th International Conference on Nano/Micro Engineered and Molecular Systems (NEMS) Xiamen, China 25–29 April 2021 780 785 10.1109/NEMS51815.2021.9451371 35. Xie Y. Shi H. Zhang H. Yu S. Llerioluwa L. Zheng Y. Li G. Sun Y. Chen H. A Bridge-Type Inductance Sensor with a Two-Stage Filter Circuit for High-Precision Detection of Metal Debris in the Oil IEEE Sens. J. 2021 21 17738 17748 10.1109/JSEN.2021.3085361 36. Jia R. Ma B. Zheng C. Wang L. Ba X. Du Q. Wang K. Magnetic Properties of Ferromagnetic Particles under Alternating Magnetic Fields: Focus on Particle Detection Sensor Applications Sensors 2018 18 4144 10.3390/s18124144 37. Li J. Kong M. Xu C. Wang S. Fan Y. An Integrated Instrumentation System for Velocity, Concentration and Mass Flow Rate Measurement of Solid Particles Based on Electrostatic and Capacitance Sensors Sensors 2015 15 31023 31035 10.3390/s151229843 26690434

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093471 sensors-22-03471 Article Rapid Post-Earthquake Structural Damage Assessment Using Convolutional Neural Networks and Transfer Learning https://orcid.org/0000-0002-5607-9307 Ogunjinmi Peter Damilola 1 Park Sung-Sik 2 https://orcid.org/0000-0003-4226-7435 Kim Bubryur 3* https://orcid.org/0000-0001-9205-3836 Lee Dong-Eun 1* Guo Qing Academic Editor 1 School of Architecture, Civil, Energy, and Environment Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Korea; peterogunjinmi@knu.ac.kr 2 Department of Civil Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Korea; sungpark@knu.ac.kr 3 Department of Robot and Smart System Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Korea * Correspondence: brkim@knu.ac.kr (B.K.); dolee@knu.ac.kr (D.-E.L.); Tel.: +82-53-950-4571 (B.K.); +82-53-950-7540 (D.-E.L.) 03 5 2022 5 2022 22 9 347129 3 2022 28 4 2022 © 2022 by the authors. 2022 https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The adoption of artificial intelligence in post-earthquake inspections and reconnaissance has received considerable attention in recent years, owing to its exponential increase in computation capabilities and inherent potential in addressing disadvantages associated with manual inspections. Herein, we present the effectiveness of automated deep learning in enhancing the assessment of damage caused by the 2017 Pohang earthquake. Six classical pre-trained convolutional neural network (CNN) models are implemented through transfer learning (TL) on a small dataset, comprising 1780 manually labeled images of structural damage. Feature extraction and fine-tuning TL methods are trained on the image datasets. The performances of various CNN models are compared on a testing image dataset. Results confirm that the MobileNet fine-tuned model offers the best performance. Therefore, the model is further developed as a web-based application for classifying earthquake damage. The severity of damage is quantified by assigning damage assessment values, derived using the CNN model and gradient-weighted class activation mapping. The web-based application can effectively and automatically classify structural damage resulting from earthquakes, rendering it suitable for decision making, such as in resource allocation, policy development, and emergency response. transfer learning convolutional neural network earthquake image classification damage detection National Research Foundation of Korea (NRF)Korean government (MSIT)NRF-2018R1A5A1025137 This work was supported by a National Research Foundation of Korea (NRF) grant, funded by the Korean government (MSIT) (No. NRF-2018R1A5A1025137). ==== Body pmc1. Introduction Classification of the magnitude of damage to buildings and infrastructure attributed to seismic events is essential for enhancing post-earthquake reconnaissance and ensuring safe and effective recovery efforts. Conventionally, property damage attributed to earthquakes is documented manually using labor-intensive methods [1,2,3,4,5]. Manual damage inspections may be time consuming and involve arbitrary judgment by a novice inspector who may not be adequately trained. These disadvantages can be addressed by performing fully automated inspections using computer-vision technologies [6]. The automated deep learning (DL) method may be critical for enabling the rapid real-time detection and classification of structural damage (SD) attributed to earthquakes. DL algorithms for image classification may be applicable for assessing SDs [6,7,8,9,10,11]. Gao and Mosalam [6] created an image database known as “Structural ImageNet,” which implements a visual geometry group (VGG) convolutional neural network (CNN) model through transfer learning (TL) to classify SD caused by earthquakes. They curated the Pacific Earthquake Engineering Research (PEER) Hub ImageNet [12] dataset, which serves as a benchmark for similar computer-vision-based classification and detection tasks [13]. Nahata et al. [7] employed the VGG16 TL model to classify post-earthquake building damage into four categories. After training the model with more than 1,200 images, they obtained training and validation accuracies of 97.85% and 89.38%, respectively. In addition, DL methods have been exploited for damage-detection tasks, in which bounding boxes are used to identify and localize SD [14,15]. Decision makers can allocate the appropriate resources to retrofit, repair, and recover facilities by locating and quantifying SDs. A numerical scale that quantifies the magnitude of SD to facilitate such efforts has been established. Li et al. [16] identified a mismatch in the damage detected using conventional approaches. They proposed a novel approach to quantify the severity of SD, using a smooth image heat map based on gradient-weighted class activation mapping (Grad-CAM). In fact, this approach has been employed in several applications, such as post-disaster damage assessments [10] and steel frame damage investigations [17], and demonstrated performances superior to or comparable with other state-of-the-art methods, while requiring low computation time. We employed the approach to quantify and locate SD caused by the 2017 Pohang earthquake using CNN based on TL strategies. Through TL, CNN models can learn complex patterns from data without needing a large amount of training data. Additionally, they can generalize well to new datasets, which is important when dealing with SD that may vary in appearance from one instance to another. Therefore, the performance of Feature Extraction (FE) and Fine Tuning (FT) TL methods on SD image datasets were compared, in order to explore the possibility of applying the knowledge from a pre-trained model (source domain) to another (target domain), by tuning some of the model parameters. Finally, the optimal CNN model used to implement the approach was deployed on an interactive webpage that automatically classifies SD caused by earthquakes. Invisible damage, which is beyond the scope of this study, is typically examined via anomaly detection in structural members using specialized sensors and signal-processing techniques. However, in the abovementioned study, damage was considered visible to either the human eye or computer vision. This novel approach can facilitate rapid responses following an earthquake. Researchers have successfully identified SD characteristics using classification [6,7], bounding box detection [8], and segmentation techniques [9]. However, most of those methods do not involve a tool with a post-disaster assessment framework that is accessible to the structural engineering community. Moreover, only a few studies have considered the deployment of post-earthquake damage classification, rendering it less useful for industrial applications and field validation. By contrast, both object localization with Grad-CAM and model deployment for practical applications are considered in the current study. This novel approach is relevant to researchers and practitioners as it fills the research gap by providing an interactive tool for SD assessment. The remainder of this paper is organized as follows: Section 2 presents a brief overview of related studies. Section 3 describes the data acquisition process and methodology, and Section 4 discusses the results of the CNN model training, damage localization, and quantification. Section 5 presents an interactive webpage for damage classification, and Section 6 presents the conclusions and future research directions. The workflow of the research method is shown in Figure 1. 2. Related Studies This section provides a brief overview of existing studies related to the current study. A comprehensive review of the applications of computer-vision-based civil infrastructure inspection has recently been presented [18]. Pan and Yang [8] implemented an object detection algorithm to quantify damage to structural elements and the associated repair costs. Their proposed algorithm achieved average precisions of 98.2% and 84.5% on the training and testing image datasets, respectively. For automated post-earthquake inspection, Hoskere et al. [9] proposed a multiscale deep CNN, incorporating ResNet23 and VGG19 as damage classifiers and damage segmenters, which achieved accuracies of 88.8% and 71.4%, respectively. Liang [11] investigated an image-based approach for inspecting bridges by considering system, component, and local damage level detection. The proposed DL network comprises a pre-trained VGG-16 CNN for system-level failure classification, a faster region-based CNN for component-level bridge column detection, and a fully convolutional network for damage segmentation. Bayesian optimization enhanced the model performance and afforded an accuracy exceeding 90% for all the three-level tasks considered. Some disadvantages in the existing multiclass damage assessment approach mentioned earlier include dataset class imbalance, which results in overfitting, lack of scalability and flexibility of the CNN architecture for solving various challenges, noisy training data, and a complex CNN architecture [19]. Therefore, recent applications of CNN-based models for SD assessments focus more on quality data preparation, the algorithmic optimization of the CNN model architecture, and damage quantification. Techniques typically adopted for quality image data preparation include image enhancement approaches, such as gray-level thresholding, histogram equalization, and adaptive histogram equalization [20]. Moreover, the algorithmic optimization of hyperparameters enhances the accuracy of CNN-based models and reduces the computational power used for execution [21]. Recently, Kim et al. [22] developed an optimized LeNet (OLeNet) model by tuning a shallow LeNet-5 CNN architecture for concrete surface crack detection. Consequently, OLeNet achieved an optimum validation accuracy of 99.8% at 19 epochs within 220 s of model training. Meanwhile, pre-trained deep CNN architectures, including ResNet, VGG16, and Inception, required at least 45 epochs to achieve the same validation accuracy within 524 s. 3. Methodology 3.1. Data Acquisition, Division, and Preprocessing A total of 2750 images were acquired from field investigations [1,2,3,4,5] for different earthquakes. This study focuses on the Pohang earthquake. However, data obtained from other earthquakes were used to build a robust model to increase generalizability. A summary of the image datasets is presented in Table 1. Light damage indicates hairline cracks in structural elements, whereas moderate damage indicates wider cracks and spalling in concrete. By contrast, severe damage represents elemental collapse or structural failure [23]. The methodology involves a supervised learning image classification problem. Therefore, the labeled image dataset was split into two to train and evaluate the model’s performance after each epoch. The ratio of the training and validation sets was empirically set at 4:1. In addition, the validation datasets were used to test the training performance of the models after each epoch. A total of 1780 images were selected from the database, of which 1600 were used for training and validation (Table 2). To address the data imbalance during model training, each damage class was penalized by assigning class weights of 1.0, 1.5, 1.5 and 2.4 to the severe, light, moderate, and no damage classes, respectively. A total of 180 images were obtained exclusively from the damage database of the Pohang earthquake and these were used to evaluate the generalizability of the trained model. Figure 2 shows a sample of 1600 images selected to train the CNN model. 3.2. TL Using Pre-Trained CNN Models Six pre-trained classical CNN setups were implemented via TL. TL is an efficient approach used for training a small dataset, whereby a neural network pre-trained on a large dataset in the source domain is applied to the target domain. The underlying hypothesis of TL is that common features learned from a sufficiently large dataset are transferred to different datasets [24]. For practical applications, two strategies are used while conducting TL in deep CNNs: feature extraction (FE) and FT. We used FE and FT TL methods to train the models on the datasets. In the FE method, the fully connected layers are removed from a network that has been pre-trained on the ImageNet dataset, while maintaining the convolutional base as a feature extractor. The pre-trained network serves as an arbitrary feature extractor that performs convolutional operations once on the input image during forward propagation, stops at the pre-specified layer, and uses the outputs of that layer as bottleneck features. In summary, the pre-trained CNN models serve as the backbone for FE, in which all the parameters in the convolution layers are frozen, whereas the fully connected layers are updated during backpropagation [25]. However, the FT method requires the unfreezing and retraining of the pre-trained convolutional base through backpropagation. During retraining, the convolutional layers learn mid- to high-order features, such as edges, which are more specific to the dataset in the target domain than the more generic features from the dataset in the source domain. Because the parameters in the last convolutional layer are unfrozen and updated during backpropagation, FT typically requires more computational time than FE. The procedures for TL using FE and FT are shown in Figure 3. Similar studies using the TL approach for SD assessment include real-time crack detection using unmanned aerial vehicles [24], building defect detection [26], concrete bridge surface damage detection [27], and crack segmentation on masonry surfaces [28]. Well-established versions of VGGNet are VGG16 (16 layers) and VGG19 (19 layers), which contain 138 and 144 million parameters, respectively. The VGGNet architecture comprises five convolutional blocks, with each block containing two or more convolutional layers and a max-pooling layer. ReLU activation functions are provided in all hidden layers, and the output comprises three fully connected layers with softmax functions. Applications of pre-trained VGGNets through TL include crack detection [29], bolt-loosening detection [30], steel damage condition assessment [31], building defect detection [26], and post-earthquake SD assessment [6,7]. The inception network is engineered significantly for performance improvement and has a relatively lower error rate compared with VGGNet. Different versions of the inception modules that have evolved include V1, V2, V3, and V4. Within the inception block, parallel filter operations are applied to the input from the previous layer, followed by depth-wise concatenation of the filter outputs. Previous applications of inception networks in image classification include crack detection [32] and tunnel rock structure identification [33]. Xception is an extension of inceptionV3, where the convolutional layers are replaced with depth-wise separable convolutions. It comprises blocks of convolution and separable convolution followed by batch normalization and max-pooling layers. Use cases of Xception include aerial visual geolocalization [34] and construction site safety [35]. ResNet is a deep neural network that is based on residual learning. ResNet50 comprises 50 main layers and 177 layers, whereas ResNet101 comprises 101 main layers and a total of 347 layers. ResNet has been successfully applied to bridge component extraction [36] and road crack detection [37]. MobileNet comprises a class of efficient models based on depth-wise separable convolutions, which are widely used for mobile applications. The MobileNet block typically comprises batch normalization, 3 × 3 depth-wise convolution, 1 × 1 convolution layers, and ReLU activation. Because MobileNets have fewer parameters and a higher classification accuracy, they are typically adopted to build lightweight deep neural networks. MobileNet is used for road damage detection [38] and post-hurricane aerial damage assessment [39]. The pseudocode of the algorithm for the CNN model is presented in Table 3. Each model was trained with an SGD optimizer on a high-performance computer with an Intel (R) Core i7-8700 CPU @ 3.20 GHz, 32 GB RAM, and an NVIDIA RTX Quadro 5000 GPU in a Keras/TensorFlow environment. A preliminary experiment was performed on the dataset based on a learning rate of 0.0001, a momentum set of 0.9, and a batch size of 32 images. The number of training epochs was set to 60 for all the experiments, and the images were resized to 224 × 224 × 3 before training. The validation set was used to tune the hyperparameters and optimize the weights of the CNN model. During FT, only the final convolutional block of the pre-trained model was retrained. In addition, a dropout rate of 0.5 was used between fully connected dense layers to reduce overfitting. To avoid overfitting problems, data augmentation techniques such as image cropping, standardization, random shifts, and horizontal image flips were implemented during model training. The properties of the pre-trained CNN models considered in this study are listed in Table 4. 4. Results and Discussion Several experiments were performed to establish the performance of the 12 CNN models on image datasets. The potential of both FE and FT TL methods for structural image classification is analyzed in this section. 4.1. FE with Bottleneck Features Figure 4a,b show the FE results of FE using the six pre-trained models. The pre-trained MobileNet CNN model exhibited training and validation accuracies of approximately 59% and 58.4%, respectively. Thus, it outperformed all the other models. Notably, the ResNet50 model demonstrated categorically unsatisfactory performance compared with the other models, indicating that the architecture of the ResNet50 model was deeper and more difficult to train than those of the other models. Similarly, the VGG16 and VGG19 models demonstrated unsatisfactory performance, which might be due to their shallow architectures. However, the superior accuracy of MobileNet suggests that it is the best model for mobile application development. 4.2. FT The FT results for the six pre-trained models are shown in Figure 5a,b. Similarly, the pre-trained MobileNet CNN model outperformed the other models in terms of its training and validation accuracies of approximately 73.4% and 71.8%, respectively. 4.3. Comparison between FE and FT The FT method performed better than the FE method for all models and datasets considered in this study. However, the FT method is computationally expensive because it involves retraining one convolutional block. Figure 6 shows the training and validation accuracies for each model implemented through TL. The results of the testing accuracy analyses for all the models are presented as bar charts in Figure 7. 4.4. Comparative Study: Effect of Dataset Size on Fine-Tuned Model Because DL models are generally data intensive, the effect of data size on the performance of the fine-tuned MobileNet model was examined by gradually increasing the amount of training image data (Figure 8). An increase in the number of training images considerably affected the performance of the model (Figure 9). For example, the testing accuracies of the fine-tuned MobileNet model for datasets A, B, and C were 88.3%, 90.6%, and 95.6%, respectively. Thus, we infer that adding more training data to the model can improve its validation accuracy. Moreover, this is consistent with the findings of [6], which suggests that increasing the data and fine-tuning the convolutional blocks can improve the model performance. The fine-tuned MobileNet CNN model, which exhibited optimal performance with a testing accuracy of 88.3%, was selected for deployment in a web-based application for earthquake-damage classification. Figure 10 shows plots of the confusion matrix used to evaluate the model performance of the testing images. To assess the performance of the fine-tuned MobileNet CNN model, the testing accuracy was compared with those of various CNN architectures used for similar SD classification tasks. A comparison of the different models with the optimal model is presented in Table 5. Accuracy can be expressed as the ratio of the true predictions to the total predicted cases in the dataset. The precision metric measures the classifier’s ability to correctly identify positive classes. The recall metric is the ratio of positive instances that are correctly detected by the classifier to the total number of positive instances. The mathematical expressions for accuracy, precision, recall, and F1 score are shown in Equations (1a)–(1d), respectively. (1a) Accuracy = TP + TNTP + TN + FP + FN (1b) Precision = TPTP + FP (1c) Recall = TPTP + FN (1d) F1 = 2 × precision × recallprecision + recall = TPTP + FN + FP2 where TP = number of true positives, TN = number of true negatives, FP = number of false positives, and FN = number of false negatives. The proposed model was trained on datasets containing images of all structural members similar to those used by Gao and Mosalam [6], which involve extremely noisy backgrounds. However, the dataset considered by Pan and Yang [8] contained only images of reinforced concrete structural columns with less background noise; hence, their approach afforded higher accuracy. A sample of the testing images with predictions obtained from the fine-tuned MobileNet model is shown in Figure 11. Despite the varying inclination of the camera view and light intensity of the images, the model successfully predicted the SD classes, with extremely few instances of incorrect predictions. For example, it predicted light damage in two cases, as shown in Figure 9b, instead of the ground truth, which indicates moderate damage. This misclassification can be attributed to the overlapping of hairline cracks (light damage) and wide cracks (moderate damage) in the images. Similarly, moderate damage was occasionally misclassified as severe damage, which might be attributed to background noise, such as the presence of iron bars and large window voids in the images. Hence, a more robust bounding box object-detection technique or other forms of damage localization in the model should be considered to overcome this deficiency. The accuracy of computer-vision-based SD assessment is mainly affected by the complexity of the structure and damage. The damage assessment results can be affected by the varying lighting conditions, occlusion, and insufficient known reference points on a damaged structure that can be used for comparison with pre-damage images to accurately assess damage levels. Moreover, SD caused by debris and rubble can often be difficult or impossible to detect using computer-vision algorithms alone. 4.5. Visualization and Localization of Damage Using Grad-CAM Grad-CAM is a visualization technique that visualizes and clarifies predictions from large classes of CNNs to render them more transparent. Initially published by Selvaraju et al. [40], Grad-CAM uses the gradient of the target concept in the last convolution layer to create an approximate localization map that highlights the areas of interest to predict the concept. Grad-CAM was used to extract gradients from the fine-tuned MobileNet CNN model in the final convolutional layer to generate localization maps that identify relevant regions in the test images. This visualization technique is advantageous over the conventional bounding-box method, which is subjective as it requires manual annotations. The heat maps generated via Grad-CAM exhibit smooth boundaries, which provide insight into the precise location of defects or damage in the SD images. Figure 12 shows representative images from different SD classes localized using the Grad-CAM and guided Grad-CAM methods. The mislocalization of the moderate damage image (in Figure 12b) is attributed to the lower predicted probability (88.83%) for this image compared with the light (98.13 %) and severe (97.29 %) damage images. 4.6. Damage Severity Measurement Following the approach of Li et al. [16], damage severity was quantified by assigning a damage assessment value (DAV) obtained from Grad-CAM-based damage detection map (DDM). Mathematically, for an input image x with output damage class yD of the VGG19 CNN model, the gradient-based weight parameter wk is the aggregate of gradients in y with respect to fk(i,j) for i and j, and is expressed as follows:(2) wk = 114 × 14 ∑i,j∂yD∂fi,jk, where fk(i,j) is the k-th feature map in the last convolutional layer (which measures 14 × 14 × 512 in this study), i = 1, …, 14, j = 1, …, 14, and k = 1, …, 512. For feature maps fk and the corresponding weights wk, a 14 × 14 matrix S can be defined as (3) si,j = ReLU(∑kwkfi,jk), where ReLU() eliminates the effects of negative values and emphasizes positive values. In the DDM, numerical values are assigned to quantify the damage severity based on the pixel intensity. Higher pixel intensities reflect more severe damage and are represented by a heat map in the DDM. The average numerical values obtained from the heat map of an image are regarded as the overall DAV, which quantifies the damage severity of the image. Hence, a high DAV indicates severe damage and is defined as follows:(4) DAV = 114 × 14 ∑ksi,j, where si,j represents the elements in matrix S, and the dimensions of S are 14 × 14. The DAV ranges between 0 (no damage) and 1 (total collapse). An annotation tool, known as LabelMe [41], accessible at http://labelme.csail.mit.edu, is used to annotate the SD images manually. The numerical values are assigned as follows: no damage = 0, light damage = 0.25, moderate damage = 0.5, severe damage = 0.75, and total collapse = 1 [42]. The annotated sample images are shown in Figure 13, along with their corresponding severity values. 5. Development of CNN Model as Interactive Web Application Access to trained DL/machine learning models in portable and interactive formats can facilitate real-time practical damage assessments. As shown in Figure 14, the optimal earthquake damage classifier model is converted to a Tensorflow.js compatible format and deployed as a web application with an easy-to-use graphic user interface. Tensorflow.js, built on the Tensorflow framework, facilitates the conversion of machine learning models to JavaScript formats, accessible through web browsers [43]. In addition to the superior accuracy of the optimal MobileNet CNN model, its lightweight size renders it the best model among all the trained models. An interactive web application is a useful tool that allows users to upload SD images and rapidly determine the class of SD with the corresponding confidence level of prediction. The prediction probability is computed based on the softmax function, as shown in Equation (5). (5) P(yi) = expyi∑j = 1nexpyj, where P(yi) is the prediction probability of class i, yi is the output score for class i, and n is the number of classes. The trained CNN model is accessible to web browsers at https://bit.ly/3hXRyyc. This allows emergency responders to rapidly assess post-earthquake damage and make informed decisions regarding resource allocation. In addition, users can upload images captured at ground level from different sources to identify the SD and further validate the performance of the proposed earthquake-damage-classifier model. 6. Conclusions and Recommendations Artificial intelligence for post-earthquake inspections and reconnaissance has recently received significant attention, owing to its exponential increase in computational capabilities and the inherent potential of artificial intelligence to address the disadvantages associated with manual inspections, including subjectivity. In this study, we used data from the 2017 Pohang earthquake to demonstrate the potential of automated DL for rapid and accurate inspections of post-earthquake damage with insignificant human input. Our key findings are as follows:The FT method outperformed the FE method for all the CNN models evaluated. However, the FT method is more computationally complex than the FE method because it involves retraining one convolutional block. The MobileNet model exhibited the best performance for both the FE and FT TL methods, exhibiting testing accuracies of 76.1% and 88.3%, respectively. The superiority of the MobileNet model in performing classification promoted its deployment as a web-based application for earthquake-damage classification. The web application successfully predicted the damage class in new images of seismic damage with high certainty. In addition, interactive web pages can rapidly and automatically classify SD from earthquakes, thereby facilitating decision making in response to earthquakes. In this study, we demonstrated the potential of automated DL to facilitate post-earthquake damage inspections and surveys. Despite the limitations of this study, including the lack of a large and sophisticated training dataset and the complexity of the four damage classes, future studies will be conducted that focus on establishing a large benchmark dataset with high-quality annotations, such as the PEER Hub ImageNet [12]. In addition, future experiments, involving unmanned aerial vehicles, will be performed to capture real-time images from SD sites that can be sent to a webpage interface for fully automated damage assessment. Author Contributions Conceptualization, P.D.O., S.-S.P. and B.K.; methodology, P.D.O. and S.-S.P.; software, P.D.O.; validation, P.D.O. and B.K.; data curation, P.D.O.; writing—original draft preparation, P.D.O.; writing—review and editing, P.D.O., S.-S.P., B.K. and D.-E.L.; visualization, P.D.O.; supervision, S.-S.P., B.K. and D.-E.L.; project administration, B.K. and D.-E.L.; funding acquisition, D.-E.L. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Abbreviations The abbreviations used in this manuscript are as follows: CNN Convolutional neural network DAV Damage assessment value DDM Damage detection map DL Deep learning FE Feature extraction FT Fine-tuning GPU Graphic processing unit Grad-CAM Gradient-weighted class activation mapping OLeNet Optimized LeNet PEER Pacific Earthquake Engineering Research ReLU Rectified linear unit SD Structural damage TL Transfer learning VGG Visual geometry group Figure 1 Workflow of the research method used in current study. Figure 2 Samples used for training images for each damage class: (a) no, (b) light, (c) moderate, and (d) severe damage. Figure 3 Procedure for TL using (a) FE and (b) FT. Figure 4 Plots of accuracy for models trained using FE TL: (a) training and (b) validation. Figure 5 Plots of accuracy for models trained using FT TL: (a) training and (b) validation. Figure 6 Training and validation accuracies of various CNN models implemented through TL: (a) VGG16, (b) VGG19, (c) Inception, (d) MobileNet, (e) ResNet50, and (f) Xception models. Figure 7 Bar charts showing testing accuracies for (a) FT and (b) FE of CNN models. Figure 8 Summary of training and validation datasets for comparative study. Figure 9 Bar charts showing testing accuracies for datasets A, B, and C using fine-tuned MobileNet CNN model. Figure 10 Confusion matrix for the fine-tuned MobileNet CNN model. Figure 11 Sample testing images of structural damage with predicted probability for cases of (a) correct and (b) incorrect predictions. Figure 12 Representative images illustrating damage visualization and localization analyses via gradient-weighted class activation mapping (Grad-CAM) methods for images of (a) light, (b) moderate, and (c) severe damage. Figure 13 Sample images with annotations for severity and corresponding damage assessment value (DAV) scores for images of (a) light damage, (b) moderate damage, and (c) severe damage. Figure 14 Graphical user interface for web-based application that integrates optimal MobileNet damage classifier model. sensors-22-03471-t001_Table 1 Table 1 Categorized summary of the image dataset. Image Source No Damage Light Damage Moderate Damage Severe Damage Pohang (2017) [4] 49 294 187 551 Haiti (2010) [1] 52 55 174 127 Nepal (2015) [3] 152 153 123 255 Taiwan (2016) [2] 3 99 27 34 Ecuador (2016) [5] 4 108 115 188 Total 260 709 626 1155 sensors-22-03471-t002_Table 2 Table 2 Categorized summary of images in training, validation, and testing datasets. Image No Damage Light Damage Moderate Damage Severe Damage Training 160 320 320 480 Validation 40 80 80 120 Testing 45 45 45 45 Total 245 445 445 645 sensors-22-03471-t003_Table 3 Table 3 CNN model algorithm pseudocode. CNN Algorithm Programming language used for implementation: Python. Libraries for CNN model building: Tensorflow and Keras. Libraries used for image augmentation: OpenCV and computer vision library. Libraries used for visualizations: Matplotlib and 2D graph tool. 1. Let X be the input image of the batch and y be the label for the image X. 2. Extract features from the image using a CNN algorithm. Freeze all the pretrained convolutional blocks to serve as a feature extractor or fine tune by unfreezing the last convolutional blocks. Obtain feature maps of the first layer a0 after passing the image into the convolution layer with 7 × 7 filters and apply batch normalization function along with ReLU function. Apply the global average pooling function to the output tensor a0. Flatten the output to obtain a feature vector. 3. Execute the feature classification network on the feature vector. Initialize the weight w and bias b arrays of the linear network comprising 256 neural nodes. Add 50% dropout to serve as a regularizer and reduce overfitting. Perform z = w. afeature + b. Perform ReLU activation function al = max (z, 0). Initialize weight w and bias b arrays of linear network with four neural nodes. Perform z = w. al + b. Perform ReLU activation function al = max (z, 0). Apply softmax function on al to obtain the probability distribution of the four classes: no, light, moderate, and severe damage. sensors-22-03471-t004_Table 4 Table 4 Comparison of proposed pre-trained CNN models. Model No. of Parameters Depth of Layers Size (MB) VGG16 138.4 M 16 528 VGG19 143.7 M 19 549 Inception 23.9 M 189 92 Xception 22.9 M 81 88 ResNet 25.6 M 107 98 MobileNet 4.3 M 55 16 sensors-22-03471-t005_Table 5 Table 5 CNN-based SD classification models compared with current study. Task Description Algorithm Accuracy (%) * Precision (%) * Recall (%) References Classification of damage in all structural members VGG16 68.8 - - [6] Classification of damage in columns only ResNet50 87.47 - - [8] Classification of damage in all structural members MobileNet 88.3 89 88.2 Current work * Values are not provided in the referenced study. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Lowes L. DesRoches R. Eberhard M. Parra-Montesinos G. NSF RAPID: Collection of Damage Data Following Haiti Earthquake (NEES-2010-0872) 2017 Available online: https://datacenterhub.org/resources/14372 (accessed on 21 August 2020) 2. NCREE Purdue University Performance of Reinforced Concrete Buildings in the 2016 Taiwan (Meinong) Earthquake 2016 Available online: https://datacenterhub.org/resources/14098 (accessed on 21 August 2020) 3. Shah P. Pujol S. Puranam A. Laughery L. Database on Performance of Low-Rise Reinforced Concrete Buildings in the 2015 Nepal Earthquake Purdue University Research Repository Lafayette, IN, USA 2015 Available online: https://datacenterhub.org/resources/238 (accessed on 21 August 2020) 4. Sim C. Laughery L. Chiou T.C. Weng P. 2017 Pohang Earthquake-Reinforced Concrete Building Damage Survey 2018 Available online: https://datacenterhub.org/resources/14728 (accessed on 21 August 2020) 5. Sim C. Villalobos E. Smith J.P. Rojas P. Pujol S. Puranam A.Y. Laughery L. Performance of Low-Rise Reinforced Concrete Buildings in the 2016 Ecuador Earthquake 2016 Available online: https://datacenterhub.org/resources/14160 (accessed on 21 August 2020) 6. Gao Y. Mosalam K.M. Deep transfer learning for image-based structural damage recognition Comput. Aid. Civ. Infrastruct. Eng. 2018 33 748 768 10.1111/mice.12363 7. Nahata D. Mulchandani H. Bansal S. Muthukumar G. Post-earthquake assessment of buildings using deep learning arXiv 2019 1907.07877 8. Pan X. Yang T.Y. Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks Comput. Aided Civ. Infrastruct. Eng. 2020 35 495 510 10.1111/mice.12549 9. Hoskere V. Narazaki Y. Hoang T.A. Spencer B.F. Jr. Vision-based structural inspection using multiscale deep convolutional neural networks Proceedings of the 3rd Huixian International Forum on Earthquake Engineering for Young Researchers Urbana-Champaign, IL, USA 11–12 August 2012 10. Zhai W. Peng Z.R. Damage assessment using Google street view: Evidence from hurricane Michael in Mexico Beach, Florida Appl. Geogr. 2020 123 102252 10.1016/j.apgeog.2020.102252 11. Liang X. Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization Comput. Aided Civ. Infrastruct. Eng. 2019 34 415 430 10.1111/mice.12425 12. Gao Y. Mosalam K.M. PEER Hub ImageNet (Ø-Net): A Large-Scale Multi-Attribute Benchmark Dataset of Structural Images Report No. 2019/07 Earthquake Engineering Research Center Headquarters at the University of California Berkeley, CA, USA 2019 10.1061/(ASCE)ST.1943-541X.0002745 13. Naser M.Z. Kodur V. Thai H.T. Hawileh R. Abdalla J. Degtyarev V.V. StructuresNet and FireNet: Benchmarking databases and machine learning algorithms in structural and fire engineering domains J. Build. Eng. 2021 44 102977 10.1016/j.jobe.2021.102977 14. Cha Y.J. Choi W. Büyüköztürk O. Deep learning-based crack damage detection using convolutional neural networks Comput. Aided Civ. Infrastruct. Eng. 2017 32 361 378 10.1111/mice.12263 15. Ghosh Mondal T.G. Jahanshahi M.R. Wu R.T. Wu Z.Y. Deep learning-based multi-class damage detection for autonomous post-disaster reconnaissance Str. Control Health Monit. 2020 27 e2507 10.1002/stc.2507 16. Li X. Caragea D. Zhang H. Imran M. Localizing and quantifying infrastructure damage using class activation mapping approaches Soc. Netw. Anal. Min. 2019 9 44 10.1007/s13278-019-0588-4 17. Kim B. Yuvaraj N. Park H.W. Preethaa K.R.S. Pandian R.A. Lee D. Investigation of steel frame damage based on computer vision and deep learning Autom. Constr. 2021 132 103941 10.1016/j.autcon.2021.103941 18. Spencer B.F. Hoskere V. Narazaki Y. Advances in computer vision-based civil infrastructure inspection and monitoring Engineering 2019 5 199 222 10.1016/j.eng.2018.11.030 19. Sony S. Dunphy K. Sadhu A. Capretz M. A Systematic Review of Convolutional Neural Network-Based Structural Condition Assessment Techniques Eng. Struct. 2021 226 111347 10.1016/j.engstruct.2020.111347 20. Kim B. Serfa Juan R.O.S. Lee D.-E. Chen Z. Importance of image enhancement and CDF for fault assessment of photovoltaic module using IR thermal image Appl. Sci. 2021 11 8388 10.3390/app11188388 21. Kim B. Yuvaraj N. Sri Preethaa K.R. Santhosh R. Sabari A. Enhanced pedestrian detection using optimized deep convolution neural network for smart building surveillance Soft Comput. 2020 24 17081 17092 10.1007/s00500-020-04999-1 22. Kim B. Yuvaraj N. Sri Preethaa K.R. Arun Pandian R. Surface crack detection using deep learning with shallow CNN architecture for enhanced computation Neural Comput. Appl. 2021 33 9289 9305 10.1007/s00521-021-05690-8 23. ATC-58 Development of next Generation Performance-Based Seismic Design Procedures for New and Existing Buildings. ATC 2007 Redwood City, CA, USA Available online: https://www.atcouncil.org (accessed on 28 March 2022) 24. Yuvaraj N. Kim B. Preethaa K.R.S. Transfer learning based real-time crack detection using unmanned aerial system Int. J. High-Rise Build. 2020 9 351 360 10.21022/IJHRB.2020.9.4.351 25. Dhanamjayulu C. Nizhal U.N. Maddikunta P.K.R. Gadekallu T.R. Iwendi C. Wei C. Xin Q. Identification of malnutrition and prediction of BMI from facial images using real-time image processing and machine learning IET Image Process. 2022 16 647 658 10.1049/IPR2.12222 26. Perez H. Tah J.H.M. Mosavi A. Deep learning for detecting building defects using convolutional neural networks Sensors 2019 19 3556 10.3390/s19163556 27. Zhang C. Chang C.-C. Jamshidi M. Concrete bridge surface damage detection using a single-stage detector Comput. Aided Civ. Infrastruct. Eng. 2020 35 389 409 10.1111/mice.12500 28. Dais D. Bal İ.E. Smyrou E. Sarhosis V. Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning Autom. Constr. 2021 125 103606 10.1016/j.autcon.2021.103606 29. Dung C.V. Anh L.D. Autonomous concrete crack detection using deep fully convolutional neural network Autom. Constr. 2019 99 52 58 10.1016/j.autcon.2018.11.028 30. Zhang Y. Sun X. Loh K.J. Su W. Xue Z. Zhao X. Autonomous bolt loosening detection using deep learning Str. Health Monit. 2019 19 105 122 10.1177/1475921719837509 31. Liu H. Zhang Y. Image-driven structural steel damage condition assessment method using deep learning algorithm Measurement 2019 133 168 181 10.1016/j.measurement.2018.09.081 32. Ali L. Alnajjar F. Jassmi H.A. Gocho M. Khan W. Serhani M.A. Performance evaluation of deep CNN-based crack detection and localization techniques for concrete structures Sensors 2021 21 1688 10.3390/s21051688 33804490 33. Chen J. Yang T. Zhang D. Huang H. Tian Y. Deep learning based classification of rock structure of tunnel face Geosci. Front. 2021 12 395 404 10.1016/j.gsf.2020.04.003 34. Harvey W. Rainwater C. Cothren J. Direct aerial visual geolocalization using deep neural networks Remote Sens. 2021 13 4017 10.3390/rs13194017 35. Nath N.D. Behzadan A.H. Paal S.G. Deep learning for site safety: Real-time detection of personal protective equipment Autom. Constr. 2020 112 103085 10.1016/j.autcon.2020.103085 36. Narazaki Y. Hoskere V. Hoang T.A. Fujino Y. Sakurai A. Spencer B.F. Vision-based automated bridge component recognition with high-level scene consistency Comput. Aided Civ. Infrastruct. Eng. 2020 35 465 482 10.1111/mice.12505 37. Bang S. Park S. Kim H. Kim H. Encoder–decoder network for pixel-level road crack detection in black-box images Comput. Aided Civ. Infrastruct. Eng. 2019 34 713 727 10.1111/mice.12440 38. Maeda H. Sekimoto Y. Seto T. Kashiyama T. Omata H. Road damage detection and classification using deep neural networks with smartphone images Comput. Aided Civ. Infrastruct. Eng. 2018 33 1127 1141 10.1111/mice.12387 39. Cheng C.S. Behzadan A.H. Noshadravan A. Deep learning for post-hurricane aerial damage assessment of buildings Comput. Aided Civ. Infrastruct. Eng. 2021 36 695 710 10.1111/mice.12658 40. Selvaraju R.R. Cogswell M. Das A. Vedantam R. Parikh D. Batra D. Grad-CAM: Visual explanations from deep networks via gradient-based localization Int. J. Comput. Vis. 2020 128 336 359 10.1007/s11263-019-01228-7 41. Russell B.C. Torralba A. Murphy K.P. Freeman W.T. LabelMe: A database and web-based tool for image annotation Int. J. Comput. Vis. 2008 77 157 173 10.1007/s11263-007-0090-8 42. Nia K.R. Mori G. Building Damage Assessment Using Deep Learning and Ground-Level Image Data Proceedings of the 14th Conference on Computer and Robot Vision (CRV) Edmonton, AB, Canada 16–19 May 2017 IEEE Publications Piscataway, NJ, USA 2017 Volume 2017 95 102 10.1109/CRV.2017.54 43. TensorFlow. Js Available online: https://www.tensorflow.org/js (accessed on 22 February 2022)